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Sample records for hybrid jigsaw approach

  1. Cooperative learning in 'Special Needs in Dentistry' for undergraduate students using the Jigsaw approach.

    Science.gov (United States)

    Suárez-Cunqueiro, M M; Gándara-Lorenzo, D; Mariño-Pérez, R; Piñeiro-Abalo, S; Pérez-López, D; Tomás, I

    2017-11-01

    The goals of this study were to (i) describe the use of the Jigsaw approach for the resolution of clinical cases by undergraduate students in the subject 'Special Needs in Dentistry' and (ii) assess the impact of its implementation on academic performance and the students' perception. The Jigsaw approach was applied to the fifth-year in the subject 'Special Needs in Dentistry', as part of the Dentistry degree curriculum of the University of Santiago de Compostela, during the academic years 2012/2013 and 2013/2014. A total of 109 dental students were enrolled in the study, and the final marks of the Jigsaw (n = 55) and the non-Jigsaw groups (n = 54) were compared. Students' perceptions on the Jigsaw technique were assessed using a 13-question questionnaire. Academic performance based on the final examination mark for the Jigsaw and non-Jigsaw groups was 6.45 ± 1.49 and 6.13 ± 1.50, respectively. There were not students in the Jigsaw group who failed to attend the mandatory examination (0% vs. 12.96% in the non-Jigsaw group, P = 0.006). The questionnaire's internal consistency was 0.90. The mean value for all the questionnaire items was 3.80, with the highest response score of 4.35 for the statement 'I have seen the complexity that the resolution of a clinical case can involve'. Based on the students' perceptions, the Jigsaw approach could contribute to a better understanding of the complexity of solving clinical cases in the subject 'Special Needs in Dentistry'. However, further investigations should be conducted to analyse the influence of this technique on students' academic performance in the field of clinical dentistry. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  2. Freestyle multiple propeller flap reconstruction (jigsaw puzzle approach) for complicated back defects.

    Science.gov (United States)

    Park, Sung Woo; Oh, Tae Suk; Eom, Jin Sup; Sun, Yoon Chi; Suh, Hyun Suk; Hong, Joon Pio

    2015-05-01

    The reconstruction of the posterior trunk remains to be a challenge as defects can be extensive, with deep dead space, and fixation devices exposed. Our goal was to achieve a tension-free closure for complex defects on the posterior trunk. From August 2006 to May 2013, 18 cases were reconstructed with multiple flaps combining perforator(s) and local skin flaps. The reconstructions were performed using freestyle approach. Starting with propeller flap(s) in single or multilobed design and sequentially in conjunction with adjacent random pattern flaps such as fitting puzzle. All defects achieved tensionless primary closure. The final appearance resembled a jigsaw puzzle-like appearance. The average size of defect was 139.6 cm(2) (range, 36-345 cm(2)). A total of 26 perforator flaps were used in addition to 19 random pattern flaps for 18 cases. In all cases, a single perforator was used for each propeller flap. The defect and the donor site all achieved tension-free closure. The reconstruction was 100% successful without flap loss. One case of late infection was noted at 12 months after surgery. Using multiple lobe designed propeller flaps in conjunction with random pattern flaps in a freestyle approach, resembling putting a jigsaw puzzle together, we can achieve a tension-free closure by distributing the tension to multiple flaps, supplying sufficient volume to obliterate dead space, and have reliable vascularity as the flaps do not need to be oversized. This can be a viable approach to reconstruct extensive defects on the posterior trunk. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  3. EFEKTIVITAS MODEL JIGSAW DISERTAI PENILAIAN DISKUSI UNTUK MENINGKATKAN KEMAMPUAN MATEMATIS MAHASISWA

    Directory of Open Access Journals (Sweden)

    Sofia Edriati

    2015-06-01

    Full Text Available Abstrak: Penelitian ini bertujuan untuk mengetahui perbedaan peningkatan kemampuan matematis mahasiswa yang menggunakan model jigsaw disertai penilaian diskusi dengan tanpa penilaian diskusi dan perkuliahan konvensional. Penelitian ini menggunakan metode true eksperiment dengan randomized control-group pretest-posttest design. Populasi penelitian adalah mahasiswa yang mengambil mata kuliah Aljabar Linier Elementer. Sampel sebanyak tiga kelas dipilih secara cluster random sampling. Data yang diperoleh dengan teknik tes (awal dan akhir, sedang analisis data dilakukan dengan menggunakan skor gain rata-rata. Sebelum data dianalisis terlebih dahulu dilakukan uji persyaratan, yaitu berupa uji normalitas, homogenitas, dan kesamaan kompeetnsi awal. Hasil penelitian menunjukkan bahwa terdapat perbedaan peningkatan kemampuan matematis mahasiswa yang menggunakan model jigsaw disertai penilaian diskusi dengan tanpa penilaian diskusi dan perkuliahan konvensional. Kata Kunci: penilaian diskusi, model jigsaw, kemampuan matematis THE EFFECTIVENESS OF JIGSAW MODELS WITH ASSESSMENT OF DISCUSSION TO IMPROVE MATHEMATICAL ABILITY OF STUDENT Abstract: This research aims to determine of differences in improvement of student mathematical ability who use the jigsaw model accompanied with discussion assessment to without discussion assessment and conventional learning. The research method used true approach experiment with randomized control-group pretest-posttest design. The study population were students who take courses Elementary Linear Algebra. The data obtained were analyzed by using gain score. The results showed that there are differences in improvement of student mathematical ability who use the jigsaw model with discussion assessment to without discussion assessment and conventional learning. Keywords: discussion assessment, jigsaw model, mathemathical ability

  4. Teaching Chemical Equilibrium with the Jigsaw Technique

    Science.gov (United States)

    Doymus, Kemal

    2008-03-01

    This study investigates the effect of cooperative learning (jigsaw) versus individual learning methods on students’ understanding of chemical equilibrium in a first-year general chemistry course. This study was carried out in two different classes in the department of primary science education during the 2005-2006 academic year. One of the classes was randomly assigned as the non-jigsaw group (control) and other as the jigsaw group (cooperative). Students participating in the jigsaw group were divided into four “home groups” since the topic chemical equilibrium is divided into four subtopics (Modules A, B, C and D). Each of these home groups contained four students. The groups were as follows: (1) Home Group A (HGA), representin g the equilibrium state and quantitative aspects of equilibrium (Module A), (2) Home Group B (HGB), representing the equilibrium constant and relationships involving equilibrium constants (Module B), (3) Home Group C (HGC), representing Altering Equilibrium Conditions: Le Chatelier’s principle (Module C), and (4) Home Group D (HGD), representing calculations with equilibrium constants (Module D). The home groups then broke apart, like pieces of a jigsaw puzzle, and the students moved into jigsaw groups consisting of members from the other home groups who were assigned the same portion of the material. The jigsaw groups were then in charge of teaching their specific subtopic to the rest of the students in their learning group. The main data collection tool was a Chemical Equilibrium Achievement Test (CEAT), which was applied to both the jigsaw and non-jigsaw groups The results indicated that the jigsaw group was more successful than the non-jigsaw group (individual learning method).

  5. Jigsaw Cooperative Learning: Acid-Base Theories

    Science.gov (United States)

    Tarhan, Leman; Sesen, Burcin Acar

    2012-01-01

    This study focused on investigating the effectiveness of jigsaw cooperative learning instruction on first-year undergraduates' understanding of acid-base theories. Undergraduates' opinions about jigsaw cooperative learning instruction were also investigated. The participants of this study were 38 first-year undergraduates in chemistry education…

  6. PENERAPAN JIGSAW PUZZLE COMPETITION DALAM PEMBELAJARAN KONTEKSTUAL UNTUK MENINGKATKAN MINAT DAN HASIL BELAJAR FISIKA SISWA SMP

    Directory of Open Access Journals (Sweden)

    D. Yulianti

    2012-01-01

    Full Text Available Untuk mengatasi kurangnya minat dan hasil belajar fisika siswa dilakukan penelitian melalui kegiatan pembelajaran fisikakontekstual berbantuan jigsaw puzzle competititon. Subjek penelitian ini adalah siswa kelas VII H SMP Negeri 18 Semarang.Penelitian ini telah dilakukan pembelajaran dengan pendekatan kontekstual berbantuan jigsaw puzzle competition. Hasilpenelitian menunjukkan bahwa pembelajaran kontekstual berbantuan jigsaw puzzle competition mampu meningkatan minat danhasil belajar siswa kelas VII H SMPNegeri 18 Semarang tahun pelajaran 2008/2009 secara signifikan. Agar lebih efektif sebaiknyadikembangkan pembelajaran kontekstual dengan metode lain agar diperoleh peningkatan minat dan hasil belajar Model ini perludiaplikasikan dalam pembelajaran fisika untuk materi yang lain. To overcome the problem of lack of students' interest as well as their achievements a Jigsaw Puzzle Competition in physicscontextual learning process was done. The students from VIIHclass of Junior High School 18 Semarang academic year 2008/2009were chosen as the subjects. The result of this research shows that contextual teaching and learning using Jigsaw PuzzleCompetition approach was not only increase the students' interest but also improve their achievements. In order to get moreeffective result, it is necessary to develop contextual teaching and learning by combining them with other method. Because of thegreat benefit of this model, it is necessary to apply this model to other physics learning concepts.Keywords: Jigsaw Puzzle Competition, contextual, interest;

  7. Evaporator modeling - A hybrid approach

    International Nuclear Information System (INIS)

    Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun

    2009-01-01

    In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis

  8. A Hybrid Approach to Teaching Managerial Economics

    Science.gov (United States)

    Metzgar, Matthew

    2014-01-01

    Many institutions in higher education are experimenting with hybrid teaching approaches to undergraduate courses. Online resources may provide a number of advantages to students as compared to in-class approaches. Research regarding the effectiveness of hybrid approaches is mixed and still accumulating. This paper discusses the use of a hybrid…

  9. A Jigsaw Lesson for Operations of Complex Numbers.

    Science.gov (United States)

    Lucas, Carol A.

    2000-01-01

    Explains the cooperative learning technique of jigsaw. Details the use of a jigsaw lesson for explaining complex numbers to intermediate algebra students. Includes copies of the handouts given to the expert groups. (Author/ASK)

  10. Hybrid soft computing approaches research and applications

    CERN Document Server

    Dutta, Paramartha; Chakraborty, Susanta

    2016-01-01

    The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

  11. A Hybrid Approach to Protect Palmprint Templates

    Directory of Open Access Journals (Sweden)

    Hailun Liu

    2014-01-01

    Full Text Available Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach.

  12. Using Jigsaw-Style Spectroscopy Problem-Solving to Elucidate Molecular Structure through Online Cooperative Learning

    Science.gov (United States)

    Winschel, Grace A.; Everett, Renata K.; Coppola, Brian P.; Shultz, Ginger V.

    2015-01-01

    Cooperative learning was employed as an instructional approach to facilitate student development of spectroscopy problem solving skills. An interactive online environment was used as a framework to structure weekly discussions around spectroscopy problems outside of class. Weekly discussions consisted of modified jigsaw-style problem solving…

  13. Dramatherapy and Family Therapy in Education: Essential Pieces of the Multi-Agency Jigsaw

    Science.gov (United States)

    McFarlane, Penny; Harvey, Jenny

    2012-01-01

    A collaborative therapeutic approach often proves the best way to assess and meet the needs of children experiencing barriers to learning. This book gives a concise overview of drama and family therapy and describes how both therapies can work together to provide essential pieces of the jigsaw of emotional support for troubled children within an…

  14. Solving jigsaw puzzles using image features

    DEFF Research Database (Denmark)

    Nielsen, Ture R.; Drewsen, Peter; Hansen, Klaus

    2008-01-01

    In this article, we describe a method for automatic solving of the jigsaw puzzle problem based on using image features instead of the shape of the pieces. The image features are used for obtaining an accurate measure for edge similarity to be used in a new edge matching algorithm. The algorithm i...

  15. Teaching Chemical Equilibrium with the Jigsaw Technique

    Science.gov (United States)

    Doymus, Kemal

    2008-01-01

    This study investigates the effect of cooperative learning (jigsaw) versus individual learning methods on students' understanding of chemical equilibrium in a first-year general chemistry course. This study was carried out in two different classes in the department of primary science education during the 2005-2006 academic year. One of the classes…

  16. Detection of cardiovascular anomalies: Hybrid systems approach

    KAUST Repository

    Ledezma, Fernando

    2012-06-06

    In this paper, we propose a hybrid interpretation of the cardiovascular system. Based on a model proposed by Simaan et al. (2009), we study the problem of detecting cardiovascular anomalies that can be caused by variations in some physiological parameters, using an observerbased approach. We present the first numerical results obtained. © 2012 IFAC.

  17. A HYBRID APPROACH FOR RURAL FEEDER DESIGN

    Directory of Open Access Journals (Sweden)

    DAMANJEET KAUR

    2012-08-01

    Full Text Available In this paper, a population based approach for conductor size selection in rural radial distribution system is presented. The proposed hybrid approach implies a particle swarm optimization (PSO approach in combination with mutant property of differential evolution (DE for conductor size selection in radial distribution system. The conductor size for each feeder segment is selected such that the total cost of capital investment and capitalized cost of energy losses is minimized while constraints of voltage at each node and current carrying capacity of conductor is within the limits. The applicability and effectiveness of the proposed method is demonstrated with the help of 32-node test system.

  18. A hybrid approach for biobjective optimization

    DEFF Research Database (Denmark)

    Stidsen, Thomas Jacob Riis; Andersen, Kim Allan

    2018-01-01

    to singleobjective problems is that no standard multiobjective solvers exist and specialized algorithms need to be programmed from scratch.In this article we will present a hybrid approach, which operates both in decision space and in objective space. The approach enables massive efficient parallelization and can...... be used to a wide variety of biobjective Mixed Integer Programming models. We test the approach on the biobjective extension of the classic traveling salesman problem, on the standard datasets, and determine the full set of nondominated points. This has only been done once before (Florios and Mavrotas...

  19. Hybrid biasing approaches for global variance reduction

    International Nuclear Information System (INIS)

    Wu, Zeyun; Abdel-Khalik, Hany S.

    2013-01-01

    A new variant of Monte Carlo—deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses. - Highlights: ► Hybrid Monte Carlo Deterministic Method based on Gaussian Process Model is introduced. ► Method employs deterministic model to calculate responses correlations. ► Method employs correlations to bias Monte Carlo transport. ► Method compared to FW-CADIS methodology in SCALE code. ► An order of magnitude speed up is achieved for a PWR core model.

  20. Jigsaw Puzzles As Cognitive Enrichment (PACE) - the effect of solving jigsaw puzzles on global visuospatial cognition in adults 50 years of age and older: study protocol for a randomized controlled trial.

    Science.gov (United States)

    Fissler, Patrick; Küster, Olivia C; Loy, Laura S; Laptinskaya, Daria; Rosenfelder, Martin J; von Arnim, Christine A F; Kolassa, Iris-Tatjana

    2017-09-06

    Neurocognitive disorders are an important societal challenge and the need for early prevention is increasingly recognized. Meta-analyses show beneficial effects of cognitive activities on cognition. However, high financial costs, low intrinsic motivation, logistic challenges of group-based activities, or the need to operate digital devices prevent their widespread application in clinical practice. Solving jigsaw puzzles is a cognitive activity without these hindering characteristics, but cognitive effects have not been investigated yet. With this study, we aim to evaluate the effect of solving jigsaw puzzles on visuospatial cognition, daily functioning, and psychological outcomes. The pre-posttest, assessor-blinded study will include 100 cognitively healthy adults 50 years of age or older, who will be randomly assigned to a jigsaw puzzle group or a cognitive health counseling group. Within the 5-week intervention period, participants in the jigsaw puzzle group will engage in 30 days of solving jigsaw puzzles for at least 1 h per day and additionally receive cognitive health counseling. The cognitive health counseling group will receive the same counseling intervention but no jigsaw puzzles. The primary outcome, global visuospatial cognition, will depict the average of the z-standardized performance scores in visuospatial tests of perception, constructional praxis, mental rotation, processing speed, flexibility, working memory, reasoning, and episodic memory. As secondary outcomes, we will assess the eight cognitive abilities, objective and subjective visuospatial daily functioning, psychological well-being, general self-efficacy, and perceived stress. The primary data analysis will be based on mixed-effects models in an intention-to-treat approach. Solving jigsaw puzzles is a low-cost, intrinsically motivating, cognitive leisure activity, which can be executed alone or with others and without the need to operate a digital device. In the case of positive results

  1. A Hybrid Approach on Tourism Demand Forecasting

    Science.gov (United States)

    Nor, M. E.; Nurul, A. I. M.; Rusiman, M. S.

    2018-04-01

    Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is challenging to produce an accurate forecast since economic data such as the tourism data is affected by social, economic and environmental factors. In this study, an equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was assessed by taking the each individual method as a benchmark. The results showed that this hybrid approach outperformed the other two models

  2. Jigsaw model of the origin of life

    Science.gov (United States)

    McGowan, John F.

    2002-02-01

    It is suggested that life originated in a three-step process referred to as the jigsaw model. RNA, proteins, or similar organic molecules polymerized in a dehydrated carbon-rich environment, on surfaces in a carbon-rich environment, or in another environment where polymerization occurs. These polymers subsequently entered an aqueous environment where they folded into compact structures. It is argued that the folding of randomly generated polymers such as RNA or proteins in water tends to partition the folded polymer into domains with hydrophobic cores and matching shapes to minimize energy. In the aqueous environment hydrolysis or other reactions fragmented the compact structures into two or more matching molecules, occasionally producing simple living systems, also knows as autocatalytic sets of molecules. It is argued that the hydrolysis of folded polymers such as RNA or proteins is not random. The hydrophobic cores of the domains are rarely bisected due to the energy requirements in water. Hydrolysis preferentially fragments the folded polymers into pieces with complementary structures and chemical affinities. Thus the probability of producing a system of matched, interacting molecules in prebiotic chemistry is much higher than usually estimated. Environments where this process may occur are identified. For example, the jigsaw model suggests life may have originated at a seep or carbonaceous fluids beneath the ocean. The polymerization occurred beneath the sea floor. The folding and fragmentation occurred in the ocean. The implications of this hypothesis for seeking life or prebiotic chemistry in the Solar System are explored.

  3. A hybrid approach for global sensitivity analysis

    International Nuclear Information System (INIS)

    Chakraborty, Souvik; Chowdhury, Rajib

    2017-01-01

    Distribution based sensitivity analysis (DSA) computes sensitivity of the input random variables with respect to the change in distribution of output response. Although DSA is widely appreciated as the best tool for sensitivity analysis, the computational issue associated with this method prohibits its use for complex structures involving costly finite element analysis. For addressing this issue, this paper presents a method that couples polynomial correlated function expansion (PCFE) with DSA. PCFE is a fully equivalent operational model which integrates the concepts of analysis of variance decomposition, extended bases and homotopy algorithm. By integrating PCFE into DSA, it is possible to considerably alleviate the computational burden. Three examples are presented to demonstrate the performance of the proposed approach for sensitivity analysis. For all the problems, proposed approach yields excellent results with significantly reduced computational effort. The results obtained, to some extent, indicate that proposed approach can be utilized for sensitivity analysis of large scale structures. - Highlights: • A hybrid approach for global sensitivity analysis is proposed. • Proposed approach integrates PCFE within distribution based sensitivity analysis. • Proposed approach is highly efficient.

  4. Stock selection using a hybrid MCDM approach

    Directory of Open Access Journals (Sweden)

    Tea Poklepović

    2014-12-01

    Full Text Available The problem of selecting the right stocks to invest in is of immense interest for investors on both emerging and developed capital markets. Moreover, an investor should take into account all available data regarding stocks on the particular market. This includes fundamental and stock market indicators. The decision making process includes several stocks to invest in and more than one criterion. Therefore, the task of selecting the stocks to invest in can be viewed as a multiple criteria decision making (MCDM problem. Using several MCDM methods often leads to divergent rankings. The goal of this paper is to resolve these possible divergent results obtained from different MCDM methods using a hybrid MCDM approach based on Spearman’s rank correlation coefficient. Five MCDM methods are selected: COPRAS, linear assignment, PROMETHEE, SAW and TOPSIS. The weights for all criteria are obtained by using the AHP method. Data for this study includes information on stock returns and traded volumes from March 2012 to March 2014 for 19 stocks on the Croatian capital market. It also includes the most important fundamental and stock market indicators for selected stocks. Rankings using five selected MCDM methods in the stock selection problem yield divergent results. However, after applying the proposed approach the final hybrid rankings are obtained. The results show that the worse stocks to invest in happen to be the same when the industry is taken into consideration or when not. However, when the industry is taken into account, the best stocks to invest in are slightly different, because some industries are more profitable than the others.

  5. Multilayer Approach for Advanced Hybrid Lithium Battery

    KAUST Repository

    Ming, Jun

    2016-06-06

    Conventional intercalated rechargeable batteries have shown their capacity limit, and the development of an alternative battery system with higher capacity is strongly needed for sustainable electrical vehicles and hand-held devices. Herein, we introduce a feasible and scalable multilayer approach to fabricate a promising hybrid lithium battery with superior capacity and multivoltage plateaus. A sulfur-rich electrode (90 wt % S) is covered by a dual layer of graphite/Li4Ti5O12, where the active materials S and Li4Ti5O12 can both take part in redox reactions and thus deliver a high capacity of 572 mAh gcathode -1 (vs the total mass of electrode) or 1866 mAh gs -1 (vs the mass of sulfur) at 0.1C (with the definition of 1C = 1675 mA gs -1). The battery shows unique voltage platforms at 2.35 and 2.1 V, contributed from S, and 1.55 V from Li4Ti5O12. A high rate capability of 566 mAh gcathode -1 at 0.25C and 376 mAh gcathode -1 at 1C with durable cycle ability over 100 cycles can be achieved. Operando Raman and electron microscope analysis confirm that the graphite/Li4Ti5O12 layer slows the dissolution/migration of polysulfides, thereby giving rise to a higher sulfur utilization and a slower capacity decay. This advanced hybrid battery with a multilayer concept for marrying different voltage plateaus from various electrode materials opens a way of providing tunable capacity and multiple voltage platforms for energy device applications. © 2016 American Chemical Society.

  6. A hybrid modeling approach for option pricing

    Science.gov (United States)

    Hajizadeh, Ehsan; Seifi, Abbas

    2011-11-01

    The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.

  7. Detection of cardiovascular anomalies: Hybrid systems approach

    KAUST Repository

    Ledezma, Fernando; Laleg-Kirati, Taous-Meriem

    2012-01-01

    In this paper, we propose a hybrid interpretation of the cardiovascular system. Based on a model proposed by Simaan et al. (2009), we study the problem of detecting cardiovascular anomalies that can be caused by variations in some physiological

  8. Cutting force measurement of electrical jigsaw by strain gauges

    International Nuclear Information System (INIS)

    Kazup, L; Varadine Szarka, A

    2016-01-01

    This paper describes a measuring method based on strain gauges for accurate specification of electric jigsaw's cutting force. The goal of the measurement is to provide an overall perspective about generated forces in a jigsaw's gearbox during a cutting period. The lifetime of the tool is affected by these forces primarily. This analysis is part of the research and development project aiming to develop a special linear magnetic brake for realizing automatic lifetime tests of electric jigsaws or similar handheld tools. The accurate specification of cutting force facilitates to define realistic test cycles during the automatic lifetime test. The accuracy and precision resulted by the well described cutting force characteristic and the possibility of automation provide new dimension for lifetime testing of the handheld tools with alternating movement. (paper)

  9. Application of adobe flash media to optimize jigsaw learning model on geometry material

    Science.gov (United States)

    Imam, P.; Imam, S.; Ikrar, P.

    2018-05-01

    This study aims to determine and describe the effectiveness of the application of adobe flash media for jigsaw learning model on geometry material. In this study, the modified jigsaw learning with adobe flash media is called jigsaw-flash model. This research was conducted in Surakarta. The research method used is mix method research with exploratory sequential strategy. The results of this study indicate that students feel more comfortable and interested in studying geometry material taught by jigsaw-flash model. In addition, students taught using the jigsaw-flash model are more active and motivated than the students who were taught using ordinary jigsaw models. This shows that the use of the jigsaw-flash model can increase student participation and motivation. It can be concluded that the adobe flash media can be used as a solution to reduce the level of student abstraction in learning mathematics.

  10. A "Hybrid" Approach for Synthesizing Optimal Controllers of Hybrid Systems

    DEFF Research Database (Denmark)

    Zhao, Hengjun; Zhan, Naijun; Kapur, Deepak

    2012-01-01

    to discretization manageable and within bounds. A major advantage of our approach is not only that it avoids errors due to numerical computation, but it also gives a better optimal controller. In order to illustrate our approach, we use the real industrial example of an oil pump provided by the German company HYDAC...

  11. Hybrid perovskites: Approaches towards light-emitting devices

    KAUST Repository

    Alias, Mohd Sharizal

    2016-10-06

    The high optical gain and absorption of organic-inorganic hybrid perovskites have attracted extensive research for photonic device applications. Using the bromide halide as an example, we present key approaches of our work towards realizing efficient perovskites based light-emitters. The approaches involved determination of optical constants for the hybrid perovskites thin films, fabrication of photonic nanostructures in the form of subwavelength grating reflector patterned directly on the hybrid perovskites as light manipulation layer, and enhancing the emission property of the hybrid perovskites by using microcavity structure. Our results provide a platform for realization of hybrid perovskites based light-emitting devices for solid-state lighting and display applications. © 2016 IEEE.

  12. Hybrid perovskites: Approaches towards light-emitting devices

    KAUST Repository

    Alias, Mohd Sharizal; Dursun, Ibrahim; Priante, Davide; Saidaminov, Makhsud I.; Ng, Tien Khee; Bakr, Osman; Ooi, Boon S.

    2016-01-01

    The high optical gain and absorption of organic-inorganic hybrid perovskites have attracted extensive research for photonic device applications. Using the bromide halide as an example, we present key approaches of our work towards realizing efficient perovskites based light-emitters. The approaches involved determination of optical constants for the hybrid perovskites thin films, fabrication of photonic nanostructures in the form of subwavelength grating reflector patterned directly on the hybrid perovskites as light manipulation layer, and enhancing the emission property of the hybrid perovskites by using microcavity structure. Our results provide a platform for realization of hybrid perovskites based light-emitting devices for solid-state lighting and display applications. © 2016 IEEE.

  13. Scalar field dark matter in hybrid approach

    NARCIS (Netherlands)

    Friedrich, Pavel; Prokopec, Tomislav

    2017-01-01

    We develop a hybrid formalism suitable for modeling scalar field dark matter, in which the phase-space distribution associated to the real scalar field is modeled by statistical equal-time two-point functions and gravity is treated by two stochastic gravitational fields in the longitudinal gauge (in

  14. Effects of Jigsaw Learning Method on Students’ Self-Efficacy and Motivation to Learn

    OpenAIRE

    Dwi Nur Rachmah

    2017-01-01

    Jigsaw learning as a cooperative learning method, according to the results of some studies, can improve academic skills, social competence, behavior in learning, and motivation to learn. However, in some other studies, there are different findings regarding the effect of jigsaw learning method on self-efficacy. The purpose of this study is to examine the effects of jigsaw learning method on self-efficacy and motivation to learn in psychology students at the Faculty of Medicine, Universitas La...

  15. Infectious disease modeling a hybrid system approach

    CERN Document Server

    Liu, Xinzhi

    2017-01-01

    This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.

  16. A Hybrid Approach to the Optimization of Multiechelon Systems

    Directory of Open Access Journals (Sweden)

    Paweł Sitek

    2015-01-01

    Full Text Available In freight transportation there are two main distribution strategies: direct shipping and multiechelon distribution. In the direct shipping, vehicles, starting from a depot, bring their freight directly to the destination, while in the multiechelon systems, freight is delivered from the depot to the customers through an intermediate points. Multiechelon systems are particularly useful for logistic issues in a competitive environment. The paper presents a concept and application of a hybrid approach to modeling and optimization of the Multi-Echelon Capacitated Vehicle Routing Problem. Two ways of mathematical programming (MP and constraint logic programming (CLP are integrated in one environment. The strengths of MP and CLP in which constraints are treated in a different way and different methods are implemented and combined to use the strengths of both. The proposed approach is particularly important for the discrete decision models with an objective function and many discrete decision variables added up in multiple constraints. An implementation of hybrid approach in the ECLiPSe system using Eplex library is presented. The Two-Echelon Capacitated Vehicle Routing Problem (2E-CVRP and its variants are shown as an illustrative example of the hybrid approach. The presented hybrid approach will be compared with classical mathematical programming on the same benchmark data sets.

  17. Using hybrid expert system approaches for engineering applications

    Science.gov (United States)

    Allen, R. H.; Boarnet, M. G.; Culbert, C. J.; Savely, R. T.

    1987-01-01

    In this paper, the use of hybrid expert system shells and hybrid (i.e., algorithmic and heuristic) approaches for solving engineering problems is reported. Aspects of various engineering problem domains are reviewed for a number of examples with specific applications made to recently developed prototype expert systems. Based on this prototyping experience, critical evaluations of and comparisons between commercially available tools, and some research tools, in the United States and Australia, and their underlying problem-solving paradigms are made. Characteristics of the implementation tool and the engineering domain are compared and practical software engineering issues are discussed with respect to hybrid tools and approaches. Finally, guidelines are offered with the hope that expert system development will be less time consuming, more effective, and more cost-effective than it has been in the past.

  18. A novel Monte Carlo approach to hybrid local volatility models

    NARCIS (Netherlands)

    A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

    2017-01-01

    textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

  19. A hybrid approach to designing inbound-resupply strategies

    NARCIS (Netherlands)

    Dullaert, Wout; Vernimmen, Bert; Raa, Birger; Witlox, Frank

    A new hybrid approach was developed to determine the optimal inbound-resupply strategy when suppliers ship goods to receivers. The optimal reorder level was calculated on the basis of a simulation of the distribution of demand and the lead time of the various sourcing alternatives. An evolutionary

  20. A hybrid generative-discriminative approach to speaker diarization

    NARCIS (Netherlands)

    Noulas, A.K.; van Kasteren, T.; Kröse, B.J.A.

    2008-01-01

    In this paper we present a sound probabilistic approach to speaker diarization. We use a hybrid framework where a distribution over the number of speakers at each point of a multimodal stream is estimated with a discriminative model. The output of this process is used as input in a generative model

  1. A hybrid agent-based approach for modeling microbiological systems.

    Science.gov (United States)

    Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

    2008-11-21

    Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

  2. Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2014-01-01

    Full Text Available Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone’s health. Although there are several ways to measure the body fat percentage (BFP, the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR, artificial neural network (ANN, multivariate adaptive regression splines (MARS, and support vector regression (SVR techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models.

  3. Solving University Scheduling Problem Using Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Aftab Ahmed Shaikh

    2011-10-01

    Full Text Available In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.

  4. Flip-J: Development of the System for Flipped Jigsaw Supported Language Learning

    Science.gov (United States)

    Yamada, Masanori; Goda, Yoshiko; Hata, Kojiro; Matsukawa, Hideya; Yasunami, Seisuke

    2016-01-01

    This study aims to develop and evaluate a language learning system supported by the "flipped jigsaw" technique, called "Flip-J". This system mainly consists of three functions: (1) the creation of a learning material database, (2) allocation of learning materials, and (3) formation of an expert and jigsaw group. Flip-J was…

  5. Thai Undergraduate Chemistry Practical Learning Experiences Using the Jigsaw IV Method

    Science.gov (United States)

    Jansoon, Ninna; Somsook, Ekasith; Coll, Richard K.

    2008-01-01

    The research reported in this study consisted of an investigation of student learning experiences in Thai chemistry laboratories using the Jigsaw IV method. A hands-on experiment based on the Jigsaw IV method using a real life example based on green tea beverage was designed to improve student affective variables for studying topics related to…

  6. Explorers, Detectives, Matchmakers, and Lion Tamers: Understanding Jigsaw Puzzlers' Techniques and Motivations

    Science.gov (United States)

    Garcia, Angela Cora

    2013-01-01

    Why do people enjoy jigsaw puzzles, which--challenging and time-consuming as they are--might be considered more like work than play? The author investigates the motivations, preferences, and satisfactions of individuals working on jigsaw puzzles, and she explores how these elements of play relate to the procedures and strategies puzzlers use to…

  7. Effects of Computer-Assisted Jigsaw II Cooperative Learning Strategy on Physics Achievement and Retention

    Science.gov (United States)

    Gambari, Isiaka Amosa; Yusuf, Mudasiru Olalere

    2016-01-01

    This study investigated the effects of computer-assisted Jigsaw II cooperative strategy on physics achievement and retention. The study also determined how moderating variables of achievement levels as it affects students' performance in physics when Jigsaw II cooperative learning is used as an instructional strategy. Purposive sampling technique…

  8. Revealing the Relationship between Reading Interest and Critical Thinking Skills through Remap GI and Remap Jigsaw

    Science.gov (United States)

    Zubaidah, Siti; Corebima, Aloysius Duran; Mahanal, Susriyati; Mistianah

    2018-01-01

    The aim of this research was to reveal the relationship between student's reading interest and critical thinking skills through Reading Concept Map Group Investigation (Remap GI) and Reading Concept Map Jigsaw (Remap Jigsaw) learning models. To do so, two science classes from first grade of two Senior High Schools in Malang, Indonesia were…

  9. Promoting Interculturality in Spain: Assessing the Use of the Jigsaw Classroom Method

    Science.gov (United States)

    Santos Rego, Miguel A.; Moledo, M. Del Mar Lorenzo

    2005-01-01

    This note examines the effectiveness of a program in Spain that uses the Jigsaw learning technique as an educational intervention. We used a quasi-experimental research design with two groups, two measures and an independent variable (the program). Use of the Jigsaw technique is shown to have been fairly effective on a series of measures.

  10. Jigsaw Variations and Attitudes about Learning and the Self in Cognitive Psychology

    Science.gov (United States)

    Crone, Travis S.; Portillo, Mary C.

    2013-01-01

    Jigsaw classroom research has primarily explored racial relationships at the primary and secondary educational levels. The present study explored whether the jigsaw classroom would have an effect on students' attitudes about their own academic abilities and practices at the university level. The present study also sought to illuminate the…

  11. Hybrid methodological approach to context-dependent speech recognition

    Directory of Open Access Journals (Sweden)

    Dragiša Mišković

    2017-01-01

    Full Text Available Although the importance of contextual information in speech recognition has been acknowledged for a long time now, it has remained clearly underutilized even in state-of-the-art speech recognition systems. This article introduces a novel, methodologically hybrid approach to the research question of context-dependent speech recognition in human–machine interaction. To the extent that it is hybrid, the approach integrates aspects of both statistical and representational paradigms. We extend the standard statistical pattern-matching approach with a cognitively inspired and analytically tractable model with explanatory power. This methodological extension allows for accounting for contextual information which is otherwise unavailable in speech recognition systems, and using it to improve post-processing of recognition hypotheses. The article introduces an algorithm for evaluation of recognition hypotheses, illustrates it for concrete interaction domains, and discusses its implementation within two prototype conversational agents.

  12. Impact of a Modified Jigsaw Method for Learning an Unfamiliar, Complex Topic

    Directory of Open Access Journals (Sweden)

    Denise Kolanczyk

    2017-09-01

    Full Text Available Objective: The aim of this study was to use the jigsaw method with an unfamiliar, complex topic and to evaluate the effectiveness of the jigsaw teaching method on student learning of assigned material (“jigsaw expert” versus non-assigned material (“jigsaw learner”. Innovation: The innovation was implemented in an advanced cardiology elective. Forty students were assigned a pre-reading and one of four valvular heart disorders, a topic not previously taught in the curriculum. A pre-test and post-test evaluated overall student learning. Student performance on pre/post tests as the “jigsaw expert” and “jigsaw learner” was also compared. Critical Analysis: Overall, the post-test mean score of 85.75% was significantly higher than that of the pre-test score of 56.75% (p<0.05. There was significant improvement in scores regardless of whether the material was assigned (“jigsaw experts” pre=58.8% and post=82.5%; p<0.05 or not assigned (“jigsaw learners” pre= 56.25% and post= 86.56%, p<0.05 for pre-study. Next Steps: The use of the jigsaw method to teach unfamiliar, complex content helps students to become both teachers and active listeners, which are essential to the skills and professionalism of a health care provider. Further studies are needed to evaluate use of the jigsaw method to teach unfamiliar, complex content on long-term retention and to further examine the effects of expert vs. non-expert roles. Conflict of Interest We declare no conflicts of interest or financial interests that the authors or members of their immediate families have in any product or service discussed in the manuscript, including grants (pending or received, employment, gifts, stock holdings or options, honoraria, consultancies, expert testimony, patents and royalties.   Type: Note

  13. Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

    Directory of Open Access Journals (Sweden)

    Jui-Yu Wu

    2013-01-01

    Full Text Available Stochastic global optimization (SGO algorithms such as the particle swarm optimization (PSO approach have become popular for solving unconstrained global optimization (UGO problems. The PSO approach, which belongs to the swarm intelligence domain, does not require gradient information, enabling it to overcome this limitation of traditional nonlinear programming methods. Unfortunately, PSO algorithm implementation and performance depend on several parameters, such as cognitive parameter, social parameter, and constriction coefficient. These parameters are tuned by using trial and error. To reduce the parametrization of a PSO method, this work presents two efficient hybrid SGO approaches, namely, a real-coded genetic algorithm-based PSO (RGA-PSO method and an artificial immune algorithm-based PSO (AIA-PSO method. The specific parameters of the internal PSO algorithm are optimized using the external RGA and AIA approaches, and then the internal PSO algorithm is applied to solve UGO problems. The performances of the proposed RGA-PSO and AIA-PSO algorithms are then evaluated using a set of benchmark UGO problems. Numerical results indicate that, besides their ability to converge to a global minimum for each test UGO problem, the proposed RGA-PSO and AIA-PSO algorithms outperform many hybrid SGO algorithms. Thus, the RGA-PSO and AIA-PSO approaches can be considered alternative SGO approaches for solving standard-dimensional UGO problems.

  14. A novel hybridization approach for detection of citrus viroids.

    Science.gov (United States)

    Murcia, N; Serra, P; Olmos, A; Duran-Vila, N

    2009-04-01

    Citrus plants are natural hosts of several viroid species all belonging to the family Pospiviroidae. Previous attempts to detect viroids from field-grown species and cultivars yielded erratic results unless analyses were performed using Etrog citron a secondary bio-amplification host. To overcome the use of Etrog citron a number of RT-PCR approaches have been proposed with different degrees of success. Here we report the suitability of an easy to handle northern hybridization protocol for viroid detection of samples collected from field-grown citrus species and cultivars. The protocol involves: (i) Nucleic acid preparations from bark tissue samples collected from field-grown trees regardless of the growing season and storage conditions; (ii) Separation in 5% PAGE or 1% agarose, blotting to membrane and fixing; (iii) Hybridization with viroid-specific DIG-labelled probes and detection with anti-DIG-alkaline phosphatase conjugate and autoradiography with the CSPD substrate. The method has been tested with viroid-infected trees of sweet orange, lemon, mandarin, grapefruit, sour orange, Swingle citrumello, Tahiti lime and Mexican lime. This novel hybridization approach is extremely sensitive, easy to handle and shortens the time needed for reliable viroid indexing tests. The suitability of PCR generated DIG-labelled probes and the sensitivity achieved when the samples are separated and blotted from non-denaturing gels are discussed.

  15. Forecasting conditional climate-change using a hybrid approach

    Science.gov (United States)

    Esfahani, Akbar Akbari; Friedel, Michael J.

    2014-01-01

    A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.

  16. Synthesis and characterization of polypropylene/jigsaw wood ash composite

    International Nuclear Information System (INIS)

    Sudirman; Karo Karo, Aloma; Gunawan, Indra; Handayani, Ari; Hertinvyana, Evi

    2002-01-01

    The composite of polypropylene (PP) polymer with jigsaw wood ash as filler is the alternative composite material. The dispersion of the filler in the composite is random with the jigsaw wood ash composition of 10,30, and 50% by volume. The characterization of composite are done to measure its mechanical properties, physical properties and microstructure by using XRD and SEM. From this research, it is concluded that increasing filler content of the composite will decrease its mechanical and physical properties. The comparation of different composites are found that tensile strength of PP MF 10 is higher 4.24% compared with PP MF 2 as a matrix. It is also found that melting temperature of PP MF 10 is higher 4.09% compared with PP MF 2 as a matrices and the decomposition temperature different is 0.17%. The degree of crystallinity of composite with PP MF 10 as a matrices is 2.55% higher compared with PP MF 2. The higher degree of crystallinity is increasing the tensile strength

  17. A hybrid approach for efficient anomaly detection using metaheuristic methods

    Directory of Open Access Journals (Sweden)

    Tamer F. Ghanem

    2015-07-01

    Full Text Available Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

  18. Approaches to Low Fuel Regression Rate in Hybrid Rocket Engines

    Directory of Open Access Journals (Sweden)

    Dario Pastrone

    2012-01-01

    Full Text Available Hybrid rocket engines are promising propulsion systems which present appealing features such as safety, low cost, and environmental friendliness. On the other hand, certain issues hamper the development hoped for. The present paper discusses approaches addressing improvements to one of the most important among these issues: low fuel regression rate. To highlight the consequence of such an issue and to better understand the concepts proposed, fundamentals are summarized. Two approaches are presented (multiport grain and high mixture ratio which aim at reducing negative effects without enhancing regression rate. Furthermore, fuel material changes and nonconventional geometries of grain and/or injector are presented as methods to increase fuel regression rate. Although most of these approaches are still at the laboratory or concept scale, many of them are promising.

  19. A hybrid personalized data recommendation approach for geoscience data sharing

    Science.gov (United States)

    WANG, M.; Wang, J.

    2016-12-01

    Recommender systems are effective tools helping Internet users overcome information overloading. The two most widely used recommendation algorithms are collaborating filtering (CF) and content-based filtering (CBF). A number of recommender systems based on those two algorithms were developed for multimedia, online sells, and other domains. Each of the two algorithms has its advantages and shortcomings. Hybrid approaches that combine these two algorithms are better choices in many cases. In geoscience data sharing domain, where the items (datasets) are more informative (in space and time) and domain-specific, no recommender system is specialized for data users. This paper reports a dynamic weighted hybrid recommendation algorithm that combines CF and CBF for geoscience data sharing portal. We first derive users' ratings on items with their historical visiting time by Jenks Natural Break. In the CBF part, we incorporate the space, time, and subject information of geoscience datasets to compute item similarity. Predicted ratings were computed with k-NN method separately using CBF and CF, and then combined with weights. With training dataset we attempted to find the best model describing ideal weights and users' co-rating numbers. A logarithmic function was confirmed to be the best model. The model was then used to tune the weights of CF and CBF on user-item basis with test dataset. Evaluation results show that the dynamic weighted approach outperforms either solo CF or CBF approach in terms of Precision and Recall.

  20. A hybrid approach for minimizing makespan in permutation flowshop scheduling

    DEFF Research Database (Denmark)

    Govindan, Kannan; Balasundaram, R.; Baskar, N.

    2017-01-01

    This work proposes a hybrid approach for solving traditional flowshop scheduling problems to reduce the makespan (total completion time). To solve scheduling problems, a combination of Decision Tree (DT) and Scatter Search (SS) algorithms are used. Initially, the DT is used to generate a seed...... solution which is then given input to the SS to obtain optimal / near optimal solutions of makespan. The DT used the entropy function to convert the given problem into a tree structured format / set of rules. The SS provides an extensive investigation of the search space through diversification...

  1. Hybrid closure of atrial septal defect: A modified approach

    Directory of Open Access Journals (Sweden)

    Kshitij Sheth

    2015-01-01

    Full Text Available A 3.5-year-old girl underwent transcatheter closure of patent ductus arteriosus in early infancy during which time her secundum atrial septal defect (ASD was left alone. When she came for elective closure of ASD, she was found to have bilaterally blocked femoral veins. The defect was successfully closed with an Amplatzer septal occluder (ASO; St. Jude Medical, Plymouth, MN, USA using a hybrid approach via a sub-mammary mini-thoracotomy incision without using cardiopulmonary bypass. At the end of 1-year follow-up, the child is asymptomatic with device in a stable position without any residual shunt.

  2. Pengaruh Metode Pembelajaran Kooperatif Tipe Jigsaw Terhadap Prestasi Belajar Mahasiswa: Sebuah Eksperimen Semu

    Directory of Open Access Journals (Sweden)

    Zulfikar Ismail

    2011-12-01

    Full Text Available Abstract: The Effect of Cooperative Learning Method in Jigsaw Type on the Students’ Learning Performance: A Semi Quasi Experiment. This study is aimed to prove whether there are differences in students’ learning achievements in studying Financial Accounting I about IFRS between Jigsaw cooperative learning method and conventional learning method. The subject of this study is students of Accounting Department of Brawijaya University of Malang who were taking financial accounting I in the short course of 2009–2010. The data analysis is carried out by difference test to prove students’ learning achievement taught using Jigsaw cooperative learning method and conventional method. The study proves that in understanding financial accounting about IFRS, the learning process using Jigsaw cooperative learning method is better than the conventional method.

  3. An Adaptive and Hybrid Approach for Revisiting the Visibility Pipeline

    Directory of Open Access Journals (Sweden)

    Ícaro Lins Leitão da Cunha

    2016-04-01

    Full Text Available We revisit the visibility problem, which is traditionally known in Computer Graphics and Vision fields as the process of computing a (potentially visible set of primitives in the computational model of a scene. We propose a hybrid solution that uses a dry structure (in the sense of data reduction, a triangulation of the type J1a, to accelerate the task of searching for visible primitives. We came up with a solution that is useful for real-time, on-line, interactive applications as 3D visualization. In such applications the main goal is to load the minimum amount of primitives from the scene during the rendering stage, as possible. For this purpose, our algorithm executes the culling by using a hybrid paradigm based on viewing-frustum, back-face culling and occlusion models. Results have shown substantial improvement over these traditional approaches if applied separately. This novel approach can be used in devices with no dedicated processors or with low processing power, as cell phones or embedded displays, or to visualize data through the Internet, as in virtual museums applications.

  4. JIGSAW PUZZLE IMPROVE FINE MOTOR ABILITIES OF UPPER EXTREMITIES IN POST-STROKE ISCHEMIC CLIENTS

    Directory of Open Access Journals (Sweden)

    Kusnanto Kusnanto

    2017-06-01

    Full Text Available Introduction: Ischemic stroke is a disease caused by focal cerebral ischemia, where is a decline in blood flow that needed for neuronal metabolism, leading to neurologic deficit include motor deficit such as fine motor skills impairment. Therapy of fine motor skills disorders is to improve motor function, prevent contractures and complications. These study aimed to identify the effect of playing Jigsaw Puzzle on muscle strength, extensive motion, and upper extremity fine motor skills in patients with ischemic stroke at Dr. Moewardi Hospital, Surakarta. Methods: Experimental Quasi pre-posttest one group control. The number of samples were 34 respondents selected using purposive sampling technique. The samples were divided into intervention and control groups. The intervention group was 17 respondents who were given standard treatment hospital and played Jigsaw Puzzle 2 times a day for six days. Control group is one respondent given by hospital standard therapy without given additional Jigsaw Puzzle game. Evaluation of these research is done on the first and seventh day for those groups. Result: The results showed that muscle strength, the range of joint motion and fine motor skills of upper extremities increased (p = 0.001 significantly after being given the Jigsaw Puzzle games. These means playing Jigsaw Puzzle increase muscle strength, the range of joint motion and upper extremity fine motor skill of ischemic stroke patients. Discussion and conclusion: Jigsaw puzzle game administration as additional rehabilitation therapy in upper extremity fine motor to minimize the occurrence of contractures and motor disorders in patients with ischemic stroke. Jigsaw puzzle game therapy capable of creating repetitive motion as a key of neurological rehabilitation in Ischemic Stroke. This study recommends using jigsaw puzzle game as one of intervention in the nursing care of Ischemic Stroke patients.

  5. A Hybrid Genetic Algorithm Approach for Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Sydulu Maheswarapu

    2011-08-01

    Full Text Available This paper puts forward a reformed hybrid genetic algorithm (GA based approach to the optimal power flow. In the approach followed here, continuous variables are designed using real-coded GA and discrete variables are processed as binary strings. The outcomes are compared with many other methods like simple genetic algorithm (GA, adaptive genetic algorithm (AGA, differential evolution (DE, particle swarm optimization (PSO and music based harmony search (MBHS on a IEEE30 bus test bed, with a total load of 283.4 MW. Its found that the proposed algorithm is found to offer lowest fuel cost. The proposed method is found to be computationally faster, robust, superior and promising form its convergence characteristics.

  6. Effects of Jigsaw Learning Method on Students’ Self-Efficacy and Motivation to Learn

    Directory of Open Access Journals (Sweden)

    Dwi Nur Rachmah

    2017-12-01

    Full Text Available Jigsaw learning as a cooperative learning method, according to the results of some studies, can improve academic skills, social competence, behavior in learning, and motivation to learn. However, in some other studies, there are different findings regarding the effect of jigsaw learning method on self-efficacy. The purpose of this study is to examine the effects of jigsaw learning method on self-efficacy and motivation to learn in psychology students at the Faculty of Medicine, Universitas Lambung Mangkurat. The method used in the study is the experimental method using one group pre-test and post-test design. The results of the measurements before and after the use of jigsaw learning method were compared using paired samples t-test. The results showed that there is a difference in students’ self-efficacy and motivation to learn before and after subjected to the treatments; therefore, it can be said that jigsaw learning method had significant effects on self-efficacy and motivation to learn. The application of jigsaw learning model in a classroom with large number of students was the discussion of this study.

  7. Peningkatan Mutu Pembelajaran Teknologi Pengecatan melalui Metode Jigsaw Bagi Mahasiswa Otomotif FT UNY

    Directory of Open Access Journals (Sweden)

    Tawardjono Usman

    2016-04-01

    Full Text Available The objective of the study was to investigate (1 the implementation of the jigsaw technique, (2 the students’ participation in the jigsaw technique, and (3 the learning achievement of the students in the course of painting technology through the jigsaw technique. This study used a classroom action research design developed by Kemmis and Mc Taggart in 2 cycles. The study was conducted in the Department of Automotive Engineering Education, Faculty of Engineering, Yogyakarta State University involving 28 students. The data collection method used documentation, observation and tests. The instruments used in this study include: an observation sheet and a written test. The data analysis techniques used comparative descriptive and qualitative. The results of this study were: (1 the implementation of the jigsaw technique was conducted in 2 cycles in the subject of painting defects, with the formation of the groups as heterogeneous, delivering the common materials, a pretest, and group discussions between the source and the expert groups (in 2 cycles, and a post test , (2 learning with jigsaw technique can improve the quality of the students’ learning, and (3 the jigsaw technique increases 74% of the value of the pretest and the post test.

  8. Genetic algorithm and neural network hybrid approach for job-shop scheduling

    OpenAIRE

    Zhao, Kai; Yang, Shengxiang; Wang, Dingwei

    1998-01-01

    Copyright @ 1998 ACTA Press This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach for job-shop scheduling with respect to the quality of solutions and ...

  9. A Hybrid Satellite-Terrestrial Approach to Aeronautical Communication Networks

    Science.gov (United States)

    Kerczewski, Robert J.; Chomos, Gerald J.; Griner, James H.; Mainger, Steven W.; Martzaklis, Konstantinos S.; Kachmar, Brian A.

    2000-01-01

    Rapid growth in air travel has been projected to continue for the foreseeable future. To maintain a safe and efficient national and global aviation system, significant advances in communications systems supporting aviation are required. Satellites will increasingly play a critical role in the aeronautical communications network. At the same time, current ground-based communications links, primarily very high frequency (VHF), will continue to be employed due to cost advantages and legacy issues. Hence a hybrid satellite-terrestrial network, or group of networks, will emerge. The increased complexity of future aeronautical communications networks dictates that system-level modeling be employed to obtain an optimal system fulfilling a majority of user needs. The NASA Glenn Research Center is investigating the current and potential future state of aeronautical communications, and is developing a simulation and modeling program to research future communications architectures for national and global aeronautical needs. This paper describes the primary requirements, the current infrastructure, and emerging trends of aeronautical communications, including a growing role for satellite communications. The need for a hybrid communications system architecture approach including both satellite and ground-based communications links is explained. Future aeronautical communication network topologies and key issues in simulation and modeling of future aeronautical communications systems are described.

  10. A Hybrid Soft Computing Approach for Subset Problems

    Directory of Open Access Journals (Sweden)

    Broderick Crawford

    2013-01-01

    Full Text Available Subset problems (set partitioning, packing, and covering are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S can be partitioned into smaller subsets. All items in S must be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions and set covering (all items must be contained in at least one partition. Here, we present a hybrid solver based on ant colony optimization (ACO combined with arc consistency for solving this kind of problems. ACO is a swarm intelligence metaheuristic inspired on ants behavior when they search for food. It allows to solve complex combinatorial problems for which traditional mathematical techniques may fail. By other side, in constraint programming, the solving process of Constraint Satisfaction Problems can dramatically reduce the search space by means of arc consistency enforcing constraint consistencies either prior to or during search. Our hybrid approach was tested with set covering and set partitioning dataset benchmarks. It was observed that the performance of ACO had been improved embedding this filtering technique in its constructive phase.

  11. A hybrid data compression approach for online backup service

    Science.gov (United States)

    Wang, Hua; Zhou, Ke; Qin, MingKang

    2009-08-01

    With the popularity of Saas (Software as a service), backup service has becoming a hot topic of storage application. Due to the numerous backup users, how to reduce the massive data load is a key problem for system designer. Data compression provides a good solution. Traditional data compression application used to adopt a single method, which has limitations in some respects. For example data stream compression can only realize intra-file compression, de-duplication is used to eliminate inter-file redundant data, compression efficiency cannot meet the need of backup service software. This paper proposes a novel hybrid compression approach, which includes two levels: global compression and block compression. The former can eliminate redundant inter-file copies across different users, the latter adopts data stream compression technology to realize intra-file de-duplication. Several compressing algorithms were adopted to measure the compression ratio and CPU time. Adaptability using different algorithm in certain situation is also analyzed. The performance analysis shows that great improvement is made through the hybrid compression policy.

  12. Dry Port Location Problem: A Hybrid Multi-Criteria Approach

    Directory of Open Access Journals (Sweden)

    BENTALEB Fatimazahra

    2016-03-01

    Full Text Available Choosing a location for a dry port is a problem which becomes more essential and crucial. This study deals with the problem of locating dry ports. On this matter, a model combining multi-criteria (MACBETH and mono-criteria (BARYCENTER methods to find a solution to dry port location problem has been proposed. In the first phase, a systematic literature review was carried out on dry port location problem and then a methodological classification was presented for this research. In the second phase, a hybrid multi-criteria approach was developed in order to determine the best dry port location taking different criteria into account. A Computational practice and a qualitative analysis from a case study in the Moroccan context have been provided. The results show that the optimal location is very convenient with the geographical region and the government policies.

  13. Attention-level transitory response: a novel hybrid BCI approach

    Science.gov (United States)

    Diez, Pablo F.; Garcés Correa, Agustina; Orosco, Lorena; Laciar, Eric; Mut, Vicente

    2015-10-01

    Objective. People with disabilities may control devices such as a computer or a wheelchair by means of a brain-computer interface (BCI). BCI based on steady-state visual evoked potentials (SSVEP) requires visual stimulation of the user. However, this SSVEP-based BCI suffers from the ‘Midas touch effect’, i.e., the BCI can detect an SSVEP even when the user is not gazing at the stimulus. Then, these incorrect detections deteriorate the performance of the system, especially in asynchronous BCI because ongoing EEG is classified. In this paper, a novel transitory response of the attention-level of the user is reported. It was used to develop a hybrid BCI (hBCI). Approach. Three methods are proposed to detect the attention-level of the user. They are based on the alpha rhythm and theta/beta rate. The proposed hBCI scheme is presented along with these methods. Hence, the hBCI sends a command only when the user is at a high-level of attention, or in other words, when the user is really focused on the task being performed. The hBCI was tested over two different EEG datasets. Main results. The performance of the hybrid approach is superior to the standard one. Improvements of 20% in accuracy and 10 bits min-1 are reported. Moreover, the attention-level is extracted from the same EEG channels used in SSVEP detection and this way, no extra hardware is needed. Significance. A transitory response of EEG signal is used to develop the attention-SSVEP hBCI which is capable of reducing the Midas touch effect.

  14. Hybrid x-space: a new approach for MPI reconstruction.

    Science.gov (United States)

    Tateo, A; Iurino, A; Settanni, G; Andrisani, A; Stifanelli, P F; Larizza, P; Mazzia, F; Mininni, R M; Tangaro, S; Bellotti, R

    2016-06-07

    Magnetic particle imaging (MPI) is a new medical imaging technique capable of recovering the distribution of superparamagnetic particles from their measured induced signals. In literature there are two main MPI reconstruction techniques: measurement-based (MB) and x-space (XS). The MB method is expensive because it requires a long calibration procedure as well as a reconstruction phase that can be numerically costly. On the other side, the XS method is simpler than MB but the exact knowledge of the field free point (FFP) motion is essential for its implementation. Our simulation work focuses on the implementation of a new approach for MPI reconstruction: it is called hybrid x-space (HXS), representing a combination of the previous methods. Specifically, our approach is based on XS reconstruction because it requires the knowledge of the FFP position and velocity at each time instant. The difference with respect to the original XS formulation is how the FFP velocity is computed: we estimate it from the experimental measurements of the calibration scans, typical of the MB approach. Moreover, a compressive sensing technique is applied in order to reduce the calibration time, setting a fewer number of sampling positions. Simulations highlight that HXS and XS methods give similar results. Furthermore, an appropriate use of compressive sensing is crucial for obtaining a good balance between time reduction and reconstructed image quality. Our proposal is suitable for open geometry configurations of human size devices, where incidental factors could make the currents, the fields and the FFP trajectory irregular.

  15. HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.

    Science.gov (United States)

    Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

    2017-12-01

    For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm. HAMDA took not only network structure and information propagation but also node attribution into consideration, resulting in a satisfactory prediction performance. Specifically, HAMDA obtained AUCs of 0.9035 and 0.8395 in the frameworks of global and local leave-one-out cross validation, respectively. Meanwhile, HAMDA also achieved good performance with AUC of 0.8965 ± 0.0012 in 5-fold cross validation. Additionally, we conducted case studies about three important human cancers for performance evaluation of HAMDA. As a result, 90% (Lymphoma), 86% (Prostate Cancer) and 92% (Kidney Cancer) of top 50 predicted miRNAs were confirmed by recent experiment literature, which showed the reliable prediction ability of HAMDA. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

    Science.gov (United States)

    Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

    2016-01-01

    Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

  17. An energy management approach of hybrid vehicles using traffic preview information for energy saving

    International Nuclear Information System (INIS)

    Zheng, Chunhua; Xu, Guoqing; Xu, Kun; Pan, Zhongming; Liang, Quan

    2015-01-01

    Highlights: • Energy management approach of hybrid vehicles using traffic preview information. • Vehicle velocity profile and fuel consumption are optimized at the same time. • It is proved that a further energy saving is achieved by the proposed approach. • The proposed approach is useful especially for autonomous hybrid vehicles. - Abstract: The traffic preview information is very helpful for hybrid vehicles when distributing the power requirement of the vehicle to power sources and when determining the next driving route of the vehicle. In this research, an energy management approach for hybrid vehicles is proposed, which optimizes the vehicle velocity profile while minimizing the fuel consumption with the help of the traffic preview information, so that a further energy saving for hybrid vehicles can be achieved. The Pontryagin’s Minimum Principle (PMP) is adopted on the proposed approach. A fuel cell hybrid vehicle (FCHV) is selected as an example, and the proposed energy management approach is applied to the FCHV in a computer simulation environment for the offline and online cases respectively. Simulation results show that the fuel economy of the FCHV is improved by the proposed energy management approach compared to a benchmark case where the driving cycle is fixed and only the hybrid power split (allocation) ratio is optimized. The proposed energy management approach is useful especially for the autonomous hybrid vehicles.

  18. The hybrid thermography approach applied to architectural structures

    Science.gov (United States)

    Sfarra, S.; Ambrosini, D.; Paoletti, D.; Nardi, I.; Pasqualoni, G.

    2017-07-01

    This work contains an overview of infrared thermography (IRT) method and its applications relating to the investigation of architectural structures. In this method, the passive approach is usually used in civil engineering, since it provides a panoramic view of the thermal anomalies to be interpreted also thanks to the use of photographs focused on the region of interest (ROI). The active approach, is more suitable for laboratory or indoor inspections, as well as for objects having a small size. The external stress to be applied is thermal, coming from non-natural apparatus such as lamps or hot / cold air jets. In addition, the latter permits to obtain quantitative information related to defects not detectable to the naked eyes. Very recently, the hybrid thermography (HIRT) approach has been introduced to the attention of the scientific panorama. It can be applied when the radiation coming from the sun, directly arrives (i.e., possibly without the shadow cast effect) on a surface exposed to the air. A large number of thermograms must be collected and a post-processing analysis is subsequently applied via advanced algorithms. Therefore, an appraisal of the defect depth can be obtained passing through the calculation of the combined thermal diffusivity of the materials above the defect. The approach is validated herein by working, in a first stage, on a mosaic sample having known defects while, in a second stage, on a Church built in L'Aquila (Italy) and covered with a particular masonry structure called apparecchio aquilano. The results obtained appear promising.

  19. Robust Sex Differences in Jigsaw Puzzle Solving-Are Boys Really Better in Most Visuospatial Tasks?

    Science.gov (United States)

    Kocijan, Vid; Horvat, Marina; Majdic, Gregor

    2017-01-01

    Sex differences are consistently reported in different visuospatial tasks with men usually performing better in mental rotation tests while women are better on tests for memory of object locations. In the present study, we investigated sex differences in solving jigsaw puzzles in children. In total 22 boys and 24 girls were tested using custom build tablet application representing a jigsaw puzzle consisting of 25 pieces and featuring three different pictures. Girls outperformed boys in solving jigsaw puzzles regardless of the picture. Girls were faster than boys in solving the puzzle, made less incorrect moves with the pieces of the puzzle, and spent less time moving the pieces around the tablet. It appears that the strategy of solving the jigsaw puzzle was the main factor affecting differences in success, as girls tend to solve the puzzle more systematically while boys performed more trial and error attempts, thus having more incorrect moves with the puzzle pieces. Results of this study suggest a very robust sex difference in solving the jigsaw puzzle with girls outperforming boys by a large margin.

  20. Robust Sex Differences in Jigsaw Puzzle Solving—Are Boys Really Better in Most Visuospatial Tasks?

    Science.gov (United States)

    Kocijan, Vid; Horvat, Marina; Majdic, Gregor

    2017-01-01

    Sex differences are consistently reported in different visuospatial tasks with men usually performing better in mental rotation tests while women are better on tests for memory of object locations. In the present study, we investigated sex differences in solving jigsaw puzzles in children. In total 22 boys and 24 girls were tested using custom build tablet application representing a jigsaw puzzle consisting of 25 pieces and featuring three different pictures. Girls outperformed boys in solving jigsaw puzzles regardless of the picture. Girls were faster than boys in solving the puzzle, made less incorrect moves with the pieces of the puzzle, and spent less time moving the pieces around the tablet. It appears that the strategy of solving the jigsaw puzzle was the main factor affecting differences in success, as girls tend to solve the puzzle more systematically while boys performed more trial and error attempts, thus having more incorrect moves with the puzzle pieces. Results of this study suggest a very robust sex difference in solving the jigsaw puzzle with girls outperforming boys by a large margin. PMID:29109682

  1. Perbedaan Metode Peer Teaching dengan Metode Jigsaw Terhadap Tingkat Pengetahuan Kesehatan Reproduksi

    Directory of Open Access Journals (Sweden)

    tetti solehati

    2018-06-01

    Full Text Available Adolescents are particularly vulnerable to the problem of the triad of adolescent reproductive health that includes sexuality, HIV/AIDS and drugs. Lack of knowledge among adolescents is one of the causes of risky behavior on reproductive health. Health education through peer teaching method and jigsaw method can improve knowledge and prevent adolescent reproductive health problems. The purpose of this research is to analyze the differences between the effects of peer teaching method with jigsaw method toward the level knowledge of reproductive health students SMPN 1 Cilegon. The research design is quasi-experiment with non equivalent control group. The research sample consisted of 42 respondents to the peer teaching group and 42 respondents to the jigsaw group which is chosen by stratified random sampling. The results of the analysis of statistical tests using t-dependent test shows that there is significant influence after being given health education with p value 0.001 (p <0.05 and the results t-independent test obtained p value 0.021 (p <0.05, which shows the differences in effect between peer teaching method with jigsaw method toward the level knowledge of reproductive health students SMPN 1 Cilegon. The suggestion of this research is to use the jigsaw method as an alternative method in providing adolescent reproductive health education.

  2. A hybrid ensemble learning approach to star-galaxy classification

    Science.gov (United States)

    Kim, Edward J.; Brunner, Robert J.; Carrasco Kind, Matias

    2015-10-01

    There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template-fitting method. Using data from the CFHTLenS survey (Canada-France-Hawaii Telescope Lensing Survey), we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2 (Deep Extragalactic Evolutionary Probe Phase 2 ), SDSS (Sloan Digital Sky Survey), VIPERS (VIMOS Public Extragalactic Redshift Survey), and VVDS (VIMOS VLT Deep Survey), and when the demographics of sources in a low-quality training set do not match the demographics of objects in the test data set. We demonstrate that our Bayesian combination technique improves the overall performance over any individual classification method in these scenarios. Thus, strategies that combine the predictions of different classifiers may prove to be optimal in currently ongoing and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

  3. Mobile phone use while driving: a hybrid modeling approach.

    Science.gov (United States)

    Márquez, Luis; Cantillo, Víctor; Arellana, Julián

    2015-05-01

    The analysis of the effects that mobile phone use produces while driving is a topic of great interest for the scientific community. There is consensus that using a mobile phone while driving increases the risk of exposure to traffic accidents. The purpose of this research is to evaluate the drivers' behavior when they decide whether or not to use a mobile phone while driving. For that, a hybrid modeling approach that integrates a choice model with the latent variable "risk perception" was used. It was found that workers and individuals with the highest education level are more prone to use a mobile phone while driving than others. Also, "risk perception" is higher among individuals who have been previously fined and people who have been in an accident or almost been in an accident. It was also found that the tendency to use mobile phones while driving increases when the traffic speed reduces, but it decreases when the fine increases. Even though the urgency of the phone call is the most important explanatory variable in the choice model, the cost of the fine is an important attribute in order to control mobile phone use while driving. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Agricultural Tractor Selection: A Hybrid and Multi-Attribute Approach

    Directory of Open Access Journals (Sweden)

    Jorge L. García-Alcaraz

    2016-02-01

    Full Text Available Usually, agricultural tractor investments are assessed using traditional economic techniques that only involve financial attributes, resulting in reductionist evaluations. However, tractors have qualitative and quantitative attributes that must be simultaneously integrated into the evaluation process. This article reports a hybrid and multi-attribute approach to assessing a set of agricultural tractors based on AHP-TOPSIS. To identify the attributes in the model, a survey including eighteen attributes was given to agricultural machinery salesmen and farmers for determining their importance. The list of attributes was presented to a decision group for a case of study, and their importance was estimated using AHP and integrated into the TOPSIS technique. In this case, one tractor was selected from a set of six alternatives, integrating six attributes in the model: initial cost, annual maintenance cost, liters of diesel per hour, safety of the operator, maintainability and after-sale customer service offered by the supplier. Based on the results obtained, the model can be considered easy to apply and to have good acceptance among farmers and salesmen, as there are no special software requirements for the application.

  5. Jigsaw puzzle metasurface for multiple functions: polarization conversion, anomalous reflection and diffusion.

    Science.gov (United States)

    Zhao, Yi; Cao, Xiangyu; Gao, Jun; Liu, Xiao; Li, Sijia

    2016-05-16

    We demonstrate a simple reconfigurable metasurface with multiple functions. Anisotropic tiles are investigated and manufactured as fundamental elements. Then, the tiles are combined in a certain sequence to construct a metasurface. Each of the tiles can be adjusted independently which is like a jigsaw puzzle and the whole metasurface can achieve diverse functions by different layouts. For demonstration purposes, we realize polarization conversion, anomalous reflection and diffusion by a jigsaw puzzle metasurface with 6 × 6 pieces of anisotropic tile. Simulated and measured results prove that our method offers a simple and effective strategy for metasurface design.

  6. Mass Optimization of Battery/Supercapacitors Hybrid Systems Based on a Linear Programming Approach

    Science.gov (United States)

    Fleury, Benoit; Labbe, Julien

    2014-08-01

    The objective of this paper is to show that, on a specific launcher-type mission profile, a 40% gain of mass is expected using a battery/supercapacitors active hybridization instead of a single battery solution. This result is based on the use of a linear programming optimization approach to perform the mass optimization of the hybrid power supply solution.

  7. When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

    KAUST Repository

    Liu, Xiao; Liu, An; Zhang, Xiangliang; Li, Zhixu; Liu, Guanfeng; Zhao, Lei; Zhou, Xiaofang

    2017-01-01

    result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP

  8. Emergence of Life on Earth: A Physicochemical Jigsaw Puzzle.

    Science.gov (United States)

    Spitzer, Jan

    2017-01-01

    We review physicochemical factors and processes that describe how cellular life can emerge from prebiotic chemical matter; they are: (1) prebiotic Earth is a multicomponent and multiphase reservoir of chemical compounds, to which (2) Earth-Moon rotations deliver two kinds of regular cycling energies: diurnal electromagnetic radiation and seawater tides. (3) Emerging colloidal phases cyclically nucleate and agglomerate in seawater and consolidate as geochemical sediments in tidal zones, creating a matrix of microspaces. (4) Some microspaces persist and retain memory from past cycles, and others re-dissolve and re-disperse back into the Earth's chemical reservoir. (5) Proto-metabolites and proto-biopolymers coevolve with and within persisting microspaces, where (6) Macromolecular crowding and other non-covalent molecular forces govern the evolution of hydrophilic, hydrophobic, and charged molecular surfaces. (7) The matrices of microspaces evolve into proto-biofilms of progenotes with rudimentary but evolving replication, transcription, and translation, enclosed in unstable cell envelopes. (8) Stabilization of cell envelopes 'crystallizes' bacteria-like genetics and metabolism with low horizontal gene transfer-life 'as we know it.' These factors and processes constitute the 'working pieces' of the jigsaw puzzle of life's emergence. They extend the concept of progenotes as the first proto-cellular life, connected backward in time to the cycling chemistries of the Earth-Moon planetary system, and forward to the ancient cell cycle of first bacteria-like organisms. Supra-macromolecular models of 'compartments first' are preferred: they facilitate macromolecular crowding-a key abiotic/biotic transition toward living states. Evolutionary models of metabolism or genetics 'first' could not have evolved in unconfined and uncrowded environments because of the diffusional drift to disorder mandated by the second law of thermodynamics.

  9. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    Energy Technology Data Exchange (ETDEWEB)

    Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

    2011-02-15

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  10. Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

    International Nuclear Information System (INIS)

    Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.

    2011-01-01

    In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

  11. A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries

    Directory of Open Access Journals (Sweden)

    Wen-An Yang

    2016-01-01

    Full Text Available Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles and its failure can lead to reduced capability, downtime, and even catastrophic breakdowns. Remaining useful life (RUL prediction of lithium-ion batteries before the future failure event is extremely crucial for proactive maintenance/safety actions. This study proposes a hybrid prognostic approach that can predict the RUL of degraded lithium-ion batteries using physical laws and data-driven modeling simultaneously. In this hybrid prognostic approach, the relevant vectors obtained with the selective kernel ensemble-based relevance vector machine (RVM learning algorithm are fitted to the physical degradation model, which is then extrapolated to failure threshold for estimating the RUL of the lithium-ion battery of interest. The experimental results indicated that the proposed hybrid prognostic approach can accurately predict the RUL of degraded lithium-ion batteries. Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs like the conventional backpropagation (BP algorithm and support vector machines (SVMs. In addition, an investigation is also conducted to identify the effects of RVM learning algorithm on the proposed hybrid prognostic approach.

  12. Considering the intrinsic constraints for groups management of TAPPS & Jigsaw CLFPs

    NARCIS (Netherlands)

    Pérez-Sanagustín, Mar; Burgos, Javier; Hernández-Leo, Davinia; Blat, Josep

    2009-01-01

    Pérez-Sanagustín, M., Burgos, J., Hernández-Leo, D., & Blat, J. (2009). Considering the intrinsic constraints for groups management of TAPPS & Jigsaw CLFPs. Proceedings of International Conference on Intelligent Networking and Collaborative Systems (INCoS 2009). November, 4-6, 2009, Barcelona,

  13. Impact of Expert Teaching Quality on Novice Academic Performance in the Jigsaw Cooperative Learning Method

    Science.gov (United States)

    Berger, Roland; Hänze, Martin

    2015-01-01

    We assessed the impact of expert students' instructional quality on the academic performance of novice students in 12th-grade physics classes organized in an expert model of cooperative learning ("jigsaw classroom"). The instructional quality of 129 expert students was measured by a newly developed rating system. As expected, when…

  14. Instructional Media Production for Early Childhood Education: A. B. C. Jig-Saw Puzzle, a Model

    Science.gov (United States)

    Yusuf, Mudashiru Olalere; Olanrewaju, Olatayo Solomon; Soetan, Aderonke K.

    2015-01-01

    In this paper, a. b. c. jig-saw puzzle was produced for early childhood education using local materials. This study was a production based type of research, to serve as a supplemental or total learning resource. Its production followed four phases of development referred to as information, design, production and evaluation. The storyboard cards,…

  15. Cooperative Learning in Virtual Environments: The Jigsaw Method in Statistical Courses

    Science.gov (United States)

    Vargas-Vargas, Manuel; Mondejar-Jimenez, Jose; Santamaria, Maria-Letica Meseguer; Alfaro-Navarro, Jose-Luis; Fernandez-Aviles, Gema

    2011-01-01

    This document sets out a novel teaching methodology as used in subjects with statistical content, traditionally regarded by students as "difficult". In a virtual learning environment, instructional techniques little used in mathematical courses were employed, such as the Jigsaw cooperative learning method, which had to be adapted to the…

  16. The Effects of Jigsaw Learning on Students' Attitudes in a Vietnamese Higher Education Classroom

    Science.gov (United States)

    Tran, Van Dat; Lewis, Ramon

    2012-01-01

    As a part of an experimental study on the effects of jigsaw learning on Vietnamese tertiary students' achievement and knowledge retention, students' attitudes towards six weeks of this kind of instruction were assessed. As noted in our previous report, students in the experimental group (N = 40), who perceived their instruction as more cooperative…

  17. Effects of Jigsaw and Animation Techniques on Students' Understanding of Concepts and Subjects in Electrochemistry

    Science.gov (United States)

    Doymus, Kemal; Karacop, Ataman; Simsek, Umit

    2010-01-01

    This study investigated the effect of jigsaw cooperative learning and animation versus traditional teaching methods on students' understanding of electrochemistry in a first-year general chemistry course. This study was carried out in three different classes in the department of primary science education during the 2007-2008 academic year. The…

  18. Hybridization success is largely limited to homoploid Prunus hybrids: a multidisciplinary approach

    Czech Academy of Sciences Publication Activity Database

    Macková, L.; Vít, Petr; Ďurišová, Ľ.; Eliáš, P. Jr.; Urfus, T.

    2017-01-01

    Roč. 303, č. 4 (2017), s. 481-495 ISSN 0378-2697 Institutional support: RVO:67985939 Keywords : absolute genome size * interspecific hybridization * embryology Subject RIV: EF - Botanics OBOR OECD: Plant sciences, botany Impact factor: 1.239, year: 2016

  19. A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid Wind Turbine Rotors

    DEFF Research Database (Denmark)

    Herbert-Acero, José F.; Martínez-Lauranchet, Jaime; Probst, Oliver

    2014-01-01

    of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize...

  20. Hybrid Engine Powered City Car: Fuzzy Controlled Approach

    Science.gov (United States)

    Rahman, Ataur; Mohiuddin, AKM; Hawlader, MNA; Ihsan, Sany

    2017-03-01

    This study describes a fuzzy controlled hybrid engine powered car. The car is powered by the lithium ion battery capacity of 1000 Wh is charged by the 50 cc hybrid engine and power regenerative mode. The engine is operated with lean mixture at 3000 rpm to charge the battery. The regenerative mode that connects with the engine generates electrical power of 500-600 W for the deceleration of car from 90 km/h to 20 km/h. The regenerated electrical power has been used to power the air-conditioning system and to meet the other electrical power. The battery power only used to propel the car. The regenerative power also found charging the battery for longer operation about 40 minutes and more. The design flexibility of this vehicle starts with whole-vehicle integration based on radical light weighting, drag reduction, and accessory efficiency. The energy efficient hybrid engine cut carbon dioxide (CO2) and nitrogen oxides (N2O) emission about 70-80% as the loads on the crankshaft such as cam-follower and its associated rotating components are replaced by electromagnetic systems, and the flywheel, alternator and starter motor are replaced by a motor generator. The vehicle was tested and found that it was able to travel 70 km/litre with the power of hybrid engine.

  1. A promising hybrid approach to SPECT attenuation correction

    International Nuclear Information System (INIS)

    Lewis, N.H.; Faber, T.L.; Corbett, J.R.; Stokely, E.M.

    1984-01-01

    Most methods for attenuation compensation in SPECT either rely on the assumption of uniform attenuation, or use slow iteration to achieve accuracy. However, hybrid methods that combine iteration with simple multiplicative correction can accommodate nonuniform attenuation, and such methods converge faster than other iterative techniques. The authors evaluated two such methods, which differ in use of a damping factor to control convergence. Both uniform and nonuniform attenuation were modeled, using simulated and phantom data for a rotating gamma camera. For simulations done with 360 0 data and the correct attenuation map, activity levels were reconstructed to within 5% of the correct values after one iteration. Using 180 0 data, reconstructed levels in regions representing lesion and background were within 5% of the correct values in three iterations; however, further iterations were needed to eliminate the characteristic streak artifacts. The damping factor had little effect on 360 0 reconstruction, but was needed for convergence with 180 0 data. For both cold- and hot-lesion models, image contrast was better from the hybrid methods than from the simpler geometric-mean corrector. Results from the hybrid methods were comparable to those obtained using the conjugate-gradient iterative method, but required 50-100% less reconstruction time. The relative speed of the hybrid methods, and their accuracy in reconstructing photon activity in the presence of nonuniform attenuation, make them promising tools for quantitative SPECT reconstruction

  2. Using a Hybrid Approach for a Leadership Cohort Program

    Science.gov (United States)

    Norman, Maxine A.

    2013-01-01

    Because information technology continues to change rapidly, Extension is challenged with learning and using technology appropriately. We assert Extension cannot shy away from the challenges but must embrace technology because audiences and external forces demand it. A hybrid, or blended, format of a leadership cohort program was offered to public…

  3. Cooperative learning in third graders' jigsaw groups for mathematics and science with and without questioning training.

    Science.gov (United States)

    Souvignier, Elmar; Kronenberger, Julia

    2007-12-01

    There is much support for using cooperative methods, since important instructional aspects, such as elaboration of new information, can easily be realized by methods like 'jigsaw'. However, the impact of providing students with additional help like a questioning training and potential limitations of the method concerning the (minimum) age of the students have rarely been investigated. The study investigated the effects of cooperative methods at elementary school level. Three conditions of instruction were compared: jigsaw, jigsaw with a supplementary questioning training and teacher-guided instruction. Nine third grade classes from three schools with 208 students participated in the study. In each school, all the three instructional conditions were realized in three different classes. All classes studied three units on geometry and one unit on astronomy using the assigned instructional method. Each learning unit comprised six lessons. For each unit, an achievement test was administered as pre-test, post-test and delayed test. In the math units, no differences between the three conditions could be detected. In the astronomy unit, students benefited more from teacher-guided instruction. Differential analyses revealed that 'experts' learned more than students in teacher-guided instruction, whereas 'novices' were outperformed by the students in the control classes. Even third graders used the jigsaw method with satisfactory learning results. The modest impact of the questioning training and the low learning gains of the cooperative classes in the astronomy unit as well as high discrepancies between learning outcomes of experts and novices show that explicit instruction of explaining skills in combination with well-structured material are key issues in using the jigsaw method with younger students.

  4. Facile approach to prepare Pt decorated SWNT/graphene hybrid catalytic ink

    Energy Technology Data Exchange (ETDEWEB)

    Mayavan, Sundar, E-mail: sundarmayavan@cecri.res.in [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Mandalam, Aditya; Balasubramanian, M. [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Sim, Jun-Bo [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Choi, Sung-Min, E-mail: sungmin@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of)

    2015-07-15

    Highlights: • Pt NPs were in situ synthesized onto CNT–graphene support in aqueous solution. • The as-prepared material was used directly as a catalyst ink without further treatment. • Catalyst ink is active toward methanol oxidation. • This approach realizes both scalable and greener production of hybrid catalysts. - Abstract: Platinum nanoparticles were in situ synthesized onto hybrid support involving graphene and single walled carbon nanotube in aqueous solution. We investigate the reduction of graphene oxide, and platinum nanoparticle functionalization on hybrid support by X-ray photoelectron spectroscopy, Raman spectroscopy, X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The as-prepared platinum on hybrid support was used directly as a catalyst ink without further treatment and is active toward methanol oxidation. This work realizes both scalable and greener production of highly efficient hybrid catalysts, and would be valuable for practical applications of graphene based fuel cell catalysts.

  5. A Hybrid Approach for Thread Recommendation in MOOC Forums

    OpenAIRE

    Ahmad. A. Kardan; Amir Narimani; Foozhan Ataiefard

    2017-01-01

    Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC ...

  6. Interactive Digital Storytelling: Towards a Hybrid Conceptual Approach

    OpenAIRE

    Spierling, Ulrike

    2005-01-01

    1 Introduction In this contribution, Interactive Digital Storytelling is viewed as a hybrid form of game design and cinematic storytelling for the understanding and making of future learning and entertainment applications. The paper shall present formal design models that provide a conceptual bridge between both traditional linear narrative techniques as well as agent-based emergent conversations with virtual characters. In summary, a theoretical classification of thinking models for authors ...

  7. Control and fault diagnosis based sliding mode observer of a multicellular converter: Hybrid approach

    KAUST Repository

    Benzineb, Omar

    2013-01-01

    In this article, the diagnosis of a three cell converter is developed. The hybrid nature of the system represented by the presence of continuous and discrete dynamics is taken into account in the control design. The idea is based on using a hybrid control and an observer-type sliding mode to generate residuals from the observation errors of the system. The simulation results are presented at the end to illustrate the performance of the proposed approach. © 2013 FEI STU.

  8. An hybrid and non-modern approach to urban studies

    Directory of Open Access Journals (Sweden)

    Marc Grau i Solés

    2012-03-01

    Full Text Available This article draws upon the so-called Forat de la Vergonya urban controversy and the urban transformation process of a neighborhood in Barcelona: el Casc Antic. Drawing on inputs from Actor-Network Theory (ANT, the city is explored as a multiple urban assemblage. Besides, we analyze the dichotomous nature of the modern notion of politics. Especially, the role of object-subject dichotomy is explored. Through the analysis of citizen participation opportunities we propose a new hybrid notion of citizen participation and urban policy.

  9. Active diagnosis of hybrid systems - A model predictive approach

    DEFF Research Database (Denmark)

    Tabatabaeipour, Seyed Mojtaba; Ravn, Anders P.; Izadi-Zamanabadi, Roozbeh

    2009-01-01

    A method for active diagnosis of hybrid systems is proposed. The main idea is to predict the future output of both normal and faulty model of the system; then at each time step an optimization problem is solved with the objective of maximizing the difference between the predicted normal and fault...... can be used as a test signal for sanity check at the commissioning or for detection of faults hidden by regulatory actions of the controller. The method is tested on the two tank benchmark example. ©2009 IEEE....

  10. A hybrid approach for probabilistic forecasting of electricity price

    DEFF Research Database (Denmark)

    Wan, Can; Xu, Zhao; Wang, Yelei

    2014-01-01

    to the nonstationarities involved in market clearing prices (MCPs), it is rather difficult to accurately predict MCPs in advance. The challenge is getting intensified as more and more renewable energy and other new technologies emerged in smart grids. Therefore transformation from traditional point forecasts...... electricity price forecasting is proposed in this paper. The effectiveness of the proposed hybrid method has been validated through comprehensive tests using real price data from Australian electricity market.......The electricity market plays a key role in realizing the economic prophecy of smart grids. Accurate and reliable electricity market price forecasting is essential to facilitate various decision making activities of market participants in the future smart grid environment. However, due...

  11. A Hybrid ACO Approach to the Matrix Bandwidth Minimization Problem

    Science.gov (United States)

    Pintea, Camelia-M.; Crişan, Gloria-Cerasela; Chira, Camelia

    The evolution of the human society raises more and more difficult endeavors. For some of the real-life problems, the computing time-restriction enhances their complexity. The Matrix Bandwidth Minimization Problem (MBMP) seeks for a simultaneous permutation of the rows and the columns of a square matrix in order to keep its nonzero entries close to the main diagonal. The MBMP is a highly investigated {NP}-complete problem, as it has broad applications in industry, logistics, artificial intelligence or information recovery. This paper describes a new attempt to use the Ant Colony Optimization framework in tackling MBMP. The introduced model is based on the hybridization of the Ant Colony System technique with new local search mechanisms. Computational experiments confirm a good performance of the proposed algorithm for the considered set of MBMP instances.

  12. Hybrid Quantum-Classical Approach to Quantum Optimal Control.

    Science.gov (United States)

    Li, Jun; Yang, Xiaodong; Peng, Xinhua; Sun, Chang-Pu

    2017-04-14

    A central challenge in quantum computing is to identify more computational problems for which utilization of quantum resources can offer significant speedup. Here, we propose a hybrid quantum-classical scheme to tackle the quantum optimal control problem. We show that the most computationally demanding part of gradient-based algorithms, namely, computing the fitness function and its gradient for a control input, can be accomplished by the process of evolution and measurement on a quantum simulator. By posing queries to and receiving answers from the quantum simulator, classical computing devices update the control parameters until an optimal control solution is found. To demonstrate the quantum-classical scheme in experiment, we use a seven-qubit nuclear magnetic resonance system, on which we have succeeded in optimizing state preparation without involving classical computation of the large Hilbert space evolution.

  13. Hybrid simulation of reactor kinetics in CANDU reactors using a modal approach

    International Nuclear Information System (INIS)

    Monaghan, B.M.; McDonnell, F.N.; Hinds, H.W.T.; m.

    1980-01-01

    A hybrid computer model for simulating the behaviour of large CANDU (Canada Deuterium Uranium) reactor cores is presented. The main dynamic variables are expressed in terms of weighted sums of a base set of spatial natural-mode functions with time-varying co-efficients. This technique, known as the modal or synthesis approach, permits good three-dimensional representation of reactor dynamics and is well suited to hybrid simulation. The hybrid model provides improved man-machine interaction and real-time capability. The model was used in two applications. The first studies the transient that follows a loss of primary coolant and reactor shutdown; the second is a simulation of the dynamics of xenon, a fission product which has a high absorption cross-section for neutrons and thus has an important effect on reactor behaviour. Comparison of the results of the hybrid computer simulation with those of an all-digital one is good, within 1% to 2%

  14. A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran

    Directory of Open Access Journals (Sweden)

    Shakiba Khademolqorani

    2015-01-01

    Full Text Available Bankruptcy prediction is an important problem facing financial decision support for stakeholders of firms, including auditors, managers, shareholders, debt-holders, and potential investors, as well as academic researchers. Popular discourse on financial distress forecasting focuses on developing the discrete models to improve the prediction. The aim of this paper is to develop a novel hybrid financial distress model based on combining various statistical and machine learning methods. Then multiple attribute decision making method is exploited to choose the optimized model from the implemented ones. Proposed approaches have also been applied in Iranian companies that performed previous models and it can be consolidated with the help of the hybrid approach.

  15. HYBRID EDUCATION: THE ESTIMATION IN THE CATEGORIES OF INFORMATION-AXIOLOGICAL APPROACH

    Directory of Open Access Journals (Sweden)

    A. S. Kizilova

    2018-01-01

    Full Text Available Introduction: a hybrid assessment of reality is a new information-axiological level of communication between people. The term "hybrid (hybrid training" has been used as a result of the integration of digital and communication technologies in the form of online courses.Materials and methods: the main Russian forms of education are analyzed. The evaluation of the forms of education in the categories of the information-axiological approach is made on the basis of the following idea: everything is interchangeable, since everything has value. The mixing principles and models used in the process of hybrid formation are considered. Due to the fact that any mixed training requires planning, the analysis of the project and the target group, content analysis and financial analysis in this process is carried out.Results: specific educational methods are studied at the Bauman MSTU, subject to a hybrid assessment in the categories of the information-axiological approach. The analysis showed that the above explanation of the term "hybrid formation" is extremely narrow and one-sided. In particular, the search for information on volunteer education and the search for a socially-based education was conducted not only in the Bauman MSTU, but in Russia as a whole. However, the result was the portals of international student organizations with their own projects. Another example of a different interpretation of the "hybrid education" may be the assumption of quite axiologically new duties.Discussion and Conclusions: hybrid education is not limited to any temporal and territorial framework. It can manifest itself not only in the Internet-sphere, but also in the most diverse spheres of everyday life, with the interaction of various people and entire societies.

  16. PENERAPAN COOPERATIVE LEARNING TIPE JIGSAW UNTUK MENINGKATKAN PEMAHAMAN DAN KETERAMPILAN MAHASISWA

    Directory of Open Access Journals (Sweden)

    Rediana Setiani

    2009-06-01

    Full Text Available The objectives of this study are: (1 to improve students’ understanding in Accounting Computer subject mahasiswa pada mata kuliah Komputer Akuntansi, (2 to improve students’ skills in Accounting Computer subject. The subject of this research is accounting students of education program that take accounting computer subject. This research is class action research consists of  3 cycles. The given action in the first cycle according to the result of beginning reflection. In every cycle consists of 4 stages that are planning, actuating, observation, and reflection. This research reached standardized indicator that 70% students have minimum score that was 71 (B. It showed that the application of cooperative learning jigsaw type can improve the students’ ability in a computer accounting subject.   Key Words : Cooperative Learning, Jigsaw, the students’ understanding, creativity

  17. PENERAPAN COOPERATIVE LEARNING TIPE JIGSAW UNTUK MENINGKATKAN PEMAHAMAN DAN KETERAMPILAN MAHASISWA

    Directory of Open Access Journals (Sweden)

    Rediana Setiani

    2011-05-01

    Full Text Available The objectives of this study are: (1 to improve students’ understanding in Accounting Computer subject mahasiswa pada mata kuliah Komputer Akuntansi, (2 to improve students’ skills in Accounting Computer subject. The subject of this research is accounting students of education program that take accounting computer subject. This research is class action research consists of  3 cycles. The given action in the first cycle according to the result of beginning reflection. In every cycle consists of 4 stages that are planning, actuating, observation, and reflection. This research reached standardized indicator that 70% students have minimum score that was 71 (B. It showed that the application of cooperative learning jigsaw type can improve the students’ ability in a computer accounting subject.   Key Words : Cooperative Learning, Jigsaw, the students’ understanding, creativity

  18. A hybrid approach to simulate multiple photon scattering in X-ray imaging

    International Nuclear Information System (INIS)

    Freud, N.; Letang, J.-M.; Babot, D.

    2005-01-01

    A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or γ-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results

  19. A hybrid approach to simulate multiple photon scattering in X-ray imaging

    Energy Technology Data Exchange (ETDEWEB)

    Freud, N. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)]. E-mail: nicolas.freud@insa-lyon.fr; Letang, J.-M. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France); Babot, D. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)

    2005-01-01

    A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or {gamma}-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results.

  20. Pengaruh Metode Belajar Jigsaw Terhadap Keterampilan Hubungan Interpersonal dan Kerjasama Kelompok pada Mahasiswa Fakultas Psikologi

    Directory of Open Access Journals (Sweden)

    Asmadi Alsa

    2015-11-01

    Full Text Available This study aims to test the effect of cooperative learning methods, the jigsaw method to interpersonal relationship skill and teamwork of undergraduate students Faculty of Psychology in University A. This study used experimental method with one group and pre posttest design. There are 63 undergraduate students in Educational Psychology Class of 2008/2009 as the subjects. The measurement instrument was Interpersonal Relationship Skill Scale and Teamwork Scale. Interpersonal relationship and teamwork score compared before and after the learning methods were given and tested using paired samples t test. The result shows that comparing the pretest and posttest score of interpersonal relationship variable, we got t ‐1,748 with p = 0,043 (p < 0,05. This is indicated that jigsaw learning method has significant effect to improving the interpersonal relationship skill in undergraduate students. The analysis result in teamwork variable with comparing the pretest and posttest, we got t ‐3,50 with p = 0,001 (p < 0,01 which means the jigsaw learning method significantly effective to improving teamwork skill in undergraduate student

  1. E-LEARNING DENGAN PENDEKATAN KOOPERATIF TIPE JIGSAW UNTUK MENINGKATKAN AKTIVITAS DAN HASIL BELAJAR MAHASISWA

    Directory of Open Access Journals (Sweden)

    Partono Thomas

    2014-06-01

    Full Text Available Students in the first semester got difficulty to adapt the learning process in the university (student-oriented which are different with the senior high school (teacher-oriented. Thus, the lecturer needed to solve the problem to sharpen students’ independence by using Jigsaw, a cooperative learning. Then, e-learning was also an important factor to spread the knowledge widely to students. Thus; the combination of Jigsaw and e-learning was expected to improve students’ achievement. The subjects of the study were 40 Economics education students in bachelor degree (S1, Unnes in Curriculum Review class. The objective of the study was to minimize the mistake, improve the students’ interest and study result in understanding the concept of the Standard of National Education through independent learning strategy based on e-learning and cooperative learning of Jigsaw. The result of study showed that students’ activities, interest, attention, participation in discussion and presentation in the classroom increased significantly with the mean 4.14. Then, students’ test results increased from pre-test which was only 74 then rose to 79 in the 1st cycle and 81 in the 2nd cycle with the level of completeness was 87.5%. Furthermore, students thought that the strategy was very good with the score 4.12

  2. Meningkatkan Prestasi Pembelajaran Mata Kuliah Dasar-Dasar Pemasaran Global Melalui Metode Pembelajaran Koorperatif Tipe Jigsaw

    Directory of Open Access Journals (Sweden)

    Sri Wartini

    2007-06-01

    Full Text Available Conceptual learning will be more qualified if it is supported by an appropriate and good learning method system. To improve the achievement of students’ study result, it needs the  active students’ involvement  who want to think critically toward the real condition in the field. This class action research has an objective to prove that cooperative method, jigsaw type can be implemented in the learning process on each subject whose conceptual type. The subject of this research was Management Department students, Regular Class, 5th semester with the sum was 67 students who got Basics of Management Subject. This research consisted of 3 cycles and found out that the increase of average for pre test and post test score in cycle 1 was 15%, cycle 2 was 20% and cycle 3 was 25%. Whereas the difference of  average increase among cycles were on cycle 1 to cycle 2 was 5%, cycle 2 to cycle 3 was 10%. The finding means there is an increase of achievement on each cycle was 5%. It is appropriate to the hypothesis. Thus, it proved that cooperative learning method , jigsaw type can be applied well to Global Marketing Subject and finally it can improve the students’ learning achievement. Keywords: cooperative method, jigsaw type

  3. Meningkatkan Prestasi Pembelajaran Mata Kuliah Dasar-Dasar Pemasaran Global Melalui Metode Pembelajaran Koorperatif Tipe Jigsaw

    Directory of Open Access Journals (Sweden)

    Sri Wartini

    2011-06-01

    Full Text Available Conceptual learning will be more qualified if it is supported by an appropriate and good learning method system. To improve the achievement of students’ study result, it needs the  active students’ involvement  who want to think critically toward the real condition in the field. This class action research has an objective to prove that cooperative method, jigsaw type can be implemented in the learning process on each subject whose conceptual type. The subject of this research was Management Department students, Regular Class, 5th semester with the sum was 67 students who got Basics of Management Subject. This research consisted of 3 cycles and found out that the increase of average for pre test and post test score in cycle 1 was 15%, cycle 2 was 20% and cycle 3 was 25%. Whereas the difference of  average increase among cycles were on cycle 1 to cycle 2 was 5%, cycle 2 to cycle 3 was 10%. The finding means there is an increase of achievement on each cycle was 5%. It is appropriate to the hypothesis. Thus, it proved that cooperative learning method , jigsaw type can be applied well to Global Marketing Subject and finally it can improve the students’ learning achievement. Keywords: cooperative method, jigsaw type

  4. PENGARUH METODE KOOPERATIF JIGSAW TERHADAP PRESTASI BELAJAR MATA PELAJARAN IPS PADA SISWA KELAS III

    Directory of Open Access Journals (Sweden)

    Maya Kartika Sari

    2016-11-01

    Full Text Available This study aims to determine the effect of the use of cooperative learning of jigsaw method in social studies on student achievement of class III SD Pakualaman Bantul and SD Gandok Islamiyah in 2014/2015 school year. This research design uses quantitative research methods. Collecting data in this study uses the test method. The used test methods in this research are the pre-test and post-test given to the experimental group and the control group. While the data analysis is a statistical method t test (t-test.  The results of data analysis t test (t-test obtained value = 3.34. At the significance level (α = 0.05 and with db = 38 obtained value = 1.6859. So that is 3.34 ≥ 1.6859, therefore Ho is rejected H1 accepted. The conclusion of this study is that there is an effect on the use of cooperative learning of jigsaw model in social studies on student achievement of class III SD Islamiyah Pakualaman at school year 2014/2015.   Keywords: Cooperative Model Jigsaw Type, Learning Achievement

  5. A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid Wind Turbine Rotors

    Directory of Open Access Journals (Sweden)

    José F. Herbert-Acero

    2014-01-01

    Full Text Available This work presents a novel framework for the aerodynamic design and optimization of blades for small horizontal axis wind turbines (WT. The framework is based on a state-of-the-art blade element momentum model, which is complemented with the XFOIL 6.96 software in order to provide an estimate of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize the aerodynamic efficiency of small WT (SWT rotors for a wide range of operational conditions. The design variables are (1 the airfoil shape at the different blade span positions and the radial variation of the geometrical variables of (2 chord length, (3 twist angle, and (4 thickness along the blade span. A wind tunnel validation study of optimized rotors based on the NACA 4-digit airfoil series is presented. Based on the experimental data, improvements in terms of the aerodynamic efficiency, the cut-in wind speed, and the amount of material used during the manufacturing process were achieved. Recommendations for the aerodynamic design of SWT rotors are provided based on field experience.

  6. A Low Cost, Hybrid Approach to Data Mining, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed effort will combine a low cost physical modeling approach with inductive, data-centered modeling in an aerosopace relevant context to demonstrate...

  7. Hybrid Metaheuristic Approach for Nonlocal Optimization of Molecular Systems.

    Science.gov (United States)

    Dresselhaus, Thomas; Yang, Jack; Kumbhar, Sadhana; Waller, Mark P

    2013-04-09

    Accurate modeling of molecular systems requires a good knowledge of the structure; therefore, conformation searching/optimization is a routine necessity in computational chemistry. Here we present a hybrid metaheuristic optimization (HMO) algorithm, which combines ant colony optimization (ACO) and particle swarm optimization (PSO) for the optimization of molecular systems. The HMO implementation meta-optimizes the parameters of the ACO algorithm on-the-fly by the coupled PSO algorithm. The ACO parameters were optimized on a set of small difluorinated polyenes where the parameters exhibited small variance as the size of the molecule increased. The HMO algorithm was validated by searching for the closed form of around 100 molecular balances. Compared to the gradient-based optimized molecular balance structures, the HMO algorithm was able to find low-energy conformations with a 87% success rate. Finally, the computational effort for generating low-energy conformation(s) for the phenylalanyl-glycyl-glycine tripeptide was approximately 60 CPU hours with the ACO algorithm, in comparison to 4 CPU years required for an exhaustive brute-force calculation.

  8. A Hybrid Approach to Spatial Multiplexing in Multiuser MIMO Downlinks

    Directory of Open Access Journals (Sweden)

    Spencer Quentin H

    2004-01-01

    Full Text Available In the downlink of a multiuser multiple-input multiple-output (MIMO communication system, simultaneous transmission to several users requires joint optimization of the transmitted signals. Allowing all users to have multiple antennas adds an additional degree of complexity to the problem. In this paper, we examine the case where a single base station transmits to multiple users using linear processing (beamforming at each of the antenna arrays. We propose generalizations of several previous iterative algorithms for multiuser transmit beamforming that allow multiple antennas and multiple data streams for each user, and that take into account imperfect channel estimates at the transmitter. We then present a new hybrid algorithm that is based on coordinated transmit-receive beamforming, and combines the strengths of nonorthogonal iterative solutions with zero-forcing solutions. The problem of distributing power among the subchannels is solved by using standard bit-loading algorithms combined with the subchannel gains resulting from the zero-forcing solution. The result is a significant performance improvement over equal power distribution. At the same time, the number of iterations required to compute the final solution is reduced.

  9. Multi-level and hybrid modelling approaches for systems biology.

    Science.gov (United States)

    Bardini, R; Politano, G; Benso, A; Di Carlo, S

    2017-01-01

    During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

  10. A new approach to flow simulation using hybrid models

    Science.gov (United States)

    Solgi, Abazar; Zarei, Heidar; Nourani, Vahid; Bahmani, Ramin

    2017-11-01

    The necessity of flow prediction in rivers, for proper management of water resource, and the need for determining the inflow to the dam reservoir, designing efficient flood warning systems and so forth, have always led water researchers to think about models with high-speed response and low error. In the recent years, the development of Artificial Neural Networks and Wavelet theory and using the combination of models help researchers to estimate the river flow better and better. In this study, daily and monthly scales were used for simulating the flow of Gamasiyab River, Nahavand, Iran. The first simulation was done using two types of ANN and ANFIS models. Then, using wavelet theory and decomposing input signals of the used parameters, sub-signals were obtained and were fed into the ANN and ANFIS to obtain hybrid models of WANN and WANFIS. In this study, in addition to the parameters of precipitation and flow, parameters of temperature and evaporation were used to analyze their effects on the simulation. The results showed that using wavelet transform improved the performance of the models in both monthly and daily scale. However, it had a better effect on the monthly scale and the WANFIS was the best model.

  11. Hybrid Enhanced Epidermal SpaceSuit Design Approaches

    Science.gov (United States)

    Jessup, Joseph M.

    A Space suit that does not rely on gas pressurization is a multi-faceted problem that requires major stability controls to be incorporated during design and construction. The concept of Hybrid Epidermal Enhancement space suit integrates evolved human anthropomorphic and physiological adaptations into its functionality, using commercially available bio-medical technologies to address shortcomings of conventional gas pressure suits, and the impracticalities of MCP suits. The prototype HEE Space Suit explored integumentary homeostasis, thermal control and mobility using advanced bio-medical materials technology and construction concepts. The goal was a space suit that functions as an enhanced, multi-functional bio-mimic of the human epidermal layer that works in attunement with the wearer rather than as a separate system. In addressing human physiological requirements for design and construction of the HEE suit, testing regimes were devised and integrated into the prototype which was then subject to a series of detailed tests using both anatomical reproduction methods and human subject.

  12. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Science.gov (United States)

    Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin; Choo, Kim-Kwang Raymond

    2016-01-01

    To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO).

  13. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

    Directory of Open Access Journals (Sweden)

    Firdaus Afifi

    Full Text Available To deal with the large number of malicious mobile applications (e.g. mobile malware, a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS and particle swarm optimization (PSO. Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE and ant colony optimization (ANFIS-ACO.

  14. DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware

    Science.gov (United States)

    Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin

    2016-01-01

    To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO). PMID:27611312

  15. A hybrid clustering approach to recognition of protein families in 114 microbial genomes

    Directory of Open Access Journals (Sweden)

    Gogarten J Peter

    2004-04-01

    Full Text Available Abstract Background Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function. Standard clustering methods such as single-linkage clustering capture a history of cluster topologies as a function of threshold, but in practice their usefulness is limited because unrelated sequences join clusters before biologically meaningful families are fully constituted, e.g. as the result of matches to so-called promiscuous domains. Use of the Markov Cluster algorithm avoids this non-specificity, but does not preserve topological or threshold information about protein families. Results We describe a hybrid approach to sequence-based clustering of proteins that combines the advantages of standard and Markov clustering. We have implemented this hybrid approach over a relational database environment, and describe its application to clustering a large subset of PDB, and to 328577 proteins from 114 fully sequenced microbial genomes. To demonstrate utility with difficult problems, we show that hybrid clustering allows us to constitute the paralogous family of ATP synthase F1 rotary motor subunits into a single, biologically interpretable hierarchical grouping that was not accessible using either single-linkage or Markov clustering alone. We describe validation of this method by hybrid clustering of PDB and mapping SCOP families and domains onto the resulting clusters. Conclusion Hybrid (Markov followed by single-linkage clustering combines the advantages of the Markov Cluster algorithm (avoidance of non-specific clusters resulting from matches to promiscuous domains and single-linkage clustering (preservation of topological information as a function of threshold. Within the individual Markov clusters, single-linkage clustering is a more-precise instrument, discerning sub-clusters of biological relevance. Our hybrid approach thus provides a computationally efficient

  16. Molecular and morphological approaches for species delimitation and hybridization investigations of two Cichla species

    Directory of Open Access Journals (Sweden)

    Andrea A. F. Mourão

    Full Text Available ABSTRACT The hybridization is a widely-discussed issue in several studies with fish species. For some authors, hybridization may be related with diversification and speciation of several groups, or also with the extinction of populations or species. Difficulties to differentiate species and hybrids may be a problem to correctly apply a management of wild species, because hybrid lineages, especially the advanced ones, may resemble the parental species. The genus Cichla Bloch & Schneider, 1801 constitutes an interesting experimental model, considering that hybridization and taxonomic uncertainties hinder a correct identification. Considering these problems, in this study, we developed genetic methodologies and applied meristic and morphometric approaches in wild samples in order to identify species and for test a possible hybridization between Cichla kelberi Kullander & Ferreira, 2006 and Cichla piquiti Kullander & Ferreira, 2006. For this, C. kelberi, C. piquiti and potential hybrid ( carijó individuals were collected in Paraná and Tietê rivers (SP, Brazil. For meristic and morphometric methods, the individuals were analyzed using the statistical software Pcord 5:31, while for molecular methods, primers for PCR-multiplex were designed and enzyme for PCR-RFLP were selected, under the species-specific nucleotide. All results indicated that the carijó is not an interspecific hybrid, because it presented identical genetic pattern and morphology closed to C. piquiti. Thus, we propose that carijó is a C. piquiti morphotype. In addition, this study promotes a new molecular tool that could be used in future research, monitoring and management programs of the genus Cichla.

  17. A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

    Science.gov (United States)

    Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

    2017-12-01

    Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

  18. Bioenergy II. Biomass Valorisation by a Hybrid Thermochemical Fractionation Approach

    Energy Technology Data Exchange (ETDEWEB)

    De Wild, P.J.; Den Uil, H.; Reith, J.H. [ECN Biomass, Coal and Environmental Research, Petten (Netherlands); Lunshof, A.; Hendriks, C.; Van Eck, E. [Radboud University, Nijmegen (Netherlands); Heeres, E. [University of Groningen, Groningen (Netherlands)

    2009-11-15

    The need for green renewable sources is adamant because of the adverse effects of the increasing use of fossil fuels on our society. Biomass has been considered as a very attractive candidate for green energy carriers, chemicals and materials. The development of cheap and efficient fractionation technology to separate biomass into its main constituents is highly desirable. It enables treatment of each constituent separately, using dedicated conversion technologies to get specific target chemicals. The synergistic combination of aquathermolysis (hot pressurised water treatment) and pyrolysis (thermal degradation in the absence of oxygen) is a promising thermolysis option, integrating fractionation of biomass with production of valuable chemicals. Batch aquathermolysis in an autoclave and subsequent pyrolysis using bubbling fluidised bed reactor technology with beech, poplar, spruce and straw indicate the potential of this hybrid concept to valorise lignocellulosic biomass. Hemicellulose-derived furfural was obtained in yields that ranged from 2 wt% for spruce to 8 wt% for straw. Hydroxymethylfurfural from hemicellulose was obtained in yields from 0.3 wt% for poplar to 3 wt% for spruce. Pyrolysis of the aquathermolised biomass types resulted in 8 wt% (straw) to 11 wt% (spruce) of cellulose-derived levoglucosan. Next to the furfurals and levoglucosan, appreciable amounts of acetic acid were obtained as well from the aquathermolysis step, ranging from 1 wt% for spruce to 5 wt% for straw. To elucidate relations between the chemical changes occurring in the biomass during the integrated process and type and amount of the chemical products formed, a 13C-solid state NMR study has been conducted. Main conclusions are that aquathermolysis results in hemicellulose degradation to lower molecular weight components. Lignin ether bonds are broken, but apart from that, lignin is hardly affected by the aquathermolysis. Cellulose is also retained, although it seems to become more

  19. Statistical comparison of a hybrid approach with approximate and exact inference models for Fusion 2+

    Science.gov (United States)

    Lee, K. David; Wiesenfeld, Eric; Gelfand, Andrew

    2007-04-01

    One of the greatest challenges in modern combat is maintaining a high level of timely Situational Awareness (SA). In many situations, computational complexity and accuracy considerations make the development and deployment of real-time, high-level inference tools very difficult. An innovative hybrid framework that combines Bayesian inference, in the form of Bayesian Networks, and Possibility Theory, in the form of Fuzzy Logic systems, has recently been introduced to provide a rigorous framework for high-level inference. In previous research, the theoretical basis and benefits of the hybrid approach have been developed. However, lacking is a concrete experimental comparison of the hybrid framework with traditional fusion methods, to demonstrate and quantify this benefit. The goal of this research, therefore, is to provide a statistical analysis on the comparison of the accuracy and performance of hybrid network theory, with pure Bayesian and Fuzzy systems and an inexact Bayesian system approximated using Particle Filtering. To accomplish this task, domain specific models will be developed under these different theoretical approaches and then evaluated, via Monte Carlo Simulation, in comparison to situational ground truth to measure accuracy and fidelity. Following this, a rigorous statistical analysis of the performance results will be performed, to quantify the benefit of hybrid inference to other fusion tools.

  20. The business case for condition-based maintenance: a hybrid (non-) financial approach

    NARCIS (Netherlands)

    Tiddens, W.W.; Tinga, T.; Braaksma, A.J.J.; Brouwer, O.; Cepin, Marko; Bris, Radim

    2017-01-01

    Although developing business cases is key for evaluating project success, the costs and benefits of condition-based maintenance (CBM) implementations are often not explicitly defined and evaluated. Using the design science methodology, we developed a hybrid business case approach to help managers

  1. A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

  2. Students' Game Performance Improvements during a Hybrid Sport Education-Step-Game-Approach Volleyball Unit

    Science.gov (United States)

    Araújo, Rui; Mesquita, Isabel; Hastie, Peter; Pereira, Cristiana

    2016-01-01

    The purpose of this study was to examine a hybrid combination of sport education and the step-game-approach (SGA) on students' gameplay performance in volleyball, taking into account their sex and skill-level. Seventeen seventh-grade students (seven girls, 10 boys, average age 11.8) participated in a 25-lesson volleyball season, in which the…

  3. A hybrid approach to decision making and information fusion: Combining humans and artificial agents

    NARCIS (Netherlands)

    Groen, Frans C.A.; Pavlin, Gregor; Winterboer, Andi; Evers, Vanessa

    This paper argues that hybrid human–agent systems can support powerful solutions to relevant problems such as Environmental Crisis management. However, it shows that such solutions require comprehensive approaches covering different aspects of data processing, model construction and the usage. In

  4. TwitterNEED: a hybrid approach for named entity extraction and disambiguation for tweets

    NARCIS (Netherlands)

    Habib, Mena Badieh; van Keulen, Maurice

    Twitter is a rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing tasks. In this paper, we present TwitterNEED, a hybrid approach for Named Entity Extraction and Named Entity Disambiguation for tweets. We

  5. A hybrid system approach to airspeed, angle of attack and sideslip estimation in Unmanned Aerial Vehicles

    KAUST Repository

    Shaqura, Mohammad; Claudel, Christian

    2015-01-01

    , low power autopilots in real-time. The computational method is based on a hybrid decomposition of the modes of operation of the UAV. A Bayesian approach is considered for estimation, in which the estimated airspeed, angle of attack and sideslip

  6. A Hybrid Approach to Processing Big Data Graphs on Memory-Restricted Systems

    KAUST Repository

    Harshvardhan,; West, Brandon; Fidel, Adam; Amato, Nancy M.; Rauchwerger, Lawrence

    2015-01-01

    that sacrifice performance. In this work, we propose a novel RAM-Disk hybrid approach to graph processing that can scale well from a single shared-memory node to large distributed-memory systems. It works by partitioning the graph into sub graphs that fit in RAM

  7. A hybrid linked data approach to support asset management

    NARCIS (Netherlands)

    Luiten, G.T.; Bohms, H.M.; O'Keeffe, A.; Nederveen, S. van; Bakker, J.; Wikstrom, L.

    2016-01-01

    This paper evaluates experiences with applying a linked data approach for coping with the many challenges for information management in asset management from the perspective of National Road Authorities (NRAs). As influential players, NRAs are often the initiators of innovation in the civil

  8. Use of Jigsaw Technique to Teach the Unit "Science within Time" in Secondary 7th Grade Social Sciences Course and Students' Views on This Technique

    Science.gov (United States)

    Yapici, Hakki

    2016-01-01

    The aim of this study is to apply the jigsaw technique in Social Sciences teaching and to unroll the effects of this technique on learning. The unit "Science within Time" in the secondary 7th grade Social Sciences text book was chosen for the research. It is aimed to compare the jigsaw technique with the traditional teaching method in…

  9. Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

    Science.gov (United States)

    Chiadamrong, N.; Piyathanavong, V.

    2017-12-01

    Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

  10. Restraining approach for the spurious kinematic modes in hybrid equilibrium element

    Science.gov (United States)

    Parrinello, F.

    2013-10-01

    The present paper proposes a rigorous approach for the elimination of spurious kinematic modes in hybrid equilibrium elements, for three well known mesh patches. The approach is based on the identification of the dependent equations in the set of inter-element and boundary equilibrium equations of the sides involved in the spurious kinematic mode. Then the kinematic variables related to the dependent equations are reciprocally constrained and, by application of master slave elimination method, the set of inter-element equilibrium equations is reduced to full rank. The elastic solutions produced by means of the proposed approach verify the homogeneous, the inter-element and the boundary equilibrium equations. Hybrid stress formulation is developed in a rigorous mathematical setting. The results of linear elastic analysis obtained by the proposed approach and by classical displacement based method are compared for some structural examples.

  11. A Hybrid approach for aeroacoustic analysis of the engine exhaust system

    OpenAIRE

    Sathyanarayana, Y; Munjal, ML

    2000-01-01

    This paper presents a new hybrid approach for prediction of noise radiation from engine exhaust systems. It couples the time domain analysis of the engine and the frequency domain analysis of the muffler, and has the advantages of both. In this approach, cylinder/cavity is analyzed in the time domain to calculate the exhaust mass flux history at the exhaust valve by means of the method of characteristics, avoiding the tedious procedure of interpolation at every mesh point and solving a number...

  12. Unilateral robotic hybrid mini-maze: a novel experimental approach.

    Science.gov (United States)

    Moslemi, Mohammad; Rawashdeh, Badi; Meyer, Mark; Nguyen, Duy; Poston, Robert; Gharagozloo, Farid

    2016-03-01

    A complete Cox maze IV procedure is difficult to accomplish using current endoscopic and minimally invasive techniques. These techniques are hampered by inability to adequately dissect the posterior structures of the heart and place all necessary lesions. We present a novel approach, using robotic technology, that achieves placement of all the lesions of the complete maze procedure. In three cadaveric human models, the technical feasibility of using robotic instruments through the right chest to dissect the posterior structures of the heart and place all Cox maze lesions was performed. The entire posterior aspect of the heart was dissected in the cadaveric model facilitating successful placement of all Cox maze IV lesions with robotic assistance through minimally invasive incisions. The robotic Cox maze IV procedure through the novel right thoracic approach is feasible. This obviates the need for sternotomy and avoids the associated morbidity of the conventional Cox-maze procedure. Copyright © 2015 John Wiley & Sons, Ltd.

  13. The evolution of green jobs in Scotland: A hybrid approach

    International Nuclear Information System (INIS)

    Connolly, Kevin; Allan, Grant J; McIntyre, Stuart G

    2016-01-01

    In support of its ambitious target to reduce CO_2 emissions the Scottish Government is aiming to have the equivalent of 100% of Scottish electricity consumption generated from renewable sources by 2020. This is, at least in part, motivated by an expectation of subsequent employment growth in low carbon and renewable energy technologies; however there is no official data source to track employment in these areas. This has led to a variety of definitions, methodologies and alternative estimates being produced. Building on a recent study (Bishop and Brand, 2013) we develop a “hybrid” approach which combines the detail of “bottom-up” surveys with “top-down” trend data to produce estimates on employment in Low Carbon Environmental Goods and Services (LCEGS). We demonstrate this methodology to produce estimates for such employment in Scotland between 2004 and 2012. Our approach shows how survey and official sources can combine to produce a more timely measure of employment in LCEGS activities, assisting policymakers in tracking, consistently, developments. Applying our approach, we find that over this period employment in LCEGS in Scotland grew, but that this was more volatile than aggregate employment, and in particular that employment in this sector was particularly badly hit during the great recession. - Highlights: • A “hybrid” approach estimates green jobs from bottom-up detail and top-down data. • Illustrative results show the evolution of such jobs in Scotland from 2004 to 2012. • Method provides policymakers a timely measure of the jobs success of energy policy.

  14. Hybrid approaches to nanometer-scale patterning: Exploiting tailored intermolecular interactions

    International Nuclear Information System (INIS)

    Mullen, Thomas J.; Srinivasan, Charan; Shuster, Mitchell J.; Horn, Mark W.; Andrews, Anne M.; Weiss, Paul S.

    2008-01-01

    In this perspective, we explore hybrid approaches to nanometer-scale patterning, where the precision of molecular self-assembly is combined with the sophistication and fidelity of lithography. Two areas - improving existing lithographic techniques through self-assembly and fabricating chemically patterned surfaces - will be discussed in terms of their advantages, limitations, applications, and future outlook. The creation of such chemical patterns enables new capabilities, including the assembly of biospecific surfaces to be recognized by, and to capture analytes from, complex mixtures. Finally, we speculate on the potential impact and upcoming challenges of these hybrid strategies.

  15. A hybrid, coupled approach for modeling charged fluids from the nano to the mesoscale

    Science.gov (United States)

    Cheung, James; Frischknecht, Amalie L.; Perego, Mauro; Bochev, Pavel

    2017-11-01

    We develop and demonstrate a new, hybrid simulation approach for charged fluids, which combines the accuracy of the nonlocal, classical density functional theory (cDFT) with the efficiency of the Poisson-Nernst-Planck (PNP) equations. The approach is motivated by the fact that the more accurate description of the physics in the cDFT model is required only near the charged surfaces, while away from these regions the PNP equations provide an acceptable representation of the ionic system. We formulate the hybrid approach in two stages. The first stage defines a coupled hybrid model in which the PNP and cDFT equations act independently on two overlapping domains, subject to suitable interface coupling conditions. At the second stage we apply the principles of the alternating Schwarz method to the hybrid model by using the interface conditions to define the appropriate boundary conditions and volume constraints exchanged between the PNP and the cDFT subdomains. Numerical examples with two representative examples of ionic systems demonstrate the numerical properties of the method and its potential to reduce the computational cost of a full cDFT calculation, while retaining the accuracy of the latter near the charged surfaces.

  16. Numerical schemes for the hybrid modeling approach of gas-particle turbulent flows

    International Nuclear Information System (INIS)

    Dorogan, K.

    2012-01-01

    Hybrid Moments/PDF methods have shown to be well suitable for the description of poly-dispersed turbulent two-phase flows in non-equilibrium which are encountered in some industrial situations involving chemical reactions, combustion or sprays. They allow to obtain a fine enough physical description of the poly-dispersity, non-linear source terms and convection phenomena. However, their approximations are noised with the statistical error, which in several situations may be a source of a bias. An alternative hybrid Moments-Moments/PDF approach examined in this work consists in coupling the Moments and the PDF descriptions, within the description of the dispersed phase itself. This hybrid method could reduce the statistical error and remove the bias. However, such a coupling is not straightforward in practice and requires the development of accurate and stable numerical schemes. The approaches introduced in this work rely on the combined use of the up-winding and relaxation-type techniques. They allow to obtain stable unsteady approximations for a system of partial differential equations containing non-smooth external data which are provided by the PDF part of the model. A comparison of the results obtained using the present method with those of the 'classical' hybrid approach is presented in terms of the numerical errors for a case of a co-current gas-particle wall jet. (author)

  17. Entity recognition in the biomedical domain using a hybrid approach.

    Science.gov (United States)

    Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

    2017-11-09

    This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

  18. A bottom-up approach for the synthesis of highly ordered fullerene-intercalated graphene hybrids

    Directory of Open Access Journals (Sweden)

    Dimitrios eGournis

    2015-02-01

    Full Text Available Much of the research effort on graphene focuses on its use as a building block for the development of new hybrid nanostructures with well-defined dimensions and properties suitable for applications such as gas storage, heterogeneous catalysis, gas/liquid separations, nanosensing and biomedicine. Towards this aim, here we describe a new bottom-up approach, which combines self-assembly with the Langmuir Schaefer deposition technique to synthesize graphene-based layered hybrid materials hosting fullerene molecules within the interlayer space. Our film preparation consists in a bottom-up layer-by-layer process that proceeds via the formation of a hybrid organo-graphene oxide Langmuir film. The structure and composition of these hybrid fullerene-containing thin multilayers deposited on hydrophobic substrates were characterized by a combination of X-ray diffraction, Raman and X-ray photoelectron spectroscopies, atomic force microscopy and conductivity measurements. The latter revealed that the presence of C60 within the interlayer spacing leads to an increase in electrical conductivity of the hybrid material as compared to the organo-graphene matrix alone.

  19. A hybrid approach to device integration on a genetic analysis platform

    International Nuclear Information System (INIS)

    Brennan, Des; Justice, John; Aherne, Margaret; Galvin, Paul; Jary, Dorothee; Kurg, Ants; Berik, Evgeny; Macek, Milan

    2012-01-01

    Point-of-care (POC) systems require significant component integration to implement biochemical protocols associated with molecular diagnostic assays. Hybrid platforms where discrete components are combined in a single platform are a suitable approach to integration, where combining multiple device fabrication steps on a single substrate is not possible due to incompatible or costly fabrication steps. We integrate three devices each with a specific system functionality: (i) a silicon electro-wetting-on-dielectric (EWOD) device to move and mix sample and reagent droplets in an oil phase, (ii) a polymer microfluidic chip containing channels and reservoirs and (iii) an aqueous phase glass microarray for fluorescence microarray hybridization detection. The EWOD device offers the possibility of fully integrating on-chip sample preparation using nanolitre sample and reagent volumes. A key challenge is sample transfer from the oil phase EWOD device to the aqueous phase microarray for hybridization detection. The EWOD device, waveguide performance and functionality are maintained during the integration process. An on-chip biochemical protocol for arrayed primer extension (APEX) was implemented for single nucleotide polymorphism (SNiP) analysis. The prepared sample is aspirated from the EWOD oil phase to the aqueous phase microarray for hybridization. A bench-top instrumentation system was also developed around the integrated platform to drive the EWOD electrodes, implement APEX sample heating and image the microarray after hybridization. (paper)

  20. New MPPT algorithm for PV applications based on hybrid dynamical approach

    KAUST Repository

    Elmetennani, Shahrazed

    2016-10-24

    This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

  1. Mixed H∞ and passive control for linear switched systems via hybrid control approach

    Science.gov (United States)

    Zheng, Qunxian; Ling, Youzhu; Wei, Lisheng; Zhang, Hongbin

    2018-03-01

    This paper investigates the mixed H∞ and passive control problem for linear switched systems based on a hybrid control strategy. To solve this problem, first, a new performance index is proposed. This performance index can be viewed as the mixed weighted H∞ and passivity performance. Then, the hybrid controllers are used to stabilise the switched systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. The design of state updating controllers not only depends on the pre-switching subsystem and the post-switching subsystem, but also depends on the measurable output signal. The hybrid controllers proposed in this paper can include some existing ones as special cases. Combine the multiple Lyapunov functions approach with the average dwell time technique, new sufficient conditions are obtained. Under the new conditions, the closed-loop linear switched systems are globally uniformly asymptotically stable with a mixed H∞ and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example and a practical example are given.

  2. Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach

    Directory of Open Access Journals (Sweden)

    Oliveira Rui

    2010-09-01

    Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.

  3. New MPPT algorithm for PV applications based on hybrid dynamical approach

    KAUST Repository

    Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem; Djemai, M.; Tadjine, M.

    2016-01-01

    This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

  4. A Hybrid Harmony Search Algorithm Approach for Optimal Power Flow

    Directory of Open Access Journals (Sweden)

    Mimoun YOUNES

    2012-08-01

    Full Text Available Optimal Power Flow (OPF is one of the main functions of Power system operation. It determines the optimal settings of generating units, bus voltage, transformer tap and shunt elements in Power System with the objective of minimizing total production costs or losses while the system is operating within its security limits. The aim of this paper is to propose a novel methodology (BCGAs-HSA that solves OPF including both active and reactive power dispatch It is based on combining the binary-coded genetic algorithm (BCGAs and the harmony search algorithm (HSA to determine the optimal global solution. This method was tested on the modified IEEE 30 bus test system. The results obtained by this method are compared with those obtained with BCGAs or HSA separately. The results show that the BCGAs-HSA approach can converge to the optimum solution with accuracy compared to those reported recently in the literature.

  5. PENGEMBANGAN MODEL KOLABORASI JIGSAW ROLE PLAYING SEBAGAI UPAYA PENINGKATAN KEMAMPUAN BEKERJASAMA SISWA KELAS V SD PADA PELAJARAN IPS

    Directory of Open Access Journals (Sweden)

    Ika Ari Pratiwi

    2015-11-01

    Full Text Available Penelitian bertujuan untuk mengembangkan model kolaborasi jigsaw, role playing untuk meningkatkan kemampuan bekerjasama siswa yang valid, efektif dan praktis. Metode penelitian adalah penelitian dan pengembangan (R&D. Tahap uji coba pengembangan terdiri atas uji coba ahli, uji coba skala terbatas dan uji coba skala luas. Keefektifan model kolaborasi jigsaw role playing  diperoleh rata-rata 51,83 dalam kategori baik diterapkan dalam pelajaran IPS, peningkatan kemampuan bekerjasama siswa hasil N-gain = 0,56 dengan kategori sedang, peningkatan hasil belajar IPS N-gain = 0,50 dengan kategori sedang dan hasil ketuntasan klasikal pembelajaran IPS 97,14%.  Hasil respon guru dan siswa terhadap model yang digunakan adalah berkriteria baik. Model final penelitian ini menghasilkan model kolaborasi jigsaw role playing yang dikemas dalam suatu buku pedoman.

  6. NBI - plasma vaporization hybrid approach in bladder cancer endoscopic management.

    Science.gov (United States)

    Stănescu, F; Geavlete, B; Georgescu, D; Jecu, M; Moldoveanu, C; Adou, L; Bulai, C; Ene, C; Geavlete, P

    2014-06-15

    A prospective study was performed aiming to evaluate the surgical efficacy, perioperative safety profile, diagnostic accuracy and medium term results of a multi-modal approach consisting in narrow band imaging (NBI) cystoscopy and bipolar plasma vaporization (BPV) when compared to the standard protocol represented by white light cystoscopy (WLC) and transurethral resection of bladder tumors (TURBT). A total of 260 patients with apparently at least one bladder tumor over 3 cm were included in the trial. In the first group, 130 patients underwent conventional and NBI cystoscopy followed by BPV, while in a similar number of cases of the second arm, classical WLC and TURBT were applied. In all non-muscle invasive bladder tumors' (NMIBT) pathologically confirmed cases, standard monopolar Re-TUR was performed at 4-6 weeks after the initial intervention, followed by one year' BCG immunotherapy. The follow-up protocol included abdominal ultrasound, urinary cytology and WLC, performed every 3 months for a period of 2 years. The obturator nerve stimulation, bladder wall perforation, mean hemoglobin level drop, postoperative bleeding, catheterization period and hospital stay were significantly reduced for the plasma vaporization technique by comparison to conventional resection. Concerning tumoral detection, the present data confirmed the NBI superiority when compared to standard WLC regardless of tumor stage (95.3% vs. 65.1% for CIS, 93.3% vs. 82.2% for pTa, 97.4% vs. 94% for pT1, 95% vs. 84.2% overall). During standard Re-TUR the overall (6.3% versus 17.4%) and primary site (3.6% versus 12.8%) residual tumors' rates were significantly lower for the NBI-BPV group. The 1 (7.2% versus 18.3%) and 2 (11.5% versus 25.8%) years' recurrence rates were substantially lower for the combined approach. NBI cystoscopy significantly improved diagnostic accuracy, while bipolar technology showed a higher surgical efficiency, lower morbidity and faster postoperative recovery. The combined

  7. Hybrid empirical--theoretical approach to modeling uranium adsorption

    International Nuclear Information System (INIS)

    Hull, Larry C.; Grossman, Christopher; Fjeld, Robert A.; Coates, John T.; Elzerman, Alan W.

    2004-01-01

    An estimated 330 metric tons of U are buried in the radioactive waste Subsurface Disposal Area (SDA) at the Idaho National Engineering and Environmental Laboratory (INEEL). An assessment of U transport parameters is being performed to decrease the uncertainty in risk and dose predictions derived from computer simulations of U fate and transport to the underlying Snake River Plain Aquifer. Uranium adsorption isotherms were measured for 14 sediment samples collected from sedimentary interbeds underlying the SDA. The adsorption data were fit with a Freundlich isotherm. The Freundlich n parameter is statistically identical for all 14 sediment samples and the Freundlich K f parameter is correlated to sediment surface area (r 2 =0.80). These findings suggest an efficient approach to material characterization and implementation of a spatially variable reactive transport model that requires only the measurement of sediment surface area. To expand the potential applicability of the measured isotherms, a model is derived from the empirical observations by incorporating concepts from surface complexation theory to account for the effects of solution chemistry. The resulting model is then used to predict the range of adsorption conditions to be expected in the vadose zone at the SDA based on the range in measured pore water chemistry. Adsorption in the deep vadose zone is predicted to be stronger than in near-surface sediments because the total dissolved carbonate decreases with depth

  8. Hybrid modeling approach to improve the forecasting capability for the gaseous radionuclide in a nuclear site

    International Nuclear Information System (INIS)

    Jeong, Hyojoon; Hwang, Wontae; Kim, Eunhan; Han, Moonhee

    2012-01-01

    Highlights: ► This study is to improve the reliability of air dispersion modeling. ► Tracer experiments assumed gaseous radionuclides were conducted at a nuclear site. ► The performance of a hybrid modeling combined ISC with ANFIS was investigated.. ► Hybrid modeling approach shows better performance rather than a single ISC model. - Abstract: Predicted air concentrations of radioactive materials are important for an environmental impact assessment for the public health. In this study, the performance of a hybrid modeling combined with the industrial source complex (ISC) model and an adaptive neuro-fuzzy inference system (ANFIS) for predicting tracer concentrations was investigated. Tracer dispersion experiments were performed to produce the field data assuming the accidental release of radioactive material. ANFIS was trained in order that the outputs of the ISC model are similar to the measured data. Judging from the higher correlation coefficients between the measured and the calculated ones, the hybrid modeling approach could be an appropriate technique for an improvement of the modeling capability to predict the air concentrations for radioactive materials.

  9. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    International Nuclear Information System (INIS)

    Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

    2011-01-01

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

  10. A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

    Energy Technology Data Exchange (ETDEWEB)

    Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

    2011-01-15

    The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

  11. Advanced control approach for hybrid systems based on solid oxide fuel cells

    International Nuclear Information System (INIS)

    Ferrari, Mario L.

    2015-01-01

    Highlights: • Advanced new control system for SOFC based hybrid plants. • Proportional–Integral approach with feed-forward technology. • Good control of fuel cell temperature. • All critical properties maintained inside safe conditions. - Abstract: This paper shows a new advanced control approach for operations in hybrid systems equipped with solid oxide fuel cell technology. This new tool, which combines feed-forward and standard proportional–integral techniques, controls the system during load changes avoiding failures and stress conditions detrimental to component life. This approach was selected to combine simplicity and good control performance. Moreover, the new approach presented in this paper eliminates the need for mass flow rate meters and other expensive probes, as usually required for a commercial plant. Compared to previous works, better performance is achieved in controlling fuel cell temperature (maximum gradient significantly lower than 3 K/min), reducing the pressure gap between cathode and anode sides (at least a 30% decrease during transient operations), and generating a higher safe margin (at least a 10% increase) for the Steam-to-Carbon Ratio. This new control system was developed and optimized using a hybrid system transient model implemented, validated and tested within previous works. The plant, comprising the coupling of a tubular solid oxide fuel cell stack with a microturbine, is equipped with a bypass valve able to connect the compressor outlet with the turbine inlet duct for rotational speed control. Following model development and tuning activities, several operative conditions were considered to show the new control system increased performance compared to previous tools (the same hybrid system model was used with the new control approach). Special attention was devoted to electrical load steps and ramps considering significant changes in ambient conditions

  12. Hybrid Approach of Aortic Diseases: Zone 1 Delivery and Volumetric Analysis on the Descending Aorta

    Directory of Open Access Journals (Sweden)

    José Augusto Duncan

    Full Text Available Abstract Introduction: Conventional techniques of surgical correction of arch and descending aortic diseases remains as high-risk procedures. Endovascular treatments of abdominal and descending thoracic aorta have lower surgical risk. Evolution of both techniques - open debranching of the arch and endovascular approach of the descending aorta - may extend a less invasive endovascular treatment for a more extensive disease with necessity of proximal landing zone in the arch. Objective: To evaluate descending thoracic aortic remodeling by means of volumetric analysis after hybrid approach of aortic arch debranching and stenting the descending aorta. Methods: Retrospective review of seven consecutive patients treated between September 2014 and August 2016 for diseases of proximal descending aorta (aneurysms and dissections by hybrid approach to deliver the endograft at zone 1. Computed tomography angiography were analyzed using a specific software to calculate descending thoracic aorta volumes pre- and postoperatively. Results: Follow-up was done in 100% of patients with a median time of 321 days (range, 41-625 days. No deaths or permanent neurological complications were observed. There were no endoleaks or stent migrations. Freedom from reintervention was 100% at 300 days and 66% at 600 days. Median volume reduction was of 45.5 cm3, representing a median volume shrinkage by 9.3%. Conclusion: Hybrid approach of arch and descending thoracic aorta diseases is feasible and leads to a favorable aortic remodeling with significant volume reduction.

  13. Does the acceptance of hybrid learning affect learning approaches in France?

    Science.gov (United States)

    Marco, Lionel Di; Venot, Alain; Gillois, Pierre

    2017-01-01

    Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (Paffected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.

  14. Hourly forecasting of global solar radiation based on multiscale decomposition methods: A hybrid approach

    International Nuclear Information System (INIS)

    Monjoly, Stéphanie; André, Maïna; Calif, Rudy; Soubdhan, Ted

    2017-01-01

    This paper introduces a new approach for the forecasting of solar radiation series at 1 h ahead. We investigated on several techniques of multiscale decomposition of clear sky index K_c data such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) and Wavelet Decomposition. From these differents methods, we built 11 decomposition components and 1 residu signal presenting different time scales. We performed classic forecasting models based on linear method (Autoregressive process AR) and a non linear method (Neural Network model). The choice of forecasting method is adaptative on the characteristic of each component. Hence, we proposed a modeling process which is built from a hybrid structure according to the defined flowchart. An analysis of predictive performances for solar forecasting from the different multiscale decompositions and forecast models is presented. From multiscale decomposition, the solar forecast accuracy is significantly improved, particularly using the wavelet decomposition method. Moreover, multistep forecasting with the proposed hybrid method resulted in additional improvement. For example, in terms of RMSE error, the obtained forecasting with the classical NN model is about 25.86%, this error decrease to 16.91% with the EMD-Hybrid Model, 14.06% with the EEMD-Hybid model and to 7.86% with the WD-Hybrid Model. - Highlights: • Hourly forecasting of GHI in tropical climate with many cloud formation processes. • Clear sky Index decomposition using three multiscale decomposition methods. • Combination of multiscale decomposition methods with AR-NN models to predict GHI. • Comparison of the proposed hybrid model with the classical models (AR, NN). • Best results using Wavelet-Hybrid model in comparison with classical models.

  15. Integrated approach for fusion multi-physics coupled analyses based on hybrid CAD and mesh geometries

    Energy Technology Data Exchange (ETDEWEB)

    Qiu, Yuefeng, E-mail: yuefeng.qiu@kit.edu; Lu, Lei; Fischer, Ulrich

    2015-10-15

    Highlights: • Integrated approach for neutronics, thermal and structural analyses was developed. • MCNP5/6, TRIPOLI-4 were coupled with CFX, Fluent and ANSYS Workbench. • A novel meshing approach has been proposed for describing MC geometry. - Abstract: Coupled multi-physics analyses on fusion reactor devices require high-fidelity neutronic models, and flexible, accurate data exchanging between various calculation codes. An integrated coupling approach has been developed to enable the conversion of CAD, mesh, or hybrid geometries for Monte Carlo (MC) codes MCNP5/6, TRIPOLI-4, and translation of nuclear heating data for CFD codes Fluent, CFX and structural mechanical software ANSYS Workbench. The coupling approach has been implemented based on SALOME platform with CAD modeling, mesh generation and data visualization capabilities. A novel meshing approach has been developed for generating suitable meshes for MC geometry descriptions. The coupling approach has been concluded to be reliable and efficient after verification calculations of several application cases.

  16. A decision support system based on hybrid knowledge approach for nuclear power plant operation

    International Nuclear Information System (INIS)

    Yang, J.O.; Chang, S.H.

    1991-01-01

    This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. Frames and rules are adopted to represent the various knowledge types. Rule-based deduction and abduction are used for shallow and deep knowledge based reasoning respectively. The event-based operational guidelines are provided to the operator according to the diagnosed results

  17. A diagnostic expert system for NPP based on hybrid knowledge approach

    International Nuclear Information System (INIS)

    Yang, Joon On; Chang, Soon Heung

    1989-01-01

    This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem solving behavior modeled in HYPOSS. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies showed a good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

  18. Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

    Science.gov (United States)

    Wallace, Byron C; Noel-Storr, Anna; Marshall, Iain J; Cohen, Aaron M; Smalheiser, Neil R; Thomas, James

    2017-11-01

    Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML. We trained a classifier to discriminate between citations that describe RCTs and those that do not. We then adopted a simple strategy of automatically excluding citations deemed very unlikely to be RCTs by the classifier and deferring to crowdworkers otherwise. Combining ML and crowdsourcing provides a highly sensitive RCT identification strategy (our estimates suggest 95%-99% recall) with substantially less effort (we observed a reduction of around 60%-80%) than relying on manual screening alone. Hybrid crowd-ML strategies warrant further exploration for biomedical curation/annotation tasks. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  19. A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

    Science.gov (United States)

    Marzban, Hamid Reza

    2018-05-01

    In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.

  20. A Study on a Hybrid Approach for Diagnosing Faults in Nuclear Power Plant

    International Nuclear Information System (INIS)

    Yang, M.; Zhang, Z.J.; Peng, M.J.; Yan, S.Y.; Wang, H.; Ouyang, J.

    2006-01-01

    Proper and rapid identification of malfunctions is of premier importance for the safe operation of Nuclear Power Plants (NPP). Many monitoring or/and diagnosis methodologies based on artificial and computational intelligence have been proposed to aid operator to understand system problems, perform trouble-shooting action and reduce human error under serious pressure. However, because no single method is adequate to handle all requirements for diagnostic system, hybrid approaches where different methods work in conjunction to solve parts of the problem interest researchers greatly. In this study, Multilevel Flow Models (MFM) and Artificial Neural Network (ANN) are proposed and employed to develop a fault diagnosis system with the intention of improving the success rate of recognition on the one hand, and improving the understandability of diagnostic process and results on the other hand. Several simulation cases were conducted for evaluating the performance of the proposed diagnosis system. The simulation results validated the effectiveness of the proposed hybrid approach. (authors)

  1. Neuro-genetic hybrid approach for the solution of non-convex economic dispatch problem

    International Nuclear Information System (INIS)

    Malik, T.N.; Asar, A.U.

    2009-01-01

    ED (Economic Dispatch) is non-convex constrained optimization problem, and is used for both on line and offline studies in power system operation. Conventionally, it is solved as convex problem using optimization techniques by approximating generator input/output characteristic. Curves of monotonically increasing nature thus resulting in an inaccurate dispatch. The GA (Genetic Algorithm) has been used for the solution of this problem owing to its inherent ability to address the convex and non-convex problems equally. This approach brings the solution to the global minimum region of search space in a short time and then takes longer time to converge to near optimal results. GA based hybrid approaches are used to fine tune the near optimal results produced by GA. This paper proposes NGH (Neuro Genetic Hybrid) approach to solve the economic dispatch with valve point effect. The proposed approach combines the GA with the ANN (Artificial Neural Network) using SI (Swarm Intelligence) learning rule. The GA acts as a global optimizer and the neural network fine tunes the GA results to the desired targets. Three machines standard test system has been tested for validation of the approach. Comparing the results with GA and NGH model based on back-propagation learning, the proposed approach gives contrast improvements showing the promise of the approach. (author)

  2. A hybrid MCDM approach for ranking suppliers by considering ethical factors

    OpenAIRE

    Azadfallah, Mohammad

    2016-01-01

    One of the negative effects of cooperating with un-ethically behaving suppliers is that it may devastate the companies' credibility among employees, customers and the public. In this paper, a hybrid Multiple Criteria Decision Making (MCDM) approach (Disjunctive-WPM method) is proposed to resolve this limitation. The proposed methods consist of the following steps: 1. drop unethical solutions and 2. rank the remaining solutions. Therefore, the aim of t...

  3. Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

    OpenAIRE

    Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

    2015-01-01

    Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

  4. A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction

    Science.gov (United States)

    Benvenuto, Federico; Piana, Michele; Campi, Cristina; Massone, Anna Maria

    2018-01-01

    This paper introduces a novel method for flare forecasting, combining prediction accuracy with the ability to identify the most relevant predictive variables. This result is obtained by means of a two-step approach: first, a supervised regularization method for regression, namely, LASSO is applied, where a sparsity-enhancing penalty term allows the identification of the significance with which each data feature contributes to the prediction; then, an unsupervised fuzzy clustering technique for classification, namely, Fuzzy C-Means, is applied, where the regression outcome is partitioned through the minimization of a cost function and without focusing on the optimization of a specific skill score. This approach is therefore hybrid, since it combines supervised and unsupervised learning; realizes classification in an automatic, skill-score-independent way; and provides effective prediction performances even in the case of imbalanced data sets. Its prediction power is verified against NOAA Space Weather Prediction Center data, using as a test set, data in the range between 1996 August and 2010 December and as training set, data in the range between 1988 December and 1996 June. To validate the method, we computed several skill scores typically utilized in flare prediction and compared the values provided by the hybrid approach with the ones provided by several standard (non-hybrid) machine learning methods. The results showed that the hybrid approach performs classification better than all other supervised methods and with an effectiveness comparable to the one of clustering methods; but, in addition, it provides a reliable ranking of the weights with which the data properties contribute to the forecast.

  5. JIGSAW: Acquisition, Display and Analysis system designed to collect data from Multiple Gamma-Ray detectors

    International Nuclear Information System (INIS)

    Haywood, S.E.; Bamford, G.J.; Rester, A.C.; Coldwell, R.L.

    1992-01-01

    In this paper, the authors report on work performed to date on JIGSAW - a self contained data acquisition, display and analysis system designed to collect data form multiple gamma-ray detectors. The data acquisition system utilizes commercially available VMEbus and NIM hardware modules and the VME exec real time operating system. A Unix based software package, written in ANSI standard C and with the XII graphics routines, allows the user to view the acquired spectra. Analysis of the histograms can be performed in background during the run with the ROBFIT suite of curve fitting routines

  6. A Novel Combined Hybrid Approach to Enable Revascularisation of a Trauma-Induced Subclavian Artery Injury

    Directory of Open Access Journals (Sweden)

    C.N. Sabbagh

    Full Text Available : Introduction: This case highlights the complexity of upper limb revascularization after a subclavian artery traumatic injury and strengthens the role of a hybrid/multi-disciplinary approach to such injuries. Report: A 45-year-old male patient presented with an acute right upper limb following a traumatic injury to the right subclavian artery due to a motor vehicle accident (MVA. Associated injuries included an unstable cervical spine injury, a large open right clavicular injury, and a brain injury, which limited the potential revascularisation options available. The arm was revascularised using a hybrid endovascular/open surgical approach, namely embolization of the proximal subclavian artery (just distal to vertebral artery and a right common femoral artery to distal axillary artery bypass using prosthetic material. Discussion: Blunt injuries to the subclavian artery are often high impact, complex and associated with multiple injuries to surrounding structures, which limit the role of standard procedures used in the elective setting. This case highlights the role of multidisciplinary team involvement, using a hybrid approach and a novel distal inflow site to restore upper limb perfusion. Keywords: Upper limb, Ischemia, Trauma, Revascularization

  7. Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

    Science.gov (United States)

    Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

    2016-01-01

    Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

  8. A Hybrid Approach to Cognitive Engineering: Supporting Development of a Revolutionary Warfighter-Centered Command and Control System

    National Research Council Canada - National Science Library

    Ockerman, Jennifer; McKneely, Jennifer A; Koterba, Nathan

    2005-01-01

    ...) for the requirements analysis and design of revolutionary command and control systems and domains. This hybrid approach uses knowledge elicitation and representation techniques from several current cognitive engineering methodologies...

  9. A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

    Science.gov (United States)

    Oh, Yoo Rhee; Kim, Hong Kook

    In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

  10. A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

    Science.gov (United States)

    Dickman, Christopher T D; Moehring, Amanda J

    2013-01-01

    When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW) sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56%) of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

  11. A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

    Directory of Open Access Journals (Sweden)

    Christopher T D Dickman

    Full Text Available When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56% of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

  12. A hybrid simulation approach for integrating safety behavior into construction planning: An earthmoving case study.

    Science.gov (United States)

    Goh, Yang Miang; Askar Ali, Mohamed Jawad

    2016-08-01

    One of the key challenges in improving construction safety and health is the management of safety behavior. From a system point of view, workers work unsafely due to system level issues such as poor safety culture, excessive production pressure, inadequate allocation of resources and time and lack of training. These systemic issues should be eradicated or minimized during planning. However, there is a lack of detailed planning tools to help managers assess the impact of their upstream decisions on worker safety behavior. Even though simulation had been used in construction planning, the review conducted in this study showed that construction safety management research had not been exploiting the potential of simulation techniques. Thus, a hybrid simulation framework is proposed to facilitate integration of safety management considerations into construction activity simulation. The hybrid framework consists of discrete event simulation (DES) as the core, but heterogeneous, interactive and intelligent (able to make decisions) agents replace traditional entities and resources. In addition, some of the cognitive processes and physiological aspects of agents are captured using system dynamics (SD) approach. The combination of DES, agent-based simulation (ABS) and SD allows a more "natural" representation of the complex dynamics in construction activities. The proposed hybrid framework was demonstrated using a hypothetical case study. In addition, due to the lack of application of factorial experiment approach in safety management simulation, the case study demonstrated sensitivity analysis and factorial experiment to guide future research. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. A Gaussian process regression based hybrid approach for short-term wind speed prediction

    International Nuclear Information System (INIS)

    Zhang, Chi; Wei, Haikun; Zhao, Xin; Liu, Tianhong; Zhang, Kanjian

    2016-01-01

    Highlights: • A novel hybrid approach is proposed for short-term wind speed prediction. • This method combines the parametric AR model with the non-parametric GPR model. • The relative importance of different inputs is considered. • Different types of covariance functions are considered and combined. • It can provide both accurate point forecasts and satisfactory prediction intervals. - Abstract: This paper proposes a hybrid model based on autoregressive (AR) model and Gaussian process regression (GPR) for probabilistic wind speed forecasting. In the proposed approach, the AR model is employed to capture the overall structure from wind speed series, and the GPR is adopted to extract the local structure. Additionally, automatic relevance determination (ARD) is used to take into account the relative importance of different inputs, and different types of covariance functions are combined to capture the characteristics of the data. The proposed hybrid model is compared with the persistence model, artificial neural network (ANN), and support vector machine (SVM) for one-step ahead forecasting, using wind speed data collected from three wind farms in China. The forecasting results indicate that the proposed method can not only improve point forecasts compared with other methods, but also generate satisfactory prediction intervals.

  14. Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

    Science.gov (United States)

    Koeppen, W. C.; Pilger, E.; Wright, R.

    2011-07-01

    We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

  15. Effect of Jigsaw II, Reading-Writing-Presentation, and Computer Animations on the Teaching of "Light" Unit

    Science.gov (United States)

    Koç, Yasemin; Yildiz, Emre; Çaliklar, Seyma; Simsek, Ümit

    2016-01-01

    The aim of this study is to determine the effect of Jigsaw II technique, reading-writing-presentation method, and computer animation on students' academic achievements, epistemological beliefs, attitudes towards science lesson, and the retention of knowledge in the "Light" unit covered in the 7th grade. The sample of the study consists…

  16. Having Fun and Accepting Challenges Are Natural Instincts: Jigsaw Puzzles to Challenge Students and Test Their Abilities While Having Fun!

    Science.gov (United States)

    Rodenbaugh, Hanna R.; Lujan, Heidi L.; Rodenbaugh, David W.; DiCarlo, Stephen E.

    2014-01-01

    Because jigsaw puzzles are fun, and challenging, students will endure and discover that persistence and grit are rewarded. Importantly, play and fun have a biological place just like sleep and dreams. Students also feel a sense of accomplishment when they have completed a puzzle. Importantly, the reward of mastering a challenge builds confidence…

  17. The Effects of Using Jigsaw Method Based on Cooperative Learning Model in the Undergraduate Science Laboratory Practices

    Science.gov (United States)

    Karacop, Ataman

    2017-01-01

    The main aim of the present study is to determine the influence of a Jigsaw method based on cooperative learning and a confirmatory laboratory method on prospective science teachers' achievements of physics in science teaching laboratory practice courses. The sample of this study consisted of 33 female and 15 male third-grade prospective science…

  18. Meningkatkan Hasil Belajar Matematika Melalui Model Pembelajaran Kooperatif Tipe Jigsaw pada Siswa SMP

    Directory of Open Access Journals (Sweden)

    Nasruddin Nasruddin

    2017-08-01

    Full Text Available In this study, we discuss about Jigsaw type cooperative learning model to improve mathematics learning outcomes on the basic competence of cubes and beams of students of class VIIIA SMP. This research is a Classroom Action Research (CAR conducted in SMPN 2 Lasusua Year Learning 2016/2017 even semester. This study uses two cycles, each cycle has procedures such as planning, action, observation and reflection. The results of this study indicate the implementation of cooperative learning model jigsaw type can improve student learning outcomes in mathematics subjects. The value after the first cycle action increased compared with the initial test of 45,85 to 65,75. Furthermore the average score of students after the second cycle action increased compared with the average score of students on the implementation of the first cycle action that is 65,75 to 80,60 and has met the predetermined performance indicators that 85% of students have received a minimum score of 65.

  19. Bio-inspired ``jigsaw''-like interlocking sutures: Modeling, optimization, 3D printing and testing

    Science.gov (United States)

    Malik, I. A.; Mirkhalaf, M.; Barthelat, F.

    2017-05-01

    Structural biological materials such as bone, teeth or mollusk shells draw their remarkable performance from a sophisticated interplay of architectures and weak interfaces. Pushed to the extreme, this concept leads to sutured materials, which contain thin lines with complex geometries. Sutured materials are prominent in nature, and have recently served as bioinspiration for toughened ceramics and glasses. Sutures can generate large deformations, toughness and damping in otherwise all brittle systems and materials. In this study we examine the design and optimization of sutures with a jigsaw puzzle-like geometry, focusing on the non-linear traction behavior generated by the frictional pullout of the jigsaw tabs. We present analytical models which accurately predict the entire pullout response. Pullout strength and energy absorption increase with higher interlocking angles and for higher coefficients of friction, but the associated high stresses in the solid may fracture the tabs. Systematic optimization reveals a counter-intuitive result: the best pullout performance is achieved with interfaces with low coefficient of friction and high interlocking angle. We finally use 3D printing and mechanical testing to verify the accuracy of the models and of the optimization. The models and guidelines we present here can be extended to other types of geometries and sutured materials subjected to other loading/boundary conditions. The nonlinear responses of sutures are particularly attractive to augment the properties and functionalities of inherently brittle materials such as ceramics and glasses.

  20. A Hybrid Column Generation approach for an Industrial Waste Collection Routing Problem

    DEFF Research Database (Denmark)

    Hauge, Kristian; Larsen, Jesper; Lusby, Richard Martin

    2014-01-01

    , while empty containers must be returned to the depot to await further assignments. Unlike, the traditional ROROR problem, where vehicles may transport one skip container at a time regardless of whether it is full or not, we consider cases in which a vehicle can transport up to eight containers, at most...... two of which can be full. We propose a Generalized Set Partitioning formulation of the problem and describe a hybrid column generation procedure to solve it. A fast Tabu Search heuristic is used to generate new columns. The proposed methodology is tested on nine data sets, four of which are actual......, real-world problem instances. Results indicate that the hybrid column generation outperforms a purely heuristic approach in terms of both running time and solution quality. High quality solutions to problems containing up to 100 orders can be solved in approximately 15 minutes....

  1. A hybrid least squares support vector machines and GMDH approach for river flow forecasting

    Science.gov (United States)

    Samsudin, R.; Saad, P.; Shabri, A.

    2010-06-01

    This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

  2. A frequency domain approach to analyzing passive battery-ultracapacitor hybrids supplying periodic pulsed current loads

    International Nuclear Information System (INIS)

    Kuperman, Alon; Aharon, Ilan; Kara, Avi; Malki, Shalev

    2011-01-01

    Highlights: → Passive battery-ultracapacitor hybrids are examined. → Frequency domain analysis is employed. → The ultracapacitor branch operates as a low-pass filter for the battery. → The battery supplies the average load demand. → Design requirements are discussed. - Abstract: A Fourier-based analysis of passive battery-ultracapacitor hybrid sources is introduced in the manuscript. The approach is first introduced for a general load, and then is followed by a study for a case of periodic pulsed current load. It is shown that the ultracapacitor branch is perceived by the battery as a low-pass filter, which absorbs the majority of the high frequency harmonic current and letting the battery to supply the average load demand in addition to the small part of dynamic current. Design requirements influence on the ultracapacitor capacitance and internal resistance choice are quantitatively discussed. The theory is enforced by simulation and experimental results, showing an excellent agreement.

  3. A hybrid approach to solving the problem of design of nuclear fuel cells

    International Nuclear Information System (INIS)

    Montes T, J. L.; Perusquia del C, R.; Ortiz S, J. J.; Castillo, A.

    2015-09-01

    An approach to solving the problem of fuel cell design for BWR power reactor is presented. For this purpose the hybridization of a method based in heuristic knowledge rules called S15 and the advantages of a meta-heuristic method is proposed. The synergy of potentialities of both techniques allows finding solutions of more quality. The quality of each solution is obtained through a multi-objective function formed from the main cell parameters that are provided or obtained during the simulation with the CASMO-4 code. To evaluate this alternative of solution nuclear fuel cells of reference of nuclear power plant of Laguna Verde were used. The results show that in a systematic way the results improve when both methods are coupled. As a result of the hybridization process of the mentioned techniques an improvement is achieved in a range of 2% with regard to the achieved results in an independent way by the S15 method. (Author)

  4. Formal verification of dynamic hybrid systems: a NuSMV-based model checking approach

    Directory of Open Access Journals (Sweden)

    Xu Zhi

    2018-01-01

    Full Text Available Software security is an important and challenging research topic in developing dynamic hybrid embedded software systems. Ensuring the correct behavior of these systems is particularly difficult due to the interactions between the continuous subsystem and the discrete subsystem. Currently available security analysis methods for system risks have been limited, as they rely on manual inspections of the individual subsystems under simplifying assumptions. To improve this situation, a new approach is proposed that is based on the symbolic model checking tool NuSMV. A dual PID system is used as an example system, for which the logical part and the computational part of the system are modeled in a unified manner. Constraints are constructed on the controlled object, and a counter-example path is ultimately generated, indicating that the hybrid system can be analyzed by the model checking tool.

  5. Non-adaptive and adaptive hybrid approaches for enhancing water quality management

    Science.gov (United States)

    Kalwij, Ineke M.; Peralta, Richard C.

    2008-09-01

    SummaryUsing optimization to help solve groundwater management problems cost-effectively is becoming increasingly important. Hybrid optimization approaches, that combine two or more optimization algorithms, will become valuable and common tools for addressing complex nonlinear hydrologic problems. Hybrid heuristic optimizers have capabilities far beyond those of a simple genetic algorithm (SGA), and are continuously improving. SGAs having only parent selection, crossover, and mutation are inefficient and rarely used for optimizing contaminant transport management. Even an advanced genetic algorithm (AGA) that includes elitism (to emphasize using the best strategies as parents) and healing (to help assure optimal strategy feasibility) is undesirably inefficient. Much more efficient than an AGA is the presented hybrid (AGCT), which adds comprehensive tabu search (TS) features to an AGA. TS mechanisms (TS probability, tabu list size, search coarseness and solution space size, and a TS threshold value) force the optimizer to search portions of the solution space that yield superior pumping strategies, and to avoid reproducing similar or inferior strategies. An AGCT characteristic is that TS control parameters are unchanging during optimization. However, TS parameter values that are ideal for optimization commencement can be undesirable when nearing assumed global optimality. The second presented hybrid, termed global converger (GC), is significantly better than the AGCT. GC includes AGCT plus feedback-driven auto-adaptive control that dynamically changes TS parameters during run-time. Before comparing AGCT and GC, we empirically derived scaled dimensionless TS control parameter guidelines by evaluating 50 sets of parameter values for a hypothetical optimization problem. For the hypothetical area, AGCT optimized both well locations and pumping rates. The parameters are useful starting values because using trial-and-error to identify an ideal combination of control

  6. A hybrid approach for integrated healthcare cooperative purchasing and supply chain configuration.

    Science.gov (United States)

    Rego, Nazaré; Claro, João; Pinho de Sousa, Jorge

    2014-12-01

    This paper presents an innovative and flexible approach for recommending the number, size and composition of purchasing groups, for a set of hospitals willing to cooperate, while minimising their shared supply chain costs. This approach makes the financial impact of the various cooperation alternatives transparent to the group and the individual participants, opening way to a negotiation process concerning the allocation of the cooperation costs and gains. The approach was developed around a hybrid Variable Neighbourhood Search (VNS)/Tabu Search metaheuristic, resulting in a flexible tool that can be applied to purchasing groups with different characteristics, namely different operative and market circumstances, and to supply chains with different topologies and atypical cost characteristics. Preliminary computational results show the potential of the approach in solving a broad range of problems.

  7. A hybrid modelling approach to simulating foot-and-mouth disease outbreaks in Australian livestock

    Directory of Open Access Journals (Sweden)

    Richard A Bradhurst

    2015-03-01

    Full Text Available Foot-and-mouth disease (FMD is a highly contagious and economically important viral disease of cloven-hoofed animals. Australia's freedom from FMD underpins a valuable trade in live animals and animal products. An outbreak of FMD would result in the loss of export markets and cause severe disruption to domestic markets. The prevention of, and contingency planning for, FMD are of key importance to government, industry, producers and the community. The spread and control of FMD is complex and dynamic due to a highly contagious multi-host pathogen operating in a heterogeneous environment across multiple jurisdictions. Epidemiological modelling is increasingly being recognized as a valuable tool for investigating the spread of disease under different conditions and the effectiveness of control strategies. Models of infectious disease can be broadly classified as: population-based models that are formulated from the top-down and employ population-level relationships to describe individual-level behaviour, individual-based models that are formulated from the bottom-up and aggregate individual-level behaviour to reveal population-level relationships, or hybrid models which combine the two approaches into a single model.The Australian Animal Disease Spread (AADIS hybrid model employs a deterministic equation-based model (EBM to model within-herd spread of FMD, and a stochastic, spatially-explicit agent-based model (ABM to model between-herd spread and control. The EBM provides concise and computationally efficient predictions of herd prevalence and clinical signs over time. The ABM captures the complex, stochastic and heterogeneous environment in which an FMD epidemic operates. The AADIS event-driven hybrid EBM/ABM architecture is a flexible, efficient and extensible framework for modelling the spread and control of disease in livestock on a national scale. We present an overview of the AADIS hybrid approach and a description of the model

  8. PENERAPAN PEMBELAJARAN KOOPERATIF TIPE JIGSAW BERBASIS LESSON STUDY UNTUK MENINGKATAN AKTIVITAS KOLABORATIF MAHASISWA PGSD PADA MATA KULIAH PENDIDIKAN MATEMATIKA I

    Directory of Open Access Journals (Sweden)

    Ratih Purnamasari

    2016-09-01

    Full Text Available Abstrak. Penelitian ini bertujuan mengetahui peningkatan aktivitas kolaboratif mahasiswa pada mata kuliah pendidikan matematika I dengan menerapkan pembelajaran kooperatif tipe jigsaw berbasis lesson study. Penelitian dilakukan dengan tahapan-tahapan yang berlaku dalam pembelajaran berbasis lesson study yang terdiri dari plan, do dan see. Lokasi penelitian di FKIP UNPAK dengan waktu pelaksanaan antara bulan Mei-Juni 2013. Subyek penelitian mahasiswa S1 Prodi Pendidikan Guru Sekolah Dasar (PGSD semester VI yang mengambil mata kuliah pendidikan matematika I. Pengumpulan data dengan teknik dokumentasi, observasi, wawancara dan angket. Instrumen meliputi : lembar observasi, pedoman wawancara dan angket. Data hasil observasi dianalisis secara deskriptif kualitatif untuk mengetahui peningkatan aktivitas kolaboratif mahasiswa dalam kerja kelompok. Hasil penelitian menunjukkan penerapan pembelajaran kooperatif tipe jigsaw berbasis lesson study dapat meningkatkan aktivitas kolaboratif mahasiswa dalam kerja kelompok pada mata kuliah pendidikan matematika I, khususnya pada materi KPK, FPB dan pecahan. Hal ini dapat dilihat dari peningkatan ketercapaian indikator kegiatan lesson study di setiap siklusnya, serta hasil angket respon mahasiswa yang mayoritas menyatakan positif terhadap proses pembelajaran yang dilakukan. Selain itu, hasil wawancara terhadap mahasiswa juga menunjukkan bahwa pembelajaran kooperatif tipe jigsaw ternyata dapat meningkatkan motivasi mahasiswa untuk belajar secara berkolaborasi. Alangkah baiknya jika para dosen dalam membelajarkan mata kuliah pendidikan matematika 1 mencoba menggunakan pembelajaran kooperatif tipe jigsaw berbasis lesson study. Kata Kunci: Aktivitas Kolaboratif, Jigsaw, Lesson Study  Abstract. This study aimed to increase collaborative activities of students in the subject of Pendidikan Matematika I by implementing cooperative learning jigsaw-based lesson study. Research carried out by stages that apply in lesson

  9. A hybrid bio-jetting approach for directly engineering living cells

    International Nuclear Information System (INIS)

    Kwok, Albert; Irvine, Scott; Arumuganathar, Sumathy; Jayasinghe, Suwan N; McEwan, Jean R

    2008-01-01

    This paper reports developments on a hybrid cell-engineering protocol coupling both bio-electrosprays and aerodynamically assisted bio-jets for process-handling living cells. The current work demonstrates the ability to couple these two cell-jetting protocols for handling a wide range of cells for deposition. The post-treated cells are assessed for their viability by way of flow cytometry, which illustrates a significant population of viable cells post-treatment in comparison to those controls. This work is the first example of coupling these two protocols for the process handling of living cells. The hybrid protocol demonstrates the achievement of stable cone jetting of a cellular suspension in the single-needle configuration which was previously unachieved with single-needle bio-electrosprays. Furthermore the living cells explored in these investigations expressed GFP, thus demonstrating the ability to couple gene therapy with this hybrid protocol. Hence, this approach could one day be explored for building biologically viable tissues incorporating a therapeutic payload for combating a range of cellular/tissue-based pathologies

  10. Opposition-Based Memetic Algorithm and Hybrid Approach for Sorting Permutations by Reversals.

    Science.gov (United States)

    Soncco-Álvarez, José Luis; Muñoz, Daniel M; Ayala-Rincón, Mauricio

    2018-02-21

    Sorting unsigned permutations by reversals is a difficult problem; indeed, it was proved to be NP-hard by Caprara (1997). Because of its high complexity, many approximation algorithms to compute the minimal reversal distance were proposed until reaching the nowadays best-known theoretical ratio of 1.375. In this article, two memetic algorithms to compute the reversal distance are proposed. The first one uses the technique of opposition-based learning leading to an opposition-based memetic algorithm; the second one improves the previous algorithm by applying the heuristic of two breakpoint elimination leading to a hybrid approach. Several experiments were performed with one-hundred randomly generated permutations, single benchmark permutations, and biological permutations. Results of the experiments showed that the proposed OBMA and Hybrid-OBMA algorithms achieve the best results for practical cases, that is, for permutations of length up to 120. Also, Hybrid-OBMA showed to improve the results of OBMA for permutations greater than or equal to 60. The applicability of our proposed algorithms was checked processing permutations based on biological data, in which case OBMA gave the best average results for all instances.

  11. Energy level alignment at hybridized organic-metal interfaces from a GW projection approach

    Science.gov (United States)

    Chen, Yifeng; Tamblyn, Isaac; Quek, Su Ying

    Energy level alignments at organic-metal interfaces are of profound importance in numerous (opto)electronic applications. Standard density functional theory (DFT) calculations generally give incorrect energy level alignments and missing long-range polarization effects. Previous efforts to address this problem using the many-electron GW method have focused on physisorbed systems where hybridization effects are insignificant. Here, we use state-of-the-art GW methods to predict the level alignment at the amine-Au interface, where molecular levels do hybridize with metallic states. This non-trivial hybridization implies that DFT result is a poor approximation to the quasiparticle states. However, we find that the self-energy operator is approximately diagonal in the molecular basis, allowing us to use a projection approach to predict the level alignments. Our results indicate that the metallic substrate reduces the HOMO-LUMO gap by 3.5 4.0 eV, depending on the molecular coverage/presence of Au adatoms. Our GW results are further compared with those of a simple image charge model that describes the level alignment in physisorbed systems. Syq and YC acknowledge Grant NRF-NRFF2013-07 and the medium-sized centre program from the National Research Foundation, Singapore.

  12. Nanotubule and Tour Molecule Based Molecular Electronics: Suggestion for a Hybrid Approach

    Science.gov (United States)

    Srivastava, Deepak; Saini, Subhash (Technical Monitor)

    1998-01-01

    Recent experimental and theoretical attempts and results indicate two distinct broad pathways towards future molecular electronic devices and architectures. The first is the approach via Tour type ladder molecules and their junctions which can be fabricated with solution phase chemical approaches. Second are fullerenes or nanotubules and their junctions which may have better conductance, switching and amplifying characteristics but can not be made through well controlled and defined chemical means. A hybrid approach combining the two pathways to take advantage of the characteristics of both is suggested. Dimension and scale of such devices would be somewhere in between isolated molecule and nanotubule based devices but it maybe possible to use self-assembly towards larger functional and logicalunits.

  13. Photo-Ionization of Noble Gases: A Demonstration of Hybrid Coupled Channels Approach

    Directory of Open Access Journals (Sweden)

    Vinay Pramod Majety

    2015-01-01

    Full Text Available We present here an application of the recently developed hybrid coupled channels approach to study photo-ionization of noble gas atoms: Neon and Argon. We first compute multi-photon ionization rates and cross-sections for these inert gas atoms with our approach and compare them with reliable data available from R-matrix Floquet theory. The good agreement between coupled channels and R-matrix Floquet theory show that our method treats multi-electron systems on par with the well established R-matrix theory. We then apply the time dependent surface flux (tSURFF method with our approach to compute total and angle resolved photo-electron spectra from Argon with linearly and circularly polarized 12 nm wavelength laser fields, a typical wavelength available from Free Electron Lasers (FELs.

  14. A Hybrid Approach to Processing Big Data Graphs on Memory-Restricted Systems

    KAUST Repository

    Harshvardhan,

    2015-05-01

    With the advent of big-data, processing large graphs quickly has become increasingly important. Most existing approaches either utilize in-memory processing techniques that can only process graphs that fit completely in RAM, or disk-based techniques that sacrifice performance. In this work, we propose a novel RAM-Disk hybrid approach to graph processing that can scale well from a single shared-memory node to large distributed-memory systems. It works by partitioning the graph into sub graphs that fit in RAM and uses a paging-like technique to load sub graphs. We show that without modifying the algorithms, this approach can scale from small memory-constrained systems (such as tablets) to large-scale distributed machines with 16, 000+ cores.

  15. When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

    KAUST Repository

    Liu, Xiao

    2017-03-21

    Privacy risks of recommender systems have caused increasing attention. Users’ private data is often collected by probably untrusted recommender system in order to provide high-quality recommendation. Meanwhile, malicious attackers may utilize recommendation results to make inferences about other users’ private data. Existing approaches focus either on keeping users’ private data protected during recommendation computation or on preventing the inference of any single user’s data from the recommendation result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP) with randomized perturbation (RP). We theoretically show the noise added by RP has limited effect on recommendation accuracy and the noise added by DP can be well controlled based on the sensitivity analysis of functions on the perturbed data. Extensive experiments on three large-scale real world datasets show that the hybrid approach generally provides more privacy protection with acceptable recommendation accuracy loss, and surprisingly sometimes achieves better privacy without sacrificing accuracy, thus validating its feasibility in practice.

  16. Identification and Prediction of Large Pedestrian Flow in Urban Areas Based on a Hybrid Detection Approach

    Directory of Open Access Journals (Sweden)

    Kaisheng Zhang

    2016-12-01

    Full Text Available Recently, population density has grown quickly with the increasing acceleration of urbanization. At the same time, overcrowded situations are more likely to occur in populous urban areas, increasing the risk of accidents. This paper proposes a synthetic approach to recognize and identify the large pedestrian flow. In particular, a hybrid pedestrian flow detection model was constructed by analyzing real data from major mobile phone operators in China, including information from smartphones and base stations (BS. With the hybrid model, the Log Distance Path Loss (LDPL model was used to estimate the pedestrian density from raw network data, and retrieve information with the Gaussian Progress (GP through supervised learning. Temporal-spatial prediction of the pedestrian data was carried out with Machine Learning (ML approaches. Finally, a case study of a real Central Business District (CBD scenario in Shanghai, China using records of millions of cell phone users was conducted. The results showed that the new approach significantly increases the utility and capacity of the mobile network. A more reasonable overcrowding detection and alert system can be developed to improve safety in subway lines and other hotspot landmark areas, such as the Bundle, People’s Square or Disneyland, where a large passenger flow generally exists.

  17. Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

    Directory of Open Access Journals (Sweden)

    JingRui Zhang

    2015-03-01

    Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

  18. Hybrid generative-discriminative approach to age-invariant face recognition

    Science.gov (United States)

    Sajid, Muhammad; Shafique, Tamoor

    2018-03-01

    Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

  19. Fuzzy hybrid MCDM approach for selection of wind turbine service technicians

    Directory of Open Access Journals (Sweden)

    Goutam Kumar Bose

    2016-01-01

    Full Text Available This research paper is aimed to present a fuzzy Hybrid Multi-criteria decision making (MCDM methodology for selecting employees. The present study aspires to present the hybrid approach of Fuzzy multiple MCDM techniques with tactical viewpoint to support the recruitment process of wind turbine service technicians. The methodology is based on the application of Fuzzy ARAS (Additive Ratio Assessment and Fuzzy MOORA (Multi-Objective Optimization on basis of Ratio Analysis which are integrated through group decision making (GDM method in the model for selection of wind turbine service technicians’ ranking. Here a group of experts from different fields of expertise are engaged to finalize the decision. Series of tests are conducted regarding physical fitness, technical written test, practical test along with general interview and medical examination to facilitate the final selection using the above techniques. In contrast to single decision making approaches, the proposed group decision making model efficiently supports the wind turbine service technicians ranking process. The effectiveness of the proposed approach manifest from the case study of service technicians required for the maintenance department of wind power plant using Fuzzy ARAS and Fuzzy MOORA. This set of potential technicians is evaluated based on five main criteria.

  20. An Approach for Designing Thermal Management Systems for Electric and Hybrid Vehicle Battery Packs

    International Nuclear Information System (INIS)

    Pesaran, Ahmad A.; Keyser, Matthew; Burch, Steve

    1999-01-01

    If battery packs for electric vehicles (EVs) and hybrid electric vehicles (HEVs) are to operate effectively in all climates, thermal management of the packs is essential. In this paper, we will review a systematic approach for designing and evaluating battery pack thermal management systems. A thermal management system using air as the heat transfer medium is less complicated than a system using liquid cooling/heating. Generally, for parallel HEVs, an air thermal management system is adequate, whereas for EVs and series HEVs, liquid-based systems may be required for optimum thermal performance. Further information on battery thermal management can be found on the Web site www.ctts.nrel.gov/BTM

  1. AEROSTATIC AND AERODYNAMIC MODULES OF A HYBRID BUOYANT AIRCRAFT: AN ANALYTICAL APPROACH

    Directory of Open Access Journals (Sweden)

    Anwar Ul Haque

    2015-05-01

    Full Text Available An analytical approach is essential for the estimation of the requirements of aerodynamic and aerostatic lift for a hybrid buoyant aircraft. Such aircrafts have two different modules to balance the weight of aircraft; aerostatic module and aerodynamic module. Both these modules are to be treated separately for estimation of the mass budget of propulsion systems and required power. In the present work, existing relationships of aircraft and airship are reviewed for its further application for these modules. Limitations of such relationships are also disussed and it is precieved that it will provide a strating point for better understanding of design anatomy of such aircraft.

  2. "Elephant trunk" and endovascular stentgrafting : a hybrid approach to the treatment of extensive thoracic aortic aneurysm

    OpenAIRE

    Holubec, Tomás; Raupach, Jan; Dominik, Jan; Vojácek, Jan

    2013-01-01

    hybrid approach to elephant trunk technique for treatment of thoracic aortic aneurysms combines a conventional surgical and endovascular therapy. Compared to surgery alone, there is a presumption that mortality and morbidity is reduced. We present a case report of a 42-year-old man with a giant aneurysm of the entire thoracic aorta, significant aortic and tricuspid regurgitation and ventricular septum defect. The patient underwent multiple consecutive operations and interventions having, am...

  3. Towards a comprehensive theory for He II: I. A zero-temperature hybrid approach

    International Nuclear Information System (INIS)

    Ghassib, H.B.; Khudeir, A.M.

    1982-09-01

    A simple hybrid approach based on a gauge theory as well as a Hartree formalism, is presented for He II at zero temperature. Although this is intended to be merely a first step in an all-embracing theory, it already resolves quite neatly several old inconsistencies and corrects a few errors. As an illustration of its feasibility, a crude but instructive calculation is performed for the static structure factor of the system at low momentum transfers. A number of planned extensions and generalizations are outlined. (author)

  4. An integrated optimization approach for a hybrid energy system in electric vehicles

    International Nuclear Information System (INIS)

    Hung, Yi-Hsuan; Wu, Chien-Hsun

    2012-01-01

    Highlights: ► Second-order control-oriented dynamics for a battery/supercapacitor EV is modeled. ► Multiple for-loop programming and global searchwith constraints are main design principles of integrated optimization algorithm (IOA). ► Optimal hybridization is derived based on maximizing energy storage capacity. ► Optimal energy management in three EV operation modes is searched based on minimizing total consumed power. ► Simulation results prove that 6+% of total energy is saved by the IOA method. -- Abstract: This paper develops a simple but innovative integrated optimization approach (IOA) for deriving the best solutions of component sizing and control strategies of a hybrid energy system (HES) which consists of a lithium battery and a supercapacitor module. To implement IOA, a multiple for-loop structure with a preset cost function is needed to globally calculate the best hybridization and energy management of the HES. For system hybridization, the optimal size ratio is evaluated by maximizing the HES energy stored capacity at various costs. For energy management, the optimal power distribution combined with a three-mode rule-based strategy is searched to minimize the total consumed energy. Combining above two for-loop structures and giving a time-dependent test scenario, the IOA is derived by minimizing the accumulated HES power. Simulation results show that 6% of the total HES energy can be saved in the IOA case compared with the original system in two driving cycles: ECE and UDDS, and two vehicle weights, respectively. It proves that the IOA effectively derives the maximum energy storage capacity and the minimum energy consumption of the HES at the same time. Experimental verification will be carried out in the near future.

  5. A simplified computational fluid-dynamic approach to the oxidizer injector design in hybrid rockets

    Science.gov (United States)

    Di Martino, Giuseppe D.; Malgieri, Paolo; Carmicino, Carmine; Savino, Raffaele

    2016-12-01

    Fuel regression rate in hybrid rockets is non-negligibly affected by the oxidizer injection pattern. In this paper a simplified computational approach developed in an attempt to optimize the oxidizer injector design is discussed. Numerical simulations of the thermo-fluid-dynamic field in a hybrid rocket are carried out, with a commercial solver, to investigate into several injection configurations with the aim of increasing the fuel regression rate and minimizing the consumption unevenness, but still favoring the establishment of flow recirculation at the motor head end, which is generated with an axial nozzle injector and has been demonstrated to promote combustion stability, and both larger efficiency and regression rate. All the computations have been performed on the configuration of a lab-scale hybrid rocket motor available at the propulsion laboratory of the University of Naples with typical operating conditions. After a preliminary comparison between the two baseline limiting cases of an axial subsonic nozzle injector and a uniform injection through the prechamber, a parametric analysis has been carried out by varying the oxidizer jet flow divergence angle, as well as the grain port diameter and the oxidizer mass flux to study the effect of the flow divergence on heat transfer distribution over the fuel surface. Some experimental firing test data are presented, and, under the hypothesis that fuel regression rate and surface heat flux are proportional, the measured fuel consumption axial profiles are compared with the predicted surface heat flux showing fairly good agreement, which allowed validating the employed design approach. Finally an optimized injector design is proposed.

  6. A hybrid filtering approach for storage optimization in main-memory cloud database

    Directory of Open Access Journals (Sweden)

    Ghada M. Afify

    2015-11-01

    Full Text Available Enterprises and cloud service providers face dramatic increase in the amount of data stored in private and public clouds. Thus, data storage costs are growing hastily because they use only one single high-performance storage tier for storing all cloud data. There’s considerable potential to reduce cloud costs by classifying data into active (hot and inactive (cold. In the main-memory databases research, recent works focus on approaches to identify hot/cold data. Most of these approaches track tuple accesses to identify hot/cold tuples. In contrast, we introduce a novel Hybrid Filtering Approach (HFA that tracks both tuples and columns accesses in main-memory databases. Our objective is to enhance the performance in terms of three dimensions: storage space, query elapsed time and CPU time. In order to validate the effectiveness of our approach, we realized its concrete implementation on Hekaton, a SQL’s server memory-optimized engine using the well-known TPC-H benchmark. Experimental results show that the proposed HFA outperforms Hekaton approach in respect of all performance dimensions. In specific, HFA reduces the storage space by average of 44–96%, reduces the query elapsed time by average of 25–93% and reduces the CPU time by average of 31–97% compared to the traditional database approach.

  7. An Odometry-free Approach for Simultaneous Localization and Online Hybrid Map Building

    Directory of Open Access Journals (Sweden)

    Wei Hong Chin

    2016-11-01

    Full Text Available In this paper, a new approach is proposed for mobile robot localization and hybrid map building simultaneously without using any odometry hardware system. The proposed method termed as Genetic Bayesian ARAM which comprises two main components: 1 Steady state genetic algorithm (SSGA for self-localization and occupancy grid map building; 2 Bayesian Adaptive Resonance Associative Memory (ARAM for online topological map building. The model of the explored environment is formed as a hybrid representation, both topological and grid-based, and it is incrementally constructed during the exploration process. During occupancy map building, robot estimated self-position is updated by SSGA. At the same time, robot estimated self position is transmit to Bayesian ARAM for topological map building and localization. The effectiveness of our proposed approach is validated by a number of standardized benchmark datasets and real experimental results carried on mobile robot. Benchmark datasets are used to verify the proposed method capable of generating topological map in different environment conditions. Real robot experiment is to verify the proposed method can be implemented in real world.

  8. Hybrid discrete PSO and OPF approach for optimization of biomass fueled micro-scale energy system

    International Nuclear Information System (INIS)

    Gómez-González, M.; López, A.; Jurado, F.

    2013-01-01

    Highlights: ► Method to determine the optimal location and size of biomass power plants. ► The proposed approach is a hybrid of PSO algorithm and optimal power flow. ► Comparison among the proposed algorithm and other methods. ► Computational costs are enough lower than that required for exhaustive search. - Abstract: This paper addresses generation of electricity in the specific aspect of finding the best location and sizing of biomass fueled gas micro-turbine power plants, taking into account the variables involved in the problem, such as the local distribution of biomass resources, biomass transportation and extraction costs, operation and maintenance costs, power losses costs, network operation costs, and technical constraints. In this paper a hybrid method is introduced employing discrete particle swarm optimization and optimal power flow. The approach can be applied to search the best sites and capacities to connect biomass fueled gas micro-turbine power systems in a distribution network among a large number of potential combinations and considering the technical constraints of the network. A fair comparison among the proposed algorithm and other methods is performed.

  9. Output Tracking Control of Switched Hybrid Systems: A Fliess Functional Expansion Approach

    Directory of Open Access Journals (Sweden)

    Fenghua He

    2013-01-01

    Full Text Available The output tracking problem is investigated for a nonlinear affine system with multiple modes of continuous control inputs. We convert the family of nonlinear affine systems under consideration into a switched hybrid system by introducing a multiple-valued logic variable. The Fliess functional expansion is adopted to express the input and output relationship of the switched hybrid system. The optimal switching control is determined for a multiple-step output tracking performance index. The proposed approach is applied to a multitarget tracking problem for a flight vehicle aiming for one real target with several decoys flying around it in the terminal guidance course. These decoys appear as apparent targets and have to be distinguished with the approaching of the flight vehicle. The guidance problem of one flight vehicle versus multiple apparent targets should be considered if no large miss distance might be caused due to the limitation of the flight vehicle maneuverability. The target orientation at each time interval is determined. Simulation results show the effectiveness of the proposed method.

  10. Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels

    Directory of Open Access Journals (Sweden)

    Antonino Laudani

    2015-01-01

    Full Text Available A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented. The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model. Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task. The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form. The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters. It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture. Validations are made on about 10000 PV panels belonging to the California Energy Commission database.

  11. A diagnostic expert system for the nuclear power plant b ased on the hybrid knowledge approach

    International Nuclear Information System (INIS)

    Yang, J.O.; Chang, S.H.

    1989-01-01

    A diagnostic expert system, the hybrid knowledge based plant operation supporting system (HYPOSS), which has been developed to support operators' decisionmaking during the transients of the nuclear power plant, is described. HYPOSS adopts the hybrid knowledge approach, which combines both shallow and deep knowledge to take advantage of the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure. They are structural, functional, behavioral, and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions, respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem-solving behavior modeled in HYPOSS. The event-based operational guidelines are provided to the operator according to the diagnosed results. If the exact anomalies cannot be identified while some of the critical safety functions are challenged, the function-based operational guidelines are provided to the operator. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies show good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

  12. A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran

    International Nuclear Information System (INIS)

    Mostafavi, Elham Sadat; Ramiyani, Sara Saeidi; Sarvar, Rahim; Moud, Hashem Izadi; Mousavi, Seyyed Mohammad

    2013-01-01

    This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated annealing (SA), called GP/SA. The solar radiation was formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years in two cities of Iran were used to develop GP/SA-based models. Separate models were established for each city. The generalization of the models was verified using a separate testing database. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the solar radiation. The derived models make accurate predictions of the solar global radiation and notably outperform the existing models. -- Highlights: ► A hybrid approach is presented for the estimation of the solar global radiation. ► The proposed method integrates the capabilities of GP and SA. ► Several climatological and meteorological parameters are included in the analysis. ► The GP/SA models make accurate predictions of the solar global radiation.

  13. Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

    Directory of Open Access Journals (Sweden)

    Yuliang Su

    2015-04-01

    Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

  14. A hybrid simulated annealing approach to handle energy resource management considering an intensive use of electric vehicles

    DEFF Research Database (Denmark)

    Sousa, Tiago; Vale, Zita; Carvalho, Joao Paulo

    2014-01-01

    The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed...... to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated...... annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA...

  15. Issues for the future. Putting the jigsaw together.

    Science.gov (United States)

    1998-07-01

    Oxfam's efforts to support organizations working with disabled people in Bosnia highlight the necessity of taking into account other forms of disadvantage that increase vulnerability, such as gender, when planning interventions. When Oxfam began working in Bosnia in 1993, disability was widely perceived as a medical rather than a social development issue. An Oxfam-inspired inter-Association project set up the Lotos Resource Center to create badly needed joint social space and office space for vocational training. Realizing that it was difficult to reach women with disabilities, Oxfam representatives made home visits to encourage women to participate in activities. Oxfam also actively co-opted women to join the steering committee. This work gave Oxfam a better understanding of the fact that a diversity of needs exists for disabled men and women, for able-bodied women caring for disabled partners, and for women caring for disabled children. Lessons learned include 1) people with disabilities are not homogeneous in their needs; 2) it is essential to take positive action to involve disabled women; 3) gender and disability analysis must be inclusive and must consider different sources of marginalization or else marginalization will be reinforced; and 4) a basic rights approach provides a clear framework to understand dimensions of disadvantage within households.

  16. A Hybrid Heuristic Optimization Approach for Leak Detection in Pipe Networks Using Ordinal Optimization Approach and the Symbiotic Organism Search

    Directory of Open Access Journals (Sweden)

    Chao-Chih Lin

    2017-10-01

    Full Text Available A new transient-based hybrid heuristic approach is developed to optimize a transient generation process and to detect leaks in pipe networks. The approach couples the ordinal optimization approach (OOA and the symbiotic organism search (SOS to solve the optimization problem by means of iterations. A pipe network analysis model (PNSOS is first used to determine steady-state head distribution and pipe flow rates. The best transient generation point and its relevant valve operation parameters are optimized by maximizing the objective function of transient energy. The transient event is created at the chosen point, and the method of characteristics (MOC is used to analyze the transient flow. The OOA is applied to sift through the candidate pipes and the initial organisms with leak information. The SOS is employed to determine the leaks by minimizing the sum of differences between simulated and computed head at the observation points. Two synthetic leaking scenarios, a simple pipe network and a water distribution network (WDN, are chosen to test the performance of leak detection ordinal symbiotic organism search (LDOSOS. Leak information can be accurately identified by the proposed approach for both of the scenarios. The presented technique makes a remarkable contribution to the success of leak detection in the pipe networks.

  17. A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN

    Directory of Open Access Journals (Sweden)

    Yimei Kang

    2014-04-01

    Full Text Available Energy efficiency is usually a significant goal in wireless sensor networks (WSNs. In this work, an energy efficient chain (EEC data routing approach is first presented. The coverage and connectivity of WSNs are discussed based on EEC. A hybrid node scheduling approach is then proposed. It includes sleep scheduling for cyclically monitoring regions of interest in time-driven modes and wakeup scheduling for tracking emergency events in event-driven modes. A failure rate is introduced to the sleep scheduling to improve the reliability of the system. A wakeup sensor threshold and a sleep time threshold are introduced in the wakeup scheduling to reduce the consumption of energy to the possible extent. The results of the simulation show that the proposed algorithm can extend the effective lifetime of the network to twice that of PEAS. In addition, the proposed methods are computing efficient because they are very simple to implement.

  18. A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Jian Xiong

    2012-01-01

    Full Text Available This paper addresses multiobjective flexible job-shop scheduling problem (FJSP with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach (H-MOEA is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to maintain the diversity of individuals. In the proposed H-MOEA, well-designed chromosome representation and genetic operators are developed for FJSP. Moreover, a local search procedure based on critical path theory is incorporated in H-MOEA to improve the convergence ability of the algorithm. Experiment results on several well-known benchmark instances demonstrate the efficiency and stability of the proposed algorithm. The comparison with other recently published approaches validates that H-MOEA can obtain Pareto-optimal solutions with better quality and/or diversity.

  19. A Practical Approach to Improve Optical Channel Utilization Period for Hybrid FSO/RF Systems

    Directory of Open Access Journals (Sweden)

    Ahmet Akbulut

    2014-01-01

    Full Text Available In hybrid FSO/RF systems, mostly a hard switching mechanism is preferred in case of the FSO signal level falls below to the predefined threshold. In this work, a computationally simple approach is proposed to increase the utilization of the FSO channels bandwidth advantage. For the channel, clear air conditions have been supposed with the atmospheric turbulence. In this approach, FSO bit rate is adaptively changed to achieve desired BER performance. An IM/DD modulation, OOK (NRZ format has been used to show the benefit of the proposed method. Furthermore, to be more realistic with respect to the atmospheric turbulence variations within a day, some experimental observations have been followed up.

  20. Gold-nanoparticle-mediated jigsaw-puzzle-like assembly of supersized plasmonic DNA origami.

    Science.gov (United States)

    Yao, Guangbao; Li, Jiang; Chao, Jie; Pei, Hao; Liu, Huajie; Zhao, Yun; Shi, Jiye; Huang, Qing; Wang, Lianhui; Huang, Wei; Fan, Chunhai

    2015-03-02

    DNA origami has rapidly emerged as a powerful and programmable method to construct functional nanostructures. However, the size limitation of approximately 100 nm in classic DNA origami hampers its plasmonic applications. Herein, we report a jigsaw-puzzle-like assembly strategy mediated by gold nanoparticles (AuNPs) to break the size limitation of DNA origami. We demonstrated that oligonucleotide-functionalized AuNPs function as universal joint units for the one-pot assembly of parent DNA origami of triangular shape to form sub-microscale super-origami nanostructures. AuNPs anchored at predefined positions of the super-origami exhibited strong interparticle plasmonic coupling. This AuNP-mediated strategy offers new opportunities to drive macroscopic self-assembly and to fabricate well-defined nanophotonic materials and devices. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. A Theoretical Model of Jigsaw-Puzzle Pattern Formation by Plant Leaf Epidermal Cells.

    Science.gov (United States)

    Higaki, Takumi; Kutsuna, Natsumaro; Akita, Kae; Takigawa-Imamura, Hisako; Yoshimura, Kenji; Miura, Takashi

    2016-04-01

    Plant leaf epidermal cells exhibit a jigsaw puzzle-like pattern that is generated by interdigitation of the cell wall during leaf development. The contribution of two ROP GTPases, ROP2 and ROP6, to the cytoskeletal dynamics that regulate epidermal cell wall interdigitation has already been examined; however, how interactions between these molecules result in pattern formation remains to be elucidated. Here, we propose a simple interface equation model that incorporates both the cell wall remodeling activity of ROP GTPases and the diffusible signaling molecules by which they are regulated. This model successfully reproduces pattern formation observed in vivo, and explains the counterintuitive experimental results of decreased cellulose production and increased thickness. Our model also reproduces the dynamics of three-way cell wall junctions. Therefore, this model provides a possible mechanism for cell wall interdigitation formation in vivo.

  2. Creation and implementation of a flipped jigsaw activity to stimulate interest in biochemistry among medical students.

    Science.gov (United States)

    Williams, Charlene; Perlis, Susan; Gaughan, John; Phadtare, Sangita

    2018-05-06

    Learner-centered pedagogical methods that are based on clinical application of basic science concepts through active learning and problem solving are shown to be effective for improving knowledge retention. As the clinical relevance of biochemistry is not always apparent to health-profession students, effective teaching of medical biochemistry should highlight the implications of biochemical concepts in pathology, minimize memorization, and make the concepts memorable for long-term retention. Here, we report the creation and successful implementation of a flipped jigsaw activity that was developed to stimulate interest in learning biochemistry among medical students. The activity combined the elements of a flipped classroom for learning concepts followed by a jigsaw activity to retrieve these concepts by solving clinical cases, answering case-based questions, and creating concept maps. The students' reception of the activity was very positive. They commented that the activity provided them an opportunity to review and synthesize information, helped to gage their learning by applying this information and work with peers. Students' improved performance especially for answering the comprehension-based questions correctly in the postquiz as well as the depth of information included in the postquiz concept maps suggested that the activity helped them to understand how different clinical scenarios develop owing to deviations in basic biochemical pathways. Although this activity was created for medical students, the format of this activity can also be useful for other health-professional students as well as undergraduate and graduate students. © 2018 by The International Union of Biochemistry and Molecular Biology, 2018. © 2018 The International Union of Biochemistry and Molecular Biology.

  3. THE APPLICATION OF JIGSAW AND NUMBERED HEADS TOGETHER TECHNIQUES IN IMPROVING STUDENTS’ ABILITY IN SPEAKING SKILL

    Directory of Open Access Journals (Sweden)

    Siti Aimah

    2017-04-01

    Full Text Available This research was aimed to investigate how the study of speaking was developed through Jigsaw and Numbered Heads Together techniques and find out the improvement of students’ ability in speaking. For this purpose, 14 students of the second semester students were taken in the academic year of 2012/2013. A classroom action research was conducted in which consisted of two cycles through the stages of planning, action, observation, and reflection. The speaking tests, the observation note, and the questionnaire were taken as the data. The result of this research showed the students’ ability in speaking improved significantly. They were more enthusiastic in joining the class. They could learn together with their team in understanding the material and conveying it to the others well. They were also dared to tell what they wanted to tell the others without any pressuring from anyone else. They tried to snatch away each others in conveying their idea based on the number mentioned by the lecturer. In some cases, they even argued their argumentation attractively. While from the questionnaire which was distributed showed that more than 75% students felt the application of Jigsaw and Numbered Heads Together techniques helped them easily in developing their ability in speaking skill. And more than 80% students agreed those techniques facilitated them on having the accountability in understanding and conveying the material that they had learnt easily to the others. Studying in a team proved that the students enjoyed more in joining the English class. So it is suggested that the English lecturers should use the types of cooperative learning in teaching language skills.

  4. MODEL PEMBELAJARAN JIGSAW DENGAN STRATEGI METAKOGNITIF UNTUK MENINGKATKAN SELF-EFFICACY DAN KEMAMPUAN PEMECAHAN MASALAH

    Directory of Open Access Journals (Sweden)

    Purtiana Septi Alfurofika

    2013-12-01

    Full Text Available Tujuan penelitian ini untuk menghasilkan perangkat pembelajaran matematika model Jigsaw strategi Metakognitif untuk meningkatkan self-efficacy terhadap kemampuan pemecahan masalah dengan materi segi empat kelas VII valid, praktis dan efektif. Penelitian ini merupakan penelitian pengembangan modifikasi Plomp. Jenis perangkat pembelajaran yang dikembangkan adalah silabus, RPP, bahan ajar, LKS, media pembelajaran, Tes Kemampuan Pemecahan Masalah. Teknik pengambilan data menggunakan lembar validasi, lembar pengamatan self-efficacy dan aktifitas, Lembar angket, dan Tes Kemampuan Pemecahan Masalah. Hasil penelitian menunjukkan: (1 perangkat yang dikembangkan valid; (2 pembelajaran praktis ditandai dengan respon positif siswa dan kemampuan guru baik; (3 Efektifitas ditandai dengan (a kemampuan pemecahan masalah mencapai KKM yaitu 83,4 dan ketuntasan klasikal sebesar 90,3%; (b self-efficacy dan aktifitas siswa secara bersama – sama berpengaruh positif terhadap kemampuan pemecahan masalah sebesar 71,9%; dan (c self-efficacy dan aktivitas siswa mengalami peningkatan. Berdasarkan hasil penelitian dapat disimpulkan tujuan pengembangan perangkat tercapai. The aim of this research to produce mathematics’ learning device the Jigsaw model with Metacognitive strategies for increasing self-efficacy towards problem solving ability to quadrilateral of class VII valid, practical and effective. This research is development of modifications Plomp. Kinds of learning devices are developed syllabi, lesson plans, teaching materials, worksheets, instructional media, and problem solving ability test. Technique of data collection by using validation sheet, observation sheet student’s self-efficacy and activity, questionnaire, and problem solving ability test. The results showed: (1 device developed valid; (2 practical learning is characterized by the positive response of students and good teachers ability; (3 effectiveness characterized by (a the ability of problem

  5. Potential-vorticity inversion and the wave-turbulence jigsaw: some recent clarifications

    Directory of Open Access Journals (Sweden)

    M. E. McIntyre

    2008-06-01

    Full Text Available Two key ideas stand out as crucial to understanding atmosphere-ocean dynamics, and the dynamics of other planets including the gas giants. The first key idea is the invertibility principle for potential vorticity (PV. Without it, one can hardly give a coherent account of even so important and elementary a process as Rossby-wave propagation, going beyond the simplest textbook cases. Still less can one fully understand nonlinear processes like the self-sharpening or narrowing of jets – the once-mysterious "negative viscosity" phenomenon. The second key idea, also crucial to understanding jets, might be summarized in the phrase "there is no such thing as turbulence without waves", meaning Rossby waves especially. Without this idea one cannot begin to make sense of, for instance, momentum budgets and eddy momentum transports in complex large-scale flows. Like the invertibility principle the idea has long been recognized, or at least adumbrated. However, it is worth articulating explicitly if only because it can be forgotten when, in the usual way, we speak of "turbulence" and "turbulence theory" as if they were autonomous concepts. In many cases of interest, such as the well-studied terrestrial stratosphere, reality is more accurately described as a highly inhomogeneous "wave-turbulence jigsaw puzzle" in which wavelike and turbulent regions fit together and crucially affect each other's evolution. This modifies, for instance, formulae for the Rhines scale interpreted as indicating the comparable importance of wavelike and turbulent dynamics. Also, weakly inhomogeneous turbulence theory is altogether inapplicable. For instance there is no scale separation. Eddy scales are not much smaller than the sizes of the individual turbulent regions in the jigsaw. Here I review some recent progress in clarifying these ideas and their implications.

  6. Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach.

    Directory of Open Access Journals (Sweden)

    Kristen Feher

    Full Text Available Heterosis, the greater vigor of hybrids compared to their parents, has been exploited in maize breeding for more than 100 years to produce ever better performing elite hybrids of increased yield. Despite extensive research, the underlying mechanisms shaping the extent of heterosis are not well understood, rendering the process of selecting an optimal set of parental lines tedious. This study is based on a dataset consisting of 112 metabolite levels in young roots of four parental maize inbred lines and their corresponding twelve hybrids, along with the roots' biomass as a heterotic trait. Because the parental biomass is a poor predictor for hybrid biomass, we established a model framework to deduce the biomass of the hybrid from metabolite profiles of its parental lines. In the proposed framework, the hybrid metabolite levels are expressed relative to the parental levels by incorporating the standard concept of additivity/dominance, which we name the Combined Relative Level (CRL. Our modeling strategy includes a feature selection step on the parental levels which are demonstrated to be predictive of CRL across many hybrid metabolites. We demonstrate that these selected parental metabolites are further predictive of hybrid biomass. Our approach directly employs the diallel structure in a multivariate fashion, whereby we attempt to not only predict macroscopic phenotype (biomass, but also molecular phenotype (metabolite profiles. Therefore, our study provides the first steps for further investigations of the genetic determinants to metabolism and, ultimately, growth. Finally, our success on the small-scale experiments implies a valid strategy for large-scale experiments, where parental metabolite profiles may be used together with profiles of selected hybrids as a training set to predict biomass of all possible hybrids.

  7. Proposed prediction algorithms based on hybrid approach to deal with anomalies of RFID data in healthcare

    Directory of Open Access Journals (Sweden)

    A. Anny Leema

    2013-07-01

    Full Text Available The RFID technology has penetrated the healthcare sector due to its increased functionality, low cost, high reliability, and easy-to-use capabilities. It is being deployed for various applications and the data captured by RFID readers increase according to timestamp resulting in an enormous volume of data duplication, false positive, and false negative. The dirty data stream generated by the RFID readers is one of the main factors limiting the widespread adoption of RFID technology. In order to provide reliable data to RFID application, it is necessary to clean the collected data and this should be done in an effective manner before they are subjected to warehousing. The existing approaches to deal with anomalies are physical, middleware, and deferred approach. The shortcomings of existing approaches are analyzed and found that robust RFID system can be built by integrating the middleware and deferred approach. Our proposed algorithms based on hybrid approach are tested in the healthcare environment which predicts false positive, false negative, and redundant data. In this paper, healthcare environment is simulated using RFID and the data observed by RFID reader consist of anomalies false positive, false negative, and duplication. Experimental evaluation shows that our cleansing methods remove errors in RFID data more accurately and efficiently. Thus, with the aid of the planned data cleaning technique, we can bring down the healthcare costs, optimize business processes, streamline patient identification processes, and improve patient safety.

  8. An Introduction to the Hybrid Approach of Neural Networks and the Linear Regression Model : An Illustration in the Hedonic Pricing Model of Building Costs

    OpenAIRE

    浅野, 美代子; マーコ, ユー K.W.

    2007-01-01

    This paper introduces the hybrid approach of neural networks and linear regression model proposed by Asano and Tsubaki (2003). Neural networks are often credited with its superiority in data consistency whereas the linear regression model provides simple interpretation of the data enabling researchers to verify their hypotheses. The hybrid approach aims at combing the strengths of these two well-established statistical methods. A step-by-step procedure for performing the hybrid approach is pr...

  9. Heuristic hybrid game approach for fleet condition-based maintenance planning

    International Nuclear Information System (INIS)

    Feng, Qiang; Bi, Xiong; Zhao, Xiujie; Chen, Yiran; Sun, Bo

    2017-01-01

    The condition-based maintenance (CBM) method is commonly used to select appropriate maintenance opportunities according to equipment status over a period of time. The CBM of aircraft fleets is a fleet maintenance planning problem. In this problem, mission requirements, resource constraints, and aircraft statuses are considered to find an optimal strategy set. Given that the maintenance strategies for each aircraft are finite, fleet CBM can be treated as a combinatorial optimization problem. In this study, the process of making a decision on the CBM of military fleets is analyzed. The fleet CBM problem is treated as a two-stage dynamic decision-making problem. Aircraft are divided into dispatch and standby sets; thus, the problem scale is significantly reduced. A heuristic hybrid game (HHG) approach comprising a competition game and a cooperative game is proposed on the basis of heuristic rule. In the dispatch set, a competition game approach is proposed to search for a local optimal strategy matrix. A cooperative game method for the two sets is also proposed to ensure global optimization. Finally, a case study regarding a fleet comprising 20 aircraft is conducted, with the results proving that the approach efficiently generates outcomes that meet the mission risk-oriented schedule requirement. - Highlights: • A new heuristic hybrid game method for fleet condition-based maintenance is proposed. • The problem is simplified by hierarchical solving based on dispatch and standby set. • The local optimal solution is got by competition game algorithm for dispatch set. • The global optimal solution is got by cooperative game algorithm between two sets.

  10. An approach for identification of unknown viruses using sequencing-by-hybridization.

    Science.gov (United States)

    Katoski, Sarah E; Meyer, Hermann; Ibrahim, Sofi

    2015-09-01

    Accurate identification of biological threat agents, especially RNA viruses, in clinical or environmental samples can be challenging because the concentration of viral genomic material in a given sample is usually low, viral genomic RNA is liable to degradation, and RNA viruses are extremely diverse. A two-tiered approach was used for initial identification, then full genomic characterization of 199 RNA viruses belonging to virus families Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, and Togaviridae. A Sequencing-by-hybridization (SBH) microarray was used to tentatively identify a viral pathogen then, the identity is confirmed by guided next-generation sequencing (NGS). After optimization and evaluation of the SBH and NGS methodologies with various virus species and strains, the approach was used to test the ability to identify viruses in blinded samples. The SBH correctly identified two Ebola viruses in the blinded samples within 24 hr, and by using guided amplicon sequencing with 454 GS FLX, the identities of the viruses in both samples were confirmed. SBH provides at relatively low-cost screening of biological samples against a panel of viral pathogens that can be custom-designed on a microarray. Once the identity of virus is deduced from the highest hybridization signal on the SBH microarray, guided (amplicon) NGS sequencing can be used not only to confirm the identity of the virus but also to provide further information about the strain or isolate, including a potential genetic manipulation. This approach can be useful in situations where natural or deliberate biological threat incidents might occur and a rapid response is required. © 2015 Wiley Periodicals, Inc.

  11. The Importance of Being Hybrid for Spatial Epidemic Models:A Multi-Scale Approach

    Directory of Open Access Journals (Sweden)

    Arnaud Banos

    2015-11-01

    Full Text Available This work addresses the spread of a disease within an urban system, definedas a network of interconnected cities. The first step consists of comparing two differentapproaches: a macroscopic one, based on a system of coupled Ordinary DifferentialEquations (ODE Susceptible-Infected-Recovered (SIR systems exploiting populations onnodes and flows on edges (so-called metapopulational model, and a hybrid one, couplingODE SIR systems on nodes and agents traveling on edges. Under homogeneous conditions(mean field approximation, this comparison leads to similar results on the outputs on whichwe focus (the maximum intensity of the epidemic, its duration and the time of the epidemicpeak. However, when it comes to setting up epidemic control strategies, results rapidlydiverge between the two approaches, and it appears that the full macroscopic model is notcompletely adapted to these questions. In this paper, we focus on some control strategies,which are quarantine, avoidance and risk culture, to explore the differences, advantages anddisadvantages of the two models and discuss the importance of being hybrid when modelingand simulating epidemic spread at the level of a whole urban system.

  12. Modular approach for conversion to the ion-hybrid wave and α gyroresonance

    International Nuclear Information System (INIS)

    Kaufman, A.N.; Morehead, J.J.; Brizard, A.J.; Tracy, E.R.

    1997-01-01

    Linear conversion of an incoming magnetosonic wave (a.k.a. fast or compressional wave) to an ion-hybrid wave can be considered as a 3-step process in ray phase space. This is demonstrated by casting the cold-fluid model into the Friedland-Kaufman normal form for linear mode conversion. First, the incoming magnetosonic ray (MSR) converts a fraction of its action to an intermediate ion-hybrid ray (IHR), with the transmitted ray proceeding through the conversion layer. The IHR propagates in k-space to a second conversion point, where it converts in turn a fraction of its action into a reflected MSR, with the remainder of the its action constituting the converted IHR. The modular approach gives exact agreement with the more standard Budden formulation for the transmission, reflection and conversion coefficients, but has the important advantage of exposing the intermediate IHR. The existence of the intermediate IHR has important physical consequences as it can resonate with α particles. We estimate the time-integrated damping coefficient between the two conversions and show that ∫γdt is of order -100, thus the IH wave is completely annihilated between conversions and transfers its energy to the α close-quote s. This suggests that proposals to use the IH mode for current drive or DT heating are likely to fail in the presence of fusion α close-quote s. copyright 1997 American Institute of Physics

  13. A hybrid approach to automatic de-identification of psychiatric notes.

    Science.gov (United States)

    Lee, Hee-Jin; Wu, Yonghui; Zhang, Yaoyun; Xu, Jun; Xu, Hua; Roberts, Kirk

    2017-11-01

    De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing system for automatic de-identification of psychiatric notes, which was designed to participate in the 2016 CEGS N-GRID shared task Track 1. The system has a hybrid structure that combines machine leaning techniques and rule-based approaches. The rule-based components exploit the structure of the psychiatric notes as well as characteristic surface patterns of PHI mentions. The machine learning components utilize supervised learning with rich features. In addition, the system performance was boosted with integration of additional data to the training set through domain adaptation. The hybrid system showed overall micro-averaged F-score 90.74 on the test set, second-best among all the participants of the CEGS N-GRID task. Copyright © 2017. Published by Elsevier Inc.

  14. Aeroacoustic analysis of the human phonation process based on a hybrid acoustic PIV approach

    Science.gov (United States)

    Lodermeyer, Alexander; Tautz, Matthias; Becker, Stefan; Döllinger, Michael; Birk, Veronika; Kniesburges, Stefan

    2018-01-01

    The detailed analysis of sound generation in human phonation is severely limited as the accessibility to the laryngeal flow region is highly restricted. Consequently, the physical basis of the underlying fluid-structure-acoustic interaction that describes the primary mechanism of sound production is not yet fully understood. Therefore, we propose the implementation of a hybrid acoustic PIV procedure to evaluate aeroacoustic sound generation during voice production within a synthetic larynx model. Focusing on the flow field downstream of synthetic, aerodynamically driven vocal folds, we calculated acoustic source terms based on the velocity fields obtained by time-resolved high-speed PIV applied to the mid-coronal plane. The radiation of these sources into the acoustic far field was numerically simulated and the resulting acoustic pressure was finally compared with experimental microphone measurements. We identified the tonal sound to be generated downstream in a small region close to the vocal folds. The simulation of the sound propagation underestimated the tonal components, whereas the broadband sound was well reproduced. Our results demonstrate the feasibility to locate aeroacoustic sound sources inside a synthetic larynx using a hybrid acoustic PIV approach. Although the technique employs a 2D-limited flow field, it accurately reproduces the basic characteristics of the aeroacoustic field in our larynx model. In future studies, not only the aeroacoustic mechanisms of normal phonation will be assessable, but also the sound generation of voice disorders can be investigated more profoundly.

  15. Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

    Directory of Open Access Journals (Sweden)

    Ahmed Hussein

    2018-01-01

    Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

  16. Jigsaw Semantics

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    Paul J. E. Dekker

    2010-12-01

    Full Text Available In the last decade the enterprise of formal semantics has been under attack from several philosophical and linguistic perspectives, and it has certainly suffered from its own scattered state, which hosts quite a variety of paradigms which may seem to be incompatible. It will not do to try and answer the arguments of the critics, because the arguments are often well-taken. The negative conclusions, however, I believe are not. The only adequate reply seems to be a constructive one, which puts several pieces of formal semantics, in particular dynamic semantics, together again. In this paper I will try and sketch an overview of tasks, techniques, and results, which serves to at least suggest that it is possible to develop a coherent overall picture of undeniably important and structural phenomena in the interpretation of natural language. The idea is that the concept of meanings as truth conditions after all provides an excellent start for an integrated study of the meaning and use of natural language, and that an extended notion of goal directed pragmatics naturally complements this picture. None of the results reported here are really new, but we think it is important to re-collect them.ReferencesAsher, Nicholas & Lascarides, Alex. 1998. ‘Questions in Dialogue’. Linguistics and Philosophy 23: 237–309.http://dx.doi.org/10.1023/A:1005364332007Borg, Emma. 2007. ‘Minimalism versus contextualism in semantics’. In Gerhard Preyer & Georg Peter (eds. ‘Context-Sensitivity and Semantic Minimalism’, pp. 339–359. Oxford: Oxford University Press.Cappelen, Herman & Lepore, Ernest. 1997. ‘On an Alleged Connection between Indirect Quotation and Semantic Theory’. Mind and Language 12: pp. 278–296.Cappelen, Herman & Lepore, Ernie. 2005. Insensitive Semantics. Oxford: Blackwell.http://dx.doi.org/10.1002/9780470755792Dekker, Paul. 2002. ‘Meaning and Use of Indefinite Expressions’. Journal of Logic, Language and Information 11: pp. 141–194.http://dx.doi.org/10.1023/A:1017575313451Dekker, Paul. 2004. ‘Grounding Dynamic Semantics’. In Anne Bezuidenhout & Marga Reimer (eds. ‘Descriptions and Beyond: An Interdisciplinary Collection of Essays on Definite and Indefinite Descriptions and other Related Phenomena’, Oxford: Oxford University Press.Dekker, Paul. 2007. ‘Optimal Inquisitive Discourse’. In Maria Aloni, Alastair Butler & Paul Dekker (eds. ‘Questions in Dynamic Semantics’, CRiSPI 17, pp. 83–101. Amsterdam: Elsevier.Frege, Gottlob. 1892. ‘Über Sinn und Bedeutung’. Zeitschrift für Philosophie und philosophische Kritik NF 100: pp. 25–50.Ginzburg, Jonathan. 1995. ‘Resolving Questions, I & II’. Linguistics and Philosophy 18, no. 5,6: pp. 459–527 and 567–609.Ginzburg, Jonathan. To appear. The Interactive Stance: Meaning for Conversation. Oxford: Oxford University Press.Groenendijk, Jeroen. 1999. ‘The Logic of Interrogation’. In T. Matthews & D. Strolovitch (eds. ‘Proceedings of SALT IX’, Also appeared in Aloni, M., Butler, A., and Dekker, P., 2007, Questions in Dynamic Semantics, CRiSPI, Elsevier.: CLC Publications.Groenendijk, Jeroen & Roelofsen, Floris. 2009. ‘Inquisitive Semantics and Pragmatics’. In Jesus M. Larrazabal & Larraitz Zubeldia (eds. ‘Meaning, Content, and Argument: Proceedings of the ILCLI International Workshop on Semantics, Pragmatics, and Rhetoric’, Bilbao: University of the Basque Country Press.Groenendijk, Jeroen & Stokhof, Martin. 1991. ‘Dynamic Predicate Logic’. Linguistics and Philosophy 14, no. 1: pp. 39–100.http://dx.doi.org/10.1007/BF00628304Hulstijn, Joris. 1997. ‘Structured Information States. Raising and Resolving Issues’. In Anton Benz & Gerhard Jäger (eds. ‘Proceedings of MunDial97’, pp. 99–117. University of Munich.Jäger, Gerhard. 1996. ‘Only Updates. On the Dynamics of the Focus Particle only’. In Martin Stokhof & Paul Dekker (eds. ‘Proceedings of the Tenth Amsterdam Colloquium’, pp. 387–405. Amsterdam: ILLC, University of Amsterdam.Lascarides, Alex & Asher, Nicholas. 2009. ‘The Interpretation of Questions in Dialogue’. In Arndt Riester & Torgrim Solstad (eds. ‘Proceedings of Sinn und Bedeutung 13’,17–30. Stuttgart: IMS.Lewis, David. 1970. ‘General Semantics’. Synthese 22: 18–67.http://dx.doi.org/10.1007/BF00413598Montague, Richard. 1974. ‘English as a Formal Language’. In Richmond Thomason (ed. ‘Formal Philosophy. Selected papers of Richard Montague’, pp. 188–221. New Haven: Yale University Press. Originally published in Bruno Visentini (et al., 1970, Linguagginella Società e nella Tecnica, Edizioni di Comunità, Milan, pp. 189–224.Pagin, Peter & Pelletier, Francis Jeffry. 2007. ‘Content, context, and composition’. In Gerhard Preyer & Georg Peter (eds. ‘Context-Sensitivity and Semantic Minimalism’, pp. 25–62. Oxford: Oxford University Press. Original manuscript, 2006, with abstract: http://people.su.se/~ppagin/papers/jeffandpeter10.pdf.Partee, Barbara H. 1973. ‘Some transformational extensions of Montague grammar’. Journal of Philosophical Logic 2: 509–534.Partee, Barbara H. 2004. ‘Reflections of a Formal Semanticist’. In Barbara H. Partee (ed. ‘Compositionality in Formal Semantics’, Oxford: Blackwell.Partee, B.H. 1979. ‘Semantics — mathematics of psychology?’ In Rainer Bäuerle, Urs Egli & Arnim von Stechow (eds. ‘Semantics from different points of view’, pp. 1–14. Berlin: Springer-Verlag.Quine, Willard Van Orman. 1960. ‘Translation and Meaning’. In W.V.O. Quine (ed. ‘word and Object’, Cambridge: MIT Press.Quine, Willard Van Orman. 1987. ‘Indeterminacy of Translation again’. Journal of Philosophical Logic 84: 5–10.Recanati, François. 1994. ‘Contextualism and Anti-Contextualism in the Philosophy of Language’. In S. L. Tsohatzidis (ed. ‘Foundations of Speech Act Theory: Philosophical and Linguistic Perspectives’, London and New York: Routledge. Pp. 156–66.Recanati, François. 2005. ‘Literalism and contextualism: Some varieties’. In Gerhard Preyer & Georg Peter (eds. ‘Contextualism in Philosophy: Knowledge, Meaning, and Truth’, pp. 171–196. Oxford: Oxford University Press.Recanati, François. 2006. ‘Crazy Minimalism’. Mind and Language 21, no. 1: pp. 21–30. http://dx.doi.org/10.1111/j.1468-0017.2006.00303.xRoberts, Craige. 1996. ‘Information structure in discourse’. In J. H. Yoon & A. Kathol (eds. ‘Working Papers in Linguistics 49’, pp. 91–136. Ohio State University.Roberts, Craige. 2004. ‘Context in dynamic interpretation’. In Laurence Horn & Gregory Ward (eds. ‘Handbook of Contemporary Pragmatic Theory’, Blackwell.Stanley, Jason. 2005. ‘Semantics in context’. In Gerhard Preyer & Georg Peter (eds. ‘Contextualism in Philosophy: Knowledge, Meaning, and Truth’, pp. 221–253. Oxford: Oxford University Press.Stokhof, Martin. 2007. ‘Hand or Hammer’. The Journal of Indian Philosophy 35: pp. 597–626.http://dx.doi.org/10.1007/s10781-007-9023-7Tarski, Alfred. 1944. ‘The Semantic Conception of Truth and the Foundations of Semantics’. Philosophy and Phenomenological Research 4.Wittgenstein, Ludwig. 1922. Tractatus Logico-Philosophicus. Oxford: Routledge and Kegan. Originally appeared in 1921 as Logisch-Philosophische Abhandlung in the Annalen der Naturphilosophie, 14.Wittgenstein, Ludwig. 1953. Philosophische Untersuchungen/Philosophical Investigations. Oxford: Blackwell. Translation by G.E.M. Anscombe.

  17. Numerical Prediction of Combustion-induced Noise using a hybrid LES/CAA approach

    Science.gov (United States)

    Ihme, Matthias; Pitsch, Heinz; Kaltenbacher, Manfred

    2006-11-01

    Noise generation in technical devices is an increasingly important problem. Jet engines in particular produce sound levels that not only are a nuisance but may also impair hearing. The noise emitted by such engines is generated by different sources such as jet exhaust, fans or turbines, and combustion. Whereas the former acoustic mechanisms are reasonably well understood, combustion-generated noise is not. A methodology for the prediction of combustion-generated noise is developed. In this hybrid approach unsteady acoustic source terms are obtained from an LES and the propagation of pressure perturbations are obtained using acoustic analogies. Lighthill's acoustic analogy and a non-linear wave equation, accounting for variable speed of sound, have been employed. Both models are applied to an open diffusion flame. The effects on the far field pressure and directivity due to the variation of speed of sound are analyzed. Results for the sound pressure level will be compared with experimental data.

  18. Optimum design of brake friction material using hybrid entropy-GRA approach

    Directory of Open Access Journals (Sweden)

    Kumar Naresh

    2016-01-01

    Full Text Available The effect of Kevlar and natural fibres on the performance of brake friction materials was evaluated. Four friction material specimens were developed by varying the proportion of Kevlar and natural fibres. Two developed composite contained 5-10 wt.% of Kevlar fibre while in the other two the Kevlar fibre was replaced with same amount of natural fibre. SAE J661 protocol was used for the assessment of the tribological properties on a Chase testing machine. Result shows that the specimens containing Kevlar fibres shows higher friction and wear performance, whereas Kevlar replacement with natural fibre resulted in improved fade, recovery and friction fluctuations. Further hybrid entropy-GRA (grey relation analysis approach was applied to select the optimal friction materials using various performance defining attributes (PDA including friction, wear, fade, recovery, friction fluctuations and cost. The friction materials with 10 wt% of natural fibre exhibited the best overall quality.

  19. A Model Predictive Control Approach for Fuel Economy Improvement of a Series Hydraulic Hybrid Vehicle

    Directory of Open Access Journals (Sweden)

    Tri-Vien Vu

    2014-10-01

    Full Text Available This study applied a model predictive control (MPC framework to solve the cruising control problem of a series hydraulic hybrid vehicle (SHHV. The controller not only regulates vehicle velocity, but also engine torque, engine speed, and accumulator pressure to their corresponding reference values. At each time step, a quadratic programming problem is solved within a predictive horizon to obtain the optimal control inputs. The objective is to minimize the output error. This approach ensures that the components operate at high efficiency thereby improving the total efficiency of the system. The proposed SHHV control system was evaluated under urban and highway driving conditions. By handling constraints and input-output interactions, the MPC-based control system ensures that the system operates safely and efficiently. The fuel economy of the proposed control scheme shows a noticeable improvement in comparison with the PID-based system, in which three Proportional-Integral-Derivative (PID controllers are used for cruising control.

  20. A Hybrid dasymetric and machine learning approach to high-resolution residential electricity consumption modeling

    Energy Technology Data Exchange (ETDEWEB)

    Morton, April M [ORNL; Nagle, Nicholas N [ORNL; Piburn, Jesse O [ORNL; Stewart, Robert N [ORNL; McManamay, Ryan A [ORNL

    2017-01-01

    As urban areas continue to grow and evolve in a world of increasing environmental awareness, the need for detailed information regarding residential energy consumption patterns has become increasingly important. Though current modeling efforts mark significant progress in the effort to better understand the spatial distribution of energy consumption, the majority of techniques are highly dependent on region-specific data sources and often require building- or dwelling-level details that are not publicly available for many regions in the United States. Furthermore, many existing methods do not account for errors in input data sources and may not accurately reflect inherent uncertainties in model outputs. We propose an alternative and more general hybrid approach to high-resolution residential electricity consumption modeling by merging a dasymetric model with a complementary machine learning algorithm. The method s flexible data requirement and statistical framework ensure that the model both is applicable to a wide range of regions and considers errors in input data sources.

  1. Dual-acting of Hybrid Compounds - A New Dawn in the Discovery of Multi-target Drugs: Lead Generation Approaches.

    Science.gov (United States)

    Abdolmaleki, Azizeh; Ghasemi, Jahan B

    2017-01-01

    Finding high quality beginning compounds is a critical job at the start of the lead generation stage for multi-target drug discovery (MTDD). Designing hybrid compounds as selective multitarget chemical entity is a challenge, opportunity, and new idea to better act against specific multiple targets. One hybrid molecule is formed by two (or more) pharmacophore group's participation. So, these new compounds often exhibit two or more activities going about as multi-target drugs (mtdrugs) and may have superior safety or efficacy. Application of integrating a range of information and sophisticated new in silico, bioinformatics, structural biology, pharmacogenomics methods may be useful to discover/design, and synthesis of the new hybrid molecules. In this regard, many rational and screening approaches have followed by medicinal chemists for the lead generation in MTDD. Here, we review some popular lead generation approaches that have been used for designing multiple ligands (DMLs). This paper focuses on dual- acting chemical entities that incorporate a part of two drugs or bioactive compounds to compose hybrid molecules. Also, it presents some of key concepts and limitations/strengths of lead generation methods by comparing combination framework method with screening approaches. Besides, a number of examples to represent applications of hybrid molecules in the drug discovery are included. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  2. Evaluation of wind power generation potential using a three hybrid approach for households in Ardebil Province, Iran

    International Nuclear Information System (INIS)

    Qolipour, Mojtaba; Mostafaeipour, Ali; Shamshirband, Shahaboddin; Alavi, Omid; Goudarzi, Hossein; Petković, Dalibor

    2016-01-01

    Highlights: • Technical–economic feasibility of small wind turbines for six areas in Ardabil province of Iran was investigated. • Hybrid approach of Data Envelopment Analysis, Balanced Scorecard, and Game Theory was analyzed. • HOMER software was used for economic evaluation. • Technical–economic feasibility was studied using wind speed data during 2008–2014. • The areas of Airport, Nir, Namin, BilaSavar, Firozabad and Ardabil were ranked from first to last, respectively. - Abstract: The objective of the present paper is to conduct a thorough technical–economic evaluation for the construction of small wind turbines in six areas within Ardabil province of Iran using the Hybrid Optimization of Multiple Energy Resources software, and also to rank these areas by a hybrid approach composed of Data Envelopment Analysis, Balanced Scorecard, and Game Theory methodologies. Higher accuracy of the proposed hybrid approach and its ability to properly detect the relationships between the decision-making components make it preferable over the simple Data Envelopment Analysis method. Technical–economic feasibility study is conducted by analyzing wind speed data for period from 2008 to 2014 using Hybrid Optimization of Multiple Energy Resources software. In the next step, the type of equipment used in the design, benefit, costs, total net costs, depreciation and amount of generated electricity are obtained separately for each location. The results show that; Airport, Nir, Namin, Bilasavar, Firozabad and Ardabil were rank first to last respectively.

  3. Improved Wetland Classification Using Eight-Band High Resolution Satellite Imagery and a Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Charles R. Lane

    2014-12-01

    Full Text Available Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of wetland maps derived with moderate resolution imagery and traditional techniques have been limited and often unsatisfactory. We explored and evaluated the utility of a newly launched high-resolution, eight-band satellite system (Worldview-2; WV2 for identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta of Lake Baikal, Russia, using a hybrid approach and a novel application of Indicator Species Analysis (ISA. We achieved an overall classification accuracy of 86.5% (Kappa coefficient: 0.85 for 22 classes of aquatic and wetland habitats and found that additional metrics, such as the Normalized Difference Vegetation Index and image texture, were valuable for improving the overall classification accuracy and particularly for discriminating among certain habitat classes. Our analysis demonstrated that including WV2’s four spectral bands from parts of the spectrum less commonly used in remote sensing analyses, along with the more traditional bandwidths, contributed to the increase in the overall classification accuracy by ~4% overall, but with considerable increases in our ability to discriminate certain communities. The coastal band improved differentiating open water and aquatic (i.e., vegetated habitats, and the yellow, red-edge, and near-infrared 2 bands improved discrimination among different vegetated aquatic and terrestrial habitats. The use of ISA provided statistical rigor in developing associations between spectral classes and field-based data. Our analyses demonstrated the utility of a hybrid approach and the benefit of additional bands and metrics in providing the first spatially explicit mapping of a large and heterogeneous wetland system.

  4. Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

    Science.gov (United States)

    Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

    2015-01-01

    The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

  5. A hybrid wavelet transform based short-term wind speed forecasting approach.

    Science.gov (United States)

    Wang, Jujie

    2014-01-01

    It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China's wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

  6. A HYBRID GENETIC ALGORITHM-NEURAL NETWORK APPROACH FOR PRICING CORES AND REMANUFACTURED CORES

    Directory of Open Access Journals (Sweden)

    M. Seidi

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT:Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. Remanufacturing is an industrial process that makes used products reusable. One of the important aspects in both reverse logistics and remanufacturing is the pricing of returned and remanufactured products (called cores. In this paper, we focus on pricing the cores and remanufactured cores. First we present a mathematical model for this purpose. Since this model does not satisfy our requirements, we propose a simulation optimisation approach. This approach consists of a hybrid genetic algorithm based on a neural network employed as the fitness function. We use automata learning theory to obtain the learning rate required for training the neural network. Numerical results demonstrate that the optimal value of the acquisition price of cores and price of remanufactured cores is obtained by this approach.

    AFRIKAANSE OPSOMMING: Volhoubaarheid het ‘n belangrike saak geword in die meeste ekonomieë, wat verskeie maatskappye genoop het om produkherwinning en omgekeerde logistiek te onder oë te neem. Hervervaardiging is ‘n industriële proses wat gebruikte produkte weer bruikbaar maak. Een van die belangrike aspekte in beide omgekeerde logistiek en hervervaardiging is die prysbepaling van herwinne en hervervaardigde produkte. Hierdie artikel fokus op die prysbepalingsaspekte by wyse van ‘n wiskundige model.

  7. Infrared exploration of the architectural heritage: from passive infrared thermography to hybrid infrared thermography (HIRT approach

    Directory of Open Access Journals (Sweden)

    Sfarra, S.

    2016-09-01

    Full Text Available Up to now, infrared thermographic approaches have been considered either passive or active. In the latter case, the heat flux is historically attributed to a non-natural heat source. The use of the sun has recently been incorporated into the active approach thanks to multi-temporal inspections. In this paper, an innovative hybrid thermographic (HIRT approach is illustrated. It combines both the time component and the solar source to obtain quantitative information such as the defect depth. Thermograms were obtained by inspecting the facade of the Santa Maria Collemaggio church (L’Aquila, Italy, whereas quantitative results related to the sub-superficial discontinuities were obtained thanks to the use of advanced techniques. Experimental results linked to passive approach (i.e., the mosaicking procedure of the thermograms performed by selecting a set of historic churches are also included in order to explain, when and where, the hybrid procedure should be used.Hasta la fecha, los enfoques sobre la termografía infrarroja han sido considerados, o pasivos, o activos. En este último caso, el flujo de calor se obtiene a través de una fuente de calor no natural. El uso de energía solar ha sido recientemente incorporado al enfoque activo gracias a los estudios multitemporales. En este trabajo, se ilustra un enfoque innovador de la termografía híbrida (HIRT. Se combina tanto el componente de tiempo y la fuente de energía solar para recuperar la información cuantitativa así como la profundidad del defecto. Las imágenes térmicas se obtuvieron mediante el análisis de la fachada de la Iglesia de Santa María Collemaggio (L’Aquila, Italia, mientras que los resultados cuantitativos inherentes a las discontinuidades sub-superficiales se obtuvieron gracias al uso de otras técnicas avanzadas. Los resultados experimentales vinculados al enfoque pasivo (es decir, el proceso de mosaico de las imágenes térmicas derivan de un conjunto de Iglesias

  8. Incorporating historical information in biosimilar trials: Challenges and a hybrid Bayesian-frequentist approach.

    Science.gov (United States)

    Mielke, Johanna; Schmidli, Heinz; Jones, Byron

    2018-05-01

    For the approval of biosimilars, it is, in most cases, necessary to conduct large Phase III clinical trials in patients to convince the regulatory authorities that the product is comparable in terms of efficacy and safety to the originator product. As the originator product has already been studied in several trials beforehand, it seems natural to include this historical information into the showing of equivalent efficacy. Since all studies for the regulatory approval of biosimilars are confirmatory studies, it is required that the statistical approach has reasonable frequentist properties, most importantly, that the Type I error rate is controlled-at least in all scenarios that are realistic in practice. However, it is well known that the incorporation of historical information can lead to an inflation of the Type I error rate in the case of a conflict between the distribution of the historical data and the distribution of the trial data. We illustrate this issue and confirm, using the Bayesian robustified meta-analytic-predictive (MAP) approach as an example, that simultaneously controlling the Type I error rate over the complete parameter space and gaining power in comparison to a standard frequentist approach that only considers the data in the new study, is not possible. We propose a hybrid Bayesian-frequentist approach for binary endpoints that controls the Type I error rate in the neighborhood of the center of the prior distribution, while improving the power. We study the properties of this approach in an extensive simulation study and provide a real-world example. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. A hybrid life cycle and multi-criteria decision analysis approach for identifying sustainable development strategies of Beijing's taxi fleet

    International Nuclear Information System (INIS)

    Cai, Yanpeng; Applegate, Scott; Yue, Wencong; Cai, Jianying; Wang, Xuan; Liu, Gengyuan; Li, Chunhui

    2017-01-01

    To identify and evaluate sustainable strategies of taxi fleet in Beijing in terms of economic, policy, and environmental implications, a hybrid approach was developed through incorporating multi-criteria decision analysis (MCDA) methods within a general life-cycle analysis (LCA) framework. The approach can (a) help comprehensive evaluate environmental impacts of multiple types of vehicles, (b) facilitate analysis of environmental, economic and policy features of such vehicles, and (c) identify desirable taxi fleet development strategies for the city. The developed approach represented an improvement of the decision-making capability for taxi implementation based on multiple available technologies and their performance that can be specifically tailored to Beijing. The results demonstrated that the proposed approach could comprehensively reflect multiple implications of strategies for the taxi fleet in Beijing to reduce air pollution in the city. The results also indicated that the electric vehicle powered with the year 2020 electricity projections would be the ideal solution, outranking the other alternatives. The conventional vehicle ranked the lowest among the alternatives. The plug-in hybrid vehicle powered by 2020 electricity projects ranked the third, followed by the plug-in hybrid vehicle ranking the fourth, and the hybrid vehicle ranking the fifth. - Highlights: • An hybrid approach was proposed for evaluating sustainable strategies of Beijing's taxi fleet. • This approach was based on the combination of multi-criteria decision analysis methods and life-cycle assessment. • Environmental, economic and policy performances of multiple strategies were compared. • Detailed responses of taxi drivers and local residents were interviewed. • The electric vehicle would be the ideal solution for Beijing Taxi fleet.

  10. CO-OP JIGSAW TEAM PROJECTS: A COOPERATIVE TEACHING METHOD TO IMPROVE STUDENTS‘ SPEAKING SKILL (An Experimental Study in a Senior High School

    Directory of Open Access Journals (Sweden)

    Diaz Innova Citra Arum

    2017-12-01

    Full Text Available An effective speaking activity involves active students to participate and create a life communication. The ideal condition of English speaking class involves the students‘ effectiveness in participating teaching and learning process. Nevertheless, some problems are emerged and one of them is that they often get nervous to speak in front of many people when they are asked to present their work to their friends. This paper reveals an experiment study in teaching speaking in a senior high school in Lamongan, East Java. It discusses about the effectiveness of cooperative teaching method known as coop jigsaw team projects in teaching speaking. All tenth grade students were used as the population and eighty students were taken as sample being divided into experimental group taught using coop jigsaw team projects and control group taught using direct instruction. Cluster random sampling was applied as the technique to determine sample. To obtain the data of students‘ speaking score, a speaking test was conducted. The score was the average score resulted by two independent examiners. The data were analysed through descriptive and inferential analysis using two-sample t-test. The research hypothesised that coop jigsaw will result a better English speaking score rather than direct instruction method. The research finding using 95% significance level shows that coop jigsaw team projects was more effective in teaching speaking compared to direct instruction for the tenth grade students because the activities in coop jigsaw team project pushed the students to be more active and cooperative in learning speaking.

  11. Hybrid Air Quality Modeling Approach for use in the Hear-road Exposures to Urban air pollutant Study(NEXUS)

    Science.gov (United States)

    The paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associa...

  12. A hybrid regional approach to model discharge at multiple sub-basins within the Calapooia Watershed, Oregon, USA

    Science.gov (United States)

    Modeling is a useful tool for quantifying ecosystem services and understanding their temporal dynamics. Here we describe a hybrid regional modeling approach for sub-basins of the Calapooia watershed that incorporates both a precipitation-runoff model and an indexed regression mo...

  13. Comparing Hybrid Learning with Traditional Approaches on Learning the Microsoft Office Power Point 2003 Program in Tertiary Education

    Science.gov (United States)

    Vernadakis, Nikolaos; Antoniou, Panagiotis; Giannousi, Maria; Zetou, Eleni; Kioumourtzoglou, Efthimis

    2011-01-01

    The purpose of this study was to determine the effectiveness of a hybrid learning approach to deliver a computer science course concerning the Microsoft office PowerPoint 2003 program in comparison to delivering the same course content in the form of traditional lectures. A hundred and seventy-two first year university students were randomly…

  14. Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

    DEFF Research Database (Denmark)

    Shuai, Hang; Ai, Xiaomeng; Wen, Jinyu

    2017-01-01

    This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future...

  15. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.

    Science.gov (United States)

    Murat, Miraemiliana; Chang, Siow-Wee; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

    2017-01-01

    Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99

  16. Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

    Science.gov (United States)

    Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.

    2017-11-01

    The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general

  17. A hybrid deterministic-probabilistic approach to model the mechanical response of helically arranged hierarchical strands

    Science.gov (United States)

    Fraldi, M.; Perrella, G.; Ciervo, M.; Bosia, F.; Pugno, N. M.

    2017-09-01

    Very recently, a Weibull-based probabilistic strategy has been successfully applied to bundles of wires to determine their overall stress-strain behaviour, also capturing previously unpredicted nonlinear and post-elastic features of hierarchical strands. This approach is based on the so-called "Equal Load Sharing (ELS)" hypothesis by virtue of which, when a wire breaks, the load acting on the strand is homogeneously redistributed among the surviving wires. Despite the overall effectiveness of the method, some discrepancies between theoretical predictions and in silico Finite Element-based simulations or experimental findings might arise when more complex structures are analysed, e.g. helically arranged bundles. To overcome these limitations, an enhanced hybrid approach is proposed in which the probability of rupture is combined with a deterministic mechanical model of a strand constituted by helically-arranged and hierarchically-organized wires. The analytical model is validated comparing its predictions with both Finite Element simulations and experimental tests. The results show that generalized stress-strain responses - incorporating tension/torsion coupling - are naturally found and, once one or more elements break, the competition between geometry and mechanics of the strand microstructure, i.e. the different cross sections and helical angles of the wires in the different hierarchical levels of the strand, determines the no longer homogeneous stress redistribution among the surviving wires whose fate is hence governed by a "Hierarchical Load Sharing" criterion.

  18. A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings.

    Science.gov (United States)

    Liu, Jie; Hu, Youmin; Wu, Bo; Wang, Yan; Xie, Fengyun

    2017-05-18

    The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD). Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features' information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components.

  19. A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings

    Directory of Open Access Journals (Sweden)

    Jie Liu

    2017-05-01

    Full Text Available The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD. Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features’ information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components.

  20. A hybrid modelling approach to develop scenarios for China's carbon dioxide emissions to 2050

    International Nuclear Information System (INIS)

    Gambhir, Ajay; Schulz, Niels; Napp, Tamaryn; Tong, Danlu; Munuera, Luis; Faist, Mark; Riahi, Keywan

    2013-01-01

    This paper describes a hybrid modelling approach to assess the future development of China's energy system, for both a “hypothetical counterfactual baseline” (HCB) scenario and low carbon (“abatement”) scenarios. The approach combines a technology-rich integrated assessment model (MESSAGE) of China's energy system with a set of sector-specific, bottom-up, energy demand models for the transport, buildings and industrial sectors developed by the Grantham Institute for Climate Change at Imperial College London. By exploring technology-specific solutions in all major sectors of the Chinese economy, we find that a combination of measures, underpinned by low-carbon power options based on a mix of renewables, nuclear and carbon capture and storage, would fundamentally transform the Chinese energy system, when combined with increasing electrification of demand-side sectors. Energy efficiency options in these demand sectors are also important. - Highlights: • Combining energy supply and demand models reveals low-carbon technology choices across China's economy. • China could reduce its CO 2 emissions to close to 3 Gt in 2050, costing around 2% of GDP. • Decarbonising the power sector underpins the energy system transformation. • Electrification of industrial processes, building heating and transport is required. • Energy efficiency across the demand side is also important

  1. A Two-Step Hybrid Approach for Modeling the Nonlinear Dynamic Response of Piezoelectric Energy Harvesters

    Directory of Open Access Journals (Sweden)

    Claudio Maruccio

    2018-01-01

    Full Text Available An effective hybrid computational framework is described here in order to assess the nonlinear dynamic response of piezoelectric energy harvesting devices. The proposed strategy basically consists of two steps. First, fully coupled multiphysics finite element (FE analyses are performed to evaluate the nonlinear static response of the device. An enhanced reduced-order model is then derived, where the global dynamic response is formulated in the state-space using lumped coefficients enriched with the information derived from the FE simulations. The electromechanical response of piezoelectric beams under forced vibrations is studied by means of the proposed approach, which is also validated by comparing numerical predictions with some experimental results. Such numerical and experimental investigations have been carried out with the main aim of studying the influence of material and geometrical parameters on the global nonlinear response. The advantage of the presented approach is that the overall computational and experimental efforts are significantly reduced while preserving a satisfactory accuracy in the assessment of the global behavior.

  2. Multimodal Logistics Network Design over Planning Horizon through a Hybrid Meta-Heuristic Approach

    Science.gov (United States)

    Shimizu, Yoshiaki; Yamazaki, Yoshihiro; Wada, Takeshi

    Logistics has been acknowledged increasingly as a key issue of supply chain management to improve business efficiency under global competition and diversified customer demands. This study aims at improving a quality of strategic decision making associated with dynamic natures in logistics network optimization. Especially, noticing an importance to concern with a multimodal logistics under multiterms, we have extended a previous approach termed hybrid tabu search (HybTS). The attempt intends to deploy a strategic planning more concretely so that the strategic plan can link to an operational decision making. The idea refers to a smart extension of the HybTS to solve a dynamic mixed integer programming problem. It is a two-level iterative method composed of a sophisticated tabu search for the location problem at the upper level and a graph algorithm for the route selection at the lower level. To keep efficiency while coping with the resulting extremely large-scale problem, we invented a systematic procedure to transform the original linear program at the lower-level into a minimum cost flow problem solvable by the graph algorithm. Through numerical experiments, we verified the proposed method outperformed the commercial software. The results indicate the proposed approach can make the conventional strategic decision much more practical and is promising for real world applications.

  3. Covercrete with hybrid functions - A novel approach to durable reinforced concrete structures

    Energy Technology Data Exchange (ETDEWEB)

    Tang, L.; Zhang, E.Q. [Chalmers University of Technology, SE-412 96 Gothenburg (Sweden); Fu, Y. [KTH Royal Institute of Technology, SE-106 91 Stockholm (Sweden); Schouenborg, B.; Lindqvist, J.E. [CBI Swedish Cement and Concrete Research Institute, c/o SP, Box 857, SE-501 15 Boraas (Sweden)

    2012-12-15

    Due to the corrosion of steel in reinforced concrete structures, the concrete with low water-cement ratio (w/c), high cement content, and large cover thickness is conventionally used for prolonging the passivation period of steel. Obviously, this conventional approach to durable concrete structures is at the sacrifice of more CO{sub 2} emission and natural resources through consuming higher amount of cement and more constituent materials, which is against sustainability. By placing an economically affordable conductive mesh made of carbon fiber or conductive polymer fiber in the near surface zone of concrete acting as anode we can build up a cathodic prevention system with intermittent low current density supplied by, e.g., the solar cells. In such a way, the aggressive negative ions such as Cl{sup -}, CO{sub 3}{sup 2-}, and SO{sub 4}{sup 2-} can be stopped near the cathodic (steel) zone. Thus the reinforcement steel is prevented from corrosion even in the concrete with relatively high w/c and small cover thickness. This conductive mesh functions not only as electrode, but also as surface reinforcement to prevent concrete surface from cracking. Therefore, this new type of covercrete has hybrid functions. This paper presents the theoretical analysis of feasibility of this approach and discusses the potential durability problems and possible solutions to the potential problems. (Copyright copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  4. A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

    Science.gov (United States)

    Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

    2015-06-01

    The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

  5. Developing hybrid approaches to predict pKa values of ionizable groups

    Science.gov (United States)

    Witham, Shawn; Talley, Kemper; Wang, Lin; Zhang, Zhe; Sarkar, Subhra; Gao, Daquan; Yang, Wei

    2011-01-01

    Accurate predictions of pKa values of titratable groups require taking into account all relevant processes associated with the ionization/deionization. Frequently, however, the ionization does not involve significant structural changes and the dominating effects are purely electrostatic in origin allowing accurate predictions to be made based on the electrostatic energy difference between ionized and neutral forms alone using a static structure. On another hand, if the change of the charge state is accompanied by a structural reorganization of the target protein, then the relevant conformational changes have to be taken into account in the pKa calculations. Here we report a hybrid approach that first predicts the titratable groups, which ionization is expected to cause conformational changes, termed “problematic” residues, then applies a special protocol on them, while the rest of the pKa’s are predicted with rigid backbone approach as implemented in multi-conformation continuum electrostatics (MCCE) method. The backbone representative conformations for “problematic” groups are generated with either molecular dynamics simulations with charged and uncharged amino acid or with ab-initio local segment modeling. The corresponding ensembles are then used to calculate the pKa of the “problematic” residues and then the results are averaged. PMID:21744395

  6. Hybrid approaches to clinical trial monitoring: Practical alternatives to 100% source data verification

    Directory of Open Access Journals (Sweden)

    Sourabh De

    2011-01-01

    Full Text Available For years, a vast majority of clinical trial industry has followed the tenet of 100% source data verification (SDV. This has been driven partly by the overcautious approach to linking quality of data to the extent of monitoring and SDV and partly by being on the safer side of regulations. The regulations however, do not state any upper or lower limits of SDV. What it expects from researchers and the sponsors is methodologies which ensure data quality. How the industry does it is open to innovation and application of statistical methods, targeted and remote monitoring, real time reporting, adaptive monitoring schedules, etc. In short, hybrid approaches to monitoring. Coupled with concepts of optimum monitoring and SDV at site and off-site monitoring techniques, it should be possible to save time required to conduct SDV leading to more available time for other productive activities. Organizations stand to gain directly or indirectly from such savings, whether by diverting the funds back to the R&D pipeline; investing more in technology infrastructure to support large trials; or simply increasing sample size of trials. Whether it also affects the work-life balance of monitors who may then need to travel with a less hectic schedule for the same level of quality and productivity can be predicted only when there is more evidence from field.

  7. Hybrid approaches to clinical trial monitoring: Practical alternatives to 100% source data verification.

    Science.gov (United States)

    De, Sourabh

    2011-07-01

    For years, a vast majority of clinical trial industry has followed the tenet of 100% source data verification (SDV). This has been driven partly by the overcautious approach to linking quality of data to the extent of monitoring and SDV and partly by being on the safer side of regulations. The regulations however, do not state any upper or lower limits of SDV. What it expects from researchers and the sponsors is methodologies which ensure data quality. How the industry does it is open to innovation and application of statistical methods, targeted and remote monitoring, real time reporting, adaptive monitoring schedules, etc. In short, hybrid approaches to monitoring. Coupled with concepts of optimum monitoring and SDV at site and off-site monitoring techniques, it should be possible to save time required to conduct SDV leading to more available time for other productive activities. Organizations stand to gain directly or indirectly from such savings, whether by diverting the funds back to the R&D pipeline; investing more in technology infrastructure to support large trials; or simply increasing sample size of trials. Whether it also affects the work-life balance of monitors who may then need to travel with a less hectic schedule for the same level of quality and productivity can be predicted only when there is more evidence from field.

  8. A New Hybrid Approach for Augmented Reality Maintenance in Scientific Facilities

    Directory of Open Access Journals (Sweden)

    Héctor Martínez

    2013-09-01

    Full Text Available Maintenance in scientific facilities is a difficult issue, especially in large and hazardous facilities, due to the complexity of tasks and equipment. Augmented reality is a technology that has already shown great promise in the maintenance field. With the help of augmented reality applications, maintenance tasks can be carried out faster and more safely. The problem with current applications is that they are small-scale prototypes that do not easily scale to large facility maintenance applications. This paper presents a new hybrid approach that enables the creation of augmented reality maintenance applications for large and hazardous scientific facilities. In this paper, a new augmented reality marker and the algorithm for its recognition is proposed. The performance of the algorithm is verified in three test cases, showing promising results in two of them. Improvements in robustness in the third test case in which the camera is moving quickly or when light conditions are extreme are subject to further studies. The proposed new approach will be integrated into an existing augmented reality maintenance system.

  9. A hybrid stochastic approach for self-location of wireless sensors in indoor environments.

    Science.gov (United States)

    Lloret, Jaime; Tomas, Jesus; Garcia, Miguel; Canovas, Alejandro

    2009-01-01

    Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS) in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

  10. A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments

    Directory of Open Access Journals (Sweden)

    Alejandro Canovas

    2009-05-01

    Full Text Available Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

  11. “ELEPHANT TRUNK” AND ENDOVASCULAR STENTGRAFTING – A HYBRID APPROACH TO THE TREATMENT OF EXTENSIVE THORACIC AORTIC ANEURYSM

    Directory of Open Access Journals (Sweden)

    Tomáš Holubec

    2013-01-01

    Full Text Available A hybrid approach to elephant trunk technique for treatment of thoracic aortic aneurysms combines a conventional surgical and endovascular therapy. Compared to surgery alone, there is a presumption that mortality and morbidity is reduced. We present a case report of a 42-year-old man with a giant aneurysm of the entire thoracic aorta, significant aortic and tricuspid regurgitation and ventricular septum defect. The patient underwent multiple consecutive operations and interventions having, among others, finally replaced the entire thoracic aorta with the use of the hybrid elephant trunk technique.

  12. Innovative molecular approach to the identification of Colossoma macropomum and its hybrids

    Directory of Open Access Journals (Sweden)

    Fátima Gomes

    2012-06-01

    Full Text Available Tambaqui (Colossoma macropomum is the fish species most commonly raised in the Brazilian fish farms. The species is highly adaptable to captive conditions, and is both fast-growing and relatively fecund. In recent years, artificial breeding has produced hybrids with Characiform species, known as "Tambacu" and "Tambatinga". Identifying hybrids is a difficult process, given their morphological similarities with the parent species. This study presents an innovative molecular approach to the identification of hybrids based primarily on Multiplex PCR of a nuclear gene (α-Tropomyosin, which was tested on 93 specimens obtained from fish farms in northern Brazil. The sequencing of a 505-bp fragment of the Control Region (CR permitted the identification of the maternal lineage of the specimen, all of which corresponded to C. macropomum. Unexpectedly, only two CR haplotype were found in 93 samples, a very low genetic diversity for the pisciculture of Tambaqui. Multiplex PCR identified 42 hybrids, in contrast with 23 identified by the supplier on the basis of external morphology. This innovative tool has considerable potential for the development of the Brazilian aquaculture, given the possibility of the systematic identification of the genetic traits of both fry-producing stocks, and the fry and juveniles raised in farms.O Tambaqui (Colossoma macropomum é a espécie de peixe mais comumente cultivada em pisciculturas no Brasil. A espécie é altamente adaptada às condições de cativeiro, apresentando rápido crescimento e alta fecundidade. Nos últimos anos tem ocorrido o cruzamento artificial entre espécies de Characiformes, produzindo os híbridos "Tambacu" e "Tambatinga". A identificação de híbridos é uma tarefa difícil, em virtude da grande similaridade morfológica entre as espécies parentais. O presente estudo apresenta uma abordagem molecular inovadora para identificação de híbridos com base em PCR Multiplex de um gene nuclear (

  13. Recent Development in Pulmonary Valve Replacement after Tetralogy of Fallot Repair: The Emergence of Hybrid Approaches

    Directory of Open Access Journals (Sweden)

    Tariq eSuleiman

    2015-06-01

    Full Text Available In the current era approximately 90% of infants born with tetralogy of Fallot (ToF are expected to live beyond 40 years of age making it the fastest growing population amongst patients with congenital heart disease. One of the most common late consequences after repair of ToF, is pulmonary valve regurgitation (PVR. Significant PVR results in progressive dilatation and dysfunction of the right ventricle, decrease in exercise tolerance, arrhythmias, heart failure, and increased risk of sudden death. The conventional approach of dealing with this problem is to perform pulmonary valve replacement using cardiopulmonary bypass (CPB and cardioplegic arrest. However, this approach is associated not only with long operative times but also side effects related to the use of CPB. Development of percutaneous approaches to valve disease is one of the most exciting areas of research and clinical innovation in cardiovascular research. The main development has been that of transcatheter pulmonary valve replacement for the rehabilitation of conduits between the right ventricle and pulmonary artery in patients after surgery for ToF. However, with the percutaneous technique, a limited size of prosthesis can be inserted. Moreover, the technique does not offer the opportunity of treating additional defects that are frequently associated with severe PR, such as pulmonary artery dilatation, and it cannot be used in the significantly dilated native right ventricular outlet tract (RVOT. The advent of the hybrid surgical options for treating cardiac disease has integrated the techniques of interventional cardiology with the techniques of cardiac surgery to provide a form of therapy that combines the respective strengths of both fields.In this review, we present and compare recent advances in procedures to replace the pulmonary valve in patients with ToF presenting with severe PVR and dilated RVOT.

  14. A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.

    Science.gov (United States)

    Xue, Xiaoming; Zhou, Jianzhong

    2017-01-01

    To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  15. A hybrid agent-based computational economics and optimization approach for supplier selection problem

    Directory of Open Access Journals (Sweden)

    Zahra Pourabdollahi

    2017-12-01

    Full Text Available Supplier evaluation and selection problem is among the most important of logistics decisions that have been addressed extensively in supply chain management. The same logistics decision is also important in freight transportation since it identifies trade relationships between business establishments and determines commodity flows between production and consumption points. The commodity flows are then used as input to freight transportation models to determine cargo movements and their characteristics including mode choice and shipment size. Various approaches have been proposed to explore this latter problem in previous studies. Traditionally, potential suppliers are evaluated and selected using only price/cost as the influential criteria and the state-of-practice methods. This paper introduces a hybrid agent-based computational economics and optimization approach for supplier selection. The proposed model combines an agent-based multi-criteria supplier evaluation approach with a multi-objective optimization model to capture both behavioral and economical aspects of the supplier selection process. The model uses a system of ordered response models to determine importance weights of the different criteria in supplier evaluation from a buyers’ point of view. The estimated weights are then used to calculate a utility for each potential supplier in the market and rank them. The calculated utilities are then entered into a mathematical programming model in which best suppliers are selected by maximizing the total accrued utility for all buyers and minimizing total shipping costs while balancing the capacity of potential suppliers to ensure market clearing mechanisms. The proposed model, herein, was implemented under an operational agent-based supply chain and freight transportation framework for the Chicago Metropolitan Area.

  16. A novel approach for fire recognition using hybrid features and manifold learning-based classifier

    Science.gov (United States)

    Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

    2018-03-01

    Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

  17. Super-resolution nanofabrication with metal-ion doped hybrid material through an optical dual-beam approach

    International Nuclear Information System (INIS)

    Cao, Yaoyu; Li, Xiangping; Gu, Min

    2014-01-01

    We apply an optical dual-beam approach to a metal-ion doped hybrid material to achieve nanofeatures beyond the optical diffraction limit. By spatially inhibiting the photoreduction and the photopolymerization, we realize a nano-line, consisting of polymer matrix and in-situ generated gold nanoparticles, with a lateral size of sub 100 nm, corresponding to a factor of 7 improvement compared to the diffraction limit. With the existence of gold nanoparticles, a plasmon enhanced super-resolution fabrication mechanism in the hybrid material is observed, which benefits in a further reduction in size of the fabricated feature. The demonstrated nanofeature in hybrid materials paves the way for realizing functional nanostructures

  18. A New Hybrid Approach for Wind Speed Prediction Using Fast Block Least Mean Square Algorithm and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Ummuhan Basaran Filik

    2016-01-01

    Full Text Available A new hybrid wind speed prediction approach, which uses fast block least mean square (FBLMS algorithm and artificial neural network (ANN method, is proposed. FBLMS is an adaptive algorithm which has reduced complexity with a very fast convergence rate. A hybrid approach is proposed which uses two powerful methods: FBLMS and ANN method. In order to show the efficiency and accuracy of the proposed approach, seven-year real hourly collected wind speed data sets belonging to Turkish State Meteorological Service of Bozcaada and Eskisehir regions are used. Two different ANN structures are used to compare with this approach. The first six-year data is handled as a train set; the remaining one-year hourly data is handled as test data. Mean absolute error (MAE and root mean square error (RMSE are used for performance evaluations. It is shown for various cases that the performance of the new hybrid approach gives better results than the different conventional ANN structure.

  19. Deterministic linear-optics quantum computing based on a hybrid approach

    International Nuclear Information System (INIS)

    Lee, Seung-Woo; Jeong, Hyunseok

    2014-01-01

    We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources

  20. Deterministic linear-optics quantum computing based on a hybrid approach

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung-Woo; Jeong, Hyunseok [Center for Macroscopic Quantum Control, Department of Physics and Astronomy, Seoul National University, Seoul, 151-742 (Korea, Republic of)

    2014-12-04

    We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources.

  1. Physical and JIT Model Based Hybrid Modeling Approach for Building Thermal Load Prediction

    Science.gov (United States)

    Iino, Yutaka; Murai, Masahiko; Murayama, Dai; Motoyama, Ichiro

    Energy conservation in building fields is one of the key issues in environmental point of view as well as that of industrial, transportation and residential fields. The half of the total energy consumption in a building is occupied by HVAC (Heating, Ventilating and Air Conditioning) systems. In order to realize energy conservation of HVAC system, a thermal load prediction model for building is required. This paper propose a hybrid modeling approach with physical and Just-in-Time (JIT) model for building thermal load prediction. The proposed method has features and benefits such as, (1) it is applicable to the case in which past operation data for load prediction model learning is poor, (2) it has a self checking function, which always supervises if the data driven load prediction and the physical based one are consistent or not, so it can find if something is wrong in load prediction procedure, (3) it has ability to adjust load prediction in real-time against sudden change of model parameters and environmental conditions. The proposed method is evaluated with real operation data of an existing building, and the improvement of load prediction performance is illustrated.

  2. A Hybrid Information Mining Approach for Knowledge Discovery in Cardiovascular Disease (CVD

    Directory of Open Access Journals (Sweden)

    Stefania Pasanisi

    2018-04-01

    Full Text Available The healthcare ambit is usually perceived as “information rich” yet “knowledge poor”. Nowadays, an unprecedented effort is underway to increase the use of business intelligence techniques to solve this problem. Heart disease (HD is a major cause of mortality in modern society. This paper analyzes the risk factors that have been identified in cardiovascular disease (CVD surveillance systems. The Heart Care study identifies attributes related to CVD risk (gender, age, smoking habit, etc. and other dependent variables that include a specific form of CVD (diabetes, hypertension, cardiac disease, etc.. In this paper, we combine Clustering, Association Rules, and Neural Networks for the assessment of heart-event-related risk factors, targeting the reduction of CVD risk. With the use of the K-means algorithm, significant groups of patients are found. Then, the Apriori algorithm is applied in order to understand the kinds of relations between the attributes within the dataset, first looking within the whole dataset and then refining the results through the subsets defined by the clusters. Finally, both results allow us to better define patients’ characteristics in order to make predictions about CVD risk with a Multilayer Perceptron Neural Network. The results obtained with the hybrid information mining approach indicate that it is an effective strategy for knowledge discovery concerning chronic diseases, particularly for CVD risk.

  3. Online energy management strategy of fuel cell hybrid electric vehicles based on data fusion approach

    Science.gov (United States)

    Zhou, Daming; Al-Durra, Ahmed; Gao, Fei; Ravey, Alexandre; Matraji, Imad; Godoy Simões, Marcelo

    2017-10-01

    Energy management strategy plays a key role for Fuel Cell Hybrid Electric Vehicles (FCHEVs), it directly affects the efficiency and performance of energy storages in FCHEVs. For example, by using a suitable energy distribution controller, the fuel cell system can be maintained in a high efficiency region and thus saving hydrogen consumption. In this paper, an energy management strategy for online driving cycles is proposed based on a combination of the parameters from three offline optimized fuzzy logic controllers using data fusion approach. The fuzzy logic controllers are respectively optimized for three typical driving scenarios: highway, suburban and city in offline. To classify patterns of online driving cycles, a Probabilistic Support Vector Machine (PSVM) is used to provide probabilistic classification results. Based on the classification results of the online driving cycle, the parameters of each offline optimized fuzzy logic controllers are then fused using Dempster-Shafer (DS) evidence theory, in order to calculate the final parameters for the online fuzzy logic controller. Three experimental validations using Hardware-In-the-Loop (HIL) platform with different-sized FCHEVs have been performed. Experimental comparison results show that, the proposed PSVM-DS based online controller can achieve a relatively stable operation and a higher efficiency of fuel cell system in real driving cycles.

  4. A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products

    Directory of Open Access Journals (Sweden)

    Animesh Debnath

    2017-07-01

    Full Text Available Due to the increasing size of the population, society faces several challenges for sustainable and adequate agricultural production, quality, distribution, and food safety in the strategic project portfolio selection (SPPS. The initial adaptation of strategic portfolio management of genetically modified (GM Agro by-products (Ab-Ps is a huge challenge in terms of processing the agro food product supply-chain practices in an environmentally nonthreatening way. As a solution to the challenges, the socio-economic characteristics for SPPS of GM food purchasing scenarios are studied. Evaluation and selection of the GM agro portfolio management are the dynamic issues due to physical and immaterial criteria involving a hybrid multiple criteria decision making (MCDM approach, combining modified grey Decision-Making Trial and Evaluation Laboratory (DEMATEL, Multi-Attributive Border Approximation area Comparison (MABAC and sensitivity analysis. Evaluation criteria are grouped into social, differential and beneficial clusters, and the modified DEMATEL procedure is used to derive the criteria weights. The MABAC method is applied to rank the strategic project portfolios according to the aggregated preferences of decision makers (DMs. The usefulness of the proposed research framework is validated with a case study. The GM by-products are found to be the best portfolio. Moreover, this framework can unify the policies of agro technological improvement, corporate social responsibility (CSR and agro export promotion.

  5. An event driven hybrid identity management approach to privacy enhanced e-health.

    Science.gov (United States)

    Sánchez-Guerrero, Rosa; Almenárez, Florina; Díaz-Sánchez, Daniel; Marín, Andrés; Arias, Patricia; Sanvido, Fabio

    2012-01-01

    Credential-based authorization offers interesting advantages for ubiquitous scenarios involving limited devices such as sensors and personal mobile equipment: the verification can be done locally; it offers a more reduced computational cost than its competitors for issuing, storing, and verification; and it naturally supports rights delegation. The main drawback is the revocation of rights. Revocation requires handling potentially large revocation lists, or using protocols to check the revocation status, bringing extra communication costs not acceptable for sensors and other limited devices. Moreover, the effective revocation consent--considered as a privacy rule in sensitive scenarios--has not been fully addressed. This paper proposes an event-based mechanism empowering a new concept, the sleepyhead credentials, which allows to substitute time constraints and explicit revocation by activating and deactivating authorization rights according to events. Our approach is to integrate this concept in IdM systems in a hybrid model supporting delegation, which can be an interesting alternative for scenarios where revocation of consent and user privacy are critical. The delegation includes a SAML compliant protocol, which we have validated through a proof-of-concept implementation. This article also explains the mathematical model describing the event-based model and offers estimations of the overhead introduced by the system. The paper focus on health care scenarios, where we show the flexibility of the proposed event-based user consent revocation mechanism.

  6. A hybrid computational-experimental approach for automated crystal structure solution

    Science.gov (United States)

    Meredig, Bryce; Wolverton, C.

    2013-02-01

    Crystal structure solution from diffraction experiments is one of the most fundamental tasks in materials science, chemistry, physics and geology. Unfortunately, numerous factors render this process labour intensive and error prone. Experimental conditions, such as high pressure or structural metastability, often complicate characterization. Furthermore, many materials of great modern interest, such as batteries and hydrogen storage media, contain light elements such as Li and H that only weakly scatter X-rays. Finally, structural refinements generally require significant human input and intuition, as they rely on good initial guesses for the target structure. To address these many challenges, we demonstrate a new hybrid approach, first-principles-assisted structure solution (FPASS), which combines experimental diffraction data, statistical symmetry information and first-principles-based algorithmic optimization to automatically solve crystal structures. We demonstrate the broad utility of FPASS to clarify four important crystal structure debates: the hydrogen storage candidates MgNH and NH3BH3; Li2O2, relevant to Li-air batteries; and high-pressure silane, SiH4.

  7. A hybrid approach to fault diagnosis of roller bearings under variable speed conditions

    Science.gov (United States)

    Wang, Yanxue; Yang, Lin; Xiang, Jiawei; Yang, Jianwei; He, Shuilong

    2017-12-01

    Rolling element bearings are one of the main elements in rotating machines, whose failure may lead to a fatal breakdown and significant economic losses. Conventional vibration-based diagnostic methods are based on the stationary assumption, thus they are not applicable to the diagnosis of bearings working under varying speeds. This constraint limits the bearing diagnosis to the industrial application significantly. A hybrid approach to fault diagnosis of roller bearings under variable speed conditions is proposed in this work, based on computed order tracking (COT) and variational mode decomposition (VMD)-based time frequency representation (VTFR). COT is utilized to resample the non-stationary vibration signal in the angular domain, while VMD is used to decompose the resampled signal into a number of band-limited intrinsic mode functions (BLIMFs). A VTFR is then constructed based on the estimated instantaneous frequency and instantaneous amplitude of each BLIMF. Moreover, the Gini index and time-frequency kurtosis are both proposed to quantitatively measure the sparsity and concentration measurement of time-frequency representation, respectively. The effectiveness of the VTFR for extracting nonlinear components has been verified by a bat signal. Results of this numerical simulation also show the sparsity and concentration of the VTFR are better than those of short-time Fourier transform, continuous wavelet transform, Hilbert-Huang transform and Wigner-Ville distribution techniques. Several experimental results have further demonstrated that the proposed method can well detect bearing faults under variable speed conditions.

  8. Nucleon polarizabilities from deuteron Compton scattering within a Green's function hybrid approach

    Energy Technology Data Exchange (ETDEWEB)

    Hildebrandt, R.P.; Hemmert, T.R. [Technische Universitaet Muenchen, Institut fuer Theoretische Physik (T39), Physik-Department, Garching (Germany); Griesshammer, H.W. [Technische Universitaet Muenchen, Institut fuer Theoretische Physik (T39), Physik-Department, Garching (Germany); Universitaet Erlangen-Nuernberg, Institut fuer Theoretische Physik III, Naturwissenschaftliche Fakultaet I, Erlangen (Germany); The George Washington University, Center for Nuclear Studies, Department of Physics, Washington DC (United States)

    2010-10-15

    We examine elastic Compton scattering from the deuteron for photon energies ranging from zero to 100MeV, using state-of-the-art deuteron wave functions and NN potentials. Nucleon-nucleon rescattering between emission and absorption of the two photons is treated by Green's functions in order to ensure gauge invariance and the correct Thomson limit. With this Green's function hybrid approach, we fulfill the low-energy theorem of deuteron Compton scattering and there is no significant dependence on the deuteron wave function used. Concerning the nucleon structure, we use the chiral effective field theory with explicit {delta} (1232) degrees of freedom within the small-scale expansion up to leading-one-loop order. Agreement with available data is good at all energies. Our 2-parameter fit to all elastic {gamma} d data leads to values for the static isoscalar dipole polarizabilities which are in excellent agreement with the isoscalar Baldin sum rule. Taking this value as additional input, we find {alpha}{sub E}{sup s} = (11.3{+-}0.7(stat){+-}0.6(Baldin){+-}1(theory)){sup .}10{sup -4} fm{sup 3} and {beta}{sub M}{sup s} = (3.2{+-}0.7(stat){+-}0.6(Baldin){+-}1(theory)){sup .}10{sup -4} fm{sup 3} and conclude by comparison to the proton numbers that neutron and proton polarizabilities are the same within rather small errors. (orig.)

  9. A Hybrid Approach for Reliability Analysis Based on Analytic Hierarchy Process and Bayesian Network

    International Nuclear Information System (INIS)

    Zubair, Muhammad

    2014-01-01

    By using analytic hierarchy process (AHP) and Bayesian Network (BN) the present research signifies the technical and non-technical issues of nuclear accidents. The study exposed that the technical faults was one major reason of these accidents. Keep an eye on other point of view it becomes clearer that human behavior like dishonesty, insufficient training, and selfishness are also play a key role to cause these accidents. In this study, a hybrid approach for reliability analysis based on AHP and BN to increase nuclear power plant (NPP) safety has been developed. By using AHP, best alternative to improve safety, design, operation, and to allocate budget for all technical and non-technical factors related with nuclear safety has been investigated. We use a special structure of BN based on the method AHP. The graphs of the BN and the probabilities associated with nodes are designed to translate the knowledge of experts on the selection of best alternative. The results show that the improvement in regulatory authorities will decrease failure probabilities and increase safety and reliability in industrial area.

  10. A hybrid system approach to airspeed, angle of attack and sideslip estimation in Unmanned Aerial Vehicles

    KAUST Repository

    Shaqura, Mohammad

    2015-06-01

    Fixed wing Unmanned Aerial Vehicles (UAVs) are an increasingly common sensing platform, owing to their key advantages: speed, endurance and ability to explore remote areas. While these platforms are highly efficient, they cannot easily be equipped with air data sensors commonly found on their larger scale manned counterparts. Indeed, such sensors are bulky, expensive and severely reduce the payload capability of the UAVs. In consequence, UAV controllers (humans or autopilots) have little information on the actual mode of operation of the wing (normal, stalled, spin) which can cause catastrophic losses of control when flying in turbulent weather conditions. In this article, we propose a real-time air parameter estimation scheme that can run on commercial, low power autopilots in real-time. The computational method is based on a hybrid decomposition of the modes of operation of the UAV. A Bayesian approach is considered for estimation, in which the estimated airspeed, angle of attack and sideslip are described statistically. An implementation on a UAV is presented, and the performance and computational efficiency of this method are validated using hardware in the loop (HIL) simulation and experimental flight data and compared with classical Extended Kalman Filter estimation. Our benchmark tests shows that this method is faster than EKF by up to two orders of magnitude. © 2015 IEEE.

  11. Hybrid 3D printing and electrodeposition approach for controllable 3D alginate hydrogel formation.

    Science.gov (United States)

    Shang, Wanfeng; Liu, Yanting; Wan, Wenfeng; Hu, Chengzhi; Liu, Zeyang; Wong, Chin To; Fukuda, Toshio; Shen, Yajing

    2017-06-07

    Calcium alginate hydrogels are widely used as biocompatible materials in a substantial number of biomedical applications. This paper reports on a hybrid 3D printing and electrodeposition approach for forming 3D calcium alginate hydrogels in a controllable manner. Firstly, a specific 3D hydrogel printing system is developed by integrating a customized ejection syringe with a conventional 3D printer. Then, a mixed solution of sodium alginate and CaCO 3 nanoparticles is filled into the syringe and can be continuously ejected out of the syringe nozzle onto a conductive substrate. When applying a DC voltage (∼5 V) between the substrate (anode) and the nozzle (cathode), the Ca 2+ released from the CaCO 3 particles can crosslink the alginate to form calcium alginate hydrogel on the substrate. To elucidate the gel formation mechanism and better control the gel growth, we can further establish and verify a gel growth model by considering several key parameters, i.e., applied voltage and deposition time. The experimental results indicate that the alginate hydrogel of various 3D structures can be formed by controlling the movement of the 3D printer. A cell viability test is conducted and shows that the encapsulated cells in the gel can maintain a high survival rate (∼99% right after gel formation). This research establishes a reliable method for the controllable formation of 3D calcium alginate hydrogel, exhibiting great potential for use in basic biology and applied biomedical engineering.

  12. A hybrid clustering and classification approach for predicting crash injury severity on rural roads.

    Science.gov (United States)

    Hasheminejad, Seyed Hessam-Allah; Zahedi, Mohsen; Hasheminejad, Seyed Mohammad Hossein

    2018-03-01

    As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011-2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.

  13. Hybrid Vibration Control under Broadband Excitation and Variable Temperature Using Viscoelastic Neutralizer and Adaptive Feedforward Approach

    Directory of Open Access Journals (Sweden)

    João C. O. Marra

    2016-01-01

    Full Text Available Vibratory phenomena have always surrounded human life. The need for more knowledge and domain of such phenomena increases more and more, especially in the modern society where the human-machine integration becomes closer day after day. In that context, this work deals with the development and practical implementation of a hybrid (passive-active/adaptive vibration control system over a metallic beam excited by a broadband signal and under variable temperature, between 5 and 35°C. Since temperature variations affect directly and considerably the performance of the passive control system, composed of a viscoelastic dynamic vibration neutralizer (also called a viscoelastic dynamic vibration absorber, the associative strategy of using an active-adaptive vibration control system (based on a feedforward approach with the use of the FXLMS algorithm working together with the passive one has shown to be a good option to compensate the neutralizer loss of performance and generally maintain the extended overall level of vibration control. As an additional gain, the association of both vibration control systems (passive and active-adaptive has improved the attenuation of vibration levels. Some key steps matured over years of research on this experimental setup are presented in this paper.

  14. Polymer Combustion as a Basis for Hybrid Propulsion: A Comprehensive Review and New Numerical Approaches

    Directory of Open Access Journals (Sweden)

    Vasily Novozhilov

    2011-10-01

    Full Text Available Hybrid Propulsion is an attractive alternative to conventional liquid and solid rocket motors. This is an active area of research and technological developments. Potential wide application of Hybrid Engines opens the possibility for safer and more flexible space vehicle launching and manoeuvring. The present paper discusses fundamental combustion issues related to further development of Hybrid Rockets. The emphasis is made on the two aspects: (1 properties of potential polymeric fuels, and their modification, and (2 implementation of comprehensive CFD models for combustion in Hybrid Engines. Fundamentals of polymeric fuel combustion are discussed. Further, steps necessary to accurately describe their burning behaviour by means of CFD models are investigated. Final part of the paper presents results of preliminary CFD simulations of fuel burning process in Hybrid Engine using a simplified set-up.

  15. PENINGKATAN PRESTASI BELAJAR SISWA DALAM PEMBELAJARAN KIMIA DENGAN PENERAPAN COOPERATIVE LEARNING MODEL JIGSAW PADA KELAS X IPA3 DI SMA NEGERI 1 PADANG

    Directory of Open Access Journals (Sweden)

    Prima Aswirna

    2012-07-01

    Full Text Available The problem of this Classroom Action Research is how Cooperative Learning Model Jigsaw should be implemented in the learning of Chemistry at Grade X, Scince 3 of Senior High School 1 Padang.  This study was done through the following stages such as Planning, Action, Observation, and Evaluation or Reflection.  The results show among other that some important aspects were improved.  The average score of each cycles show improvement in students’ mastery and total average of the three actions become 98 percent.  It can be concluded that Cooperative Learning through Jigsaw technique improved students’ achievement of the subject being investigated.

  16. Efectos de la aplicación de "jigsaw" sobre la adquisición de competencias en dirección de operaciones || Effects of the "Jigsaw" Technique on Student' Learning Competences within Operations Management

    Directory of Open Access Journals (Sweden)

    López Vargas, Cristina

    2017-12-01

    Full Text Available El presente trabajo analiza los efectos de la aplicación de la técnica de "jigsaw", puzzle o rompecabezas de Aronson en la adquisición de competencias por parte de estudiantes universitarios. Más concretamente buscamos determinar qué competencias sistémicas, instrumentales e interpersonales se adquieren más fácilmente al implantar "jigsaw" en el proceso de enseñanza-aprendizaje. Los resultados alcanzados muestran que esta técnica de aprendizaje cooperativo facilita en mayor medida la adquisición de competencias sistémicas e instrumentales en comparación con las interpersonales. Dentro de las competencias sistémicas, la que desarrollan con más facilidad los alumnos es la denominada metareflexión; es decir, el aprendizaje progresivo por repetición. En el grupo de competencias instrumentales, destacan la interacción entre compañeros, las habilidades comunicativas del alumno, la participación, la ayuda en la resolución de conflictos entre compañeros surgidos durante la dinámica y la mejora de la instrucción directa. Finalmente, en relación a las competencias interpersonales, la más desarrollada es el sentido de la responsabilidad del alumno. || The aim of this study was to determine the effects of the cooperative ``jigsaw'' method on generic competence-based training by university students. This specifically sought to understand how systemic, instrumental and interpersonal competences are more easily acquired by adopting ``jigsaw'' in the teaching-learning procedure. The results reveal that this cooperative learning method makes the development of systemic and instrumental competences easier to a greater extent than interpersonal ones. Meta-reflection or progressive rote learning achieved a highest score among systemic competences. Focusing our attention on the instrumental dimension, peer interaction, students' communication skills, participation, resolution of peer conflicts and direct instruction, these competences sty

  17. A Hybrid Approach to Finding Relevant Social Media Content for Complex Domain Specific Information Needs.

    Science.gov (United States)

    Cameron, Delroy; Sheth, Amit P; Jaykumar, Nishita; Thirunarayan, Krishnaprasad; Anand, Gaurish; Smith, Gary A

    2014-12-01

    While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex domain specific information needs. The domain of prescription drug abuse, for example, requires knowledge of both ontological concepts and "intelligible constructs" not typically modeled in ontologies. These intelligible constructs convey essential information that include notions of intensity, frequency, interval, dosage and sentiments, which could be important to the holistic needs of the information seeker. In this paper, we present a hybrid approach to domain specific information retrieval that integrates ontology-driven query interpretation with synonym-based query expansion and domain specific rules, to facilitate search in social media on prescription drug abuse. Our framework is based on a context-free grammar (CFG) that defines the query language of constructs interpretable by the search system. The grammar provides two levels of semantic interpretation: 1) a top-level CFG that facilitates retrieval of diverse textual patterns, which belong to broad templates and 2) a low-level CFG that enables interpretation of specific expressions belonging to such textual patterns. These low-level expressions occur as concepts from four different categories of data: 1) ontological concepts, 2) concepts in lexicons (such as emotions and sentiments), 3) concepts in lexicons with only partial ontology representation, called lexico-ontology concepts (such as side effects and routes of administration (ROA)), and 4) domain specific expressions (such as date, time, interval, frequency and dosage) derived solely through rules. Our approach is embodied in a novel Semantic Web platform called PREDOSE, which provides search support for complex domain specific information needs in prescription drug abuse epidemiology. When applied to a corpus of over 1 million drug abuse-related web forum posts, our search framework proved effective in retrieving

  18. Alternative policy impacts on US GHG emissions and energy security: A hybrid modeling approach

    International Nuclear Information System (INIS)

    Sarica, Kemal; Tyner, Wallace E.

    2013-01-01

    This study addresses the possible impacts of energy and climate policies, namely corporate average fleet efficiency (CAFE) standard, renewable fuel standard (RFS) and clean energy standard (CES), and an economy wide equivalent carbon tax on GHG emissions in the US to the year 2045. Bottom–up and top–down modeling approaches find widespread use in energy economic modeling and policy analysis, in which they differ mainly with respect to the emphasis placed on technology of the energy system and/or the comprehensiveness of endogenous market adjustments. For this study, we use a hybrid energy modeling approach, MARKAL–Macro, that combines the characteristics of two divergent approaches, in order to investigate and quantify the cost of climate policies for the US and an equivalent carbon tax. The approach incorporates Macro-economic feedbacks through a single sector neoclassical growth model while maintaining sectoral and technological detail of the bottom–up optimization framework with endogenous aggregated energy demand. Our analysis is done for two important objectives of the US energy policy: GHG reduction and increased energy security. Our results suggest that the emission tax achieves results quite similar to the CES policy but very different results in the transportation sector. The CAFE standard and RFS are more expensive than a carbon tax for emission reductions. However, the CAFE standard and RFS are much more efficient at achieving crude oil import reductions. The GDP losses are 2.0% and 1.2% relative to the base case for the policy case and carbon tax. That difference may be perceived as being small given the increased energy security gained from the CAFE and RFS policy measures and the uncertainty inherent in this type of analysis. - Highlights: • Evaluates US impacts of three energy/climate policies and a carbon tax (CT) • Analysis done with bottom–up MARKAL model coupled with a macro model • Electricity clean energy standard very close to

  19. A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

    Directory of Open Access Journals (Sweden)

    Fernando Sánchez Lasheras

    2015-03-01

    Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

  20. Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach

    Directory of Open Access Journals (Sweden)

    Miraemiliana Murat

    2017-09-01

    Full Text Available Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM, Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD, Histogram of Oriented Gradients (HOG, Hu invariant moments (Hu and Zernike moments (ZM. Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN, random forest (RF, support vector machine (SVM, k-nearest neighbour (k-NN, linear discriminant analysis (LDA and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM. In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS and Pearson’s coefficient correlation (PCC. The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia

  1. Combination of Biorthogonal Wavelet Hybrid Kernel OCSVM with Feature Weighted Approach Based on EVA and GRA in Financial Distress Prediction

    Directory of Open Access Journals (Sweden)

    Chao Huang

    2014-01-01

    Full Text Available Financial distress prediction plays an important role in the survival of companies. In this paper, a novel biorthogonal wavelet hybrid kernel function is constructed by combining linear kernel function with biorthogonal wavelet kernel function. Besides, a new feature weighted approach is presented based on economic value added (EVA and grey relational analysis (GRA. Considering the imbalance between financially distressed companies and normal ones, the feature weighted one-class support vector machine based on biorthogonal wavelet hybrid kernel (BWH-FWOCSVM is further put forward for financial distress prediction. The empirical study with real data from the listed companies on Growth Enterprise Market (GEM in China shows that the proposed approach has good performance.

  2. Targeted and untargeted high resolution mass approach for a putative profiling of glycosylated simple phenols in hybrid grapes.

    Science.gov (United States)

    Barnaba, Chiara; Dellacassa, Eduardo; Nicolini, Giorgio; Giacomelli, Mattia; Roman Villegas, Tomas; Nardin, Tiziana; Larcher, Roberto

    2017-08-01

    Vitis vinifera is one of the most widespread grapevines around the world representing the raw material for high quality wine production. The availability of more resistant interspecific hybrid vine varieties, developed from crosses between Vitis vinifera and other Vitis species, has generated much interest, also due to the low environmental effect of production. However, hybrid grape wine composition and varietal differences between interspecific hybrids have not been well defined, particularly for the simple phenols profile. The dynamic of these phenols in wines, where the glycosylated forms can be transformed into the free ones during winemaking, also raises an increasing health interest by their role as antoxidants in wine consumers. In this work an on-line SPE clean-up device, to reduce matrix interference, was combined with ultra-high liquid chromatography-high resolution mass spectrometry in order to increase understanding of the phenolic composition of hybrid grape varieties. Specifically, the phenolic composition of 4 hybrid grape varieties (red, Cabernet Cantor and Prior; white, Muscaris and Solaris) and 2 European grape varieties (red, Merlot; white, Chardonnay) was investigated, focusing on free and glycosidically bound simple phenols and considering compound distribution in pulp, skin, seeds and wine. Using a targeted approach 53 free simple phenols and 7 glycosidic precursors were quantified with quantification limits ranging from 0.001 to 2mgKg -1 and calibration R 2 of 0.99 for over 86% of compounds. The untargeted approach made it possible to tentatively identify 79 glycosylated precursors of selected free simple phenols in the form of -hexoside (N=30), -pentoside (21), -hexoside-hexoside (17), -hexoside-pentoside (4), -pentoside-hexoside (5) and -pentoside-pentoside (2) derivatives on the basis of accurate mass, isotopic pattern and MS/MS fragmentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. G-centers in irradiated silicon revisited: A screened hybrid density functional theory approach

    KAUST Repository

    Wang, H.; Chroneos, A.; Londos, C. A.; Sgourou, E. N.; Schwingenschlö gl, Udo

    2014-01-01

    Electronic structure calculations employing screened hybrid density functional theory are used to gain fundamental insight into the interaction of carbon interstitial (Ci) and substitutional (Cs) atoms forming the CiCs defect known as G

  4. A Formal Approach to User Interface Design using Hybrid System Theory, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Optimal Synthesis Inc.(OSI) proposes to develop an aiding tool for user interface design that is based on mathematical formalism of hybrid system theory. The...

  5. Hybrid Type II fuzzy system & data mining approach for surface finish

    Directory of Open Access Journals (Sweden)

    Tzu-Liang (Bill Tseng

    2015-07-01

    Full Text Available In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

  6. Early experience with the Occlutech PLD occluder for mitral paravalvar leak closure through a hybrid transapical approach.

    Science.gov (United States)

    Bedair, Radwa; Morgan, Gareth J; Bapat, Vinayak; Kapetanakis, Stamatis; Goreczny, Sebastian; Simpson, John; Qureshi, Shakeel A

    2016-12-10

    We sought to evaluate the feasibility and efficacy of hybrid transapical closure of paravalvar mitral leaks using a new Occlutech PLD occluder in patients with heart failure and/or haemolytic anaemia. Retrospective analysis of clinical and procedural data was undertaken for patients who had attempted closure of paravalvar mitral leaks via a hybrid transapical approach with the Occlutech PLD occluder. Eight patients (four males, median age 69 years) underwent closure of 10 mitral paravalvar leaks using eight Occlutech PLD occluders and two AMPLATZER Vascular Plugs (AVP II). Successful deployment, with significant reduction of the paravalvar leak was achieved in seven patients with short procedure (median 131 min) and fluoroscopy times (median 22 min). One patient had mechanical interference with prosthetic valve function, requiring surgery. Another patient with a high EuroSCORE (48.8%) died of multi-organ failure two days after the procedure. Clinical improvement in either heart failure or haemolysis was seen in all discharged patients. In our series of patients with challenging anatomy, the Occlutech PLD occluders performed well when implanted via a hybrid transapical approach. Further work is needed to assess this methodology fully for a wider population and to assess other deployment approaches for this promising new occluder.

  7. Numerical methodologies for investigation of moderate-velocity flow using a hybrid computational fluid dynamics - molecular dynamics simulation approach

    International Nuclear Information System (INIS)

    Ko, Soon Heum; Kim, Na Yong; Nikitopoulos, Dimitris E.; Moldovan, Dorel; Jha, Shantenu

    2014-01-01

    Numerical approaches are presented to minimize the statistical errors inherently present due to finite sampling and the presence of thermal fluctuations in the molecular region of a hybrid computational fluid dynamics (CFD) - molecular dynamics (MD) flow solution. Near the fluid-solid interface the hybrid CFD-MD simulation approach provides a more accurate solution, especially in the presence of significant molecular-level phenomena, than the traditional continuum-based simulation techniques. It also involves less computational cost than the pure particle-based MD. Despite these advantages the hybrid CFD-MD methodology has been applied mostly in flow studies at high velocities, mainly because of the higher statistical errors associated with low velocities. As an alternative to the costly increase of the size of the MD region to decrease statistical errors, we investigate a few numerical approaches that reduce sampling noise of the solution at moderate-velocities. These methods are based on sampling of multiple simulation replicas and linear regression of multiple spatial/temporal samples. We discuss the advantages and disadvantages of each technique in the perspective of solution accuracy and computational cost.

  8. Introgressive hybridization in Iberian cyprinid fishes:a cytogenomic approach to homoploid Leuciscinae

    OpenAIRE

    Pereira, Carla Sofia Alves, 1983-

    2013-01-01

    Tese de doutoramento, Biologia (Biologia Evolutiva), Universidade de Lisboa, Faculdade de Ciências, 2013 Hybridization is currently a well-recognized process amongst animals responsible for biodiversity, evolution and speciation processes while defying most species concepts. Hybridization is prevalent among fishes, particularly cyprinids, which therefore constitute good models of study (1) to access general patterns of genomic variation, (2) to identify the genetic basis and the evolutiona...

  9. A Hybrid Change Detection Approach for Damage Detection and Recovery Monitoring

    Science.gov (United States)

    de Alwis Pitts, Dilkushi; Wieland, Marc; Wang, Shifeng; So, Emily; Pittore, Massimiliano

    2014-05-01

    Following a disaster, change detection via pre- and post-event very high resolution remote sensing images is an essential technique for damage assessment and recovery monitoring over large areas in complex urban environments. Most assessments to date focus on detection, destruction and recovery of man-made objects that facilitate shelter and accessibility, such as buildings, roads, bridges, etc., as indicators for assessment and better decision making. Moreover, many current change-detection mechanisms do not use all the data and knowledge which are often available for the pre-disaster state. Recognizing the continuous rather than dichotomous character of the data-rich/data-poor distinction permits the incorporation of ancillary data and existing knowledge into the processing flow. Such incorporation could improve the reliability of the results and thereby enhance the usability of robust methods for disaster management. This study proposes an application-specific and robust change detection method from multi-temporal very high resolution multi-spectral satellite images. This hybrid indicator-specific method uses readily available pre-disaster GIS data and integrates existing knowledge into the processing flow to optimize the change detection while offering the possibility to target specific types of changes to man-made objects. The indicator-specific information of the GIS objects is used as a series of masks to treat the GIS objects with similar characteristics similarly for better accuracy. The proposed approach is based on a fusion of a multi-index change detection method based on gradient, texture and edge similarity filters. The change detection index is flexible for disaster cases in which the pre-disaster and post-disaster images are not of the same resolution. The proposed automated method is evaluated with QuickBird and Ikonos datasets for abrupt changes soon after disaster. The method could also be extended in a semi-automated way for monitoring

  10. MeMo: a hybrid SQL/XML approach to metabolomic data management for functional genomics

    Directory of Open Access Journals (Sweden)

    Hardy Nigel

    2006-06-01

    Full Text Available Abstract Background The genome sequencing projects have shown our limited knowledge regarding gene function, e.g. S. cerevisiae has 5–6,000 genes of which nearly 1,000 have an uncertain function. Their gross influence on the behaviour of the cell can be observed using large-scale metabolomic studies. The metabolomic data produced need to be structured and annotated in a machine-usable form to facilitate the exploration of the hidden links between the genes and their functions. Description MeMo is a formal model for representing metabolomic data and the associated metadata. Two predominant platforms (SQL and XML are used to encode the model. MeMo has been implemented as a relational database using a hybrid approach combining the advantages of the two technologies. It represents a practical solution for handling the sheer volume and complexity of the metabolomic data effectively and efficiently. The MeMo model and the associated software are available at http://dbkgroup.org/memo/. Conclusion The maturity of relational database technology is used to support efficient data processing. The scalability and self-descriptiveness of XML are used to simplify the relational schema and facilitate the extensibility of the model necessitated by the creation of new experimental techniques. Special consideration is given to data integration issues as part of the systems biology agenda. MeMo has been physically integrated and cross-linked to related metabolomic and genomic databases. Semantic integration with other relevant databases has been supported through ontological annotation. Compatibility with other data formats is supported by automatic conversion.

  11. A Game-Theoretic approach to Fault Diagnosis of Hybrid Systems

    Directory of Open Access Journals (Sweden)

    Davide Bresolin

    2011-06-01

    Full Text Available Physical systems can fail. For this reason the problem of identifying and reacting to faults has received a large attention in the control and computer science communities. In this paper we study the fault diagnosis problem for hybrid systems from a game-theoretical point of view. A hybrid system is a system mixing continuous and discrete behaviours that cannot be faithfully modeled neither by using a formalism with continuous dynamics only nor by a formalism including only discrete dynamics. We use the well known framework of hybrid automata for modeling hybrid systems, and we define a Fault Diagnosis Game on them, using two players: the environment and the diagnoser. The environment controls the evolution of the system and chooses whether and when a fault occurs. The diagnoser observes the external behaviour of the system and announces whether a fault has occurred or not. Existence of a winning strategy for the diagnoser implies that faults can be detected correctly, while computing such a winning strategy corresponds to implement a diagnoser for the system. We will show how to determine the existence of a winning strategy, and how to compute it, for some decidable classes of hybrid automata like o-minimal hybrid automata.

  12. Prediction of Currency Volume Issued in Taiwan Using a Hybrid Artificial Neural Network and Multiple Regression Approach

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2013-01-01

    Full Text Available Because the volume of currency issued by a country always affects its interest rate, price index, income levels, and many other important macroeconomic variables, the prediction of currency volume issued has attracted considerable attention in recent years. In contrast to the typical single-stage forecast model, this study proposes a hybrid forecasting approach to predict the volume of currency issued in Taiwan. The proposed hybrid models consist of artificial neural network (ANN and multiple regression (MR components. The MR component of the hybrid models is established for a selection of fewer explanatory variables, wherein the selected variables are of higher importance. The ANN component is then designed to generate forecasts based on those important explanatory variables. Subsequently, the model is used to analyze a real dataset of Taiwan's currency from 1996 to 2011 and twenty associated explanatory variables. The prediction results reveal that the proposed hybrid scheme exhibits superior forecasting performance for predicting the volume of currency issued in Taiwan.

  13. Simulation of a Wall-Bounded Flow using a Hybrid LES/RAS Approach with Turbulence Recycling

    Science.gov (United States)

    Quinlan, Jesse R.; Mcdaniel, James; Baurle, Robert A.

    2012-01-01

    Simulations of a supersonic recessed-cavity flow are performed using a hybrid large-eddy/ Reynolds-averaged simulation approach utilizing an inflow turbulence recycling procedure and hybridized inviscid flux scheme. Calorically perfect air enters the three-dimensional domain at a free stream Mach number of 2.92. Simulations are performed to assess grid sensitivity of the solution, efficacy of the turbulence recycling, and effect of the shock sensor used with the hybridized inviscid flux scheme. Analysis of the turbulent boundary layer upstream of the rearward-facing step for each case indicates excellent agreement with theoretical predictions. Mean velocity and pressure results are compared to Reynolds-averaged simulations and experimental data for each case, and these comparisons indicate good agreement on the finest grid. Simulations are repeated on a coarsened grid, and results indicate strong grid density sensitivity. The effect of turbulence recycling on the solution is illustrated by performing coarse grid simulations with and without inflow turbulence recycling. Two shock sensors, one of Ducros and one of Larsson, are assessed for use with the hybridized inviscid flux reconstruction scheme.

  14. Evaluation and Validation of Assembling Corrected PacBio Long Reads for Microbial Genome Completion via Hybrid Approaches.

    Science.gov (United States)

    Lin, Hsin-Hung; Liao, Yu-Chieh

    2015-01-01

    Despite the ever-increasing output of next-generation sequencing data along with developing assemblers, dozens to hundreds of gaps still exist in de novo microbial assemblies due to uneven coverage and large genomic repeats. Third-generation single-molecule, real-time (SMRT) sequencing technology avoids amplification artifacts and generates kilobase-long reads with the potential to complete microbial genome assembly. However, due to the low accuracy (~85%) of third-generation sequences, a considerable amount of long reads (>50X) are required for self-correction and for subsequent de novo assembly. Recently-developed hybrid approaches, using next-generation sequencing data and as few as 5X long reads, have been proposed to improve the completeness of microbial assembly. In this study we have evaluated the contemporary hybrid approaches and demonstrated that assembling corrected long reads (by runCA) produced the best assembly compared to long-read scaffolding (e.g., AHA, Cerulean and SSPACE-LongRead) and gap-filling (SPAdes). For generating corrected long reads, we further examined long-read correction tools, such as ECTools, LSC, LoRDEC, PBcR pipeline and proovread. We have demonstrated that three microbial genomes including Escherichia coli K12 MG1655, Meiothermus ruber DSM1279 and Pdeobacter heparinus DSM2366 were successfully hybrid assembled by runCA into near-perfect assemblies using ECTools-corrected long reads. In addition, we developed a tool, Patch, which implements corrected long reads and pre-assembled contigs as inputs, to enhance microbial genome assemblies. With the additional 20X long reads, short reads of S. cerevisiae W303 were hybrid assembled into 115 contigs using the verified strategy, ECTools + runCA. Patch was subsequently applied to upgrade the assembly to a 35-contig draft genome. Our evaluation of the hybrid approaches shows that assembling the ECTools-corrected long reads via runCA generates near complete microbial genomes, suggesting

  15. HyDEn: A Hybrid Steganocryptographic Approach for Data Encryption Using Randomized Error-Correcting DNA Codes

    Directory of Open Access Journals (Sweden)

    Dan Tulpan

    2013-01-01

    Full Text Available This paper presents a novel hybrid DNA encryption (HyDEn approach that uses randomized assignments of unique error-correcting DNA Hamming code words for single characters in the extended ASCII set. HyDEn relies on custom-built quaternary codes and a private key used in the randomized assignment of code words and the cyclic permutations applied on the encoded message. Along with its ability to detect and correct errors, HyDEn equals or outperforms existing cryptographic methods and represents a promising in silico DNA steganographic approach.

  16. The Effect of Using Jigsaw Strategy in Teaching Science on the Acquisition of Scientific Concepts among the Fourth Graders of Bani Kinana Directorate of Education

    Science.gov (United States)

    Hamadneh, Qaseem Mohammad Salim

    2017-01-01

    The study aimed to identify the effect of using Jigsaw strategy in teaching science on the acquisition of scientific concepts among the fourth graders of Bani Kinana Directorate of Education compared to the traditional way. The study sample consisted of 70 male and female students, divided into two groups: experimental and control where the…

  17. Effect of the Jigsaw-Based Cooperative Learning Method on Student Performance in the General Certificate of Education Advanced-Level Psychology: An Exploratory Brunei Case Study

    Science.gov (United States)

    Azmin, Nur Hafizah

    2016-01-01

    The mixed-methods study investigated the effect of the jigsaw cooperative learning method on student performance in psychology and their views towards it. Experimental data were obtained via pre-and-post tests and an open-ended questionnaire from 16 conveniently selected students at one Sixth Form College in Brunei. Moreover, the participants…

  18. The Effect of Jigsaw Technique on 6th Graders' Learning of Force and Motion Unit and Their Science Attitudes and Motivation

    Science.gov (United States)

    Ural, Evrim; Ercan, Orhan; Gençoglan, Durdu Mehmet

    2017-01-01

    The study aims to investigate the effects of jigsaw technique on 6th graders' learning of "Force and Motion" unit, their science learning motivation and their attitudes towards science classes. The sample of the study consisted of 49 6th grade students from two different classes taking the Science and Technology course at a government…

  19. Using the jigsaw cooperative learning method to teach medical students about long-term and postacute care.

    Science.gov (United States)

    Buhr, Gwendolen T; Heflin, Mitchell T; White, Heidi K; Pinheiro, Sandro O

    2014-06-01

    Since many of the frailest and most vulnerable Americans reside in nursing homes, medical students need focused education and training pertaining to this setting. A unique cooperative learning experience utilizing the jigsaw method was developed to engage and expose students to the institutional long-term and postacute care (LTPAC) setting and the roles of personnel there. To accomplish these goals, small groups of medical students interviewed LTPAC personnel about their role, generally, and in relation to a specific patient case. These groups were then rearranged into new groups containing 1 student from each of the original groups plus a faculty facilitator. Each student in the new groups taught about the role of the LTPAC professional they interviewed. To assess the effectiveness of this learning experience, students and LTPAC personnel provided written feedback and rated the activity using a 5-point Likert scale (1 = worst; 5 = best). Students also took a knowledge test. The activity received ratings from students of 3.65 to 4.12 (mean = 3.91). The knowledge test results indicated that students understood the roles of the LTPAC personnel. In general, the jigsaw exercise was well-received by participants and provided an effective means of introducing medical students to the nursing home environment. Copyright © 2014 American Medical Directors Association, Inc. Published by Elsevier Inc. All rights reserved.

  20. Influence on Learning of a Collaborative Learning Method Comprising the Jigsaw Method and Problem-based Learning (PBL).

    Science.gov (United States)

    Takeda, Kayoko; Takahashi, Kiyoshi; Masukawa, Hiroyuki; Shimamori, Yoshimitsu

    2017-01-01

    Recently, the practice of active learning has spread, increasingly recognized as an essential component of academic studies. Classes incorporating small group discussion (SGD) are conducted at many universities. At present, assessments of the effectiveness of SGD have mostly involved evaluation by questionnaires conducted by teachers, by peer assessment, and by self-evaluation of students. However, qualitative data, such as open-ended descriptions by students, have not been widely evaluated. As a result, we have been unable to analyze the processes and methods involved in how students acquire knowledge in SGD. In recent years, due to advances in information and communication technology (ICT), text mining has enabled the analysis of qualitative data. We therefore investigated whether the introduction of a learning system comprising the jigsaw method and problem-based learning (PBL) would improve student attitudes toward learning; we did this by text mining analysis of the content of student reports. We found that by applying the jigsaw method before PBL, we were able to improve student attitudes toward learning and increase the depth of their understanding of the area of study as a result of working with others. The use of text mining to analyze qualitative data also allowed us to understand the processes and methods by which students acquired knowledge in SGD and also changes in students' understanding and performance based on improvements to the class. This finding suggests that the use of text mining to analyze qualitative data could enable teachers to evaluate the effectiveness of various methods employed to improve learning.

  1. DNA is structured as a linear "jigsaw puzzle" in the genomes of Arabidopsis, rice, and budding yeast.

    Science.gov (United States)

    Liu, Yun-Hua; Zhang, Meiping; Wu, Chengcang; Huang, James J; Zhang, Hong-Bin

    2014-01-01

    Knowledge of how a genome is structured and organized from its constituent elements is crucial to understanding its biology and evolution. Here, we report the genome structuring and organization pattern as revealed by systems analysis of the sequences of three model species, Arabidopsis, rice and yeast, at the whole-genome and chromosome levels. We found that all fundamental function elements (FFE) constituting the genomes, including genes (GEN), DNA transposable elements (DTE), retrotransposable elements (RTE), simple sequence repeats (SSR), and (or) low complexity repeats (LCR), are structured in a nonrandom and correlative manner, thus leading to a hypothesis that the DNA of the species is structured as a linear "jigsaw puzzle". Furthermore, we showed that different FFE differ in their importance in the formation and evolution of the DNA jigsaw puzzle structure between species. DTE and RTE play more important roles than GEN, LCR, and SSR in Arabidopsis, whereas GEN and RTE play more important roles than LCR, SSR, and DTE in rice. The genes having multiple recognized functions play more important roles than those having single functions. These results provide useful knowledge necessary for better understanding genome biology and evolution of the species and for effective molecular breeding of rice.

  2. Hybrid Wavelet De-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

    Science.gov (United States)

    WANG, D.; Wang, Y.; Zeng, X.

    2017-12-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

  3. An Approach to Management of Health Care and Medical Diagnosis Using of a Hybrid Disease Diagnosis System

    Directory of Open Access Journals (Sweden)

    Hodjat Hamidi

    2017-02-01

    Full Text Available Introduction: In order to simplify the information exchange within the medical diagnosis process, a collaborative software agent’s framework is presented. The purpose of the framework is to allow the automated information exchange between different medicine specialists. Methods: This study presented architecture of a hybrid disease diagnosis system. The architecture employed a learning algorithm and used soft computing to build a medical knowledge base. These machine intelligences are combined in a complementary approach to overcome the weakness of each other. To evaluate the hybrid learning algorithm and compare it with other methods, 699 samples were used in each experiment, where 60% was for training, 20% was for cross validation, and 20% for testing. Results: The results were obtained from the experiments on the breast cancer dataset. Different methods of soft computing system were merged to create diagnostic software functionality. As it is shown in the structure, the system has the ability to learn and collect knowledge that can be used in the detection of new images. Currently, the system is at the design stage. The system is to evaluate the performance of hybrid learning algorithm. The preliminary results showed a better performance of this system than other methods. However, the results can be tested with hybrid system on larger data sets to improve hybrid learning algorithm. Conclusion: The purpose of this paper was to simplify the diagnosis process of a patient by splitting the medical domain concepts (e.g., causes, effects, symptoms, tests in human body systems (e.g., respiratory, cardiovascular, though maintaining the holistic perspective through the links between common concepts.

  4. PV-wind hybrid system performance. A new approach and a case study

    Energy Technology Data Exchange (ETDEWEB)

    Arribas, Luis; Cano, Luis; Cruz, Ignacio [Departamento de Energias Renovables, CIEMAT, Avda. Complutense 22, 28040 Madrid (Spain); Mata, Montserrat; Llobet, Ermen [Ecotecnia, Roc Boronat 78, 08005 Barcelona (Spain)

    2010-01-15

    Until now, there is no internationally accepted guideline for the measurement, data exchange and analysis of PV-Wind Hybrid Systems. As there is a need for such a tool, so as to overcome the barrier that the lack of confidence due to the absence of reliability means for the development of the market of Hybrid Systems, an effort has been made to suggest one tool for PV-Wind Hybrid Systems. The suggested guidelines presented in this work are based on the existing guidelines for PV Systems, as a PV-Wind Hybrid system can be roughly thought of as a PV System to which wind generation has been added. So, the guidelines for PV Systems are valid for the PV-Wind System, and only the part referred to wind generation should be included. This has been the process followed in this work. The proposed method is applied to a case study, the CICLOPS Project, a 5 kW PV, 7.5 kW Wind Hybrid system installed at the Isolated Wind Systems Test Site that CIEMAT owns in CEDER (Soria, Spain). This system has been fully monitored through a year and the results of the monitoring activity, characterizing the long-term performance of the system are shown in this work. (author)

  5. Hybrid energy system evaluation in water supply system energy production: neural network approach

    Energy Technology Data Exchange (ETDEWEB)

    Goncalves, Fabio V.; Ramos, Helena M. [Civil Engineering Department, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal); Reis, Luisa Fernanda R. [Universidade de Sao Paulo, EESC/USP, Departamento de Hidraulica e Saneamento., Avenida do Trabalhador Saocarlense, 400, Sao Carlos-SP (Brazil)

    2010-07-01

    Water supply systems are large consumers of energy and the use of hybrid systems for green energy production is this new proposal. This work presents a computational model based on neural networks to determine the best configuration of a hybrid system to generate energy in water supply systems. In this study the energy sources to make this hybrid system can be the national power grid, micro-hydro and wind turbines. The artificial neural network is composed of six layers, trained to use data generated by a model of hybrid configuration and an economic simulator - CES. The reason for the development of an advanced model of forecasting based on neural networks is to allow rapid simulation and proper interaction with hydraulic and power model simulator - HPS. The results show that this computational model is useful as advanced decision support system in the design of configurations of hybrid power systems applied to water supply systems, improving the solutions in the development of its global energy efficiency.

  6. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng

    2016-07-06

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  7. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

    Directory of Open Access Journals (Sweden)

    Guozheng Liu

    Full Text Available Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1 examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2 explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3 investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L. and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs, but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  8. Improved signal processing approaches in an offline simulation of a hybrid brain–computer interface

    Science.gov (United States)

    Brunner, Clemens; Allison, Brendan Z.; Krusienski, Dean J.; Kaiser, Vera; Müller-Putz, Gernot R.; Pfurtscheller, Gert; Neuper, Christa

    2012-01-01

    In a conventional brain–computer interface (BCI) system, users perform mental tasks that yield specific patterns of brain activity. A pattern recognition system determines which brain activity pattern a user is producing and thereby infers the user’s mental task, allowing users to send messages or commands through brain activity alone. Unfortunately, despite extensive research to improve classification accuracy, BCIs almost always exhibit errors, which are sometimes so severe that effective communication is impossible. We recently introduced a new idea to improve accuracy, especially for users with poor performance. In an offline simulation of a “hybrid” BCI, subjects performed two mental tasks independently and then simultaneously. This hybrid BCI could use two different types of brain signals common in BCIs – event-related desynchronization (ERD) and steady-state evoked potentials (SSEPs). This study suggested that such a hybrid BCI is feasible. Here, we re-analyzed the data from our initial study. We explored eight different signal processing methods that aimed to improve classification and further assess both the causes and the extent of the benefits of the hybrid condition. Most analyses showed that the improved methods described here yielded a statistically significant improvement over our initial study. Some of these improvements could be relevant to conventional BCIs as well. Moreover, the number of illiterates could be reduced with the hybrid condition. Results are also discussed in terms of dual task interference and relevance to protocol design in hybrid BCIs. PMID:20153371

  9. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    KAUST Repository

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

  10. PV-wind hybrid system performance. A new approach and a case study

    International Nuclear Information System (INIS)

    Arribas, Luis; Cano, Luis; Cruz, Ignacio; Mata, Montserrat; Llobet, Ermen

    2010-01-01

    Until now, there is no internationally accepted guideline for the measurement, data exchange and analysis of PV-Wind Hybrid Systems. As there is a need for such a tool, so as to overcome the barrier that the lack of confidence due to the absence of reliability means for the development of the market of Hybrid Systems, an effort has been made to suggest one tool for PV-Wind Hybrid Systems. The suggested guidelines presented in this work are based on the existing guidelines for PV Systems, as a PV-Wind Hybrid system can be roughly thought of as a PV System to which wind generation has been added. So, the guidelines for PV Systems are valid for the PV-Wind System, and only the part referred to wind generation should be included. This has been the process followed in this work. The proposed method is applied to a case study, the CICLOPS Project, a 5 kW PV, 7.5 kW Wind Hybrid system installed at the Isolated Wind Systems Test Site that CIEMAT owns in CEDER (Soria, Spain). This system has been fully monitored through a year and the results of the monitoring activity, characterizing the long-term performance of the system are shown in this work. (author)

  11. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

    Science.gov (United States)

    Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

    2016-01-01

    Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population. PMID:27383841

  12. Time-dependent mass of cosmological perturbations in the hybrid and dressed metric approaches to loop quantum cosmology

    Science.gov (United States)

    Elizaga Navascués, Beatriz; Martín de Blas, Daniel; Mena Marugán, Guillermo A.

    2018-02-01

    Loop quantum cosmology has recently been applied in order to extend the analysis of primordial perturbations to the Planck era and discuss the possible effects of quantum geometry on the cosmic microwave background. Two approaches to loop quantum cosmology with admissible ultraviolet behavior leading to predictions that are compatible with observations are the so-called hybrid and dressed metric approaches. In spite of their similarities and relations, we show in this work that the effective equations that they provide for the evolution of the tensor and scalar perturbations are somewhat different. When backreaction is neglected, the discrepancy appears only in the time-dependent mass term of the corresponding field equations. We explain the origin of this difference, arising from the distinct quantization procedures. Besides, given the privileged role that the big bounce plays in loop quantum cosmology, e.g. as a natural instant of time to set initial conditions for the perturbations, we also analyze the positivity of the time-dependent mass when this bounce occurs. We prove that the mass of the tensor perturbations is positive in the hybrid approach when the kinetic contribution to the energy density of the inflaton dominates over its potential, as well as for a considerably large sector of backgrounds around that situation, while this mass is always nonpositive in the dressed metric approach. Similar results are demonstrated for the scalar perturbations in a sector of background solutions that includes the kinetically dominated ones; namely, the mass then is positive for the hybrid approach, whereas it typically becomes negative in the dressed metric case. More precisely, this last statement is strictly valid when the potential is quadratic for values of the inflaton mass that are phenomenologically favored.

  13. The Effect of Two Different Cooperative Approaches on Students' Learning and Practices within the Context of a WebQuest Science Investigation

    Science.gov (United States)

    Zacharia, Zacharias C.; Xenofontos, Nikoletta A.; Manoli, Constantinos C.

    2011-01-01

    The goal of this study was to investigate the effect of two different cooperative learning approaches, namely, the Jigsaw Cooperative Approach (JCA) and the Traditional Cooperative Approach (TCA), on students' learning and practices/actions within the context of a WebQuest science investigation. Another goal of this study was to identify possible…

  14. A hybrid particle–field molecular dynamics approach: a route toward efficient coarse-grained models for biomembranes

    International Nuclear Information System (INIS)

    Milano, Giuseppe; De Nicola, Antonio; Kawakatsu, Toshihiro

    2013-01-01

    This paper gives an overview of the coarse-grained models of phospholipids recently developed by the authors in the frame of a hybrid particle–field molecular dynamics technique. This technique employs a special class of coarse-grained models that are gaining popularity because they allow simulations of large scale systems and, at the same time, they provide sufficiently detailed chemistry for the mapping scheme adopted. The comparison of the computational costs of our approach with standard molecular dynamics simulations is a function of the system size and the number of processors employed in the parallel calculations. Due to the low amount of data exchange, the larger the number of processors, the better are the performances of the hybrid particle–field models. This feature makes these models very promising ones in the exploration of several problems in biophysics. (paper)

  15. PEMBELAJARAN METODE KOOPERATIF TIPE JIGSAW DALAM MENINGKATKAN HASIL BELAJAR BAHASA ARAB (QOWA’ID MAHASISWA PERBANKAN SYARI’AH IAIM NU METRO LAMPUNG TAHUN 2017

    Directory of Open Access Journals (Sweden)

    Muhammad Syaifullah

    2017-11-01

    Full Text Available Learning Arabic qowa'id student Syari'ah Banking Second semester Ma'arif Institute of Islamic NU Metro Lampung still not maximized. Students have difficulties to understand Arabic qowa'id material. Student learning motivation is also low. This is what makes researchers want to do research in that class. Problems to be expressed in this research are: (1 How is the application of Arabic qowa'id learning with cooperative model of jigsaw method in class A, second semester of Syari'ah Banking, (2 How to improve learning qowa'id after getting learning with cooperative learning model of jigsaw method, (3 What are the advantages and disadvantages of implementing cooperative Arabic qawaid in class A with jigsaw method. This research is a classroom action research conducted in two cycles. Each cycle is done in a cycle consisting of four stages: planning, execution, observation and reflection. The results of this study indicate an increase from cycle I of cycle II. The average class cycle I is 60.83 and the average of cycle II is 71. The students also show behavior change in the positive direction. Student activity is increasing. The improvement of test result is also followed by behavioral and motivational change based on research which has been done by the researcher that through cooperative learning with jigsaw method, Arabic qowa'id learning becomes more fun and easier for students in learning qowa'id. Suggestions that can be given is a lecturer of Arabic language should be more creative in using techniques and learning methods that involve the active role of student learning so that the learning process to get the maximum value. One alternative of learning Arabic qowa'id is by using cooperative learning jigsaw model.

  16. THE EFFECT OF JIGSAW II TOWARD LEARNING MOTIVATION AND READING COMPREHENSION AT THE SECOND GRADE OF ENGLISH STUDENTS IN STKIP DHARMA BAKTI

    Directory of Open Access Journals (Sweden)

    eka melati

    2016-10-01

    Full Text Available In teaching Reading, learning motivation and reading comprehension are essential. Ideally, after students learn the reading skills, both of their learning motivation and reading comprehension are better than before. In fact, the students still face some problems in comprehending the text. The problems are: they got low score of reading comprehension, they are lack of motivation, they are lack of vocabulary mastery, their reading achievement is still low, and the lecturer always uses small group discussion method without any variation. The purpose of this research was to find out the effect of JIgsaw II on learning motivation and reading comprehension.This study was an experimental research. Poupulation of this research was the second grade students of English Department of STKIP Dharma Bakti Lubuk Alung academic year 2010/2011 who was totally 133 students. The sample was selected by cluster random technique. The instruments were questionnaire of learning motivation and test of reading comprehension. The data were analyzed manually by t-test formula.The result of this study were learning motivation of students who were taught by Jigsaw II was better than those who were taught by small group discussion; and reading comprehension of students who taught by Jigsaw II was better than those who taught by small group discussion. It concluded that Jigsaw II produced better result on learning motivation and reading comprehension. It was implied that Jigsaw II could be used as method of teaching reading for English students.Doi: 10.22216/jit.2014.v8i2.211 

  17. Cryptic Species Due to Hybridization: A Combined Approach to Describe a New Species (Carex: Cyperaceae).

    Science.gov (United States)

    Maguilla, Enrique; Escudero, Marcial

    2016-01-01

    Disappearance of diagnostic morphological characters due to hybridization is considered to be one of the causes of the complex taxonomy of the species-rich (ca. 2000 described species) genus Carex (Cyperaceae). Carex furva s.l. belongs to section Glareosae. It is an endemic species from the high mountains of the Iberian Peninsula (Spain and Portugal). Previous studies suggested the existence of two different, cryptic taxa within C. furva s.l. Intermediate morphologies found in the southern Iberian Peninsula precluded the description of a new taxa. We aimed to determine whether C. furva s.l. should be split into two different species based on the combination of morphological and molecular data. We sampled ten populations across its full range and performed a morphological study based on measurements on herbarium specimens and silica-dried inflorescences. Both morphological and phylogenetic data support the existence of two different species within C. furva s.l. Nevertheless, intermediate morphologies and sterile specimens were found in one of the southern populations (Sierra Nevada) of C. furva s.l., suggesting the presence of hybrid populations in areas where both supposed species coexist. Hybridization between these two putative species has blurred morphological and genetic limits among them in this hybrid zone. We have proved the utility of combining molecular and morphological data to discover a new cryptic species in a scenario of hybridization. We now recognize a new species, C. lucennoiberica, endemic to the Iberian Peninsula (Sierra Nevada, Central system and Cantabrian Mountains). On the other hand, C. furva s.s. is distributed only in Sierra Nevada, where it may be threatened by hybridization with C. lucennoiberica. The restricted distribution of both species and their specific habitat requirements are the main limiting factors for their conservation.

  18. Aerodynamic Shape Optimization Design of Wing-Body Configuration Using a Hybrid FFD-RBF Parameterization Approach

    Science.gov (United States)

    Liu, Yuefeng; Duan, Zhuoyi; Chen, Song

    2017-10-01

    Aerodynamic shape optimization design aiming at improving the efficiency of an aircraft has always been a challenging task, especially when the configuration is complex. In this paper, a hybrid FFD-RBF surface parameterization approach has been proposed for designing a civil transport wing-body configuration. This approach is simple and efficient, with the FFD technique used for parameterizing the wing shape and the RBF interpolation approach used for handling the wing body junction part updating. Furthermore, combined with Cuckoo Search algorithm and Kriging surrogate model with expected improvement adaptive sampling criterion, an aerodynamic shape optimization design system has been established. Finally, the aerodynamic shape optimization design on DLR F4 wing-body configuration has been carried out as a study case, and the result has shown that the approach proposed in this paper is of good effectiveness.

  19. Hybrid Approach To Steganography System Based On Quantum Encryption And Chaos Algorithms

    Directory of Open Access Journals (Sweden)

    ZAID A. ABOD

    2018-01-01

    Full Text Available A hybrid scheme for secretly embedding image into a dithered multilevel image is presented. This work inputs both a cover image and secret image, which are scrambling and divided into groups to embedded together based on multiple chaos algorithms (Lorenz map, Henon map and Logistic map respectively. Finally, encrypt the embedded images by using one of the quantum cryptography mechanisms, which is quantum one time pad. The experimental results show that the proposed hybrid system successfully embedded images and combine with the quantum cryptography algorithms and gives high efficiency for secure communication.

  20. A hybrid approach for short-term forecasting of wind speed.

    Science.gov (United States)

    Tatinati, Sivanagaraja; Veluvolu, Kalyana C

    2013-01-01

    We propose a hybrid method for forecasting the wind speed. The wind speed data is first decomposed into intrinsic mode functions (IMFs) with empirical mode decomposition. Based on the partial autocorrelation factor of the individual IMFs, adaptive methods are then employed for the prediction of IMFs. Least squares-support vector machines are employed for IMFs with weak correlation factor, and autoregressive model with Kalman filter is employed for IMFs with high correlation factor. Multistep prediction with the proposed hybrid method resulted in improved forecasting. Results with wind speed data show that the proposed method provides better forecasting compared to the existing methods.

  1. Review and Comparison of Power Management Approaches for Hybrid Vehicles with Focus on Hydraulic Drives

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Karbaschian

    2014-05-01

    Full Text Available The main advantage of hybrid powertrains is based on the efficient transfer of power and torque from power sources to the powertrain as well as recapturing of reversible energies without effecting the vehicle performance. The benefits of hybrid hydraulic powertrains can be better utilized with an appropriate power management. In this paper, different types of power management algorithms like off-line and on-line methods are briefly reviewed and classified. Finally, the algorithms are evaluated and compared. Therefore, different related criteria are evaluated and applied.

  2. Spin injection across a hybrid heterojunction: Theoretical understanding and experimental approach (invited)

    DEFF Research Database (Denmark)

    Hu, C.M.; Nitta, J.; Jensen, Ane

    2002-01-01

    Spin injection across a hybrid ferromagnet/semiconductor junction has proven to be difficult, unlike in an all-metal junction used in giant magnetoresistance devices. The difference responsible is highlighted in a simple model. We perform spin-injection-detection experiments on devices with two...... ferromagnetic contacts on a two-dimensional electron gas confined in an InAs quantum well. We demonstrate that spin injection allows the hybrid device to combine both the advantage of the ferromagnet as well as that of the semiconductor....

  3. OPTIMISATION OF BUFFER SIZE FOR ENHANCING QOS OF VIDEO TRAFFIC USING CROSS LAYERED HYBRID TRANSPORT LAYER PROTOCOL APPROACH

    Directory of Open Access Journals (Sweden)

    S. Matilda

    2011-03-01

    Full Text Available Video streaming is gaining importance, with the wide popularity of multimedia rich applications in the Internet. Video streams are delay sensitive and require seamless flow for continuous visualization. Properly designed buffers offer a solution to queuing delay. The diagonally opposite QoS metrics associated with video traffic poses an optimization problem, in the design of buffers. This paper is a continuation of our previous work [1] and deals with the design of buffers. It aims at finding the optimum buffer size for enhancing QoS offered to video traffic. Network-centric QoS provisioning approach, along with hybrid transport layer protocol approach is adopted, to arrive at an optimum size which is independent of RTT. In this combinational approach, buffers of routers and end devices are designed to satisfy the various QoS parameters at the transport layer. OPNET Modeler is used to simulate environments for testing the design. Based on the results of simulation it is evident that the hybrid transport layer protocol approach is best suited for transmitting video traffic as it supports the economical design.

  4. Model-based design approaches for plug-in hybrid vehicle design

    Energy Technology Data Exchange (ETDEWEB)

    Mendes, C.J. [CrossChasm Technologies, Cambridge, ON (Canada); Stevens, M.B.; Fowler, M.W. [Waterloo Univ., ON (Canada). Dept. of Chemical Engineering; Fraser, R.A. [Waterloo Univ., ON (Canada). Dept. of Mechanical Engineering; Wilhelm, E.J. [Paul Scherrer Inst., Villigen (Switzerland). Energy Systems Analysis

    2007-07-01

    A model-based design process for plug-in hybrid vehicles (PHEVs) was presented. The paper discussed steps between the initial design concept and a working vehicle prototype, and focused on an investigation of the software-in-the-loop (SIL), hardware-in-the-loop (HIL), and component-in-the-loop (CIL) design phases. The role and benefits of using simulation were also reviewed. A method for mapping and identifying components was provided along with a hybrid control strategy and component-level control optimization process. The role of simulation in component evaluation, architecture design, and de-bugging procedures was discussed, as well as the role simulation networks can play in speeding deployment times. The simulations focused on work performed on a 2005 Chevrolet Equinox converted to a fuel cell hybrid electric vehicle (FCHEV). Components were aggregated to create a complete virtual vehicle. A simplified vehicle model was implemented onto the on-board vehicle control hardware. Optimization metrics were estimated at 10 alpha values during each control loop iteration. The simulation was then used to tune the control system under a variety of drive cycles and conditions. A CIL technique was used to place a physical hybrid electric vehicle (HEV) component under the control of a real time HEV/PHEV simulation. It was concluded that controllers should have a standardized component description that supports integration into advanced testing procedures. 4 refs., 9 figs.

  5. Approach to Hybrid Energy Storage Systems Dimensioning for Urban Electric Buses Regarding Efficiency and Battery Aging

    Directory of Open Access Journals (Sweden)

    Jorge Nájera

    2017-10-01

    Full Text Available This paper focuses on Hybrid Energy Storage Systems (HESS, consisting of a combination of batteries and Electric Double Layer Capacitors (EDLC, for electric urban busses. The aim of the paper is to develop a methodology to determine the hybridization percentage that allows the electric bus to work with the highest efficiency while reducing battery aging, depending on the chosen topology, control strategy, and driving cycle. Three power electronic topologies are qualitatively analyzed based on different criteria, with the topology selected as the favorite being analyzed in detail. The whole system under study is comprised of the following elements: a battery pack (LiFePO4 batteries, an EDLC pack, up to two DC-DC converters (depending on the topology, and an equivalent load, which behaves as an electric bus drive (including motion resistances and inertia. Mathematical models for the battery, EDLCs, DC-DC converter, and the vehicle itself are developed for this analysis. The methodology presented in this work, as the main scientific contribution, considers performance variation (energy efficiency and battery aging and hybridization percentage (ratio between batteries and EDLCs, defined in terms of mass, using a power load profile based on standard driving cycles. The results state that there is a hybridization percentage that increases energy efficiency and reduces battery aging, maximizing the economic benefits of the vehicle, for every combination of topology, type of storage device, control strategy, and driving cycle.

  6. A hybrid sequential approach for data clustering using K-Means and ...

    African Journals Online (AJOL)

    Experiments on four kinds of data sets have been conducted. The obtained results are compared with K-Means, PSO, Hybrid, K-Means+Genetic Algorithm and it has been found that the proposed algorithm generates more accurate, robust and better clustering results. International Journal of Engineering, Science and ...

  7. A Frequency Control Approach for Hybrid Power System Using Multi-Objective Optimization

    Directory of Open Access Journals (Sweden)

    Mohammed Elsayed Lotfy

    2017-01-01

    Full Text Available A hybrid power system uses many wind turbine generators (WTG and solar photovoltaics (PV in isolated small areas. However, the output power of these renewable sources is not constant and can diverge quickly, which has a serious effect on system frequency and the continuity of demand supply. In order to solve this problem, this paper presents a new frequency control scheme for a hybrid power system to ensure supplying a high-quality power in isolated areas. The proposed power system consists of a WTG, PV, aqua-electrolyzer (AE, fuel cell (FC, battery energy storage system (BESS, flywheel (FW and diesel engine generator (DEG. Furthermore, plug-in hybrid electric vehicles (EVs are implemented at the customer side. A full-order observer is utilized to estimate the supply error. Then, the estimated supply error is considered in a frequency domain. The high-frequency component is reduced by BESS and FW; while the low-frequency component of supply error is mitigated using FC, EV and DEG. Two PI controllers are implemented in the proposed system to control the system frequency and reduce the supply error. The epsilon multi-objective genetic algorithm ( ε -MOGA is applied to optimize the controllers’ parameters. The performance of the proposed control scheme is compared with that of recent well-established techniques, such as a PID controller tuned by the quasi-oppositional harmony search algorithm (QOHSA. The effectiveness and robustness of the hybrid power system are investigated under various operating conditions.

  8. Reliable Radiation Hybrid Maps: An Efficient Scalable Clustering-based Approach

    Science.gov (United States)

    The process of mapping markers from radiation hybrid mapping (RHM) experiments is equivalent to the traveling salesman problem and, thereby, has combinatorial complexity. As an additional problem, experiments typically result in some unreliable markers that reduce the overall quality of the map. We ...

  9. A hybrid classical-quantum approach for ultra-scaled confined nanostructures : modeling and simulation*

    Directory of Open Access Journals (Sweden)

    Pietra Paola

    2012-04-01

    Full Text Available We propose a hybrid classical-quantum model to study the motion of electrons in ultra-scaled confined nanostructures. The transport of charged particles, considered as one dimensional, is described by a quantum effective mass model in the active zone coupled directly to a drift-diffusion problem in the rest of the device. We explain how this hybrid model takes into account the peculiarities due to the strong confinement and we present numerical simulations for a simplified carbon nanotube. Nous proposons un modèle hybride classique-quantique pour décrire le mouvement des électrons dans des nanostructures très fortement confinées. Le transport des particules, consideré unidimensionel, est décrit par un modèle quantique avec masse effective dans la zone active couplé à un problème de dérive-diffusion dans le reste du domaine. Nous expliquons comment ce modèle hybride prend en compte les spécificités de ce très fort confinement et nous présentons des résultats numériques pour un nanotube de carbone simplifié.

  10. A novel hybrid approach for predicting wind farm power production based on wavelet transform, hybrid neural networks and imperialist competitive algorithm

    International Nuclear Information System (INIS)

    Aghajani, Afshin; Kazemzadeh, Rasool; Ebrahimi, Afshin

    2016-01-01

    Highlights: • Proposing a novel hybrid method for short-term prediction of wind farms with high accuracy. • Investigating the prediction accuracy for proposed method in comparison with other methods. • Investigating the effect of six types of parameters as input data on predictions. • Comparing results for 6 & 4 types of the input parameters – addition of pressure and air humidity. - Abstract: This paper proposes a novel hybrid approach to forecast electric power production in wind farms. Wavelet transform (WT) is employed to filter input data of wind power, while radial basis function (RBF) neural network is utilized for primary prediction. For better predictions the main forecasting engine is comprised of three multilayer perceptron (MLP) neural networks by different learning algorithms of Levenberg–Marquardt (LM), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and Bayesian regularization (BR). Meta-heuristic technique Imperialist Competitive Algorithm (ICA) is used to optimize neural networks’ weightings in order to escape from local minima. In the forecast process, the real data of wind farms located in the southern part of Alberta, Canada, are used to train and test the proposed model. The data are a complete set of six meteorological and technical characteristics, including wind speed, wind power, wind direction, temperature, pressure, and air humidity. In order to demonstrate the efficiency of the proposed method, it is compared with several other wind power forecast techniques. Results of optimizations indicate the superiority of the proposed method over the other mentioned techniques; and, forecasting error is remarkably reduced. For instance, the average normalized root mean square error (NRMSE) and average mean absolute percentage error (MAPE) are respectively 11% and 14% lower for the proposed method in 1-h-ahead forecasts over a 24-h period with six types of input than those for the best of the compared models.

  11. Eksperimentasi Model Pembelajaran Kooperatif Tipe Jigsaw dan Team Assisted Individualized (Tai) pada Materi Sistem Persamaan Linear Dua Variabel (Spldv) Ditinjau dari Adversity Quotient (Aq) Siswa Kelas VIII SMP Negeri Se-kabupaten Karanganyar

    OpenAIRE

    Pambudi, Pangesti Arum; Mardiyana, Mardiyana; Sari Saputro, Dewi Retno

    2016-01-01

    The aim of this research was to determine the effect of learning models on mathematics achievement viewed from students' AQ. The learning models compared were Jigsaw cooperative learning, TAI cooperative learning, and direct learning. The type of this research was quasi-experimental research. Population was all of state Junior High School students in Karanganyar Regency on academic year 2015/2016. Samples for group experiment 1 (Jigsaw cooperative learning model) were 98 students, group exper...

  12. Optimizing Thermal-Elastic Properties of C/C–SiC Composites Using a Hybrid Approach and PSO Algorithm

    Science.gov (United States)

    Xu, Yingjie; Gao, Tian

    2016-01-01

    Carbon fiber-reinforced multi-layered pyrocarbon–silicon carbide matrix (C/C–SiC) composites are widely used in aerospace structures. The complicated spatial architecture and material heterogeneity of C/C–SiC composites constitute the challenge for tailoring their properties. Thus, discovering the intrinsic relations between the properties and the microstructures and sequentially optimizing the microstructures to obtain composites with the best performances becomes the key for practical applications. The objective of this work is to optimize the thermal-elastic properties of unidirectional C/C–SiC composites by controlling the multi-layered matrix thicknesses. A hybrid approach based on micromechanical modeling and back propagation (BP) neural network is proposed to predict the thermal-elastic properties of composites. Then, a particle swarm optimization (PSO) algorithm is interfaced with this hybrid model to achieve the optimal design for minimizing the coefficient of thermal expansion (CTE) of composites with the constraint of elastic modulus. Numerical examples demonstrate the effectiveness of the proposed hybrid model and optimization method. PMID:28773343

  13. A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-25

    This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

  14. A novel hybrid approach based on Particle Swarm Optimization and Ant Colony Algorithm to forecast energy demand of Turkey

    International Nuclear Information System (INIS)

    Kıran, Mustafa Servet; Özceylan, Eren; Gündüz, Mesut; Paksoy, Turan

    2012-01-01

    Highlights: ► PSO and ACO algorithms are hybridized for forecasting energy demands of Turkey. ► Linear and quadratic forms are developed to meet the fluctuations of indicators. ► GDP, population, export and import have significant impacts on energy demand. ► Quadratic form provides better fit solution than linear form. ► Proposed approach gives lower estimation error than ACO and PSO, separately. - Abstract: This paper proposes a new hybrid method (HAP) for estimating energy demand of Turkey using Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). Proposed energy demand model (HAPE) is the first model which integrates two mentioned meta-heuristic techniques. While, PSO, developed for solving continuous optimization problems, is a population based stochastic technique; ACO, simulating behaviors between nest and food source of real ants, is generally used for discrete optimizations. Hybrid method based PSO and ACO is developed to estimate energy demand using gross domestic product (GDP), population, import and export. HAPE is developed in two forms which are linear (HAPEL) and quadratic (HAPEQ). The future energy demand is estimated under different scenarios. In order to show the accuracy of the algorithm, a comparison is made with ACO and PSO which are developed for the same problem. According to obtained results, relative estimation errors of the HAPE model are the lowest of them and quadratic form (HAPEQ) provides better-fit solutions due to fluctuations of the socio-economic indicators.

  15. A hybrid nudging-ensemble Kalman filter approach to data assimilation. Part I: application in the Lorenz system

    Directory of Open Access Journals (Sweden)

    Lili Lei

    2012-05-01

    Full Text Available A hybrid data assimilation approach combining nudging and the ensemble Kalman filter (EnKF for dynamic analysis and numerical weather prediction is explored here using the non-linear Lorenz three-variable model system with the goal of a smooth, continuous and accurate data assimilation. The hybrid nudging-EnKF (HNEnKF computes the hybrid nudging coefficients from the flow-dependent, time-varying error covariance matrix from the EnKF's ensemble forecasts. It extends the standard diagonal nudging terms to additional off-diagonal statistical correlation terms for greater inter-variable influence of the innovations in the model's predictive equations to assist in the data assimilation process. The HNEnKF promotes a better fit of an analysis to data compared to that achieved by either nudging or incremental analysis update (IAU. When model error is introduced, it produces similar or better root mean square errors compared to the EnKF while minimising the error spikes/discontinuities created by the intermittent EnKF. It provides a continuous data assimilation with better inter-variable consistency and improved temporal smoothness than that of the EnKF. Data assimilation experiments are also compared to the ensemble Kalman smoother (EnKS. The HNEnKF has similar or better temporal smoothness than that of the EnKS, and with much smaller central processing unit (CPU time and data storage requirements.

  16. Teaching research methods in nursing using Aronson's Jigsaw Technique. A cross-sectional survey of student satisfaction.

    Science.gov (United States)

    Leyva-Moral, Juan M; Riu Camps, Marta

    2016-05-01

    To adapt nursing studies to the European Higher Education Area, new teaching methods have been included that assign maximum importance to student-centered learning and collaborative work. The Jigsaw Technique is based on collaborative learning and everyone in the group must play their part because each student's mark depends on the other students. Home group members are given the responsibility to become experts in a specific area of knowledge. Experts meet together to reach an agreement and improve skills. Finally, experts return to their home groups to share all their findings. The aim of this study was to evaluate nursing student satisfaction with the Jigsaw Technique used in the context of a compulsory course in research methods for nursing. A cross-sectional study was conducted using a self-administered anonymous questionnaire administered to students who completed the Research Methods course during the 2012-13 and 2013-14 academic years. The questionnaire was developed taking into account the learning objectives, competencies and skills that should be acquired by students, as described in the course syllabus. The responses were compared by age group (younger or older than 22years). A total of 89.6% of nursing students under 22years believed that this methodology helped them to develop teamwork, while this figure was 79.6% in older students. Nursing students also believed it helped them to work independently, with differences according to age, 79.7% and 58% respectively (p=0.010). Students disagreed with the statement "The Jigsaw Technique involves little workload", with percentages of 88.5% in the group under 22years and 80% in older students. Most believed that this method should not be employed in upcoming courses, although there were differences by age, with 44.3% of the younger group being against and 62% of the older group (p=0.037). The method was not highly valued by students, mainly by those older than 22years, who concluded that they did not learn

  17. A hybrid approach to predict the relationship between tablet tensile strength and compaction pressure using analytical powder compression.

    Science.gov (United States)

    Persson, Ann-Sofie; Alderborn, Göran

    2018-04-01

    The objective was to present a hybrid approach to predict the strength-pressure relationship (SPR) of tablets using common compression parameters and a single measurement of tablet tensile strength. Experimental SPR were derived for six pharmaceutical powders with brittle and ductile properties and compared to predicted SPR based on a three-stage approach. The prediction was based on the Kawakita b -1 parameter and the in-die Heckel yield stress, an estimate of maximal tensile strength, and a parameter proportionality factor α. Three values of α were used to investigate the influence of the parameter on the SPR. The experimental SPR could satisfactorily be described by the three stage model, however for sodium bicarbonate the tensile strength plateau could not be observed experimentally. The shape of the predicted SPR was to a minor extent influenced by the Kawakita b -1 but the width of the linear region was highly influenced by α. An increased α increased the width of the linear region and thus also the maximal predicted tablet tensile strength. Furthermore, the correspondence between experimental and predicted SPR was influenced by the α value and satisfactory predictions were in general obtained for α = 4.1 indicating the predictive potential of the hybrid approach. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  18. An Approach to Evaluate Stability for Cable-Based Parallel Camera Robots with Hybrid Tension-Stiffness Properties

    Directory of Open Access Journals (Sweden)

    Huiling Wei

    2015-12-01

    Full Text Available This paper focuses on studying the effect of cable tensions and stiffness on the stability of cable-based parallel camera robots. For this purpose, the tension factor and the stiffness factor are defined, and the expression of stability is deduced. A new approach is proposed to calculate the hybrid-stability index with the minimum cable tension and the minimum singular value. Firstly, the kinematic model of a cable-based parallel camera robot is established. Based on the model, the tensions are solved and a tension factor is defined. In order to obtain the tension factor, an optimization of the cable tensions is carried out. Then, an expression of the system's stiffness is deduced and a stiffness factor is defined. Furthermore, an approach to evaluate the stability of the cable-based camera robots with hybrid tension-stiffness properties is presented. Finally, a typical three-degree-of-freedom cable-based parallel camera robot with four cables is studied as a numerical example. The simulation results show that the approach is both reasonable and effective.

  19. Application of a hybrid multiscale approach to simulate hydrologic and biogeochemical processes in the river-groundwater interaction zone.

    Energy Technology Data Exchange (ETDEWEB)

    Hammond, Glenn Edward; Yang, Xiaofan; Song, Xuehang; Song, Hyun-Seob; Hou, Zhangshuan; Chen, Xingyuan; Liu, Yuanyuan; Scheibe, Tim

    2017-03-01

    The groundwater-surface water interaction zone (GSIZ) plays an important role in riverine and watershed ecosystems as the exchange of waters of variable composition and temperature (hydrologic exchange flows) stimulate microbial activity and associated biogeochemical reactions. Variable temporal and spatial scales of hydrologic exchange flows, heterogeneity of the subsurface environment, and complexity of biogeochemical reaction networks in the GSIZ present challenges to incorporation of fundamental process representations and model parameterization across a range of spatial scales (e.g. from pore-scale to field scale). This paper presents a novel hybrid multiscale simulation approach that couples hydrologic-biogeochemical (HBGC) processes between two distinct length scales of interest.

  20. Chaotic system synchronization with an unknown master model using a hybrid HOD active control approach

    Energy Technology Data Exchange (ETDEWEB)

    Du Shengzhi [Department of EAD, ICT Faculty, Tshwane University of Technology, Pretoria 0001 (South Africa); French South Africa Technical Institute of Electronics (F' SATIE), Tshwane University of Technology, Pretoria 0001 (South Africa)], E-mail: dushengzhi@gmail.com; Wyk, Barend J. van; Qi Guoyuan; Tu Chunling [French South Africa Technical Institute of Electronics (F' SATIE), Tshwane University of Technology, Pretoria 0001 (South Africa)

    2009-11-15

    In this paper, a hybrid method using active control and a High Order Differentiator (HOD) methodology is proposed to synchronize chaotic systems. Compared to some traditional active control methods, this new method can synchronize chaotic systems where only output states of the master system are available, i.e. the system is considered a black box. The HOD is used to estimate the derivative information of the master system followed by an active control methodology relying on HOD information. The Qi hyperchaotic system is used to verify the performance of this hybrid method. The proposed method is also compared to some traditional methods. Experimental results show that the proposed method has high synchronization precision and speed and is robust against uncertainties in the master system. The circus implements of the proposed synchronizing scheme are included in this paper. The simulation results show the feasibility of the proposed scheme.

  1. A novel hybrid approach with multidimensional-like effects for compressible flow computations

    Science.gov (United States)

    Kalita, Paragmoni; Dass, Anoop K.

    2017-07-01

    A multidimensional scheme achieves good resolution of strong and weak shocks irrespective of whether the discontinuities are aligned with or inclined to the grid. However, these schemes are computationally expensive. This paper achieves similar effects by hybridizing two schemes, namely, AUSM and DRLLF and coupling them through a novel shock switch that operates - unlike existing switches - on the gradient of the Mach number across the cell-interface. The schemes that are hybridized have contrasting properties. The AUSM scheme captures grid-aligned (and strong) shocks crisply but it is not so good for non-grid-aligned weaker shocks, whereas the DRLLF scheme achieves sharp resolution of non-grid-aligned weaker shocks, but is not as good for grid-aligned strong shocks. It is our experience that if conventional shock switches based on variables like density, pressure or Mach number are used to combine the schemes, the desired effect of crisp resolution of grid-aligned and non-grid-aligned discontinuities are not obtained. To circumvent this problem we design a shock switch based - for the first time - on the gradient of the cell-interface Mach number with very impressive results. Thus the strategy of hybridizing two carefully selected schemes together with the innovative design of the shock switch that couples them, affords a method that produces the effects of a multidimensional scheme with a lower computational cost. It is further seen that hybridization of the AUSM scheme with the recently developed DRLLFV scheme using the present shock switch gives another scheme that provides crisp resolution for both shocks and boundary layers. Merits of the scheme are established through a carefully selected set of numerical experiments.

  2. Towards a hybrid strong/weak coupling approach to jet quenching

    CERN Document Server

    Casalderrey-Solana, Jorge; Milhano, José Guilherme; Pablos, Daniel; Rajagopal, Krishna

    2014-01-01

    We explore a novel hybrid model containing both strong and weak coupling physics for high energy jets traversing a deconfined medium. This model is based on supplementing a perturbative DGLAP shower with strongly coupled energy loss rate. We embed this system into a realistic hydrodynamic evolution of hot QCD plasma. We confront our results with LHC data, obtaining good agreement for jet RAARAA, dijet imbalance AJAJ and fragmentation functions.

  3. Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

    Science.gov (United States)

    Moeeni, Hamid; Bonakdari, Hossein; Ebtehaj, Isa

    2017-03-01

    Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA-GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years' worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA-GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA-ANN models. The results indicate that the SARIMA-GEP model ( R 2=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA-ANN ( R 2=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA-GEP over the SARIMA-ANN model.

  4. Novel hybrid (magnet plus curve grasper) technique during transumbilical cholecystectomy: initial experience of a promising approach.

    Science.gov (United States)

    Millan, Carolina; Bignon, Horacion; Bellia, Gaston; Buela, Enrique; Rabinovich, Fernando; Albertal, Mariano; Martinez Ferro, Marcelo

    2013-10-01

    The use of magnets in transumbilical cholecystectomy (TUC) improves triangulation and achieves an optimal critical view. Nonetheless, the tendency of the magnets to collide hinders the process. In order to simplify the surgical technique, we developed a hybrid model with a single magnet and a curved grasper. All TUCs performed with a hybrid strategy in our pediatric population between September 2009 and July 2012 were retrospectively reviewed. Of 260 surgical procedures in which at least one magnet was used, 87 were TUCs. Of those, 62 were hybrid: 33 in adults and 29 in pediatric patients. The technique combines a magnet and a curved grasper. Through a transumbilical incision, we placed a 12-mm trocar and another flexible 5-mm trocar. The laparoscope with the working channel used the 12-mm trocar. The magnetic grasper was introduced to the abdominal cavity using the working channel to provide cephalic retraction of the gallbladder fundus. Across the flexible trocar, the assistant manipulated the curved grasper to mobilize the infundibulum. The surgeon operated through the working channel of the laparoscope. In this pediatric population, the mean age was 14 years (range, 4-17 years), and mean weight was 50 kg (range, 18-90 kg); 65% were girls. Mean operative time was 62 minutes. All procedures achieved a critical view of safety with no instrumental collision. There were no intraoperative or postoperative complications. The hospital stay was 1.4±0.6 days, and the median follow-up was 201 days. A hybrid technique, combining magnets and a curved grasper, simplifies transumbilical surgery. It seems feasible and safe for TUC and potentially reproducible.

  5. Experts and Machines against Bullies: A Hybrid Approach to Detect Cyberbullies

    OpenAIRE

    Dadvar, M.; Trieschnigg, Rudolf Berend; de Jong, Franciska M.G.

    2014-01-01

    Cyberbullying is becoming a major concern in online environments with troubling consequences. However, most of the technical studies have focused on the detection of cyberbullying through identifying harassing comments rather than preventing the incidents by detecting the bullies. In this work we study the automatic detection of bully users on YouTube. We compare three types of automatic detection: an expert system, supervised machine learning models, and a hybrid type combining the two. All ...

  6. Thermo-optic characteristics of hybrid polymer/silica microstructured optical fiber: An analytical approach

    Science.gov (United States)

    Sharma, Dinesh Kumar; Sharma, Anurag; Tripathi, Saurabh Mani

    2018-04-01

    Microstructured optical fibers (MOFs) allow a variety of advanced materials to be infiltrated in their air-voids for obtaining the increased fiber functionality, and offering a new versatile platform for developing the compact sensors devices. We aim to investigate the thermal characteristics of high-index core triangular hybrid polymer/silica MOFs with circular air-voids infused with polymer by using the analytical field model [1]. We demonstrate that infiltration of air-voids with polymer, e.g., polydimethylsiloxane (PDMS) can facilitate to tune the fundamental modal properties of MOF such as effective index of the mode, near and the far-field profiles, effective mode area and the numerical aperture over the temperature ranging from 0 °C to 100 °C, for different values of relative air-void ratios. The evolution of the mode shape for a given temperature has been investigated in transition from near-field to far-field regime. We have studied the thermal dependence of splice losses between hybrid MOF and the standard step-index single-mode optical fiber in combination with Fresnel losses. For enhancing the evanescent field interactions, we have evaluated fraction of power associated with fundamental mode of hybrid MOF. We have compared the accuracy of our results with those based on full-vector finite-difference (FD) method, as available in the literature.

  7. Performance of hybrid nano-micro reinforced mg metal matrix composites brake calliper: simulation approach

    Science.gov (United States)

    Fatchurrohman, N.; Chia, S. T.

    2017-10-01

    Most commercial vehicles use brake calliper made of grey cast iron (GCI) which possesses heavy weight. This contributes to the total weight of the vehicle which can lead to higher fuel consumption. Another major problem is GCI calliper tends to deflect during clamping action, known as “bending of bridge”. This will result in extended pedal travel. Magnesium metal matrix composites (Mg-MMC) has a potential application in the automotive industry since it having a lower density, higher strength and very good modulus of elasticity as compared to GCI. This paper proposed initial development of hybrid Mg-MMC brake calliper. This was achieved by analyzing the performance of hybrid nano-micro reinforced Mg-MMC and comparing with the conventional GCI brake calliper. It was performed using simulation in ANSYS, a finite element analysis (FEA) software. The results show that hybrid Mg-MMC has better performance in terms of reduction the weight of the brake calliper, reduction in total deformation/deflection and better ability to withstand equivalent elastic strain.

  8. Modeling level change in Lake Urmia using hybrid artificial intelligence approaches

    Science.gov (United States)

    Esbati, M.; Ahmadieh Khanesar, M.; Shahzadi, Ali

    2017-06-01

    The investigation of water level fluctuations in lakes for protecting them regarding the importance of these water complexes in national and regional scales has found a special place among countries in recent years. The importance of the prediction of water level balance in Lake Urmia is necessary due to several-meter fluctuations in the last decade which help the prevention from possible future losses. For this purpose, in this paper, the performance of adaptive neuro-fuzzy inference system (ANFIS) for predicting the lake water level balance has been studied. In addition, for the training of the adaptive neuro-fuzzy inference system, particle swarm optimization (PSO) and hybrid backpropagation-recursive least square method algorithm have been used. Moreover, a hybrid method based on particle swarm optimization and recursive least square (PSO-RLS) training algorithm for the training of ANFIS structure is introduced. In order to have a more fare comparison, hybrid particle swarm optimization and gradient descent are also applied. The models have been trained, tested, and validated based on lake level data between 1991 and 2014. For performance evaluation, a comparison is made between these methods. Numerical results obtained show that the proposed methods with a reasonable error have a good performance in water level balance prediction. It is also clear that with continuing the current trend, Lake Urmia will experience more drop in the water level balance in the upcoming years.

  9. A hierarchical approach of hybrid image classification for land use and land cover mapping

    Directory of Open Access Journals (Sweden)

    Rahdari Vahid

    2018-01-01

    Full Text Available Remote sensing data analysis can provide thematic maps describing land-use and land-cover (LULC in a short period. Using proper image classification method in an area, is important to overcome the possible limitations of satellite imageries for producing land-use and land-cover maps. In the present study, a hierarchical hybrid image classification method was used to produce LULC maps using Landsat Thematic mapper TM for the year of 1998 and operational land imager OLI for the year of 2016. Images were classified using the proposed hybrid image classification method, vegetation cover crown percentage map from normalized difference vegetation index, Fisher supervised classification and object-based image classification methods. Accuracy assessment results showed that the hybrid classification method produced maps with total accuracy up to 84 percent with kappa statistic value 0.81. Results of this study showed that the proposed classification method worked better with OLI sensor than with TM. Although OLI has a higher radiometric resolution than TM, the produced LULC map using TM is almost accurate like OLI, which is because of LULC definitions and image classification methods used.

  10. A templated approach for multi-physics modeling of hybrid energy systems in Modelica

    Energy Technology Data Exchange (ETDEWEB)

    Greenwood, Michael Scott [ORNL; Cetiner, Sacit M. [ORNL; Harrison, Thomas J. [ORNL; Fugate, David [Oak Ridge National Laboratory (ORNL)

    2018-01-01

    A prototypical hybrid energy system (HES) couples a primary thermal power generator (i.e., nuclear power plant) with one or more additional subsystems beyond the traditional balance of plant electricity generation system. The definition and architecture of an HES can be adapted based on the needs and opportunities of a given local market. For example, locations in need of potable water may be best served by coupling a desalination plant to the HES. A location near an oil refinery may have a need for emission-free hydrogen production. The flexible, multidomain capabilities of Modelica are being used to investigate the dynamics (e.g., thermal hydraulics and electrical generation/consumption) of such a hybrid system. This paper examines the simulation infrastructure created to enable the coupling of multiphysics subsystem models for HES studies. A demonstration of a tightly coupled nuclear hybrid energy system implemented using the Modelica based infrastructure is presented for two representative cases. An appendix is also included providing a step-by-step procedure for using the template-based infrastructure.

  11. A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation

    International Nuclear Information System (INIS)

    Mohammadi, Kasra; Shamshirband, Shahaboddin; Tong, Chong Wen; Arif, Muhammad; Petković, Dalibor; Ch, Sudheer

    2015-01-01

    Highlights: • Horizontal global solar radiation (HGSR) is predicted based on a new hybrid approach. • Support Vector Machines and Wavelet Transform algorithm (SVM–WT) are combined. • Different sets of meteorological elements are used to predict HGSR. • The precision of SVM–WT is assessed thoroughly against ANN, GP and ARMA. • SVM–WT would be an appealing approach to predict HGSR and outperforms others. - Abstract: In this paper, a new hybrid approach by combining the Support Vector Machine (SVM) with Wavelet Transform (WT) algorithm is developed to predict horizontal global solar radiation. The predictions are conducted on both daily and monthly mean scales for an Iranian coastal city. The proposed SVM–WT method is compared against other existing techniques to demonstrate its efficiency and viability. Three different sets of parameters are served as inputs to establish three models. The results indicate that the model using relative sunshine duration, difference between air temperatures, relative humidity, average temperature and extraterrestrial solar radiation as inputs shows higher performance than other models. The statistical analysis demonstrates that SVM–WT approach enjoys very good performance and outperforms other approaches. For the best SVM–WT model, the obtained statistical indicators of mean absolute percentage error, mean absolute bias error, root mean square error, relative root mean square error and coefficient of determination for daily estimation are 6.9996%, 0.8405 MJ/m 2 , 1.4245 MJ/m 2 , 7.9467% and 0.9086, respectively. Also, for monthly mean estimation the values are 3.2601%, 0.5104 MJ/m 2 , 0.6618 MJ/m 2 , 3.6935% and 0.9742, respectively. Based upon relative percentage error, for the best SVM–WT model, 88.70% of daily predictions fall within the acceptable range of −10% to +10%

  12. A hybrid wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series.

    Science.gov (United States)

    Wang, Dong; Borthwick, Alistair G; He, Handan; Wang, Yuankun; Zhu, Jieyu; Lu, Yuan; Xu, Pengcheng; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

    2018-01-01

    Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Design-order, non-conformal low-Mach fluid algorithms using a hybrid CVFEM/DG approach

    Science.gov (United States)

    Domino, Stefan P.

    2018-04-01

    A hybrid, design-order sliding mesh algorithm, which uses a control volume finite element method (CVFEM), in conjunction with a discontinuous Galerkin (DG) approach at non-conformal interfaces, is outlined in the context of a low-Mach fluid dynamics equation set. This novel hybrid DG approach is also demonstrated to be compatible with a classic edge-based vertex centered (EBVC) scheme. For the CVFEM, element polynomial, P, promotion is used to extend the low-order P = 1 CVFEM method to higher-order, i.e., P = 2. An equal-order low-Mach pressure-stabilized methodology, with emphasis on the non-conformal interface boundary condition, is presented. A fully implicit matrix solver approach that accounts for the full stencil connectivity across the non-conformal interface is employed. A complete suite of formal verification studies using the method of manufactured solutions (MMS) is performed to verify the order of accuracy of the underlying methodology. The chosen suite of analytical verification cases range from a simple steady diffusion system to a traveling viscous vortex across mixed-order non-conformal interfaces. Results from all verification studies demonstrate either second- or third-order spatial accuracy and, for transient solutions, second-order temporal accuracy. Significant accuracy gains in manufactured solution error norms are noted even with modest promotion of the underlying polynomial order. The paper also demonstrates the CVFEM/DG methodology on two production-like simulation cases that include an inner block subjected to solid rotation, i.e., each of the simulations include a sliding mesh, non-conformal interface. The first production case presented is a turbulent flow past a high-rate-of-rotation cube (Re, 4000; RPM, 3600) on like and mixed-order polynomial interfaces. The final simulation case is a full-scale Vestas V27 225 kW wind turbine (tower and nacelle omitted) in which a hybrid topology, low-order mesh is used. Both production simulations

  14. Effects of age and type of picture on visuospatial working memory assessed with a computerized jigsaw-puzzle task.

    Science.gov (United States)

    Toril, Pilar; Reales, José M; Mayas, Julia; Ballesteros, Soledad

    2017-09-15

    We investigated the effect of age and color in a computerized version of the jigsaw-puzzle task. In Experiment 1, young and older adults were presented with puzzles in color and black-and-white line drawings, varying in difficulty from 4 to 9 pieces. Older adults performed the task better with the black-and-white stimuli and younger adults performed better with the color ones. In Experiment 2, new older and young adults identified the same fragmented pictures as fast and accurately as possible. The older group identified the black-and-white stimuli faster than those presented in color, while the younger adults identified both similarly. In Experiment 3A, new older and young groups performed the puzzle task with the same color pictures and their monochrome versions. In Experiment 3B, participants performed a speeded identification task with the two sets. The findings of these experiments showed that older adults have a memory not a perceptual difficulty.

  15. Hybrid Approach for Biliary Interventions Employing MRI-Guided Bile Duct Puncture with Near-Real-Time Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Wybranski, Christian, E-mail: Christian.Wybranski@uk-koeln.de [University Hospital of Cologne, Department of Diagnostic and Interventional Radiology (Germany); Pech, Maciej [Otto-von-Guericke University Medical School, Department of Radiology and Nuclear Medicine (Germany); Lux, Anke [Otto-von-Guericke University Medical School, Institute of Biometry and Medical Informatics (Germany); Ricke, Jens; Fischbach, Frank; Fischbach, Katharina [Otto-von-Guericke University Medical School, Department of Radiology and Nuclear Medicine (Germany)

    2017-06-15

    ObjectiveTo assess the feasibility of a hybrid approach employing MRI-guided bile duct (BD) puncture for subsequent fluoroscopy-guided biliary interventions in patients with non-dilated (≤3 mm) or dilated BD (≥3 mm) but unfavorable conditions for ultrasonography (US)-guided BD puncture.MethodsA total of 23 hybrid interventions were performed in 21 patients. Visualization of BD and puncture needles (PN) in the interventional MR images was rated on a 5-point Likert scale by two radiologists. Technical success, planning time, BD puncture time and positioning adjustments of the PN as well as technical success of the biliary intervention and complication rate were recorded.ResultsVisualization even of third-order non-dilated BD and PN was rated excellent by both radiologists with good to excellent interrater agreement. MRI-guided BD puncture was successful in all cases. Planning and BD puncture times were 1:36 ± 2.13 (0:16–11:07) min. and 3:58 ± 2:35 (1:11–9:32) min. Positioning adjustments of the PN was necessary in two patients. Repeated capsular puncture was not necessary in any case. All biliary interventions were completed successfully without major complications.ConclusionA hybrid approach which employs MRI-guided BD puncture for subsequent fluoroscopy-guided biliary intervention is feasible in clinical routine and yields high technical success in patients with non-dilated BD and/or unfavorable conditions for US-guided puncture. Excellent visualization of BD and PN in near-real-time interventional MRI allows successful cannulation of the BD.

  16. Relative efficiency of hydrogen technologies for the hydrogen economy : a fuzzy AHP/DEA hybrid model approach

    International Nuclear Information System (INIS)

    Lee, S.

    2009-01-01

    As a provider of national energy security, the Korean Institute of Energy Research is seeking to establish a long term strategic technology roadmap for a hydrogen-based economy. This paper addressed 5 criteria regarding the strategy, notably economic impact, commercial potential, inner capacity, technical spinoff, and development cost. The fuzzy AHP and DEA hybrid model were used in a two-stage multi-criteria decision making approach to evaluate the relative efficiency of hydrogen technologies for the hydrogen economy. The fuzzy analytic hierarchy process reflects the uncertainty of human thoughts with interval values instead of clear-cut numbers. It therefore allocates the relative importance of 4 criteria, notably economic impact, commercial potential, inner capacity and technical spin-off. The relative efficiency of hydrogen technologies for the hydrogen economy can be measured via data envelopment analysis. It was concluded that the scientific decision making approach can be used effectively to allocate research and development resources and activities

  17. Relative efficiency of hydrogen technologies for the hydrogen economy : a fuzzy AHP/DEA hybrid model approach

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S. [Korea Inst. of Energy Research, Daejeon (Korea, Republic of). Energy Policy Research Division; Mogi, G. [Tokyo Univ., (Japan). Dept. of Technology Management for Innovation, Graduate School of Engineering; Kim, J. [Korea Inst. of Energy Research, Daejeon (Korea, Republic of)

    2009-07-01

    As a provider of national energy security, the Korean Institute of Energy Research is seeking to establish a long term strategic technology roadmap for a hydrogen-based economy. This paper addressed 5 criteria regarding the strategy, notably economic impact, commercial potential, inner capacity, technical spinoff, and development cost. The fuzzy AHP and DEA hybrid model were used in a two-stage multi-criteria decision making approach to evaluate the relative efficiency of hydrogen technologies for the hydrogen economy. The fuzzy analytic hierarchy process reflects the uncertainty of human thoughts with interval values instead of clear-cut numbers. It therefore allocates the relative importance of 4 criteria, notably economic impact, commercial potential, inner capacity and technical spin-off. The relative efficiency of hydrogen technologies for the hydrogen economy can be measured via data envelopment analysis. It was concluded that the scientific decision making approach can be used effectively to allocate research and development resources and activities.

  18. New approaches to the development of hybrid nanocomposites: from structural materials to high-tech applications

    International Nuclear Information System (INIS)

    Gerasin, V A; Antipov, Evgenii M; Karbushev, V V; Kulichikhin, Valerii G; Karpacheva, Galina P; Talroze, Raisa V; Kudryavtsev, Y V

    2013-01-01

    Current challenges in the development of various polymer nanocomposites and in the study of their properties are considered. Results of studying hybrid structural (polymer–layered silicates, polymer–nanodiamonds) and functional (based on conducting or liquid-crystalline polymers) nanomaterials are presented. Methods of modification of nanoparticles and their dispersion in a polymer matrix, and the role of interactions between a polymer matrix and fillers, as well as of nanoparticle morphology realized in the course of processing, are discussed. The bibliography includes 453 references.

  19. A Piecewise Affine Hybrid Systems Approach to Fault Tolerant Satellite Formation Control

    DEFF Research Database (Denmark)

    Grunnet, Jacob Deleuran; Larsen, Jesper Abildgaard; Bak, Thomas

    2008-01-01

    In this paper a procedure for modelling satellite formations   including failure dynamics as a piecewise-affine hybrid system is   shown. The formulation enables recently developed methods and tools   for control and analysis of piecewise-affine systems to be applied   leading to synthesis of fault...... tolerant controllers and analysis of   the system behaviour given possible faults.  The method is   illustrated using a simple example involving two satellites trying   to reach a specific formation despite of actuator faults occurring....

  20. Physical Interactions with Digital Strings - A hybrid approach to a digital keyboard instrument

    DEFF Research Database (Denmark)

    Dahlstedt, Palle

    2017-01-01

    of stopping and muting the strings at arbitrary positions. The parameters of the string model are controlled through TouchKeys multitouch sensors on each key, combined with MIDI data and acoustic signals from the digital keyboard frame, using a novel mapping. The instrument is evaluated from a performing...... of control. The contributions are two-fold. First, the use of acoustic sounds from a physical keyboard for excitations and resonances results in a novel hybrid keyboard instrument in itself. Second, the digital model of "inside piano" playing, using multitouch keyboard data, allows for performance techniques...

  1. G-centers in irradiated silicon revisited: A screened hybrid density functional theory approach

    KAUST Repository

    Wang, H.

    2014-05-13

    Electronic structure calculations employing screened hybrid density functional theory are used to gain fundamental insight into the interaction of carbon interstitial (Ci) and substitutional (Cs) atoms forming the CiCs defect known as G-center in silicon (Si). The G-center is one of the most important radiation related defects in Czochralski grown Si. We systematically investigate the density of states and formation energy for different types of CiCs defects with respect to the Fermi energy for all possible charge states. Prevalence of the neutral state for the C-type defect is established.

  2. Comparison of Two Different Techniques of Cooperative Learning Approach: Undergraduates' Conceptual Understanding in the Context of Hormone Biochemistry

    Science.gov (United States)

    Mutlu, Ayfer

    2018-01-01

    The purpose of the research was to compare the effects of two different techniques of the cooperative learning approach, namely Team-Game Tournament and Jigsaw, on undergraduates' conceptual understanding in a Hormone Biochemistry course. Undergraduates were randomly assigned to Group 1 (N = 23) and Group 2 (N = 29). Instructions were accomplished…

  3. Electronic Structure Approach to Tunable Electronic Properties of Hybrid Organic-Inorganic Perovskites

    Science.gov (United States)

    Liu, Garnett; Huhn, William; Mitzi, David B.; Kanai, Yosuke; Blum, Volker

    We present a study of the electronic structure of layered hybrid organic-inorganic perovskite (HOIP) materials using all-electron density-functional theory. Varying the nature of the organic and inorganic layers should enable systematically fine-tuning the carrier properties of each component. Using the HSE06 hybrid density functional including spin-orbit coupling (SOC), we validate the principle of tuning subsystem-specific parts of the electron band structures and densities of states in CH3NH3PbX3 (X=Cl, Br, I) compared to a modified organic component in layered (C6H5C2H4NH3) 2PbX4 (X=Cl, Br, I) and C20H22S4N2PbX4 (X=Cl, Br, I). We show that tunable shifts of electronic levels indeed arise by varying Cl, Br, I as the inorganic components, and CH3NH3+ , C6H5C2H4NH3+ , C20H22S4N22 + as the organic components. SOC is found to play an important role in splitting the conduction bands of the HOIP compounds investigated here. The frontier orbitals of the halide shift, increasing the gap, when Cl is substituted for Br and I.

  4. TTSA: An Effective Scheduling Approach for Delay Bounded Tasks in Hybrid Clouds.

    Science.gov (United States)

    Yuan, Haitao; Bi, Jing; Tan, Wei; Zhou, MengChu; Li, Bo Hu; Li, Jianqiang

    2017-11-01

    The economy of scale provided by cloud attracts a growing number of organizations and industrial companies to deploy their applications in cloud data centers (CDCs) and to provide services to users around the world. The uncertainty of arriving tasks makes it a big challenge for private CDC to cost-effectively schedule delay bounded tasks without exceeding their delay bounds. Unlike previous studies, this paper takes into account the cost minimization problem for private CDC in hybrid clouds, where the energy price of private CDC and execution price of public clouds both show the temporal diversity. Then, this paper proposes a temporal task scheduling algorithm (TTSA) to effectively dispatch all arriving tasks to private CDC and public clouds. In each iteration of TTSA, the cost minimization problem is modeled as a mixed integer linear program and solved by a hybrid simulated-annealing particle-swarm-optimization. The experimental results demonstrate that compared with the existing methods, the optimal or suboptimal scheduling strategy produced by TTSA can efficiently increase the throughput and reduce the cost of private CDC while meeting the delay bounds of all the tasks.

  5. New approach to improve the energy density of hybrid electret-dielectric elastomer generators

    Science.gov (United States)

    Lagomarsini, Clara; Jean-Mistral, Claire; Monfray, Stephane; Sylvestre, Alain

    2017-04-01

    Harvesting human kinetic energy to produce electricity is an attractive alternative to batteries for applications in wearable electronic devices and smart textile. Dielectric elastomers generators (DEGs) represent one of the most promising technologies for these applications. Nevertheless, one of the main disadvantages of these structures is the need of an external polarization source to perform the energetic cycle. In the present work, a hybrid electret-dielectric elastomer generator in DEG mode is presented. In this configuration, the electret material is used as polarization source of a classical DEG, i.e. an electrostatic generator based on electrical capacitance variation. The electrical energy output in this mode (1.06mJ.g-1) could be higher than the one obtained using a classical electret mode (0.55mJ.g-1), i.e. charges recombination. In this paper, the operation principle of the hybrid generator will be fully described and the design rules for the realization of the prototype will be presented. The experimental data obtained from the prototype will be compared to the results of FEM simulations.

  6. Quantum chemical approaches: semiempirical molecular orbital and hybrid quantum mechanical/molecular mechanical techniques.

    Science.gov (United States)

    Bryce, Richard A; Hillier, Ian H

    2014-01-01

    The use of computational quantum chemical methods to aid drug discovery is surveyed. An overview of the various computational models spanning ab initio, density function theory, semiempirical molecular orbital (MO), and hybrid quantum mechanical (QM)/molecular mechanical (MM) methods is given and their strengths and weaknesses are highlighted, focussing on the challenge of obtaining the accuracy essential for them to make a meaningful contribution to drug discovery. Particular attention is given to hybrid QM/MM and semiempirical MO methods which have the potential to yield the necessary accurate predictions of macromolecular structure and reactivity. These methods are shown to have advanced the study of many aspects of substrate-ligand interactions relevant to drug discovery. Thus, the successful parametrization of semiempirical MO methods and QM/MM methods can be used to model noncovalent substrate-protein interactions, and to lead to improved scoring functions. QM/MM methods can be used in crystal structure refinement and are particularly valuable for modelling covalent protein-ligand interactions and can thus aid the design of transition state analogues. An extensive collection of examples from the areas of metalloenzyme structure, enzyme inhibition, and ligand binding affinities and scoring functions are used to illustrate the power of these techniques.

  7. Hybrid ANN–PLS approach to scroll compressor thermodynamic performance prediction

    International Nuclear Information System (INIS)

    Tian, Z.; Gu, B.; Yang, L.; Lu, Y.

    2015-01-01

    In this paper, a scroll compressor thermodynamic performance prediction was carried out by applying a hybrid ANN–PLS model. Firstly, an experimental platform with second-refrigeration calorimeter was set up and steady-state scroll compressor data sets were collected from experiments. Then totally 148 data sets were introduced to train and verify the validity of the ANN–PLS model for predicting the scroll compressor parameters such as volumetric efficiency, refrigerant mass flow rate, discharge temperature and power consumption. The ANN–PLS model was determined with 5 hidden neurons and 7 latent variables through the training process. Ultimately, the ANN–PLS model showed better performance than the ANN model and the PLS model working separately. ANN–PLS predictions agree well with the experimental values with mean relative errors (MREs) in the range of 0.34–1.96%, correlation coefficients (R 2 ) in the range of 0.9703–0.9999 and very low root mean square errors (RMSEs). - Highlights: • Hybrid ANN–PLS is utilized to predict the thermodynamic performance of scroll compressor. • ANN–PLS model is determined with 5 hidden neurons and 7 latent variables. • ANN–PLS model demonstrates better performance than ANN and PLS working separately. • The values of MRE and RMSE are in the range of 0.34–1.96% and 0.9703–0.9999, respectively

  8. THE HYBRID APPROACH OF INFLATION TARGETING: WHAT OPPORTUNITIES FOR AN EMERGING ECONOMY LIKE TUNISIA?

    Directory of Open Access Journals (Sweden)

    Hella Guerchi Mehri

    2016-07-01

    Full Text Available After economic crises happening in many emerging countries, flexible exchange rates became a required theoretical condition helping to target inflation. Many countries stopped using exchange rate as an anchor for monetary policy and started using inflation targeting framework. In emerging countries, monetary authorities work to stabilize the exchange rate because of their “fear of floating”. They are against high volatility of interest rate allowing speculative attacks and causing free fluctuations of their national currency. To avoid uncontrolled market movements, they have to choose between active and public exchange rate management and tight inflation targeting. In the same vein, Central bank of Tunisia follows financial measures linked closely to inflation without focusing especially on monetary aggregates in order to study a possible transition to targeting inflation strategy. It uses a simple Taylor rule where interest rates adjustment are guided by the anticipated inflation deviation from its original target and also by the gap between observed and potential GDP.As an emerging economy with a high degree of financial vulnerability, and facing different shocks, Tunisia should adopt a hybrid rule of inflation targeting in an open economy. This hybrid rule explicitly takes into account the evolution of the exchange rate in the reaction function of the central bank.

  9. An efficient chaos embedded hybrid approach for hydro-thermal unit commitment problem

    International Nuclear Information System (INIS)

    Yuan, Xiaohui; Ji, Bin; Yuan, Yanbin; Ikram, Rana M.; Zhang, Xiaopan; Huang, Yuehua

    2015-01-01

    Highlights: • Thermal unit commitment is considered in hydrothermal generation scheduling (SHTGS). • Two newly proposed promising optimization algorithms are combined to solving SHTGS. • The proposed method is enhanced by integrating a chaotic local search strategy. • Heuristic search strategies are applied to handle the constraints of the SHTGS. • The results verify the proposed method is feasible and efficient for handling SHTGS. - Abstract: This paper establishes a model to deal with the short-term hydrothermal generation scheduling (SHTGS) problem. The problem is composed of three interconnected parts: short-term hydrothermal coordination, thermal unit commitment and economic load dispatch. An efficient hybrid method composed of chaotic backtracking search optimization algorithm and binary charged system search algorithm (CBSA–BCSS) is proposed to solve this problem. In order to analyze the effect of the chaotic map on the performance of the method, three different chaotic maps are adopted to integrate into the proposed method and the corresponding consequences are achieved. Furthermore, efficient heuristic search strategies are adopted to handle with the complicated constraints of the SHTGS system. Finally, a hydrothermal unit commitment system is utilized to verify the feasibility and effectiveness of the proposed method. The results demonstrate the efficiency of the hybrid optimization method and the appropriation of the constraint handling strategies. The comparison of the solutions achieved by different methods shows that the proposed method has higher efficiency in terms of solving SHTGS problem

  10. Hybrid Forecasting Approach Based on GRNN Neural Network and SVR Machine for Electricity Demand Forecasting

    Directory of Open Access Journals (Sweden)

    Weide Li

    2017-01-01

    Full Text Available Accurate electric power demand forecasting plays a key role in electricity markets and power systems. The electric power demand is usually a non-linear problem due to various unknown reasons, which make it difficult to get accurate prediction by traditional methods. The purpose of this paper is to propose a novel hybrid forecasting method for managing and scheduling the electricity power. EEMD-SCGRNN-PSVR, the proposed new method, combines ensemble empirical mode decomposition (EEMD, seasonal adjustment (S, cross validation (C, general regression neural network (GRNN and support vector regression machine optimized by the particle swarm optimization algorithm (PSVR. The main idea of EEMD-SCGRNN-PSVR is respectively to forecast waveform and trend component that hidden in demand series to substitute directly forecasting original electric demand. EEMD-SCGRNN-PSVR is used to predict the one week ahead half-hour’s electricity demand in two data sets (New South Wales (NSW and Victorian State (VIC in Australia. Experimental results show that the new hybrid model outperforms the other three models in terms of forecasting accuracy and model robustness.

  11. A Comparison of Hybrid Approaches for Turbofan Engine Gas Path Fault Diagnosis

    Science.gov (United States)

    Lu, Feng; Wang, Yafan; Huang, Jinquan; Wang, Qihang

    2016-09-01

    A hybrid diagnostic method utilizing Extended Kalman Filter (EKF) and Adaptive Genetic Algorithm (AGA) is presented for performance degradation estimation and sensor anomaly detection of turbofan engine. The EKF is used to estimate engine component performance degradation for gas path fault diagnosis. The AGA is introduced in the integrated architecture and applied for sensor bias detection. The contributions of this work are the comparisons of Kalman Filters (KF)-AGA algorithms and Neural Networks (NN)-AGA algorithms with a unified framework for gas path fault diagnosis. The NN needs to be trained off-line with a large number of prior fault mode data. When new fault mode occurs, estimation accuracy by the NN evidently decreases. However, the application of the Linearized Kalman Filter (LKF) and EKF will not be restricted in such case. The crossover factor and the mutation factor are adapted to the fitness function at each generation in the AGA, and it consumes less time to search for the optimal sensor bias value compared to the Genetic Algorithm (GA). In a word, we conclude that the hybrid EKF-AGA algorithm is the best choice for gas path fault diagnosis of turbofan engine among the algorithms discussed.

  12. Hybrid approach for transcatheter paravalvular leak closure of mitral prosthesis in high-risk patients through transapical access.

    Science.gov (United States)

    Davidavicius, Giedrius; Rucinskas, Kestutis; Drasutiene, Agne; Samalavicius, Robertas; Bilkis, Valdas; Zakarkaite, Diana; Aidietis, Audrius

    2014-11-01

    To report "hybrid" procedure feasibility and the clinical success of transcatheter paravalvular leak closure through apical access. Seven patients (73.6±6.1 years; 4 men) with severe mitral prosthesis paravalvular leak were selected. All patients were at high risk for open surgery because of severe comorbidities and heart failure (New York Heart Association class III-IV). The defect size was 25±7.8 mm in the long axis and 9.3±2 mm in the short axis. Two defects were detected in 2 patients. The transapical procedure was performed in a "hybrid" surgery room using minithoracotomy and general anesthesia. Three-dimensional transesophageal echocardiography and fluoroscopy were used for imaging. A total of 19 Amplatzer Vascular Plug III devices (St Jude Medical) were implanted in 7 patients, 2.7/patient and 1 to 3/fistula. The procedure time was 150.7±66.8 minutes. In 6 of 7 patients (85.7%), the paravalvular leak was successfully closed, resulting in no or mild residual regurgitation. One patient had moderate regurgitation despite deployment of 3 Amplatzer Vascular Plug III devices. Two patients required blood transfusion related to procedural blood loss. The patients were discharged at 15.3±6.5 days and followed up at 215.7±138.6 days. All but 1 patient reported symptomatic improvement by ≥1 New York Heart Association class at follow-up. One patient died 216 days postoperatively. A "hybrid approach" for transcatheter paravalvular leak closure of mitral prosthesis from the apical route is effective in reducing the regurgitation grade and improving functional capacity in high-risk patients. Complete closure of the defect was maintained at follow-up in most patients. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  13. Eksperimentasi Model Jigsaw Snowball Drilling dan Peer Tutoring Snowball Drilling pada Materi Pokok Tabung, Kerucut, dan Bola Ditinjau dari Gaya Belajar Siswa

    OpenAIRE

    P, Nelly Indriastuti; Kusmayadi, Tri Atmojo; Usodo, Budi

    2014-01-01

    The aims of this research were to determine: (1) which results better mathematics learning achievement between students who were taught by using jigsaw snowball drilling, peer tutoring snowball drilling, or direct instruction, (2) which has better mathematics learning achievement between students with visual learning styles, auditory, or kinesthetic, (3). at each of the learning model, which one has better mathematics learning achievement between student with visual learning style, auditory, ...

  14. A new hybrid algorithm using thermodynamic and backward ray-tracing approaches for modeling luminescent solar concentrators

    Energy Technology Data Exchange (ETDEWEB)

    Lo, Ch. K.; Lim, Y. S.; Tan, S. G.; Rahman, F. A. [Faculty of Engineering and Science, University Tunku Abdul Rahman, Jalan Genting Klang, 53300, Kuala Lumpur (Malaysia)

    2010-12-15

    A Luminescent Solar Concentrator (LSC) is a transparent plate containing luminescent material with photovoltaic (PV) cells attached to its edges. Sunlight entering the plate is absorbed by the luminescent material, which in turn emits light. The emitted light propagates through the plate and arrives at the PV cells through total internal reflection. The ratio of the area of the relatively cheap polymer plate to that of the expensive PV cells is increased, and the cost per unit of solar electricity can be reduced by 75%. To improve the emission performance of LSCs, simulation modeling of LSCs becomes essential. Ray-tracing modeling is a popular approach for simulating LSCs due to its great ability of modeling various LSC structures under direct and diffuse sunlight. However, this approach requires substantial amount of measurement input data. Also, the simulation time is enormous because it is a forward-ray tracing method that traces all the rays propagating from the light source to the concentrator. On the other hand, the thermodynamic approach requires substantially less input parameters and simulation time, but it can only be used to model simple LSC designs with direct sunlight. Therefore, a new hybrid model was developed to perform various simulation studies effectively without facing the issues arisen from the existing ray-tracing and thermodynamic models. The simulation results show that at least 60% of the total output irradiance of a LSC is contributed by the light trapped and channeled by the LSC. The novelty of this hybrid model is the concept of integrating the thermodynamic model with a well-developed Radiance ray-tracing model, hence making this model as a fast, powerful and cost-effective tool for the design of LSCs. (authors)

  15. Effects of Jigsaw Cooperative Learning and Animation Techniques on Students' Understanding of Chemical Bonding and Their Conceptions of the Particulate Nature of Matter

    Science.gov (United States)

    Karacop, Ataman; Doymus, Kemal

    2013-04-01

    The aim of this study was to determine the effect of jigsaw cooperative learning and computer animation techniques on academic achievements of first year university students attending classes in which the unit of chemical bonding is taught within the general chemistry course and these students' learning of the particulate nature of matter of this unit. The sample of this study consisted of 115 first-year science education students who attended the classes in which the unit of chemical bonding was taught in a university faculty of education during the 2009-2010 academic year. The data collection instruments used were the Test of Scientific Reasoning, the Purdue Spatial Visualization Test: Rotations, the Chemical Bonding Academic Achievement Test, and the Particulate Nature of Matter Test in Chemical Bonding (CbPNMT). The study was carried out in three different groups. One of the groups was randomly assigned to the jigsaw group, the second was assigned to the animation group (AG), and the third was assigned to the control group, in which the traditional teaching method was applied. The data obtained with the instruments were evaluated using descriptive statistics, one-way ANOVA, and MANCOVA. The results indicate that the teaching of chemical bonding via the animation and jigsaw techniques was more effective than the traditional teaching method in increasing academic achievement. In addition, according to findings from the CbPNMT, the students from the AG were more successful in terms of correct understanding of the particulate nature of matter.

  16. Transcatheter pulmonary valve replacement by hybrid approach using a novel polymeric prosthetic heart valve: proof of concept in sheep.

    Directory of Open Access Journals (Sweden)

    Ben Zhang

    Full Text Available Since 2000, transcatheter pulmonary valve replacement has steadily advanced. However, the available prosthetic valves are restricted to bioprosthesis which have defects like poor durability. Polymeric heart valve is thought as a promising alternative to bioprosthesis. In this study, we introduced a novel polymeric transcatheter pulmonary valve and evaluated its feasibility and safety in sheep by a hybrid approach.We designed a novel polymeric trileaflet transcatheter pulmonary valve with a balloon-expandable stent, and the valve leaflets were made of 0.1-mm expanded polytetrafluoroethylene (ePTFE coated with phosphorylcholine. We chose glutaraldehyde-treated bovine pericardium valves as control. Pulmonary valve stents were implanted in situ by a hybrid transapical approach in 10 healthy sheep (8 for polymeric valve and 2 for bovine pericardium valve, weighing an average of 22.5±2.0 kg. Angiography and cardiac catheter examination were performed after implantation to assess immediate valvular functionality. After 4-week follow-up, angiography, echocardiography, computed tomography, and cardiac catheter examination were used to assess early valvular function. One randomly selected sheep with polymeric valve was euthanized and the explanted valved stent was analyzed macroscopically and microscopically.Implantation was successful in 9 sheep. Angiography at implantation showed all 9 prosthetic valves demonstrated orthotopic position and normal functionality. All 9 sheep survived at 4-week follow-up. Four-week follow-up revealed no evidence of valve stent dislocation or deformation and normal valvular and cardiac functionality. The cardiac catheter examination showed the peak-peak transvalvular pressure gradient of the polymeric valves was 11.9±5.0 mmHg, while that of two bovine pericardium valves were 11 and 17 mmHg. Gross morphology demonstrated good opening and closure characteristics. No thrombus or calcification was seen macroscopically

  17. A Hybrid ICA-SVM Approach for Determining the Quality Variables at Fault in a Multivariate Process

    Directory of Open Access Journals (Sweden)

    Yuehjen E. Shao

    2012-01-01

    Full Text Available The monitoring of a multivariate process with the use of multivariate statistical process control (MSPC charts has received considerable attention. However, in practice, the use of MSPC chart typically encounters a difficulty. This difficult involves which quality variable or which set of the quality variables is responsible for the generation of the signal. This study proposes a hybrid scheme which is composed of independent component analysis (ICA and support vector machine (SVM to determine the fault quality variables when a step-change disturbance existed in a multivariate process. The proposed hybrid ICA-SVM scheme initially applies ICA to the Hotelling T2 MSPC chart to generate independent components (ICs. The hidden information of the fault quality variables can be identified in these ICs. The ICs are then served as the input variables of the classifier SVM for performing the classification process. The performance of various process designs is investigated and compared with the typical classification method. Using the proposed approach, the fault quality variables for a multivariate process can be accurately and reliably determined.

  18. Dynamical coupling of plasmons and molecular excitations by hybrid quantum/classical calculations: time-domain approach

    International Nuclear Information System (INIS)

    Sakko, Arto; Rossi, Tuomas P; Nieminen, Risto M

    2014-01-01

    The presence of plasmonic material influences the optical properties of nearby molecules in untrivial ways due to the dynamical plasmon-molecule coupling. We combine quantum and classical calculation schemes to study this phenomenon in a hybrid system that consists of a Na 2 molecule located in the gap between two Au/Ag nanoparticles. The molecule is treated quantum-mechanically with time-dependent density-functional theory, and the nanoparticles with quasistatic classical electrodynamics. The nanoparticle dimer has a plasmon resonance in the visible part of the electromagnetic spectrum, and the Na 2 molecule has an electron-hole excitation in the same energy range. Due to the dynamical interaction of the two subsystems the plasmon and the molecular excitations couple, creating a hybridized molecular-plasmon excited state. This state has unique properties that yield e.g. enhanced photoabsorption compared to the freestanding Na 2 molecule. The computational approach used enables decoupling of the mutual plasmon-molecule interaction, and our analysis verifies that it is not legitimate to neglect the backcoupling effect when describing the dynamical interaction between plasmonic material and nearby molecules. Time-resolved analysis shows nearly instantaneous formation of the coupled state, and provides an intuitive picture of the underlying physics. (paper)

  19. A hybrid approach to the surface biofunctionalization of nanostructured porous alumina

    Energy Technology Data Exchange (ETDEWEB)

    Silvan, Miguel Manso; Ruiz, Josefa Predestinacion Garcia [Departamento de Fisica Aplicada y Departamento de Biologia Molecular, Facultad de Ciencias, Universidad Autonoma de Madrid, Unidad Asociada GMNF (ICMM-CSIC), 28049 Madrid (Spain); Centro de Investigaciones Biomedicas en Red, Bioingenieria Biomateriales y Nanomedicina (CIBERbbn) (Spain); Gonzalez, Ruy Sanz [Instituto de Ciencia de Materiales de Madrid, Consejo Superior de Investigaciones Cientificas, 28049 Madrid (Spain); Velez, Manuel Hernandez [Departamento de Fisica Aplicada y Departamento de Biologia Molecular, Facultad de Ciencias, Universidad Autonoma de Madrid, Unidad Asociada GMNF (ICMM-CSIC), 28049 Madrid (Spain)

    2010-02-15

    The application of nanostructured porous alumina templates as a solid support in biomedical assays requires a surface biofunctionalization process that has been addressed in this work by an hybrid aminopropyl-triethoxysilane/tetraisopropyl-orthotitanate (APTS/ TIPT) self assembled film. The nanostructured porous alumina templates are activated in a peroxide solution before immersion in the biofunctionalizing APTS/TIPT solution. The biofunctionalization process was followed up by UV-vis spectroscopy, which confirmed the modification of the dielectric structure of the alumina surface. The influence of the biofunctionalization step in an immunological assay was carried out by fluorescence microscopy. Results confirm the gain in activity after the immobilization of an FITC labelled mouse Igg. Specific biological recognition in a bovine serum albumin (BSA)-antiBSA assay is proved afterwards by shifts observed in the reflectance interferograms thus providing a fast biosensing transducer platform. (copyright 2010 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  20. A hybrid approach to select features and classify diseases based on medical data

    Science.gov (United States)

    AbdelLatif, Hisham; Luo, Jiawei

    2018-03-01

    Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms

  1. An improved hybrid topology optimization approach coupling simulated annealing and SIMP (SA-SIMP)

    International Nuclear Information System (INIS)

    Garcia-Lopez, N P; Sanchez-Silva, M; Medaglia, A L; Chateauneuf, A

    2010-01-01

    The Solid Isotropic Material with Penalization (SIMP) methodology has been used extensively due to its versatility and ease of implementation. However, one of its main drawbacks is that resulting topologies exhibit areas of intermediate densities which lack any physical meaning. This paper presents a hybrid methodology which couples simulated annealing and SIMP (SA-SIMP) in order to achieve solutions which are stiffer and predominantly black and white. Under a look-ahead strategy, the algorithm gradually fixes or removes those elements whose density resulting from SIMP is intermediate. Different strategies for selecting and fixing the fractional elements are examined using benchmark examples, which show that topologies resulting from SA-SIMP are more rigid than SIMP and predominantly black and white.

  2. Hybrid endovascular and surgical approach for mycotic pseudoaneurysms of the extracranial internal carotid artery

    Directory of Open Access Journals (Sweden)

    Daniela Mazzaccaro

    2014-11-01

    Full Text Available Objectives: Mycotic pseudoaneurysms of the extracranial internal carotid artery are rare, and their management often represents a challenge, but treatment is necessary due to the high risk of rupture and distal brain embolization. Systemic antibiotics associated with open surgical excision of the infected tissues and carotid reconstruction using autologous grafts are the treatment of choice. The use of endovascular techniques still remains controversial in infective fields; however, it can be an attractive alternative in high-risk patients or more often as a “temporary” solution to achieve immediate bleeding control for a safe surgical reconstruction. Methods: We discuss the unusual case of an extracranial right internal carotid artery mycotic pseudoaneurysm following methicillin-resistant Staphylococcus aureus infection, in a patient with poor general conditions. Results and Conclusion: The lesion was successfully treated using a hybrid endovascular and surgical procedure.

  3. Gas cooled solar tower power plant (GAST) KWU approach to a 20 MW hybrid system

    Energy Technology Data Exchange (ETDEWEB)

    Mayer, Martin

    1980-07-01

    The gas cooled solar tower powerplant with a hybrid solar-fossil heating system in the form given here represents a significant step towards the industrial use of solar energy. The transition from fossil fuels to solar energy can be facilitated for the power plant operators if the transition is gradual and if conventional technology is used. Using solar energy and with a turbine inlet temperature of 800/sup 0/C the GAST power plant reaches an output of approximately 20 MW and a thermal efficiency of approximately 40% reference to the heat supplied by the receiver. In the absence of solar radiation the plant can be operated exclusively on fossil fuel. Increasing the turbine inlet temperature to 1000/sup 0/C enables an efficiency of about 47% to be reached in the GUD cycle.

  4. Silver metaphosphate glass wires inside silica fibers--a new approach for hybrid optical fibers.

    Science.gov (United States)

    Jain, Chhavi; Rodrigues, Bruno P; Wieduwilt, Torsten; Kobelke, Jens; Wondraczek, Lothar; Schmidt, Markus A

    2016-02-22

    Phosphate glasses represent promising candidates for next-generation photonic devices due to their unique characteristics, such as vastly tunable optical properties, and high rare earth solubility. Here we show that silver metaphosphate wires with bulk optical properties and diameters as small as 2 µm can be integrated into silica fibers using pressure-assisted melt filling. By analyzing two types of hybrid metaphosphate-silica fibers, we show that the filled metaphosphate glass has only negligible higher attenuation and a refractive index that is identical to the bulk material. The presented results pave the way towards new fiber-type optical devices relying on metaphosphate glasses, which are promising materials for applications in nonlinear optics, sensing and spectral filtering.

  5. Economic challenges of hybrid microgrid: An analysis and approaches for rural electrification

    Science.gov (United States)

    Habibullah, Mohammad; Mahmud, Khizir; Koçar, Günnur; Islam, A. K. M. Sadrul; Salehin, Sayedus

    2017-06-01

    This paper focuses on the integration of three renewable resources: biogas, wind energy and solar energy, utilizing solar PV panels, a biogas generator, and a wind turbine, respectively, to analyze the technical and economic challenges of a hybrid micro-gird. The integration of these sources has been analyzed and optimized based on realistic data for a real location. Different combinations of these sources have been analyzed to find out the optimized combination based on the efficiency and the minimum cost of electricity (COE). Wind and solar energy are considered as the primary sources of power generation during off-peak hours, and any excess power is used to charge a battery bank. During peak hours, biogas generators produce power to support the additional demand. A business strategy to implement the integrated optimized system in rural areas is discussed.

  6. SCOTCH: Secure Counting Of encrypTed genomiC data using a Hybrid approach.

    Science.gov (United States)

    Chenghong, Wang; Jiang, Yichen; Mohammed, Noman; Chen, Feng; Jiang, Xiaoqian; Al Aziz, Md Momin; Sadat, Md Nazmus; Wang, Shuang

    2017-01-01

    As genomic data are usually at large scale and highly sensitive, it is essential to enable both efficient and secure analysis, by which the data owner can securely delegate both computation and storage on untrusted public cloud. Counting query of genotypes is a basic function for many downstream applications in biomedical research (e.g., computing allele frequency, calculating chi-squared statistics, etc.). Previous solutions show promise on secure counting of outsourced data but the efficiency is still a big limitation for real world applications. In this paper, we propose a novel hybrid solution to combine a rigorous theoretical model (homomorphic encryption) and the latest hardware-based infrastructure (i.e., Software Guard Extensions) to speed up the computation while preserving the privacy of both data owners and data users. Our results demonstrated efficiency by using the real data from the personal genome project.

  7. Transit Network Design: a Hybrid Enhanced Artificial Bee Colony Approach and a Case Study

    Directory of Open Access Journals (Sweden)

    Y. Jiang

    2013-09-01

    Full Text Available A bus network design problem in a suburban area of Hong Kong is studied. The objective is to minimize the weighted sum of the number of transfers and the total travel time of passengers by restructuring bus routes and determining new frequencies. A mixed integer optimization model is developed and was solved by a Hybrid Enhanced Artificial Bee Colony algorithm (HEABC. A case study was conducted to investigate the effects of different design parameters, including the total number of bus routes available, the maximum route duration within the study area and the maximum allowable number of bus routes that originated from each terminal. The model and results are useful for improving bus service policies.

  8. Carbon footprint evaluation at industrial park level: A hybrid life cycle assessment approach

    International Nuclear Information System (INIS)

    Dong, Huijuan; Geng, Yong; Xi, Fengming; Fujita, Tsuyoshi

    2013-01-01

    Industrial parks have become the effective strategies for government to promote sustainable economic development due to the following advantages: shared infrastructure and concentrated industrial activities within planned areas. However, due to intensive energy consumption and dependence on fossil fuels, industrial parks have become the main areas for greenhouse gas emissions. Therefore, it is critical to quantify their carbon footprints so that appropriate emission reduction policies can be raised. The objective of this paper is to seek an appropriate method on evaluating the carbon footprint of one industrial park. The tiered hybrid LCA method was selected due to its advantages over other methods. Shenyang Economic and Technological Development Zone (SETDZ), a typical comprehensive industrial park in China, was chosen as a case study park. The results show that the total life cycle carbon footprint of SETDZ was 15.29 Mt, including 6.81 Mt onsite (direct) carbon footprint, 8.47 Mt upstream carbon footprint, and only 3201 t downstream carbon footprint. Analysis from industrial sector perspectives shows that chemical industry and manufacture of general purpose machinery and special purposes machinery sector were the two largest sectors for life cycle carbon footprint. Such a sector analysis may be useful for investigation of appropriate emission reduction policies. - Highlights: ► A hybrid LCA model was employed to calculate industrial park carbon footprint. ► A case study on SETDZ is done. ► Life cycle carbon footprint of SETDZ is 15.29 Mt. ► Upstream and onsite carbon footprints account for 55.40% and 44.57%, respectively. ► Chemical industry and machinery manufacturing sectors are the two largest sectors

  9. Engineering of a novel adjuvant based on lipid-polymer hybrid nanoparticles: A quality-by-design approach.

    Science.gov (United States)

    Rose, Fabrice; Wern, Jeanette Erbo; Ingvarsson, Pall Thor; van de Weert, Marco; Andersen, Peter; Follmann, Frank; Foged, Camilla

    2015-07-28

    The purpose of this study was to design a novel and versatile adjuvant intended for mucosal vaccination based on biodegradable poly(DL-lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) modified with the cationic surfactant dimethyldioctadecylammonium (DDA) bromide and the immunopotentiator trehalose-6,6'-dibehenate (TDB) (CAF01) to tailor humoral and cellular immunity characterized by antibodies and Th1/Th17 responses. Such responses are important for the protection against diseases caused by intracellular bacteria such as Chlamydia trachomatis and Mycobacterium tuberculosis. The hybrid NPs were engineered using an oil-in-water single emulsion method and a quality-by-design approach was adopted to define the optimal operating space (OOS). Four critical process parameters (CPPs) were identified, including the acetone concentration in the water phase, the stabilizer [polyvinylalcohol (PVA)] concentration, the lipid-to-total solid ratio, and the total concentration. The CPPs were linked to critical quality attributes consisting of the particle size, polydispersity index (PDI), zeta-potential, thermotropic phase behavior, yield and stability. A central composite face-centered design was performed followed by multiple linear regression analysis. The size, PDI, enthalpy of the phase transition and yield were successfully modeled, whereas the models for the zeta-potential and the stability were poor. Cryo-transmission electron microscopy revealed that the main structural effect on the nanoparticle architecture is caused by the use of PVA, and two different morphologies were identified: i) A PLGA core coated with one or several concentric lipid bilayers, and ii) a PLGA nanoshell encapsulating lipid membrane structures. The optimal formulation, identified from the OOS, was evaluated in vivo. The hybrid NPs induced antibody and Th1/Th17 immune responses that were similar in quality and magnitude to the response induced by DDA/TDB liposomes, showing that the adjuvant

  10. On the Use of Hybrid Development Approaches in Software and Systems Development

    DEFF Research Database (Denmark)

    Kuhrmann, Marco; Münch, Jürgen; Diebold, Philipp

    2016-01-01

    A software process is the game plan to organize project teams and run projects. Yet, it still is a challenge to select the appropriate development approach for the respective context. A multitude of development approaches compete for the users’ favor, but there is no silver bullet serving all...... possible setups. Moreover, recent research as well as experience from practice shows companies utilizing different development approaches to assemble the best-fitting approach for the respective company: a more traditional process provides the basic framework to serve the organization, while project teams...

  11. Hybrid wind–photovoltaic–diesel–battery system sizing tool development using empirical approach, life-cycle cost and performance analysis: A case study in Scotland

    International Nuclear Information System (INIS)

    Gan, Leong Kit; Shek, Jonathan K.H.; Mueller, Markus A.

    2015-01-01

    Highlights: • Methods of sizing a hybrid wind–photovoltaic–diesel–battery system is described. • The hybrid system components are modelled using empirical data. • Twenty years lifecycle cost of the hybrid system is considered. • The trade-offs between battery storage capacity and diesel fuel usage is studied. • A hybrid system sizing tool has been developed as a graphical user interface (GUI). - Abstract: The concept of off-grid hybrid wind energy system is financially attractive and more reliable than stand-alone power systems since it is based on more than one electricity generation source. One of the most expensive components in a stand-alone wind-power system is the energy storage system as very often it is oversized to increase system autonomy. In this work, we consider a hybrid system which consists of wind turbines, photovoltaic panels, diesel generator and battery storage. One of the main challenges experienced by project managers is the sizing of components for different sites. This challenge is due to the variability of the renewable energy resource and the load demand for different sites. This paper introduces a sizing model that has been developed and implemented as a graphical user interface, which predicts the optimum configuration of a hybrid system. In particular, this paper focuses on seeking the optimal size of the batteries and the diesel generator usage. Both of these components are seen to be trade-offs from each other. The model simulates real time operation of the hybrid system, using the annual measured hourly wind speed and solar irradiation. The benefit of using time series approach is that it reflects a more realistic situation; here, the peaks and troughs of the renewable energy resource are a central part of the sizing model. Finally, load sensitivity and hybrid system performance analysis are demonstrated.

  12. Contrast improvement of continuous wave diffuse optical tomography reconstruction by hybrid approach using least square and genetic algorithm

    Science.gov (United States)

    Patra, Rusha; Dutta, Pranab K.

    2015-07-01

    Reconstruction of the absorption coefficient of tissue with good contrast is of key importance in functional diffuse optical imaging. A hybrid approach using model-based iterative image reconstruction and a genetic algorithm is proposed to enhance the contrast of the reconstructed image. The proposed method yields an observed contrast of 98.4%, mean square error of 0.638×10-3, and object centroid error of (0.001 to 0.22) mm. Experimental validation of the proposed method has also been provided with tissue-like phantoms which shows a significant improvement in image quality and thus establishes the potential of the method for functional diffuse optical tomography reconstruction with continuous wave setup. A case study of finger joint imaging is illustrated as well to show the prospect of the proposed method in clinical diagnosis. The method can also be applied to the concentration measurement of a region of interest in a turbid medium.

  13. Ag nanoparticle–ZnO nanowire hybrid nanostructures as enhanced and robust antimicrobial textiles via a green chemical approach

    International Nuclear Information System (INIS)

    Li, Zhou; Yuan, Weiwei; Song, Wei; Niu, Yongshan; Yan, Ling; Yu, Min; Dai, Ming; Feng, Siyu; Wang, Menghang; Fan, Yubo; Tang, Haoying; Liu, Tengjiao; Jiang, Peng; Wang, Zhong Lin

    2014-01-01

    A new approach for fabrication of a long-term and recoverable antimicrobial nanostructure/textile hybrid without increasing the antimicrobial resistance is demonstrated. Using in situ synthesized Ag nanoparticles (NPs) anchored on ZnO nanowires (NWs) grown on textiles by a ‘dip-in and light-irradiation’ green chemical method, we obtained ZnONW@AgNP nanocomposites with small-size and uniform Ag NPs, which have shown superior performance for antibacterial applications. These new Ag/ZnO/textile antimicrobial composites can be used for wound dressings and medical textiles for topical and prophylactic antibacterial treatments, point-of-use water treatment to improve the cleanliness of water and antimicrobial air filters to prevent bioaerosols accumulating in ventilation, heating, and air-conditioning systems. (paper)

  14. Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification

    Directory of Open Access Journals (Sweden)

    Pengfei Li

    2014-01-01

    Full Text Available To deal with the difficulty to obtain a large number of fault samples under the practical condition for mechanical fault diagnosis, a hybrid method that combined wavelet packet decomposition and support vector classification (SVC is proposed. The wavelet packet is employed to decompose the vibration signal to obtain the energy ratio in each frequency band. Taking energy ratios as feature vectors, the pattern recognition results are obtained by the SVC. The rolling bearing and gear fault diagnostic results of the typical experimental platform show that the present approach is robust to noise and has higher classification accuracy and, thus, provides a better way to diagnose mechanical faults under the condition of small fault samples.

  15. The numerical simulation of heat transfer during a hybrid laser-MIG welding using equivalent heat source approach

    Science.gov (United States)

    Bendaoud, Issam; Matteï, Simone; Cicala, Eugen; Tomashchuk, Iryna; Andrzejewski, Henri; Sallamand, Pierre; Mathieu, Alexandre; Bouchaud, Fréderic

    2014-03-01

    The present study is dedicated to the numerical simulation of an industrial case of hybrid laser-MIG welding of high thickness duplex steel UR2507Cu with Y-shaped chamfer geometry. It consists in simulation of heat transfer phenomena using heat equivalent source approach and implementing in finite element software COMSOL Multiphysics. A numerical exploratory designs method is used to identify the heat sources parameters in order to obtain a minimal required difference between the numerical results and the experiment which are the shape of the welded zone and the temperature evolution in different locations. The obtained results were found in good correspondence with experiment, both for melted zone shape and thermal history.

  16. Draft Sequencing of the Heterozygous Diploid Genome of Satsuma (Citrus unshiu Marc. Using a Hybrid Assembly Approach

    Directory of Open Access Journals (Sweden)

    Tokurou Shimizu

    2017-12-01

    Full Text Available Satsuma (Citrus unshiu Marc. is one of the most abundantly produced mandarin varieties of citrus, known for its seedless fruit production and as a breeding parent of citrus. De novo assembly of the heterozygous diploid genome of Satsuma (“Miyagawa Wase” was conducted by a hybrid assembly approach using short-read sequences, three mate-pair libraries, and a long-read sequence of PacBio by the PLATANUS assembler. The assembled sequence, with a total size of 359.7 Mb at the N50 length of 386,404 bp, consisted of 20,876 scaffolds. Pseudomolecules of Satsuma constructed by aligning the scaffolds to three genetic maps showed genome-wide synteny to the genomes of Clementine, pummelo, and sweet orange. Gene prediction by modeling with MAKER-P proposed 29,024 genes and 37,970 mRNA; additionally, gene prediction analysis found candidates for novel genes in several biosynthesis pathways for gibberellin and violaxanthin catabolism. BUSCO scores for the assembled scaffold and predicted transcripts, and another analysis by BAC end sequence mapping indicated the assembled genome consistency was close to those of the haploid Clementine, pummel, and sweet orange genomes. The number of repeat elements and long terminal repeat retrotransposon were comparable to those of the seven citrus genomes; this suggested no significant failure in the assembly at the repeat region. A resequencing application using the assembled sequence confirmed that both kunenbo-A and Satsuma are offsprings of Kishu, and Satsuma is a back-crossed offspring of Kishu. These results illustrated the performance of the hybrid assembly approach and its ability to construct an accurate heterozygous diploid genome.

  17. Bilateral cochlear implants in infants: a new approach--Nucleus Hybrid S12 project.

    Science.gov (United States)

    Gantz, Bruce J; Dunn, Camille C; Walker, Elizabeth A; Kenworthy, Maura; Van Voorst, Tanya; Tomblin, Bruce; Turner, Chris

    2010-10-01

    The purpose of this feasibility study was to evaluate whether the use of a shorter-length cochlear implant (10 mm) on one ear and a standard electrode (24 mm) on the contralateral ear is a viable bilateral option for children with profound bilateral sensorineural hearing loss. A secondary purpose of this study was to determine whether the ear with the shorter-length electrode performs similarly to the standard-length electrode. Our goal was to provide an option of electrical stimulation that theoretically might preserve the structures of the scala media and organ of Corti. The study is being conducted as a repeated-measure, single-subject experiment. University of Iowa-Department of Otolaryngology. Eight pediatric patients with profound bilateral sensorineural hearing loss between the ages of 12 and 24 months. Nucleus Hybrid S12 10-mm electrode and a Nucleus Freedom implant in the contralateral ear. The Infant-Toddler Meaningful Auditory Integration Scale (IT-MAIS) parent questionnaire, Early Speech Perception, Glendonald Auditory Screening Procedure word test, and Children's Vowel tests will be used to evaluate speech perception and the Minnesota Child Development Inventory and Preschool Language Scales 3 test will be used to evaluate language growth. Preliminary results for 8 children have been collected before and after the operation using the IT-MAIS. All 3 children showed incremental improvements in their IT-MAIS scores overtime. Early Speech Perception, Glendonald Auditory Screening Procedure word test, and Children's Vowel word perception results indicated no difference between the individual ears for the 2 children tested. Performance compared with age-matched children implanted with standard bilateral cochlear implants showed similar results to the children implanted with Nucleus Hybrid S12 10-mm electrode and a Nucleus Freedom implant in contralateral ears. The use of a shorter-length cochlear implant on one ear and a standard-length electrode on the

  18. A Hybrid Color Mapping Approach to Fusing MODIS and Landsat Images for Forward Prediction

    OpenAIRE

    Chiman Kwan; Bence Budavari; Feng Gao; Xiaolin Zhu

    2018-01-01

    We present a new, simple, and efficient approach to fusing MODIS and Landsat images. It is well known that MODIS images have high temporal resolution and low spatial resolution, whereas Landsat images are just the opposite. Similar to earlier approaches, our goal is to fuse MODIS and Landsat images to yield high spatial and high temporal resolution images. Our approach consists of two steps. First, a mapping is established between two MODIS images, where one is at an earlier time, t1, and the...

  19. Comparing performance of organization on implementation of customer relationship management systems using ANP and TOPSIS hybrid approach

    Directory of Open Access Journals (Sweden)

    A. Abedi

    2017-01-01

    Full Text Available As the customers are the main reason of the formation and survival of the organization, not only understanding their obvious needs, but also forecasting, determining and guiding their hidden needs, design and implementing plans of offering services for meeting these needs for attracting customers are among cornerstone of any activity in the organization. In this research, one compares the performance of e-commerce organizations, including three firms, namely Dijikala, Bamilo and Iranian regarding the implementation of Customer Relationship Management system using multiple criteria decision making approach. Along with this, hybrid fuzzy multiple criteria decision-making approach, including fuzzy network analysis has been used for examining the priority of each one of the dimensions and indexes of the proposed model and fuzzy TOPSIS technic for examining discussed options priority. The statistical population of this paper includes 12 experts, including directors and managements and assistances of three e-commerce firms. The results obtained from the study show that customer output group has the highest weight among other variables. Similarly, among evaluated indexes, the customer loyalty dimension has the highest weight in the implementation of Customer Relationship Management. The results of TOPSIS approach also show that among the studied firms, Dijikala has the best performance in implementing Customer Relationship Management.

  20. Solution Approach to Automatic Generation Control Problem Using Hybridized Gravitational Search Algorithm Optimized PID and FOPID Controllers

    Directory of Open Access Journals (Sweden)

    DAHIYA, P.

    2015-05-01

    Full Text Available This paper presents the application of hybrid opposition based disruption operator in gravitational search algorithm (DOGSA to solve automatic generation control (AGC problem of four area hydro-thermal-gas interconnected power system. The proposed DOGSA approach combines the advantages of opposition based learning which enhances the speed of convergence and disruption operator which has the ability to further explore and exploit the search space of standard gravitational search algorithm (GSA. The addition of these two concepts to GSA increases its flexibility for solving the complex optimization problems. This paper addresses the design and performance analysis of DOGSA based proportional integral derivative (PID and fractional order proportional integral derivative (FOPID controllers for automatic generation control problem. The proposed approaches are demonstrated by comparing the results with the standard GSA, opposition learning based GSA (OGSA and disruption based GSA (DGSA. The sensitivity analysis is also carried out to study the robustness of DOGSA tuned controllers in order to accommodate variations in operating load conditions, tie-line synchronizing coefficient, time constants of governor and turbine. Further, the approaches are extended to a more realistic power system model by considering the physical constraints such as thermal turbine generation rate constraint, speed governor dead band and time delay.

  1. Control and fault diagnosis based sliding mode observer of a multicellular converter: Hybrid approach

    KAUST Repository

    Benzineb, Omar; Taibi, Fateh; Laleg-Kirati, Taous-Meriem; Boucherit, Mohamed Seghir; Tadjine, Mohamed

    2013-01-01

    control and an observer-type sliding mode to generate residuals from the observation errors of the system. The simulation results are presented at the end to illustrate the performance of the proposed approach. © 2013 FEI STU.

  2. A hybrid finite element - statistical energy analysis approach to robust sound transmission modeling

    Science.gov (United States)

    Reynders, Edwin; Langley, Robin S.; Dijckmans, Arne; Vermeir, Gerrit

    2014-09-01

    When considering the sound transmission through a wall in between two rooms, in an important part of the audio frequency range, the local response of the rooms is highly sensitive to uncertainty in spatial variations in geometry, material properties and boundary conditions, which have a wave scattering effect, while the local response of the wall is rather insensitive to such uncertainty. For this mid-frequency range, a computationally efficient modeling strategy is adopted that accounts for this uncertainty. The partitioning wall is modeled deterministically, e.g. with finite elements. The rooms are modeled in a very efficient, nonparametric stochastic way, as in statistical energy analysis. All components are coupled by means of a rigorous power balance. This hybrid strategy is extended so that the mean and variance of the sound transmission loss can be computed as well as the transition frequency that loosely marks the boundary between low- and high-frequency behavior of a vibro-acoustic component. The method is first validated in a simulation study, and then applied for predicting the airborne sound insulation of a series of partition walls of increasing complexity: a thin plastic plate, a wall consisting of gypsum blocks, a thicker masonry wall and a double glazing. It is found that the uncertainty caused by random scattering is important except at very high frequencies, where the modal overlap of the rooms is very high. The results are compared with laboratory measurements, and both are found to agree within the prediction uncertainty in the considered frequency range.

  3. A Hybrid Approach using Collaborative filtering and Content based Filtering for Recommender System

    Science.gov (United States)

    Geetha, G.; Safa, M.; Fancy, C.; Saranya, D.

    2018-04-01

    In today’s digital world, it has become an irksome task to find the content of one's liking in an endless variety of content that are being consumed like books, videos, articles, movies, etc. On the other hand there has been an emerging growth among the digital content providers who want to engage as many users on their service as possible for the maximum time. This gave birth to the recommender system comes wherein the content providers recommend users the content according to the users’ taste and liking. In this paper we have proposed a movie recommendation system. A movie recommendation is important in our social life due to its features such as suggesting a set of movies to users based on their interest, or the popularities of the movies. In this paper we are proposing a movie recommendation system that has the ability to recommend movies to a new user as well as the other existing users. It mines movie databases to collect all the important information, such as, popularity and attractiveness, which are required for recommendation. We use content-based and collaborative filtering and also hybrid filtering, which is a combination of the results of these two techniques, to construct a system that provides more precise recommendations concerning movies.

  4. Chloroplast evolution in the Pinus montezumae complex: a coalescent approach to hybridization.

    Science.gov (United States)

    Matos, J A; Schaal, B A

    2000-08-01

    This study addresses the evolutionary history of the chloroplast genomes of two closely related pine species, Pinus hartwegii Lindl. and P. montezumae Lamb (subsect. Ponderosae) using coalescent theory and some of the statistical tools that have been developed from it during the past two decades. Pinus hartwegii and P. montezumae are closely related species in the P. montezumae complex (subsect. Ponderosae) of Mexico and Central America. Pinus hartwegii is a high elevation species, whereas P. montezumae occurs at lower elevations. The two species occur on many of the same mountains throughout Mexico. A total of 350 individuals of P. hartwegii and P. montezumae were collected from Nevado de Colima (Jalisco), Cerro Potosí (Nuevo León), Iztaccihuatl/Popocatepetl (México), and Nevado de Toluca (México). The chloroplast genome of P. hartwegii and P. montezumae was mapped using eight restriction enzymes. Fifty-one different haplotypes were characterized; 38 of 160 restriction sites were polymorphic. Clades of most parsimoniously related chloroplast haplotypes are geographically localized and do not overlap in distribution, and the geographically localized clades of haplotypes include both P. hartwegii and P. montezumae. Some haplotypes in the clades occur in only one of the two species, whereas other haplotypes occur in both species. These data strongly suggest ancient and/or ongoing hybridization between P. hartwegii and P. montezumae and a shared chloroplast genome history within geographic regions of Mexico.

  5. An intelligent hybrid scheme for optimizing parking space: A Tabu metaphor and rough set based approach

    Directory of Open Access Journals (Sweden)

    Soumya Banerjee

    2011-03-01

    Full Text Available Congested roads, high traffic, and parking problems are major concerns for any modern city planning. Congestion of on-street spaces in official neighborhoods may give rise to inappropriate parking areas in office and shopping mall complex during the peak time of official transactions. This paper proposes an intelligent and optimized scheme to solve parking space problem for a small city (e.g., Mauritius using a reactive search technique (named as Tabu Search assisted by rough set. Rough set is being used for the extraction of uncertain rules that exist in the databases of parking situations. The inclusion of rough set theory depicts the accuracy and roughness, which are used to characterize uncertainty of the parking lot. Approximation accuracy is employed to depict accuracy of a rough classification [1] according to different dynamic parking scenarios. And as such, the hybrid metaphor proposed comprising of Tabu Search and rough set could provide substantial research directions for other similar hard optimization problems.

  6. Using one hybrid 3D-1D-3D approach for the conceptual design of WCCB blanket for CFETR

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Kecheng; Zhang, Xiaokang [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui, 230031 (China); University of Science and Technology of China, Hefei, Anhui, 230027 (China); Li, Jia [University of Science and Technology of China, Hefei, Anhui, 230027 (China); Ma, Xuebin [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui, 230031 (China); University of Science and Technology of China, Hefei, Anhui, 230027 (China); Liu, Songlin, E-mail: slliu@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui, 230031 (China); University of Science and Technology of China, Hefei, Anhui, 230027 (China)

    2017-01-15

    Highlights: • The Hybrid 3D-1D-3D approach is used for radial building design of WCCB. • Nuclear heat obtained by this method agrees well with 3D neutronics results. • The final results of temperature and TBR satisfy with the requirements. • All the results show that this approach is high efficiency and high reliability. - Abstract: A hybrid 3D-1D-3D approach is proposed for the conceptual design of a blanket. Firstly, the neutron wall loading (NWL) of each blanket module is obtained through a neutronics calculation employing a 3D model, which contains the geometry outline of in-vacuum vessel components and the exact neutron source distribution. Secondly, a 1D cylindrical model with the blanket module containing a detailed radial building is adopted for the neutronics analysis, with the aim of calculating the tritium breeding ratio (TBR) and nuclear heating. Being normalized to the NWL, the nuclear heating is transferred to a 2D model for thermal-hydraulics analysis using the FLUENT code. Through a series analysis of nuclear-thermal iterations that considers the tritium breeding ratio (TBR) and thermal performance as optimization objectives, the optimized radial building of each module surrounding plasma can be obtained. Thirdly, the 3D structural design of each module is established by adding side walls, cover plates, stiffening plates, and other components based on the radial building. The 3D neutronics and thermal-hydraulics using the detailed blanket modules are re-analyzed. This approach has been successfully applied to the design of a water-cooled ceramic breeder blanket for the Chinese Fusion Engineering Test Reactor (CFETR). The radial building of each blanket module surrounding plasma is optimized. The global tritium breeding ratio (TBR) calculated by the 3D neutronics analysis is 1.21, and the temperature of all materials in the 3D blanket structure is below the upper limits. As indicated by the comparison of the 1D and 3D neutronics and thermal

  7. Hybrid Correlation Energy (HyCE): An Approach Based on Separate Evaluations of Internal and External Components.

    Science.gov (United States)

    Ivanic, Joseph; Schmidt, Michael W

    2018-06-04

    A novel hybrid correlation energy (HyCE) approach is proposed that determines the total correlation energy via distinct computation of its internal and external components. This approach evolved from two related studies. First, rigorous assessment of the accuracies and size extensivities of a number of electron correlation methods, that include perturbation theory (PT2), coupled-cluster (CC), configuration interaction (CI), and coupled electron pair approximation (CEPA), shows that the CEPA(0) variant of the latter and triples-corrected CC methods consistently perform very similarly. These findings were obtained by comparison to near full CI results for four small molecules and by charting recovered correlation energies for six steadily growing chain systems. Second, by generating valence virtual orbitals (VVOs) and utilizing the CEPA(0) method, we were able to partition total correlation energies into internal (or nondynamic) and external (or dynamic) parts for the aforementioned six chain systems and a benchmark test bed of 36 molecules. When using triple-ζ basis sets it was found that per orbital internal correlation energies were appreciably larger than per orbital external energies and that the former showed far more chemical variation than the latter. Additionally, accumulations of external correlation energies were seen to proceed smoothly, and somewhat linearly, as the virtual space is gradually increased. Combination of these two studies led to development of the HyCE approach, whereby the internal and external correlation energies are determined separately by CEPA(0)/VVO and PT2/external calculations, respectively. When applied to the six chain systems and the 36-molecule benchmark test set it was found that HyCE energies followed closely those of triples-corrected CC and CEPA(0) while easily outperforming MP2 and CCSD. The success of the HyCE approach is more notable when considering that its cost is only slightly more than MP2 and significantly cheaper

  8. CoFe2O4-TiO2 Hybrid Nanomaterials: Synthesis Approaches Based on the Oil-in-Water Microemulsion Reaction Method

    Directory of Open Access Journals (Sweden)

    Arturo Adrián Rodríguez-Rodríguez

    2017-01-01

    Full Text Available CoFe2O4 nanoparticles decorated and wrapped with TiO2 nanoparticles have been prepared by mixing well-dispersed CoFe2O4 with amorphous TiO2 (impregnation approach and growing amorphous TiO2 over the magnetic core (seed approach, respectively, followed by thermal treatment to achieve TiO2 crystallinity. Synthesis strategies were based on the oil-in-water microemulsion reaction method. Thermally treated nanomaterials were characterized in terms of structure, morphology, and composition, to confirm hybrid nanoparticles formation and relate with the synthesis approaches; textural, optical, and magnetic properties were evaluated. X-ray diffraction revealed coexistence of cubic spinel-type CoFe2O4 and tetragonal anatase TiO2. Electron microscopy images depicted crystalline nanoparticles (sizes below 25 nm, with homogeneous Ti distribution for the hybrid nanoparticles synthesized by seed approach. EDX microanalysis and ICP-AES corroborated established chemical composition. XPS evidenced chemical states, as well as TiO2 predominance over CoFe2O4 surface. According to BET measurements, the hybrid nanoparticles were mesoporous. UV-Vis spectroscopy showed optical response along the UV-visible light region. Magnetic properties suggested the breaking order of magnetic domains due to modification with TiO2, especially for mediated seed approach sample. The properties of the obtained hybrid nanoparticles were different in comparison with its individual components. The results highlight the usefulness of designed microemulsion approaches for the straightforward synthesis of CoFe2O4-TiO2 nanostructured hybrids.

  9. Hybrid approaches for multiple-species stochastic reaction–diffusion models

    International Nuclear Information System (INIS)

    Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen

    2015-01-01

    Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries

  10. Multiple Realities and Hybrid Objects: A Creative Approach of Schizophrenic Delusion

    Directory of Open Access Journals (Sweden)

    Michel Cermolacce

    2018-02-01

    Full Text Available Delusion is usually considered in DSM 5 as a false belief based on incorrect inference about external reality, but the issue of delusion raises crucial concerns, especially that of a possible (or absent continuity between delusional and normal experiences, and the understanding of delusional experience. In the present study, we first aim to consider delusion from a perspectivist angle, according to the Multiple Reality Theory (MRT. In this model inherited from Alfred Schütz and recently addressed by Gallagher, we are not confronting one reality only, but several (such as the reality of everyday life, of imaginary life, of work, of delusion, etc.. In other terms, the MRT states that our own experience is not drawing its meaning from one reality identified as the outer reality but rather from a multiplicity of realities, each with their own logic and style. Two clinical cases illustrate how the Multiple Realities Theory (MRT may help address the reality of delusion. Everyday reality and the reality of delusion may be articulated under a few conditions, such as compossibility [i.e., Double Book-Keeping (DBK, in Bleulerian terms] or flexibility. There are indeed possible bridges between them. Possible links with neuroscience or psychoanalysis are evoked. As the subject is confronting different realities, so do the objects among and toward which a subject is evolving. We call such objects Hybrid Objects (HO due to their multiple belonging. They can operate as shifters, i.e., as some functional operators letting one switch from one reality to another. In the final section, we will emphasize how delusion flexibility, as a dynamic interaction between Multiple Realities, may offer psychotherapeutic possibilities within some reality shared with others, entailing relocation of the present subjects in regained access to some flexibility via Multiple Realities and perspectivism.

  11. Hybrid approaches for multiple-species stochastic reaction–diffusion models

    Energy Technology Data Exchange (ETDEWEB)

    Spill, Fabian, E-mail: fspill@bu.edu [Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215 (United States); Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States); Guerrero, Pilar [Department of Mathematics, University College London, Gower Street, London WC1E 6BT (United Kingdom); Alarcon, Tomas [Centre de Recerca Matematica, Campus de Bellaterra, Edifici C, 08193 Bellaterra (Barcelona) (Spain); Departament de Matemàtiques, Universitat Atonòma de Barcelona, 08193 Bellaterra (Barcelona) (Spain); Maini, Philip K. [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Byrne, Helen [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Computational Biology Group, Department of Computer Science, University of Oxford, Oxford OX1 3QD (United Kingdom)

    2015-10-15

    Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.

  12. Management of Gastropleural Fistula after Revisional Bariatric Surgery: A Hybrid Laparoendoscopic Approach.

    Science.gov (United States)

    Ghanem, Omar M; Abu Dayyeh, Barham K; Kellogg, Todd A

    2017-10-01

    Gastropleural fistula (GPF) is a serious complication after bariatric surgery. Multiple treatment modalities including pharmacologic, endoscopic, and revisional surgery have been proposed. We present a case of a GPF managed successfully with a laparoendoscopic approach utilizing a fistula plug. A 43-year-old male patient presented with a GPF after a revisional bariatric surgery. A laparoendoscopic approach including lysis of adhesions, identification of the fistula, plugging the fistula with a BioGore A® fistula plug, placement an enteric stent, placement of a feeding tube, and surgical drainage was performed. The multimedia video illustrates the technique used. Postoperatively, upper gastrointestinal (UGI) imaging showed no evidence of leak. The enteric stent was removed after 2 months after verifying complete healing of the fistula. A laparoendoscopic approach to GPF repair with the use of fistula plug is effective, safe, and feasible.

  13. A Hybrid Density Functional Theory/Molecular Mechanics Approach for Linear Response Properties in Heterogeneous Environments.

    Science.gov (United States)

    Rinkevicius, Zilvinas; Li, Xin; Sandberg, Jaime A R; Mikkelsen, Kurt V; Ågren, Hans

    2014-03-11

    We introduce a density functional theory/molecular mechanical approach for computation of linear response properties of molecules in heterogeneous environments, such as metal surfaces or nanoparticles embedded in solvents. The heterogeneous embedding environment, consisting from metallic and nonmetallic parts, is described by combined force fields, where conventional force fields are used for the nonmetallic part and capacitance-polarization-based force fields are used for the metallic part. The presented approach enables studies of properties and spectra of systems embedded in or placed at arbitrary shaped metallic surfaces, clusters, or nanoparticles. The capability and performance of the proposed approach is illustrated by sample calculations of optical absorption spectra of thymidine absorbed on gold surfaces in an aqueous environment, where we study how different organizations of the gold surface and how the combined, nonadditive effect of the two environments is reflected in the optical absorption spectrum.

  14. A Model-Driven Approach for Hybrid Power Estimation in Embedded Systems Design

    Directory of Open Access Journals (Sweden)

    Ben Atitallah Rabie

    2011-01-01

    Full Text Available Abstract As technology scales for increased circuit density and performance, the management of power consumption in system-on-chip (SoC is becoming critical. Today, having the appropriate electronic system level (ESL tools for power estimation in the design flow is mandatory. The main challenge for the design of such dedicated tools is to achieve a better tradeoff between accuracy and speed. This paper presents a consumption estimation approach allowing taking the consumption criterion into account early in the design flow during the system cosimulation. The originality of this approach is that it allows the power estimation for both white-box intellectual properties (IPs using annotated power models and black-box IPs using standalone power estimators. In order to obtain accurate power estimates, our simulations were performed at the cycle-accurate bit-accurate (CABA level, using SystemC. To make our approach fast and not tedious for users, the simulated architectures, including standalone power estimators, were generated automatically using a model driven engineering (MDE approach. Both annotated power models and standalone power estimators can be used together to estimate the consumption of the same architecture, which makes them complementary. The simulation results showed that the power estimates given by both estimation techniques for a hardware component are very close, with a difference that does not exceed 0.3%. This proves that, even when the IP code is not accessible or not modifiable, our approach allows obtaining quite accurate power estimates that early in the design flow thanks to the automation offered by the MDE approach.

  15. A numerical approach for size optimization and performance prediction of solar P V-hybrid power systems

    International Nuclear Information System (INIS)

    Zahedi, A.; Calia, N.

    2001-10-01

    Iran is blessed with an abundance of sunlight almost all year round. so obviously, with the right planning and strategies that are coupled to the right technology and development in the market, the potential for the new renewable energies, specially solar photovoltaic, as an alternative source of power looks promising and is constantly gaining popularity. Development and application of new renewable energy in Iran, however, is still in its infancy and will require active support by government, utilities and financing institutions. some experts might argue that Iran has plenty of natural resources like oil and gas. We should not forget, however, that even in countries with cheap fossil energy, the P V system is an economical option in supplying electricity for remote located communities and facilities. But there are good reasons suggesting that like many other countries in the world, Iran also needs to be active in utilization of sun energy. The objectives of this paper are: to give a comprehensive overview on the current solar photovoltaic energy technology. (Authors of this paper believe that Photovoltaic is the most appropriate renewable energy technology for Iran); to present the results obtained from a study which has been carried out on the size optimization, cost calculation of the photovoltaic systems for climate conditions of Iran. The method presented in this paper can be used for systems of any size and application. A further objective of this paper is to present a numerical approach for evaluating the performance of P V-Hybrid power systems. A method is developed to predict the performance of all components integrated into a P V-hybrid system. The system under investigation is a hybrid power system, in which the integrated components are P V array, a battery bank for backing up the system and a diesel generator set for supporting the battery bank. State of charge of batteries is used as a measure for the performance of the system. The running time of

  16. Controlled growth of silica-titania hybrid functional nanoparticles through a multistep microfluidic approach.

    Science.gov (United States)

    Shiba, K; Sugiyama, T; Takei, T; Yoshikawa, G

    2015-11-11

    Silica/titania-based functional nanoparticles were prepared through controlled nucleation of titania and subsequent encapsulation by silica through a multistep microfluidic approach, which was successfully applied to obtaining aminopropyl-functionalized silica/titania nanoparticles for a highly sensitive humidity sensor.

  17. A Hybrid Sensor Based Backstepping Control Approach with its Application to Fault-Tolerant Flight Control

    NARCIS (Netherlands)

    Sun, L.G.; De Visser, C.C.; Chu, Q.P.; Falkena, W.

    2013-01-01

    Recently, an incremental type sensor based backstepping (SBB) control approach, based on singular perturbation theory and Tikhonov’s theorem, has been proposed. This Lyapunov function based method uses measurements of control variables and less model knowledge, and it is not susceptible to the model

  18. A hybrid approach to quantify software reliability in nuclear safety systems

    International Nuclear Information System (INIS)

    Arun Babu, P.; Senthil Kumar, C.; Murali, N.

    2012-01-01

    Highlights: ► A novel method to quantify software reliability using software verification and mutation testing in nuclear safety systems. ► Contributing factors that influence software reliability estimate. ► Approach to help regulators verify the reliability of safety critical software system during software licensing process. -- Abstract: Technological advancements have led to the use of computer based systems in safety critical applications. As computer based systems are being introduced in nuclear power plants, effective and efficient methods are needed to ensure dependability and compliance to high reliability requirements of systems important to safety. Even after several years of research, quantification of software reliability remains controversial and unresolved issue. Also, existing approaches have assumptions and limitations, which are not acceptable for safety applications. This paper proposes a theoretical approach combining software verification and mutation testing to quantify the software reliability in nuclear safety systems. The theoretical results obtained suggest that the software reliability depends on three factors: the test adequacy, the amount of software verification carried out and the reusability of verified code in the software. The proposed approach may help regulators in licensing computer based safety systems in nuclear reactors.

  19. Implementing the Project Approach: A Case Study of Hybrid Pedagogy in a Hong Kong Kindergarten

    Science.gov (United States)

    Chen, Jennifer J.; Li, Hui; Wang, Jing-ying

    2017-01-01

    The Project Approach has been promoted in Hong Kong kindergartens since the 1990s. However, the dynamic processes and underlying mechanisms involved in the teachers' implementation of this pedagogical method there have not yet been fully investigated. This case study of one typical kindergarten in Hong Kong documented how and why eight teachers…

  20. Forecasting optimal solar energy supply in Jiangsu Province (China): a systematic approach using hybrid of weather and energy forecast models.

    Science.gov (United States)

    Zhao, Xiuli; Asante Antwi, Henry; Yiranbon, Ethel

    2014-01-01

    The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, "least-cost," and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

  1. Short-term hydro generation scheduling of Three Gorges–Gezhouba cascaded hydropower plants using hybrid MACS-ADE approach

    International Nuclear Information System (INIS)

    Mo, Li; Lu, Peng; Wang, Chao; Zhou, Jianzhong

    2013-01-01

    Highlights: • MACS and ADE algorithms are hybridized as MACS-ADE method for solving STHGS problem. • An adaptive mutation is integrated into the proposed algorithm to avoid premature convergence. • MACS and ADE are run in parallel in search of better solution. • Several effective heuristic strategies are designed for dealing with various constraints of STHGS problem. - Abstract: Short-term hydro generation scheduling (STHGS) aims at determining optimal hydro generation scheduling to obtain minimum water consumption for one day or week while meeting various system constraints. In this paper, the STHGS problem is decomposed into two sub-problems: (i) unit commitment (UC) sub-problem; (ii) economic load dispatch (ELD) sub-problem. Then, we present a hybrid algorithm based on multi ant colony system (MACS) and differential evolution (DE) for solving the STHGS problem. First, MACS is used for dealing with UC sub-problem. A set of cooperating ant colonies cooperate to choose the unit state over the scheduled time horizon. Then, the adaptive differential evolution (ADE) is used to solve ELD sub-problem. MACS and ADE are run in parallel with adjusting their solutions in search of a better solution. Meanwhile, local and global pheromone updating rules in MACS and adaptive dynamic parameter adjusting strategy in DE are applied for enhancing the search ability of MACS-ADE. Finally, the proposed method is implemented to solve STHGS problem of Three Gorges–Gezhouba cascaded hydropower plants to verify the feasibility and effectiveness. Compared with other established methods, the simulation results reveal that the proposed MACS-ADE approach has the best convergence property, computational efficiency with less water consumption

  2. Forecasting Optimal Solar Energy Supply in Jiangsu Province (China: A Systematic Approach Using Hybrid of Weather and Energy Forecast Models

    Directory of Open Access Journals (Sweden)

    Xiuli Zhao

    2014-01-01

    Full Text Available The idea of aggregating information is clearly recognizable in the daily lives of all entities whether as individuals or as a group, since time immemorial corporate organizations, governments, and individuals as economic agents aggregate information to formulate decisions. Energy planning represents an investment-decision problem where information needs to be aggregated from credible sources to predict both demand and supply of energy. To do this there are varying methods ranging from the use of portfolio theory to managing risk and maximizing portfolio performance under a variety of unpredictable economic outcomes. The future demand for energy and need to use solar energy in order to avoid future energy crisis in Jiangsu province in China require energy planners in the province to abandon their reliance on traditional, “least-cost,” and stand-alone technology cost estimates and instead evaluate conventional and renewable energy supply on the basis of a hybrid of optimization models in order to ensure effective and reliable supply. Our task in this research is to propose measures towards addressing optimal solar energy forecasting by employing a systematic optimization approach based on a hybrid of weather and energy forecast models. After giving an overview of the sustainable energy issues in China, we have reviewed and classified the various models that existing studies have used to predict the influences of the weather influences and the output of solar energy production units. Further, we evaluate the performance of an exemplary ensemble model which combines the forecast output of two popular statistical prediction methods using a dynamic weighting factor.

  3. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew

    2017-12-06

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  4. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    KAUST Repository

    McCabe, Matthew; McCabe, Matthew

    2017-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

  5. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

    Science.gov (United States)

    Houborg, Rasmus; McCabe, Matthew F.

    2018-01-01

    With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory 'predictor' variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association with

  6. A Hybrid Digital-Signature and Zero-Watermarking Approach for Authentication and Protection of Sensitive Electronic Documents

    Directory of Open Access Journals (Sweden)

    Omar Tayan

    2014-01-01

    Full Text Available This paper addresses the problems and threats associated with verification of integrity, proof of authenticity, tamper detection, and copyright protection for digital-text content. Such issues were largely addressed in the literature for images, audio, and video, with only a few papers addressing the challenge of sensitive plain-text media under known constraints. Specifically, with text as the predominant online communication medium, it becomes crucial that techniques are deployed to protect such information. A number of digital-signature, hashing, and watermarking schemes have been proposed that essentially bind source data or embed invisible data in a cover media to achieve its goal. While many such complex schemes with resource redundancies are sufficient in offline and less-sensitive texts, this paper proposes a hybrid approach based on zero-watermarking and digital-signature-like manipulations for sensitive text documents in order to achieve content originality and integrity verification without physically modifying the cover text in anyway. The proposed algorithm was implemented and shown to be robust against undetected content modifications and is capable of confirming proof of originality whilst detecting and locating deliberate/nondeliberate tampering. Additionally, enhancements in resource utilisation and reduced redundancies were achieved in comparison to traditional encryption-based approaches. Finally, analysis and remarks are made about the current state of the art, and future research issues are discussed under the given constraints.

  7. NEBNext Direct: A Novel, Rapid, Hybridization-Based Approach for the Capture and Library Conversion of Genomic Regions of Interest.

    Science.gov (United States)

    Emerman, Amy B; Bowman, Sarah K; Barry, Andrew; Henig, Noa; Patel, Kruti M; Gardner, Andrew F; Hendrickson, Cynthia L

    2017-07-05

    Next-generation sequencing (NGS) is a powerful tool for genomic studies, translational research, and clinical diagnostics that enables the detection of single nucleotide polymorphisms, insertions and deletions, copy number variations, and other genetic variations. Target enrichment technologies improve the efficiency of NGS by only sequencing regions of interest, which reduces sequencing costs while increasing coverage of the selected targets. Here we present NEBNext Direct ® , a hybridization-based, target-enrichment approach that addresses many of the shortcomings of traditional target-enrichment methods. This approach features a simple, 7-hr workflow that uses enzymatic removal of off-target sequences to achieve a high specificity for regions of interest. Additionally, unique molecular identifiers are incorporated for the identification and filtering of PCR duplicates. The same protocol can be used across a wide range of input amounts, input types, and panel sizes, enabling NEBNext Direct to be broadly applicable across a wide variety of research and diagnostic needs. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

  8. A Hybrid Digital-Signature and Zero-Watermarking Approach for Authentication and Protection of Sensitive Electronic Documents

    Science.gov (United States)

    Kabir, Muhammad N.; Alginahi, Yasser M.

    2014-01-01

    This paper addresses the problems and threats associated with verification of integrity, proof of authenticity, tamper detection, and copyright protection for digital-text content. Such issues were largely addressed in the literature for images, audio, and video, with only a few papers addressing the challenge of sensitive plain-text media under known constraints. Specifically, with text as the predominant online communication medium, it becomes crucial that techniques are deployed to protect such information. A number of digital-signature, hashing, and watermarking schemes have been proposed that essentially bind source data or embed invisible data in a cover media to achieve its goal. While many such complex schemes with resource redundancies are sufficient in offline and less-sensitive texts, this paper proposes a hybrid approach based on zero-watermarking and digital-signature-like manipulations for sensitive text documents in order to achieve content originality and integrity verification without physically modifying the cover text in anyway. The proposed algorithm was implemented and shown to be robust against undetected content modifications and is capable of confirming proof of originality whilst detecting and locating deliberate/nondeliberate tampering. Additionally, enhancements in resource utilisation and reduced redundancies were achieved in comparison to traditional encryption-based approaches. Finally, analysis and remarks are made about the current state of the art, and future research issues are discussed under the given constraints. PMID:25254247

  9. A Model-Based Approach for Bridging Virtual and Physical Sensor Nodes in a Hybrid Simulation Framework

    Directory of Open Access Journals (Sweden)

    Mohammad Mozumdar

    2014-06-01

    Full Text Available The Model Based Design (MBD approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs are an emerging very promising application area for embedded systems. However, there is a lack of tools in this area, which would allow an application developer to model a WSN application by using high level abstractions, simulate it mapped to a multi-node scenario for functional analysis, and finally use the refined model to automatically generate code for different WSN platforms. Motivated by this idea, in this paper we present a hybrid simulation framework that not only follows the MBD approach for WSN application development, but also interconnects a simulated sub-network with a physical sub-network and then allows one to co-simulate them, which is also known as Hardware-In-the-Loop (HIL simulation.

  10. A hybrid mathematical modeling approach of the metabolic fate of a fluorescent sphingolipid analogue to predict cancer chemosensitivity.

    Science.gov (United States)

    Molina-Mora, J A; Kop-Montero, M; Quirós-Fernández, I; Quiros, S; Crespo-Mariño, J L; Mora-Rodríguez, R A

    2018-04-13

    Sphingolipid (SL) metabolism is a complex biological system that produces and transforms ceramides and other molecules able to modulate other cellular processes, including survival or death pathways key to cell fate decisions. This signaling pathway integrates several types of stress signals, including chemotherapy, into changes in the activity of its metabolic enzymes, altering thereby the cellular composition of bioactive SLs. Therefore, the SL pathway is a promising sensor of chemosensitivity in cancer and a target hub to overcome resistance. However, there is still a gap in our understanding of how chemotherapeutic drugs can disturb the SL pathway in order to control cellular fate. We propose to bridge this gap by a systems biology approach to integrate i) a dynamic model of SL analogue (BODIPY-FL fluorescent-sphingomyelin analogue, SM-BOD) metabolism, ii) a Gaussian mixture model (GMM) of the fluorescence features to identify how the SL pathway senses the effect of chemotherapy and iii) a fuzzy logic model (FLM) to associate SL composition with cell viability by semi-quantitative rules. Altogether, this hybrid model approach was able to predict the cell viability of double experimental perturbations with chemotherapy, indicating that the SL pathway is a promising sensor to design strategies to overcome drug resistance in cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

  11. Tailor-made rehabilitation approach using multiple types of hybrid assistive limb robots for acute stroke patients: A pilot study.

    Science.gov (United States)

    Fukuda, Hiroyuki; Morishita, Takashi; Ogata, Toshiyasu; Saita, Kazuya; Hyakutake, Koichi; Watanabe, Junko; Shiota, Etsuji; Inoue, Tooru

    2016-01-01

    This article investigated the feasibility of a tailor-made neurorehabilitation approach using multiple types of hybrid assistive limb (HAL) robots for acute stroke patients. We investigated the clinical outcomes of patients who underwent rehabilitation using the HAL robots. The Brunnstrom stage, Barthel index (BI), and functional independence measure (FIM) were evaluated at baseline and when patients were transferred to a rehabilitation facility. Scores were compared between the multiple-robot rehabilitation and single-robot rehabilitation groups. Nine hemiplegic acute stroke patients (five men and four women; mean age 59.4 ± 12.5 years; four hemorrhagic stroke and five ischemic stroke) underwent rehabilitation using multiple types of HAL robots for 19.4 ± 12.5 days, and 14 patients (six men and eight women; mean age 63.2 ± 13.9 years; nine hemorrhagic stroke and five ischemic stroke) underwent rehabilitation using a single type of HAL robot for 14.9 ± 8.9 days. The multiple-robot rehabilitation group showed significantly better outcomes in the Brunnstrom stage of the upper extremity, BI, and FIM scores. To the best of the authors' knowledge, this is the first pilot study demonstrating the feasibility of rehabilitation using multiple exoskeleton robots. The tailor-made rehabilitation approach may be useful for the treatment of acute stroke.

  12. A Hybrid Approach to the Valuation of RFID/MEMS technology applied to ordnance inventory

    OpenAIRE

    Doerr, Kenneth H.; Gates, William R.; Mutty, John E.

    2006-01-01

    We report on an analysis of the costs and benefits of fielding Radio Frequency Identification / MicroElectroMechanical System (RFID /MEMS) technology for the management of ordnance inventory. A factorial model of these benefits is proposed. Our valuation approach combines a multi-criteria tool for the valuation of qualitative factors with a monte-carlo simulation of anticipated financial factors. In a sample survey, qualitative factors are shown to account of over half of the anticipated bene...

  13. A Hybrid Approach to Composite Damage and Failure Analysis Combining Synergistic Damage Mechanics and Peridynamics

    Science.gov (United States)

    2017-03-30

    manufacturing defects in the intermediately -homogenized model of fiber-reinforced composites. 15. SUBJECT TERMS Computational micromechanics; Cavitation...defects in the intermediately -homogenized model of fiber-reinforced composites. Task 1.1 Micro-level crack initiation Background and motivation In...new Intermediate Homogenization Peridynamic approach (IH-PD model) for failure in multiphase materials. We plan to apply this IH-PD model for the

  14. Hybrid approach for the assessment of PSA models by means of binary decision diagrams

    International Nuclear Information System (INIS)

    Ibanez-Llano, Cristina; Rauzy, Antoine; Melendez, Enrique; Nieto, Francisco

    2010-01-01

    Binary decision diagrams are a well-known alternative to the minimal cutsets approach to assess the reliability Boolean models. They have been applied successfully to improve the fault trees models assessment. However, its application to solve large models, and in particular the event trees coming from the PSA studies of the nuclear industry, remains to date out of reach of an exact evaluation. For many real PSA models it may be not possible to compute the BDD within reasonable amount of time and memory without considering the truncation or simplification of the model. This paper presents a new approach to estimate the exact probabilistic quantification results (probability/frequency) based on combining the calculation of the MCS and the truncation limits, with the BDD approach, in order to have a better control on the reduction of the model and to properly account for the success branches. The added value of this methodology is that it is possible to ensure a real confidence interval of the exact value and therefore an explicit knowledge of the error bound. Moreover, it can be used to measure the acceptability of the results obtained with traditional techniques. The new method was applied to a real life PSA study and the results obtained confirm the applicability of the methodology and open a new viewpoint for further developments.

  15. Hybrid approach for the assessment of PSA models by means of binary decision diagrams

    Energy Technology Data Exchange (ETDEWEB)

    Ibanez-Llano, Cristina, E-mail: cristina.ibanez@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain); Rauzy, Antoine, E-mail: Antoine.RAUZY@3ds.co [Dassault Systemes, 10 rue Marcel Dassault CS 40501, 78946 Velizy Villacoublay Cedex (France); Melendez, Enrique, E-mail: ema@csn.e [Consejo de Seguridad Nuclear (CSN), C/Justo Dorado 11, 28040 Madrid (Spain); Nieto, Francisco, E-mail: nieto@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain)

    2010-10-15

    Binary decision diagrams are a well-known alternative to the minimal cutsets approach to assess the reliability Boolean models. They have been applied successfully to improve the fault trees models assessment. However, its application to solve large models, and in particular the event trees coming from the PSA studies of the nuclear industry, remains to date out of reach of an exact evaluation. For many real PSA models it may be not possible to compute the BDD within reasonable amount of time and memory without considering the truncation or simplification of the model. This paper presents a new approach to estimate the exact probabilistic quantification results (probability/frequency) based on combining the calculation of the MCS and the truncation limits, with the BDD approach, in order to have a better control on the reduction of the model and to properly account for the success branches. The added value of this methodology is that it is possible to ensure a real confidence interval of the exact value and therefore an explicit knowledge of the error bound. Moreover, it can be used to measure the acceptability of the results obtained with traditional techniques. The new method was applied to a real life PSA study and the results obtained confirm the applicability of the methodology and open a new viewpoint for further developments.

  16. Solving the "Personhood Jigsaw Puzzle" in Residential Care Homes for the Elderly in the Hong Kong Chinese Context.

    Science.gov (United States)

    Kong, Sui-Ting; Fang, Christine Meng-Sang; Lou, Vivian W Q

    2017-02-01

    End-of-life care studies on the nature of personhood are bourgeoning; however, the practices utilized for achieving personhood in end-of-life care, particularly in a cultural context in which interdependent being and collectivism prevail, remain underexplored. This study seeks to examine and conceptualize good practices for achieving the personhood of the dying elderly in residential care homes in a Chinese context. Twelve interviews were conducted with both medical and social care practitioners in four care homes to collect narratives of practitioners' practices. Those narratives were utilized to develop an "end-of-life case graph." Constant comparative analysis led to an understanding of the practice processes, giving rise to a process model of "solving the personhood jigsaw puzzle" that includes "understanding the person-in-relationship and person-in-time," "identifying the personhood-inhibiting experiences," and "enabling personalized care for enhanced psychosocial outcomes." Findings show how the "relational personhood" of the elderly can be maintained when physical deterioration and even death are inevitable.

  17. Hybrid Feature Selection Approach Based on GRASP for Cancer Microarray Data

    Directory of Open Access Journals (Sweden)

    Arpita Nagpal

    2017-01-01

    Full Text Available Microarray data usually contain a large number of genes, but a small number of samples. Feature subset selection for microarray data aims at reducing the number of genes so that useful information can be extracted from the samples. Reducing the dimension of data sets further helps in improving the computational efficiency of the learning model. In this paper, we propose a modified algorithm based on the tabu search as local search procedures to a Greedy Randomized Adaptive Search Procedure (GRASP for high dimensional microarray data sets. The proposed Tabu based Greedy Randomized Adaptive Search Procedure algorithm is named as TGRASP. In TGRASP, a new parameter has been introduced named as Tabu Tenure and the existing parameters, NumIter and size have been modified. We observed that different parameter settings affect the quality of the optimum. The second proposed algorithm known as FFGRASP (Firefly Greedy Randomized Adaptive Search Procedure uses a firefly optimization algorithm in the local search optimzation phase of the greedy randomized adaptive search procedure (GRASP. Firefly algorithm is one of the powerful algorithms for optimization of multimodal applications. Experimental results show that the proposed TGRASP and FFGRASP algorithms are much better than existing algorithm with respect to three performance parameters viz. accuracy, run time, number of a selected subset of features. We have also compared both the approaches with a unified metric (Extended Adjusted Ratio of Ratios which has shown that TGRASP approach outperforms existing approach for six out of nine cancer microarray datasets and FFGRASP performs better on seven out of nine datasets.

  18. Dynamic-ETL: a hybrid approach for health data extraction, transformation and loading.

    Science.gov (United States)

    Ong, Toan C; Kahn, Michael G; Kwan, Bethany M; Yamashita, Traci; Brandt, Elias; Hosokawa, Patrick; Uhrich, Chris; Schilling, Lisa M

    2017-09-13

    Electronic health records (EHRs) contain detailed clinical data stored in proprietary formats with non-standard codes and structures. Participating in multi-site clinical research networks requires EHR data to be restructured and transformed into a common format and standard terminologies, and optimally linked to other data sources. The expertise and scalable solutions needed to transform data to conform to network requirements are beyond the scope of many health care organizations and there is a need for practical tools that lower the barriers of data contribution to clinical research networks. We designed and implemented a health data transformation and loading approach, which we refer to as Dynamic ETL (Extraction, Transformation and Loading) (D-ETL), that automates part of the process through use of scalable, reusable and customizable code, while retaining manual aspects of the process that requires knowledge of complex coding syntax. This approach provides the flexibility required for the ETL of heterogeneous data, variations in semantic expertise, and transparency of transformation logic that are essential to implement ETL conventions across clinical research sharing networks. Processing workflows are directed by the ETL specifications guideline, developed by ETL designers with extensive knowledge of the structure and semantics of health data (i.e., "health data domain experts") and target common data model. D-ETL was implemented to perform ETL operations that load data from various sources with different database schema structures into the Observational Medical Outcome Partnership (OMOP) common data model. The results showed that ETL rule composition methods and the D-ETL engine offer a scalable solution for health data transformation via automatic query generation to harmonize source datasets. D-ETL supports a flexible and transparent process to transform and load health data into a target data model. This approach offers a solution that lowers technical

  19. 3D Scene Reconstruction Using Omnidirectional Vision and LiDAR: A Hybrid Approach

    Directory of Open Access Journals (Sweden)

    Michiel Vlaminck

    2016-11-01

    Full Text Available In this paper, we propose a novel approach to obtain accurate 3D reconstructions of large-scale environments by means of a mobile acquisition platform. The system incorporates a Velodyne LiDAR scanner, as well as a Point Grey Ladybug panoramic camera system. It was designed with genericity in mind, and hence, it does not make any assumption about the scene or about the sensor set-up. The main novelty of this work is that the proposed LiDAR mapping approach deals explicitly with the inhomogeneous density of point clouds produced by LiDAR scanners. To this end, we keep track of a global 3D map of the environment, which is continuously improved and refined by means of a surface reconstruction technique. Moreover, we perform surface analysis on consecutive generated point clouds in order to assure a perfect alignment with the global 3D map. In order to cope with drift, the system incorporates loop closure by determining the pose error and propagating it back in the pose graph. Our algorithm was exhaustively tested on data captured at a conference building, a university campus and an industrial site of a chemical company. Experiments demonstrate that it is capable of generating highly accurate 3D maps in very challenging environments. We can state that the average distance of corresponding point pairs between the ground truth and estimated point cloud approximates one centimeter for an area covering approximately 4000 m 2 . To prove the genericity of the system, it was tested on the well-known Kitti vision benchmark. The results show that our approach competes with state of the art methods without making any additional assumptions.

  20. Hybrid approach for detection of dental caries based on the methods FCM and level sets

    Science.gov (United States)

    Chaabene, Marwa; Ben Ali, Ramzi; Ejbali, Ridha; Zaied, Mourad

    2017-03-01

    This paper presents a new technique for detection of dental caries that is a bacterial disease that destroys the tooth structure. In our approach, we have achieved a new segmentation method that combines the advantages of fuzzy C mean algorithm and level set method. The results obtained by the FCM algorithm will be used by Level sets algorithm to reduce the influence of the noise effect on the working of each of these algorithms, to facilitate level sets manipulation and to lead to more robust segmentation. The sensitivity and specificity confirm the effectiveness of proposed method for caries detection.

  1. Optimization and design of ibuprofen-loaded nanostructured lipid carriers using a hybrid-design approach for ocular drug delivery

    Science.gov (United States)

    Rathod, Vishal

    The objective of the present project was to develop the Ibuprofen-loaded Nanostructured Lipid Carrier (IBU-NLCs) for topical ocular delivery based on substantial pre-formulation screening of the components and understanding the interplay between the formulation and process variables. The BCS Class II drug: Ibuprofen was selected as the model drug for the current study. IBU-NLCs were prepared by melt emulsification and ultrasonication technique. Extensive pre-formulation studies were performed to screen the lipid components (solid and liquid) based on drug's solubility and affinity as well as components compatibility. The results from DSC & XRD assisted in selecting the most suitable ratio to be utilized for future studies. DynasanRTM 114 was selected as the solid lipid & MiglyolRTM 840 was selected as the liquid lipid based on preliminary lipid screening. The ratio of 6:4 was predicted to be the best based on its crystallinity index and the thermal events. As there are many variables involved for further optimization of the formulation, a single design approach is not always adequate. A hybrid-design approach was applied by employing the Plackett Burman design (PBD) for preliminary screening of 7 critical variables, followed by Box-Behnken design (BBD), a sub-type of response surface methodology (RSM) design using 2 relatively significant variables from the former design and incorporating Surfactant/Co-surfactant ratio as the third variable. Comparatively, KolliphorRTM HS15 demonstrated lower Mean Particle Size (PS) & Polydispersity Index (PDI) and KolliphorRTM P188 resulted in Zeta Potential (ZP) ibuprofen thereafter over several hours. These values also confirm that the production method, and all other selected variables, effectively promoted the incorporation of ibuprofen in NLC. Quality by Design (QbD) approach was successfully implemented in developing a robust ophthalmic formulation with superior physicochemical and morphometric properties. NLCs as the

  2. A Hybrid Data Mining Approach for Credit Card Usage Behavior Analysis

    Science.gov (United States)

    Tsai, Chieh-Yuan

    Credit card is one of the most popular e-payment approaches in current online e-commerce. To consolidate valuable customers, card issuers invest a lot of money to maintain good relationship with their customers. Although several efforts have been done in studying card usage motivation, few researches emphasize on credit card usage behavior analysis when time periods change from t to t+1. To address this issue, an integrated data mining approach is proposed in this paper. First, the customer profile and their transaction data at time period t are retrieved from databases. Second, a LabelSOM neural network groups customers into segments and identify critical characteristics for each group. Third, a fuzzy decision tree algorithm is used to construct usage behavior rules of interesting customer groups. Finally, these rules are used to analysis the behavior changes between time periods t and t+1. An implementation case using a practical credit card database provided by a commercial bank in Taiwan is illustrated to show the benefits of the proposed framework.

  3. Inverse Kinematics of a Humanoid Robot with Non-Spherical Hip: A Hybrid Algorithm Approach

    Directory of Open Access Journals (Sweden)

    Rafael Cisneros Limón

    2013-04-01

    Full Text Available This paper describes an approach to solve the inverse kinematics problem of humanoid robots whose construction shows a small but non negligible offset at the hip which prevents any purely analytical solution to be developed. Knowing that a purely numerical solution is not feasible due to variable efficiency problems, the proposed one first neglects the offset presence in order to obtain an approximate “solution” by means of an analytical algorithm based on screw theory, and then uses it as the initial condition of a numerical refining procedure based on the Levenberg-Marquardt algorithm. In this way, few iterations are needed for any specified attitude, making it possible to implement the algorithm for real-time applications. As a way to show the algorithm's implementation, one case of study is considered throughout the paper, represented by the SILO2 humanoid robot.

  4. Power-Split Hybrid Electric Vehicle Energy Management Based on Improved Logic Threshold Approach

    Directory of Open Access Journals (Sweden)

    Zhumu Fu

    2013-01-01

    Full Text Available We design an improved logic threshold approach of energy management for a power-split HEV assisted by an integrated starter generator (ISG. By combining the efficiency map and the optimum torque curve of internal combustion engine (ICE with the state of charge (SOC of batteries, the improved logic threshold controller manages the ICE within its peak efficiency region at first. Then the electrical power demand is established based on the ICE energy output. On that premise, a variable logic threshold value K is defined to achieve the power distribution between the ISG and the electric motor/generator (EMG. Finally, simulation models for the power-split HEV with improved logic threshold controller are established in ADVISOR. Compared to the equally power-split HEV with the logic threshold controller, when using the improved logic threshold controller, the battery power consumption, the ICE efficiency, the fuel consumption, and the motor driving system efficiency are improved.

  5. Quantum teleportation and entanglement. A hybrid approach to optical quantum information procesing

    Energy Technology Data Exchange (ETDEWEB)

    Furusawa, Akira [Tokyo Univ. (Japan). Dept. of Applied Physics; Loock, Peter van [Erlangen-Nuernberg Univ. (Germany). Lehrstuhl fuer Optik

    2011-07-01

    Unique in that it is jointly written by an experimentalist and a theorist, this monograph presents universal quantum computation based on quantum teleportation as an elementary subroutine and multi-party entanglement as a universal resource. Optical approaches to measurement-based quantum computation are also described, including schemes for quantum error correction, with most of the experiments carried out by the authors themselves. Ranging from the theoretical background to the details of the experimental realization, the book describes results and advances in the field, backed by numerous illustrations of the authors' experimental setups. Aimed at researchers, physicists, and graduate and PhD students in physics, theoretical quantum optics, quantum mechanics, and quantum information. (orig.)

  6. A Hybrid Approach for Improving Image Segmentation: Application to Phenotyping of Wheat Leaves.

    Directory of Open Access Journals (Sweden)

    Joshua Chopin

    Full Text Available In this article we propose a novel tool that takes an initial segmented image and returns a more accurate segmentation that accurately captures sharp features such as leaf tips, twists and axils. Our algorithm utilizes basic a-priori information about the shape of plant leaves and local image orientations to fit active contour models to important plant features that have been missed during the initial segmentation. We compare the performance of our approach with three state-of-the-art segmentation techniques, using three error metrics. The results show that leaf tips are detected with roughly one half of the original error, segmentation accuracy is almost always improved and more than half of the leaf breakages are corrected.

  7. A Hybrid Autonomic Computing-Based Approach to Distributed Constraint Satisfaction Problems

    Directory of Open Access Journals (Sweden)

    Abhishek Bhatia

    2015-03-01

    Full Text Available Distributed constraint satisfaction problems (DisCSPs are among the widely endeavored problems using agent-based simulation. Fernandez et al. formulated sensor and mobile tracking problem as a DisCSP, known as SensorDCSP In this paper, we adopt a customized ERE (environment, reactive rules and entities algorithm for the SensorDCSP, which is otherwise proven as a computationally intractable problem. An amalgamation of the autonomy-oriented computing (AOC-based algorithm (ERE and genetic algorithm (GA provides an early solution of the modeled DisCSP. Incorporation of GA into ERE facilitates auto-tuning of the simulation parameters, thereby leading to an early solution of constraint satisfaction. This study further contributes towards a model, built up in the NetLogo simulation environment, to infer the efficacy of the proposed approach.

  8. A hybrid load flow and event driven simulation approach to multi-state system reliability evaluation

    International Nuclear Information System (INIS)

    George-Williams, Hindolo; Patelli, Edoardo

    2016-01-01

    Structural complexity of systems, coupled with their multi-state characteristics, renders their reliability and availability evaluation difficult. Notwithstanding the emergence of various techniques dedicated to complex multi-state system analysis, simulation remains the only approach applicable to realistic systems. However, most simulation algorithms are either system specific or limited to simple systems since they require enumerating all possible system states, defining the cut-sets associated with each state and monitoring their occurrence. In addition to being extremely tedious for large complex systems, state enumeration and cut-set definition require a detailed understanding of the system's failure mechanism. In this paper, a simple and generally applicable simulation approach, enhanced for multi-state systems of any topology is presented. Here, each component is defined as a Semi-Markov stochastic process and via discrete-event simulation, the operation of the system is mimicked. The principles of flow conservation are invoked to determine flow across the system for every performance level change of its components using the interior-point algorithm. This eliminates the need for cut-set definition and overcomes the limitations of existing techniques. The methodology can also be exploited to account for effects of transmission efficiency and loading restrictions of components on system reliability and performance. The principles and algorithms developed are applied to two numerical examples to demonstrate their applicability. - Highlights: • A discrete event simulation model based on load flow principles. • Model does not require system path or cut sets. • Applicable to binary and multi-state systems of any topology. • Supports multiple output systems with competing demand. • Model is intuitive and generally applicable.

  9. A hybrid Bayesian network approach for trade-offs between environmental flows and agricultural water using dynamic discretization

    Science.gov (United States)

    Xue, Jie; Gui, Dongwei; Lei, Jiaqiang; Sun, Huaiwei; Zeng, Fanjiang; Feng, Xinlong

    2017-12-01

    Agriculture and the eco-environment are increasingly competing for water. The extension of intensive farmland for ensuring food security has resulted in excessive water exploitation by agriculture. Consequently, this has led to a lack of water supply in natural ecosystems. This paper proposes a trade-off framework to coordinate the water-use conflict between agriculture and the eco-environment, based on economic compensation for irrigation stakeholders. A hybrid Bayesian network (HBN) is developed to implement the framework, including: (a) agricultural water shortage assessments after meeting environmental flows; (b) water-use tradeoff analysis between agricultural irrigation and environmental flows using the HBN; and (c) quantification of the agricultural economic compensation for different irrigation stakeholders. The constructed HBN is computed by dynamic discretization, which is a more robust and accurate propagation algorithm than general static discretization. A case study of the Qira oasis area in Northwest China demonstrates that the water trade-off based on economic compensation depends on the available water supply and environmental flows at different levels. Agricultural irrigation water extracted for grain crops should be preferentially guaranteed to ensure food security, in spite of higher economic compensation in other cash crops' irrigation for water coordination. Updating water-saving engineering and adopting drip irrigation technology in agricultural facilities after satisfying environmental flows would greatly relieve agricultural water shortage and save the economic compensation for different irrigation stakeholders. The approach in this study can be easily applied in water-stressed areas worldwide for dealing with water competition.

  10. A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.

    Science.gov (United States)

    Beckerman, Bernardo S; Jerrett, Michael; Serre, Marc; Martin, Randall V; Lee, Seung-Jae; van Donkelaar, Aaron; Ross, Zev; Su, Jason; Burnett, Richard T

    2013-07-02

    Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 data set included 104,172 monthly observations at 1464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R(2) values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R(2) were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S.

  11. Spatial prediction of landslides using a hybrid machine learning approach based on Random Subspace and Classification and Regression Trees

    Science.gov (United States)

    Pham, Binh Thai; Prakash, Indra; Tien Bui, Dieu

    2018-02-01

    A hybrid machine learning approach of Random Subspace (RSS) and Classification And Regression Trees (CART) is proposed to develop a model named RSSCART for spatial prediction of landslides. This model is a combination of the RSS method which is known as an efficient ensemble technique and the CART which is a state of the art classifier. The Luc Yen district of Yen Bai province, a prominent landslide prone area of Viet Nam, was selected for the model development. Performance of the RSSCART model was evaluated through the Receiver Operating Characteristic (ROC) curve, statistical analysis methods, and the Chi Square test. Results were compared with other benchmark landslide models namely Support Vector Machines (SVM), single CART, Naïve Bayes Trees (NBT), and Logistic Regression (LR). In the development of model, ten important landslide affecting factors related with geomorphology, geology and geo-environment were considered namely slope angles, elevation, slope aspect, curvature, lithology, distance to faults, distance to rivers, distance to roads, and rainfall. Performance of the RSSCART model (AUC = 0.841) is the best compared with other popular landslide models namely SVM (0.835), single CART (0.822), NBT (0.821), and LR (0.723). These results indicate that performance of the RSSCART is a promising method for spatial landslide prediction.

  12. Next-generation in situ hybridization approaches to define and quantify HIV and SIV reservoirs in tissue microenvironments.

    Science.gov (United States)

    Deleage, Claire; Chan, Chi N; Busman-Sahay, Kathleen; Estes, Jacob D

    2018-01-09

    The development of increasingly safe and effective antiretroviral treatments for human immunodeficiency virus (HIV) over the past several decades has led to vastly improved patient survival when treatment is available and affordable, an outcome that relies on uninterrupted adherence to combination antiretroviral therapy for life. Looking to the future, the discovery of an elusive 'cure' for HIV will necessitate highly sensitive methods for detecting, understanding, and eliminating viral reservoirs. Next-generation, in situ hybridization (ISH) approaches offer unique and complementary insights into viral reservoirs within their native tissue environments with a high degree of specificity and sensitivity. In this review, we will discuss how modern ISH techniques can be used, either alone or in conjunction with phenotypic characterization, to probe viral reservoir establishment and maintenance. In addition to focusing on how these techniques have already furthered our understanding of HIV reservoirs, we discuss potential avenues for how high-throughput, next-generation ISH may be applied. Finally, we will review how ISH could allow deeper phenotypic and contextual insights into HIV reservoir biology that should prove instrumental in moving the field closer to viral reservoir elimination needed for an 'HIV cure' to be realized.

  13. A Hybrid Metaheuristic Approach for Minimizing the Total Flow Time in A Flow Shop Sequence Dependent Group Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Antonio Costa

    2014-07-01

    Full Text Available Production processes in Cellular Manufacturing Systems (CMS often involve groups of parts sharing the same technological requirements in terms of tooling and setup. The issue of scheduling such parts through a flow-shop production layout is known as the Flow-Shop Group Scheduling (FSGS problem or, whether setup times are sequence-dependent, the Flow-Shop Sequence-Dependent Group Scheduling (FSDGS problem. This paper addresses the FSDGS issue, proposing a hybrid metaheuristic procedure integrating features from Genetic Algorithms (GAs and Biased Random Sampling (BRS search techniques with the aim of minimizing the total flow time, i.e., the sum of completion times of all jobs. A well-known benchmark of test cases, entailing problems with two, three, and six machines, is employed for both tuning the relevant parameters of the developed procedure and assessing its performances against two metaheuristic algorithms recently presented by literature. The obtained results and a properly arranged ANOVA analysis highlight the superiority of the proposed approach in tackling the scheduling problem under investigation.

  14. Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

    Science.gov (United States)

    Kachach, Redouane; Cañas, José María

    2016-05-01

    Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

  15. Controlled Distribution and Clustering of Silver in Ag-DLC Nanocomposite Coatings Using a Hybrid Plasma Approach.

    Science.gov (United States)

    Cloutier, M; Turgeon, S; Busby, Y; Tatoulian, M; Pireaux, J-J; Mantovani, D

    2016-08-17

    Incorporation of selected metallic elements into diamond-like carbon (DLC) has emerged as an innovative approach to add unique functional properties to DLC coatings, thus opening up a range of new potential applications in fields as diverse as sensors, tribology, and biomaterials. However, deposition by plasma techniques of metal-containing DLC coatings with well-defined structural properties and metal distribution is currently hindered by the limited understanding of their growth mechanisms. We report here a silver-incorporated diamond-like carbon coating (Ag-DLC) prepared in a hybrid plasma reactor which allowed independent control of the metal content and the carbon film structure and morphology. Morphological and chemical analyses of Ag-DLC films were performed by atomic force microscopy, scanning electron microscopy, and X-ray photoelectron spectroscopy. The vertical distribution of silver from the surface toward the coating bulk was found to be highly inhomogeneous due to top surface segregation and clustering of silver nanoparticles. Two plasma parameters, the sputtered Ag flux and ion energy, were shown to influence the spatial distribution of silver particles. On the basis of these findings, a mechanism for Ag-DLC growth by plasma was proposed.

  16. A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

    Science.gov (United States)

    Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

    2015-01-01

    Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

  17. Identification and Cloning of Differentially Expressed SOUL and ELIP Genes in Saffron Stigmas Using a Subtractive Hybridization Approach.

    Directory of Open Access Journals (Sweden)

    Oussama Ahrazem

    Full Text Available Using a subtractive hybridization approach, differentially expressed genes involved in the light response in saffron stigmas were identified. Twenty-two differentially expressed transcript-derived fragments were cloned and sequenced. Two of them were highly induced by light and had sequence similarity to early inducible proteins (ELIP and SOUL heme-binding proteins. Using these sequences, we searched for other family members expressed in saffron stigma. ELIP and SOUL are represented by small gene families in saffron, with four and five members, respectively. The expression of these genes was analyzed during the development of the stigma and in light and dark conditions. ELIP transcripts were detected in all the developmental stages showing much higher expression levels in the developed stigmas of saffron and all were up-regulated by light but at different levels. By contrast, only one SOUL gene was up-regulated by light and was highly expressed in the stigma at anthesis. Both the ELIP and SOUL genes induced by light in saffron stigmas might be associated with the structural changes affecting the chromoplast of the stigma, as a result of light exposure, which promotes the development and increases the number of plastoglobules, specialized in the recruitment of specific proteins, which enables them to act in metabolite synthesis and disposal under changing environmental conditions and developmental stages.

  18. A Hybrid Chaotic and Number Theoretic Approach for Securing DICOM Images

    Directory of Open Access Journals (Sweden)

    Jeyamala Chandrasekaran

    2017-01-01

    Full Text Available The advancements in telecommunication and networking technologies have led to the increased popularity and widespread usage of telemedicine. Telemedicine involves storage and exchange of large volume of medical records for remote diagnosis and improved health care services. Images in medical records are characterized by huge volume, high redundancy, and strong correlation among adjacent pixels. This research work proposes a novel idea of integrating number theoretic approach with Henon map for secure and efficient encryption. Modular exponentiation of the primitive roots of the chosen prime in the range of its residual set is employed in the generation of two-dimensional array of keys. The key matrix is permuted and chaotically controlled by Henon map to decide the encryption keys for every pixel of DICOM image. The proposed system is highly secure because of the randomness introduced due to the application of modular exponentiation key generation and application of Henon maps for permutation of keys. Experiments have been conducted to analyze key space, key sensitivity, avalanche effect, correlation distribution, entropy, and histograms. The corresponding results confirm the strength of the proposed design towards statistical and differential crypt analysis. The computational requirements for encryption/decryption have been reduced significantly owing to the reduced number of computations in the process of encryption/decryption.

  19. Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms

    CERN Document Server

    Siddique, Nazmul

    2014-01-01

    Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of t...

  20. EMOTION AND SARCASM IDENTIFICATION OF POSTS FROM FACEBOOK DATA USING A HYBRID APPROACH

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    V M Raghavan

    2017-01-01

    Full Text Available Facebook has become the most important source of news and people’s feedback and opinion about almost every daily topic. Facebook represents one of the largest and most dynamic datasets of user generated content. Facebook posts can express opinions on different topics. With this massive amount of information in Facebook, there has to be an automatic tool that can categorize these information based on emotions. The proposed system is to develop a prototype that help to come to an inference about the emotions of the posts namely anger, surprise, happy, fear, sorrow, trust, anticipation and disgust with three sentic levels in each. This helps in better understanding of the posts when compared to the approaches which senses the polarity of the posts and gives just their sentiments i.e., positive, negative or neutral. The posts handling these emotions might be sarcastic too. When detecting sarcasm in social media posts, the various features that are especially inherent to Facebook must be considered with importance.