Toward a reliable gaze-independent hybrid BCI combining visual and natural auditory stimuli.

Science.gov (United States)

Barbosa, Sara; Pires, Gabriel; Nunes, Urbano

2016-03-01

Brain computer interfaces (BCIs) are one of the last communication options for patients in the locked-in state (LIS). For complete LIS patients, interfaces must be gaze-independent due to their eye impairment. However, unimodal gaze-independent approaches typically present levels of performance substantially lower than gaze-dependent approaches. The combination of multimodal stimuli has been pointed as a viable way to increase users' performance. A hybrid visual and auditory (HVA) P300-based BCI combining simultaneously visual and auditory stimulation is proposed. Auditory stimuli are based on natural meaningful spoken words, increasing stimuli discrimination and decreasing user's mental effort in associating stimuli to the symbols. The visual part of the interface is covertly controlled ensuring gaze-independency. Four conditions were experimentally tested by 10 healthy participants: visual overt (VO), visual covert (VC), auditory (AU) and covert HVA. Average online accuracy for the hybrid approach was 85.3%, which is more than 32% over VC and AU approaches. Questionnaires' results indicate that the HVA approach was the less demanding gaze-independent interface. Interestingly, the P300 grand average for HVA approach coincides with an almost perfect sum of P300 evoked separately by VC and AU tasks. The proposed HVA-BCI is the first solution simultaneously embedding natural spoken words and visual words to provide a communication lexicon. Online accuracy and task demand of the approach compare favorably with state-of-the-art. The proposed approach shows that the simultaneous combination of visual covert control and auditory modalities can effectively improve the performance of gaze-independent BCIs. Copyright © 2015 Elsevier B.V. All rights reserved.

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…

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.

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.

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

Combined hybrid functional and DFT+U calculations for metal chalcogenides

Energy Technology Data Exchange (ETDEWEB)

Aras, Mehmet; Kılıç, Çetin, E-mail: cetin-kilic@gyte.edu.tr [Department of Physics, Gebze Institute of Technology, Gebze, Kocaeli 41400 (Turkey)

2014-07-28

In the density-functional studies of materials with localized electronic states, the local/semilocal exchange-correlation functionals are often either combined with a Hubbard parameter U as in the LDA+U method or mixed with a fraction of exactly computed (Fock) exchange energy yielding a hybrid functional. Although some inaccuracies of the semilocal density approximations are thus fixed to a certain extent, the improvements are not sufficient to make the predictions agree with the experimental data. Here, we put forward the perspective that the hybrid functional scheme and the LDA+U method should be treated as complementary, and propose to combine the range-separated Heyd-Scuseria-Ernzerhof (HSE) hybrid functional with the Hubbard U. We thus present a variety of HSE+U calculations for a set of II-VI semiconductors, consisting of zinc and cadmium monochalcogenides, along with comparison to the experimental data. Our findings imply that an optimal value U{sup *} of the Hubbard parameter could be determined, which ensures that the HSE+U{sup *} calculation reproduces the experimental band gap. It is shown that an improved description not only of the electronic structure but also of the crystal structure and energetics is obtained by adding the U{sup *} term to the HSE functional, proving the utility of HSE+U{sup *} approach in modeling semiconductors with localized electronic states.

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.

Comparative Transcriptional Profiling of Three Super-Hybrid Rice Combinations

Directory of Open Access Journals (Sweden)

Yonggang Peng

2014-03-01

Full Text Available Utilization of heterosis has significantly increased rice yields. However, its mechanism remains unclear. In this study, comparative transcriptional profiles of three super-hybrid rice combinations, LY2163, LY2186 and LYP9, at the flowering and filling stages, were created using rice whole-genome oligonucleotide microarray. The LY2163, LY2186 and LYP9 hybrids yielded 1193, 1630 and 1046 differentially expressed genes (DGs, accounting for 3.2%, 4.4% and 2.8% of the total number of genes (36,926, respectively, after using the z-test (p < 0.01. Functional category analysis showed that the DGs in each hybrid combination were mainly classified into the carbohydrate metabolism and energy metabolism categories. Further analysis of the metabolic pathways showed that DGs were significantly enriched in the carbon fixation pathway (p < 0.01 for all three combinations. Over 80% of the DGs were located in rice quantitative trait loci (QTLs of the Gramene database, of which more than 90% were located in the yield related QTLs in all three combinations, which suggested that there was a correlation between DGs and rice heterosis. Pathway Studio analysis showed the presence of DGs in the circadian regulatory network of all three hybrid combinations, which suggested that the circadian clock had a role in rice heterosis. Our results provide information that can help to elucidate the molecular mechanism underlying rice heterosis.

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.

Process combinations for the manufacturing of metal-plastic hybrid parts

International Nuclear Information System (INIS)

Drossel, W-G; Lies, C; Albert, A; Haase, R; Müller, R; Scholz, P

2016-01-01

The usage of innovative lightweight materials and processing technologies gains importance in manifold industrial scopes. Especially for moving parts and mobility products the weight is decisively. The aerospace and automotive industries use light and high-strength materials to reduce weight and energy consumption and thereby improve the performance of their products. Composites with reinforced plastics are of particular importance. They offer a low density in combination with high specific stiffness and strength. A pure material substitution through reinforced plastics is still not economical. The approach of using hybrid metal-plastic structures with the principle of “using the right material at the right place” is a promising solution for the economical realization of lightweight structures with a high achievement potential. The article shows four innovative manufacturing possibilities for the realization of metal-plastic-hybrid parts. (paper)

A hybrid pulse combining topology utilizing the combination of modularized avalanche transistor Marx circuits, direct pulse adding, and transmission line transformer.

Science.gov (United States)

Li, Jiangtao; Zhao, Zheng; Sun, Yi; Liu, Yuhao; Ren, Ziyuan; He, Jiaxin; Cao, Hui; Zheng, Minjun

2017-03-01

Numerous applications driven by pulsed voltage require pulses to be with high amplitude, high repetitive frequency, and narrow width, which could be satisfied by utilizing avalanche transistors. The output improvement is severely limited by power capacities of transistors. Pulse combining is an effective approach to increase the output amplitude while still adopting conventional pulse generating modules. However, there are drawbacks in traditional topologies including the saturation tendency of combining efficiency and waveform oscillation. In this paper, a hybrid pulse combining topology was adopted utilizing the combination of modularized avalanche transistor Marx circuits, direct pulse adding, and transmission line transformer. The factors affecting the combining efficiency were determined including the output time synchronization of Marx circuits, and the quantity and position of magnetic cores. The numbers of the parallel modules and the stages were determined by the output characteristics of each combining method. Experimental results illustrated the ability of generating pulses with 2-14 kV amplitude, 7-11 ns width, and a maximum 10 kHz repetitive rate on a matched 50-300 Ω resistive load. The hybrid topology would be a convinced pulse combining method for similar nanosecond pulse generators based on the solid-state switches.

Joint Adaptive Modulation and Combining for Hybrid FSO/RF Systems

KAUST Repository

Rakia, Tamer

2015-11-12

In this paper, we present and analyze a new transmission scheme for hybrid FSO/RF communication system based on joint adaptive modulation and adaptive combining. Specifically, the data rate on the FSO link is adjusted in discrete manner according to the FSO link\\'s instantaneous received signal-to-noise-ratio (SNR). If the FSO link\\'s quality is too poor to maintain the target bit-error-rate, the system activates the RF link along with the FSO link. When the RF link is activated, simultaneous transmission of the same modulated data takes place on both links, where the received signals from both links are combined using maximal ratio combining scheme. In this case, the data rate of the system is adjusted according to the instantaneous combined SNRs. Novel analytical expression for the cumulative distribution function (CDF) of the received SNR for the proposed adaptive hybrid system is obtained. This CDF expression is used to study the spectral and outage performances of the proposed adaptive hybrid FSO/RF system. Numerical examples are presented to compare the performance of the proposed adaptive hybrid FSO/RF system with that of switch-over hybrid FSO/RF and FSO-only systems employing the same adaptive modulation schemes. © 2015 IEEE.

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)

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.

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.

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

An online hybrid brain-computer interface combining multiple physiological signals for webpage browse.

Science.gov (United States)

Long Chen; Zhongpeng Wang; Feng He; Jiajia Yang; Hongzhi Qi; Peng Zhou; Baikun Wan; Dong Ming

2015-08-01

The hybrid brain computer interface (hBCI) could provide higher information transfer rate than did the classical BCIs. It included more than one brain-computer or human-machine interact paradigms, such as the combination of the P300 and SSVEP paradigms. Research firstly constructed independent subsystems of three different paradigms and tested each of them with online experiments. Then we constructed a serial hybrid BCI system which combined these paradigms to achieve the functions of typing letters, moving and clicking cursor, and switching among them for the purpose of browsing webpages. Five subjects were involved in this study. They all successfully realized these functions in the online tests. The subjects could achieve an accuracy above 90% after training, which met the requirement in operating the system efficiently. The results demonstrated that it was an efficient system capable of robustness, which provided an approach for the clinic application.

Investigation of thermodynamic performances for two solar-biomass hybrid combined cycle power generation systems

International Nuclear Information System (INIS)

Liu, Qibin; Bai, Zhang; Wang, Xiaohe; Lei, Jing; Jin, Hongguang

2016-01-01

Highlights: • Two solar-biomass hybrid combined cycle power generation systems are proposed. • The characters of the two proposed systems are compared. • The on-design and off-design properties of the system are numerically investigated. • The favorable performances of thermochemical hybrid routine are validated. - Abstract: Two solar-biomass hybrid combined cycle power generation systems are proposed in this work. The first system employs the thermochemical hybrid routine, in which the biomass gasification is driven by the concentrated solar energy, and the gasified syngas as a solar fuel is utilized in a combined cycle for generating power. The second system adopts the thermal integration concept, and the solar energy is directly used to heat the compressed air in the topping Brayton cycle. The thermodynamic performances of the developed systems are investigated under the on-design and off-design conditions. The advantages of the hybrid utilization technical mode are demonstrated. The solar energy can be converted and stored into the chemical fuel by the solar-biomass gasification, with the net solar-to-fuel efficiency of 61.23% and the net solar share of 19.01% under the specific gasification temperature of 1150 K. Meanwhile, the proposed system with the solar thermochemical routine shows more favorable behaviors, the annual system overall energy efficiency and the solar-to-electric efficiency reach to 29.36% and 18.49%, while the with thermal integration concept of 28.03% and 15.13%, respectively. The comparison work introduces a promising approach for the efficient utilization of the abundant solar and biomass resources in the western China, and realizes the mitigation of CO_2 emission.

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.

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...

Individual and combined (Plus-hybrid effect of cytoplasmic male sterility and xenia on maize grain yield

Directory of Open Access Journals (Sweden)

Sofija Bozinovic

2015-06-01

Full Text Available Plus-hybrid effect refere to a combined effect of cytoplasmic male sterility (CMS and xenia in maize (Zea mays L. It could be used in commercial production by growing a mixture of 80% CMS hybrid and 20% of another fertile hybrid. The aim of this research was to examine individual and combined CMS and xenia effects on two hybrids widely grown in Serbia. Sterile and fertile versions of ZP 1 and ZP 2 hybrids (three-way; Iodent x Lancaster dents were used as females, while ZP 1, ZP 2, ZP 3, ZP 4, and ZP 5 (three-way or single cross; Iodent (BSSS x Lancaster dents were used as pollinators. All of them belong to medium maturity group. The trial was set up at one location in Serbia (Zemun Polje in 2009, 2010, and 2011. Molecular analysis of the five genotypes was done using simple sequence repeat (SSR primers. Plus-hybrid effect on grain yield ranged from -6.2% to 6.2%; on thousand kernel weight from -1.7% to 5.2%; on number of kernels per area from -1.0% to 8.0%. The poor response could be due to a use of three-way instead of single cross hybrids in S type of sterility. Modified Rogers' distance between hybrids was in the range 0.211 to 0.378 and was not relevant for the effect, which depended mostly on the sterile hybrid genotype and the fertile hybrid pollinator ability. This approach should be more suitable for female hybrids with slightly poorer performance, already being produced on a sterile base.

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)

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.

Outage Analysis of Practical FSO/RF Hybrid System With Adaptive Combining

KAUST Repository

Rakia, Tamer

2015-08-01

Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless transmission. We present and analyze a transmission scheme for the hybrid FSO/RF communication system based on adaptive combining. Specifically, only FSO link is active as long as the instantaneous signal-to-noise ratio (SNR) at the FSO receiver is above a certain threshold level. When it falls below this threshold level, the RF link is activated along with the FSO link and the signals from the two links are combined at the receiver using a dual-branch maximal ratio combiner. Novel analytical expression for the cumulative distribution function (CDF) of the received SNR for the proposed hybrid system is obtained. This CDF expression is used to study the system outage performance. Numerical examples are presented to compare the outage performance of the proposed hybrid FSO/RF system with that of the FSO-only and RF-only systems. © 1997-2012 IEEE.

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

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

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.

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.

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)

Ka-Band Waveguide Two-Way Hybrid Combiner for MMIC Amplifiers

Science.gov (United States)

Simons, Rainee N.; Chevalier, Christine T.; Wintucky, Edwin G.; Freeman, Jon C.

2010-01-01

The design, simulation, and characterization of a novel Ka-band (32.05 0.25 GHz) rectangular waveguide two-way branch-line hybrid unequal power combiner (with port impedances matched to that of a standard WR-28 waveguide) has been created to combine input signals, which are in phase and with an amplitude ratio of two. The measured return loss and isolation of the branch-line hybrid are better than 22 and 27 dB, respectively. The measured combining efficiency is 92.9 percent at the center frequency of 32.05 GHz. This circuit is efficacious in combining the unequal output power from two Ka-band GaAs pseudomorphic high electron mobility transistor (pHEMT) monolithic microwave integrated circuit (MMIC) power amplifiers (PAs) with high efficiency. The component parts include the branch-line hybrid-based power combiner and the MMIC-based PAs. A two-way branch-line hybrid is a four-port device with all ports matched; power entering port 1 is divided in phase, and into the ratio 2:1 between ports 3 and 4. No power is coupled to port 2. MMICs are a type of integrated circuit fabricated on GaAs that operates at microwave frequencies, and performs the function of signal amplification. The power combiner is designed to operate over the frequency band of 31.8 to 32.3 GHz, which is NASA's deep space frequency band. The power combiner would have an output return loss better than 20 dB. Isolation between the output port and the isolated port is greater than 25 dB. Isolation between the two input ports is greater than 25 dB. The combining efficiency would be greater than 90 percent when the ratio of the two input power levels is two. The power combiner is machined from aluminum with E-plane split-block arrangement, and has excellent reliability. The flexibility of this design allows the combiner to be customized for combining the power from MMIC PAs with an arbitrary power output ratio. In addition, it allows combining a low-power GaAs MMIC with a high-power GaN MMIC. The arbitrary

Hybrid classifiers methods of data, knowledge, and classifier combination

CERN Document Server

Wozniak, Michal

2014-01-01

This book delivers a definite and compact knowledge on how hybridization can help improving the quality of computer classification systems. In order to make readers clearly realize the knowledge of hybridization, this book primarily focuses on introducing the different levels of hybridization and illuminating what problems we will face with as dealing with such projects. In the first instance the data and knowledge incorporated in hybridization were the action points, and then a still growing up area of classifier systems known as combined classifiers was considered. This book comprises the aforementioned state-of-the-art topics and the latest research results of the author and his team from Department of Systems and Computer Networks, Wroclaw University of Technology, including as classifier based on feature space splitting, one-class classification, imbalance data, and data stream classification.

Hybrid Combined Cycles with Biomass and Waste Fired Bottoming Cycle - a Literature Study

Energy Technology Data Exchange (ETDEWEB)

Petrov, Miroslav P.

2002-02-01

Biomass is one of the main natural resources in Sweden. The present low-CO{sub 2} emission characteristics of the Swedish electricity production system (hydro and nuclear) can be retained only by expansion of biofuel applications for energy purposes. Domestic Swedish biomass resources are vast and renewable, but not infinite. They must be utilized as efficiently as possible, in order to make sure that they meet the conditions for sustainability in the future. Application of efficient power generation cycles at low costs is essential for meeting this challenge. This applies also to municipal solid waste incineration with energy extraction, which should be preferred to its dumping in landfills. Hybrid dual-fuel combined cycle units are a simple and affordable way to increase the electric efficiency of biofuel energy utilization, without big investments, uncertainties or loss of reliability arising from complicated technologies. Configurations of such power cycles are very flexible and reliable. Their potential for high electric efficiency in condensing mode, high total efficiency in combined heat and power mode and unrivalled load flexibility is explored in this project. The present report is a literature study that concentrates on certain biomass utilization technologies, in particular the design and performance of hybrid combined cycle power units of various configurations, with gas turbines and internal combustion engines as topping cycles. An overview of published literature and general development trends on the relevant topic is presented. The study is extended to encompass a short overview of biomass utilization as an energy source (focusing on Sweden), history of combined cycles development with reference especially to combined cycles with supplementary firing and coal-fired hybrid combined cycles, repowering of old steam units into hybrid ones and combined cycles for internal combustion engines. The hybrid combined cycle concept for municipal solid waste

On battery-less autonomous polygeneration microgrids: Investigation of the combined hybrid capacitors/hydrogen alternative

International Nuclear Information System (INIS)

Kyriakarakos, George; Piromalis, Dimitrios D.; Arvanitis, Konstantinos G.; Dounis, Anastasios I.; Papadakis, George

2015-01-01

Highlights: • A battery-less autonomous polygeneration microgrid is technically feasible. • Laboratory testing of hybrid capacitors. • Investigation of hybrid capacitors utilization along with hydrogen subsystem. - Abstract: The autonomous polygeneration microgrid topology aims to cover holistically the needs in remote areas as far as electrical power, potable water through desalination, fuel for transportation in the form of hydrogen, heating and cooling are concerned. Deep discharge lead acid batteries are mostly used in such systems, associated with specific disadvantages, both technical and environmental. This paper investigated the possibility of replacing the battery bank from a polygeneration microgrid with a hybrid capacitor bank and more intensive utilization of a hydrogen subsystem. Initially commercial hybrid capacitors were tested under laboratory conditions and based on the respective results a case study was performed. The optimized combination of hybrid capacitors and higher hydrogen usage was then investigated through simulations and compared to a polygeneration microgrid featuring deep discharge lead acid batteries. From the results it was clear that it is technically possible to exchange the battery bank with a hybrid capacitor bank and higher hydrogen utilization. From the economic point of view, the current cost of the hybrid capacitors and the hydrogen components is high which leads to higher overall cost in comparison with deep discharge lead acid batteries. Taking into account, though, the decreasing cost prospects and trends of both the hybrid capacitors and the hydrogen components it is expected that this approach will become economically competitive in a few years

Hybrid Fusion for Biometrics: Combining Score-level and Decision-level Fusion

NARCIS (Netherlands)

Tao, Q.; Veldhuis, Raymond N.J.

2008-01-01

A general framework of fusion at decision level, which works on ROCs instead of matching scores, is investigated. Under this framework, we further propose a hybrid fusion method, which combines the score-level and decision-level fusions, taking advantage of both fusion modes. The hybrid fusion

Weighted hybrid technique for recommender system

Science.gov (United States)

Suriati, S.; Dwiastuti, Meisyarah; Tulus, T.

2017-12-01

Recommender system becomes very popular and has important role in an information system or webpages nowadays. A recommender system tries to make a prediction of which item a user may like based on his activity on the system. There are some familiar techniques to build a recommender system, such as content-based filtering and collaborative filtering. Content-based filtering does not involve opinions from human to make the prediction, while collaborative filtering does, so collaborative filtering can predict more accurately. However, collaborative filtering cannot give prediction to items which have never been rated by any user. In order to cover the drawbacks of each approach with the advantages of other approach, both approaches can be combined with an approach known as hybrid technique. Hybrid technique used in this work is weighted technique in which the prediction score is combination linear of scores gained by techniques that are combined.The purpose of this work is to show how an approach of weighted hybrid technique combining content-based filtering and item-based collaborative filtering can work in a movie recommender system and to show the performance comparison when both approachare combined and when each approach works alone. There are three experiments done in this work, combining both techniques with different parameters. The result shows that the weighted hybrid technique that is done in this work does not really boost the performance up, but it helps to give prediction score for unrated movies that are impossible to be recommended by only using collaborative filtering.

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...

Hybrid spacecraft attitude control system

Directory of Open Access Journals (Sweden)

Renuganth Varatharajoo

2016-02-01

Full Text Available The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.

Combining ability of tomato lines in saladette-type hybrids

Directory of Open Access Journals (Sweden)

Marcela Carvalho Andrade

2014-09-01

Full Text Available Given the growing importance of the saladette fresh tomato market in Brazil, the objective of this paper was to assess the combining abilities of lines potentially useful as parents of hybridsin this class. The experiment consisted of28 genotypes, 18 hybrids from a partial diallel crossobtained from crossing two groups of tomato lines (Group I, with 9 parents, and Group II, with 2 parents, 8 F1 experimental hybrids, and 2 commercial checks. Traits evaluated were total yield, mean fruit mass, fruit shelf life, shape and percentsoluble solids. Additive genetic effects were generally more important than non-additive effects for all traits evaluated. The TOM-542 and TOM-734 lines, from group I, and the TOM-720 line, from group II, presented high general combining ability (GCA estimates for most of the traits of importance for saladette tomatoes, and were therefore considered suitable parents of hybrids of this class. Higher fruit shelf life of TOM-723 as a parental line compared with TOM-720 (Group II, was mainly attributed to the presence in the former of the norA allele, which controls longer fruit shelf life. F1 hybrids (TOM-542 x TOM-720, (TOM-580 x TOM-720, (TOM-734 x TOM-720, and (TOM-727 x TOM-720 showed good performance and fruit quality and thus constitute possible commercial varieties.

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 ...

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…

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)

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.

Hybrid simulation models of production networks

CERN Document Server

Kouikoglou, Vassilis S

2001-01-01

This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.

Design and RF test result of High Power Hybrid Combiner for Helicon Wave Current Drive in KSTAR Plasmas

Energy Technology Data Exchange (ETDEWEB)

Park, S. Y.; Kim, H. J.; Wi, H. H.; Wang, S. J.; Kwak, J. G. [NFRI, Daejeon (Korea, Republic of)

2016-05-15

200 kW RF power will be injected to plasmas through the traveling wave antenna after combining four klystrons output powers using three hybrid combiners. Each klystron produces 60 kW output at the frequency of 500 MHz. RF power combiners commonly used to divide or combine output powers for various rf and microwave applications. It is divided into several types according to the design type such as Wilkinson combiner, radial and quadrature hybrid combiner. We designed high power hybrid combiners using 6-1/8 inch coaxial line. The power combiner has many advantages such as high isolation, low insertion loss and high power handling capability. In this paper design and rf test results of high power combiners will be described. High power combiners using three coaxial hybrid couplers will be utilized for effectively combining of 500 MHz, 200 kW output powers generated by four klystrons. We have designed, fabricated, and tested a 6-1/8 inch coaxial hybrid combiners at 500 MHz for efficiently off-axis Helicon wave current drive in KSTAR. Simulation and test results of high power coaxial hybrid combiners are good agreement.

Genetic determination of high productivity in experimental hybrid combinations of sugar beet (Beta vulgaris L.

Directory of Open Access Journals (Sweden)

М. О. Корнєєва

2016-05-01

Full Text Available Purpose. Creation of experimental sugar beet hybrid combinations of high sugar yield values and defining gene­tic determination of their heterotic effect. Methods. Diallel crossing and topcrossing, genetic analysis of quantitative traits. Results. The authors have studied the frequency of occurrence of sugar beet heterotic hybrid combinations for «sugar yield» trait created on the basis of two pollinator lines to be genetically valuable for productivity elements, CMS lines and single-cross sterile hybrids with the use of diallel and topcrossing system of controlled hybridization. The share of parental components’ effect and their interaction in CMS hybrids variability for productivity was determined. Expediency of heterotic forecasting based on high combining ability lines was substabtiated. Promising high-yielding sugar beet combinations were selected that exceeded the group standard by 4.1–16.3%. Conclusions. The theory of genetic balance by M. V. Turbin was confirmed. Such hybrids as [CMS 5OT 4]MGP 1 (116.3%, [CMS 1OT 2]MGP 1 (112.5% and [CMS 3OT 5]MGP 1 (113.2% were recognized as the best for their productivity, MGP 1 and MGP 2 lines – as the best for their combining ability.

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.

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.

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.

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.

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…

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.

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

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.

Performance comparison of two low-CO2 emission solar/methanol hybrid combined cycle power systems

International Nuclear Information System (INIS)

Li, Yuanyuan; Zhang, Na; Lior, Noam

2015-01-01

Highlights: • Two novel solar hybrid combined cycle systems have been proposed and analyzed. • The power systems integrate solar-driven thermo-chemical conversion and CO 2 capture. • Exergy efficiency of about 55% and specific CO 2 emissions of 34 g/kW h are predicted. • Systems CO 2 emissions are 36.8% lower compared to a combined cycle with CO 2 capture. • The fossil fuel demand is ∼30% lower with a solar share of ∼20%. - Abstract: Two novel hybrid combined cycle power systems that use solar heat and methanol, and integrate CO 2 capture, are proposed and analyzed, one based on solar-driven methanol decomposition and the other on solar-driven methanol reforming. The high methanol conversion rates at relatively low temperatures offer the advantage of using the solar heat at only 200–300 °C to drive the syngas production by endothermic methanol conversions and its conversion to chemical energy. Pre-combustion decarbonization is employed to produce CO 2 -free fuel from the fully converted syngas, which is then burned to produce heat at the high temperature for power generation in the proposed advanced combined cycle systems. To improve efficiency, the systems’ configurations were based on the principle of cascade use of multiple heat sources of different temperatures. The thermodynamic performance of the hybrid power systems at its design point is simulated and evaluated. The results show that the hybrid systems can attain an exergy efficiency of about 55%, and specific CO 2 emissions as low as 34 g/kW h. Compared to a gas/steam combined cycle with flue gas CO 2 capture, the proposed solar-assisted system CO 2 emissions are 36.8% lower, and a fossil fuel saving ratio of ∼30% is achievable with a solar thermal share of ∼20%. The system integration predicts high efficiency conversion of solar heat and low-energy-penalty CO 2 capture, with the additional advantage that solar heat is at relatively low temperature where its collection is cheaper and

Hybrid fur rendering: combining volumetric fur with explicit hair strands

DEFF Research Database (Denmark)

Andersen, Tobias Grønbeck; Falster, Viggo; Frisvad, Jeppe Revall

2016-01-01

Hair is typically modeled and rendered using either explicitly defined hair strand geometry or a volume texture of hair densities. Taken each on their own, these two hair representations have difficulties in the case of animal fur as it consists of very dense and thin undercoat hairs in combination...... with coarse guard hairs. Explicit hair strand geometry is not well-suited for the undercoat hairs, while volume textures are not well-suited for the guard hairs. To efficiently model and render both guard hairs and undercoat hairs, we present a hybrid technique that combines rasterization of explicitly...... defined guard hairs with ray marching of a prismatic shell volume with dynamic resolution. The latter is the key to practical combination of the two techniques, and it also enables a high degree of detail in the undercoat. We demonstrate that our hybrid technique creates a more detailed and soft fur...

Hybrid reactor based on combined cavitation and ozonation: from concept to practical reality.

Science.gov (United States)

Gogate, P R; Mededovic-Thagard, S; McGuire, D; Chapas, G; Blackmon, J; Cathey, R

2014-03-01

The present work gives an in depth discussion related to the development of a hybrid advanced oxidation reactor, which can be effectively used for the treatment of various types of water. The reactor is based on the principle of intensifying degradation/disinfection using a combination of hydrodynamic cavitation, acoustic cavitation, ozone injection and electrochemical oxidation/precipitation. Theoretical studies have been presented to highlight the uniform distribution of the cavitational activity and enhanced generation of hydroxyl radicals in the cavitation zone, as well as higher turbulence in the main reactor zone. The combination of these different oxidation technologies have been shown to result in enhanced water treatment ability, which can be attributed to the enhanced generation of hydroxyl radicals, enhanced contact of ozone and contaminants, and the elimination of mass transfer resistances during electrochemical oxidation/precipitation. Compared to the use of individual approaches, the hybrid reactor is expected to intensify the treatment process by 5-20 times, depending on the application in question, which can be confirmed based on the literature illustrations. Also, the use of Ozonix® has been successfully proven while processing recycled fluids at commercial sites on over 750 oil and natural gas wells during hydraulic operations around the United States. The superiority of the hybrid process over conventional chemical treatments in terms of bacteria and scale reduction as well as increased water flowability and better chemical compatibility, which is a key requirement for oil and gas applications, has been established. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

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.

Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

KAUST Repository

Rakia, Tamer

2015-07-23

Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

KAUST Repository

Rakia, Tamer; Hong-Chuan Yang; Gebali, Fayez; Alouini, Mohamed-Slim

2015-01-01

Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

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.

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...

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

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.

Hybrid spacecraft attitude control system

OpenAIRE

Renuganth Varatharajoo; Ramly Ajir; Tamizi Ahmad

2016-01-01

The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS) consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl...

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.

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.

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.

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.

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.

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.

Combined cycle solar central receiver hybrid power system study. Final technical report. Volume II

Energy Technology Data Exchange (ETDEWEB)

None

1979-11-01

This study develops the conceptual design for a commercial-scale (nominal 100 MWe) central receiver solar/fossil fuel hybrid power system with combined cycle energy conversion. A near-term, metallic heat pipe receiver and an advanced ceramic tube receiver hybrid system are defined through parametric and market potential analyses. Comparative evaluations of the cost of power generation, the fuel displacement potential, and the technological readiness of these two systems indicate that the near-term hybrid system has better potential for commercialization by 1990. Based on the assessment of the conceptual design, major cost and performance improvements are projected for the near-term system. Constraints preventing wide-spread use were not identified. Energy storage is not required for this system and analyses show no economic advantages with energy storage provisions. It is concluded that the solar hybrid system is a cost effective alternative to conventional gas turbines and combined cycle generating plants, and has potential for intermediate-load market penetration at 15% annual fuel escalation rate. Due to their flexibility, simple solar/nonsolar interfacing, and short startup cycles, these hybrid plants have significant operating advantages. Utility company comments suggest that hybrid power systems will precede stand-alone solar plants.

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.

Hybrid Software and System Development in Practice: Waterfall, Scrum, and Beyond

DEFF Research Database (Denmark)

Kuhrmann, Marco; Diebold, Philipp; Münch, Jürgen

2017-01-01

Software and system development faces numerous challenges of rapidly changing markets. To address such challenges, companies and projects design and adopt specific development approaches by combining well-structured comprehensive methods and flexible agile practices. Yet, the number of methods...... and practices is large, and available studies argue that the actual process composition is carried out in a fairly ad-hoc manner. The present paper reports on a survey on hybrid software development approaches. We study which approaches are used in practice, how different approaches are combined, and what...... contextual factors influence the use and combination of hybrid software development approaches. Our results from 69 study participants show a variety of development approaches used and combined in practice. We show that most combinations follow a pattern in which a traditional process model serves...

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.

Combining technologies to create bioactive hybrid scaffolds for bone tissue engineering.

Science.gov (United States)

Nandakumar, Anandkumar; Barradas, Ana; de Boer, Jan; Moroni, Lorenzo; van Blitterswijk, Clemens; Habibovic, Pamela

2013-01-01

Combining technologies to engineer scaffolds that can offer physical and chemical cues to cells is an attractive approach in tissue engineering and regenerative medicine. In this study, we have fabricated polymer-ceramic hybrid scaffolds for bone regeneration by combining rapid prototyping (RP), electrospinning (ESP) and a biomimetic coating method in order to provide mechanical support and a physico-chemical environment mimicking both the organic and inorganic phases of bone extracellular matrix (ECM). Poly(ethylene oxide terephthalate)-poly(buthylene terephthalate) (PEOT/PBT) block copolymer was used to produce three dimensional scaffolds by combining 3D fiber (3DF) deposition, and ESP, and these constructs were then coated with a Ca-P layer in a simulated physiological solution. Scaffold morphology and composition were studied using scanning electron microscopy (SEM) coupled to energy dispersive X-ray analyzer (EDX) and Fourier Tranform Infrared Spectroscopy (FTIR). Bone marrow derived human mesenchymal stromal cells (hMSCs) were cultured on coated and uncoated 3DF and 3DF + ESP scaffolds for up to 21 d in basic and mineralization medium and cell attachment, proliferation, and expression of genes related to osteogenesis were assessed. Cells attached, proliferated and secreted ECM on all the scaffolds. There were no significant differences in metabolic activity among the different groups on days 7 and 21. Coated 3DF scaffolds showed a significantly higher DNA amount in basic medium at 21 d compared with the coated 3DF + ESP scaffolds, whereas in mineralization medium, the presence of coating in 3DF+ESP scaffolds led to a significant decrease in the amount of DNA. An effect of combining different scaffolding technologies and material types on expression of a number of osteogenic markers (cbfa1, BMP-2, OP, OC and ON) was observed, suggesting the potential use of this approach in bone tissue engineering.

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.

Combining Performance and Flexibility for RMS with a Hybrid Architecture

NARCIS (Netherlands)

Dennis Koole; Arjan Groenewegen; Daniël Telgen; Patrick Wit; Leo van Moergestel; Arjan van Zanten; John-Jules Meyer; Ing. Erik Puik; Dick van der Steen; Pascal Muller

2013-01-01

Author supplied Combining Performance and Flexibility for RMS with a Hybrid Architecture Dani¨el Telgen 12? , Leo van Moergestel 1 , Erik Puik 1 , Pascal Muller 1 , Arjan Groenewegen 1 , Dick van der Steen 1 , Dennis Koole 1 , Patrick de Wit 1 , Arjen van Zanten 1 , and John-Jules

“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.

A Hybrid Vector Quantization Combining a Tree Structure and a Voronoi Diagram

Directory of Open Access Journals (Sweden)

Yeou-Jiunn Chen

2014-01-01

Full Text Available Multimedia data is a popular communication medium, but requires substantial storage space and network bandwidth. Vector quantization (VQ is suitable for multimedia data applications because of its simple architecture, fast decoding ability, and high compression rate. Full-search VQ can typically be used to determine optimal codewords, but requires considerable computational time and resources. In this study, a hybrid VQ combining a tree structure and a Voronoi diagram is proposed to improve VQ efficiency. To efficiently reduce the search space, a tree structure integrated with principal component analysis is proposed, to rapidly determine an initial codeword in low-dimensional space. To increase accuracy, a Voronoi diagram is applied to precisely enlarge the search space by modeling relations between each codeword. This enables an optimal codeword to be efficiently identified by rippling an optimal neighbor from parts of neighboring Voronoi regions. The experimental results demonstrated that the proposed approach improved VQ performance, outperforming other approaches. The proposed approach also satisfies the requirements of handheld device application, namely, the use of limited memory and network bandwidth, when a suitable number of dimensions in principal component analysis is selected.

Hybrid Doping of Few-Layer Graphene via a Combination of Intercalation and Surface Doping

KAUST Repository

Mansour, Ahmed

2017-05-23

Surface molecular doping of graphene has been shown to modify its work function and increase its conductivity. However, the associated shifts in work function and increases in carrier concentration are highly coupled and limited by the surface coverage of dopant molecules on graphene. Here we show that few-layer graphene (FLG) can be doped using a hybrid approach, effectively combining surface doping by larger (metal-)organic molecules, while smaller molecules, such as Br2 and FeCl3, intercalate into the bulk. Intercalation tunes the carrier concentration more effectively, whereas surface doping of intercalated FLG can be used to tune its work function without reducing the carrier mobility. This multi-modal doping approach yields a very high carrier density and tunable work function for FLG, demonstrating a new versatile platform for fabricating graphene-based contacts for electronic, optoelectronic and photovoltaic applications.

Hybrid Doping of Few-Layer Graphene via a Combination of Intercalation and Surface Doping

KAUST Repository

Mansour, Ahmed; Kirmani, Ahmad R.; Barlow, Stephen; Marder, Seth R.; Amassian, Aram

2017-01-01

Surface molecular doping of graphene has been shown to modify its work function and increase its conductivity. However, the associated shifts in work function and increases in carrier concentration are highly coupled and limited by the surface coverage of dopant molecules on graphene. Here we show that few-layer graphene (FLG) can be doped using a hybrid approach, effectively combining surface doping by larger (metal-)organic molecules, while smaller molecules, such as Br2 and FeCl3, intercalate into the bulk. Intercalation tunes the carrier concentration more effectively, whereas surface doping of intercalated FLG can be used to tune its work function without reducing the carrier mobility. This multi-modal doping approach yields a very high carrier density and tunable work function for FLG, demonstrating a new versatile platform for fabricating graphene-based contacts for electronic, optoelectronic and photovoltaic applications.

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.

Combined amplification and hybridization techniques for genome scanning in vegetatively propagated crops

International Nuclear Information System (INIS)

Kahl, G.; Ramser, J.; Terauchi, R.; Lopez-Peralta, C.; Asemota, H.N.; Weising, K.

1998-01-01

A combination of PCR- and hybridization-based genome scanning techniques and sequence comparisons between non-coding chloroplast DNA flanking tRNA genes has been employed to screen Dioscorea species for intra- and interspecific genetic diversity. This methodology detected extensive polymorphisms within Dioscorea bulbifera L., and revealed taxonomic and phylogenetic relationships among cultivated Guinea yams varieties and their potential wild progenitors. Finally, screening of yam germplasm grown in Jamaica permitted reliable discrimination between all major cultivars. Genome scanning by micro satellite-primed PCR (MP-PCR) and random amplified polymorphic DNA (RAPD) analysis in combination with the novel random amplified micro satellite polymorphisms (RAMPO) hybridization technique has shown high potential for the genetic analysis of yams, and holds promise for other vegetatively propagated orphan crops. (author)

Monitoring hemodynamics and oxygenation of the kidney in rats by a combined near-infrared spectroscopy and invasive probe approach

Science.gov (United States)

Grosenick, Dirk; Cantow, Kathleen; Arakelyan, Karen; Wabnitz, Heidrun; Flemming, Bert; Skalweit, Angela; Ladwig, Mechthild; Macdonald, Rainer; Niendorf, Thoralf; Seeliger, Erdmann

2015-07-01

We have developed a hybrid approach to investigate the dynamics of perfusion and oxygenation in the kidney of rats under pathophysiologically relevant conditions. Our approach combines near-infrared spectroscopy to quantify hemoglobin concentration and oxygen saturation in the renal cortex, and an invasive probe method for measuring total renal blood flow by an ultrasonic probe, perfusion by laser-Doppler fluxmetry, and tissue oxygen tension via fluorescence quenching. Hemoglobin concentration and oxygen saturation were determined from experimental data by a Monte Carlo model. The hybrid approach was applied to investigate and compare temporal changes during several types of interventions such as arterial and venous occlusions, as well as hyperoxia, hypoxia and hypercapnia induced by different mixtures of the inspired gas. The approach was also applied to study the effects of the x-ray contrast medium iodixanol on the kidney.

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.

Achieving a hybrid brain-computer interface with tactile selective attention and motor imagery

Science.gov (United States)

Ahn, Sangtae; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan

2014-12-01

Objective. We propose a new hybrid brain-computer interface (BCI) system that integrates two different EEG tasks: tactile selective attention (TSA) using a vibro-tactile stimulator on the left/right finger and motor imagery (MI) of left/right hand movement. Event-related desynchronization (ERD) from the MI task and steady-state somatosensory evoked potential (SSSEP) from the TSA task are retrieved and combined into two hybrid senses. Approach. One hybrid approach is to measure two tasks simultaneously; the features of each task are combined for testing. Another hybrid approach is to measure two tasks consecutively (TSA first and MI next) using only MI features. For comparison with the hybrid approaches, the TSA and MI tasks are measured independently. Main results. Using a total of 16 subject datasets, we analyzed the BCI classification performance for MI, TSA and two hybrid approaches in a comparative manner; we found that the consecutive hybrid approach outperformed the others, yielding about a 10% improvement in classification accuracy relative to MI alone. It is understood that TSA may play a crucial role as a prestimulus in that it helps to generate earlier ERD prior to MI and thus sustains ERD longer and to a stronger degree; this ERD may give more discriminative information than ERD in MI alone. Significance. Overall, our proposed consecutive hybrid approach is very promising for the development of advanced BCI systems.

Single and combined fault diagnosis of reciprocating compressor valves using a hybrid deep belief network

NARCIS (Netherlands)

Tran, Van Tung; Thobiani, Faisal Al; Tinga, Tiedo; Ball, Andrew David; Niu, Gang

2017-01-01

In this paper, a hybrid deep belief network is proposed to diagnose single and combined faults of suction and discharge valves in a reciprocating compressor. This hybrid integrates the deep belief network structured by multiple stacked restricted Boltzmann machines for pre-training and simplified

Effects of agroecological conditions and hybrid combinations on maize seed germination

OpenAIRE

Tabaković, M.; Glamočlija, Đ.; Jovanović, S.; Popović, V.; Simić, D.; Anđelković, S.

2013-01-01

Germination energy and seed germination of four maize combinations cultivated under different growing conditions were observed. Analysis of hybrid seed of four commercial combinations derived at the Maize Research Institute, Zemun Polje, grown in three locations, were done on the working sample of 4 x 100 seeds under laboratory conditions. The experimental data was processed for the mean and total variability (X and C.V.) for both seed traits and for each t...

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.

OPTIMISATION OF BUFFER SIZE FOR ENHANCING QOS OF VIDEO TRAFFIC USING CROSS LAYERED HYBRID TRANSPORT LAYER PROTOCOL APPROACH

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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.

Cardiac surgery or interventional cardiology? Why not both? Let's go hybrid.

Science.gov (United States)

Papakonstantinou, Nikolaos A; Baikoussis, Nikolaos G; Dedeilias, Panagiotis; Argiriou, Michalis; Charitos, Christos

2017-01-01

A hybrid strategy, firstly performed in the 1990s, is a combination of tools available only in the catheterization laboratory with those available only in the operating room in order to minimize surgical morbidity and face with any cardiovascular lesion. The continuous evolution of stent technology along with the adoption of minimally invasive surgical approaches, make hybrid approaches an attractive alternative to standard surgical or transcatheter techniques for any given set of cardiovascular lesions. Examples include hybrid coronary revascularization, when an open surgical anastomosis of the left internal mammary artery to the left anterior descending coronary artery is performed along with stent implantation in non-left anterior descending coronary vessels, open heart valve surgery combined with percutaneous coronary interventions to coronary lesions, hybrid aortic arch debranching combined with endovascular grafting for thoracic aortic aneurysms, hybrid endocardial and epicardial atrial fibrillation procedures, and carotid artery stenting along with coronary artery bypass grafting. The cornerstone of success for all of these methods is the productive collaboration between cardiac surgeons and interventional cardiologists. The indications and patient selection of these procedures are still to be defined. However, high-risk patients have already been shown to benefit from hybrid approaches. Copyright © 2016 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Combined amplification and hybridization techniques for genome scanning in vegetatively propagated crops

Energy Technology Data Exchange (ETDEWEB)

Kahl, G; Ramser, J; Terauchi, R [Biocentre, University of Frankfurt, Frankfurt am Main (Germany); Lopez-Peralta, C [IRGP, Colegio de Postgraduados, Montecillo, Edo. de Mexico, Texcoco (Mexico); Asemota, H N [Biotechnology Centre, University of the West Indies, Mona, Kingston (Jamaica); Weising, K [School of Biological Sciences, University of Auckland, Auckland (New Zealand)

1998-10-01

A combination of PCR- and hybridization-based genome scanning techniques and sequence comparisons between non-coding chloroplast DNA flanking tRNA genes has been employed to screen Dioscorea species for intra- and interspecific genetic diversity. This methodology detected extensive polymorphisms within Dioscorea bulbifera L., and revealed taxonomic and phylogenetic relationships among cultivated Guinea yams varieties and their potential wild progenitors. Finally, screening of yam germplasm grown in Jamaica permitted reliable discrimination between all major cultivars. Genome scanning by micro satellite-primed PCR (MP-PCR) and random amplified polymorphic DNA (RAPD) analysis in combination with the novel random amplified micro satellite polymorphisms (RAMPO) hybridization technique has shown high potential for the genetic analysis of yams, and holds promise for other vegetatively propagated orphan crops. (author) 46 refs, 3 figs, 3 tabs

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.

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.

A study on application of the combination of hybridization with γ-radiation in wheat breeding

International Nuclear Information System (INIS)

Wang Jinxiang

1989-11-01

F 0 and F 1 dry seeds of winter wheat were irradiated by 60 Co γ-rays. The biological effects of M 1 , variation frequency and useful types of M 2 were investigated. Percentages of the selectivities of M 2 , M 3 and M 4 were also evaluated. The results showed that the seeds treated by combining hybridization with γ-radiation could increase variation frequency by 6∼44%, useful types by 13∼34%, and percentages of the selectivities by 6∼70%, as compared with the seeds treated only by the hybridization. Thus, the strains with high yield and protein were selected. It indicates that to combine the hybridization with γ-radiation is one of the ways for raising efficiency of wheat breeding

Graphene-based hybrid structures combined with functional materials of ferroelectrics and semiconductors.

Science.gov (United States)

Jie, Wenjing; Hao, Jianhua

2014-06-21

Fundamental studies and applications of 2-dimensional (2D) graphene may be deepened and broadened via combining graphene sheets with various functional materials, which have been extended from the traditional insulator of SiO2 to a versatile range of dielectrics, semiconductors and metals, as well as organic compounds. Among them, ferroelectric materials have received much attention due to their unique ferroelectric polarization. As a result, many attractive characteristics can be shown in graphene/ferroelectric hybrid systems. On the other hand, graphene can be integrated with conventional semiconductors and some newly-discovered 2D layered materials to form distinct Schottky junctions, yielding fascinating behaviours and exhibiting the potential for various applications in future functional devices. This review article is an attempt to illustrate the most recent progress in the fabrication, operation principle, characterization, and promising applications of graphene-based hybrid structures combined with various functional materials, ranging from ferroelectrics to semiconductors. We focus on mechanically exfoliated and chemical-vapor-deposited graphene sheets integrated in numerous advanced devices. Some typical hybrid structures have been highlighted, aiming at potential applications in non-volatile memories, transparent flexible electrodes, solar cells, photodetectors, and so on.

Hybrid solar central receiver for combined cycle power plant

Science.gov (United States)

Bharathan, Desikan; Bohn, Mark S.; Williams, Thomas A.

1995-01-01

A hybrid combined cycle power plant including a solar central receiver for receiving solar radiation and converting it to thermal energy. The power plant includes a molten salt heat transfer medium for transferring the thermal energy to an air heater. The air heater uses the thermal energy to preheat the air from the compressor of the gas cycle. The exhaust gases from the gas cycle are directed to a steam turbine for additional energy production.

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.

Maize forage aptitude: Combining ability of inbred lines and stability of hybrids

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Luis Máximo Bertoia

2014-12-01

Full Text Available Breeding of forage maize should combine improvement achieved for grain with the specific needs of forage hybrids. Production stability is important when maize is used for silage if the planting area is not in the ideal agronomic environment. The objectives of the present research were: (i to quantify environmental and genetic and their interaction effects on maize silage traits; (ii to identify possible heterotic groups for forage aptitude and suggest the formation of potential heterotic patterns, and (iii to identify suitable inbred line combinations for producing hybrids with forage aptitude. Forty-five hybrids derived from diallelic crosses (without reciprocals among ten inbred lines of maize were evaluated in this study. Combined ANOVA over environments showed differences between genotypes (G, environments (E, and their interactions (GEI. Heritability (H2, and genotypic and phenotypic correlations were estimated to evaluate the variation in and relationships between forage traits. Postdictive and predictive AMMI models were fitted to determine the importance of each source of variation, G, E, and GEI, and to select genotypes simultaneously on yield, quality and stability. A predominance of additive effects was found in the evaluated traits. The heterotic pattern Reid-BSSS × Argentine flint was confirmed for ear yield (EY and harvest index (HI. High and broad genetic variation was found for stover and whole plant traits. Some inbred lines had genes with differential breeding aptitude for ear and stover. Stover and ear yield should be the main breeding objectives in maize forage breeding.

Combining motor imagery with selective sensation toward a hybrid-modality BCI.

Science.gov (United States)

Yao, Lin; Meng, Jianjun; Zhang, Dingguo; Sheng, Xinjun; Zhu, Xiangyang

2014-08-01

A hybrid modality brain-computer interface (BCI) is proposed in this paper, which combines motor imagery with selective sensation to enhance the discrimination between left and right mental tasks, e.g., the classification between left/ right stimulation sensation and right/ left motor imagery. In this paradigm, wearable vibrotactile rings are used to stimulate both the skin on both wrists. Subjects are required to perform the mental tasks according to the randomly presented cues (i.e., left hand motor imagery, right hand motor imagery, left stimulation sensation or right stimulation sensation). Two-way ANOVA statistical analysis showed a significant group effect (F (2,20) = 7.17, p = 0.0045), and the Benferroni-corrected multiple comparison test (with α = 0.05) showed that the hybrid modality group is 11.13% higher on average than the motor imagery group, and 10.45% higher than the selective sensation group. The hybrid modality experiment exhibits potentially wider spread usage within ten subjects crossed 70% accuracy, followed by four subjects in motor imagery and five subjects in selective sensation. Six subjects showed statistically significant improvement ( Benferroni-corrected) in hybrid modality in comparison with both motor imagery and selective sensation. Furthermore, among subjects having difficulties in both motor imagery and selective sensation, the hybrid modality improves their performance to 90% accuracy. The proposed hybrid modality BCI has demonstrated clear benefits for those poorly performing BCI users. Not only does the requirement of motor and sensory anticipation in this hybrid modality provide basic function of BCI for communication and control, it also has the potential for enhancing the rehabilitation during motor recovery.

"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

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, am...

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.

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

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

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.

Hybridization and genome evolution I: The role of contingency during hybrid speciation

Directory of Open Access Journals (Sweden)

Fabrice EROUKHMANOFF, Richard I. BAILEY, Glenn-Peter SæTRE

2013-10-01

Full Text Available Homoploid hybrid speciation (HHS involves the recombination of two differentiated genomes into a novel, functional one without a change in chromosome number. Theoretically, there are numerous ways for two parental genomes to recombine. Hence, chance may play a large role in the formation of a hybrid species. If these genome combinations can evolve rapidly following hybridization and sympatric situations are numerous, recurrent homoploid hybrid speciation is a possibility. We argue that three different, but not mutually exclusive, types of contingencies could influence this process. First, many of these “hopeful monsters” of recombinant parent genotypes would likely have low fitness. Only specific combinations of parental genomic contributions may produce viable, intra-fertile hybrid species able to accommodate potential constraints arising from intragenomic conflict. Second, ecological conditions (competition, geography of the contact zones or the initial frequency of both parent species might favor different outcomes ranging from sympatric coexistence to the formation of hybrid swarms and ultimately hybrid speciation. Finally, history may also play an important role in promoting or constraining recurrent HHS if multiple hybridization events occur sequentially and parental divergence or isolation differs along this continuum. We discuss under which conditions HHS may occur multiple times in parallel and to what extent recombination and selection may fuse the parent genomes in the same or different ways. We conclude by examining different approaches that might help to solve this intriguing evolutionary puzzle [Current Zoology 59 (5: 667-674, 2013].　

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%

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

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

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.

Simulation of dose deposition in stereotactic synchrotron radiation therapy: a fast approach combining Monte Carlo and deterministic algorithms

Energy Technology Data Exchange (ETDEWEB)

Smekens, F; Freud, N; Letang, J M; Babot, D [CNDRI (Nondestructive Testing using Ionizing Radiations) Laboratory, INSA-Lyon, 69621 Villeurbanne Cedex (France); Adam, J-F; Elleaume, H; Esteve, F [INSERM U-836, Equipe 6 ' Rayonnement Synchrotron et Recherche Medicale' , Institut des Neurosciences de Grenoble (France); Ferrero, C; Bravin, A [European Synchrotron Radiation Facility, Grenoble (France)], E-mail: francois.smekens@insa-lyon.fr

2009-08-07

A hybrid approach, combining deterministic and Monte Carlo (MC) calculations, is proposed to compute the distribution of dose deposited during stereotactic synchrotron radiation therapy treatment. The proposed approach divides the computation into two parts: (i) the dose deposited by primary radiation (coming directly from the incident x-ray beam) is calculated in a deterministic way using ray casting techniques and energy-absorption coefficient tables and (ii) the dose deposited by secondary radiation (Rayleigh and Compton scattering, fluorescence) is computed using a hybrid algorithm combining MC and deterministic calculations. In the MC part, a small number of particle histories are simulated. Every time a scattering or fluorescence event takes place, a splitting mechanism is applied, so that multiple secondary photons are generated with a reduced weight. The secondary events are further processed in a deterministic way, using ray casting techniques. The whole simulation, carried out within the framework of the Monte Carlo code Geant4, is shown to converge towards the same results as the full MC simulation. The speed of convergence is found to depend notably on the splitting multiplicity, which can easily be optimized. To assess the performance of the proposed algorithm, we compare it to state-of-the-art MC simulations, accelerated by the track length estimator technique (TLE), considering a clinically realistic test case. It is found that the hybrid approach is significantly faster than the MC/TLE method. The gain in speed in a test case was about 25 for a constant precision. Therefore, this method appears to be suitable for treatment planning applications.

A hybrid mammalian cell cycle model

Directory of Open Access Journals (Sweden)

Vincent Noël

2013-08-01

Full Text Available Hybrid modeling provides an effective solution to cope with multiple time scales dynamics in systems biology. Among the applications of this method, one of the most important is the cell cycle regulation. The machinery of the cell cycle, leading to cell division and proliferation, combines slow growth, spatio-temporal re-organisation of the cell, and rapid changes of regulatory proteins concentrations induced by post-translational modifications. The advancement through the cell cycle comprises a well defined sequence of stages, separated by checkpoint transitions. The combination of continuous and discrete changes justifies hybrid modelling approaches to cell cycle dynamics. We present a piecewise-smooth version of a mammalian cell cycle model, obtained by hybridization from a smooth biochemical model. The approximate hybridization scheme, leading to simplified reaction rates and binary event location functions, is based on learning from a training set of trajectories of the smooth model. We discuss several learning strategies for the parameters of the hybrid model.

Genomic Prediction of Barley Hybrid Performance

Directory of Open Access Journals (Sweden)

Norman Philipp

2016-07-01

Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

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.

Cardiac hybrid imaging

Energy Technology Data Exchange (ETDEWEB)

Gaemperli, Oliver [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); University Hospital Zurich, Nuclear Cardiology, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland)

2014-05-15

Hybrid cardiac single photon emission computed tomography (SPECT)/CT imaging allows combined assessment of anatomical and functional aspects of cardiac disease. In coronary artery disease (CAD), hybrid SPECT/CT imaging allows detection of coronary artery stenosis and myocardial perfusion abnormalities. The clinical value of hybrid imaging has been documented in several subsets of patients. In selected groups of patients, hybrid imaging improves the diagnostic accuracy to detect CAD compared to the single imaging techniques. Additionally, this approach facilitates functional interrogation of coronary stenoses and guidance with regard to revascularization procedures. Moreover, the anatomical information obtained from CT coronary angiography or coronary artery calcium scores (CACS) adds prognostic information over perfusion data from SPECT. The use of cardiac hybrid imaging has been favoured by the dissemination of dedicated hybrid systems and the release of dedicated image fusion software, which allow simple patient throughput for hybrid SPECT/CT studies. Further technological improvements such as more efficient detector technology to allow for low-radiation protocols, ultra-fast image acquisition and improved low-noise image reconstruction algorithms will be instrumental to further promote hybrid SPECT/CT in research and clinical practice. (orig.)

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

Combined cycle solar central receiver hybrid power system study. Volume III. Appendices. Final technical report

Energy Technology Data Exchange (ETDEWEB)

None

1979-11-01

A design study for a 100 MW gas turbine/steam turbine combined cycle solar/fossil-fuel hybrid power plant is presented. This volume contains the appendices: (a) preconceptual design data; (b) market potential analysis methodology; (c) parametric analysis methodology; (d) EPGS systems description; (e) commercial-scale solar hybrid power system assessment; and (f) conceptual design data lists. (WHK)

A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

Science.gov (United States)

Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

2013-01-01

In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800

Hybrid Neuroprosthesis for the Upper Limb: Combining Brain-Controlled Neuromuscular Stimulation with a Multi-Joint Arm Exoskeleton.

Science.gov (United States)

Grimm, Florian; Walter, Armin; Spüler, Martin; Naros, Georgios; Rosenstiel, Wolfgang; Gharabaghi, Alireza

2016-01-01

Brain-machine interface-controlled (BMI) neurofeedback training aims to modulate cortical physiology and is applied during neurorehabilitation to increase the responsiveness of the brain to subsequent physiotherapy. In a parallel line of research, robotic exoskeletons are used in goal-oriented rehabilitation exercises for patients with severe motor impairment to extend their range of motion (ROM) and the intensity of training. Furthermore, neuromuscular electrical stimulation (NMES) is applied in neurologically impaired patients to restore muscle strength by closing the sensorimotor loop. In this proof-of-principle study, we explored an integrated approach for providing assistance as needed to amplify the task-related ROM and the movement-related brain modulation during rehabilitation exercises of severely impaired patients. For this purpose, we combined these three approaches (BMI, NMES, and exoskeleton) in an integrated neuroprosthesis and studied the feasibility of this device in seven severely affected chronic stroke patients who performed wrist flexion and extension exercises while receiving feedback via a virtual environment. They were assisted by a gravity-compensating, seven degree-of-freedom exoskeleton which was attached to the paretic arm. NMES was applied to the wrist extensor and flexor muscles during the exercises and was controlled by a hybrid BMI based on both sensorimotor cortical desynchronization (ERD) and electromyography (EMG) activity. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. The hybrid BMI controlled the stimulation significantly better than the offline analyzed ERD (p = 0.028) or EMG (p = 0.021) modality alone. Neuromuscular stimulation could be well integrated into the exoskeleton-based training and amplified both the task-related ROM (p = 0.009) and the movement-related brain modulation (p = 0.019). Combining a hybrid BMI with neuromuscular stimulation

Hybrid Neuroprosthesis for the Upper Limb: Combining Brain-Controlled Neuromuscular Stimulation with a Multi-Joint Arm Exoskeleton

Science.gov (United States)

Grimm, Florian; Walter, Armin; Spüler, Martin; Naros, Georgios; Rosenstiel, Wolfgang; Gharabaghi, Alireza

2016-01-01

Brain-machine interface-controlled (BMI) neurofeedback training aims to modulate cortical physiology and is applied during neurorehabilitation to increase the responsiveness of the brain to subsequent physiotherapy. In a parallel line of research, robotic exoskeletons are used in goal-oriented rehabilitation exercises for patients with severe motor impairment to extend their range of motion (ROM) and the intensity of training. Furthermore, neuromuscular electrical stimulation (NMES) is applied in neurologically impaired patients to restore muscle strength by closing the sensorimotor loop. In this proof-of-principle study, we explored an integrated approach for providing assistance as needed to amplify the task-related ROM and the movement-related brain modulation during rehabilitation exercises of severely impaired patients. For this purpose, we combined these three approaches (BMI, NMES, and exoskeleton) in an integrated neuroprosthesis and studied the feasibility of this device in seven severely affected chronic stroke patients who performed wrist flexion and extension exercises while receiving feedback via a virtual environment. They were assisted by a gravity-compensating, seven degree-of-freedom exoskeleton which was attached to the paretic arm. NMES was applied to the wrist extensor and flexor muscles during the exercises and was controlled by a hybrid BMI based on both sensorimotor cortical desynchronization (ERD) and electromyography (EMG) activity. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. The hybrid BMI controlled the stimulation significantly better than the offline analyzed ERD (p = 0.028) or EMG (p = 0.021) modality alone. Neuromuscular stimulation could be well integrated into the exoskeleton-based training and amplified both the task-related ROM (p = 0.009) and the movement-related brain modulation (p = 0.019). Combining a hybrid BMI with neuromuscular stimulation

Hybrid neuroprosthesis for the upper limb: combining brain-controlled neuromuscular stimulation with a multi-joint arm exoskeleton

Directory of Open Access Journals (Sweden)

Florian Grimm

2016-08-01

Full Text Available Brain-machine interface-controlled (BMI neurofeedback training aims to modulate cortical physiology and is applied during neurorehabilitation to increase the responsiveness of the brain to subsequent physiotherapy. In a parallel line of research, robotic exoskeletons are used in goal-oriented rehabilitation exercises for patients with severe motor impairment to extend their range of motion and the intensity of training. Furthermore, neuromuscular electrical stimulation (NMES is applied in neurologically impaired patients to restore muscle strength by closing the sensorimotor loop. In this proof-of-principle study, we explored an integrated approach for providing assistance as needed to amplify the task-related range of motion and the movement-related brain modulation during rehabilitation exercises of severely impaired patients. For this purpose, we combined these three approaches (BMI, NMES, and exoskeleton in an integrated neuroprosthesis and studied the feasibility of this device in seven severely affected chronic stroke patients who performed wrist flexion and extension exercises while receiving feedback via a virtual environment. They were assisted by a gravity-compensating, seven degree-of-freedom exoskeleton which was attached to the paretic arm. Neuromuscular electrical stimulation was applied to the wrist extensor and flexor muscles during the exercises and was controlled by a hybrid BMI based on both sensorimotor cortical desynchronization (ERD and electromyography (EMG activity. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e. induced no overt support. The hybrid BMI controlled the stimulation significantly better than the offline analyzed ERD (p=0.028 or EMG (p=0.021 modality alone. Neuromuscular stimulation could be well integrated into the exoskeleton-based training and amplified both the task-related range of motion (p=0.009 and the movement-related brain modulation (p=0

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

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.

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.

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.

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.

Design Procedure for Hybrid Ventilation

DEFF Research Database (Denmark)

Heiselberg, Per; Tjelflaat, Per Olaf

Mechanical and natural ventilation systems have developed separately during many years. The natural next step in this development is development of ventilation concepts that utilises and combines the best features from each system into a new type of ventilation system - Hybrid Ventilation....... Buildings with hybrid ventilation often include other sustainable technologies and an energy optimisation requires an integrated approach in the design of the building and its mechanical systems. Therefore, the hybrid ventilation design procedure differs from the design procedure for conventional HVAC....... The first ideas on a design procedure for hybrid ventilation is presented and the different types of design methods, that is needed in different phases of the design process, is discussed....

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.

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.

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.

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.

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.

Description of the Charge Transfer States at the Pentacene/C60 Interface: Combining Range-Separated Hybrid Functionals with the Polarizable Continuum Model

KAUST Repository

Zheng, Zilong

2016-06-24

Density functional theory (DFT) approaches based on range-separated hybrid functionals are currently methods of choice for the description of the charge-transfer (CT) states in organic donor/acceptor solar cells. However, these calculations are usually performed on small-size donor/acceptor complexes and as result do not account for electronic polarization effects. Here, using a pentacene/C60 complex as a model system, we discuss the ability of long-range corrected (LCR) hybrid functionals in combination with the polarizable continuum model (PCM) to determine the impact of the solid-state environment on the CT states. The CT energies are found to be insensitive to the interactions with the dielectric medium when a conventional time-dependent DFT/PCM (TDDFT/PCM) approach is used. However, a decrease in the energy of the CT state in the framework of LRC functionals can be obtained by using a smaller range-separated parameter when going from an isolated donor/acceptor complex to the solid-state case.

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.

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

Studies on combining ability and heritability of milling and physical properties in indica hybrid rice

International Nuclear Information System (INIS)

Zhang Lihua; Wang Linyou; Wang Jianjun

2003-01-01

14 different qualities parents of indica hybrid rice, including 7 CMS lines and 7 restorers, were chosen to analyze the combining ability of milling property and physical property by way of p x q incomplete diallel cross (NC II) design. The results showed that: 1) Both general combining ability (gca) and specific combining ability (sca) were highly significant in all 12 characters; the genetic additive effects was principal in brown rice length (BRL), brown rice width (BRW), ratio of length to width of brown rice (RLWBR), milled rice length (MRL), milled rice width (MRW), ratio of length to width of milled rice (RLWMR) and chalkyness (CN); while the nonadditive effects were greater in brown rice rate (BRR), milled rice rate (MRR), head rice rate (HRR), chalky rice percentage (CRP) and area of chalky rice (ACR). 2) Through the analysis of the contribution ratio of the male, female and their interaction to the total variance of the quality characters in F 1 hybrids, the results showed that BRR, MRR, BRL, MRL and ACR were influenced more greatly by restorer line than by CMS line, but the others were influenced more greatly by CMS line than by restorer line. 3) The gca and sca effects were independent each other, which suggests that it is essential to make widely testcrosses in the selection of hybrid combinations. There existed a positive correlation between gca and phenotypic value of parents, which indicates that great attention must be paid to the improvement of parent own characters in hybrid rice breeding. 4) BRL, BRW, RLWBR, MRL, MRW and RLWMR had higher narrow heritabilities (h N 2 ), and these characters may be used as indirect traits in early breeding generation

Breeding of early restorer Fuhui 306 and predominant performance of F1 hybrid combinations

International Nuclear Information System (INIS)

Wu Wanyi; Liu Yongqiang; Wu Maoli; Xue Xingqiong

2004-01-01

Fuhui 306, an early rice restorer with strong restoring ability, short growth period (86 days) and no restriction of separating areas in seed production, was bred by radiation treatment. F 1 hybrid combinations with different mature period were developed when cross with different sterile lines, that combination would be widely applied to meet the requirement of different ecological environment and harvest period. (authors)

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)

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)

A Hybrid Approach Based on the Combination of Adaptive Neuro-Fuzzy Inference System and Imperialist Competitive Algorithm: Oil Flow Rate of the Wells Prediction Case Study

Directory of Open Access Journals (Sweden)

Shahram Mollaiy Berneti

2013-04-01

Full Text Available In this paper, a novel hybrid approach composed of adaptive neuro-fuzzy inference system (ANFIS and imperialist competitive algorithm is proposed. The imperialist competitive algorithm (ICA is used in this methodology to determine the most suitable initial membership functions of the ANFIS. The proposed model combines the global search ability of ICA with local search ability of gradient descent method. To illustrate the suitability and capability of the proposed model, this model is applied to predict oil flow rate of the wells utilizing data set of 31 wells in one of the northern Persian Gulf oil fields of Iran. The data set collected in a three month period for each well from Dec. 2002 to Nov. 2010. For the sake of performance evaluation, the results of the proposed model are compared with the conventional ANFIS model. The results show that the significant improvements are achievable using the proposed model in comparison with the results obtained by conventional ANFIS.

The plus-hybrid effect on the grain yield of two ZP maize hybrids

Directory of Open Access Journals (Sweden)

Božinović Sofija

2010-01-01

Full Text Available The combined effect of cytoplasmic male sterility and xenia on maize hybrid traits is referred to as the plus-hybrid effect. Two studied ZP hybrids differently responded to this effect for grain yield. All plus-hybrid combinations of the firstly observed hybrid had a higher yield than their fertile counterparts, but not significantly, while only one combination of the second hybrid positively responded, also without statistical significance. It seems that the observed effect mostly depended on the genotype of the female component.

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.

Bounded Model Checking and Inductive Verification of Hybrid Discrete-Continuous Systems

DEFF Research Database (Denmark)

Becker, Bernd; Behle, Markus; Eisenbrand, Fritz

2004-01-01

We present a concept to signicantly advance the state of the art for bounded model checking (BMC) and inductive verication (IV) of hybrid discrete-continuous systems. Our approach combines the expertise of partners coming from dierent domains, like hybrid systems modeling and digital circuit veri...

The new era of cardiac surgery: hybrid therapy for cardiovascular disease.

Science.gov (United States)

Solenkova, Natalia V; Umakanthan, Ramanan; Leacche, Marzia; Zhao, David X; Byrne, John G

2010-11-01

Surgical therapy for cardiovascular disease carries excellent long-term outcomes but it is relatively invasive. With the development of new devices and techniques, modern cardiovascular surgery is trending toward less invasive approaches, especially for patients at high risk for traditional open heart surgery. A hybrid strategy combines traditional surgical treatments performed in the operating room with treatments traditionally available only in the catheterization laboratory with the goal of offering patients the best available therapy for any set of cardiovascular diseases. Examples of hybrid procedures include hybrid coronary artery bypass grafting, hybrid valve surgery and percutaneous coronary intervention, hybrid endocardial and epicardial atrial fibrillation procedures, and hybrid coronary artery bypass grafting/carotid artery stenting. This multidisciplinary approach requires strong collaboration between cardiac surgeons, vascular surgeons, and interventional cardiologists to obtain optimal patient outcomes.

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.

A dedicated lab for interventional cardiology and hybrid surgery

Energy Technology Data Exchange (ETDEWEB)

Berger, F. [KinderSpital Zurich (Switzerland). Department of Congenital Heart Disease/Pediatric Cardiology

2004-07-01

Pediatric interventionalists and surgeons treating congenital heart defects at the KinderSpital children's hospital in Zurich, Switzerland, use a ''hybrid'' approach to minimize the incidence and extent of open-heart surgery. The hybrid approach combines catheterization and surgical techniques in a single procedure, performed in the same lab. The combined cardiac cath lab/surgery suite is equipped with a Philips Integris Allura BH5000 9''/9'' biplane system, designed to meet all the requirements for pediatric applications, including the need to keep the quantity of contrast agent and the radiation dose to the minimum. Wherever possible, diagnostic X-ray examinations are supplemented by MR and Ultrasound. (orig.)

Visibility and oxidation stability of hybrid-type copper mesh electrodes with combined nickel-carbon nanotube coating

Science.gov (United States)

Kim, Bu-Jong; Hwang, Young-Jin; Park, Jin-Seok

2017-04-01

Hybrid-type transparent conductive electrodes (TCEs) were fabricated by coating copper (Cu) meshes with carbon nanotube (CNT) via electrophoretic deposition, and with nickel (Ni) via electroplating. For the fabricated electrodes, the effects of the coating with CNT and Ni on their transmittance and reflectance in the visible-light range, electrical sheet resistance, and chromatic parameters (e.g., redness and yellowness) were characterized. Also, an oxidation stability test was performed by exposing the electrodes to air for 20 d at 85 °C and 85% temperature and humidity conditions, respectively. It was discovered that the CNT coating considerably reduced the reflectance of the Cu meshes, and that the Ni coating effectively protected the Cu meshes against oxidation. Furthermore, after the coating with CNT, both the redness and yellowness of the Cu mesh regardless of the Ni coating approached almost zero, indicating a natural color. The experiment results confirmed that the hybrid-type Cu meshes with combined Ni-CNT coating improved characteristics in terms of reflectance, sheet resistance, oxidation stability, and color, superior to those of the primitive Cu mesh, and also simultaneously satisfied most of the requirements for TCEs.

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.

Comparison of HMM experts with MLP experts in the Full Combination Multi-Band Approach to Robust ASR

OpenAIRE

Hagen, Astrid; Morris, Andrew

2000-01-01

In this paper we apply the Full Combination (FC) multi-band approach, which has originally been introduced in the framework of posterior-based HMM/ANN (Hidden Markov Model/Artificial Neural Network) hybrid systems, to systems in which the ANN (or Multilayer Perceptron (MLP)) is itself replaced by a Multi Gaussian HMM (MGM). Both systems represent the most widely used statistical models for robust ASR (automatic speech recognition). It is shown how the FC formula for the likelihood--based MGMs...

Combination of water-jet dissection and needle-knife as a hybrid knife simplifies endoscopic submucosal dissection.

Science.gov (United States)

Lingenfelder, Tobias; Fischer, Klaus; Sold, Moritz G; Post, Stefan; Enderle, Markus D; Kaehler, Georg F B A

2009-07-01

The safety and efficacy of endoscopic submucosal dissection (ESD) is very dependent on an effective injection beneath the submucosal lamina and on a controlled cutting technique. After our study group demonstrated the efficacy of the HydroJet in needleless submucosal injections under various physical conditions to create a submucosal fluid cushion (Selective tissue elevation by pressure = STEP technique), the next step was to develop a new instrument to combine the capabilities of an IT-Knife with a high-pressure water-jet in a single instrument. In this experimental study, we compared this new instrument with a standard ESD technique. Twelve gastric ESD were performed in six pigs under endotracheal anesthesia. Square areas measuring 4-cm x 4-cm were marked out on the anterior and posterior wall in the corpus-antrum transition region. The HybridKnife was used as an standard needle knife with insulated tip (i.e., the submucosal injection was performed with an injection needle and only the radiofrequency (RF) part of the HybridKnife was used for cutting (conventional technique)) or the HybridKnife was used in all the individual stages of the ESD, making use of the HybridKnife's combined functions (HybridKnife technique). The size of the resected specimens, the operating time, the frequency with which instruments were changed, the number of bleeding episodes, and the number of injuries to the gastric wall together with the subjective overall assessment of the intervention by the operating physician were recorded. The resected specimens were the same size, with average sizes of 16.96 cm(2) and 15.85 cm(2) resp (p = 0.8125). Bleeding episodes have been less frequent in the HybridKnife group (2.83 vs. 3.5; p = 0.5625). The standard knife caused more injuries to the lamina muscularis propria (0.17 vs. 1.33; p = 0.0313). The operating times had a tendency to be shorter with the HybridKnife technique (47.18 vs. 58.32 minute; p = 0.0313). The combination of a needle

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....

A deep learning / neuroevolution hybrid for visual control

DEFF Research Database (Denmark)

Poulsen, Andreas Precht; Thorhauge, Mark; Funch, Mikkel Hvilshj

2017-01-01

This paper presents a deep learning / neuroevolution hybrid approach called DLNE, which allows FPS bots to learn to aim & shoot based only on high-dimensional raw pixel input. The deep learning component is responsible for visual recognition and translating raw pixels to compact feature...... representations, while the evolving network takes those features as inputs to infer actions. The results suggest that combining deep learning and neuroevolution in a hybrid approach is a promising research direction that could make complex visual domains directly accessible to networks trained through evolution....

A Hybrid Approach Combining the Multi-Temporal Scale Spatio-Temporal Network with the Continuous Triangular Model for Exploring Dynamic Interactions in Movement Data: A Case Study of Football

Directory of Open Access Journals (Sweden)

Pengdong Zhang

2018-01-01

Full Text Available Benefiting from recent advantages in location-aware technologies, movement data are becoming ubiquitous. Hence, numerous research topics with respect to movement data have been undertaken. Yet, the research of dynamic interactions in movement data is still in its infancy. In this paper, we propose a hybrid approach combining the multi-temporal scale spatio-temporal network (MTSSTN and the continuous triangular model (CTM for exploring dynamic interactions in movement data. The approach mainly includes four steps: first, the relative trajectory calculus (RTC is used to derive three types of interaction patterns; second, for each interaction pattern, a corresponding MTSSTN is generated; third, for each MTSSTN, the interaction intensity measures and three centrality measures (i.e., degree, betweenness and closeness are calculated; finally, the results are visualized at multiple temporal scales using the CTM and analyzed based on the generated CTM diagrams. Based on the proposed approach, three distinctive aims can be achieved for each interaction pattern at multiple temporal scales: (1 exploring the interaction intensities between any two individuals; (2 exploring the interaction intensities among multiple individuals, and (3 exploring the importance of each individual and identifying the most important individuals. The movement data obtained from a real football match are used as a case study to validate the effectiveness of the proposed approach. The results demonstrate that the proposed approach is useful in exploring dynamic interactions in football movement data and discovering insightful information.

A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

KAUST Repository

McCabe, Matthew

2017-12-06

with inherent extrapolation and transferability limitations. Explanatory VIs formed from bands in the near-infrared (NIR) and shortwave infrared domains (e.g., NDWI) were associated with the highest predictive ability, whereas Cubist models relying entirely on VIs based on NIR and red band combinations (e.g., NDVI) were associated with comparatively high uncertainties (i.e., rMAD ∼21%). The most transferable and best performing models were based on combinations of several predictor variables, which included both NDWI- and NDVI-like variables. In this process, prior screening of input VIs based on an assessment of variable relevance served as an effective mechanism for optimizing prediction accuracies from both Cubist and RF. While this study demonstrated benefit in combining data mining operations with physically based constraints via a hybrid training approach, the concept of transferability and portability warrants further investigations in order to realize the full potential of emerging machine-learning techniques for regression purposes.

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

inherent extrapolation and transferability limitations. Explanatory VIs formed from bands in the near-infrared (NIR) and shortwave infrared domains (e.g., NDWI) were associated with the highest predictive ability, whereas Cubist models relying entirely on VIs based on NIR and red band combinations (e.g., NDVI) were associated with comparatively high uncertainties (i.e., rMAD ∼ 21%). The most transferable and best performing models were based on combinations of several predictor variables, which included both NDWI- and NDVI-like variables. In this process, prior screening of input VIs based on an assessment of variable relevance served as an effective mechanism for optimizing prediction accuracies from both Cubist and RF. While this study demonstrated benefit in combining data mining operations with physically based constraints via a hybrid training approach, the concept of transferability and portability warrants further investigations in order to realize the full potential of emerging machine-learning techniques for regression purposes.

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 inherent extrapolation and transferability limitations. Explanatory VIs formed from bands in the near-infrared (NIR) and shortwave infrared domains (e.g., NDWI) were associated with the highest predictive ability, whereas Cubist models relying entirely on VIs based on NIR and red band combinations (e.g., NDVI) were associated with comparatively high uncertainties (i.e., rMAD ∼21%). The most transferable and best performing models were based on combinations of several predictor variables, which included both NDWI- and NDVI-like variables. In this process, prior screening of input VIs based on an assessment of variable relevance served as an effective mechanism for optimizing prediction accuracies from both Cubist and RF. While this study demonstrated benefit in combining data mining operations with physically based constraints via a hybrid training approach, the concept of transferability and portability warrants further investigations in order to realize the full potential of emerging machine-learning techniques for regression purposes.

H-Ransac a Hybrid Point Cloud Segmentation Combining 2d and 3d Data

Science.gov (United States)

Adam, A.; Chatzilari, E.; Nikolopoulos, S.; Kompatsiaris, I.

2018-05-01

In this paper, we present a novel 3D segmentation approach operating on point clouds generated from overlapping images. The aim of the proposed hybrid approach is to effectively segment co-planar objects, by leveraging the structural information originating from the 3D point cloud and the visual information from the 2D images, without resorting to learning based procedures. More specifically, the proposed hybrid approach, H-RANSAC, is an extension of the well-known RANSAC plane-fitting algorithm, incorporating an additional consistency criterion based on the results of 2D segmentation. Our expectation that the integration of 2D data into 3D segmentation will achieve more accurate results, is validated experimentally in the domain of 3D city models. Results show that HRANSAC can successfully delineate building components like main facades and windows, and provide more accurate segmentation results compared to the typical RANSAC plane-fitting algorithm.

The ATPG Attack for Reverse Engineering of Combinational Hybrid Custom-Programmable Circuits

Science.gov (United States)

2017-03-23

Introduction The widely practiced horizontal integrated circuit supply chain exposes a design to various types of attacks including the reverse engineering ...STT_CMOS designs for reverse- engineering prevention, DAC 2016. [5] M. E. Massad and et. al. Integrated circuit (IC) decamouflaging: reverse...The ATPG Attack for Reverse Engineering of Combinational Hybrid Custom-Programmable Circuits Raza Shafiq Hamid Mahmoodi Houman Homayoun Hassan

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.

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.

Vehicle Sideslip Angle Estimation Based on Hybrid Kalman Filter

Directory of Open Access Journals (Sweden)

Jing Li

2016-01-01

Full Text Available Vehicle sideslip angle is essential for active safety control systems. This paper presents a new hybrid Kalman filter to estimate vehicle sideslip angle based on the 3-DoF nonlinear vehicle dynamic model combined with Magic Formula tire model. The hybrid Kalman filter is realized by combining square-root cubature Kalman filter (SCKF, which has quick convergence and numerical stability, with square-root cubature based receding horizon Kalman FIR filter (SCRHKF, which has robustness against model uncertainty and temporary noise. Moreover, SCKF and SCRHKF work in parallel, and the estimation outputs of two filters are merged by interacting multiple model (IMM approach. Experimental results show the accuracy and robustness of the hybrid Kalman filter.

Hybrid and Blended Learning: Modifying Pedagogy across Path, Pace, Time, and Place

Science.gov (United States)

O'Byrne, W. Ian; Pytash, Kristine E.

2015-01-01

Hybrid or blended learning is defined as a pedagogical approach that includes a combination of face-to-face instruction with computer-mediated instruction. The terms "blended learning", "hybrid learning", and "mixed-mode learning" are used interchangeably in current research; however, in the United States,…

Hybrid colloidal plasmonic-photonic crystals.

Science.gov (United States)

Romanov, Sergei G; Korovin, Alexander V; Regensburger, Alois; Peschel, Ulf

2011-06-17

We review the recently emerged class of hybrid metal-dielectric colloidal photonic crystals. The hybrid approach is understood as the combination of a dielectric photonic crystal with a continuous metal film. It allows to achieve a strong modification of the optical properties of photonic crystals by involving the light scattering at electronic excitations in the metal component into moulding of the light flow in series to the diffraction resonances occurring in the body of the photonic crystal. We consider different realizations of hybrid plasmonic-photonic crystals based on two- and three-dimensional colloidal photonic crystals in association with flat and corrugated metal films. In agreement with model calculations, different resonance phenomena determine the optical response of hybrid crystals leading to a broadly tuneable functionality of these crystals. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modelling of combined ICRF and NBI heating in JET hybrid plasmas

Directory of Open Access Journals (Sweden)

Gallart Dani

2017-01-01

Full Text Available During the 2015-2016 JET campaigns many efforts have been devoted to the exploration of high performance plasma scenarios envisaged for ITER operation. In this paper we model the combined ICRF+NBI heating in selected key hybrid discharges using PION. The antenna frequency was tuned to match the cyclotron frequency of minority hydrogen (H at the center of the tokamak coinciding with the second harmonic cyclotron resonance of deuterium. The modelling takes into account the synergy between ICRF and NBI heating through the second harmonic cyclotron resonance of deuterium beam ions which allows us to assess its impact on the neutron rate RNT. We evaluate the influence of H concentration which was varied in different discharges in order to test their role in the heating performance. According to our modelling, the ICRF enhancement of RNT increases by decreasing the H concentration which increases the ICRF power absorbed by deuterons. We find that in the recent hybrid discharges this ICRF enhancement was in the range of 10-25%. Finally, we extrapolate the results to D-T and find that the best performing hybrid discharges correspond to an equivalent fusion power of ∼7.0 MW in D-T.

Methodological approaches in the research of organizational culture

Directory of Open Access Journals (Sweden)

Janićijević Nebojša

2011-01-01

Full Text Available In the thirty-years-long research of organizational culture, two mutually opposed methodological approaches have emerged: objectivistic quantitative and subjectivistic-qualitative. These two approaches are based on opposite ontological and epistemological assumptions: they include different types of research, and use opposite, quantitative vs. qualitative, methods of research. Each of the methodological approaches has its advantages and disadvantages. For this reason a hybrid approach emerges as a legitimate choice in organizational culture research methodology. It combines elements of both subjectivistic and objectivistic methodological approaches, according to the goals, content, and context of the research and preferences of the researcher himself/herself. Since it is possible to combine the two principal methodological approaches in various ways, there are several possible hybrid methodologies in organizational culture research. After the review of objectivistic quantitative and subjectivistic-qualitative methodological approaches, one of possible hybrid approaches in the research of organizational culture is presented in this paper.

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.

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.

Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.

Directory of Open Access Journals (Sweden)

Jakub Jończyk

Full Text Available The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand-receptor interactions for reference compounds.

Hybrid Broadband Ground-Motion Simulations: Combining Long-Period Deterministic Synthetics with High-Frequency Multiple S-to-S Backscattering

KAUST Repository

Mai, Paul Martin; Imperatori, W.; Olsen, K. B.

2010-01-01

We present a new approach for computing broadband (0-10 Hz) synthetic seismograms by combining high-frequency (HF) scattering with low-frequency (LF) deterministic seismograms, considering finite-fault earthquake rupture models embedded in 3D earth structure. Site-specific HF-scattering Green's functions for a heterogeneous medium with uniformly distributed random isotropic scatterers are convolved with a source-time function that characterizes the temporal evolution of the rupture process. These scatterograms are then reconciled with the LF-deterministic waveforms using a frequency-domain optimization to match both amplitude and phase spectra around the target intersection frequency. The scattering parameters of the medium, scattering attenuation ηs, intrinsic attenuation ηi, and site-kappa, as well as frequency-dependent attenuation, determine waveform and spectral character of the HF-synthetics and thus affect the hybrid broadband seismograms. Applying our methodology to the 1994 Northridge earthquake and validating against near-field recordings at 24 sites, we find that our technique provides realistic broadband waveforms and consistently reproduces LF ground-motion intensities for two independent source descriptions. The least biased results, compared to recorded strong-motion data, are obtained after applying a frequency-dependent site-amplification factor to the broadband simulations. This innovative hybrid ground-motion simulation approach, applicable to any arbitrarily complex earthquake source model, is well suited for seismic hazard analysis and ground-motion estimation.

Hybrid Broadband Ground-Motion Simulations: Combining Long-Period Deterministic Synthetics with High-Frequency Multiple S-to-S Backscattering

KAUST Repository

Mai, Paul Martin

2010-09-20

We present a new approach for computing broadband (0-10 Hz) synthetic seismograms by combining high-frequency (HF) scattering with low-frequency (LF) deterministic seismograms, considering finite-fault earthquake rupture models embedded in 3D earth structure. Site-specific HF-scattering Green\\'s functions for a heterogeneous medium with uniformly distributed random isotropic scatterers are convolved with a source-time function that characterizes the temporal evolution of the rupture process. These scatterograms are then reconciled with the LF-deterministic waveforms using a frequency-domain optimization to match both amplitude and phase spectra around the target intersection frequency. The scattering parameters of the medium, scattering attenuation ηs, intrinsic attenuation ηi, and site-kappa, as well as frequency-dependent attenuation, determine waveform and spectral character of the HF-synthetics and thus affect the hybrid broadband seismograms. Applying our methodology to the 1994 Northridge earthquake and validating against near-field recordings at 24 sites, we find that our technique provides realistic broadband waveforms and consistently reproduces LF ground-motion intensities for two independent source descriptions. The least biased results, compared to recorded strong-motion data, are obtained after applying a frequency-dependent site-amplification factor to the broadband simulations. This innovative hybrid ground-motion simulation approach, applicable to any arbitrarily complex earthquake source model, is well suited for seismic hazard analysis and ground-motion estimation.

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.

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.

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

Online Assessment of Human-Robot Interaction for Hybrid Control of Walking

Directory of Open Access Journals (Sweden)

Ana de-los-Reyes

2011-12-01

Full Text Available Restoration of walking ability of Spinal Cord Injury subjects can be achieved by different approaches, as the use of robotic exoskeletons or electrical stimulation of the user’s muscles. The combined (hybrid approach has the potential to provide a solution to the drawback of each approach. Specific challenges must be addressed with specific sensory systems and control strategies. In this paper we present a system and a procedure to estimate muscle fatigue from online physical interaction assessment to provide hybrid control of walking, regarding the performances of the muscles under stimulation.

Sequence-dependent theory of oligonucleotide hybridization kinetics

International Nuclear Information System (INIS)

Marimuthu, Karthikeyan; Chakrabarti, Raj

2014-01-01

A theoretical approach to the prediction of the sequence and temperature-dependent rate constants for oligonucleotide hybridization reactions has been developed based on the theory of relaxation kinetics. One-sided and two-sided melting reaction mechanisms for oligonucleotide hybridization reactions have been considered, analyzed, modified, and compared to select a physically consistent as well as robust model for prediction of the relaxation times of DNA hybridization reactions that agrees with the experimental evidence. The temperature- and sequence-dependent parameters of the proposed model have been estimated using available experimental data. The relaxation time model that we developed has been combined with the nearest neighbor model of hybridization thermodynamics to estimate the temperature- and sequence-dependent rate constants of an oligonucleotide hybridization reaction. The model-predicted rate constants are compared to experimentally determined rate constants for the same oligonucleotide hybridization reactions. Finally, we consider a few important applications of kinetically controlled DNA hybridization reactions

A Review of Hybrid Brain-Computer Interface Systems

Directory of Open Access Journals (Sweden)

Setare Amiri

2013-01-01

Full Text Available Increasing number of research activities and different types of studies in brain-computer interface (BCI systems show potential in this young research area. Research teams have studied features of different data acquisition techniques, brain activity patterns, feature extraction techniques, methods of classifications, and many other aspects of a BCI system. However, conventional BCIs have not become totally applicable, due to the lack of high accuracy, reliability, low information transfer rate, and user acceptability. A new approach to create a more reliable BCI that takes advantage of each system is to combine two or more BCI systems with different brain activity patterns or different input signal sources. This type of BCI, called hybrid BCI, may reduce disadvantages of each conventional BCI system. In addition, hybrid BCIs may create more applications and possibly increase the accuracy and the information transfer rate. However, the type of BCIs and their combinations should be considered carefully. In this paper, after introducing several types of BCIs and their combinations, we review and discuss hybrid BCIs, different possibilities to combine them, and their advantages and disadvantages.

Omnidirectional Wheel-Legged Hybrid Mobile Robot

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István Vilikó

2015-06-01

Full Text Available The purpose of developing hybrid locomotion systems is to merge the advantages and to eliminate the disadvantages of different type of locomotion. The proposed solution combines wheeled and legged locomotion methods. This paper presents the mechatronic design approach and the development stages of the prototype.

Combining ability and mode of inheritance of stem thickness in forage sorghum (Sorghum bicolor L. Moench F1 hybrids

Directory of Open Access Journals (Sweden)

Pataki Imre

2011-01-01

Full Text Available Aim of this research was determination of mode of inheritance, gene effects components of genetic variance, combining abilities, average contribution of lines and testers and their interactions in expression of stem thickness in forage sorghum F1 generation. Method line x tester was applied. Material comprised of eight genetically divergent A-inbred lines of grain sorghum three R lines-testers of Sudan grass and twenty-four F1 hybrids obtained by crossing lines with testers. Among tested genotypes there were significant differences in mean values of stem thickness. Analysis of variance of combining abilities showed that there were highly significant differences for general combining abilities (GCA and specific combining abilities (SCA non-additive component of genetic variance (dominance and epistasis had greater portion in total genetic variance for stem thickness. During the first research year, interaction between inbred maternal line with testers had the largest contribution in expression of stem thickness of F1 hybrid at both locations, while in the second year at location Rimski Šančevi the largest contribution belongs to lines and at location Mačvanski Prnjavor the largest contribution belongs to testers. Assessment of combining abilities showed that these inbred lines of grain sorghum can be used as mothers: SS-1 646, SS-1 688 and S-8 682 in breeding forage sorghum for thicker stem. According to SCA, promising forage sorghum hybrids are S-8 682 x ST-R lin H and P-21 656 x C-198. This research can be of importance for developing new high-yielding forage sorghum hybrids.

Hybrid Detectors for Neutrons Combining Phenyl- Polysiloxanes with 3D Silicon Detectors

International Nuclear Information System (INIS)

Dalla Palma, Matteo; Quaranta, Alberto; Collazuol, Gianmaria; Carturan, Sara; Cinausero, Marco; Gramegna, Fabiana; Marchi, Tommaso; Dalla Betta, Gian-Franco; Mendicino, Roberto; Povoli, Marco; Boscardin, Maurizio; Giacomini, Gabriele; Ronchin, Sabina; Zorzi, Nicola

2013-06-01

We report on the initial results of a research project aimed at the development hybrid detectors for fast neutrons by combining a phenyl-polysiloxane-based converter with a 3D silicon detector. To this purpose, new 3D sensor structures have been designed, fabricated and electrically tested, showing low depletion voltage and good leakage current. Moreover, the radiation detection capability of 3D sensors was tested by measuring the signals recorded from alpha particles, gamma rays, and pulsed lasers. The converter has been poured into the 3D cavities with excellent coupling, as confirmed by cross-section SEM analyses. Preliminary tests with neutrons have been carried out on the first hybrid detector prototypes at the CN accelerator of INFN LNL. The device design and technology are discussed, along with the first results from the electrical and functional characterization. (authors)

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.

Assume-Guarantee Abstraction Refinement Meets Hybrid Systems

Science.gov (United States)

Bogomolov, Sergiy; Frehse, Goran; Greitschus, Marius; Grosu, Radu; Pasareanu, Corina S.; Podelski, Andreas; Strump, Thomas

2014-01-01

Compositional verification techniques in the assume- guarantee style have been successfully applied to transition systems to efficiently reduce the search space by leveraging the compositional nature of the systems under consideration. We adapt these techniques to the domain of hybrid systems with affine dynamics. To build assumptions we introduce an abstraction based on location merging. We integrate the assume-guarantee style analysis with automatic abstraction refinement. We have implemented our approach in the symbolic hybrid model checker SpaceEx. The evaluation shows its practical potential. To the best of our knowledge, this is the first work combining assume-guarantee reasoning with automatic abstraction-refinement in the context of hybrid automata.

Thermoeconomic Analysis of Hybrid Power Plant Concepts for Geothermal Combined Heat and Power Generation

Directory of Open Access Journals (Sweden)

Florian Heberle

2014-07-01

Full Text Available We present a thermo-economic analysis for a low-temperature Organic Rankine Cycle (ORC in a combined heat and power generation (CHP case. For the hybrid power plant, thermal energy input is provided by a geothermal resource coupled with the exhaust gases of a biogas engine. A comparison to alternative geothermal CHP concepts is performed by considering variable parameters like ORC working fluid, supply temperature of the heating network or geothermal water temperature. Second law efficiency as well as economic parameters show that hybrid power plants are more efficient compared to conventional CHP concepts or separate use of the energy sources.

Photothermal and biodegradable polyaniline/porous silicon hybrid nanocomposites as drug carriers for combined chemo-photothermal therapy of cancer.

Science.gov (United States)

Xia, Bing; Wang, Bin; Shi, Jisen; Zhang, Yu; Zhang, Qi; Chen, Zhenyu; Li, Jiachen

2017-03-15

To develop photothermal and biodegradable nanocarriers for combined chemo-photothermal therapy of cancer, polyaniline/porous silicon hybrid nanocomposites had been successfully fabricated via surface initiated polymerization of aniline onto porous silicon nanoparticles in our experiments. As-prepared polyaniline/porous silicon nanocomposites could be well dispersed in aqueous solution without any extra hydrophilic surface coatings, and showed a robust photothermal effect under near-infrared (NIR) laser irradiation. Especially, after an intravenous injection into mice, these biodegradable porous silicon-based nanocomposites as non-toxic agents could be completely cleared in body. Moreover, these polyaniline/porous silicon nanocomposites as drug carriers also exhibited an efficient loading and dual pH/NIR light-triggered release of doxorubicin hydrochloride (DOX, a model anticancer drug). Most importantly, assisted with NIR laser irradiation, polyaniline/PSiNPs nanocomposites with loading DOX showed a remarkable synergistic anticancer effect combining chemotherapy with photothermal therapy, whether in vitro or in vivo. Therefore, based on biodegradable PSiNPs-based nanocomposites, this combination approach of chemo-photothermal therapy would have enormous potential on clinical cancer treatments in the future. Considering the non-biodegradable nature and potential long-term toxicity concerns of photothermal nanoagents, it is of great interest and importance to develop biodegradable and photothermal nanoparticles with an excellent biocompatibility for their future clinical applications. In our experiments, we fabricated porous silicon-based hybrid nanocomposites via surface initiated polymerization of aniline, which showed an excellent photothermal effect, aqueous dispersibility, biodegradability and biocompatibility. Furthermore, after an efficient loading of DOX molecules, polyaniline/porous silicon nanocomposites exhibited the remarkable synergistic anticancer

Performance of U.S. hybrid distributed energy systems: Solar photovoltaic, battery and combined heat and power

International Nuclear Information System (INIS)

Shah, Kunal K.; Mundada, Aishwarya S.; Pearce, J.M.

2015-01-01

Highlights: • Simulated PV + battery + CHP hybrid systems deployed in three U.S. regions. • Used hybrid optimization model for electric renewable pro microgrid analysis. • Limited size of each sub-module to singe family house size. • Results show that the electricity generated meets residential load demand. • Hybrid systems are technically viable in hot, moderate and cold climates in U.S. - Abstract: Until recently, the relatively high levelized cost of electricity from solar photovoltaic (PV) technology limited deployment; however, recent cost reductions, combined with various financial incentives and innovative financing techniques, have made PV fully competitive with conventional sources in many American regions. In addition, the costs of electrical storage have also declined enough to make PV + battery systems potentially economically viable for a mass-scale off-grid low-emission transition. However, many regions in the U.S. (e.g. Northern areas) cannot have off-grid PV systems without prohibitively large battery systems. Small-scale combined heat and power (CHP) systems provide a potential solution for off-grid power backup of residential-scale PV + battery arrays, while also minimizing emissions from conventional sources. Thus, an opportunity is now available to maximize the use of solar energy and gain the improved efficiencies possible with CHPs to deploy PV + battery + CHP systems throughout the U.S. The aim of this study is to determine the technical viability of such systems by simulating PV + battery + CHP hybrid systems deployed in three representative regions in the U.S., using the Hybrid Optimization Model for Electric Renewable (HOMER) Pro Microgrid Analysis tool. The results show that the electricity generated by each component of the hybrid system can be coupled to fulfill the residential load demand. A sensitivity analysis of these hybrid off grid systems is carried out as a function capacity factor of both the PV and CHP units. The

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%

An Adaptive and Hybrid Approach for Revisiting the Visibility Pipeline

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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.

A Novel approach for predicting monthly water demand by combining singular spectrum analysis with neural networks

Science.gov (United States)

Zubaidi, Salah L.; Dooley, Jayne; Alkhaddar, Rafid M.; Abdellatif, Mawada; Al-Bugharbee, Hussein; Ortega-Martorell, Sandra

2018-06-01

Valid and dependable water demand prediction is a major element of the effective and sustainable expansion of municipal water infrastructures. This study provides a novel approach to quantifying water demand through the assessment of climatic factors, using a combination of a pretreatment signal technique, a hybrid particle swarm optimisation algorithm and an artificial neural network (PSO-ANN). The Singular Spectrum Analysis (SSA) technique was adopted to decompose and reconstruct water consumption in relation to six weather variables, to create a seasonal and stochastic time series. The results revealed that SSA is a powerful technique, capable of decomposing the original time series into many independent components including trend, oscillatory behaviours and noise. In addition, the PSO-ANN algorithm was shown to be a reliable prediction model, outperforming the hybrid Backtracking Search Algorithm BSA-ANN in terms of fitness function (RMSE). The findings of this study also support the view that water demand is driven by climatological variables.

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.

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

A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model

International Nuclear Information System (INIS)

Wang, Jianzhou; Hu, Jianming

2015-01-01

With the increasing importance of wind power as a component of power systems, the problems induced by the stochastic and intermittent nature of wind speed have compelled system operators and researchers to search for more reliable techniques to forecast wind speed. This paper proposes a combination model for probabilistic short-term wind speed forecasting. In this proposed hybrid approach, EWT (Empirical Wavelet Transform) is employed to extract meaningful information from a wind speed series by designing an appropriate wavelet filter bank. The GPR (Gaussian Process Regression) model is utilized to combine independent forecasts generated by various forecasting engines (ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM)) in a nonlinear way rather than the commonly used linear way. The proposed approach provides more probabilistic information for wind speed predictions besides improving the forecasting accuracy for single-value predictions. The effectiveness of the proposed approach is demonstrated with wind speed data from two wind farms in China. The results indicate that the individual forecasting engines do not consistently forecast short-term wind speed for the two sites, and the proposed combination method can generate a more reliable and accurate forecast. - Highlights: • The proposed approach can make probabilistic modeling for wind speed series. • The proposed approach adapts to the time-varying characteristic of the wind speed. • The hybrid approach can extract the meaningful components from the wind speed series. • The proposed method can generate adaptive, reliable and more accurate forecasting results. • The proposed model combines four independent forecasting engines in a nonlinear way.

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.

Personal Rotorcraft Design and Performance with Electric Hybridization

Science.gov (United States)

Snyder, Christopher A.

2017-01-01

Recent and projected improvements for more or all-electric aviation propulsion systems can enable greater personal mobility, while also reducing environmental impact (noise and emissions). However, all-electric energy storage capability is significantly less than present, hydrocarbon-fueled systems. A system study was performed exploring design and performance assuming hybrid propulsion ranging from traditional hydrocarbon-fueled cycles (gasoline Otto and diesel) to all-electric systems using electric motors generators, with batteries for energy storage and load leveling. Study vehicles were a conventional, single-main rotor (SMR) helicopter and an advanced vertical takeoff and landing (VTOL) aircraft. Vehicle capability was limited to two or three people (including pilot or crew); the design range for the VTOL aircraft was set to 150 miles (about one hour total flight). Search and rescue (SAR), loiter, and cruise-dominated missions were chosen to illustrate each vehicle and degree of hybrid propulsion strengths and weaknesses. The traditional, SMR helicopter is a hover-optimized design; electric hybridization was performed assuming a parallel hybrid approach by varying degree of hybridization. Many of the helicopter hybrid propulsion combinations have some mission capabilities that might be effective for short range or on-demand mobility missions. However, even for 30 year technology electrical components, all hybrid propulsion systems studied result in less available fuel, lower maximum range, and reduced hover and loiter duration than the baseline vehicle. Results for the VTOL aircraft were more encouraging. Series hybrid combinations reflective of near-term systems could improve range and loiter duration by 30. Advanced, higher performing series hybrid combinations could double or almost triple the VTOL aircrafts range and loiter duration. Additional details on the study assumptions and work performed are given, as well as suggestions for future study effort.

Agent-based power sharing scheme for active hybrid power sources

Science.gov (United States)

Jiang, Zhenhua

The active hybridization technique provides an effective approach to combining the best properties of a heterogeneous set of power sources to achieve higher energy density, power density and fuel efficiency. Active hybrid power sources can be used to power hybrid electric vehicles with selected combinations of internal combustion engines, fuel cells, batteries, and/or supercapacitors. They can be deployed in all-electric ships to build a distributed electric power system. They can also be used in a bulk power system to construct an autonomous distributed energy system. An important aspect in designing an active hybrid power source is to find a suitable control strategy that can manage the active power sharing and take advantage of the inherent scalability and robustness benefits of the hybrid system. This paper presents an agent-based power sharing scheme for active hybrid power sources. To demonstrate the effectiveness of the proposed agent-based power sharing scheme, simulation studies are performed for a hybrid power source that can be used in a solar car as the main propulsion power module. Simulation results clearly indicate that the agent-based control framework is effective to coordinate the various energy sources and manage the power/voltage profiles.

Quantum Mechanics/Molecular Mechanics Method Combined with Hybrid All-Atom and Coarse-Grained Model: Theory and Application on Redox Potential Calculations.

Science.gov (United States)

Shen, Lin; Yang, Weitao

2016-04-12

We developed a new multiresolution method that spans three levels of resolution with quantum mechanical, atomistic molecular mechanical, and coarse-grained models. The resolution-adapted all-atom and coarse-grained water model, in which an all-atom structural description of the entire system is maintained during the simulations, is combined with the ab initio quantum mechanics and molecular mechanics method. We apply this model to calculate the redox potentials of the aqueous ruthenium and iron complexes by using the fractional number of electrons approach and thermodynamic integration simulations. The redox potentials are recovered in excellent accordance with the experimental data. The speed-up of the hybrid all-atom and coarse-grained water model renders it computationally more attractive. The accuracy depends on the hybrid all-atom and coarse-grained water model used in the combined quantum mechanical and molecular mechanical method. We have used another multiresolution model, in which an atomic-level layer of water molecules around redox center is solvated in supramolecular coarse-grained waters for the redox potential calculations. Compared with the experimental data, this alternative multilayer model leads to less accurate results when used with the coarse-grained polarizable MARTINI water or big multipole water model for the coarse-grained layer.

Conceptual design of distillation-based hybrid separation processes.

Science.gov (United States)

Skiborowski, Mirko; Harwardt, Andreas; Marquardt, Wolfgang

2013-01-01

Hybrid separation processes combine different separation principles and constitute a promising design option for the separation of complex mixtures. Particularly, the integration of distillation with other unit operations can significantly improve the separation of close-boiling or azeotropic mixtures. Although the design of single-unit operations is well understood and supported by computational methods, the optimal design of flowsheets of hybrid separation processes is still a challenging task. The large number of operational and design degrees of freedom requires a systematic and optimization-based design approach. To this end, a structured approach, the so-called process synthesis framework, is proposed. This article reviews available computational methods for the conceptual design of distillation-based hybrid processes for the separation of liquid mixtures. Open problems are identified that must be addressed to finally establish a structured process synthesis framework for such processes.

Hybrid treatment strategies for 2,4,6-trichlorophenol degradation based on combination of hydrodynamic cavitation and AOPs.

Science.gov (United States)

Barik, Arati J; Gogate, Parag R

2018-01-01

Utilization of hybrid treatment schemes involving advanced oxidation processes and hydrodynamic cavitation in the wastewater treatment forms the prime focus of the present work. The initial phase of the work includes analysis of recent literature relating to the performance of combined approach based on hydrodynamic cavitation (HC) for degradation of different pollutants followed by a detailed investigation into degradation of 2,4,6-trichlorophenol (2,4,6-TCP). The degradation of the priority pollutant, 2,4,6-TCP, using combination of HC based on slit-venturi used as the cavitating device, ozone and H 2 O 2 has been investigated. The effect of operating pressure (2-5bar) and initial pH (3-11) have been investigated for the degradation using only HC. The degradation using only ozone (100-400mg/h) and only H 2 O 2 has also been studied. The efficacy of the combined operation of HC+O 3 at different ozone flow rates (100-400mg/h) and the combined operation of HC+H 2 O 2 at different loadings of H 2 O 2 (2,4,6-TCP:H 2 O 2 as 1:1-1:7) have been subsequently investigated. The degradation efficacy has also been established for the combined treatment strategies of O 3 +H 2 O 2 and HC+O 3 +H 2 O 2 at the optimum conditions of temperature as 30°C, inlet pressure of 4bar and initial pH of 7. Extent of 2,4,6-TCP degradation, TOC and COD removal obtained for HC+O 3 process were 97.1%, 94.4% and 78.5% respectively whereas for O 3 +H 2 O 2 process, the values were 95.5%, 94.8% and 76.2% and for HC+O 3 +H 2 O 2 process the extent of reduction were 100%, 95.6% and 80.9% in the same order. The combined treatment approach as HC+O 3 +H 2 O 2 was established as the most efficient approach for complete removal of 2,4,6-TCP with near complete TOC removal. Copyright © 2017 Elsevier B.V. All rights reserved.

Is there a prospect for hybrid aortic arch surgery?

Science.gov (United States)

Bashir, Mohamad; Harky, Amer; Bilal, Haris

2018-05-16

The surge of endovascular repair of aortic aneurysm in current modern aortic surgery practice has been the key for surgical management of elective cases of thoracic aortic aneurysms. This has paved way for the combined hybrid approach to be amongst the armamentarium for the management of aortic arch disease. The pivotal understanding of the aortic arch natural history coupled with device technology advancement allowed surgeons insight into delivery of hybrid surgery with acceptable morbidity and mortality results. This review article provides current insights into hybrid technique of aortic arch aneurysm repair and the evidences behind its applicability to arch surgery. It is aimed to highlight the challenges encountered for this innovative approach and correlate its challenges to those that are met by the conventional open aortic arch repair.

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.

Treatment of critical lower limb ischemia using a hybrid technique

Directory of Open Access Journals (Sweden)

Ricardo Wagner da Costa Moreira

2014-09-01

Full Text Available Critical ischemia of a lower limb is a condition that threatens its viability and must be treated promptly to avoid major amputation. Revascularization is the most effective treatment method and is performed using surgical or endovascular techniques. For patients with thoracoabdominal aortic aneurysms, combining these two approaches into a "hybrid technique" makes it possible to treat patients who could not be adequately treated by either technique in isolation. We report on a case of lower limb critical ischemia treated using a combination of surgery and endovascular techniques, in an application of the hybrid technique in a different arterial bed.

Hybrid Arrays for Chemical Sensing

Science.gov (United States)

Kramer, Kirsten E.; Rose-Pehrsson, Susan L.; Johnson, Kevin J.; Minor, Christian P.

intelligence and robotics, all share the same essential data fusion challenges. The design of a hybrid sensor array should draw on this extended body of knowledge. In this chapter, various techniques for data preprocessing, feature extraction, feature selection, and modeling of sensor data will be introduced and illustrated with data fusion approaches that have been implemented in applications involving data from hybrid arrays. The example systems discussed in this chapter involve the development of prototype sensor networks for damage control event detection aboard US Navy vessels and the development of analysis algorithms to combine multiple sensing techniques for enhanced remote detection of unexploded ordnance (UXO) in both ground surveys and wide area assessments.

DESIGN OF THE THREE-LEVEL MULTICRITERIAL STRATEGY OF HYBRID MARINE POWER PLANT CONTROL FOR A COMBINED PROPULSION COMPLEX

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V.V. Budashko

2017-04-01

Full Text Available Purpose. Efficiency of hybrid ships power plants (SPP combined propulsion complexes (CPC by various criteria for energy management systems strategies. Methodology. Based on the classification system topologies SPP CPC for mechanical, electrical and hybrid types of motors schematic diagrams of management strategies for the criterion of minimum power consumption are defined. Changing the technical component of the traditional approach to building hybrid ships electric power systems (SEPS SPP CPC the principle of modifying the structure of SEPS is applied with the integration of additional static alternative power source as dynamic reserve, which allowed to meet modern requirements for energy efficiency, levels of vibration, noise and degradation effects produced to SPP CPC, in all areas of the energy for the transfer of power from energy to propellers. Modeling of power transmission of energy to propellers in MatLab/Simulink is conducted, using blocks of optimization library and definition of identity markers. Results. Major advantages and disadvantages SPP CPC depending on the topology of energy distribution systems are determined. According to the chosen structure system electricity characteristics were obtained in the process of power transmission SPP CPC and power systems and their control strategies in terms of increased efficiency and eliminate these drawbacks. And finally, mathematical apparatus for research in terms of the development of methods for designing and managing SPP hybrid CPC to reduced fuel consumption, emissions into the environment and improving maintainability, flexibility and comfort level are improved. Originality. The methodology for improving SPP CPC implementation by developing methods of identification markers mutually influencing processes in SPP CPC and the development of implementing these methods of settlement and information systems. Practical value. The method enables iterative optimization parameters SPP CPC, it

Reciprocal Genetics: Identifying QTL for General and Specific Combining Abilities in Hybrids Between Multiparental Populations from Two Maize (Zea mays L.) Heterotic Groups.

Science.gov (United States)

Giraud, Héloïse; Bauland, Cyril; Falque, Matthieu; Madur, Delphine; Combes, Valérie; Jamin, Philippe; Monteil, Cécile; Laborde, Jacques; Palaffre, Carine; Gaillard, Antoine; Blanchard, Philippe; Charcosset, Alain; Moreau, Laurence

2017-11-01

Several plant and animal species of agricultural importance are commercialized as hybrids to take advantage of the heterosis phenomenon. Understanding the genetic architecture of hybrid performances is therefore of key importance. We developed two multiparental maize ( Zea mays L.) populations, each corresponding to an important heterotic group (dent or flint) and comprised of six connected biparental segregating populations of inbred lines (802 and 822 lines for each group, respectively) issued from four founder lines. Instead of using "testers" to evaluate their hybrid values, segregating lines were crossed according to an incomplete factorial design to produce 951 dent-flint hybrids, evaluated for four biomass production traits in eight environments. QTL detection was carried out for the general-combining-ability (GCA) and specific-combining-ability (SCA) components of hybrid value, considering allelic effects transmitted from each founder line. In total, 42 QTL were detected across traits. We detected mostly QTL affecting GCA, 31% (41% for dry matter yield) of which also had mild effects on SCA. The small impact of dominant effects is consistent with the known differentiation between the dent and flint heterotic groups and the small percentage of hybrid variance due to SCA observed in our design (∼20% for the different traits). Furthermore, most (80%) of GCA QTL were segregating in only one of the two heterotic groups. Relative to tester-based designs, use of hybrids between two multiparental populations appears highly cost efficient to detect QTL in two heterotic groups simultaneously. This presents new prospects for selecting superior hybrid combinations with markers. Copyright © 2017 by the Genetics Society of America.

A new hybrid BCI paradigm based on P300 and SSVEP.

Science.gov (United States)

Wang, Minjue; Daly, Ian; Allison, Brendan Z; Jin, Jing; Zhang, Yu; Chen, Lanlan; Wang, Xingyu

2015-04-15

P300 and steady-state visual evoked potential (SSVEP) approaches have been widely used for brain-computer interface (BCI) systems. However, neither of these approaches can work for all subjects. Some groups have reported that a hybrid BCI that combines two or more approaches might provide BCI functionality to more users. Hybrid P300/SSVEP BCIs have only recently been developed and validated, and very few avenues to improve performance have been explored. The present study compares an established hybrid P300/SSVEP BCIs paradigm to a new paradigm in which shape changing, instead of color changing, is adopted for P300 evocation to decrease the degradation on SSVEP strength. The result shows that the new hybrid paradigm presented in this paper yields much better performance than the normal hybrid paradigm. A performance increase of nearly 20% in SSVEP classification is achieved using the new hybrid paradigm in comparison with the normal hybrid paradigm. All the paradigms except the normal hybrid paradigm used in this paper obtain 100% accuracy in P300 classification. The new hybrid P300/SSVEP BCIs paradigm in which shape changing, instead of color changing, could obtain as high classification accuracy of SSVEP as the traditional SSVEP paradigm and could obtain as high classification accuracy of P300 as the traditional P300 paradigm. P300 did not interfere with the SSVEP response using the new hybrid paradigm presented in this paper, which was superior to the normal hybrid P300/SSVEP paradigm. Copyright © 2014 Elsevier B.V. All rights reserved.

A Hybrid Genetic Algorithm Approach for Optimal Power Flow

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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.

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...

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

Improved Hybrid Opponent System for Professional Military Training

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Michael Pelosi

2017-10-01

Full Text Available Described herein is a general-purpose software engineering architecture for autonomous, computer controlled opponent implementation in modern maneuver warfare simulation and training. The implementation has been developed, refined, and tested in the user crucible for several years. The approach represents a hybrid application of various well-known AI techniques, including domain modeling, agent modeling, and object-oriented programming. Inspired by computer chess approaches, the methodology combines this theoretical foundation with a hybrid and scalable portfolio of additional techniques. The result remains simple enough to be maintainable, comprehensible for the code writers as well as the end-users, and robust enough to handle a wide spectrum of possible mission scenarios and circumstances without modification.

A hybrid nudging-ensemble Kalman filter approach to data assimilation. Part I: application in the Lorenz system

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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.

Hybrid Microscopy: Enabling Inexpensive High-Performance Imaging through Combined Physical and Optical Magnifications.

Science.gov (United States)

Zhang, Yu Shrike; Chang, Jae-Byum; Alvarez, Mario Moisés; Trujillo-de Santiago, Grissel; Aleman, Julio; Batzaya, Byambaa; Krishnadoss, Vaishali; Ramanujam, Aishwarya Aravamudhan; Kazemzadeh-Narbat, Mehdi; Chen, Fei; Tillberg, Paul W; Dokmeci, Mehmet Remzi; Boyden, Edward S; Khademhosseini, Ali

2016-03-15

To date, much effort has been expended on making high-performance microscopes through better instrumentation. Recently, it was discovered that physical magnification of specimens was possible, through a technique called expansion microscopy (ExM), raising the question of whether physical magnification, coupled to inexpensive optics, could together match the performance of high-end optical equipment, at a tiny fraction of the price. Here we show that such "hybrid microscopy" methods--combining physical and optical magnifications--can indeed achieve high performance at low cost. By physically magnifying objects, then imaging them on cheap miniature fluorescence microscopes ("mini-microscopes"), it is possible to image at a resolution comparable to that previously attainable only with benchtop microscopes that present costs orders of magnitude higher. We believe that this unprecedented hybrid technology that combines expansion microscopy, based on physical magnification, and mini-microscopy, relying on conventional optics--a process we refer to as Expansion Mini-Microscopy (ExMM)--is a highly promising alternative method for performing cost-effective, high-resolution imaging of biological samples. With further advancement of the technology, we believe that ExMM will find widespread applications for high-resolution imaging particularly in research and healthcare scenarios in undeveloped countries or remote places.

4E analysis and multi objective optimization of a micro gas turbine and solid oxide fuel cell hybrid combined heat and power system

Science.gov (United States)

Sanaye, Sepehr; Katebi, Arash

2014-02-01

Energy, exergy, economic and environmental (4E) analysis and optimization of a hybrid solid oxide fuel cell and micro gas turbine (SOFC-MGT) system for use as combined generation of heat and power (CHP) is investigated in this paper. The hybrid system is modeled and performance related results are validated using available data in literature. Then a multi-objective optimization approach based on genetic algorithm is incorporated. Eight system design parameters are selected for the optimization procedure. System exergy efficiency and total cost rate (including capital or investment cost, operational cost and penalty cost of environmental emissions) are the two objectives. The effects of fuel unit cost, capital investment and system power output on optimum design parameters are also investigated. It is observed that the most sensitive and important design parameter in the hybrid system is fuel cell current density which has a significant effect on the balance between system cost and efficiency. The selected design point from the Pareto distribution of optimization results indicates a total system exergy efficiency of 60.7%, with estimated electrical energy cost 0.057 kW-1 h-1, and payback period of about 6.3 years for the investment.

Space – An Essential Feature of the Hybrid War

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Ioniţă Dorin

2017-03-01

Full Text Available Hybrid Warfare is an unofficial intellectual construct to describe the combination or integration of conventional and non-conventional approaches used by adversaries to avoid conventional military strengths, often times occurring below the threshold that would trigger a conventional military.

Fuzzy hybrid MCDM approach for selection of wind turbine service technicians

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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.

Combined operation of pellet injection and lower hybrid current drive on ASDEX

International Nuclear Information System (INIS)

Soeldner, F.X.; Mertens, V.; Bosch, H.S.; Kornherr, M.; Lang, R.; Leuterer, F.; Loch, R.; Sandmann, W.; Bartiromo, R.; Ushigusa, K.

1990-10-01

Simultaneous operation of Lower Hybrid-current drive and pellet injection could be successfully achieved. With peripheral ablation of the pellets by suprathermal electrons, the same net inward flux of particles is found as with deep penetration of pellets into ohmically heated plasmas. The density profile n e (r) peaks with the same increment of the peaking factor Q n = n eo / e > in both cases. The global energy confinement time rises with density, τ E ∝ anti n e , in the combined operation. (orig.)

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

Disease processes as hybrid dynamical systems

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Pietro Liò

2012-08-01

Full Text Available We investigate the use of hybrid techniques in complex processes of infectious diseases. Since predictive disease models in biomedicine require a multiscale approach for understanding the molecule-cell-tissue-organ-body interactions, heterogeneous methodologies are often employed for describing the different biological scales. Hybrid models provide effective means for complex disease modelling where the action and dosage of a drug or a therapy could be meaningfully investigated: the infection dynamics can be classically described in a continuous fashion, while the scheduling of multiple treatment discretely. We define an algebraic language for specifying general disease processes and multiple treatments, from which a semantics in terms of hybrid dynamical system can be derived. Then, the application of control-theoretic tools is proposed in order to compute the optimal scheduling of multiple therapies. The potentialities of our approach are shown in the case study of the SIR epidemic model and we discuss its applicability on osteomyelitis, a bacterial infection affecting the bone remodelling system in a specific and multiscale manner. We report that formal languages are helpful in giving a general homogeneous formulation for the different scales involved in a multiscale disease process; and that the combination of hybrid modelling and control theory provides solid grounds for computational medicine.

A hybrid method for flood simulation in small catchments combining hydrodynamic and hydrological techniques

Science.gov (United States)

Bellos, Vasilis; Tsakiris, George

2016-09-01

The study presents a new hybrid method for the simulation of flood events in small catchments. It combines a physically-based two-dimensional hydrodynamic model and the hydrological unit hydrograph theory. Unit hydrographs are derived using the FLOW-R2D model which is based on the full form of two-dimensional Shallow Water Equations, solved by a modified McCormack numerical scheme. The method is tested at a small catchment in a suburb of Athens-Greece for a storm event which occurred in February 2013. The catchment is divided into three friction zones and unit hydrographs of 15 and 30 min are produced. The infiltration process is simulated by the empirical Kostiakov equation and the Green-Ampt model. The results from the implementation of the proposed hybrid method are compared with recorded data at the hydrometric station at the outlet of the catchment and the results derived from the fully hydrodynamic model FLOW-R2D. It is concluded that for the case studied, the proposed hybrid method produces results close to those of the fully hydrodynamic simulation at substantially shorter computational time. This finding, if further verified in a variety of case studies, can be useful in devising effective hybrid tools for the two-dimensional flood simulations, which are lead to accurate and considerably faster results than those achieved by the fully hydrodynamic simulations.

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)

Experimental Investigation for Fault Diagnosis Based on a Hybrid Approach Using Wavelet Packet and Support Vector Classification

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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.

Poly (amidoamine) dendrimer-mediated hybrid formulation for combination therapy of ramipril and hydrochlorothiazide.

Science.gov (United States)

Singh, Mayank Kumar; Pooja, Deep; Kulhari, Hitesh; Jain, Sanjay Kumar; Sistla, Ramakrishna; Chauhan, Abhay Singh

2017-01-01

We present a dendrimer-based hybrid formulation strategy to explore the potential of poly (amidoamine) PAMAM dendrimers to be used as drug carriers for combination therapy of an anti-hypertensive drug ramipril (RAPL) and a diuretic hydrochlorothiazide (HCTZ). The drug-dendrimer complexes were prepared by phase-equilibration method. The results showed that the solubility of RAPL and HCTZ was dependent on dendrimer concentration and pH of dendrimer solution. The solubility profile of both RAPL and HCTZ dendrimer complexes illustrated a non-linear relationship with dendrimer concentration. At 0.8% (w/v) dendrimer concentration, solubility of RAPL was increased 4.91 folds with amine-terminated while for HCTZ, solubility enhancement was highest (3.72 folds) with carboxy-terminated. The complexes were characterized by Fourier transform infrared spectroscopy, nuclear magnetic resonance analysis and high performance liquid chromatography. In-vitro drug dissolution performance of pure drugs, individual drug loaded dendrimer formulations and hybrid formulations was studied in USP dissolution medium (pH7.0) and in simulated gastric fluid (pH1.2). Dendrimer mediated formulations showed faster and complete dissolution compared to pure RAPL or HCTZ. Surprisingly, similar pattern of dissolution profile was established with hybrid formulations as compared to individual drug loaded dendrimers. The dendrimer-based hybrid formulations were found to be stable at dark and refrigerated conditions up to 5weeks. Conclusively, the proposed formulation strategy establishes a novel multitasking platform using dendrimer for simultaneous loading and delivery of multiple drugs for pharmaceutical applications. Copyright © 2016 Elsevier B.V. All rights reserved.

Concurrent Coronary Artery and Valvular Heart Disease - Hybrid Treatment Strategies in 2013.

Science.gov (United States)

Grubb, Kendra J; Nazif, Tamim; Williams, Mathew R; George, Isaac

2013-08-01

Concomitant coronary artery disease (CAD) and valvular heart disease is an increasingly common problem in the ageing population. Hybrid procedures combine surgical and transcatheter approaches to facilitate minimally invasive surgery or to transform a single high-risk open surgery into two less risky procedures. In ideal circumstances, this strategy may decrease the surgical risk in elderly, high-risk and reoperative surgical candidates, while improving patient comfort, convenience and cost-effectiveness. Hybrid procedures can be performed in a staged fashion or as a 'one-stop' procedure in a hybrid operating suite. Increasing evidence supports the safety and short-term efficacy of hybrid valve repair or replacement and coronary revascularisation procedures. Nevertheless, important questions remain, including the optimal timing of the individual procedures and the optimal antiplatelet therapy after percutaneous coronary intervention. With ongoing advances in procedural techniques and anticoagulation strategies, as well as the accumulation of long-term outcomes data, hybrid approaches to concomitant CAD and valvular heart disease will likely become increasingly common.

Hyper- and hybrid nonlocality

Science.gov (United States)

Li, Yanna; Gessner, Manuel; Li, Weidong; Smerzi, Augusto

2018-02-01

The controlled generation and identification of quantum correlations, usually encoded in either qubits or continuous degrees of freedom, builds the foundation of quantum information science. Recently, more sophisticated approaches, involving a combination of two distinct degrees of freedom, have been proposed to improve on the traditional strategies. Hyperentanglement describes simultaneous entanglement in more than one distinct degree of freedom, whereas hybrid entanglement refers to entanglement shared between a discrete and a continuous degree of freedom. In this work we propose a scheme that allows us to combine the two approaches, and to extend them to the strongest form of quantum correlations. Specifically, we show how two identical, initially separated particles can be manipulated to produce Bell nonlocality among their spins, among their momenta, as well as across their spins and momenta. We discuss possible experimental realizations with atomic and photonic systems.

Linear and Nonlinear Rheology Combined with Dielectric Spectroscopy of Hybrid Polymer Nanocomposites for Semiconductive Applications

Science.gov (United States)

Kádár, Roland; Abbasi, Mahdi; Figuli, Roxana; Rigdahl, Mikael; Wilhelm, Manfred

2017-01-01

The linear and nonlinear oscillatory shear, extensional and combined rheology-dielectric spectroscopy of hybrid polymer nanocomposites for semiconductive applications were investigated in this study. The main focus was the influence of processing conditions on percolated poly(ethylene-butyl acrylate) (EBA) nanocomposite hybrids containing graphite nanoplatelets (GnP) and carbon black (CB). The rheological response of the samples was interpreted in terms of dispersion properties, filler distortion from processing, filler percolation, as well as the filler orientation and distribution dynamics inside the matrix. Evidence of the influence of dispersion properties was found in linear viscoelastic dynamic frequency sweeps, while the percolation of the nanocomposites was detected in nonlinearities developed in dynamic strain sweeps. Using extensional rheology, hybrid samples with better dispersion properties lead to a more pronounced strain hardening behavior, while samples with a higher volume percentage of fillers caused a drastic reduction in strain hardening. The rheo-dielectric time-dependent response showed that in the case of nanocomposites containing only GnP, the orientation dynamics leads to non-conductive samples. However, in the case of hybrids, the orientation of the GnP could be offset by the dispersing of the CB to bridge the nanoplatelets. The results were interpreted in the framework of a dual PE-BA model, where the fillers would be concentrated mainly in the BA regions. Furthermore, better dispersed hybrids obtained using mixing screws at the expense of filler distortion via extrusion processing history were emphasized through the rheo-dielectric tests. PMID:28336857

Linear and Nonlinear Rheology Combined with Dielectric Spectroscopy of Hybrid Polymer Nanocomposites for Semiconductive Applications

Directory of Open Access Journals (Sweden)

Roland Kádár

2017-01-01

Full Text Available The linear and nonlinear oscillatory shear, extensional and combined rheology-dielectric spectroscopy of hybrid polymer nanocomposites for semiconductive applications were investigated in this study. The main focus was the influence of processing conditions on percolated poly(ethylene-butyl acrylate (EBA nanocomposite hybrids containing graphite nanoplatelets (GnP and carbon black (CB. The rheological response of the samples was interpreted in terms of dispersion properties, filler distortion from processing, filler percolation, as well as the filler orientation and distribution dynamics inside the matrix. Evidence of the influence of dispersion properties was found in linear viscoelastic dynamic frequency sweeps, while the percolation of the nanocomposites was detected in nonlinearities developed in dynamic strain sweeps. Using extensional rheology, hybrid samples with better dispersion properties lead to a more pronounced strain hardening behavior, while samples with a higher volume percentage of fillers caused a drastic reduction in strain hardening. The rheo-dielectric time-dependent response showed that in the case of nanocomposites containing only GnP, the orientation dynamics leads to non-conductive samples. However, in the case of hybrids, the orientation of the GnP could be offset by the dispersing of the CB to bridge the nanoplatelets. The results were interpreted in the framework of a dual PE-BA model, where the fillers would be concentrated mainly in the BA regions. Furthermore, better dispersed hybrids obtained using mixing screws at the expense of filler distortion via extrusion processing history were emphasized through the rheo-dielectric tests.

Microwave imaging for conducting scatterers by hybrid particle swarm optimization with simulated annealing

International Nuclear Information System (INIS)

Mhamdi, B.; Grayaa, K.; Aguili, T.

2011-01-01

In this paper, a microwave imaging technique for reconstructing the shape of two-dimensional perfectly conducting scatterers by means of a stochastic optimization approach is investigated. Based on the boundary condition and the measured scattered field derived by transverse magnetic illuminations, a set of nonlinear integral equations is obtained and the imaging problem is reformulated in to an optimization problem. A hybrid approximation algorithm, called PSO-SA, is developed in this work to solve the scattering inverse problem. In the hybrid algorithm, particle swarm optimization (PSO) combines global search and local search for finding the optimal results assignment with reasonable time and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The hybrid approach elegantly combines the exploration ability of PSO with the exploitation ability of SA. Reconstruction results are compared with exact shapes of some conducting cylinders; and good agreements with the original shapes are observed.

Fuzzy Shannon Entropy: A Hybrid GIS-Based Landslide Susceptibility Mapping Method

Directory of Open Access Journals (Sweden)

Majid Shadman Roodposhti

2016-09-01

Full Text Available Assessing Landslide Susceptibility Mapping (LSM contributes to reducing the risk of living with landslides. Handling the vagueness associated with LSM is a challenging task. Here we show the application of hybrid GIS-based LSM. The hybrid approach embraces fuzzy membership functions (FMFs in combination with Shannon entropy, a well-known information theory-based method. Nine landslide-related criteria, along with an inventory of landslides containing 108 recent and historic landslide points, are used to prepare a susceptibility map. A random split into training (≈70% and testing (≈30% samples are used for training and validation of the LSM model. The study area—Izeh—is located in the Khuzestan province of Iran, a highly susceptible landslide zone. The performance of the hybrid method is evaluated using receiver operating characteristics (ROC curves in combination with area under the curve (AUC. The performance of the proposed hybrid method with AUC of 0.934 is superior to multi-criteria evaluation approaches using a subjective scheme in this research in comparison with a previous study using the same dataset through extended fuzzy multi-criteria evaluation with AUC value of 0.894, and was built on the basis of decision makers’ evaluation in the same study area.

Hybrid approximations via second order combined dynamic derivatives on time scales

Directory of Open Access Journals (Sweden)

Qin Sheng

2007-09-01

Full Text Available This article focuses on the approximation of conventional second order derivative via the combined (diamond-$\\alpha$ dynamic derivative on time scales with necessary smoothness conditions embedded. We will show the constraints under which the second order dynamic derivative provides a consistent approximation to the conventional second derivative; the cases where the dynamic derivative approximates the derivative only via a proper modification of the existing formula; and the situations in which the dynamic derivative can never approximate consistently even with the help of available structure correction methods. Constructive error analysis will be given via asymptotic expansions for practical hybrid modeling and computational applications.

A hybrid MCDM framework combined with DEMATEL-based ANP to evaluate enterprise technological innovation capabilities assessment

Directory of Open Access Journals (Sweden)

Meng-Jong Kuan

2014-08-01

Full Text Available The efficient evaluation of technological innovation capabilities of enterprises is an important factor to enhance competitiveness. This paper aims to assess and to rank technological innovation evaluation criteria in order to provide a practical insight of systematic analysis by gathering the qualified experts’ opinions combined with three methods of multi-criteria decision making approach. A framework is proposed and uses a novel hybrid multiple criteria decision-making (MCDM model to address the dependence relationships of criteria with the aid of the Decision-Making Trial and Evaluation Laboratory (DEMATEL, analytical network process (ANP and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje. The study reports that the interaction between criteria is essential and influences technological innovation capabilities; furthermore, this ranking development of technological innovation capabilities assessment is also one of key management tools for managements of other related high- tech enterprises. Managers can then judge the need to improve and determine which criteria provide the most effective direction towards improvement.

Primary gamma ray selection in a hybrid timing/imaging Cherenkov array

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Postnikov E.B.

2017-01-01

Full Text Available This work is a methodical study on hybrid reconstruction techniques for hybrid imaging/timing Cherenkov observations. This type of hybrid array is to be realized at the gamma-observatory TAIGA intended for very high energy gamma-ray astronomy (> 30 TeV. It aims at combining the cost-effective timing-array technique with imaging telescopes. Hybrid operation of both of these techniques can lead to a relatively cheap way of development of a large area array. The joint approach of gamma event selection was investigated on both types of simulated data: the image parameters from the telescopes, and the shower parameters reconstructed from the timing array. The optimal set of imaging parameters and shower parameters to be combined is revealed. The cosmic ray background suppression factor depending on distance and energy is calculated. The optimal selection technique leads to cosmic ray background suppression of about 2 orders of magnitude on distances up to 450 m for energies greater than 50 TeV.

Hybrid Modeling KMeans – Genetic Algorithms in the Health Care Data

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Tessy Badriyah

2013-06-01

Full Text Available K-Means is one of the major algorithms widely used in clustering due to its good computational performance. However, K-Means is very sensitive to the initially selected points which randomly selected, and therefore it does not always generate optimum solutions. Genetic algorithm approach can be applied to solve this problem. In this research we examine the potential of applying hybrid GA- KMeans with focus on the area of health care data. We proposed a new technique using hybrid method combining KMeans Clustering and Genetic Algorithms, called the “Hybrid K-Means Genetic Algorithms” (HKGA. HKGA combines the power of Genetic Algorithms and the efficiency of K-Means Clustering. We compare our results with other conventional algorithms and also with other published research as well. Our results demonstrate that the HKGA achieves very good results and in some cases superior to other methods. Keywords: Machine Learning, K-Means, Genetic Algorithms, Hybrid KMeans Genetic Algorithm (HGKA.

Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

International Nuclear Information System (INIS)

Meo, Santolo; Zohoori, Alireza; Vahedi, Abolfazl

2016-01-01

Highlights: • A new optimal design of flux switching permanent magnet generator is developed. • A prototype is employed to validate numerical data used for optimization. • A novel hybrid multi-objective particle swarm optimization approach is proposed. • Optimization targets are weight, cost, voltage and its total harmonic distortion. • The hybrid approach preference is proved compared with other optimization methods. - Abstract: In this paper a new hybrid approach obtained combining a multi-objective particle swarm optimization and artificial neural network is proposed for the design optimization of a direct-drive permanent magnet flux switching generators for low power wind applications. The targets of the proposed multi-objective optimization are to reduce the costs and weight of the machine while maximizing the amplitude of the induced voltage as well as minimizing its total harmonic distortion. The permanent magnet width, the stator and rotor tooth width, the rotor teeth number and stator pole number of the machine define the search space for the optimization problem. Four supervised artificial neural networks are designed for modeling the complex relationships among the weight, the cost, the amplitude and the total harmonic distortion of the output voltage respect to the quantities of the search space. Finite element analysis is adopted to generate training dataset for the artificial neural networks. Finite element analysis based model is verified by experimental results with a 1.5 kW permanent magnet flux switching generator prototype suitable for renewable energy applications, having 6/19 stator poles/rotor teeth. Finally the effectiveness of the proposed hybrid procedure is compared with the results given by conventional multi-objective optimization algorithms. The obtained results show the soundness of the proposed multi objective optimization technique and its feasibility to be adopted as suitable methodology for optimal design of permanent

Tetraoxane-pyrimidine nitrile hybrids as dual stage antimalarials.

Science.gov (United States)

Oliveira, Rudi; Guedes, Rita C; Meireles, Patrícia; Albuquerque, Inês S; Gonçalves, Lídia M; Pires, Elisabete; Bronze, Maria Rosário; Gut, Jiri; Rosenthal, Philip J; Prudêncio, Miguel; Moreira, Rui; O'Neill, Paul M; Lopes, Francisca

2014-06-12

The use of artemisinin or other endoperoxides in combination with other drugs is a strategy to prevent development of resistant strains of Plasmodium parasites. Our previous work demonstrated that hybrid compounds, comprising endoperoxides and vinyl sulfones, were capable of high activity profiles comparable to artemisinin and chloroquine while acting through two distinct mechanisms of action: oxidative stress and falcipain inhibition. In this study, we adapted this approach to a novel class of falcipain inhibitors: peptidomimetic pyrimidine nitriles. Pyrimidine tetraoxane hybrids displayed potent nanomolar activity against three strains of Plasmodium falciparum and falcipain-2, combined with low cytotoxicity. In vivo, a decrease in parasitemia and an increase in survival of mice infected with Plasmodium berghei was observed when compared to control. All tested compounds combined good blood stage activity with significant effects on liver stage parasitemia, a most welcome feature for any new class of antimalarial drug.

Approaches to Low Fuel Regression Rate in Hybrid Rocket Engines

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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.

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.

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.

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 ...

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.

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.

Hybrid Fuel Cell Technology Overview

Energy Technology Data Exchange (ETDEWEB)

None available

2001-05-31

For the purpose of this STI product and unless otherwise stated, hybrid fuel cell systems are power generation systems in which a high temperature fuel cell is combined with another power generating technology. The resulting system exhibits a synergism in which the combination performs with an efficiency far greater than can be provided by either system alone. Hybrid fuel cell designs under development include fuel cell with gas turbine, fuel cell with reciprocating (piston) engine, and designs that combine different fuel cell technologies. Hybrid systems have been extensively analyzed and studied over the past five years by the Department of Energy (DOE), industry, and others. These efforts have revealed that this combination is capable of providing remarkably high efficiencies. This attribute, combined with an inherent low level of pollutant emission, suggests that hybrid systems are likely to serve as the next generation of advanced power generation systems.

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.

A framework for combining social impact assessment and risk assessment

Energy Technology Data Exchange (ETDEWEB)

Mahmoudi, Hossein, E-mail: mahmoudi@uni-hohenheim.de [Department of Social Sciences in Agriculture, University of Hohenheim (Germany); Environmental Sciences Research Institute, Shahid Beheshti University, G.C. (Iran, Islamic Republic of); Renn, Ortwin [Department of Technology and Environmental Sociology (and DIALOGIK), University of Stuttgart (Germany); Vanclay, Frank [Department of Cultural Geography, Faculty of Spatial Sciences, University of Groningen, Groningen (Netherlands); Hoffmann, Volker [Department of Social Sciences in Agriculture, University of Hohenheim (Germany); Karami, Ezatollah [College of Agriculture, Shiraz University, Shiraz (Iran, Islamic Republic of)

2013-11-15

An increasing focus on integrative approaches is one of the current trends in impact assessment. There is potential to combine impact assessment with various other forms of assessment, such as risk assessment, to make impact assessment and the management of social risks more effective. We identify the common features of social impact assessment (SIA) and social risk assessment (SRA), and discuss the merits of a combined approach. A hybrid model combining SIA and SRA to form a new approach called, ‘risk and social impact assessment’ (RSIA) is introduced. RSIA expands the capacity of SIA to evaluate and manage the social impacts of risky projects such as nuclear energy as well as natural hazards and disasters such as droughts and floods. We outline the three stages of RSIA, namely: impact identification, impact assessment, and impact management. -- Highlights: • A hybrid model to combine SIA and SRA namely RSIA is proposed. • RSIA can provide the proper mechanism to assess social impacts of natural hazards. • RSIA can play the role of ex-post as well as ex-ante assessment. • For some complicated and sensitive cases like nuclear energy, conducting a RSIA is necessary.

A framework for combining social impact assessment and risk assessment

International Nuclear Information System (INIS)

Mahmoudi, Hossein; Renn, Ortwin; Vanclay, Frank; Hoffmann, Volker; Karami, Ezatollah

2013-01-01

An increasing focus on integrative approaches is one of the current trends in impact assessment. There is potential to combine impact assessment with various other forms of assessment, such as risk assessment, to make impact assessment and the management of social risks more effective. We identify the common features of social impact assessment (SIA) and social risk assessment (SRA), and discuss the merits of a combined approach. A hybrid model combining SIA and SRA to form a new approach called, ‘risk and social impact assessment’ (RSIA) is introduced. RSIA expands the capacity of SIA to evaluate and manage the social impacts of risky projects such as nuclear energy as well as natural hazards and disasters such as droughts and floods. We outline the three stages of RSIA, namely: impact identification, impact assessment, and impact management. -- Highlights: • A hybrid model to combine SIA and SRA namely RSIA is proposed. • RSIA can provide the proper mechanism to assess social impacts of natural hazards. • RSIA can play the role of ex-post as well as ex-ante assessment. • For some complicated and sensitive cases like nuclear energy, conducting a RSIA is necessary

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.

Welding of Thin Steel Plates by Hybrid Welding Process Combined TIG Arc with YAG Laser

Science.gov (United States)

Kim, Taewon; Suga, Yasuo; Koike, Takashi

TIG arc welding and laser welding are used widely in the world. However, these welding processes have some advantages and problems respectively. In order to improve problems and make use of advantages of the arc welding and the laser welding processes, hybrid welding process combined the TIG arc with the YAG laser was studied. Especially, the suitable welding conditions for thin steel plate welding were investigated to obtain sound weld with beautiful surface and back beads but without weld defects. As a result, it was confirmed that the shot position of the laser beam is very important to obtain sound welds in hybrid welding. Therefore, a new intelligent system to monitor the welding area using vision sensor is constructed. Furthermore, control system to shot the laser beam to a selected position in molten pool, which is formed by TIG arc, is constructed. As a result of welding experiments using these systems, it is confirmed that the hybrid welding process and the control system are effective on the stable welding of thin stainless steel plates.

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

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.

A Novel Method for Rapid Hybridization of DNA to a Solid Support

Science.gov (United States)

Pettersson, Erik; Ahmadian, Afshin; Ståhl, Patrik L.

2013-01-01

Here we present a novel approach entitled Magnetic Forced Hybridization (MFH) that provides the means for efficient and direct hybridization of target nucleic acids to complementary probes immobilized on a glass surface in less than 15 seconds at ambient temperature. In addition, detection is carried out instantly since the beads become visible on the surface. The concept of MFH was tested for quality control of array manufacturing, and was combined with a multiplex competitive hybridization (MUCH) approach for typing of Human Papilloma Virus (HPV). Magnetic Forced Hybridization of bead-DNA constructs to a surface achieves a significant reduction in diagnostic testing time. In addition, readout of results by visual inspection of the unassisted eye eliminates the need for additional expensive instrumentation. The method uses the same set of beads throughout the whole process of manipulating and washing DNA constructs prior to detection, as in the actual detection step itself. PMID:23950946

Travelling Waves in Hybrid Chemotaxis Models

KAUST Repository

Franz, Benjamin

2013-12-18

Hybrid models of chemotaxis combine agent-based models of cells with partial differential equation models of extracellular chemical signals. In this paper, travelling wave properties of hybrid models of bacterial chemotaxis are investigated. Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death. Cells consume the extracellular nutrient field (chemoattractant), which is modelled using a partial differential equation. Mesoscopic and macroscopic equations representing the behaviour of the hybrid model are derived and the existence of travelling wave solutions for these models is established. It is shown that cell proliferation is necessary for the existence of non-transient (stationary) travelling waves in hybrid models. Additionally, a numerical comparison between the wave speeds of the continuum models and the hybrid models shows good agreement in the case of weak chemotaxis and qualitative agreement for the strong chemotaxis case. In the case of slow cell adaptation, we detect oscillating behaviour of the wave, which cannot be explained by mean-field approximations. © 2013 Society for Mathematical Biology.

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.

Hybrid cryptosystem RSA - CRT optimization and VMPC

Science.gov (United States)

Rahmadani, R.; Mawengkang, H.; Sutarman

2018-03-01

Hybrid cryptosystem combines symmetric algorithms and asymmetric algorithms. This combination utilizes speeds on encryption/decryption processes of symmetric algorithms and asymmetric algorithms to secure symmetric keys. In this paper we propose hybrid cryptosystem that combine symmetric algorithms VMPC and asymmetric algorithms RSA - CRT optimization. RSA - CRT optimization speeds up the decryption process by obtaining plaintext with dp and p key only, so there is no need to perform CRT processes. The VMPC algorithm is more efficient in software implementation and reduces known weaknesses in RC4 key generation. The results show hybrid cryptosystem RSA - CRT optimization and VMPC is faster than hybrid cryptosystem RSA - VMPC and hybrid cryptosystem RSA - CRT - VMPC. Keyword : Cryptography, RSA, RSA - CRT, VMPC, Hybrid Cryptosystem.

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.

Energy Efficiency Comparison between Hydraulic Hybrid and Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Jia-Shiun Chen

2015-05-01

Full Text Available Conventional vehicles tend to consume considerable amounts of fuel, which generates exhaust gases and environmental pollution during intermittent driving cycles. Therefore, prospective vehicle designs favor improved exhaust emissions and energy consumption without compromising vehicle performance. Although pure electric vehicles feature high performance and low pollution characteristics, their limitations are their short driving range and high battery costs. Hybrid electric vehicles (HEVs are comparatively environmentally friendly and energy efficient, but cost substantially more compared with conventional vehicles. Hydraulic hybrid vehicles (HHVs are mainly operated using engines, or using alternate combinations of engine and hydraulic power sources while vehicles accelerate. When the hydraulic system accumulator is depleted, the conventional engine reengages; concurrently, brake-regenerated power is recycled and reused by employing hydraulic motor–pump modules in circulation patterns to conserve fuel and recycle brake energy. This study adopted MATLAB Simulink to construct complete HHV and HEV models for backward simulations. New European Driving Cycles were used to determine the changes in fuel economy. The output of power components and the state-of-charge of energy could be retrieved. Varying power component models, energy storage component models, and series or parallel configurations were combined into seven different vehicle configurations: the conventional manual transmission vehicle, series hybrid electric vehicle, series hydraulic hybrid vehicle, parallel hybrid electric vehicle, parallel hydraulic hybrid vehicle, purely electric vehicle, and hydraulic-electric hybrid vehicle. The simulation results show that fuel consumption was 21.80% lower in the series hydraulic hybrid vehicle compared to the series hybrid electric vehicle; additionally, fuel consumption was 3.80% lower in the parallel hybrid electric vehicle compared to the

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

Novel brewing yeast hybrids: creation and application.

Science.gov (United States)

Krogerus, Kristoffer; Magalhães, Frederico; Vidgren, Virve; Gibson, Brian

2017-01-01

The natural interspecies Saccharomyces cerevisiae × Saccharomyces eubayanus hybrid yeast is responsible for global lager beer production and is one of the most important industrial microorganisms. Its success in the lager brewing environment is due to a combination of traits not commonly found in pure yeast species, principally low-temperature tolerance, and maltotriose utilization. Parental transgression is typical of hybrid organisms and has been exploited previously for, e.g., the production of wine yeast with beneficial properties. The parental strain S. eubayanus has only been discovered recently and newly created lager yeast strains have not yet been applied industrially. A number of reports attest to the feasibility of this approach and artificially created hybrids are likely to have a significant impact on the future of lager brewing. De novo S. cerevisiae × S. eubayanus hybrids outperform their parent strains in a number of respects, including, but not restricted to, fermentation rate, sugar utilization, stress tolerance, and aroma formation. Hybrid genome function and stability, as well as different techniques for generating hybrids and their relative merits are discussed. Hybridization not only offers the possibility of generating novel non-GM brewing yeast strains with unique properties, but is expected to aid in unraveling the complex evolutionary history of industrial lager yeast.

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.

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.

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

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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.

Finite element modeling of reinforced concrete beams with a hybrid combination of steel and aramid reinforcement

International Nuclear Information System (INIS)

Hawileh, R.A.

2015-01-01

Highlights: • Modeling of concrete beams reinforced steel and FRP bars. • Developed finite element models achieved good results. • The models are validated via comparison with experimental results. • Parametric studies are performed. - Abstract: Corrosion of steel bars has an adverse effect on the life-span of reinforced concrete (RC) members and is usually associated with crack development in RC beams. Fiber reinforced polymer (FRP) bars have been recently used to reinforce concrete members in flexure due to their high tensile strength and superior corrosion resistance properties. However, FRP materials are brittle in nature, thus RC beams reinforced with such materials would exhibit a less ductile behavior when compared to similar members reinforced with conventional steel reinforcement. Recently, researchers investigated the performance of concrete beams reinforced with a hybrid combination of steel and Aramid Fiber Reinforced Polymer (AFRP) reinforcement to maintain a reasonable level of ductility in such members. The function of the AFRP bars is to increase the load-carrying capacity, while the function of the steel bars is to ensure ductility of the flexural member upon yielding in tension. This paper presents a three-dimensional (3D) finite element (FE) model that predicted the load versus mid-span deflection response of tested RC beams conducted by other researchers with a hybrid combination of steel and AFRP bars. The developed FE models account for the constituent material nonlinearities and bond–slip behavior between the reinforcing bars and adjacent concrete surfaces. It was concluded that the developed models can accurately capture the behavior and predicts the load-carrying capacity of such RC members. In addition, a parametric study is conducted using the validated models to investigate the effect of AFRP bar size, FRP material type, bond–slip action, and concrete compressive strength on the performance of concrete beams when reinforced

Self-organizing bioinspired oligothiophene–oligopeptide hybrids

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Alexey K. Shaytan

2011-09-01

Full Text Available In this minireview, we survey recent advances in the synthesis, characterization, and modeling of new oligothiophene–oligopeptide hybrids capable of forming nanostructured fibrillar aggregates in solution and on solid substrates. Compounds of this class are promising for applications because their self-assembly and stimuli-responsive properties, provided by the peptide moieties combined with the semiconducting properties of the thiophene blocks, can result in novel opportunities for the design of advanced smart materials. These bio-inspired molecular hybrids are experimentally shown to form stable fibrils as visualized by AFM and TEM. While the experimental evidence alone is not sufficient to reveal the exact molecular organization of the fibrils, theoretical approaches based on quantum chemistry calculations and large-scale atomistic molecular dynamics simulations are attempted in an effort to reveal the structure of the fibrils at the nanoscale. Based on the combined theoretical and experimental analysis, the most likely models of fibril formation and aggregation are suggested.

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

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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.

The Use of a Hybrid Strategy Combining Problem-based Learning and Magisterial Lectures to Enhance Learning

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Carlos Alberto Acosta-Nassar

2014-09-01

Full Text Available This paper addresses the problem of capturing the attention of intermediate level students in the Thermodynamics 1 course from the Mechanical and Agricultural Engineering Program, with the purpose of helping students improve their learning process. A hybrid teaching strategy was proposed based on Problem-based Learning (PBL principles combined with magisterial lectures. Digital and traditional didactic resources were also used in order to find the best mean to minimize the lack of attention in learners. The strategy was developed by sensitizing students to get involved in their formation process. PowerPoint presentations, video clips, the traditional white board and an ultra slim digital tablet board were used to develop the theoretical issues and present the solutions to the problems chosen for the PBL strategy. Finally, the strategy was evaluated and results were analyzed, indicating that using a hybrid strategy combining PBL and traditional magisterial lectures is an optimal resource to improve the learning process of students taking Thermodynamics 1. In addition, it was also concluded that the ultra slim digital tablet board is the optimal didactic resource.

Transparent and flexible conducting hybrid film combined with 3-Aminopropyltriethoxysilane-coated polymer and graphene

International Nuclear Information System (INIS)

Jung, Daesung; Ko, Yong-Hun; Cho, Jumi; Adhikari, Prashanta Dhoj; Lee, Su Il; Kim, Yooseok; Song, Wooseok; Jung, Min Wook; Jang, Sung Won; Lee, Seung Youb; An, Ki-Seok; Park, Chong-Yun

2015-01-01

A simple approach to fabricate graphene hybrid film consisted of Graphene/3-aminopropyltriethoxysilane (APTES)/polyethylene terephthalate (PET) is presented, using self-assembled monolayers (SAMs) for enhancement of conductivity. The SAMs of APTES was prepared on ultraviolet-ozone (UVO)-irradiated PET films via wet chemical technique. The density of APTES was saturated after UV treatment time of 1 h for PET films; the carrier density and the optical transmittance were 9.3 × 10 12 /cm 2 and 82% for pristine graphene and 1.16 × 10 13 /cm 2 and 86% for graphene hybrid films, respectively, and experienced at inflection point at 30 min in UV treatment time. This behavior can be explained by surface morphology transition due to coalescence or clustering of mobile and low-molecular-weight oxidized components of PET.

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...

A Hybrid Machine Learning Method for Fusing fMRI and Genetic Data: Combining both Improves Classification of Schizophrenia

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Honghui Yang

2010-10-01

Full Text Available We demonstrate a hybrid machine learning method to classify schizophrenia patients and healthy controls, using functional magnetic resonance imaging (fMRI and single nucleotide polymorphism (SNP data. The method consists of four stages: (1 SNPs with the most discriminating information between the healthy controls and schizophrenia patients are selected to construct a support vector machine ensemble (SNP-SVME. (2 Voxels in the fMRI map contributing to classification are selected to build another SVME (Voxel-SVME. (3 Components of fMRI activation obtained with independent component analysis (ICA are used to construct a single SVM classifier (ICA-SVMC. (4 The above three models are combined into a single module using a majority voting approach to make a final decision (Combined SNP-fMRI. The method was evaluated by a fully-validated leave-one-out method using 40 subjects (20 patients and 20 controls. The classification accuracy was: 0.74 for SNP-SVME, 0.82 for Voxel-SVME, 0.83 for ICA-SVMC, and 0.87 for Combined SNP-fMRI. Experimental results show that better classification accuracy was achieved by combining genetic and fMRI data than using either alone, indicating that genetic and brain function representing different, but partially complementary aspects, of schizophrenia etiopathology. This study suggests an effective way to reassess biological classification of individuals with schizophrenia, which is also potentially useful for identifying diagnostically important markers for the disorder.

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)

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...

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...

Hybrid closure of atrial septal defect: A modified approach

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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.

A combined classical genetic and high resolution two-dimensional electrophoretic approach to the assessment of the number of genes affecting hybrid male sterility in Drosophila simulans and Drosophila sechellia.

Science.gov (United States)

Zeng, L W; Singh, R S

1993-09-01

We have attempted to estimate the number of genes involved in postzygotic reproductive isolation between two closely related species, Drosophila simulans and Drosophila sechellia, by a novel approach that involves the use of high resolution two-dimensional gel electrophoresis (2DE) to examine testis proteins in parents, hybrids and fertile and sterile backcross progenies. The important results that have emerged from this study are as follows: (1) about 8% of about 1000 proteins examined showed divergence (presence/absence) between the two species; (2) by tracing individual proteins in parental, hybrid and backcross males, we were able to associate the divergent proteins with different chromosomes and found that most divergent proteins are associated with autosomes and very few with X chromosome, Y chromosome and cytoplasm; (3) when proteins showing both quantitative and qualitative differences between the two species were examined in F1 hybrid males, most (97.4%) proteins were expressed at levels between the two parents and no sign of large scale changes in spot density was observed. All the proteins observed in the two parental species were present in F1 hybrid males except two species-specific proteins that may be encoded (or regulated) by sex chromosomes; (4) when different fertile and sterile backcross male testes were compared, a few D. sechellia-specific proteins were identified to be consistently associated with male sterility. These results along with the observation that a large proportion (23.6%) of first generation backcross males were fertile show that hybrid male sterility between D. simulans and D. sechellia involves a relatively small number of genes. Role of large scale genetic changes due to general genome incompatibility is not supported. The results also suggest that the large effect of X chromosome on hybrid male sterility is not due to higher divergence of X chromosome than autosomes.

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.

Application brushless machines with combine excitation for a hybrid car and an electric car

OpenAIRE

GANDZHA S.A.; KIESSH I.E.

2015-01-01

This article shows advantages of application the brushless machines with combined excitation (excitation from permanent magnets and excitation winding) for the hybrid car and the electric car. This type of electric machine is compared with a typical brushless motor and an induction motor. The main advantage is the decrease of the dimensions of electric machine and the reduction of the price for an electronic control system. It is shown the design and the principle of operation of the electric...

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.

The new Nissan FF Hybrid + new 4-cylinder 2.5L supercharged engine. A new approach to powersource evolution

Energy Technology Data Exchange (ETDEWEB)

Minakawa, Shunichi; Onoyama, Taiichi; Ishizuka, Takashi [Nissan Motor Co., Ltd., Kanagawa (Japan)

2013-08-01

In 2013, Nissan is going to launch a technology combination of 1-Motor 2-Clutch Parallel Hybrid system and 4-cylinder 2.5L supercharged engine for Infiniti QX60 HYBRID and new Nissan Pathfinder HYBRID. This Hybrid system has been developed to have three key advantages: (1) Significant improvement in fuel economy even when Highway driving, (2) Better response and more direct feeling, (3) Lightweight system and low-cost. To achieve these objectives, Nissan fitted a 1-Motor 2-Clutch Parallel system onto a new generation CVT without Torque Converter, combined with downsized 4 cylinder 2.5L supercharged Engine, which provides better fuel economy and V6 3.5-liter class driving performance. Nissan has developed the following proprietary technologies to realize the development of this Hybrid system: - High output and compact Li-ion battery, - Innovative high speed and precise motor and clutch control. Additionally, new technologies are added to both Engine and CVT. Engine: New 4-lobes Roots supercharger with precise electrical boost control. CVT: Chain driven, high efficiency and low friction with wide cover ratio. In this paper Nissan will introduce an outline of the system, key breakthrough technologies and how low fuel economy comparable with the compact car class, has been achieved and demonstrated. (orig.)

CoFe2O4-TiO2 Hybrid Nanomaterials: Synthesis Approaches Based on the Oil-in-Water Microemulsion Reaction Method

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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.

Iterative Multiuser Equalization for Subconnected Hybrid mmWave Massive MIMO Architecture

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R. Magueta

2017-01-01

Full Text Available Millimeter waves and massive MIMO are a promising combination to achieve the multi-Gb/s required by future 5G wireless systems. However, fully digital architectures are not feasible due to hardware limitations, which means that there is a need to design signal processing techniques for hybrid analog-digital architectures. In this manuscript, we propose a hybrid iterative block multiuser equalizer for subconnected millimeter wave massive MIMO systems. The low complexity user-terminals employ pure-analog random precoders, each with a single RF chain. For the base station, a subconnected hybrid analog-digital equalizer is designed to remove multiuser interference. The hybrid equalizer is optimized using the average bit-error-rate as a metric. Due to the coupling between the RF chains in the optimization problem, the computation of the optimal solutions is too complex. To address this problem, we compute the analog part of the equalizer sequentially over the RF chains using a dictionary built from the array response vectors. The proposed subconnected hybrid iterative multiuser equalizer is compared with a recently proposed fully connected approach. The results show that the performance of the proposed scheme is close to the fully connected hybrid approach counterpart after just a few iterations.

Combining metadynamics simulation and experiments to characterize dendrimers in solution

NARCIS (Netherlands)

Pavan, G.M.; Barducci, A.; Albertazzi, L.; Parrinello, M.

2013-01-01

We report a combined theoretical-experimental approach to characterize dendrimers and Polyethylene Glycol (PEG)-dendrimer hybrids in solution. Well-tempered metadynamics simulation allows for an exhaustive sampling of the conformational fluctuations in solution. In contrast to classical molecular

QTL mapping of combining ability and heterosis of agronomic traits in rice backcross recombinant inbred lines and hybrid crosses.

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Zhen Qu

Full Text Available BACKGROUND: Combining ability effects are very effective genetic parameters in deciding the next phase of breeding programs. Although some breeding strategies on the basis of evaluating combining ability have been utilized extensively in hybrid breeding, little is known about the genetic basis of combining ability. Combining ability is a complex trait that is controlled by polygenes. With the advent and development of molecular markers, it is feasible to evaluate the genetic bases of combining ability and heterosis of elite rice hybrids through QTL analysis. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we first developed a QTL-mapping method for dissecting combining ability and heterosis of agronomic traits. With three testcross populations and a BCRIL population in rice, biometric and QTL analyses were conducted for ten agronomic traits. The significance of general combining ability and special combining ability for most of the traits indicated the importance of both additive and non-additive effects on expression levels. A large number of additive effect QTLs associated with performance per se of BCRIL and general combining ability, and dominant effect QTLs associated with special combining ability and heterosis were identified for the ten traits. CONCLUSIONS/SIGNIFICANCE: The combining ability of agronomic traits could be analyzed by the QTL mapping method. The characteristics revealed by the QTLs for combining ability of agronomic traits were similar with those by multitudinous QTLs for agronomic traits with performance per se of BCRIL. Several QTLs (1-6 in this study were identified for each trait for combining ability. It demonstrated that some of the QTLs were pleiotropic or linked tightly with each other. The identification of QTLs responsible for combining ability and heterosis in the present study provides valuable information for dissecting genetic basis of combining ability.

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.

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

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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.

PV-hybrid and mini-grid

Energy Technology Data Exchange (ETDEWEB)

NONE

2010-07-01

) Optimization of a wind/diesel hybrid configuration in a remote grid with battery implementation: Case study of Melinka Island; (23) Provisional acceptance of installations and online data submission of PV and hybrid kits in remote areas of Latin-America under the EC's EURO-SOLAR programme; (24) Experience of the Canary Islands in the development of insular 100 % RES systems and micro-grids; (25) Assessment of photovoltaic hybrid power systems in the United States; (26) Solar hybrid school project in East Malaysia; (27) Eigg Island - Electrification of a British Island by a unique PV wind hydro diesel hybrid system; (28) A pragmatic performance reporting approach for describing PV hybrid systems within mini-grids: Work in progress from IEA's PVPS Task 11 Act. 31; (29) Hybrid renewable energy systems for the supply of services in rural settlements of Mediterranean partner countries. The HYRESS project - The case study of the hybrid system - Micro grid in Egypt. Beside these lectures, the following poster contributions were presented: (1) Performance of conventional MPPT techniques in the presence of partial shielding; (2) Photovoltaic and thermal collector (PV/T) hybrid system's performance analysis under the mild climate conditions of Izmir City; (3) Influential parameters on a building integrated hybrid PVT concentrator; (4) The solution to combine and manage renewable energies in hybrid applications and mini-grids; (5) Stabilization of distribution networks with PV and vanadium redox-battery backup systems - Simulation and first experiences; (6) Control, monitoring and data acquisition architecture design for clean production of hydrogen from mini-wind energy; (7) Remote Telecom System including photovoltaic energy and H{sub 2} production by electrolysis; (8) Effective combination of solar and wind energy systems; (9) Standardisation of distributed grid support - An analogous approach for the smart grid; (10) Optimizing energy management of decentralized

Analysis of a Hybrid Wing Body Center Section Test Article

Science.gov (United States)

Wu, Hsi-Yung T.; Shaw, Peter; Przekop, Adam

2013-01-01

The hybrid wing body center section test article is an all-composite structure made of crown, floor, keel, bulkhead, and rib panels utilizing the Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) design concept. The primary goal of this test article is to prove that PRSEUS components are capable of carrying combined loads that are representative of a hybrid wing body pressure cabin design regime. This paper summarizes the analytical approach, analysis results, and failure predictions of the test article. A global finite element model of composite panels, metallic fittings, mechanical fasteners, and the Combined Loads Test System (COLTS) test fixture was used to conduct linear structural strength and stability analyses to validate the specimen under the most critical combination of bending and pressure loading conditions found in the hybrid wing body pressure cabin. Local detail analyses were also performed at locations with high stress concentrations, at Tee-cap noodle interfaces with surrounding laminates, and at fastener locations with high bearing/bypass loads. Failure predictions for different composite and metallic failure modes were made, and nonlinear analyses were also performed to study the structural response of the test article under combined bending and pressure loading. This large-scale specimen test will be conducted at the COLTS facility at the NASA Langley Research Center.

Minilaparoscopic technique for inguinal hernia repair combining transabdominal pre-peritoneal and totally extraperitoneal approaches.

Science.gov (United States)

Carvalho, Gustavo L; Loureiro, Marcelo P; Bonin, Eduardo A; Claus, Christiano P; Silva, Frederico W; Cury, Antonio M; Fernandes, Flavio A M

2012-01-01

Endoscopic surgical repair of inguinal hernia is currently conducted using 2 techniques: the totally extraperitoneal (TEP) and the transabdominal (TAPP) hernia repair. The TEP procedure is technically advantageous, because of the use of no mesh fixation and the elimination of the peritoneal flap, leading to less postoperative pain and faster recovery. The drawback is that TEP is not performed as frequently, because of its complexity and longer learning curve. In this study, we propose a hybrid technique that could potentially become the gold standard of minimally invasive inguinal hernia surgery. This will be achieved by combining established advantages of TEP and TAPP associated with the precision and cosmetics of minilaparoscopy (MINI). Between January and July 2011, 22 patients were admitted for endoscopic inguinal hernia repair. The combined technique was initiated with TAPP inspection and direct visualization of a minilaparoscopic trocar dissection of the preperitoneum space. A10-mm trocar was then placed inside the previously dissected preperitoneal space, using the same umbilical TAPP skin incision. Minilaparoscopic retroperitoneal dissection was completed by TEP, and the surgical procedure was finalized with intraperitoneal review and correction of the preperitoneal work. The minilaparoscopic TEP-TAPP combined approach for inguinal hernia is feasible, safe, and allows a simple endoscopic repair. This is achieved by combining features and advantages of both TAPP and TEP techniques using precise and sophisticated MINI instruments. Minilaparoscopic preperitoneal dissection allows a faster and easier creation of the preperitoneal space for the TEP component of the procedure.

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.

Effectiveness-implementation hybrid designs: combining elements of clinical effectiveness and implementation research to enhance public health impact.

Science.gov (United States)

Curran, Geoffrey M; Bauer, Mark; Mittman, Brian; Pyne, Jeffrey M; Stetler, Cheryl

2012-03-01

This study proposes methods for blending design components of clinical effectiveness and implementation research. Such blending can provide benefits over pursuing these lines of research independently; for example, more rapid translational gains, more effective implementation strategies, and more useful information for decision makers. This study proposes a "hybrid effectiveness-implementation" typology, describes a rationale for their use, outlines the design decisions that must be faced, and provides several real-world examples. An effectiveness-implementation hybrid design is one that takes a dual focus a priori in assessing clinical effectiveness and implementation. We propose 3 hybrid types: (1) testing effects of a clinical intervention on relevant outcomes while observing and gathering information on implementation; (2) dual testing of clinical and implementation interventions/strategies; and (3) testing of an implementation strategy while observing and gathering information on the clinical intervention's impact on relevant outcomes. The hybrid typology proposed herein must be considered a construct still in evolution. Although traditional clinical effectiveness and implementation trials are likely to remain the most common approach to moving a clinical intervention through from efficacy research to public health impact, judicious use of the proposed hybrid designs could speed the translation of research findings into routine practice.

Hybrid quantum-classical modeling of quantum dot devices

Science.gov (United States)

Kantner, Markus; Mittnenzweig, Markus; Koprucki, Thomas

2017-11-01

The design of electrically driven quantum dot devices for quantum optical applications asks for modeling approaches combining classical device physics with quantum mechanics. We connect the well-established fields of semiclassical semiconductor transport theory and the theory of open quantum systems to meet this requirement. By coupling the van Roosbroeck system with a quantum master equation in Lindblad form, we introduce a new hybrid quantum-classical modeling approach, which provides a comprehensive description of quantum dot devices on multiple scales: it enables the calculation of quantum optical figures of merit and the spatially resolved simulation of the current flow in realistic semiconductor device geometries in a unified way. We construct the interface between both theories in such a way, that the resulting hybrid system obeys the fundamental axioms of (non)equilibrium thermodynamics. We show that our approach guarantees the conservation of charge, consistency with the thermodynamic equilibrium and the second law of thermodynamics. The feasibility of the approach is demonstrated by numerical simulations of an electrically driven single-photon source based on a single quantum dot in the stationary and transient operation regime.

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.

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.

Objective-function Hybridization in Adjoint Seismic Tomography

Science.gov (United States)

Yuan, Y. O.; Bozdag, E.; Simons, F.; Gao, F.

2016-12-01

In the realm of seismic tomography, we are at the threshold of a new era of huge seismic datasets. However, how to assimilate as much information as possible from every seismogram is still a challenge. Cross-correlation measurements are generally tailored to some window selection algorithms, such as FLEXWIN (Maggie et al. 2008), to balance amplitude differences between seismic phases. However, these measurements naturally favor maximum picks in selected windows. It is also difficult to select all usable portions of seismograms in an optimum way that lots of information is generally lost, particularly the scattered waves. Instantaneous phase type of misfits extract information from every wiggle without cutting seismograms into small pieces, however, dealing with cycle skips at short periods can be challenging. For this purpose, we introduce a flexible hybrid approach for adjoint seismic tomography, to combine various objective functions. We initially focus on phase measurements and propose using instantaneous phase to take into account relatively small-magnitude scattered waves at long periods while using cross-correlation measurements on FLEXWIN windows to select distinct body-wave arrivals without complicating measurements due to non-linearities at short periods. To better deal with cycle skips and reliably measure instantaneous phases we design a new misfit function that incorporates instantaneous phase information implicitly instead of measuring it explicitly, through using normalized analytic signals. We present in our synthetic experiments how instantaneous phase, cross-correlation and their hybridization affect tomographic results. The combination of two different phase measurements in a hybrid approach constitutes progress towards using "anything and everything" in a data set, addressing data quality and measurement challenges simultaneously. We further extend hybridisation of misfit functions for amplitude measurements such as cross-correlation amplitude

Modelling and Optimising the Value of a Hybrid Solar-Wind System

Science.gov (United States)

Nair, Arjun; Murali, Kartik; Anbuudayasankar, S. P.; Arjunan, C. V.

2017-05-01

In this paper, a net present value (NPV) approach for a solar hybrid system has been presented. The system, in question aims at supporting an investor by assessing an investment in solar-wind hybrid system in a given area. The approach follow a combined process of modelling the system, with optimization of major investment-related variables to maximize the financial yield of the investment. The consideration of solar wind hybrid supply presents significant potential for cost reduction. The investment variables concern the location of solar wind plant, and its sizing. The system demand driven, meaning that its primary aim is to fully satisfy the energy demand of the customers. Therefore, the model is a practical tool in the hands of investor to assess and optimize in financial terms an investment aiming at covering real energy demand. Optimization is performed by taking various technical, logical constraints. The relation between the maximum power obtained between individual system and the hybrid system as a whole in par with the net present value of the system has been highlighted.

Hybrid Optimization for Wind Turbine Thick Airfoils

Energy Technology Data Exchange (ETDEWEB)

Grasso, F. [ECN Wind Energy, Petten (Netherlands)

2012-06-15

One important element in aerodynamic design of wind turbines is the use of specially tailored airfoils to increase the ratio of energy capture and reduce cost of energy. This work is focused on the design of thick airfoils for wind turbines by using numerical optimization. A hybrid scheme is proposed in which genetic and gradient based algorithms are combined together to improve the accuracy and the reliability of the design. Firstly, the requirements and the constraints for this class of airfoils are described; then, the hybrid approach is presented. The final part of this work is dedicated to illustrate a numerical example regarding the design of a new thick airfoil. The results are discussed and compared to existing airfoils.

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.

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.

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

Principle, function, experiences, hybrid chilled ceilings; Prinzip, Funktion, Erfahrungen. Hybrid-Kuehldecken

Energy Technology Data Exchange (ETDEWEB)

Schulz, Uwe W. [Hochschule Luzern (Switzerland). Technik und Architektur

2010-12-15

Hybrid chilled ceilings combine a radiation chilled ceiling with thermal activations of a concrete ceiling. The activation permits the utilization of alternative and/or small cold generators for the efficient night cooling. The traditional chilled ceiling grants a speedy reaction to load variations as well as a reduction of the reverberation periods. In addition, the combination supplies a draught-free insertion of air. Beside established solutions, MWH Barcol-Air (Staefa, Switzerland) also offers project-specific hybrid chilled ceilings.

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

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.

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.

Mathematical Modeling of Hybrid Electrical Engineering Systems

Directory of Open Access Journals (Sweden)

A. A. Lobaty

2016-01-01

Full Text Available A large class of systems that have found application in various industries and households, electrified transportation facilities and energy sector has been classified as electrical engineering systems. Their characteristic feature is a combination of continuous and discontinuous modes of operation, which is reflected in the appearance of a relatively new term “hybrid systems”. A wide class of hybrid systems is pulsed DC converters operating in a pulse width modulation, which are non-linear systems with variable structure. Using various methods for linearization it is possible to obtain linear mathematical models that rather accurately simulate behavior of such systems. However, the presence in the mathematical models of exponential nonlinearities creates considerable difficulties in the implementation of digital hardware. The solution can be found while using an approximation of exponential functions by polynomials of the first order, that, however, violates the rigor accordance of the analytical model with characteristics of a real object. There are two practical approaches to synthesize algorithms for control of hybrid systems. The first approach is based on the representation of the whole system by a discrete model which is described by difference equations that makes it possible to synthesize discrete algorithms. The second approach is based on description of the system by differential equations. The equations describe synthesis of continuous algorithms and their further implementation in a digital computer included in the control loop system. The paper considers modeling of a hybrid electrical engineering system using differential equations. Neglecting the pulse duration, it has been proposed to describe behavior of vector components in phase coordinates of the hybrid system by stochastic differential equations containing generally non-linear differentiable random functions. A stochastic vector-matrix equation describing dynamics of the

A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion

Energy Technology Data Exchange (ETDEWEB)

Yang, Y. X.; Van Reeth, E.; Poh, C. L., E-mail: clpoh@ntu.edu.sg [School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore 637459 (Singapore); Teo, S.-K. [Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore 138632 (Singapore); Tan, C. H. [Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore 308433 (Singapore); Tham, I. W. K. [Department of Radiation Oncology, National University Cancer Institute, Singapore 119082 (Singapore)

2015-08-15

Purpose: Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors’ proposed approach. Methods: A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. Results: The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors’ proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. Conclusions: The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.

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.

Estimation of Heterosis and Combining Ability in F1 Hybrids of Upland Cotton for Yield and Fiber Traits

International Nuclear Information System (INIS)

Arain, B.T.; Baloch, M.J.; Bughio, Q.U.A.; Sial, P.; Arain, M.A.; Baloch, A.

2015-01-01

The experimental research was conducted so as to determine the general combining ability (GCA) and specific combining ability (SCA) estimates and heterotic effects for seed cotton yield and fibre traits in 5 x 5 half diallel crosses of upland cotton (Gossypium hirsutum L.). The parental genotypes studied were; CRIS-134, IR-3701, IR-1524, FH-113 and MG-6. The characters such as bolls/plant, sympodial branches/plant, boll weight (g), plant height (cm), fibre length (mm), seed cotton yield/plant (g), seed index (g) and ginning out turn percentage were studied. The experiment was laid-out in a randomized complete block design with four replications at experimental field of the Department of Plant Breeding and Genetics, Sindh Agriculture University Tandojam, Pakistan during 2013. The results revealed that, parents and hybrids differed significantly for their mean performance regarding all the traits studied. The importance of heterotic effects was evident from the significance of parents vs. hybrids performance. The variances due to GCA and SCA were significant for all the traits except that GCA was non-significant for boll weight only whereas, SCA was non-significant for boll weight, seed index and ginning out turn percentage. The significance of GCA indicated the importance of additive genes advocating the traits while, the involvement of non-additive genes was evident from the significance of SCA variances. The GCA variances were greater than SCA for bolls per plant, plant height, seed cotton yield and lint percentage while, SCA variances were higher than GCA for sympodial branches/plant and fibre length. Parents IR-3701, FH-113 and MG-6 displayed higher positive GCA effects for bolls/plant, sympodial branches/plant, fibre length, seed cotton yield, seed index and ginning out turn percentage. The per se performance of these three parents was exactly reflected in their GCA effects and such happenings are exceptional. Such results suggested that, all three parents were

The Hybrid Advantage: Graduate Student Perspectives of Hybrid Education Courses

Science.gov (United States)

Hall, Sarah; Villareal, Donna

2015-01-01

Hybrid courses combine online and face-to-face learning environments. To organize and teach hybrid courses, instructors must understand the uses of multiple online learning tools and face-toface classroom activities to promote and monitor the progress of students. The purpose of this phenomenological study was to explore the perspectives of…

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.

Engineering Hybrid Learning Communities: The Case of a Regional Parent Community

Directory of Open Access Journals (Sweden)

Sven Strickroth

2014-09-01

Full Text Available We present an approach (and a corresponding system design for supporting regionally bound hybrid learning communities (i.e., communities which combine traditional face-to-face elements with web based media such as online community platforms, e-mail and SMS newsletters. The goal of the example community used to illustrate the approach was to support and motivate (especially hard-to-reach underprivileged parents in the education of their young children. The article describes the design process used and the challenges faced during the socio-technical system design. An analysis of the community over more than one year indicates that the hybrid approach works better than the two separated “traditional” approaches separately. Synergy effects like advertising effects from the offline trainings for the online platform and vice versa occurred and regular newsletters turned out to have a noticeable effect on the community.

Combination of microautoradiography and fluorescence in situ hybridization for identification of microorganisms degrading xenobiotic contaminants.

Science.gov (United States)

Yang, Yanru; Zarda, Annatina; Zeyer, Josef

2003-12-01

One of the central topics in environmental bioremediation research is to identify microorganisms that are capable of degrading the contaminants of interest. Here we report application of combined microautoradiography (MAR) and fluorescence in situ hybridization (FISH). The method has previously been used in a number of systems; however, here we demonstrate its feasibility in studying the degradation of xenobiotic compounds. With a model system (coculture of Pseudomonas putida B2 and Sphingomonas stygia incubated with [14C] o-nitrophenol), combination of MAR and FISH was shown to be able to successfully identify the microorganisms degrading o-nitrophenol. Compared with the conventional techniques, MAR-FISH allows fast and accurate identification of the microorganisms involved in environmental contaminant degradation.

On the development of an intrinsic hybrid composite

International Nuclear Information System (INIS)

Kießling, R; Ihlemann, J; Riemer, M; Drossel, W-G; Scharf, I; Lampke, T; Sharafiev, S; Pouya, M; Wagner, M F-X

2016-01-01

Hybrid parts, which combine low weight with high strength, are moving into the focus of the automotive industry, due to their high potential for usage in the field of crash-relevant structures. In this contribution, the development of an intrinsic hybrid composite is presented, with a focus on the manufacturing process, complex simulations of the material behaviour and material testing. The hybrid composite is made up of a continuous fibre- reinforced plastic (FRP), in which a metallic insert is integrated. The mechanical behaviour of the individual components is characterised. For material modelling, an approach is pointed out that enables modelling at large strains by directly connected rheological elements. The connection between the FRP and the metallic insert is realised by a combination of form fit and adhesive bonds. On the one hand, adhesive bonds are generated within a sol gel process. On the other hand, local form elements of the metallic insert are pressed into the FRP. We show how these form elements are generated during the macroscopic forming process. In addition, the applied sol gel process is explained. Finally, we consider design concepts for a specimen type for high strain testing of the resulting interfaces. (paper)

Expanding photovoltaic penetration with residential distributed generation from hybrid solar photovoltaic and combined heat and power systems

International Nuclear Information System (INIS)

Pearce, J.M.

2009-01-01

The recent development of small scale combined heat and power (CHP) systems has provided the opportunity for in-house power backup of residential-scale photovoltaic (PV) arrays. This paper investigates the potential of deploying a distributed network of PV + CHP hybrid systems in order to increase the PV penetration level in the U.S. The temporal distribution of solar flux, electrical and heating requirements for representative U.S. single family residences were analyzed and the results clearly show that hybridizing CHP with PV can enable additional PV deployment above what is possible with a conventional centralized electric generation system. The technical evolution of such PV + CHP hybrid systems was developed from the present (near market) technology through four generations, which enable high utilization rates of both PV-generated electricity and CHP-generated heat. A method to determine the maximum percent of PV-generated electricity on the grid without energy storage was derived and applied to an example area. The results show that a PV + CHP hybrid system not only has the potential to radically reduce energy waste in the status quo electrical and heating systems, but it also enables the share of solar PV to be expanded by about a factor of five. (author)

Prediction of a service demand using combined forecasting approach

Science.gov (United States)

Zhou, Ling

2017-08-01

Forecasting facilitates cutting down operational and management costs while ensuring service level for a logistics service provider. Our case study here is to investigate how to forecast short-term logistic demand for a LTL carrier. Combined approach depends on several forecasting methods simultaneously, instead of a single method. It can offset the weakness of a forecasting method with the strength of another, which could improve the precision performance of prediction. Main issues of combined forecast modeling are how to select methods for combination, and how to find out weight coefficients among methods. The principles of method selection include that each method should apply to the problem of forecasting itself, also methods should differ in categorical feature as much as possible. Based on these principles, exponential smoothing, ARIMA and Neural Network are chosen to form the combined approach. Besides, least square technique is employed to settle the optimal weight coefficients among forecasting methods. Simulation results show the advantage of combined approach over the three single methods. The work done in the paper helps manager to select prediction method in practice.

Pure white-light emitting ultrasmall organic-inorganic hybrid perovskite nanoclusters.

Science.gov (United States)

Teunis, Meghan B; Lawrence, Katie N; Dutta, Poulami; Siegel, Amanda P; Sardar, Rajesh

2016-10-14

Organic-inorganic hybrid perovskites, direct band-gap semiconductors, have shown tremendous promise for optoelectronic device fabrication. We report the first colloidal synthetic approach to prepare ultrasmall (∼1.5 nm diameter), white-light emitting, organic-inorganic hybrid perovskite nanoclusters. The nearly pure white-light emitting ultrasmall nanoclusters were obtained by selectively manipulating the surface chemistry (passivating ligands and surface trap-states) and controlled substitution of halide ions. The nanoclusters displayed a combination of band-edge and broadband photoluminescence properties, covering a major part of the visible region of the solar spectrum with unprecedentedly large quantum yields of ∼12% and photoluminescence lifetime of ∼20 ns. The intrinsic white-light emission of perovskite nanoclusters makes them ideal and low cost hybrid nanomaterials for solid-state lighting applications.

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.

Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

Directory of Open Access Journals (Sweden)

Laszlo Papp

2018-06-01

Full Text Available Medical imaging has evolved from a pure visualization tool to representing a primary source of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral part of this approach, as it provides complementary visual and quantitative information in the form of morphological and functional insights into the living body. As such, non-invasive imaging modalities no longer provide images only, but data, as stated recently by pioneers in the field. Today, such information, together with other, non-imaging medical data creates highly heterogeneous data sets that underpin the concept of medical big data. While the exponential growth of medical big data challenges their processing, they inherently contain information that benefits a patient-centric personalized healthcare. Novel machine learning approaches combined with high-performance distributed cloud computing technologies help explore medical big data. Such exploration and subsequent generation of knowledge require a profound understanding of the technical challenges. These challenges increase in complexity when employing hybrid, aka dual- or even multi-modality image data as input to big data repositories. This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information. First, hybrid imaging is introduced (see further contributions to this special Research Topic, also in the context of medical big data, then the technological background of machine learning as well as state-of-the-art distributed cloud computing technologies are presented, followed by the discussion of data preservation and data sharing trends. Joint data exploration endeavors in the context of in vivo radiomics and hybrid imaging will be presented. Standardization challenges of imaging protocol, delineation, feature engineering, and machine learning evaluation will be detailed. Last, the paper will provide an outlook into the future role of hybrid

Compositional Modelling of Stochastic Hybrid Systems

NARCIS (Netherlands)

Strubbe, S.N.

2005-01-01

In this thesis we present a modelling framework for compositional modelling of stochastic hybrid systems. Hybrid systems consist of a combination of continuous and discrete dynamics. The state space of a hybrid system is hybrid in the sense that it consists of a continuous component and a discrete

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

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.

Aesthethic and masticatory rehabilitation on post mandibular resection with combination of hollow obturator and hybrid prosthesis

Directory of Open Access Journals (Sweden)

Arif Rachman

2009-06-01

Full Text Available Background: Replacing tooth lost caused by caries, periodontal disease, trauma and neoplasm including ameloblastoma which requires mandibular resection is important. Purpose: The aim of the study to rehabilitation of post mandibular resection with combination of hollow obturator and hybrid prosthesis. Case: A patient 25 years old, male, for having prosthesis to cover defect due to post right mandibular resection. Case Management: In this presented case, mandibular plate was applied due to spreading defect with losing almost a half body of mandible (class II modification 2 according to cantor and curtis classification. The design of therapy was mandibular obturator using hybrid prosthesis (removable partial denture metal frame and fixed splint crown with precision attachment with hollow obturator. The application was based on several advantages: good aesthetic performance, retention, stability, lighter weight and equal share of vertical load for teeth on non surgical site. The result of control I, II, III, showed that aesthetic performance, masticatory function, speech and swallowing were in good condition. Conclusion: The design of mandibular obturator using hybrid denture with hollow obturator could rehabilitate aesthetic performance, masticatory function, speech and swallowing for patient with post mandibular resection.

[Hybrid surgery for the treatment of ovarial cysts in newborns].

Science.gov (United States)

Kozlov, Iu A; Novozhilov, V A; Rasputin, A A; Syrkin, N V; Podkamenev, A V; Iurkov, P S; Solov'ev, A A; Radikevich, O V

2013-01-01

The aim of this study was to evaluate the effect of hybrid technology (laparoscopy and open surgery) for treatment of ovarian cysts in small babies and infants. Between January 2002 and November 2012, we have performed 11 operation for neonatal ovarian cysts repaired through standard circumumbilical incision (Group I) and 16 operation with using combined hybrid laparoscopic-assisted technique (Group II). The circumumbilical incision utilized at our institution is a classic Bianchi procedure. The hybrid approach combined 2 technique - laparoscopic and open. The trocar for optic telescope was inserted through a circumumbilical incision. The one working instrument was introduced into the peritoneal cavity direct through umbilicus. Afterwords, ovarian cyst was deflated with using transabdominal needle aspiration, delivered by an extended umbilical incision and enucleated as in standard open surgery. The two groups were compared for patients demographics, operative report and early postoperative outcomes. All procedures were performed successfully with no complications rate. There were no differences in the preoperative parameters between the two groups. The differences between groups for operative and postoperative results were statistically significant (p<0.05). The mean operative time in Group I was 30.91 min. In contrast, the mean duration of the operation in the Group II was 21.56 min. The mean time to beginning and time of full enteral feeding for patients with hybrid approach were significantly shorter as for patients with umbilical incision (4.06 hours vs 10.91 hours; 13 hours vs 20.55 hours). Prolonged mean postoperative hospital stay were registered in patients of the Group I (6.36 days vs 3.19 days; p<0.05). The postoperative course and follow up was uneventful in the all patients. The experience described in this study confirms that hybrid operation can be applied for treatment of neonatal ovarian cysts with outcomes better than standard open surgery.

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.

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.

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.

Advanced Nano hybrid Materials: Surface Modification and Applications

International Nuclear Information System (INIS)

Liu, L.H.; Metivier, R.; Wang, Sh.; Wang, Sh.; Hui Wang

2012-01-01

The field of functional nano scale hybrid materials is one of the most promising and rapidly emerging research areas in materials chemistry. Nano scale hybrid materials can be broadly defined as synthetic materials with organic and inorganic components that are linked together by noncovalent bonds (Class I, linked by hydrogen bond, electrostatic force, or van der Waals force) or covalent bonds (Class II) at nanometer scale. The unlimited possible combinations of the distinct properties of inorganic, organic, or even bioactive components in a single material, either in molecular or nano scale dimensions, have attracted considerable attention. This approach provides an opportunity to create a vast number of novel advanced materials with well-controlled structures and multiple functions. The unique properties of advanced hybrid nano materials can be advantageous to many fields, such as optical and electronic materials, biomaterials, catalysis, sensing, coating, and energy storage. In this special issue, the breadth of papers shows that the hybrid materials is attracting attention, because of both growing fundamental interest, and a route to new materials. Two review articles and seven research papers that report new results of hybrid materials should gather widespread interest.

Combined Hybrid DFE and CCK Remodulator for Medium-Range Single-Carrier Underwater Acoustic Communications

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Xialin Jiang

2017-01-01

Full Text Available Advanced modulation and channel equalization techniques are essential for improving the performance of medium-range single-carrier underwater acoustic communications. In this paper, an enhanced detection scheme, hybrid time-frequency domain decision feedback equalizer (DFE combined with complementary code keying (CCK remodulator, is presented. CCK modulation technique provides strong tolerance to intersymbol interference caused by multipath propagation in underwater acoustic channels. The conventional hybrid DFE, using a frequency domain feedforward filter and a time domain feedback filter, provides good performance along with low computational complexity. The error propagation in the feedback filter, caused by feedbacking wrong decisions prior to CCK demodulation, may lead to great performance degradation. In our proposed scheme, with the help of CCK coding gain, more accurate remodulated CCK chips can be used as feedback. The proposed detection scheme is tested by the practical ocean experiments. The experimental results show that the proposed detection scheme ensures robust communications over 10-kilometre underwater acoustic channels with the data rate at 5 Kbits/s in 3 kHz of channel bandwidth.

Transbasal versus endoscopic endonasal versus combined approaches for olfactory groove meningiomas: importance of approach selection.

Science.gov (United States)

Liu, James K; Silva, Nicole A; Sevak, Ilesha A; Eloy, Jean Anderson

2018-04-01

OBJECTIVE There has been much debate regarding the optimal surgical approach for resecting olfactory groove meningiomas (OGMs). In this paper, the authors analyzed the factors involved in approach selection and reviewed the surgical outcomes in a series of OGMs. METHODS A retrospective review of 28 consecutive OGMs from a prospective database was conducted. Each tumor was treated via one of 3 approaches: transbasal approach (n = 15), pure endoscopic endonasal approach (EEA; n = 5), and combined (endoscope-assisted) transbasal-EEA (n = 8). RESULTS The mean tumor volume was greatest in the transbasal (92.02 cm 3 ) and combined (101.15 cm 3 ) groups. Both groups had significant lateral dural extension over the orbits (transbasal 73.3%, p 95%) was achieved in 20% of transbasal and 37.5% of combined cases, all due to tumor adherence to the critical neurovascular structures. The rate of CSF leakage was 0% in the transbasal and combined groups, and there was 1 leak in the EEA group (20%), resulting in an overall CSF leakage rate of 3.6%. Olfaction was preserved in 66.7% in the transbasal group. There was no significant difference in length of stay or 30-day readmission rate between the 3 groups. The mean modified Rankin Scale score was 0.79 after the transbasal approach, 2.0 after EEA, and 2.4 after the combined approach (p = 0.0604). The mean follow-up was 14.5 months (range 1-76 months). CONCLUSIONS The transbasal approach provided the best clinical outcomes with the lowest rate of complications for large tumors (> 40 mm) and for smaller tumors (OGMs invading the sinonasal cavity. Careful patient selection using an individualized, tailored strategy is important to optimize surgical outcomes.

Edge turbulence measurement in Heliotron J using a combination of hybrid probe system and fast cameras

International Nuclear Information System (INIS)

Nishino, N.; Zang, L.; Takeuchi, M.; Mizuuchi, T.; Ohshima, S.; Kasajima, K.; Sha, M.; Mukai, K.; Lee, H.Y.; Nagasaki, K.; Okada, H.; Minami, T.; Kobayashi, S.; Yamamoto, S.; Konoshima, S.; Nakamura, Y.; Sano, F.

2013-01-01

The hybrid probe system (a combination of Langmuir probes and magnetic probes), fast camera and gas puffing system were installed at the same toroidal section to study edge plasma turbulence/fluctuation in Heliotron J, especially blob (intermittent filament). Fast camera views the location of the probe head, so that the probe system yields the time evolution of the turbulence/fluctuation while the camera images the spatial profile. Gas puff at the same toroidal section was used to control the plasma density and simultaneous gas puff imaging technique. Using this combined system the filamentary structure associated with magnetic fluctuation was found in Heliotron J at the first time. The other kind of fluctuation was also observed at another experiment. This combination measurement enables us to distinguish MHD activity and electro-static activity

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.

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.

Hybrid robotic systems for upper limb rehabilitation after stroke: A review.

Science.gov (United States)

Resquín, Francisco; Cuesta Gómez, Alicia; Gonzalez-Vargas, Jose; Brunetti, Fernando; Torricelli, Diego; Molina Rueda, Francisco; Cano de la Cuerda, Roberto; Miangolarra, Juan Carlos; Pons, José Luis

2016-11-01

In recent years the combined use of functional electrical stimulation (FES) and robotic devices, called hybrid robotic rehabilitation systems, has emerged as a promising approach for rehabilitation of lower and upper limb motor functions. This paper presents a review of the state of the art of current hybrid robotic solutions for upper limb rehabilitation after stroke. For this aim, studies have been selected through a search using web databases: IEEE-Xplore, Scopus and PubMed. A total of 10 different hybrid robotic systems were identified, and they are presented in this paper. Selected systems are critically compared considering their technological components and aspects that form part of the hybrid robotic solution, the proposed control strategies that have been implemented, as well as the current technological challenges in this topic. Additionally, we will present and discuss the corresponding evidences on the effectiveness of these hybrid robotic therapies. The review also discusses the future trends in this field. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

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.

Efficiently Combining Water Reuse and Desalination through Forward Osmosis-Reverse Osmosis (FO-RO) Hybrids: A Critical Review.

Science.gov (United States)

Blandin, Gaetan; Verliefde, Arne R D; Comas, Joaquim; Rodriguez-Roda, Ignasi; Le-Clech, Pierre

2016-07-01

Forward osmosis (FO) is a promising membrane technology to combine seawater desalination and water reuse. More specifically, in a FO-reverse osmosis (RO) hybrid process, high quality water recovered from the wastewater stream is used to dilute seawater before RO treatment. As such, lower desalination energy needs and/or water augmentation can be obtained while delivering safe water for direct potable reuse thanks to the double dense membrane barrier protection. Typically, FO-RO hybrid can be a credible alternative to new desalination facilities or to implementation of stand-alone water reuse schemes. However, apart from the societal (public perception of water reuse for potable application) and water management challenges (proximity of wastewater and desalination plants), FO-RO hybrid has to overcome technical limitation such as low FO permeation flux to become economically attractive. Recent developments (i.e., improved FO membranes, use of pressure assisted osmosis, PAO) demonstrated significant improvement in water flux. However, flux improvement is associated with drawbacks, such as increased fouling behaviour, lower rejection of trace organic compounds (TrOCs) in PAO operation, and limitation in FO membrane mechanical resistance, which need to be better considered. To support successful implementation of FO-RO hybrid in the industry, further work is required regarding up-scaling to apprehend full-scale challenges in term of mass transfer limitation, pressure drop, fouling and cleaning strategies on a module scale. In addition, refined economics assessment is expected to integrate fouling and other maintenance costs/savings of the FO/PAO-RO hybrid systems, as well as cost savings from any treatment step avoided in the water recycling.

Combining accounting approaches to practice valuation.

Science.gov (United States)

Schwartzben, D; Finkler, S A

1998-06-01

Healthcare organizations that wish to acquire physician or ambulatory care practices can choose from a variety of practice valuation approaches. Basic accounting methods assess the value of a physician practice on the basis of a historical, balance-sheet description of tangible assets. Yet these methods alone are inadequate to determine the true financial value of a practice. By using a combination of accounting approaches to practice valuation that consider factors such as fair market value, opportunity cost, and discounted cash flow over a defined time period, organizations can more accurately assess a practice's actual value.

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.

Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

Science.gov (United States)

Asaithambi, Sasikumar; Rajappa, Muthaiah

2018-05-01

In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

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....

Hybrid Electric Vehicle Testing | Transportation Research | NREL

Science.gov (United States)

Hybrid Electric Vehicle Evaluations Hybrid Electric Vehicle Evaluations How Hybrid Electric Vehicles Work Hybrid electric vehicles combine a primary power source, an energy storage system, and an is used to propel the vehicle during normal drive cycles. The batteries supply additional power for

Hybrid cluster state proposal for a quantum game

International Nuclear Information System (INIS)

Paternostro, M; Tame, M S; Kim, M S

2005-01-01

We propose an experimental implementation of a quantum game algorithm in a hybrid scheme combining the quantum circuit approach and the cluster state model. An economical cluster configuration is suggested to embody a quantum version of the Prisoners' Dilemma. Our proposal is shown to be within the experimental state of the art and can be realized with existing technology.The effects of relevant experimental imperfections are also carefully examined

Socioecological Approaches for Combining Ecosystem-Based and Customary Management in Oceania

Directory of Open Access Journals (Sweden)

Shankar Aswani

2011-01-01

Full Text Available This paper summarizes various integrated methodological approaches for studying Customary Management for the purpose of designing hybrid CM-Ecosystem-Based Management (EBM systems in Oceania. Using marine conservation in the Western Solomon Islands as an example, the paper illustrates various interdisciplinary human ecological methods that can assist in designing hybrid conservation programs. The study of human-environmental interactions from a socio-ecological perspective allows us to discern people's understanding of their immediate environment, differential forms of local resource governance and use (e.g., sea tenure and foraging strategies, and existing conflicts between various stakeholders, among other social and ecological factors. More generally, the paper shows how coupled studies of natural and social processes can foster management regimes that are more adaptive and effective and that move toward holistic, ecosystem-based marine conservation in the Pacific Island region.

A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

Science.gov (United States)

Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

2016-09-01

In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic

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...

Insight and Evidence Motivating the Simplification of Dual-Analysis Hybrid Systems into Single-Analysis Hybrid Systems

Science.gov (United States)

Todling, Ricardo; Diniz, F. L. R.; Takacs, L. L.; Suarez, M. J.

2018-01-01

Many hybrid data assimilation systems currently used for NWP employ some form of dual-analysis system approach. Typically a hybrid variational analysis is responsible for creating initial conditions for high-resolution forecasts, and an ensemble analysis system is responsible for creating sample perturbations used to form the flow-dependent part of the background error covariance required in the hybrid analysis component. In many of these, the two analysis components employ different methodologies, e.g., variational and ensemble Kalman filter. In such cases, it is not uncommon to have observations treated rather differently between the two analyses components; recentering of the ensemble analysis around the hybrid analysis is used to compensated for such differences. Furthermore, in many cases, the hybrid variational high-resolution system implements some type of four-dimensional approach, whereas the underlying ensemble system relies on a three-dimensional approach, which again introduces discrepancies in the overall system. Connected to these is the expectation that one can reliably estimate observation impact on forecasts issued from hybrid analyses by using an ensemble approach based on the underlying ensemble strategy of dual-analysis systems. Just the realization that the ensemble analysis makes substantially different use of observations as compared to their hybrid counterpart should serve as enough evidence of the implausibility of such expectation. This presentation assembles numerous anecdotal evidence to illustrate the fact that hybrid dual-analysis systems must, at the very minimum, strive for consistent use of the observations in both analysis sub-components. Simpler than that, this work suggests that hybrid systems can reliably be constructed without the need to employ a dual-analysis approach. In practice, the idea of relying on a single analysis system is appealing from a cost-maintenance perspective. More generally, single-analysis systems avoid

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.

A hybrid measure-correlate-predict method for long-term wind condition assessment

International Nuclear Information System (INIS)

Zhang, Jie; Chowdhury, Souma; Messac, Achille; Hodge, Bri-Mathias

2014-01-01

the energy production of a wind farm. The best hybrid MCP strategy from 256 different combinations of MCP algorithms and reference stations is investigated and selected. The results illustrate that the many-to-one correlation in such a hybrid approach can provide a more reliable prediction of long-term on-site wind variations than that provided by the one-to-one correlations. The accuracy of the hybrid MCP method is found to be highly sensitive to the combination of individual MCP algorithms and reference stations used. It is also observed that the best combination of MCP algorithms is influenced by the length of the concurrent short-term correlation period

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.

All-optical bidirectional neural interfacing using hybrid multiphoton holographic optogenetic stimulation.

Science.gov (United States)

Paluch-Siegler, Shir; Mayblum, Tom; Dana, Hod; Brosh, Inbar; Gefen, Inna; Shoham, Shy

2015-07-01

Our understanding of neural information processing could potentially be advanced by combining flexible three-dimensional (3-D) neuroimaging and stimulation. Recent developments in optogenetics suggest that neurophotonic approaches are in principle highly suited for noncontact stimulation of network activity patterns. In particular, two-photon holographic optical neural stimulation (2P-HONS) has emerged as a leading approach for multisite 3-D excitation, and combining it with temporal focusing (TF) further enables axially confined yet spatially extended light patterns. Here, we study key steps toward bidirectional cell-targeted 3-D interfacing by introducing and testing a hybrid new 2P-TF-HONS stimulation path for accurate parallel optogenetic excitation into a recently developed hybrid multiphoton 3-D imaging system. The system is shown to allow targeted all-optical probing of in vitro cortical networks expressing channelrhodopsin-2 using a regeneratively amplified femtosecond laser source tuned to 905 nm. These developments further advance a prospective new tool for studying and achieving distributed control over 3-D neuronal circuits both in vitro and in vivo.

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.

Hybrid platform. Economical hybrid drive for commercial vehicles; Hybrid Plattform. Wirtschaftlicher Hybridantrieb fuer Nutzfahrzeuge

Energy Technology Data Exchange (ETDEWEB)

Wallner, S.; Lamke, M.; Mohr, M.; Sedlacek, M.; Speck, F.D. [ZF Friedrichshafen AG, Friedrichshafen (Germany)

2011-07-01

Up to now, hybrid systems have been adapted to their specific requirements in the various applications for trucks, buses as well as mobile and building machines. From a technical point of view, this does indeed result in optimized hybrid drives for each single vehicle application, but due to small volumes, such single developments are critical from a business point of view. ZF Friedrichshafen AG is providing a solution to the technical and economical requirements of the cost-sensitive CV segment in the form of a modular CV parallel hybrid platform composed of a hybrid module system, an inverter, a battery system, and a hybrid software integrated into the overall vehicle. Thanks to the intelligent combination of assemblies and the use of as many identical parts as possible, platforms are realized which cover power ranges between 60 and 120 kW, voltage ranges between 350 and 650 V, and battery capacities between 2 and 4 kWh. The dimensions of the platform elements are such that integration into the diverse commercial vehicle applications is made easy. The hybrid software required for the vehicle-specific functions is also configurable for the mentioned CV applications. (orig.)

Hybrid Information Flow Analysis for Programs with Arrays

Directory of Open Access Journals (Sweden)

Gergö Barany

2016-07-01

Full Text Available Information flow analysis checks whether certain pieces of (confidential data may affect the results of computations in unwanted ways and thus leak information. Dynamic information flow analysis adds instrumentation code to the target software to track flows at run time and raise alarms if a flow policy is violated; hybrid analyses combine this with preliminary static analysis. Using a subset of C as the target language, we extend previous work on hybrid information flow analysis that handled pointers to scalars. Our extended formulation handles arrays, pointers to array elements, and pointer arithmetic. Information flow through arrays of pointers is tracked precisely while arrays of non-pointer types are summarized efficiently. A prototype of our approach is implemented using the Frama-C program analysis and transformation framework. Work on a full machine-checked proof of the correctness of our approach using Isabelle/HOL is well underway; we present the existing parts and sketch the rest of the correctness argument.

A hybrid model for combining case-control and cohort studies in systematic reviews of diagnostic tests

Science.gov (United States)

Chen, Yong; Liu, Yulun; Ning, Jing; Cormier, Janice; Chu, Haitao

2014-01-01

Systematic reviews of diagnostic tests often involve a mixture of case-control and cohort studies. The standard methods for evaluating diagnostic accuracy only focus on sensitivity and specificity and ignore the information on disease prevalence contained in cohort studies. Consequently, such methods cannot provide estimates of measures related to disease prevalence, such as population averaged or overall positive and negative predictive values, which reflect the clinical utility of a diagnostic test. In this paper, we propose a hybrid approach that jointly models the disease prevalence along with the diagnostic test sensitivity and specificity in cohort studies, and the sensitivity and specificity in case-control studies. In order to overcome the potential computational difficulties in the standard full likelihood inference of the proposed hybrid model, we propose an alternative inference procedure based on the composite likelihood. Such composite likelihood based inference does not suffer computational problems and maintains high relative efficiency. In addition, it is more robust to model mis-specifications compared to the standard full likelihood inference. We apply our approach to a review of the performance of contemporary diagnostic imaging modalities for detecting metastases in patients with melanoma. PMID:25897179

Hybridization and adaptive evolution of diverse Saccharomyces species for cellulosic biofuel production.

Science.gov (United States)

Peris, David; Moriarty, Ryan V; Alexander, William G; Baker, EmilyClare; Sylvester, Kayla; Sardi, Maria; Langdon, Quinn K; Libkind, Diego; Wang, Qi-Ming; Bai, Feng-Yan; Leducq, Jean-Baptiste; Charron, Guillaume; Landry, Christian R; Sampaio, José Paulo; Gonçalves, Paula; Hyma, Katie E; Fay, Justin C; Sato, Trey K; Hittinger, Chris Todd

2017-01-01

Lignocellulosic biomass is a common resource across the globe, and its fermentation offers a promising option for generating renewable liquid transportation fuels. The deconstruction of lignocellulosic biomass releases sugars that can be fermented by microbes, but these processes also produce fermentation inhibitors, such as aromatic acids and aldehydes. Several research projects have investigated lignocellulosic biomass fermentation by the baker's yeast Saccharomyces cerevisiae . Most projects have taken synthetic biological approaches or have explored naturally occurring diversity in S. cerevisiae to enhance stress tolerance, xylose consumption, or ethanol production. Despite these efforts, improved strains with new properties are needed. In other industrial processes, such as wine and beer fermentation, interspecies hybrids have combined important traits from multiple species, suggesting that interspecies hybridization may also offer potential for biofuel research. To investigate the efficacy of this approach for traits relevant to lignocellulosic biofuel production, we generated synthetic hybrids by crossing engineered xylose-fermenting strains of S. cerevisiae with wild strains from various Saccharomyces species. These interspecies hybrids retained important parental traits, such as xylose consumption and stress tolerance, while displaying intermediate kinetic parameters and, in some cases, heterosis (hybrid vigor). Next, we exposed them to adaptive evolution in ammonia fiber expansion-pretreated corn stover hydrolysate and recovered strains with improved fermentative traits. Genome sequencing showed that the genomes of these evolved synthetic hybrids underwent rearrangements, duplications, and deletions. To determine whether the genus Saccharomyces contains additional untapped potential, we screened a genetically diverse collection of more than 500 wild, non-engineered Saccharomyces isolates and uncovered a wide range of capabilities for traits relevant to

Efficiently Combining Water Reuse and Desalination through Forward Osmosis—Reverse Osmosis (FO-RO Hybrids: A Critical Review

Directory of Open Access Journals (Sweden)

Gaetan Blandin

2016-07-01

Full Text Available Forward osmosis (FO is a promising membrane technology to combine seawater desalination and water reuse. More specifically, in a FO-reverse osmosis (RO hybrid process, high quality water recovered from the wastewater stream is used to dilute seawater before RO treatment. As such, lower desalination energy needs and/or water augmentation can be obtained while delivering safe water for direct potable reuse thanks to the double dense membrane barrier protection. Typically, FO-RO hybrid can be a credible alternative to new desalination facilities or to implementation of stand-alone water reuse schemes. However, apart from the societal (public perception of water reuse for potable application and water management challenges (proximity of wastewater and desalination plants, FO-RO hybrid has to overcome technical limitation such as low FO permeation flux to become economically attractive. Recent developments (i.e., improved FO membranes, use of pressure assisted osmosis, PAO demonstrated significant improvement in water flux. However, flux improvement is associated with drawbacks, such as increased fouling behaviour, lower rejection of trace organic compounds (TrOCs in PAO operation, and limitation in FO membrane mechanical resistance, which need to be better considered. To support successful implementation of FO-RO hybrid in the industry, further work is required regarding up-scaling to apprehend full-scale challenges in term of mass transfer limitation, pressure drop, fouling and cleaning strategies on a module scale. In addition, refined economics assessment is expected to integrate fouling and other maintenance costs/savings of the FO/PAO-RO hybrid systems, as well as cost savings from any treatment step avoided in the water recycling.

Efficiently Combining Water Reuse and Desalination through Forward Osmosis—Reverse Osmosis (FO-RO) Hybrids: A Critical Review

Science.gov (United States)

Blandin, Gaetan; Verliefde, Arne R.D.; Comas, Joaquim; Rodriguez-Roda, Ignasi; Le-Clech, Pierre

2016-01-01

Forward osmosis (FO) is a promising membrane technology to combine seawater desalination and water reuse. More specifically, in a FO-reverse osmosis (RO) hybrid process, high quality water recovered from the wastewater stream is used to dilute seawater before RO treatment. As such, lower desalination energy needs and/or water augmentation can be obtained while delivering safe water for direct potable reuse thanks to the double dense membrane barrier protection. Typically, FO-RO hybrid can be a credible alternative to new desalination facilities or to implementation of stand-alone water reuse schemes. However, apart from the societal (public perception of water reuse for potable application) and water management challenges (proximity of wastewater and desalination plants), FO-RO hybrid has to overcome technical limitation such as low FO permeation flux to become economically attractive. Recent developments (i.e., improved FO membranes, use of pressure assisted osmosis, PAO) demonstrated significant improvement in water flux. However, flux improvement is associated with drawbacks, such as increased fouling behaviour, lower rejection of trace organic compounds (TrOCs) in PAO operation, and limitation in FO membrane mechanical resistance, which need to be better considered. To support successful implementation of FO-RO hybrid in the industry, further work is required regarding up-scaling to apprehend full-scale challenges in term of mass transfer limitation, pressure drop, fouling and cleaning strategies on a module scale. In addition, refined economics assessment is expected to integrate fouling and other maintenance costs/savings of the FO/PAO-RO hybrid systems, as well as cost savings from any treatment step avoided in the water recycling. PMID:27376337

Protein Level the Influence and the Period of Combined Feed Administration in Ross 308 Hybrid in Serbia

Directory of Open Access Journals (Sweden)

Daniel Omoran

2015-10-01

Full Text Available There are various researches where during growth period of broilers are used 2 or 4 combined feed (CF recipes, with different nutritional characteristics, which can cover the chickens need, and which can also satisfy the technical-economical condition. The purpose of this work was to assess the possibility to simplify the way of feeding the chickens Ross 308 hybrid, by reducing the number of forage recipes from 4 to 3, and by administering combined feed with a protein level of 4% higher during the so-called growing period (11-33 days. In meat chickens, Ross 308 hybrid, for which the growing technology was applied with 4 types of CF: starter, I grower, II grower and finisher, at the age of 43 days, there was obtained an average body weight of 2557.81 g, an intake of 4790 g/chicken, a feed conversion ratio of 1.90, the feed costs to achieve 1 kg live weight being of 0.685 euros; in chickens fodder-fed with 3 CF structures, the body weight was of about 5.6% higher, a close feed intake, and the same feed conversion ratio, and the foraging costs related to kg live weight were of 0.15% higher. The conclusion is the simplification of broiler feeding technology reducing from 4 and 3 structures of combined feed by administering a CF with up 4p% more protein, during the so-called growing period.

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.

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.

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

Hybrid Organic/Inorganic Nanocomposites for Photovoltaic Cells

Science.gov (United States)

Liu, Ruchuan

2014-01-01

Inorganic/organic hybrid solar cells have attracted a lot of interest due to their potential in combining the advantages of both components. To understand the key issues in association with photoinduced charge separation/transportation processes and to improve overall power conversion efficiency, various combinations with nanostructures of hybrid systems have been investigated. Here, we briefly review the structures of hybrid nanocomposites studied so far, and attempt to associate the power conversion efficiency with these nanostructures. Subsequently, we are then able to summarize the factors for optimizing the performance of inorganic/organic hybrid solar cells. PMID:28788591

Direct hydrogen fuel cell systems for hybrid vehicles

Science.gov (United States)

Ahluwalia, Rajesh K.; Wang, X.

Hybridizing a fuel cell system with an energy storage system offers an opportunity to improve the fuel economy of the vehicle through regenerative braking and possibly to increase the specific power and decrease the cost of the combined energy conversion and storage systems. Even in a hybrid configuration it is advantageous to operate the fuel cell system in a load-following mode and use the power from the energy storage system when the fuel cell alone cannot meet the power demand. This paper discusses an approach for designing load-following fuel cell systems for hybrid vehicles and illustrates it by applying it to pressurized, direct hydrogen, polymer-electrolyte fuel cell (PEFC) systems for a mid-size family sedan. The vehicle level requirements relative to traction power, response time, start-up time and energy conversion efficiency are used to select the important parameters for the PEFC stack, air management system, heat rejection system and the water management system.

The Pace of Hybrid Incompatibility Evolution in House Mice.

Science.gov (United States)

Wang, Richard J; White, Michael A; Payseur, Bret A

2015-09-01

Hybrids between species are often sterile or inviable. This form of reproductive isolation is thought to evolve via the accumulation of mutations that interact to reduce fitness when combined in hybrids. Mathematical formulations of this "Dobzhansky-Muller model" predict an accelerating buildup of hybrid incompatibilities with divergence time (the "snowball effect"). Although the Dobzhansky-Muller model is widely accepted, the snowball effect has only been tested in two species groups. We evaluated evidence for the snowball effect in the evolution of hybrid male sterility among subspecies of house mice, a recently diverged group that shows partial reproductive isolation. We compared the history of subspecies divergence with patterns of quantitative trait loci (QTL) detected in F2 intercrosses between two pairs of subspecies (Mus musculus domesticus with M. m. musculus and M. m. domesticus with M. m. castaneus). We used a recently developed phylogenetic comparative method to statistically measure the fit of these data to the snowball prediction. To apply this method, QTL were partitioned as either shared or unshared in the two crosses. A heuristic partitioning based on the overlap of QTL confidence intervals produced unambiguous support for the snowball effect. An alternative approach combining data among crosses favored the snowball effect for the autosomes, but a linear accumulation of incompatibilities for the X chromosome. Reasoning that the X chromosome analyses are complicated by low mapping resolution, we conclude that hybrid male sterility loci have snowballed in house mice. Our study illustrates the power of comparative genetic mapping for understanding mechanisms of speciation. Copyright © 2015 by the Genetics Society of America.

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.

Self-Assembly of 1D/2D Hybrid Nanostructures Consisting of a Cd(II Coordination Polymer and NiAl-Layered Double Hydroxides

Directory of Open Access Journals (Sweden)

Gonzalo Abellán

2015-12-01

Full Text Available The preparation and characterization of a novel hybrid material based on the combination of a 2D-layered double hydroxide (LDH nanosheets and a 1D-coordination polymer (1D-CP has been achieved through a simple mixture of suspensions of both building blocks via an exfoliation/restacking approach. The hybrid material has been thoroughly characterized demonstrating that the 1D-CP moieties are intercalated as well as adsorbed on the surface of the LDH, giving rise to a layered assembly with the coexistence of the functionalities of their initial constituents. This hybrid represents the first example of the assembly of 1D/2D nanomaterials combining LDH with CP and opens the door for a plethora of different functional hybrid systems.

A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI

Directory of Open Access Journals (Sweden)

Piotr Stawicki

2017-04-01

Full Text Available Steady state visual evoked potentials (SSVEPs-based Brain-Computer interfaces (BCIs, as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users. As Eye tracking data is not used for activation of letters, false positives due to inappropriate dwell times are avoided. This novel approach combines the high speed of eye tracking systems and the high classification accuracies of low target SSVEP-based BCIs, leading to an optimal combination of both methods. We evaluated accuracy and speed of the proposed hybrid system with a 30-target spelling application implementing all three control approaches (pure eye tracking, SSVEP and the hybrid system with 32 participants. Although the highest information transfer rates (ITRs were achieved with pure eye tracking, a considerable amount of subjects was not able to gain sufficient control over the stand-alone eye-tracking device or the pure SSVEP system (78.13% and 75% of the participants reached reliable control, respectively. In this respect, the proposed hybrid was most universal (over 90% of users achieved reliable control, and outperformed the pure SSVEP system in terms of speed and user friendliness. The presented hybrid system might offer communication to a wider range of users in comparison to the standard techniques.

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.

Combining Compact Representation and Incremental Generation in Large Games with Sequential Strategies

DEFF Research Database (Denmark)

Bosansky, Branislav; Xin Jiang, Albert; Tambe, Milind

2015-01-01

representation of sequential strategies and linear programming, or by incremental strategy generation of iterative double-oracle methods. In this paper, we present novel hybrid of these two approaches: compact-strategy double-oracle (CS-DO) algorithm that combines the advantages of the compact representation...

Indexical Hybrid Tense Logic

DEFF Research Database (Denmark)

Blackburn, Patrick Rowan; Jørgensen, Klaus Frovin

2012-01-01

In this paper we explore the logic of now, yesterday, today and tomorrow by combining the semantic approach to indexicality pioneered by Hans Kamp [9] and refined by David Kaplan [10] with hybrid tense logic. We first introduce a special now nominal (our @now corresponds to Kamp’s original now...... operator N) and prove completeness results for both logical and contextual validity. We then add propositional constants to handle yesterday, today and tomorrow; our system correctly treats sentences like “Niels will die yesterday” as contextually unsatisfiable. Building on our completeness results for now......, we prove completeness for the richer language, again for both logical and contextual validity....

A combinatorial approach to synthetic transcription factor-promoter combinations for yeast strain engineering

DEFF Research Database (Denmark)

Dossani, Zain Y.; Apel, Amanda Reider; Szmidt-Middleton, Heather

2018-01-01

regions, we have built a library of hybrid promoters that are regulated by a synthetic transcription factor. The hybrid promoters consist of native S. cerevisiae promoters, in which the operator regions have been replaced with sequences that are recognized by the bacterial LexA DNA binding protein....... Correspondingly, the synthetic transcription factor (TF) consists of the DNA binding domain of the LexA protein, fused with the human estrogen binding domain and the viral activator domain, VP16. The resulting system with a bacterial DNA binding domain avoids the transcription of native S. cerevisiae genes...... levels, using the same synthetic TF and a given estradiol. This set of promoters, in combination with our synthetic TF, has the potential to regulate numerous genes or pathways simultaneously, to multiple desired levels, in a single strain....

The combined hybrid system: A symbiotic thermal reactor/fast reactor system for power generation and radioactive waste toxicity reduction

International Nuclear Information System (INIS)

Hollaway, W.R.

1991-08-01

If there is to be a next generation of nuclear power in the United States, then the four fundamental obstacles confronting nuclear power technology must be overcome: safety, cost, waste management, and proliferation resistance. The Combined Hybrid System (CHS) is proposed as a possible solution to the problems preventing a vigorous resurgence of nuclear power. The CHS combines Thermal Reactors (for operability, safety, and cost) and Integral Fast Reactors (for waste treatment and actinide burning) in a symbiotic large scale system. The CHS addresses the safety and cost issues through the use of advanced reactor designs, the waste management issue through the use of actinide burning, and the proliferation resistance issue through the use of an integral fuel cycle with co-located components. There are nine major components in the Combined Hybrid System linked by nineteen nuclear material mass flow streams. A computer code, CHASM, is used to analyze the mass flow rates CHS, and the reactor support ratio (the ratio of thermal/fast reactors), IFR of the system. The primary advantages of the CHS are its essentially actinide-free high-level radioactive waste, plus improved reactor safety, uranium utilization, and widening of the option base. The primary disadvantages of the CHS are the large capacity of IFRs required (approximately one MW e IFR capacity for every three MW e Thermal Reactor) and the novel radioactive waste streams produced by the CHS. The capability of the IFR to burn pure transuranic fuel, a primary assumption of this study, has yet to be proven. The Combined Hybrid System represents an attractive option for future nuclear power development; that disposal of the essentially actinide-free radioactive waste produced by the CHS provides an excellent alternative to the disposal of intact actinide-bearing Light Water Reactor spent fuel (reducing the toxicity based lifetime of the waste from roughly 360,000 years to about 510 years)

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.

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.

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.

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.

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.

Hybrid method based on embedded coupled simulation of vortex particles in grid based solution

Science.gov (United States)

Kornev, Nikolai

2017-09-01

The paper presents a novel hybrid approach developed to improve the resolution of concentrated vortices in computational fluid mechanics. The method is based on combination of a grid based and the grid free computational vortex (CVM) methods. The large scale flow structures are simulated on the grid whereas the concentrated structures are modeled using CVM. Due to this combination the advantages of both methods are strengthened whereas the disadvantages are diminished. The procedure of the separation of small concentrated vortices from the large scale ones is based on LES filtering idea. The flow dynamics is governed by two coupled transport equations taking two-way interaction between large and fine structures into account. The fine structures are mapped back to the grid if their size grows due to diffusion. Algorithmic aspects of the hybrid method are discussed. Advantages of the new approach are illustrated on some simple two dimensional canonical flows containing concentrated vortices.

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.

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.

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

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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.

Hybrid Solar Cells: Materials, Interfaces, and Devices

Science.gov (United States)

Mariani, Giacomo; Wang, Yue; Kaner, Richard B.; Huffaker, Diana L.

Photovoltaic technologies could play a pivotal role in tackling future fossil fuel energy shortages, while significantly reducing our carbon dioxide footprint. Crystalline silicon is pervasively used in single junction solar cells, taking up 80 % of the photovoltaic market. Semiconductor-based inorganic solar cells deliver relatively high conversion efficiencies at the price of high material and manufacturing costs. A great amount of research has been conducted to develop low-cost photovoltaic solutions by incorporating organic materials. Organic semiconductors are conjugated hydrocarbon-based materials that are advantageous because of their low material and processing costs and a nearly unlimited supply. Their mechanical flexibility and tunable electronic properties are among other attractions that their inorganic counterparts lack. Recently, collaborations in nanotechnology research have combined inorganic with organic semiconductors in a "hybrid" effort to provide high conversion efficiencies at low cost. Successful integration of these two classes of materials requires a profound understanding of the material properties and an exquisite control of the morphology, surface properties, ligands, and passivation techniques to ensure an optimal charge carrier generation across the hybrid device. In this chapter, we provide background information of this novel, emerging field, detailing the various approaches for obtaining inorganic nanostructures and organic polymers, introducing a multitude of methods for combining the two components to achieve the desired morphologies, and emphasizing the importance of surface manipulation. We highlight several studies that have fueled new directions for hybrid solar cell research, including approaches for maximizing efficiencies by controlling the morphologies of the inorganic component, and in situ molecular engineering via electrochemical polymerization of a polymer directly onto the inorganic nanowire surfaces. In the end, we

Combined Conformal Strongly-Coupled Magnetic Resonance for Efficient Wireless Power Transfer

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Matjaz Rozman

2017-04-01

Full Text Available This paper proposes a hybrid circuit between a conformal strongly-coupled magnetic resonance (CSCMR and a strongly-coupled magnetic resonance (SCMR, for better wireless power transmission (WPT. This combination promises to enhance the flexibility of the proposed four-loop WPT system. The maximum efficiency at various distances is achieved by combining coupling-matching between the source and transmitting coils along with the coupling factor between the transmitting and receiving coils. Furthermore, the distance between transmitting and receiving coils is investigated along with the distance relationship between the source loop and transmission coil, in order to achieve the maximum efficiency of the proposed hybrid WPT system. The results indicate that the proposed approach can be effectively employed at distances comparatively smaller than the maximum distance without frequency matching. The achievable efficiency can be as high as 84% for the whole working range of the transmitter. In addition, the proposed hybrid system allows more spatial freedom compared to existing chargers.

Toyota hybrid synergy drive

Energy Technology Data Exchange (ETDEWEB)

Gautschi, H.

2008-07-01

This presentation made at the Swiss 2008 research conference on traffic by Hannes Gautschi, director of service and training at the Toyota company in Switzerland, takes a look at Toyota's hybrid drive vehicles. The construction of the vehicles and their combined combustion engines and electric generators and drives is presented and the combined operation of these components is described. Braking and energy recovery are discussed. Figures on the performance, fuel consumption and CO{sub 2} output of the hybrid vehicles are compared with those of conventional vehicles.

Application brushless machines with combine excitation for a hybrid car and an electric car

Directory of Open Access Journals (Sweden)

Gandzha S.A.

2015-08-01

Full Text Available This article shows advantages of application the brushless machines with combined excitation (excitation from permanent magnets and excitation winding for the hybrid car and the electric car. This type of electric machine is compared with a typical brushless motor and an induction motor. The main advantage is the decrease of the dimensions of electric machine and the reduction of the price for an electronic control system. It is shown the design and the principle of operation of the electric machine. The machine was modeled using Solidworks program for creating design and Maxwell program for the magnetic field analysis. The result of tests is shown as well.

Application of a hybrid method based on the combination of genetic algorithm and Hopfield neural network for burnable poison placement

International Nuclear Information System (INIS)

Khoshahval, F.; Fadaei, A.

2012-01-01

Highlights: ► The performance of GA, HNN and combination of them in BPP optimization in PWR core are adequate. ► It seems HNN + GA arrives to better final parameter value in comparison with the two other methods. ► The computation time for HNN + GA is higher than GA and HNN. Thus a trade-off is necessary. - Abstract: In the last decades genetic algorithm (GA) and Hopfield Neural Network (HNN) have attracted considerable attention for the solution of optimization problems. In this paper, a hybrid optimization method based on the combination of the GA and HNN is introduced and applied to the burnable poison placement (BPP) problem to increase the quality of the results. BPP in a nuclear reactor core is a combinatorial and complicated problem. Arrangement and the worth of the burnable poisons (BPs) has an impressive effect on the main control parameters of a nuclear reactor. Improper design and arrangement of the BPs can be dangerous with respect to the nuclear reactor safety. In this paper, increasing BP worth along with minimizing the radial power peaking are considered as objective functions. Three optimization algorithms, genetic algorithm, Hopfield neural network optimization and a hybrid optimization method, are applied to the BPP problem and their efficiencies are compared. The hybrid optimization method gives better result in finding a better BP arrangement.

Evaluation of Edge Assembly Crossover for Hybrid GA

OpenAIRE

Yoshihara, Ikuo; Sato, Masakazu; Nguyen, Hung Dinh; Yamanori, Kunihito

2004-01-01

Abstract ###Traveling Salesman Problem (TSP) is one of the representative combinatorial optimization prob-###lems. The promising approach to solve TSP is Genetic Algorithm (GA). GA has global search ability, ###and heuristic is used in order to compensate local search ability, because GA is lack of local search abil-###ity. Hybrid (GA (HGA) combined with heuristics can be expected to obtain high quality solutions.We ###employ Lin-Kernighan heuristics which is very effective in TSP. Because cr...

Hybrid III-V/silicon lasers

Science.gov (United States)

Kaspar, P.; Jany, C.; Le Liepvre, A.; Accard, A.; Lamponi, M.; Make, D.; Levaufre, G.; Girard, N.; Lelarge, F.; Shen, A.; Charbonnier, P.; Mallecot, F.; Duan, G.-H.; Gentner, J.-.; Fedeli, J.-M.; Olivier, S.; Descos, A.; Ben Bakir, B.; Messaoudene, S.; Bordel, D.; Malhouitre, S.; Kopp, C.; Menezo, S.

2014-05-01

The lack of potent integrated light emitters is one of the bottlenecks that have so far hindered the silicon photonics platform from revolutionizing the communication market. Photonic circuits with integrated light sources have the potential to address a wide range of applications from short-distance data communication to long-haul optical transmission. Notably, the integration of lasers would allow saving large assembly costs and reduce the footprint of optoelectronic products by combining photonic and microelectronic functionalities on a single chip. Since silicon and germanium-based sources are still in their infancy, hybrid approaches using III-V semiconductor materials are currently pursued by several research laboratories in academia as well as in industry. In this paper we review recent developments of hybrid III-V/silicon lasers and discuss the advantages and drawbacks of several integration schemes. The integration approach followed in our laboratory makes use of wafer-bonded III-V material on structured silicon-on-insulator substrates and is based on adiabatic mode transfers between silicon and III-V waveguides. We will highlight some of the most interesting results from devices such as wavelength-tunable lasers and AWG lasers. The good performance demonstrates that an efficient mode transfer can be achieved between III-V and silicon waveguides and encourages further research efforts in this direction.

Advances in hybrid optics physical sensors for extreme environments

Science.gov (United States)

Riza, Nabeel A.

2010-04-01

Highlighted are novel innovations in hybrid optical design physical sensors for extreme environments. Various hybrid design compositions are proposed that are suited for a particular sensor application. Examples includes combining freespace (wireless) and fiber-optics (wired) for gas turbine sensing and combining single crystal and sintered Silicon Carbide (SiC) materials for robust extreme environment Coefficent of Thermal Expansion (CTE) matched frontend probe design. Sensor signal processing also includes the hybrid theme where for example Black-Body radiation thermometry (pyrometry) is combined with laser interferometry to provide extreme temperature measurements. The hybrid theme also operates on the optical device level where a digital optical device such as a Digital Micromirror Device (DMD) is combined with an analog optical device such as an Electronically Controlled Variable Focal Length Lens (ECVFL) to deliver a smart and compressive Three Dimensional (3-D) imaging sensor for remote scene and object shape capture including both ambient light (passive) mode and active laser targeting and receive processing. Within a device level, the hybrid theme also operates via combined analog and digital control such as within a wavelength-coded variable optical delay line. These powerful hybrid design optical sensors have numerous applications in engineering and science applications from the military to the commercial/industrial sectors.

ADAPTING HYBRID MACHINE TRANSLATION TECHNIQUES FOR CROSS-LANGUAGE TEXT RETRIEVAL SYSTEM

Directory of Open Access Journals (Sweden)

P. ISWARYA

2017-03-01

Full Text Available This research work aims in developing Tamil to English Cross - language text retrieval system using hybrid machine translation approach. The hybrid machine translation system is a combination of rule based and statistical based approaches. In an existing word by word translation system there are lot of issues and some of them are ambiguity, Out-of-Vocabulary words, word inflections, and improper sentence structure. To handle these issues, proposed architecture is designed in such a way that, it contains Improved Part-of-Speech tagger, machine learning based morphological analyser, collocation based word sense disambiguation procedure, semantic dictionary, and tense markers with gerund ending rules, and two pass transliteration algorithm. From the experimental results it is clear that the proposed Tamil Query based translation system achieves significantly better translation quality over existing system, and reaches 95.88% of monolingual performance.

A Method for Estimating Urban Background Concentrations in Support of Hybrid Air Pollution Modeling for Environmental Health Studies

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Saravanan Arunachalam

2014-10-01

Full Text Available Exposure studies rely on detailed characterization of air quality, either from sparsely located routine ambient monitors or from central monitoring sites that may lack spatial representativeness. Alternatively, some studies use models of various complexities to characterize local-scale air quality, but often with poor representation of background concentrations. A hybrid approach that addresses this drawback combines a regional-scale model to provide background concentrations and a local-scale model to assess impacts of local sources. However, this approach may double-count sources in the study regions. To address these limitations, we carefully define the background concentration as the concentration that would be measured if local sources were not present, and to estimate these background concentrations we developed a novel technique that combines space-time ordinary kriging (STOK of observations with outputs from a detailed chemistry-transport model with local sources zeroed out. We applied this technique to support an exposure study in Detroit, Michigan, for several pollutants (including NOx and PM2.5, and evaluated the estimated hybrid concentrations (calculated by combining the background estimates that addresses this issue of double counting with local-scale dispersion model estimates using observations. Our results demonstrate the strength of this approach specifically by eliminating the problem of double-counting reported in previous hybrid modeling approaches leading to improved estimates of background concentrations, and further highlight the relative importance of NOx vs. PM2.5 in their relative contributions to total concentrations. While a key limitation of this approach is the requirement for another detailed model simulation to avoid double-counting, STOK improves the overall characterization of background concentrations at very fine spatial scales.

A Hybrid Approach to Spatial Multiplexing in Multiuser MIMO Downlinks

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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.

Course on hybrid calculation

International Nuclear Information System (INIS)

Weill, J.; Tellier; Bonnemay; Craigne; Chareton; Di Falco

1969-02-01

After a definition of hybrid calculation (combination of analogue and digital calculation) with a distinction between series and parallel hybrid computing, and a description of a hybrid computer structure and of task sharing between computers, this course proposes a description of hybrid hardware used in Saclay and Cadarache computing centres, and of operations performed by these systems. The next part addresses issues related to programming languages and software. The fourth part describes how a problem is organised for its processing on these computers. Methods of hybrid analysis are then addressed: resolution of optimisation problems, of partial differential equations, and of integral equations by means of different methods (gradient, maximum principle, characteristics, functional approximation, time slicing, Monte Carlo, Neumann iteration, Fischer iteration)

Taxonomic Identification of Mediterranean Pines and Their Hybrids Based on the High Resolution Melting (HRM) and trnL Approaches: From Cytoplasmic Inheritance to Timber Tracing

Science.gov (United States)

Ganopoulos, Ioannis; Aravanopoulos, Filippos; Madesis, Panagiotis; Pasentsis, Konstantinos; Bosmali, Irene; Ouzounis, Christos; Tsaftaris, Athanasios

2013-01-01

Fast and accurate detection of plant species and their hybrids using molecular tools will facilitate the assessment and monitoring of local biodiversity in an era of climate and environmental change. Herein, we evaluate the utility of the plastid trnL marker for species identification applied to Mediterranean pines (Pinus spp.). Our results indicate that trnL is a very sensitive marker for delimiting species biodiversity. Furthermore, High Resolution Melting (HRM) analysis was exploited as a molecular fingerprint for fast and accurate discrimination of Pinus spp. DNA sequence variants. The trnL approach and the HRM analyses were extended to wood samples of two species (Pinus nigra and Pinus sylvestris) with excellent results, congruent to those obtained using leaf tissue. Both analyses demonstrate that hybrids from the P. brutia (maternal parent) × P. halepensis (paternal parent) cross, exhibit the P. halepensis profile, confirming paternal plastid inheritance in Group Halepensis pines. Our study indicates that a single one-step reaction method and DNA marker are sufficient for the identification of Mediterranean pines, their hybrids and the origin of pine wood. Furthermore, our results underline the potential for certain DNA regions to be used as novel biological information markers combined with existing morphological characters and suggest a relatively reliable and open taxonomic system that can link DNA variation to phenotype-based species or hybrid assignment status and direct taxa identification from recalcitrant tissues such as wood samples. PMID:23577179

Simultaneous Optimization of Topology and Component Sizes for Double Planetary Gear Hybrid Powertrains

Directory of Open Access Journals (Sweden)

Weichao Zhuang

2016-05-01

Full Text Available Hybrid powertrain technologies are successful in the passenger car market and have been actively developed in recent years. Optimal topology selection, component sizing, and controls are required for competitive hybrid vehicles, as multiple goals must be considered simultaneously: fuel efficiency, emissions, performance, and cost. Most of the previous studies explored these three design dimensions separately. In this paper, two novel frameworks combining these three design dimensions together are presented and compared. One approach is nested optimization which searches through the whole design space exhaustively. The second approach is called enhanced iterative optimization, which executes the topology optimization and component sizing alternately. A case study shows that the later method can converge to the global optimal design generated from the nested optimization, and is much more computationally efficient. In addition, we also address a known issue of optimal designs: their sensitivity to parameters, such as varying vehicle weight, which is a concern especially for the design of hybrid buses. Therefore, the iterative optimization process is applied to design a robust multi-mode hybrid electric bus under different loading scenarios as the final design challenge of this paper.

Conceptual Design and Optimal Power Control Strategy for AN Eco-Friendly Hybrid Vehicle

Science.gov (United States)

Nasiri, N. Mir; Chieng, Frederick T. A.

2011-06-01

This paper presents a new concept for a hybrid vehicle using a torque and speed splitting technique. It is implemented by the newly developed controller in combination with a two degree of freedom epicyclic gear transmission. This approach enables optimization of the power split between the less powerful electrical motor and more powerful engine while driving a car load. The power split is fundamentally a dual-energy integration mechanism as it is implemented by using the epicyclic gear transmission that has two inputs and one output for a proper power distribution. The developed power split control system manages the operation of both the inputs to have a known output with the condition of maintaining optimum operating efficiency of the internal combustion engine and electrical motor. This system has a huge potential as it is possible to integrate all the features of hybrid vehicle known to-date such as the regenerative braking system, series hybrid, parallel hybrid, series/parallel hybrid, and even complex hybrid (bidirectional). By using the new power split system it is possible to further reduce fuel consumption and increase overall efficiency.

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

Energy Technology Data Exchange (ETDEWEB)

Wichapa, Narong; Khokhajaikiat, Porntep

2017-07-01

Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

Using the hybrid fuzzy goal programming model and hybrid genetic algorithm to solve a multi-objective location routing problem for infectious waste disposaL

International Nuclear Information System (INIS)

Wichapa, Narong; Khokhajaikiat, Porntep

2017-01-01

Disposal of infectious waste remains one of the most serious problems in the social and environmental domains of almost every nation. Selection of new suitable locations and finding the optimal set of transport routes to transport infectious waste, namely location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Design/methodology/approach: Due to the complexity of this problem, location routing problem for a case study, forty hospitals and three candidate municipalities in sub-Northeastern Thailand, was divided into two phases. The first phase is to choose suitable municipalities using hybrid fuzzy goal programming model which hybridizes the fuzzy analytic hierarchy process and fuzzy goal programming. The second phase is to find the optimal routes for each selected municipality using hybrid genetic algorithm which hybridizes the genetic algorithm and local searches including 2-Opt-move, Insertion-move and ?-interchange-move. Findings: The results indicate that the hybrid fuzzy goal programming model can guide the selection of new suitable municipalities, and the hybrid genetic algorithm can provide the optimal routes for a fleet of vehicles effectively. Originality/value: The novelty of the proposed methodologies, hybrid fuzzy goal programming model, is the simultaneous combination of both intangible and tangible factors in order to choose new suitable locations, and the hybrid genetic algorithm can be used to determine the optimal routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation, efficiently.

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

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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.

Hybrid Engine Powered City Car: Fuzzy Controlled Approach

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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.

A Game-Theoretic approach to Fault Diagnosis of Hybrid Systems

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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.

Economic Evaluation of a Hybrid Desalination System Combining Forward and Reverse Osmosis

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Choi, Yongjun; Cho, Hyeongrak; Shin, Yonghyun; Jang, Yongsun; Lee, Sangho

2015-01-01

This study seeks to evaluate the performance and economic feasibility of the forward osmosis (FO)–reverse osmosis (RO) hybrid process; to propose a guideline by which this hybrid process might be more price-competitive in the field. A solution-diffusion model modified with film theory was applied to analyze the effects of concentration polarization, water, and salt transport coefficient on flux, recovery, seawater concentration, and treated wastewater of the FO process of an FO-RO hybrid system. A simple cost model was applied to analyze the effects of flux; recovery of the FO process; energy; and membrane cost on the FO-RO hybrid process. The simulation results showed that the water transport coefficient and internal concentration polarization resistance are very important factors that affect performance in the FO process; however; the effect of the salt transport coefficient does not seem to be large. It was also found that the flux and recovery of the FO process, the FO membrane, and the electricity cost are very important factors that influence the water cost of an FO-RO hybrid system. This hybrid system can be price-competitive with RO systems when its recovery rate is very high, the flux and the membrane cost of the FO are similar to those of the RO, and the electricity cost is expensive. The most important thing in commercializing the FO process is enhancing performance (e.g.; flux and the recovery of FO membranes). PMID:26729176

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

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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...

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...

Modeling protective anti-tumor immunity via preventative cancer vaccines using a hybrid agent-based and delay differential equation approach.

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Kim, Peter S; Lee, Peter P

2012-01-01

A next generation approach to cancer envisions developing preventative vaccinations to stimulate a person's immune cells, particularly cytotoxic T lymphocytes (CTLs), to eliminate incipient tumors before clinical detection. The purpose of our study is to quantitatively assess whether such an approach would be feasible, and if so, how many anti-cancer CTLs would have to be primed against tumor antigen to provide significant protection. To understand the relevant dynamics, we develop a two-compartment model of tumor-immune interactions at the tumor site and the draining lymph node. We model interactions at the tumor site using an agent-based model (ABM) and dynamics in the lymph node using a system of delay differential equations (DDEs). We combine the models into a hybrid ABM-DDE system and investigate dynamics over a wide range of parameters, including cell proliferation rates, tumor antigenicity, CTL recruitment times, and initial memory CTL populations. Our results indicate that an anti-cancer memory CTL pool of 3% or less can successfully eradicate a tumor population over a wide range of model parameters, implying that a vaccination approach is feasible. In addition, sensitivity analysis of our model reveals conditions that will result in rapid tumor destruction, oscillation, and polynomial rather than exponential decline in the tumor population due to tumor geometry.

Optimized molecular reconstruction procedure combining hybrid reverse Monte Carlo and molecular dynamics

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Bousige, Colin; Boţan, Alexandru; Coasne, Benoît, E-mail: coasne@mit.edu [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); UMI 3466 CNRS-MIT, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Ulm, Franz-Josef [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); Pellenq, Roland J.-M. [Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); UMI 3466 CNRS-MIT, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 (United States); CINaM, CNRS/Aix Marseille Université, Campus de Luminy, 13288 Marseille Cedex 09 (France)

2015-03-21

We report an efficient atom-scale reconstruction method that consists of combining the Hybrid Reverse Monte Carlo algorithm (HRMC) with Molecular Dynamics (MD) in the framework of a simulated annealing technique. In the spirit of the experimentally constrained molecular relaxation technique [Biswas et al., Phys. Rev. B 69, 195207 (2004)], this modified procedure offers a refined strategy in the field of reconstruction techniques, with special interest for heterogeneous and disordered solids such as amorphous porous materials. While the HRMC method generates physical structures, thanks to the use of energy penalties, the combination with MD makes the method at least one order of magnitude faster than HRMC simulations to obtain structures of similar quality. Furthermore, in order to ensure the transferability of this technique, we provide rational arguments to select the various input parameters such as the relative weight ω of the energy penalty with respect to the structure optimization. By applying the method to disordered porous carbons, we show that adsorption properties provide data to test the global texture of the reconstructed sample but are only weakly sensitive to the presence of defects. In contrast, the vibrational properties such as the phonon density of states are found to be very sensitive to the local structure of the sample.

Cooperative Control for A Hybrid Rehabilitation System Combining Functional Electrical Stimulation and Robotic Exoskeleton

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Dingguo Zhang

2017-12-01

Full Text Available Functional electrical stimulation (FES and robotic exoskeletons are two important technologies widely used for physical rehabilitation of paraplegic patients. We developed a hybrid rehabilitation system (FEXO Knee that combined FES and an exoskeleton for swinging movement control of human knee joints. This study proposed a novel cooperative control strategy, which could realize arbitrary distribution of torque generated by FES and exoskeleton, and guarantee harmonic movements. The cooperative control adopted feedfoward control for FES and feedback control for exoskeleton. A parameter regulator was designed to update key parameters in real time to coordinate FES controller and exoskeleton controller. Two muscle groups (quadriceps and hamstrings were stimulated to generate active torque for knee joint in synchronization with torque compensation from exoskeleton. The knee joint angle and the interactive torque between exoskeleton and shank were used as feedback signals for the control system. Central pattern generator (CPG was adopted that acted as a phase predictor to deal with phase confliction of motor patterns, and realized synchronization between the two different bodies (shank and exoskeleton. Experimental evaluation of the hybrid FES-exoskeleton system was conducted on five healthy subjects and four paraplegic patients. Experimental results and statistical analysis showed good control performance of the cooperative control on torque distribution, trajectory tracking, and phase synchronization.

Synergistic Combination of Unquenching and Plasmonic Fluorescence Enhancement in Fluorogenic Nucleic Acid Hybridization Probes.

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Vietz, Carolin; Lalkens, Birka; Acuna, Guillermo P; Tinnefeld, Philip

2017-10-11

Fluorogenic nucleic acid hybridization probes are widely used for detecting and quantifying nucleic acids. The achieved sensitivity strongly depends on the contrast between a quenched closed form and an unquenched opened form with liberated fluorescence. So far, this contrast was improved by improving the quenching efficiency of the closed form. In this study, we modularly combine these probes with optical antennas used for plasmonic fluorescence enhancement and study the effect of the nanophotonic structure on the fluorescence of the quenched and the opened form. As quenched fluorescent dyes are usually enhanced more by fluorescence enhancement, a detrimental reduction of the contrast between closed and opened form was anticipated. In contrast, we could achieve a surprising increase of the contrast with full additivity of quenching of the dark form and fluorescence enhancement of the bright form. Using single-molecule experiments, we demonstrate that the additivity of the two mechanisms depends on the perfect quenching in the quenched form, and we delineate the rules for new nucleic acid probes for enhanced contrast and absolute brightness. Fluorogenic hybridization probes optimized not only for quenching but also for the brightness of the open form might find application in nucleic acid assays with PCR avoiding detection schemes.

Cooperative Control for A Hybrid Rehabilitation System Combining Functional Electrical Stimulation and Robotic Exoskeleton.

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Zhang, Dingguo; Ren, Yong; Gui, Kai; Jia, Jie; Xu, Wendong

2017-01-01

Functional electrical stimulation (FES) and robotic exoskeletons are two important technologies widely used for physical rehabilitation of paraplegic patients. We developed a hybrid rehabilitation system (FEXO Knee) that combined FES and an exoskeleton for swinging movement control of human knee joints. This study proposed a novel cooperative control strategy, which could realize arbitrary distribution of torque generated by FES and exoskeleton, and guarantee harmonic movements. The cooperative control adopted feedfoward control for FES and feedback control for exoskeleton. A parameter regulator was designed to update key parameters in real time to coordinate FES controller and exoskeleton controller. Two muscle groups (quadriceps and hamstrings) were stimulated to generate active torque for knee joint in synchronization with torque compensation from exoskeleton. The knee joint angle and the interactive torque between exoskeleton and shank were used as feedback signals for the control system. Central pattern generator (CPG) was adopted that acted as a phase predictor to deal with phase confliction of motor patterns, and realized synchronization between the two different bodies (shank and exoskeleton). Experimental evaluation of the hybrid FES-exoskeleton system was conducted on five healthy subjects and four paraplegic patients. Experimental results and statistical analysis showed good control performance of the cooperative control on torque distribution, trajectory tracking, and phase synchronization.

An SVM model with hybrid kernels for hydrological time series

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Wang, C.; Wang, H.; Zhao, X.; Xie, Q.

2017-12-01

Support Vector Machine (SVM) models have been widely applied to the forecast of climate/weather and its impact on other environmental variables such as hydrologic response to climate/weather. When using SVM, the choice of the kernel function plays the key role. Conventional SVM models mostly use one single type of kernel function, e.g., radial basis kernel function. Provided that there are several featured kernel functions available, each having its own advantages and drawbacks, a combination of these kernel functions may give more flexibility and robustness to SVM approach, making it suitable for a wide range of application scenarios. This paper presents such a linear combination of radial basis kernel and polynomial kernel for the forecast of monthly flowrate in two gaging stations using SVM approach. The results indicate significant improvement in the accuracy of predicted series compared to the approach with either individual kernel function, thus demonstrating the feasibility and advantages of such hybrid kernel approach for SVM applications.

Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

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Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

2018-04-01

Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.