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Sample records for hybrid classification scheme

  1. Small-scale classification schemes

    DEFF Research Database (Denmark)

    Hertzum, Morten

    2004-01-01

    . While coordination mechanisms focus on how classification schemes enable cooperation among people pursuing a common goal, boundary objects embrace the implicit consequences of classification schemes in situations involving conflicting goals. Moreover, the requirements specification focused on functional...... requirements and provided little information about why these requirements were considered relevant. This stands in contrast to the discussions at the project meetings where the software engineers made frequent use of both abstract goal descriptions and concrete examples to make sense of the requirements....... This difference between the written requirements specification and the oral discussions at the meetings may help explain software engineers’ general preference for people, rather than documents, as their information sources....

  2. Current terminology and diagnostic classification schemes.

    Science.gov (United States)

    Okeson, J P

    1997-01-01

    This article reviews the current terminology and classification schemes available for temporomandibular disorders. The origin of each term is presented, and the classification schemes that have been offered for temporomandibular disorders are briefly reviewed. Several important classifications are presented in more detail, with mention of advantages and disadvantages. Final recommendations are provided for future direction in the area of classification schemes.

  3. A hierarchical classification scheme of psoriasis images

    DEFF Research Database (Denmark)

    Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær

    2003-01-01

    the normal skin in the second stage. These tools are the Expectation-Maximization Algorithm, the quadratic discrimination function and a classification window of optimal size. Extrapolation of classification parameters of a given image to other images of the set is evaluated by means of Cohen's Kappa......A two-stage hierarchical classification scheme of psoriasis lesion images is proposed. These images are basically composed of three classes: normal skin, lesion and background. The scheme combines conventional tools to separate the skin from the background in the first stage, and the lesion from...

  4. Hybrid scheme for Brownian semistationary processes

    DEFF Research Database (Denmark)

    Bennedsen, Mikkel; Lunde, Asger; Pakkanen, Mikko S.

    the asymptotics of the mean square error of the hybrid scheme and we observe that the scheme leads to a substantial improvement of accuracy compared to the ordinary forward Riemann-sum scheme, while having the same computational complexity. We exemplify the use of the hybrid scheme by two numerical experiments......, where we examine the finite-sample properties of an estimator of the roughness parameter of a Brownian semistationary process and study Monte Carlo option pricing in the rough Bergomi model of Bayer et al. (2015), respectively....

  5. Hybrid Transmission Scheme for MIMO Relay Channels

    Directory of Open Access Journals (Sweden)

    Guangming Xu

    2009-11-01

    Full Text Available To improve the achievable rate for the MIMO channels, we propose a hybrid transmission (HT scheme that mixes half-duplex decode-and-forward cooperative relaying transmission (DFRH)with direct transmission (DT. In the HT scheme, the source message is divided into two parts: one is transmitted by DFRH scheme and another is transmitted by DT scheme. Precoding and decoding are considered to convert the original MIMO relay channel into several parallel subchannels so that resource allocation can be easily performed. We focus on the spatial subchannel and power allocation problem. The objective of this problem is to maximize the total achievable rate under the constraints of joint total transmission power. Simulation results show that significant capacity gain can be achieved by the HT scheme compared to the DT scheme and the pure DFRH scheme.

  6. A classification scheme for risk assessment methods.

    Energy Technology Data Exchange (ETDEWEB)

    Stamp, Jason Edwin; Campbell, Philip LaRoche

    2004-08-01

    This report presents a classification scheme for risk assessment methods. This scheme, like all classification schemes, provides meaning by imposing a structure that identifies relationships. Our scheme is based on two orthogonal aspects--level of detail, and approach. The resulting structure is shown in Table 1 and is explained in the body of the report. Each cell in the Table represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. This report imposes structure on the set of risk assessment methods in order to reveal their relationships and thus optimize their usage.We present a two-dimensional structure in the form of a matrix, using three abstraction levels for the rows and three approaches for the columns. For each of the nine cells in the matrix we identify the method type by name and example. The matrix helps the user understand: (1) what to expect from a given method, (2) how it relates to other methods, and (3) how best to use it. Each cell in the matrix represent a different arrangement of strengths and weaknesses. Those arrangements shift gradually as one moves through the table, each cell optimal for a particular situation. The intention of this report is to enable informed use of the methods so that a method chosen is optimal for a situation given. The matrix, with type names in the cells, is introduced in Table 2 on page 13 below. Unless otherwise stated we use the word 'method' in this report to refer to a 'risk assessment method', though often times we use the full phrase. The use of the terms 'risk assessment' and 'risk management' are close enough that we do not attempt to distinguish them in this report. The remainder of this report is organized as follows. In

  7. A Classification Scheme for Glaciological AVA Responses

    Science.gov (United States)

    Booth, A.; Emir, E.

    2014-12-01

    A classification scheme is proposed for amplitude vs. angle (AVA) responses as an aid to the interpretation of seismic reflectivity in glaciological research campaigns. AVA responses are a powerful tool in characterising the material properties of glacier ice and its substrate. However, before interpreting AVA data, careful true amplitude processing is required to constrain basal reflectivity and compensate amplitude decay mechanisms, including anelastic attenuation and spherical divergence. These fundamental processing steps can be difficult to design in cases of noisy data, e.g. where a target reflection is contaminated by surface wave energy (in the case of shallow glaciers) or by energy reflected from out of the survey plane. AVA methods have equally powerful usage in estimating the fluid fill of potential hydrocarbon reservoirs. However, such applications seldom use true amplitude data and instead consider qualitative AVA responses using a well-defined classification scheme. Such schemes are often defined in terms of the characteristics of best-fit responses to the observed reflectivity, e.g. the intercept (I) and gradient (G) of a linear approximation to the AVA data. The position of the response on a cross-plot of I and G then offers a diagnostic attribute for certain fluid types. We investigate the advantages in glaciology of emulating this practice, and develop a cross-plot based on the 3-term Shuey AVA approximation (using I, G, and a curvature term C). Model AVA curves define a clear lithification trend: AVA responses to stiff (lithified) substrates fall discretely into one quadrant of the cross-plot, with positive I and negative G, whereas those to fluid-rich substrates plot diagonally opposite (in the negative I and positive G quadrant). The remaining quadrants are unoccupied by plausible single-layer responses and may therefore be diagnostic of complex thin-layer reflectivity, and the magnitude and polarity of the C term serves as a further indicator

  8. Environmental endocrine disruptors: A proposed classification scheme

    Energy Technology Data Exchange (ETDEWEB)

    Fur, P.L. de; Roberts, J. [Environmental Defense Fund, Washington, DC (United States)

    1995-12-31

    A number of chemicals known to act on animal systems through the endocrine system have been termed environmental endocrine disruptors. This group includes some of the PCBs and TCDDs, as well as lead, mercury and a large number of pesticides. The common feature is that the chemicals interact with endogenous endocrine systems at the cellular and/or molecular level to alter normal processes that are controlled or regulated by hormones. Although the existence of artificial or environmental estrogens (e.g. chlordecone and DES) has been known for some time, recent data indicate that this phenomenon is widespread. Indeed, anti-androgens have been held responsible for reproductive dysfunction in alligator populations in Florida. But the significance of endocrine disruption was recognized by pesticide manufacturers when insect growth regulators were developed to interfere with hormonal control of growth. Controlling, regulating or managing these chemicals depends in no small part on the ability to identify, screen or otherwise know that a chemical is an endocrine disrupter. Two possible classifications schemes are: using the effects caused in an animal, or animals as an exposure indicator; and using a known screen for the point of contact with the animal. The former would require extensive knowledge of cause and effect relationships in dozens of animal groups; the latter would require a screening tool comparable to an estrogen binding assay. The authors present a possible classification based on chemicals known to disrupt estrogenic, androgenic and ecdysone regulated hormonal systems.

  9. A Hybrid Mode and a Classification of Beam Plasma Instabilities

    Science.gov (United States)

    2014-09-26

    classification scheme, based on the beam energy and beam density. This classification identifies the domains for the hybrid mode, the Weibel mode,13 and...the classical two stream instabilities. In that section, we also furnish a simple derivation of the Weibel mode for a relativist..c electron beam...w p which is non-zero. This mode has been called a Weibel mode,1 3𔃻 4 and is predominant in Domain III in the classification shown in Fig. 4. (B2

  10. Hybrid Support Vector Machines-Based Multi-fault Classification

    Institute of Scientific and Technical Information of China (English)

    GAO Guo-hua; ZHANG Yong-zhong; ZHU Yu; DUAN Guang-huang

    2007-01-01

    Support Vector Machines (SVM) is a new general machine-learning tool based on structural risk minimization principle. This characteristic is very signific ant for the fault diagnostics when the number of fault samples is limited. Considering that SVM theory is originally designed for a two-class classification, a hybrid SVM scheme is proposed for multi-fault classification of rotating machinery in our paper. Two SVM strategies, 1-v-1 (one versus one) and 1-v-r (one versus rest), are respectively adopted at different classification levels. At the parallel classification level, using 1-v-1 strategy, the fault features extracted by various signal analysis methods are transferred into the multiple parallel SVM and the local classification results are obtained. At the serial classification level, these local results values are fused by one serial SVM based on 1-v-r strategy. The hybrid SVM scheme introduced in our paper not only generalizes the performance of signal binary SVMs but improves the precision and reliability of the fault classification results. The actually testing results show the availability suitability of this new method.

  11. State of the Art in the Cramer Classification Scheme and ...

    Science.gov (United States)

    Slide presentation at the SOT FDA Colloquium on State of the Art in the Cramer Classification Scheme and Threshold of Toxicological Concern in College Park, MD. Slide presentation at the SOT FDA Colloquium on State of the Art in the Cramer Classification Scheme and Threshold of Toxicological Concern in College Park, MD.

  12. International proposal for an acoustic classification scheme for dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2014-01-01

    Acoustic classification schemes specify different quality levels for acoustic conditions. Regulations and classification schemes for dwellings typically include criteria for airborne and impact sound insulation, façade sound insulation and service equipment noise. However, although important...... European countries have introduced classification schemes. The schemes typically include four classes. Comparative studies have shown significant discrepancies between countries due to national development of schemes. The diversity is an obstacle for exchange of construction experience for different...... classes, implying also trade barriers. Thus, a harmonized classification scheme would be useful, and the European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", running 2009-2013 with members from 32 countries, including three overseas...

  13. A Physical Classification Scheme for Blazars

    CERN Document Server

    Landt, H; Perlman, E S; Giommi, P

    2004-01-01

    Blazars are currently separated into BL Lacertae objects (BL Lacs) and flat spectrum radio quasars (FSRQ) based on the strength of their emission lines. This is done rather arbitrarily by defining a diagonal line in the Ca H&K break value -- equivalent width plane, following Marcha et al. We readdress this problem and put the classification scheme for blazars on firm physical grounds. We study ~100 blazars and radio galaxies from the Deep X-ray Radio Blazar Survey (DXRBS) and 2 Jy radio survey and find a significant bimodality for the narrow emission line [OIII] 5007. This suggests the presence of two physically distinct classes of radio-loud AGN. We show that all radio-loud AGN, blazars and radio galaxies, can be effectively separated into weak- and strong-lined sources using the [OIII] 5007 -- [OII] 3727 equivalent width plane. This plane allows one to disentangle orientation effects from intrinsic variations in radio-loud AGN. Based on DXRBS, the strongly beamed sources of the new class of weak-lined r...

  14. Sound classification of dwellings - Comparison of schemes in Europe

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2009-01-01

    National sound classification schemes for dwellings exist in nine countries in Europe, and proposals are under preparation in more countries. The schemes specify class criteria concerning several acoustic aspects, the main criteria being about airborne and impact sound insulation between dwellings......, facade sound insulation and installation noise. The quality classes reflect dierent levels of acoustical comfort. The paper presents and compares the sound classification schemes in Europe. The schemes have been implemented and revised gradually since the 1990es. However, due to lack of coordination....... The current variety of descriptors and classes also causes trade barriers. Thus, there is a need to harmonize concepts and other characteristics of the schemes....

  15. A hybrid scheme for encryption and watermarking

    Science.gov (United States)

    Xu, Xiaowei; Dexter, Scott D.; Eskicioglu, Ahmet M.

    2004-06-01

    Encryption and watermarking are complementary lines of defense in protecting multimedia content. Recent watermarking techniques have therefore been developed independent from encryption techniques. In this paper, we present a hybrid image protection scheme to establish a relation between the data encryption key and the watermark. Prepositioned secret sharing allows the reconstruction of different encryption keys by communicating different activating shares for the same prepositioned information. Each activating share is used by the receivers to generate a fresh content decryption key. In the proposed scheme, the activating share is used to carry copyright or usage rights data. The bit stream that represents this data is also embedded in the content as a visual watermark. When the encryption key needs to change, the data source generates a new activating share, and embeds the corresponding watermark into the multimedia stream. Before transmission, the composite stream is encrypted with the key constructed from the new activating share. Each receiver can decrypt the stream after reconstructing the same key, and extract the watermark from the image. Our presentation will include the application of the scheme to a test image, and a discussion on the data hiding capacity, watermark transparency, and robustness to common attacks.

  16. A Classification Scheme for Phenomenological Universalities in Growth Problems

    CERN Document Server

    Castorina, P; Guiot, C

    2006-01-01

    A classification in universality classes of broad categories of phenomenologies, belonging to different disciplines, may be very useful for a crossfertilization among them and for the purpose of pattern recognition. We present here a simple scheme for the classification of nonlinear growth problems. The success of the scheme in predicting and characterizing the well known Gompertz, West and logistic models suggests to us the study of a hitherto unexplored class of nonlinear growth problems.

  17. Comparing document classification schemes using k-means clustering

    OpenAIRE

    Šivić, Artur; Žmak, Lovro; Dalbelo Bašić, Bojana; Moens, Marie-Francine

    2008-01-01

    In this work, we jointly apply several text mining methods to a corpus of legal documents in order to compare the separation quality of two inherently different document classification schemes. The classification schemes are compared with the clusters produced by the k-means algorithm. In the future, we believe that our comparison method will be coupled with semi-supervised and active learning techniques. Also, this paper presents the idea of combining k-means and Principal Component Analysis...

  18. HYBRID INTERNET TRAFFIC CLASSIFICATION TECHNIQUE1

    Institute of Scientific and Technical Information of China (English)

    Li Jun; Zhang Shunyi; Lu Yanqing; Yan Junrong

    2009-01-01

    Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P applications using dynamic port numbers, masquerading techniques, and payload encryption to avoid detection, traditional classification approaches turn to be ineffective. In this paper, we present a layered hybrid system to classify current Internet traffic, motivated by variety of network activities and their requirements of traffic classification. The proposed method could achieve fast and accurate traffic classification with low overheads and robustness to accommodate both known and unknown/encrypted applications. Furthermore, it is feasible to be used in the context of real-time traffic classification. Our experimental results show the distinct advantages of the proposed classification system, compared with the one-step Machine Learning (ML) approach.

  19. Towards a Collaborative Intelligent Tutoring System Classification Scheme

    Science.gov (United States)

    Harsley, Rachel

    2014-01-01

    This paper presents a novel classification scheme for Collaborative Intelligent Tutoring Systems (CITS), an emergent research field. The three emergent classifications of CITS are unstructured, semi-structured, and fully structured. While all three types of CITS offer opportunities to improve student learning gains, the full extent to which these…

  20. Four classification schemes of adult motivation: current views and measures.

    Science.gov (United States)

    Barbuto, John E

    2006-04-01

    Classification of perspectives on motivation and recommendations for measurement are provided. Motivation is classified into four broad categories: content theories, process theories, decision-making theories, and sustained-effort theories--drawing from different theories and measures. Recommendations on measurement are developed for each classification scheme of motivation.

  1. A High Resolution Low Dissipation Hybrid Scheme for Compressible Flows

    Institute of Scientific and Technical Information of China (English)

    YU Jian; YAN Chao; JIANG Zhenhua

    2011-01-01

    In this paper,an efficient hybrid shock capturing scheme is proposed to obtain accurate results both in the smooth region and around discontinuities for compressible flows.The hybrid algorithm is based on a fifth-order weighted essentially non-oscillatory (WENO) scheme in the finite volume form to solve the smooth part of the flow field,which is coupled with a characteristic-based monotone upstream-centered scheme for conservation laws(MUSCL) to capture discontinuities.The hybrid scheme is intended to combine high resolution of MUSCL scheme and low dissipation of WENO scheme.The two ingredients in this hybrid scheme are switched with an indicator.Three typical indicators are chosen and compared.MUSCL and WENO are both shock capturing schemes making the choice of the indicator parameter less crucial.Several test cases are carried out to investigate hybrid scheme with different indicators in terms of accuracy and efficiency.Numerical results demonstrate that the hybrid scheme in the present work performs well in a broad range of problems.

  2. Hybrid optimization schemes for quantum control

    Energy Technology Data Exchange (ETDEWEB)

    Goerz, Michael H.; Koch, Christiane P. [Universitaet Kassel, Theoretische Physik, Kassel (Germany); Whaley, K. Birgitta [University of California, Department of Chemistry, Berkeley, CA (United States)

    2015-12-15

    Optimal control theory is a powerful tool for solving control problems in quantum mechanics, ranging from the control of chemical reactions to the implementation of gates in a quantum computer. Gradient-based optimization methods are able to find high fidelity controls, but require considerable numerical effort and often yield highly complex solutions. We propose here to employ a two-stage optimization scheme to significantly speed up convergence and achieve simpler controls. The control is initially parametrized using only a few free parameters, such that optimization in this pruned search space can be performed with a simplex method. The result, considered now simply as an arbitrary function on a time grid, is the starting point for further optimization with a gradient-based method that can quickly converge to high fidelities. We illustrate the success of this hybrid technique by optimizing a geometric phase gate for two superconducting transmon qubits coupled with a shared transmission line resonator, showing that a combination of Nelder-Mead simplex and Krotov's method yields considerably better results than either one of the two methods alone. (orig.)

  3. Mapping of the Universe of Knowledge in Different Classification Schemes

    Directory of Open Access Journals (Sweden)

    M. P. Satija

    2017-06-01

    Full Text Available Given the variety of approaches to mapping the universe of knowledge that have been presented and discussed in the literature, the purpose of this paper is to systematize their main principles and their applications in the major general modern library classification schemes. We conducted an analysis of the literature on classification and the main classification systems, namely Dewey/Universal Decimal Classification, Cutter’s Expansive Classification, Subject Classification of J.D. Brown, Colon Classification, Library of Congress Classification, Bibliographic Classification, Rider’s International Classification, Bibliothecal Bibliographic Klassification (BBK, and Broad System of Ordering (BSO. We conclude that the arrangement of the main classes can be done following four principles that are not mutually exclusive: ideological principle, social purpose principle, scientific order, and division by discipline. The paper provides examples and analysis of each system. We also conclude that as knowledge is ever-changing, classifications also change and present a different structure of knowledge depending upon the society and time of their design.

  4. Transporter taxonomy - a comparison of different transport protein classification schemes.

    Science.gov (United States)

    Viereck, Michael; Gaulton, Anna; Digles, Daniela; Ecker, Gerhard F

    2014-06-01

    Currently, there are more than 800 well characterized human membrane transport proteins (including channels and transporters) and there are estimates that about 10% (approx. 2000) of all human genes are related to transport. Membrane transport proteins are of interest as potential drug targets, for drug delivery, and as a cause of side effects and drug–drug interactions. In light of the development of Open PHACTS, which provides an open pharmacological space, we analyzed selected membrane transport protein classification schemes (Transporter Classification Database, ChEMBL, IUPHAR/BPS Guide to Pharmacology, and Gene Ontology) for their ability to serve as a basis for pharmacology driven protein classification. A comparison of these membrane transport protein classification schemes by using a set of clinically relevant transporters as use-case reveals the strengths and weaknesses of the different taxonomy approaches.

  5. A Dewey-Eyed Look at Children's Book Classification: A Comparison of Four Classification Schemes Used in Children's Libraries.

    Science.gov (United States)

    Polan, Ruth

    Four classification schemes for subject access to children's books are compared. Two of these are general schemes (the "Dewey Decimal Classification" and the abridged "Dewey Decimal Classification"), and two others were devised specifically for children's books (the Toronto Public Library's "Boys and Girls Book Classification" and the Inglewood…

  6. Monitoring nanotechnology using patent classifications: an overview and comparison of nanotechnology classification schemes

    Science.gov (United States)

    Jürgens, Björn; Herrero-Solana, Victor

    2017-04-01

    Patents are an essential information source used to monitor, track, and analyze nanotechnology. When it comes to search nanotechnology-related patents, a keyword search is often incomplete and struggles to cover such an interdisciplinary discipline. Patent classification schemes can reveal far better results since they are assigned by experts who classify the patent documents according to their technology. In this paper, we present the most important classifications to search nanotechnology patents and analyze how nanotechnology is covered in the main patent classification systems used in search systems nowadays: the International Patent Classification (IPC), the United States Patent Classification (USPC), and the Cooperative Patent Classification (CPC). We conclude that nanotechnology has a significantly better patent coverage in the CPC since considerable more nanotechnology documents were retrieved than by using other classifications, and thus, recommend its use for all professionals involved in nanotechnology patent searches.

  7. The hybrid Eulerian Lagrangian numerical scheme tested with Chemistry

    Directory of Open Access Journals (Sweden)

    A. B. Hansen

    2012-11-01

    Full Text Available A newly developed advection scheme, the Hybrid Eulerian Lagrangian (HEL scheme, has been tested, including a module for atmospheric chemistry, including 58 chemical species, and compared to two other traditional advection schemes; a classical pseudospectral Eulerian method the Accurate Space Derivative (ASD scheme and the bi-cubic semi-Lagrangian (SL scheme using classical rotation tests. The rotation tests have been designed to test and compare the advection schemes for different spatial and temporal resolutions in different chemical conditions (rural and urban and for different shapes (cone and slotted cylinder giving the advection schemes different challenges with respect to relatively slow or fast chemistry and smooth or sharp gradients, respectively. In every test, error measures have been calculated and used for ranking of the advection schemes with respect to performance, i.e. lowest overall errors for all chemical species. Furthermore, the HEL and SL schemes have been compared in a shallow water model, demonstrating the performance in a more realistic non-linear deformation flow.

    The results in this paper show that the new advection scheme, HEL, by far outperforms both the Eulerian and semi-Lagrangian schemes with very low error estimates compared to the two other schemes. Although no analytic solution can be obtained for the performance in the non-linear shallow water model flow, the tracer distribution appears realistic as compared to LMCSL when a mixing between local parcel concentrations is introduced in HEL.

  8. Investigation into Text Classification With Kernel Based Schemes

    Science.gov (United States)

    2010-03-01

    classification/categorization applications. The text database considered in this study was collected from the IEEE Xplore database website [2]. The...database considered in this study was collected from the IEEE Xplore database website [2]. The documents collected were limited to Electrical engineering...Linear Discriminant Analysis (LDA) scheme. Titles, along with abstracts from IEEE journal articles published between 1990 and 1999 with specific key

  9. Computer-aided diagnosis system: a Bayesian hybrid classification method.

    Science.gov (United States)

    Calle-Alonso, F; Pérez, C J; Arias-Nicolás, J P; Martín, J

    2013-10-01

    A novel method to classify multi-class biomedical objects is presented. The method is based on a hybrid approach which combines pairwise comparison, Bayesian regression and the k-nearest neighbor technique. It can be applied in a fully automatic way or in a relevance feedback framework. In the latter case, the information obtained from both an expert and the automatic classification is iteratively used to improve the results until a certain accuracy level is achieved, then, the learning process is finished and new classifications can be automatically performed. The method has been applied in two biomedical contexts by following the same cross-validation schemes as in the original studies. The first one refers to cancer diagnosis, leading to an accuracy of 77.35% versus 66.37%, originally obtained. The second one considers the diagnosis of pathologies of the vertebral column. The original method achieves accuracies ranging from 76.5% to 96.7%, and from 82.3% to 97.1% in two different cross-validation schemes. Even with no supervision, the proposed method reaches 96.71% and 97.32% in these two cases. By using a supervised framework the achieved accuracy is 97.74%. Furthermore, all abnormal cases were correctly classified.

  10. A hybrid TIM-NOMA scheme for the Broadcast Channel

    Directory of Open Access Journals (Sweden)

    V. Kalokidou

    2015-07-01

    Full Text Available Future mobile communication networks will require enhanced network efficiency and reduced system overhead. Research on Blind Interference Alignment and Topological Interference Management (TIM has shown that optimal Degrees of Freedom can be achieved, in the absence of Channel State Information at the transmitters. Moreover, the recently emerged Non- Orthogonal Multiple Access (NOMA scheme suggests a different multiple access approach, compared to the orthogonal methods employed in 4G, resulting in high capacity gains. Our contribution is a hybrid TIM-NOMA scheme in K-user cells, where users are divided into T groups. By superimposing users in the power domain, we introduce a two-stage decoding process, managing “inter-group” interference based on the TIM principles, and “intra-group” interference based on Successful Interference Cancellation, as proposed by NOMA. We show that the hybrid scheme can improve the sum rate by at least 100% compared to Time Division Multiple Access, for high SNR values.

  11. Image classification based on scheme of principal node analysis

    Science.gov (United States)

    Yang, Feng; Ma, Zheng; Xie, Mei

    2016-11-01

    This paper presents a scheme of principal node analysis (PNA) with the aim to improve the representativeness of the learned codebook so as to enhance the classification rate of scene image. Original images are normalized into gray ones and the scale-invariant feature transform (SIFT) descriptors are extracted from each image in the preprocessing stage. Then, the PNA-based scheme is applied to the SIFT descriptors with iteration and selection algorithms. The principal nodes of each image are selected through spatial analysis of the SIFT descriptors with Manhattan distance (L1 norm) and Euclidean distance (L2 norm) in order to increase the representativeness of the codebook. With the purpose of evaluating the performance of our scheme, the feature vector of the image is calculated by two baseline methods after the codebook is constructed. The L1-PNA- and L2-PNA-based baseline methods are tested and compared with different scales of codebooks over three public scene image databases. The experimental results show the effectiveness of the proposed scheme of PNA with a higher categorization rate.

  12. A Hybrid Immigrants Scheme for Genetic Algorithms in Dynamic Environments

    Institute of Scientific and Technical Information of China (English)

    Shengxiang Yang; Renato Tinós

    2007-01-01

    Dynamic optimization problems are a kind of optimization problems that involve changes over time. They pose a serious challenge to traditional optimization methods as well as conventional genetic algorithms since the goal is no longer to search for the optimal solution(s) of a fixed problem but to track the moving optimum over time. Dynamic optimization problems have attracted a growing interest from the genetic algorithm community in recent years. Several approaches have been developed to enhance the performance of genetic algorithms in dynamic environments. One approach is to maintain the diversity of the population via random immigrants. This paper proposes a hybrid immigrants scheme that combines the concepts of elitism, dualism and random immigrants for genetic algorithms to address dynamic optimization problems. In this hybrid scheme, the best individual, i.e., the elite, from the previous generation and its dual individual are retrieved as the bases to create immigrants via traditional mutation scheme. These elitism-based and dualism-based immigrants together with some random immigrants are substituted into the current population, replacing the worst individuals in the population. These three kinds of immigrants aim to address environmental changes of slight, medium and significant degrees respectively and hence efficiently adapt genetic algorithms to dynamic environments that are subject to different severities of changes. Based on a series of systematically constructed dynamic test problems, experiments are carried out to investigate the performance of genetic algorithms with the hybrid immigrants scheme and traditional random immigrants scheme. Experimental results validate the efficiency of the proposed hybrid immigrants scheme for improving the performance of genetic algorithms in dynamic environments.

  13. CANDELS Visual Classifications: Scheme, Data Release, and First Results

    CERN Document Server

    Kartaltepe, Jeyhan S; Kocevski, Dale; McIntosh, Daniel H; Lotz, Jennifer; Bell, Eric F; Faber, Sandra; Ferguson, Henry; Koo, David; Bassett, Robert; Bernyk, Maksym; Blancato, Kirsten; Bournaud, Frederic; Cassata, Paolo; Castellano, Marco; Cheung, Edmond; Conselice, Christopher J; Croton, Darren; Dahlen, Tomas; de Mello, Duilia F; DeGroot, Laura; Donley, Jennifer; Guedes, Javiera; Grogin, Norman; Hathi, Nimish; Hilton, Matt; Hollon, Brett; Inami, Hanae; Kassin, Susan; Koekemoer, Anton; Lani, Caterina; Liu, Nick; Lucas, Ray A; Martig, Marie; McGrath, Elizabeth; McPartland, Conor; Mobasher, Bahram; Morlock, Alice; Mutch, Simon; O'Leary, Erin; Peth, Mike; Pforr, Janine; Pillepich, Annalisa; Poole, Gregory B; Rizer, Zachary; Rosario, David; Soto, Emmaris; Straughn, Amber; Telford, Olivia; Sunnquist, Ben; Weiner, Benjamin; Wuyts, Stijn

    2014-01-01

    We have undertaken an ambitious program to visually classify all galaxies in the five CANDELS fields down to H<24.5 involving the dedicated efforts of 65 individual classifiers. Once completed, we expect to have detailed morphological classifications for over 50,000 galaxies up to z<4 over all the fields. Here, we present our detailed visual classification scheme, which was designed to cover a wide range of CANDELS science goals. This scheme includes the basic Hubble sequence types, but also includes a detailed look at mergers and interactions, the clumpiness of galaxies, $k$-corrections, and a variety of other structural properties. In this paper, we focus on the first field to be completed -- GOODS-S. The wide area coverage spanning the full field includes 7634 galaxies that have been classified by at least three different people. In the deep area of the field, 2534 galaxies have been classified by at least five different people at three different depths. With this paper, we release to the public all ...

  14. A Unified Near Infrared Spectral Classification Scheme for T Dwarfs

    CERN Document Server

    Burgasser, A J; Leggett, S K; Kirkpatrick, J D; Golimowski, D A; Burgasser, Adam J.; Golimowski, David A.

    2006-01-01

    A revised near infrared classification scheme for T dwarfs is presented, based on and superseding prior schemes developed by Burgasser et al. and Geballe et al., and defined following the precepts of the MK Process. Drawing from two large spectroscopic libraries of T dwarfs identified largely in the Sloan Digital Sky Survey and the Two Micron All Sky Survey, nine primary spectral standards and five alternate standards spanning spectral types T0 to T8 are identified that match criteria of spectral character, brightness, absence of a resolved companion and accessibility from both northern and southern hemispheres. The classification of T dwarfs is formally made by the direct comparison of near infrared spectral data of equivalent resolution to the spectra of these standards. Alternately, we have redefined five key spectral indices measuring the strengths of the major H$_2$O and CH$_4$ bands in the 1-2.5 micron region that may be used as a proxy to direct spectral comparison. Two methods of determining T spectra...

  15. Minimally-sized balanced decomposition schemes for multi-class classification

    NARCIS (Netherlands)

    Smirnov, E.N.; Moed, M.; Nalbantov, G.I.; Sprinkhuizen-Kuyper, I.G.

    2011-01-01

    Error-Correcting Output Coding (ECOC) is a well-known class of decomposition schemes for multi-class classification. It allows representing any multiclass classification problem as a set of binary classification problems. Due to code redundancy ECOC schemes can significantly improve generalization p

  16. CANDELS Visual Classifications: Scheme, Data Release, and First Results

    Science.gov (United States)

    Kartaltepe, Jeyhan S.; Mozena, Mark; Kocevski, Dale; McIntosh, Daniel H.; Lotz, Jennifer; Bell, Eric F.; Faber, Sandy; Ferguson, Henry; Koo, David; Bassett, Robert; Bernyk, Maksym; Blancato, Kirsten; Bournaud, Frederic; Cassata, Paolo; Castellano, Marco; Cheung, Edmond; Conselice, Christopher J.; Croton, Darren; Dahlen, Tomas; deMello, Duilia F.; DeGroot, Laura; Donley, Jennifer; Guedes, Javiera; Grogin, Norman; Hathi, Nimish; Hilton, Matt; Hollon, Brett; Inami, Hanae; Kassin, Susan; Koekemoer, Anton; Lani, Caterina; Liu, Nick; Lucas, Ray A.; Martig, Marie; McGrath, Elizabeth; McPartland, Conor; Mobasher, Bahram; Morlock, Alice; O'Leary, Erin; Peth, Mike; Pforr, Janine; Pillepich, Annalisa; Rizer, Zachary; Rosario, David; Soto, Emmaris; Straughn, Amber; Telford, Olivia; Sunnquist, Ben; Weiner, Benjamin; Wuyts, Stijn

    2014-01-01

    We have undertaken an ambitious program to visually classify all galaxies in the five CANDELS fields down to H <24.5 involving the dedicated efforts of 65 individual classifiers. Once completed, we expect to have detailed morphological classifications for over 50,000 galaxies spanning 0 < z < 4 over all the fields. Here, we present our detailed visual classification scheme, which was designed to cover a wide range of CANDELS science goals. This scheme includes the basic Hubble sequence types, but also includes a detailed look at mergers and interactions, the clumpiness of galaxies, k-corrections, and a variety of other structural properties. In this paper, we focus on the first field to be completed - GOODS-S, which has been classified at various depths. The wide area coverage spanning the full field (wide+deep+ERS) includes 7634 galaxies that have been classified by at least three different people. In the deep area of the field, 2534 galaxies have been classified by at least five different people at three different depths. With this paper, we release to the public all of the visual classifications in GOODS-S along with the Perl/Tk GUI that we developed to classify galaxies. We present our initial results here, including an analysis of our internal consistency and comparisons among multiple classifiers as well as a comparison to the Sersic index. We find that the level of agreement among classifiers is quite good and depends on both the galaxy magnitude and the galaxy type, with disks showing the highest level of agreement and irregulars the lowest. A comparison of our classifications with the Sersic index and restframe colors shows a clear separation between disk and spheroid populations. Finally, we explore morphological k-corrections between the V-band and H-band observations and find that a small fraction (84 galaxies in total) are classified as being very different between these two bands. These galaxies typically have very clumpy and extended morphology or

  17. Hepatic CT Image Query Based on Threshold-based Classification Scheme with Gabor Features

    Institute of Scientific and Technical Information of China (English)

    JIANG Li-jun; LUO Yong-zing; ZHAO Jun; ZHUANG Tian-ge

    2008-01-01

    Hepatic computed tomography (CT) images with Gabor function were analyzed.Then a thresholdbased classification scheme was proposed using Gabor features and proceeded with the retrieval of the hepatic CT images.In our experiments,a batch of hepatic CT images containing several types of CT findings was used and compared with the Zhao's image classification scheme,support vector machines (SVM) scheme and threshold-based scheme.

  18. Classification and prioritization of usability problems using an augmented classification scheme.

    Science.gov (United States)

    Khajouei, R; Peute, L W P; Hasman, A; Jaspers, M W M

    2011-12-01

    's classification and added a classification for expressing the potential impact of usability problems on final task outcomes. Such an augmented scheme will provide the necessary information to system developers to understand the essence of usability problems, to prioritize problems and to tackle them in a system redesign. To investigate the feasibility of such an augmented scheme, it was applied to the results of usability studies of a computerized physician order entry system (CPOE). The evaluators classified the majority of the usability problems identically by use of the augmented UAF. In addition it helped in differentiating problems that looked similar but yet affect the user-system interaction and the task results differently and vice versa. This work is of value not only for system developers but also for researchers who want to study the results of other usability evaluation studies, because this scheme makes the results of usability studies comparable and easily retrievable.

  19. Runoff prediction using an integrated hybrid modelling scheme

    Science.gov (United States)

    Remesan, Renji; Shamim, Muhammad Ali; Han, Dawei; Mathew, Jimson

    2009-06-01

    SummaryRainfall runoff is a very complicated process due to its nonlinear and multidimensional dynamics, and hence difficult to model. There are several options for a modeller to consider, for example: the type of input data to be used, the length of model calibration (training) data and whether or not the input data be treated as signals with different frequency bands so that they can be modelled separately. This paper describes a new hybrid modelling scheme to answer the above mentioned questions. The proposed methodology is based on a hybrid model integrating wavelet transformation, a modelling engine (Artificial Neural Network) and the Gamma Test. First, the Gamma Test is used to decide the required input data dimensions and its length. Second, the wavelet transformation decomposes the input signals into different frequency bands. Finally, a modelling engine (ANN in this study) is used to model the decomposed signals separately. The proposed scheme was tested using the Brue catchment, Southwest England, as a case study and has produced very positive results. The hybrid model outperforms all other models tested. This study has a wider implication in the hydrological modelling field since its general framework could be applied to other model combinations (e.g., model engine could be Support Vector Machines, neuro-fuzzy systems, or even a conceptual model. The signal decomposition could be carried out by Fourier transformation).

  20. Scalable classification by clustering: Hybrid can be better than Pure

    Institute of Scientific and Technical Information of China (English)

    Deng Shengchun; He Zengyou; Xu Xiaofei

    2007-01-01

    The problem of scalable classification by clustering in large databases was discussed. Clustering based classification method first generates clusters using clustering algorithms . To classify new coming data points , it finds the k nearest clusters of the data point as neighbors , and assign each data point to the dominant class of these neighbors . Existing algorithms incorporated class information in making clustering decisions and produced pure clusters (each cluster associated with only one class) . We presented hybrid cluster based algorithms , which produce clusters by unsupervised clustering and allow each cluster associated with multiple classes . Experimental results show that hybrid cluster based algorithms outperform pure ones in both classification accuracy and training speed.

  1. A Hybrid Data Compression Scheme for Improved VNC

    Directory of Open Access Journals (Sweden)

    Xiaozheng (Jane Zhang

    2007-04-01

    Full Text Available Virtual Network Computing (VNC has emerged as a promising technology in distributed computing environment since its invention in the late nineties. Successful application of VNC requires rapid data transfer from one machine to another over a TCP/IP network connection. However transfer of screen data consumes much network bandwidth and current data encoding schemes for VNC are far from being ideal. This paper seeks to improve screen data compression techniques to enable VNC over slow connections and present a reasonable speed and image quality. In this paper, a hybrid technique is proposed for improving coding efficiency. The algorithm first divides a screen image into pre-defined regions and applies encoding schemes to each area according to the region characteristics. Second, correlation of screen data in consecutive frames is exploited where multiple occurrences of similar image contents are detected. The improved results are demonstrated in a dynamic environment with various screen image types and desktop manipulation.

  2. DSBCS modulation scheme for hybrid wireless and cable television system.

    Science.gov (United States)

    Peng, P C; Wang, H Y; Chang, C H; Hu, H L; Yang, W Y; Wu, F K

    2014-01-13

    This work develops and demonstrates a double sideband with optical carrier suppression (DSBCS) modulation scheme for a hybrid wireless and cable television system based on a phase modulator (PM) and a polarization beam splitter (PBS). A carrier suppression ratio greater than 20 dB is achieved between two sidebands. In addition, the values of carrier-to-noise ratio, composite second-order and composite triple beat in various channels after 25 km of transmission are higher than the threshold value, and the power penalty of microwave signal in back-to-back and 25 km transmission perform well. Additionally, the constellation diagram of upstream signal is successfully recovered. Above results demonstrate that the proposed scheme is highly promising for practical applications.

  3. 15 CFR 921.3 - National Estuarine Research Reserve System biogeographic classification scheme and estuarine...

    Science.gov (United States)

    2010-01-01

    ... biogeographic classification scheme and estuarine typologies. (a) National Estuarine Research Reserves are... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false National Estuarine Research Reserve System biogeographic classification scheme and estuarine typologies. 921.3 Section 921.3 Commerce...

  4. An evolutionary scheme for morphological classification of Martian gullies

    Science.gov (United States)

    Aston, A. H.; Balme, M.

    2009-04-01

    Martian gullies are geologically recent small-scale features characterised by an alcove-channel-apron morphology associated on Earth with liquid water. Since their discovery by Malin and Edgett (1), several theories have been advanced to explain their formation. These typically emphasise either groundwater processes (1, 2) or melting of ground ice or snowpack (3). The former approach has been challenged on the basis of gullies observed on hills and central peaks, where aquifers are unlikely (4). Studies of gullied walls have been undertaken (5), but though morphological classifications of gullies have been proposed (1), they are largely descriptive. This study proposes an evolutionary classification scheme and a pilot study to determine its potential to address controversies in gully formation. A morphological classification of gullies was developed, and four types identified: Type I: V-shaped gullies in slope mantling material or scree (i.e. not cutting bedrock); no distinct alcoves. Type II: Alcoves capped by a distinct and continuous stratum of rock. Type III: Alcoves extending vertically upslope, without reaching top of slope. Type IV: Alcoves reaching top of slope and cutting back into cliff. The types form an evolutionary sequence: in particular, the sequence II-III-IV appears to represent the development of many Martian gullies. Moreover, we have found that average length increases from Type I to Type IV. Furthermore, the presence of small gullies (mostly I and II) in the mantling deposits filling larger alcoves suggests multiple stages of gully activity. To test the classifications in practice, a sample of gullied slope sections imaged by MOC (Mars Orbital Camera) on Mars Global Surveyor at a resolution of 1-7 m/pixel were catalogued using ArcGIS software. 210 slope sections were covered, representing 1734 gullies across the southern mid-latitudes. Broad geographical coverage was obtained by working through MOC image numbers. For each slope section, the

  5. Spin-orbit hybrid entanglement quantum key distribution scheme

    Institute of Scientific and Technical Information of China (English)

    ZHANG ChengXian; GUO BangHong; CHENG GuangMing; GUO JianJun; FAN RongHua

    2014-01-01

    We propose a novel quantum key distribution scheme by using the SAM-OAM hybrid entangled state as the physical resource.To obtain this state,the polarization entangled photon pairs are created by the spontaneous parametric down conversion process,and then,the q-plate acts as a SAM-to-OAM transverter to transform the polarization entangled pairs into the hybrid entangled pattern,which opens the possibility to exploit the features of the higher-dimensional space of OAM state to encode information.In the manipulation and encoding process,Alice performs the SAM measurement by modulating the polarization state |θ>π on one photon,whereas Bob modulates the OAM sector state |x>1 on the other photon to encode his key elements using the designed holograms which is implemented by the computer-controlled SLM.With coincidence measurement,Alice could extract the key information.It is showed that N-based keys can be encoded with each pair of entangled photon,and this scheme is robust against Eve's individual attack.Also,the MUBs are not used.Alice and Bob do not need the classical communication for the key recovery.

  6. Adaptive codebook selection schemes for image classification in correlated channels

    Science.gov (United States)

    Hu, Chia Chang; Liu, Xiang Lian; Liu, Kuan-Fu

    2015-09-01

    The multiple-input multiple-output (MIMO) system with the use of transmit and receive antenna arrays achieves diversity and array gains via transmit beamforming. Due to the absence of full channel state information (CSI) at the transmitter, the transmit beamforming vector can be quantized at the receiver and sent back to the transmitter by a low-rate feedback channel, called limited feedback beamforming. One of the key roles of Vector Quantization (VQ) is how to generate a good codebook such that the distortion between the original image and the reconstructed image is the minimized. In this paper, a novel adaptive codebook selection scheme for image classification is proposed with taking both spatial and temporal correlation inherent in the channel into consideration. The new codebook selection algorithm is developed to select two codebooks from the discrete Fourier transform (DFT) codebook, the generalized Lloyd algorithm (GLA) codebook and the Grassmannian codebook to be combined and used as candidates of the original image and the reconstructed image for image transmission. The channel is estimated and divided into four regions based on the spatial and temporal correlation of the channel and an appropriate codebook is assigned to each region. The proposed method can efficiently reduce the required information of feedback under the spatially and temporally correlated channels, where each region is adaptively. Simulation results show that in the case of temporally and spatially correlated channels, the bit-error-rate (BER) performance can be improved substantially by the proposed algorithm compared to the one with only single codebook.

  7. Acoustic classification schemes in Europe – Applicability for new, existing and renovated housing

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2016-01-01

    of the international scheme for classification of dwellings under development in ISO/TC43/SC2 will be explained. One of several key characteristics of the proposal is a wide range of classes, implying applicability to a major part of the existing housing stock in Europe, thus enabling acoustic labelling like energy......The first acoustic classification schemes for dwellings were published in the 1990’es as national standards with the main purpose to introduce the possibility of specifying easily stricter acoustic criteria for new-build than the minimum requirements found in building regulations. Since then, more...... countries have introduced acoustic classification schemes, the first countries updated more times and some countries introduced acoustic classification also for other building categories. However, the classification schemes continued to focus on new buildings and have in general limited applicability...

  8. A novel adaptive classification scheme for digital modulations in satellite communication

    Institute of Scientific and Technical Information of China (English)

    Wu Dan; Gu Xuemai; Guo Qing

    2007-01-01

    To make the modulation classification system more suitable for signals in a wide range of signal to noise ratios (SNRs) , a novel adaptive modulation classification scheme is presented in this paper. Different from traditional schemes, the proposed scheme employs a new SNR estimation algorithm for small samples before modulation classification, which makes the modulation classifier work adaptively according to estimated SNRs. Furthermore, it uses three efficient features and support vector machines (SVM) in modulation classification. Computer simulation shows that the scheme can adaptively classify ten digital modulation types (i.e. 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, 16QAM, TFM, π/4QPSK and OQPSK) at SNRS ranging from OdB to 25 dB and success rates are over 95% when SNR is not lower than 3dB. Accuracy, efficiency and simplicity of the proposed scheme are obviously improved, which make it more adaptive to engineering applications.

  9. Intelligent Hybrid Cluster Based Classification Algorithm for Social Network Analysis

    Directory of Open Access Journals (Sweden)

    S. Muthurajkumar

    2014-05-01

    Full Text Available In this paper, we propose an hybrid clustering based classification algorithm based on mean approach to effectively classify to mine the ordered sequences (paths from weblog data in order to perform social network analysis. In the system proposed in this work for social pattern analysis, the sequences of human activities are typically analyzed by switching behaviors, which are likely to produce overlapping clusters. In this proposed system, a robust Modified Boosting algorithm is proposed to hybrid clustering based classification for clustering the data. This work is useful to provide connection between the aggregated features from the network data and traditional indices used in social network analysis. Experimental results show that the proposed algorithm improves the decision results from data clustering when combined with the proposed classification algorithm and hence it is proved that of provides better classification accuracy when tested with Weblog dataset. In addition, this algorithm improves the predictive performance especially for multiclass datasets which can increases the accuracy.

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

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan;

    2001-01-01

    The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...... diagnoses. The final result is a short but robust rule based classification scheme, achieving high degree of classification accuracy (exceeding 90% of accuracy for most classes) in a meaningful and user-friendly representation form for the medical expert. The domain of application analyzed through the paper...... is the well-known Pap-Test problem, corresponding to a numerical database, which consists of 450 medical records, 25 diagnostic attributes and 5 different diagnostic classes. Experimental data are divided in two equal parts for the training and testing phase, and 8 mutually dependent rules for diagnosis...

  11. The EB-ANUBAD translator: A hybrid scheme

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    This article is aimed at describing a hybrid scheme for English to Bangla translation. The translated output in English scripts is useful for learning Bengali language. This is a significant contribution to Human Language Technology generation also.About two hundred million people in West Bengal and Tripura (two states in India) and in Bangladesh (a country whose people speak and write Bangla as their first language). This proposed translator would benefit Bengalee society because rural people are not usually very conversant with English. The English to Bangla Translator is being enhanced. This system (EnglishBangla-ANUBAD or EB-ANUBAD) takes a paragraph of English sentences as input sentences and produces equivalent Bangla sentences. EB-ANUBAD system is comprised of a preprocessor, morphological parser, semantic parser using English word ontology for context disambiguation, an electronic lexicon associated with grammatical information and a discourse processor,and also uses a lexical disambiguation analyzer. This system does not rely on a stochastic approach. Rather, it is based on a special kind of hybrid architecture of transformer and rule-based Natural Language Engineering (NLE) architectures along with various linguistic knowledge components of both English and Bangla.

  12. A Hybrid Combination Scheme for Cooperative Spectrum Sensing in Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    Changhua Yao

    2014-01-01

    Full Text Available We propose a novel hybrid combination scheme in cooperative spectrum sensing (CSS, which utilizes the diversity of reporting channels to achieve better throughput performance. Secondary users (SUs with good reporting channel quality transmit quantized local observation statistics to fusion center (FC, while others report their local decisions. FC makes the final decision by carrying out hybrid combination. We derive the closed-form expressions of throughput and detection performance as a function of the number of SUs which report local observation statistics. The simulation and numerical results show that the hybrid combination scheme can achieve better throughput performance than hard combination scheme and soft combination scheme.

  13. Mathematics subject classification and related schemes in the OAI framework

    OpenAIRE

    De Robbio, Antonella; Maguolo, Dario; Marini, Alberto

    2002-01-01

    This paper aims to give a feeling of the roles that discipline-oriented subject classifications can play in the Open Archive movement for the free dissemination of information in research activities. Mathematics, and Mathematics Subject Classification, will be the focuses around which we will move to discover a variety of presentation modes, protocols and tools for human and machine interoperability. The Open Archives Initiative (OAI) is intended to be the effective framework for such a play....

  14. A Hybrid Ensemble Learning Approach to Star-Galaxy Classification

    CERN Document Server

    Kim, Edward J; Kind, Matias Carrasco

    2015-01-01

    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, we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2, SDSS, VIPERS, and VVDS, 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, s...

  15. A computerized English-Spanish correlation index to five biomedical library classification schemes based on MeSH.

    Science.gov (United States)

    Muench, E V

    1971-07-01

    A computerized English/Spanish correlation index to five biomedical library classification schemes and a computerized English/Spanish, Spanish/English listings of MeSH are described. The index was accomplished by supplying appropriate classification numbers of five classification schemes (National Library of Medicine; Library of Congress; Dewey Decimal; Cunningham; Boston Medical) to MeSH and a Spanish translation of MeSH The data were keypunched, merged on magnetic tape, and sorted in a computer alphabetically by English and Spanish subject headings and sequentially by classification number. SOME BENEFITS AND USES OF THE INDEX ARE: a complete index to classification schemes based on MeSH terms; a tool for conversion of classification numbers when reclassifying collections; a Spanish index and a crude Spanish translation of five classification schemes; a data base for future applications, e.g., automatic classification. Other classification schemes, such as the UDC, and translations of MeSH into other languages can be added.

  16. Sound classification of dwellings – A diversity of national schemes in Europe

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2011-01-01

    constructions fulfilling different classes. The current variety of descriptors and classes also causes trade barriers. Thus, there is a need to harmonize characteristics of the schemes, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing......Sound classification schemes for dwellings exist in ten countries in Europe, typically prepared and published as national standards. The schemes define quality classes intended to reflect different levels of acoustical comfort. The main criteria concern airborne and impact sound insulation between...... dwellings, facade sound insulation and installation noise. This paper presents the sound classification schemes in Europe and compares the class criteria for sound insulation between dwellings. The schemes have been implemented and revised gradually since the early 1990s. However, due to lack...

  17. Electroencephalography epilepsy classifications using hybrid cuckoo search and neural network

    Science.gov (United States)

    Pratiwi, A. B.; Damayanti, A.; Miswanto

    2017-07-01

    Epilepsy is a condition that affects the brain and causes repeated seizures. This seizure is episodes that can vary and nearly undetectable to long periods of vigorous shaking or brain contractions. Epilepsy often can be confirmed with an electrocephalography (EEG). Neural Networks has been used in biomedic signal analysis, it has successfully classified the biomedic signal, such as EEG signal. In this paper, a hybrid cuckoo search and neural network are used to recognize EEG signal for epilepsy classifications. The weight of the multilayer perceptron is optimized by the cuckoo search algorithm based on its error. The aim of this methods is making the network faster to obtained the local or global optimal then the process of classification become more accurate. Based on the comparison results with the traditional multilayer perceptron, the hybrid cuckoo search and multilayer perceptron provides better performance in term of error convergence and accuracy. The purpose methods give MSE 0.001 and accuracy 90.0 %.

  18. Polarimetric Synthetic Aperture Radar Image Classification by a Hybrid Method

    Institute of Scientific and Technical Information of China (English)

    Kamran Ullah Khan; YANG Jian

    2007-01-01

    Different methods proposed so far for accurate classification of land cover types in polarimetric synthetic aperture radar (SAR) image are data specific and no general method is available. A novel hybrid framework for this classification was developed in this work. A set of effective features derived from the coherence matrix of polarimetric SARdata was proposed.Constituents of the feature set are wavelet,texture,and nonlinear features.The proposed feature set has a strong discrimination power. A neural network was used as the classification engine in a unique way. By exploiting the speed of the conjugate gradient method and the convergence rate of the Levenberg-Marquardt method (near the optimal point), an overall speed up of the classification procedure was achieved. Principal component analysis(PCA)was used to shrink the dimension of the feature vector without sacrificing much of the classification accuracy. The proposed approach is compared with the maximum likelihood estimator (MLE)based on the complex Wishart distribution and the results show the superiority of the proposed method,with the average classification accuracy by the proposed method(95.4%)higher than that of the MLE(93.77%). Use of PCA to reduce the dimensionality of the feature vector helps reduce the memory requirements and computational cost, thereby enhancing the speed of the process.

  19. Hybrid overlay metrology with CDSEM in a BEOL patterning scheme

    Science.gov (United States)

    Leray, Philippe; Jehoul, Christiane; Inoue, Osamu; Okagawa, Yutaka

    2015-03-01

    Overlay metrology accuracy is a major concern for our industry. Advanced logic process require more tighter overlay control for multipatterning schemes. TIS (Tool Induced Shift) and WIS (Wafer Induced Shift) are the main issues for IBO (Image Based Overlay) and DBO (Diffraction Based Overlay). Methods of compensation have been introduced, some are even very efficient to reduce these measured offsets. Another related question is about the overlay target designs. These targets are never fully representative of the design rules, strong efforts have been achieved, but the device cannot be completely duplicated. Ideally, we would like to measure in the device itself to verify the real overlay value. Top down CDSEM can measure critical dimensions of any structure, it is not dependent of specific target design. It can also measure the overlay errors but only in specific cases like LELE (Litho Etch Litho Etch) after final patterning. In this paper, we will revisit the capability of the CDSEM at final patterning by measuring overlay in dedicated targets as well as inside a logic and an SRAM design. In the dedicated overlay targets, we study the measurement differences between design rules gratings and relaxed pitch gratings. These relaxed pitch which are usually used in IBO or DBO targets. Beyond this "simple" LELE case, we will explore the capability of the CDSEM to measure overlay even if not at final patterning, at litho level. We will assess the hybridization of DBO and CDSEM for reference to optical tools after final patterning. We will show that these reference data can be used to validate the DBO overlay results (correctables and residual fingerprints).

  20. Secure searching of biomarkers through hybrid homomorphic encryption scheme.

    Science.gov (United States)

    Kim, Miran; Song, Yongsoo; Cheon, Jung Hee

    2017-07-26

    As genome sequencing technology develops rapidly, there has lately been an increasing need to keep genomic data secure even when stored in the cloud and still used for research. We are interested in designing a protocol for the secure outsourcing matching problem on encrypted data. We propose an efficient method to securely search a matching position with the query data and extract some information at the position. After decryption, only a small amount of comparisons with the query information should be performed in plaintext state. We apply this method to find a set of biomarkers in encrypted genomes. The important feature of our method is to encode a genomic database as a single element of polynomial ring. Since our method requires a single homomorphic multiplication of hybrid scheme for query computation, it has the advantage over the previous methods in parameter size, computation complexity, and communication cost. In particular, the extraction procedure not only prevents leakage of database information that has not been queried by user but also reduces the communication cost by half. We evaluate the performance of our method and verify that the computation on large-scale personal data can be securely and practically outsourced to a cloud environment during data analysis. It takes about 3.9 s to search-and-extract the reference and alternate sequences at the queried position in a database of size 4M. Our solution for finding a set of biomarkers in DNA sequences shows the progress of cryptographic techniques in terms of their capability can support real-world genome data analysis in a cloud environment.

  1. A Hybrid MacCormack-type Scheme for Computational Aeroacoustics

    Science.gov (United States)

    Yazdani, Soroush

    A new type of MacCormack scheme, using a modified Low Dissipation and Dispersion Runge-Kutta time marching method, is presented. This scheme is using two stages in every step which implements biased spatial differencing stencils and for the remaining stages uses non-dissipative central differencing stencils. Because of using the MacCormack-type scheme in this method, the new scheme carries an inherent artificial dissipation which uses the ease of implementing boundary condition specifications of a two-stage MacCormack scheme.

  2. Sound classification of dwellings – A diversity of national schemes in Europe

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2011-01-01

    dwellings, facade sound insulation and installation noise. This paper presents the sound classification schemes in Europe and compares the class criteria for sound insulation between dwellings. The schemes have been implemented and revised gradually since the early 1990s. However, due to lack...... constructions fulfilling different classes. The current variety of descriptors and classes also causes trade barriers. Thus, there is a need to harmonize characteristics of the schemes, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing...... Constructions", has been established and runs 2009-2013. The main objectives of TU0901 are to prepare proposals for harmonized sound insulation descriptors and for a European sound classification scheme with a number of quality classes for dwellings....

  3. The Nutraceutical Bioavailability Classification Scheme: Classifying Nutraceuticals According to Factors Limiting their Oral Bioavailability.

    Science.gov (United States)

    McClements, David Julian; Li, Fang; Xiao, Hang

    2015-01-01

    The oral bioavailability of a health-promoting dietary component (nutraceutical) may be limited by various physicochemical and physiological phenomena: liberation from food matrices, solubility in gastrointestinal fluids, interaction with gastrointestinal components, chemical degradation or metabolism, and epithelium cell permeability. Nutraceutical bioavailability can therefore be improved by designing food matrices that control their bioaccessibility (B*), absorption (A*), and transformation (T*) within the gastrointestinal tract (GIT). This article reviews the major factors influencing the gastrointestinal fate of nutraceuticals, and then uses this information to develop a new scheme to classify the major factors limiting nutraceutical bioavailability: the nutraceutical bioavailability classification scheme (NuBACS). This new scheme is analogous to the biopharmaceutical classification scheme (BCS) used by the pharmaceutical industry to classify drug bioavailability, but it contains additional factors important for understanding nutraceutical bioavailability in foods. The article also highlights potential strategies for increasing the oral bioavailability of nutraceuticals based on their NuBACS designation (B*A*T*).

  4. Joint efforts to harmonize sound insulation descriptors and classification schemes in Europe (COST TU0901)

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2010-01-01

    Sound insulation descriptors, regulatory requirements and classification schemes in Europe represent a high degree of diversity. One implication is very little exchange of experience of housing design and construction details for different levels of sound insulation; another is trade barriers...... Aspects in Sustainable Urban Housing Constructions", has been approved and runs 2009-2013. The main objectives are to prepare proposals for harmonized sound insulation descriptors and for a European sound classification scheme. Other goals are e.g. to establish a catalogue of sound insulation data...

  5. Brownian-motion ensembles of random matrix theory: A classification scheme and an integral transform method

    Energy Technology Data Exchange (ETDEWEB)

    Macedo-Junior, A.F. [Departamento de Fisica, Laboratorio de Fisica Teorica e Computacional, Universidade Federal de Pernambuco, 50670-901 Recife, PE (Brazil)]. E-mail: ailton@df.ufpe.br; Macedo, A.M.S. [Departamento de Fisica, Laboratorio de Fisica Teorica e Computacional, Universidade Federal de Pernambuco, 50670-901 Recife, PE (Brazil)

    2006-09-25

    We study a class of Brownian-motion ensembles obtained from the general theory of Markovian stochastic processes in random-matrix theory. The ensembles admit a complete classification scheme based on a recent multivariable generalization of classical orthogonal polynomials and are closely related to Hamiltonians of Calogero-Sutherland-type quantum systems. An integral transform is proposed to evaluate the n-point correlation function for a large class of initial distribution functions. Applications of the classification scheme and of the integral transform to concrete physical systems are presented in detail.

  6. Intelligent Control Scheme of Engineering Machinery of Cluster Hybrid System

    Institute of Scientific and Technical Information of China (English)

    GAO Qiang; WANG Hongli

    2005-01-01

    In a hybrid system, the subsystems with discrete dynamics play a central role in a hybrid system. In the course of engineering machinery of cluster construction, the discrete control law is hard to obtain because the construction environment is complex and there exist many affecting factors. In this paper, hierarchically intelligent control, expert control and fuzzy control are introduced into the discrete subsystems of engineering machinery of cluster hybrid system, so as to rebuild the hybrid system and make the discrete control law easily and effectively obtained. The structures, reasoning mechanism and arithmetic of intelligent control are replanted to discrete dynamic, conti-nuous process and the interface of the hybrid system. The structures of three types of intelligent hybrid system are presented and the human experiences summarized from engineering machinery of cluster are taken into account.

  7. Enhanced Harmonic Up-Conversion Using a Hybrid HGHG-EEHG Scheme

    Energy Technology Data Exchange (ETDEWEB)

    Marksteiner, Quinn R. [Los Alamos National Laboratory; Bishofberger, Kip A. [Los Alamos National Laboratory; Carlsten, Bruce E. [Los Alamos National Laboratory; Freund, Henry P. [Los Alamos National Laboratory; Yampolsky, Nikolai A. [Los Alamos National Laboratory

    2012-04-30

    We introduce a novel harmonic generation scheme which can be used, for a given desired harmonic, to achieve higher bunching factors, weaker chicanes, and/or less final energy spread than can be achieved using Echo-Enabled Harmonic Generation. This scheme only requires a single laser with relatively low power, and is a hybrid of High-Gain Harmonic Generation and EEHG. We present a design of this scheme applied to the Next Generation Light Source (NGLS).

  8. 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.

  9. Standard land-cover classification scheme for remote-sensing applications in South Africa

    CSIR Research Space (South Africa)

    Thompson, M

    1996-01-01

    Full Text Available For large areas, satellite remote-sensing techniques have now become the single most effective method for land-cover and land-use data acquisition. However, the majority of land-cover (and land-use) classification schemes used have been developed...

  10. Job Performance Measurement Classification Scheme for Validation Research in the Military.

    Science.gov (United States)

    1986-02-01

    the information and procedures used with this approach. In order to develop a measurement methodology for job performance , a classification scheme of... job performance measurement quality was needed (a) to summarize and organize research progress in terms of previous empirical work and (b) to identify...literature review and specific directions for future job performance measurement research.

  11. A Classification Scheme for Adult Education. Education Libraries Bulletin, Supplement Twelve.

    Science.gov (United States)

    Greaves, Monica A., Comp.

    This classification scheme, based on the 'facet formula' theory of Ranganathan, is designed primarily for the library of the National Institute of Adult Education in London, England. Kinds of persons being educated (educands), methods and problems of education, specific countries, specific organizations, and forms in which the information is…

  12. Hybrid flux splitting schemes for numerical resolution of two-phase flows

    Energy Technology Data Exchange (ETDEWEB)

    Flaatten, Tore

    2003-07-01

    This thesis deals with the construction of numerical schemes for approximating. solutions to a hyperbolic two-phase flow model. Numerical schemes for hyperbolic models are commonly divided in two main classes: Flux Vector Splitting (FVS) schemes which are based on scalar computations and Flux Difference Splitting (FDS) schemes which are based on matrix computations. FVS schemes are more efficient than FDS schemes, but FDS schemes are more accurate. The canonical FDS schemes are the approximate Riemann solvers which are based on a local decomposition of the system into its full wave structure. In this thesis the mathematical structure of the model is exploited to construct a class of hybrid FVS/FDS schemes, denoted as Mixture Flux (MF) schemes. This approach is based on a splitting of the system in two components associated with the pressure and volume fraction variables respectively, and builds upon hybrid FVS/FDS schemes previously developed for one-phase flow models. Through analysis and numerical experiments it is demonstrated that the MF approach provides several desirable features, including (1) Improved efficiency compared to standard approximate Riemann solvers, (2) Robustness under stiff conditions, (3) Accuracy on linear and nonlinear phenomena. In particular it is demonstrated that the framework allows for an efficient weakly implicit implementation, focusing on an accurate resolution of slow transients relevant for the petroleum industry. (author)

  13. Sound classification schemes in Europe - Quality classes intended for renovated housing

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2010-01-01

    According to social surveys in several European countries, occupants of multifamily housing are considerably annoyed by noise from neighbours’ activities. The noise issue has also received increasing attention from WHO. Neighbour noise has been identified as a health problem and reduction of noise...... exposure in the home included in the proposed main objectives for a housing policy. In most countries in Europe, building regulations specify minimum requirements concerning acoustical conditions for new dwellings. In addition, several countries have introduced sound classification schemes with classes...... intended to reflect different levels of acoustical comfort. Consequently, acoustic requirements for a dwelling can be specified as the legal minimum requirements or as a specific class in a classification scheme. Most schemes have both higher classes than corresponding to the regulatory requirements...

  14. A Hybrid Advection Scheme for Conserving Angular Momentum on a Refined Cartesian Mesh

    CERN Document Server

    Byerly, Zachary D; Tohline, Joel E; Marcello, Dominic C

    2014-01-01

    We test a new "hybrid" scheme for simulating dynamical fluid flows in which cylindrical components of the momentum are advected across a rotating Cartesian coordinate mesh. This hybrid scheme allows us to conserve angular momentum to machine precision while capitalizing on the advantages offered by a Cartesian mesh, such as a straightforward implementation of mesh refinement. Our test focuses on measuring the real and imaginary parts of the eigenfrequency of unstable axisymmetric modes that naturally arise in massless polytropic tori having a range of different aspect ratios, and quantifying the uncertainty in these measurements. Our measured eigenfrequencies show good agreement with the results obtained from the linear stability analysis of Kojima (1986) and from nonlinear hydrodynamic simulations performed on a cylindrical coordinate mesh by Woodward et al. (1994). When compared against results conducted with a traditional Cartesian advection scheme, the hybrid scheme achieves qualitative convergence at the...

  15. A comparison between national scheme for the acoustic classification of dwellings in Europe and in the U.S

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2015-01-01

    work item. This paper compares sound classification schemes in Europe with the current situation in the United States. Economic evaluations related to the technological choices necessary to achieve different sound classification classes are also discussed. The hope is that a common sound classification......, focusing on sound insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant...... diversity in terms of descriptors, number of classes, and class intervals occurred between national schemes. However, a proposal ”acoustic classification scheme for dwellings” has been developed recently in the European COST Action TU0901 with 32 member countries. This proposal has been accepted as an ISO...

  16. Hybrid Explicit Residual Distribution Scheme for Compressible Multiphase Flows

    Science.gov (United States)

    Bacigaluppi, Paola; Abgrall, Rémi; Kaman, Tulin

    2017-03-01

    The aim of this work is the development of a fully explicit scheme in the framework of time dependent hyperbolic problems with strong interacting discontinuities to retain high order accuracy in the context of compressible multiphase flows. A new methodology is presented to compute compressible two-fluid problems applied to the five equation reduced model given in Kapila et al. (Physics of Fluids 2001). With respect to other contributions in that area, we investigate a method that provides mesh convergence to the exact solutions, where the studied non-conservative system is associated to consistent jump relations. The adopted scheme consists of a coupled predictor-corrector scheme, which follows the concept of residual distributions in Ricchiuto and Abgrall (J. Comp. Physics 2010), with a classical Glimm’s scheme (J. Sci. Stat. Comp. 1982) applied to the area where a shock is occurring. This numerical methodology can be easily extended to unstructured meshes. Test cases on a perfect gas for a two phase compressible flow on a Riemann problem have verified that the approximation converges to its exact solution. The results have been compared with the pure Glimm’s scheme and the expected exact solution, finding a good overlap.

  17. An intelligent hybrid scheme for optimizing parking space: A Tabu metaphor and rough set based approach

    Directory of Open Access Journals (Sweden)

    Soumya Banerjee

    2011-03-01

    Full Text Available Congested roads, high traffic, and parking problems are major concerns for any modern city planning. Congestion of on-street spaces in official neighborhoods may give rise to inappropriate parking areas in office and shopping mall complex during the peak time of official transactions. This paper proposes an intelligent and optimized scheme to solve parking space problem for a small city (e.g., Mauritius using a reactive search technique (named as Tabu Search assisted by rough set. Rough set is being used for the extraction of uncertain rules that exist in the databases of parking situations. The inclusion of rough set theory depicts the accuracy and roughness, which are used to characterize uncertainty of the parking lot. Approximation accuracy is employed to depict accuracy of a rough classification [1] according to different dynamic parking scenarios. And as such, the hybrid metaphor proposed comprising of Tabu Search and rough set could provide substantial research directions for other similar hard optimization problems.

  18. A Hybrid Nonlinear Control Scheme for Active Magnetic Bearings

    Science.gov (United States)

    Xia, F.; Albritton, N. G.; Hung, J. Y.; Nelms, R. M.

    1996-01-01

    A nonlinear control scheme for active magnetic bearings is presented in this work. Magnet winding currents are chosen as control inputs for the electromechanical dynamics, which are linearized using feedback linearization. Then, the desired magnet currents are enforced by sliding mode control design of the electromagnetic dynamics. The overall control scheme is described by a multiple loop block diagram; the approach also falls in the class of nonlinear controls that are collectively known as the 'integrator backstepping' method. Control system hardware and new switching power electronics for implementing the controller are described. Various experiments and simulation results are presented to demonstrate the concepts' potentials.

  19. VLSI Implementation of Hybrid Wave-Pipelined 2D DWT Using Lifting Scheme

    Directory of Open Access Journals (Sweden)

    G. Seetharaman

    2008-01-01

    Full Text Available A novel approach is proposed in this paper for the implementation of 2D DWT using hybrid wave-pipelining (WP. A digital circuit may be operated at a higher frequency by using either pipelining or WP. Pipelining requires additional registers and it results in more area, power dissipation and clock routing complexity. Wave-pipelining does not have any of these disadvantages but requires complex trial and error procedure for tuning the clock period and clock skew between input and output registers. In this paper, a hybrid scheme is proposed to get the benefits of both pipelining and WP techniques. In this paper, two automation schemes are proposed for the implementation of 2D DWT using hybrid WP on both Xilinx, San Jose, CA, USA and Altera FPGAs. In the first scheme, Built-in self-test (BIST approach is used to choose the clock skew and clock period for I/O registers between the wave-pipelined blocks. In the second approach, an on-chip soft-core processor is used to choose the clock skew and clock period. The results for the hybrid WP are compared with nonpipelined and pipelined approaches. From the implementation results, the hybrid WP scheme requires the same area but faster than the nonpipelined scheme by a factor of 1.25–1.39. The pipelined scheme is faster than the hybrid scheme by a factor of 1.15–1.39 at the cost of an increase in the number of registers by a factor of 1.78–2.73, increase in the number of LEs by a factor of 1.11–1.32 and it increases the clock routing complexity.

  20. A new Fourier transform based CBIR scheme for mammographic mass classification: a preliminary invariance assessment

    Science.gov (United States)

    Gundreddy, Rohith Reddy; Tan, Maxine; Qui, Yuchen; Zheng, Bin

    2015-03-01

    The purpose of this study is to develop and test a new content-based image retrieval (CBIR) scheme that enables to achieve higher reproducibility when it is implemented in an interactive computer-aided diagnosis (CAD) system without significantly reducing lesion classification performance. This is a new Fourier transform based CBIR algorithm that determines image similarity of two regions of interest (ROI) based on the difference of average regional image pixel value distribution in two Fourier transform mapped images under comparison. A reference image database involving 227 ROIs depicting the verified soft-tissue breast lesions was used. For each testing ROI, the queried lesion center was systematically shifted from 10 to 50 pixels to simulate inter-user variation of querying suspicious lesion center when using an interactive CAD system. The lesion classification performance and reproducibility as the queried lesion center shift were assessed and compared among the three CBIR schemes based on Fourier transform, mutual information and Pearson correlation. Each CBIR scheme retrieved 10 most similar reference ROIs and computed a likelihood score of the queried ROI depicting a malignant lesion. The experimental results shown that three CBIR schemes yielded very comparable lesion classification performance as measured by the areas under ROC curves with the p-value greater than 0.498. However, the CBIR scheme using Fourier transform yielded the highest invariance to both queried lesion center shift and lesion size change. This study demonstrated the feasibility of improving robustness of the interactive CAD systems by adding a new Fourier transform based image feature to CBIR schemes.

  1. Codon sextets with leading role of serine create "ideal" symmetry classification scheme of the genetic code.

    Science.gov (United States)

    Rosandić, Marija; Paar, Vladimir

    2014-06-10

    The standard classification scheme of the genetic code is organized for alphabetic ordering of nucleotides. Here we introduce the new, "ideal" classification scheme in compact form, for the first time generated by codon sextets encoding Ser, Arg and Leu amino acids. The new scheme creates the known purine/pyrimidine, codon-anticodon, and amino/keto type symmetries and a novel A+U rich/C+G rich symmetry. This scheme is built from "leading" and "nonleading" groups of 32 codons each. In the ensuing 4 × 16 scheme, based on trinucleotide quadruplets, Ser has a central role as initial generator. Six codons encoding Ser and six encoding Arg extend continuously along a linear array in the "leading" group, and together with four of six Leu codons uniquely define construction of the "leading" group. The remaining two Leu codons enable construction of the "nonleading" group. The "ideal" genetic code suggests the evolution of genetic code with serine as an initiator. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Evaluation of Effectiveness of Wavelet Based Denoising Schemes Using ANN and SVM for Bearing Condition Classification

    Directory of Open Access Journals (Sweden)

    Vijay G. S.

    2012-01-01

    Full Text Available The wavelet based denoising has proven its ability to denoise the bearing vibration signals by improving the signal-to-noise ratio (SNR and reducing the root-mean-square error (RMSE. In this paper seven wavelet based denoising schemes have been evaluated based on the performance of the Artificial Neural Network (ANN and the Support Vector Machine (SVM, for the bearing condition classification. The work consists of two parts, the first part in which a synthetic signal simulating the defective bearing vibration signal with Gaussian noise was subjected to these denoising schemes. The best scheme based on the SNR and the RMSE was identified. In the second part, the vibration signals collected from a customized Rolling Element Bearing (REB test rig for four bearing conditions were subjected to these denoising schemes. Several time and frequency domain features were extracted from the denoised signals, out of which a few sensitive features were selected using the Fisher’s Criterion (FC. Extracted features were used to train and test the ANN and the SVM. The best denoising scheme identified, based on the classification performances of the ANN and the SVM, was found to be the same as the one obtained using the synthetic signal.

  3. Hybrid, explicit-implicit, finite-volume schemes on unstructured grids for unsteady compressible flows

    Science.gov (United States)

    Timofeev, Evgeny; Norouzi, Farhang

    2016-06-01

    The motivation for using hybrid, explicit-implicit, schemes rather than fully implicit or explicit methods for some unsteady high-speed compressible flows with shocks is firstly discussed. A number of such schemes proposed in the past are briefly overviewed. A recently proposed hybridization approach is then introduced and used for the development of a hybrid, explicit-implicit, TVD (Total Variation Diminishing) scheme of the second order in space and time on smooth solutions in both, explicit and implicit, modes for the linear advection equation. Further generalizations of this finite-volume method for the Burgers, Euler and Navier-Stokes equations discretized on unstructured grids are mentioned in the concluding remarks.

  4. ANALYSIS OF AUGMENTED THREE-FIELD MACRO-HYBRID MIXED FINITE ELEMENT SCHEMES

    Institute of Scientific and Technical Information of China (English)

    Gonzalo Alduncin

    2009-01-01

    On the basis of composition duality principles, augmented three-field macro-hybrid mixed variational problems and finite element schemes are analyzed. The compati-bility condition adopted here, for compositional dualization, is the coupling operator surjec-tivity, property that expresses in a general operator sense the Ladysenskaja-Babuska-Brezzi inf-sup condition. Variational macro-hybridization is performed under the assumption of decomposable primal and dual spaces relative to nonoverlapping domain decompositions. Then, through compositional dualization macro-hybrid mixed problems are obtained, with internal boundary dual traces as Lagrange multipliers. Also, "mass" preconditioned aug-mentation of three-field formulations are derived, stabilizing macro-hybrid mixed finite element schemes and rendering possible speed up of rates of convergence. Dual mixed incompressible Darcy flow problems illustrate the theory throughout the paper.

  5. Evaluation of rock mass classification schemes: a case study from the Bowen Basin, Australia

    Science.gov (United States)

    Brook, Martin; Hebblewhite, Bruce; Mitra, Rudrajit

    2016-04-01

    The development of an accurate engineering geological model and adequate knowledge of spatial variation in rock mass conditions are important prerequisites for slope stability analyses, tunnel design, mine planning and risk management. Rock mass classification schemes such as Rock Mass Rating (RMR), Coal Mine Roof Rating (CMRR), Q-system and Roof Strength Index (RSI) have been used for a range of engineering geological applications, including transport tunnels, "hard rock" mining and underground and open-cut coal mines. Often, rock mass classification schemes have been evaluated on subaerial exposures, where weathering has affected joint characteristics and intact strength. In contrast, the focus of this evaluation of the above classification schemes is an underground coal mine in the Bowen Basin, central Queensland, Australia, 15 km east of the town of Moranbah. Rock mass classification was undertaken at 68 sites across the mine. Both the target coal seam and overlying rock show marked spatial variability in terms of RMR, CMRR and Q, but RSI showed limited sensitivity to changes in rock mass condition. Relationships were developed between different parameters with varying degrees of success. A mine-wide analysis of faulting was undertaken, and compared with in situ stress field and local-scale measurements of joint and cleat. While there are no unequivocal relationships between rock mass classification parameters and faulting, a central graben zone shows heterogeneous rock mass properties. The corollary is that if geological features can be accurately defined by remote sensing technologies, then this can assist in predicting rock mass conditions and risk management ahead of development and construction.

  6. Attribution of local climate zones using a multitemporal land use/land cover classification scheme

    Science.gov (United States)

    Wicki, Andreas; Parlow, Eberhard

    2017-04-01

    Worldwide, the number of people living in an urban environment exceeds the rural population with increasing tendency. Especially in relation to global climate change, cities play a major role considering the impacts of extreme heat waves on the population. For urban planners, it is important to know which types of urban structures are beneficial for a comfortable urban climate and which actions can be taken to improve urban climate conditions. Therefore, it is essential to differ between not only urban and rural environments, but also between different levels of urban densification. To compare these built-up types within different cities worldwide, Stewart and Oke developed the concept of local climate zones (LCZ) defined by morphological characteristics. The original LCZ scheme often has considerable problems when adapted to European cities with historical city centers, including narrow streets and irregular patterns. In this study, a method to bridge the gap between a classical land use/land cover (LULC) classification and the LCZ scheme is presented. Multitemporal Landsat 8 data are used to create a high accuracy LULC map, which is linked to the LCZ by morphological parameters derived from a high-resolution digital surface model and cadastral data. A bijective combination of the different classification schemes could not be achieved completely due to overlapping threshold values and the spatially homogeneous distribution of morphological parameters, but the attribution of LCZ to the LULC classification was successful.

  7. A Computerized English-Spanish Correlation Index to Five Biomedical Library Classification Schemes Based on MeSH*

    Science.gov (United States)

    Muench, Eugene V.

    1971-01-01

    A computerized English/Spanish correlation index to five biomedical library classification schemes and a computerized English/Spanish, Spanish/English listings of MeSH are described. The index was accomplished by supplying appropriate classification numbers of five classification schemes (National Library of Medicine; Library of Congress; Dewey Decimal; Cunningham; Boston Medical) to MeSH and a Spanish translation of MeSH The data were keypunched, merged on magnetic tape, and sorted in a computer alphabetically by English and Spanish subject headings and sequentially by classification number. Some benefits and uses of the index are: a complete index to classification schemes based on MeSH terms; a tool for conversion of classification numbers when reclassifying collections; a Spanish index and a crude Spanish translation of five classification schemes; a data base for future applications, e.g., automatic classification. Other classification schemes, such as the UDC, and translations of MeSH into other languages can be added. PMID:5172471

  8. A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model

    Science.gov (United States)

    Mizzi, A. P.

    2011-12-01

    A regional hybrid GSI/ETKF data assimilation scheme for the WRF/ARW model Arthur P. Mizzi National Center for Atmospheric Research Boulder, CO 80307 303-497-8987 mizzi@ucar.edu Recently, there has been increased interest in hybrid variational data assimilation due to its ability to improve numerical weather forecast accuracy by incorporating ensemble error information into the data assimilation process (Buehner, 2010a, b; Wang 2010). In this paper, we introduce a GSI/ETKF regional hybrid (Mizzi, 2011). The GSI/ETKF regional hybrid uses a modified version of NOAA/EMC's GSI global hybrid (Wang, 2010) for the ensemble mean analysis and an ETKF (Bishop, et. al., 2001) to update the ensemble perturbations. We tested the GSI/ETKF regional hybrid by applying it to cycling experiments with WRF/ARW on a coarse-resolution domain covering the continental United States (CONUS) that: (i) compared different ETKF schemes, and (ii) reduced and held the number of ETKF observations constant. The results from those experiments showed that: (i) the ETKF scheme requiring the least amount of inflation provided the lowest 12-hr forecast RMSEs (ii) holding the number of ETKF observations constant removed the oscillation in the posterior ETKF ensemble spread noted by Bowler et al., (2008), and (iii) reducing the number of ETKF observations lowered the 12-hr forecast RMSEs. Presently, we are extending this work to a comparison of the GSI/ETKF regional hybrid with a GSI/LETKF regional hybrid based on the LETKF of Ott, et. al., (2004) and a GSI/EnKF regional hybrid based on the DART EnKF (Anderson et. al., 2009). Generally, the GSI/LETKF and GSI/EnKF schemes require less ensemble spread inflation compared to the GSI/ETKF scheme. Consequently, we expect the GSI/LETKF and GSI/EnKF schemes to provide lower 12-hr forecast RMSEs compared to the GSI/ETKF results. Our preliminary results are consistent with that supposition.

  9. 3D HYBRID DEPTH MIGRATION AND FOUR-WAY SPLITTING SCHEMES

    Institute of Scientific and Technical Information of China (English)

    Wen-sheng Zhang; Guan-quan Zhang

    2006-01-01

    The alternately directional implicit (ADI) scheme is usually used in 3D depth migration.It splits the 3D square-root operator along crossline and inline directions alternately. In this paper, based on the ideal of data line, the four-way splitting schemes and their splitting errors for the finite-difference (FD) method and the hybrid method are investigated. The wavefield extrapolation of four-way splitting scheme is accomplished on a data line and is stable unconditionally. Numerical analysis of splitting errors show that the two-way FD migration have visible numerical anisotropic errors, and that four-way FD migration has much less splitting errors than two-way FD migration has. For the hybrid method, the differences of numerical anisotropic errors between two-way scheme and four-way scheme are small in the case of lower lateral velocity variations. The schemes presented in this paper can be used in 3D post-stack or prestack depth migration. Two numerical calculations of 3D depth migration are completed. One is the four-way FD and hybrid 3D post-stack depth migration for an impulse response, which shows that the anisotropic errors can be eliminated effectively in the cases of constant and variable velocity variations. The other is the 3D shot-profile prestack depth migration for SEG/EAEG benchmark model with twoway hybrid splitting scheme, which presents good imaging results. The Message Passing Interface (MPI) programme based on shot number is adopted.

  10. Agent-based power sharing scheme for active hybrid power sources

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Zhenhua [Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33146 (United States)

    2008-02-15

    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. (author)

  11. A Novel Homogenous Hybridization Scheme for Performance Improvement of Support Vector Machines Regression in Reservoir Characterization

    Directory of Open Access Journals (Sweden)

    Kabiru O. Akande

    2016-01-01

    Full Text Available Hybrid computational intelligence is defined as a combination of multiple intelligent algorithms such that the resulting model has superior performance to the individual algorithms. Therefore, the importance of fusing two or more intelligent algorithms to achieve better performance cannot be overemphasized. In this work, a novel homogenous hybridization scheme is proposed for the improvement of the generalization and predictive ability of support vector machines regression (SVR. The proposed and developed hybrid SVR (HSVR works by considering the initial SVR prediction as a feature extraction process and then employs the SVR output, which is the extracted feature, as its sole descriptor. The developed hybrid model is applied to the prediction of reservoir permeability and the predicted permeability is compared to core permeability which is regarded as standard in petroleum industry. The results show that the proposed hybrid scheme (HSVR performed better than the existing SVR in both generalization and prediction ability. The outcome of this research will assist petroleum engineers to effectively predict permeability of carbonate reservoirs with higher degree of accuracy and will invariably lead to better reservoir. Furthermore, the encouraging performance of this hybrid will serve as impetus for further exploring homogenous hybrid system.

  12. 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.

  13. HYBRID SCHEMES OF HOMOGENEOUS AND HETEROGENEOUS CLASSIFIERS FOR CURSIVE WORD RECOGNITION

    NARCIS (Netherlands)

    Kim, J.H.; Kim, K.K.; Suen, C.Y.

    2004-01-01

    Sophisticated hybrid schemes of the homogeneous and heterogeneous classifiers for cursive word recognition are presented. Two homogeneous MLPs (multi­layer perceptrons) are combined into a new single powerful classifier at the architectural level, and HMM (hidden Markov model) is added to the new cl

  14. A Multi-layer Hybrid Framework for Dimensional Emotion Classification

    NARCIS (Netherlands)

    Nicolaou, Mihalis A.; Gunes, Hatice; Pantic, Maja

    2011-01-01

    This paper investigates dimensional emotion prediction and classification from naturalistic facial expressions. Similarly to many pattern recognition problems, dimensional emotion classification requires generating multi-dimensional outputs. To date, classification for valence and arousal dimensions

  15. Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks

    DEFF Research Database (Denmark)

    Hagen, Espen; Dahmen, David; Stavrinou, Maria L

    2016-01-01

    and electrophysiological features of neurons near the recording electrode, as well as synaptic inputs from the entire network. Here we propose a hybrid modeling scheme combining efficient point-neuron network models with biophysical principles underlying LFP generation by real neurons. The LFP predictions rely...... on populations of network-equivalent multicompartment neuron models with layer-specific synaptic connectivity, can be used with an arbitrary number of point-neuron network populations, and allows for a full separation of simulated network dynamics and LFPs. We apply the scheme to a full-scale cortical network...... model for a ∼1 mm(2) patch of primary visual cortex, predict laminar LFPs for different network states, assess the relative LFP contribution from different laminar populations, and investigate effects of input correlations and neuron density on the LFP. The generic nature of the hybrid scheme and its...

  16. Hybrid TOA/AOA Schemes for Mobile Location In Cellular Communications Systems

    Directory of Open Access Journals (Sweden)

    Chien-Sheng Chen

    2010-06-01

    Full Text Available Wireless location is to determine the position of t he mobile station (MS in wireless communication networks. Due to the measurements with large errors , location schemes give poorer performance in non-line-of-sight (NLOS environments. This paper i llustrates methods to integrate all the available heterogeneous measurements to achieve more accurate location estimation. The proposed hybrid schemes combine time of arrival (TOA at seven BSs and angle of arrival (AOA information at the serving BS to give location estimation of the MS. T he schemes mitigate the NLOS effect simply by the weighted sum of the intersections between seven TOA circles and the AOA line without requiring priori knowledge of NLOS error statistics. Different NLOS models were used to evaluate the proposed methods. It is shown by the simulation results that the prop osed methods provide better location accuracy comparing with Taylor series algorithm (TSA and th e hybrid lines of position algorithm (HLOP.

  17. A hybrid convection scheme for use in non-hydrostatic numerical weather prediction models

    Directory of Open Access Journals (Sweden)

    Volker Kuell

    2008-12-01

    Full Text Available The correct representation of convection in numerical weather prediction (NWP models is essential for quantitative precipitation forecasts. Due to its small horizontal scale convection usually has to be parameterized, e.g. by mass flux convection schemes. Classical schemes originally developed for use in coarse grid NWP models assume zero net convective mass flux, because the whole circulation of a convective cell is confined to the local grid column and all convective mass fluxes cancel out. However, in contemporary NWP models with grid sizes of a few kilometers this assumption becomes questionable, because here convection is partially resolved on the grid. To overcome this conceptual problem we propose a hybrid mass flux convection scheme (HYMACS in which only the convective updrafts and downdrafts are parameterized. The generation of the larger scale environmental subsidence, which may cover several grid columns, is transferred to the grid scale equations. This means that the convection scheme now has to generate a net convective mass flux exerting a direct dynamical forcing to the grid scale model via pressure gradient forces. The hybrid convection scheme implemented into the COSMO model of Deutscher Wetterdienst (DWD is tested in an idealized simulation of a sea breeze circulation initiating convection in a realistic manner. The results are compared with analogous simulations with the classical Tiedtke and Kain-Fritsch convection schemes.

  18. A new classification scheme of plastic wastes based upon recycling labels

    Energy Technology Data Exchange (ETDEWEB)

    Özkan, Kemal, E-mail: kozkan@ogu.edu.tr [Computer Engineering Dept., Eskişehir Osmangazi University, 26480 Eskişehir (Turkey); Ergin, Semih, E-mail: sergin@ogu.edu.tr [Electrical Electronics Engineering Dept., Eskişehir Osmangazi University, 26480 Eskişehir (Turkey); Işık, Şahin, E-mail: sahini@ogu.edu.tr [Computer Engineering Dept., Eskişehir Osmangazi University, 26480 Eskişehir (Turkey); Işıklı, İdil, E-mail: idil.isikli@bilecik.edu.tr [Electrical Electronics Engineering Dept., Bilecik University, 11210 Bilecik (Turkey)

    2015-01-15

    experimental setup with a camera and homogenous backlighting. Due to the giving global solution for a classification problem, Support Vector Machine (SVM) is selected to achieve the classification task and majority voting technique is used as the decision mechanism. This technique equally weights each classification result and assigns the given plastic object to the class that the most classification results agree on. The proposed classification scheme provides high accuracy rate, and also it is able to run in real-time applications. It can automatically classify the plastic bottle types with approximately 90% recognition accuracy. Besides this, the proposed methodology yields approximately 96% classification rate for the separation of PET or non-PET plastic types. It also gives 92% accuracy for the categorization of non-PET plastic types into HPDE or PP.

  19. Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks

    Science.gov (United States)

    Wagstaff, Kiri L.; Sosnowski, Scott; Lane, Terran

    2012-01-01

    Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events as well as faster responses, such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if learners at individual nodes can communicate with their neighbors. In previous work, methods were developed by which classification algorithms deployed at sensor nodes can communicate information about event labels to each other, building on prior work with co-training, self-training, and active learning. The idea of collaborative learning was extended to function for clustering algorithms as well, similar to ideas from penta-training and consensus clustering. However, collaboration between these learner types had not been explored. A new protocol was developed by which classifiers and clusterers can share key information about their observations and conclusions as they learn. This is an active collaboration in which learners of either type can query their neighbors for information that they then use to re-train or re-learn the concept they are studying. The protocol also supports broadcasts from the classifiers and clusterers to the rest of the network to announce new discoveries. Classifiers observe an event and assign it a label (type). Clusterers instead group observations into clusters without assigning them a label, and they collaborate in terms of pairwise constraints between two events [same-cluster (mustlink) or different-cluster (cannot-link)]. Fundamentally, these two learner types speak different languages. To bridge this gap, the new communication protocol provides four types of exchanges: hybrid queries for information, hybrid "broadcasts" of learned information, each specified for classifiers-to-clusterers, and clusterers

  20. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers

    Science.gov (United States)

    Bennett, David A.; Blennow, Kaj; Carrillo, Maria C.; Feldman, Howard H.; Frisoni, Giovanni B.; Hampel, Harald; Jagust, William J.; Johnson, Keith A.; Knopman, David S.; Petersen, Ronald C.; Scheltens, Philip; Sperling, Reisa A.; Dubois, Bruno

    2016-01-01

    Biomarkers have become an essential component of Alzheimer disease (AD) research and because of the pervasiveness of AD pathology in the elderly, the same biomarkers are used in cognitive aging research. A number of current issues suggest that an unbiased descriptive classification scheme for these biomarkers would be useful. We propose the “A/T/N” system in which 7 major AD biomarkers are divided into 3 binary categories based on the nature of the pathophysiology that each measures. “A” refers to the value of a β-amyloid biomarker (amyloid PET or CSF Aβ42); “T,” the value of a tau biomarker (CSF phospho tau, or tau PET); and “N,” biomarkers of neurodegeneration or neuronal injury ([18F]-fluorodeoxyglucose–PET, structural MRI, or CSF total tau). Each biomarker category is rated as positive or negative. An individual score might appear as A+/T+/N−, or A+/T−/N−, etc. The A/T/N system includes the new modality tau PET. It is agnostic to the temporal ordering of mechanisms underlying AD pathogenesis. It includes all individuals in any population regardless of the mix of biomarker findings and therefore is suited to population studies of cognitive aging. It does not specify disease labels and thus is not a diagnostic classification system. It is a descriptive system for categorizing multidomain biomarker findings at the individual person level in a format that is easy to understand and use. Given the present lack of consensus among AD specialists on terminology across the clinically normal to dementia spectrum, a biomarker classification scheme will have broadest acceptance if it is independent from any one clinically defined diagnostic scheme. PMID:27371494

  1. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers.

    Science.gov (United States)

    Jack, Clifford R; Bennett, David A; Blennow, Kaj; Carrillo, Maria C; Feldman, Howard H; Frisoni, Giovanni B; Hampel, Harald; Jagust, William J; Johnson, Keith A; Knopman, David S; Petersen, Ronald C; Scheltens, Philip; Sperling, Reisa A; Dubois, Bruno

    2016-08-02

    Biomarkers have become an essential component of Alzheimer disease (AD) research and because of the pervasiveness of AD pathology in the elderly, the same biomarkers are used in cognitive aging research. A number of current issues suggest that an unbiased descriptive classification scheme for these biomarkers would be useful. We propose the "A/T/N" system in which 7 major AD biomarkers are divided into 3 binary categories based on the nature of the pathophysiology that each measures. "A" refers to the value of a β-amyloid biomarker (amyloid PET or CSF Aβ42); "T," the value of a tau biomarker (CSF phospho tau, or tau PET); and "N," biomarkers of neurodegeneration or neuronal injury ([(18)F]-fluorodeoxyglucose-PET, structural MRI, or CSF total tau). Each biomarker category is rated as positive or negative. An individual score might appear as A+/T+/N-, or A+/T-/N-, etc. The A/T/N system includes the new modality tau PET. It is agnostic to the temporal ordering of mechanisms underlying AD pathogenesis. It includes all individuals in any population regardless of the mix of biomarker findings and therefore is suited to population studies of cognitive aging. It does not specify disease labels and thus is not a diagnostic classification system. It is a descriptive system for categorizing multidomain biomarker findings at the individual person level in a format that is easy to understand and use. Given the present lack of consensus among AD specialists on terminology across the clinically normal to dementia spectrum, a biomarker classification scheme will have broadest acceptance if it is independent from any one clinically defined diagnostic scheme.

  2. Hybrid independent component analysis and twin support vector machine learning scheme for subtle gesture recognition.

    Science.gov (United States)

    Naik, Ganesh R; Kumar, Dinesh K; Jayadeva

    2010-10-01

    Myoelectric signal classification is one of the most difficult pattern recognition problems because large variations in surface electromyogram features usually exist. In the literature, attempts have been made to apply various pattern recognition methods to classify surface electromyography into components corresponding to the activities of different muscles, but this has not been very successful, as some muscles are bigger and more active than others. This results in dataset discrepancy during classification. Multicategory classification problems are usually solved by solving many, one-versus-rest binary classification tasks. These subtasks unsurprisingly involve unbalanced datasets. Consequently, we need a learning methodology that can take into account unbalanced datasets in addition to large variations in the distributions of patterns corresponding to different classes. Here, we attempt to address the above issues using hybrid features extracted from independent component analysis and twin support vector machine techniques.

  3. A two-tier atmospheric circulation classification scheme for the European-North Atlantic region

    Science.gov (United States)

    Guentchev, Galina S.; Winkler, Julie A.

    A two-tier classification of large-scale atmospheric circulation was developed for the European-North-Atlantic domain. The classification was constructed using a combination of principal components and k-means cluster analysis applied to reanalysis fields of mean sea-level pressure for 1951-2004. Separate classifications were developed for the winter, spring, summer, and fall seasons. For each season, the two classification tiers were identified independently, such that the definition of one tier does not depend on the other tier having already been defined. The first tier of the classification is comprised of supertype patterns. These broad-scale circulation classes are useful for generalized analyses such as investigations of the temporal trends in circulation frequency and persistence. The second, more detailed tier consists of circulation types and is useful for numerous applied research questions regarding the relationships between large-scale circulation and local and regional climate. Three to five supertypes and up to 19 circulation types were identified for each season. An intuitive nomenclature scheme based on the physical entities (i.e., anomaly centers) which dominate the specific patterns was used to label each of the supertypes and types. Two example applications illustrate the potential usefulness of a two-tier classification. In the first application, the temporal variability of the supertypes was evaluated. In general, the frequency and persistence of supertypes dominated by anticyclonic circulation increased during the study period, whereas the supertypes dominated by cyclonic features decreased in frequency and persistence. The usefulness of the derived circulation types was exemplified by an analysis of the circulation associated with heat waves and cold spells reported at several cities in Bulgaria. These extreme temperature events were found to occur with a small number of circulation types, a finding that can be helpful in understanding past

  4. Segmentation techniques evaluation based on a single compact breast mass classification scheme

    Science.gov (United States)

    Matheus, Bruno R. N.; Marcomini, Karem D.; Schiabel, Homero

    2016-03-01

    In this work some segmentation techniques are evaluated by using a simple centroid-based classification system regarding breast mass delineation in digital mammography images. The aim is to determine the best one for future CADx developments. Six techniques were tested: Otsu, SOM, EICAMM, Fuzzy C-Means, K-Means and Level-Set. All of them were applied to segment 317 mammography images from DDSM database. A single compact set of attributes was extracted and two centroids were defined, one for malignant and another for benign cases. The final classification was based on proximity with a given centroid and the best results were presented by the Level-Set technique with a 68.1% of Accuracy, which indicates this method as the most promising for breast masses segmentation aiming a more precise interpretation in schemes CADx.

  5. The four-populations model: a new classification scheme for pre-planetesimal collisions

    CERN Document Server

    Geretshauser, Ralf J; Speith, Roland; Kley, WIlhelm

    2011-01-01

    Within the collision growth scenario for planetesimal formation, the growth step from centimetre sized pre-planetesimals to kilometre sized planetesimals is still unclear. The formation of larger objects from the highly porous pre-planetesimals may be halted by a combination of fragmentation in disruptive collisions and mutual rebound with compaction. However, the right amount of fragmentation is necessary to explain the observed dust features in late T Tauri discs. Therefore, detailed data on the outcome of pre-planetesimal collisions is required and has to be presented in a suitable and precise format. We propose and apply a new classification scheme for pre-planetesimal collisions based on the quantitative aspects of four fragment populations: the largest and second largest fragment, a power-law population, and a sub-resolution population. For the simulations of pre-planetesimal collisions, we adopt the SPH numerical scheme with extensions for the simulation of porous solid bodies. By means of laboratory b...

  6. Thermally-induced ventilation in atria: an atrium classification scheme and promising test sites

    Energy Technology Data Exchange (ETDEWEB)

    1981-06-01

    In establishing the atrium classification scheme, specific attention was given to: climate (hot-arid, warm-humid, and temperate), atrium configuration (open, closed, and adjustable tops), and thermal mechanism (natural convection, radiative cooling, shading, and others). Application of the resulting three-dimensional (three-coordinate) matrix was considered and tested. Although the testing was for purposes of checking scheme application, the procedure indicated that most of the atria examined were of the adjustable-top configuration with daylighting the principal functional mode. However, it was noted that thermally-induced air flow was present in many of the atria classified. In the identification of promising test sites it was noted that there appears to be a shortage of buildings which meet the atrium definition. Consequently, prospective test sites were categorized as follows based upon anticipated value to the study: commercial atria already constructed, commercial atria planned or under construction, and residential atria already constructed.

  7. Highly Robust and Imperceptible Luminance Based Hybrid Digital Video Watermarking Scheme for Ownership Protection

    Directory of Open Access Journals (Sweden)

    Himanshu Agarwal

    2012-10-01

    Full Text Available In this paper a hybrid digital video watermarking scheme based on discrete wavelet transform and singular value decomposition is proposed. Unlike the most existing watermarking schemes, the used watermark is a gray scale image instead of a binary watermark. The watermark is embedded in the original video frames by first converted it into YCbCr color space and than decomposing the luminance part (Y component into four sub-bands using discrete wavelet transform and finally the singular values of LL sub-band are shaped perceptually by singular values of watermark image. The experimental result shows a tradeoff between imperceptibility and resiliency against intentional attacks such as rotation, cropping, histogram stretching, JPEG compression on individual frames, Indeo5 video compression and unintentional attacks like frame swapping, frame averaging, frame insertion and different types of noise addition. Superiority of the proposed scheme is carried out by comparison with existing schemes to reveal its efficiency for practical applications.

  8. A hybrid LDG-HWENO scheme for KdV-type equations

    Science.gov (United States)

    Luo, Dongmi; Huang, Weizhang; Qiu, Jianxian

    2016-05-01

    A hybrid LDG-HWENO scheme is proposed for the numerical solution of KdV-type partial differential equations. It evolves the cell averages of the physical solution and its moments (a feature of Hermite WENO) while discretizes high order spatial derivatives using the local DG method. The new scheme has the advantages of both LDG and HWENO methods, including the ability to deal with high order spatial derivatives and the use of a small number of global unknown variables. The latter is independent of the order of the scheme and the spatial order of the underlying differential equations. One and two dimensional numerical examples are presented to show that the scheme can attain the same formal high order accuracy as the LDG method.

  9. A comparison between national scheme for the acoustic classification of dwellings in Europe and in the U.S

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2015-01-01

    The classification of dwellings according to different building performances have been proposed through many schemes worldwide in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particula...... scheme may facilitate exchanging experiences about constructions fulfilling different classes, reducing trade barriers, and finally increasing the sound insulation of dwellings....

  10. Harmonization of sound insulation descriptors and classification schemes in Europe: COST Action TU0901

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    of the inhabitants and the society. References [1] "Sound insulation between dwellings – Descriptors in building regulations in Europe" by Birgit Rasmussen & Jens Holger Rindel. Applied Acoustics, 2010, 71(3), 171-180. http://dx.doi.org/10.1016/j.apacoust.2009.05.002 [2] "Sound insulation between dwellings...... – Requirements in building regulations in Europe" by Birgit Rasmussen. Applied Acoustics, 2010, 71(4), 373-385. http://dx.doi.org/10.1016/j.apacoust.2009.08.011 [3] "Sound insulation of residential housing – building codes and classification schemes in Europe" by Birgit Rasmussen. In: Crocker Malcolm J, Editor...

  11. Seafloor classification using echo- waveforms: A method employing hybrid neural network architecture

    Digital Repository Service at National Institute of Oceanography (India)

    Chakraborty, B.; Mahale, V.; DeSouza, C.; Das, P.

    This letter presents seafloor classification study results of a hybrid artificial neural network architecture known as learning vector quantization. Single beam echo-sounding backscatter waveform data from three different seafloors of the western...

  12. A classification scheme for analyzing mobile apps used to prevent and manage disease in late life.

    Science.gov (United States)

    Wang, Aiguo; An, Ning; Lu, Xin; Chen, Hongtu; Li, Changqun; Levkoff, Sue

    2014-02-17

    There are several mobile apps that offer tools for disease prevention and management among older adults, and promote health behaviors that could potentially reduce or delay the onset of disease. A classification scheme that categorizes apps could be useful to both older adult app users and app developers. The objective of our study was to build and evaluate the effectiveness of a classification scheme that classifies mobile apps available for older adults in the "Health & Fitness" category of the iTunes App Store. We constructed a classification scheme for mobile apps according to three dimensions: (1) the Precede-Proceed Model (PPM), which classifies mobile apps in terms of predisposing, enabling, and reinforcing factors for behavior change; (2) health care process, specifically prevention versus management of disease; and (3) health conditions, including physical health and mental health. Content analysis was conducted by the research team on health and fitness apps designed specifically for older adults, as well as those applicable to older adults, released during the months of June and August 2011 and August 2012. Face validity was assessed by a different group of individuals, who were not related to the study. A reliability analysis was conducted to confirm the accuracy of the coding scheme of the sample apps in this study. After applying sample inclusion and exclusion criteria, a total of 119 apps were included in the study sample, of which 26/119 (21.8%) were released in June 2011, 45/119 (37.8%) in August 2011, and 48/119 (40.3%) in August 2012. Face validity was determined by interviewing 11 people, who agreed that this scheme accurately reflected the nature of this application. The entire study sample was successfully coded, demonstrating satisfactory inter-rater reliability by two independent coders (95.8% initial concordance and 100% concordance after consensus was reached). The apps included in the study sample were more likely to be used for the

  13. Hybrid threshold adaptable quantum secret sharing scheme with reverse Huffman-Fibonacci-tree coding

    Science.gov (United States)

    Lai, Hong; Zhang, Jun; Luo, Ming-Xing; Pan, Lei; Pieprzyk, Josef; Xiao, Fuyuan; Orgun, Mehmet A.

    2016-08-01

    With prevalent attacks in communication, sharing a secret between communicating parties is an ongoing challenge. Moreover, it is important to integrate quantum solutions with classical secret sharing schemes with low computational cost for the real world use. This paper proposes a novel hybrid threshold adaptable quantum secret sharing scheme, using an m-bonacci orbital angular momentum (OAM) pump, Lagrange interpolation polynomials, and reverse Huffman-Fibonacci-tree coding. To be exact, we employ entangled states prepared by m-bonacci sequences to detect eavesdropping. Meanwhile, we encode m-bonacci sequences in Lagrange interpolation polynomials to generate the shares of a secret with reverse Huffman-Fibonacci-tree coding. The advantages of the proposed scheme is that it can detect eavesdropping without joint quantum operations, and permits secret sharing for an arbitrary but no less than threshold-value number of classical participants with much lower bandwidth. Also, in comparison with existing quantum secret sharing schemes, it still works when there are dynamic changes, such as the unavailability of some quantum channel, the arrival of new participants and the departure of participants. Finally, we provide security analysis of the new hybrid quantum secret sharing scheme and discuss its useful features for modern applications.

  14. Optical Code-Division Multiple-Access and Wavelength Division Multiplexing: Hybrid Scheme Review

    Directory of Open Access Journals (Sweden)

    P. Susthitha Menon

    2012-01-01

    Full Text Available Problem statement: Hybrid Optical Code-Division Multiple-Access (OCDMA and Wavelength-Division Multiplexing (WDM have flourished as successful schemes for expanding the transmission capacity as well as enhancing the security for OCDMA. However, a comprehensive review related to this hybrid system are lacking currently. Approach: The purpose of this paper is to review the literature on OCDMA-WDM overlay systems, including our hybrid approach of one-dimensional coding of SAC OCDMA with WDM signals. In addition, we present an additional review of other categorios of hybrid WDM/OCDMA schemes, where codes of OCDMA can be employed on each WDM wavelength. Furthermore, an essential background of OCDMA, recent coding techniques and security issues are also presented. Results: Our results indicate that the feasibility of transmitting both OCDMA and WDM users on the same spectrum band can be achieved using MQC family code with an acceptable performance as well as good data confidentiality. In addition, the WDM interference signals can be suppressed properly for detection of optical broadband CDMA using notch filters. Conclusion: The paper provides a comprehensive overview of hybrid OCDMA-WDM systems and can be used as a baseline study for other scientists in the similar scope of research.

  15. Head/tail Breaks: A New Classification Scheme for Data with a Heavy-tailed Distribution

    CERN Document Server

    Jiang, Bin

    2012-01-01

    This paper introduces a new classification scheme - head/tail breaks - in order to find groupings or hierarchy for data with a heavy-tailed distribution. The heavy-tailed distributions are heavily right skewed, with a minority of large values in the head and a majority of small values in the tail, commonly characterized by a power law, a lognormal or an exponential function. For example, a country's population is often distributed in such a heavy-tailed manner, with a minority of people (e.g., 20 percent) in the countryside and the vast majority (e.g., 80 percent) in urban areas. This heavy-tailed distribution is also called scaling, hierarchy or scaling hierarchy. This new classification scheme partitions all of the data values around the mean into two parts and continues the process iteratively for the values (above the mean) in the head until the head part values are no longer heavy-tailed distributed. Thus, the number of classes and the class intervals are both naturally determined. We therefore claim tha...

  16. Optimal design of a hybridization scheme with a fuel cell using genetic optimization

    Science.gov (United States)

    Rodriguez, Marco A.

    Fuel cell is one of the most dependable "green power" technologies, readily available for immediate application. It enables direct conversion of hydrogen and other gases into electric energy without any pollution of the environment. However, the efficient power generation is strictly stationary process that cannot operate under dynamic environment. Consequently, fuel cell becomes practical only within a specially designed hybridization scheme, capable of power storage and power management functions. The resultant technology could be utilized to its full potential only when both the fuel cell element and the entire hybridization scheme are optimally designed. The design optimization in engineering is among the most complex computational tasks due to its multidimensionality, nonlinearity, discontinuity and presence of constraints in the underlying optimization problem. this research aims at the optimal utilization of the fuel cell technology through the use of genetic optimization, and advance computing. This study implements genetic optimization in the definition of optimum hybridization rules for a PEM fuel cell/supercapacitor power system. PEM fuel cells exhibit high energy density but they are not intended for pulsating power draw applications. They work better in steady state operation and thus, are often hybridized. In a hybrid system, the fuel cell provides power during steady state operation while capacitors or batteries augment the power of the fuel cell during power surges. Capacitors and batteries can also be recharged when the motor is acting as a generator. Making analogies to driving cycles, three hybrid system operating modes are investigated: 'Flat' mode, 'Uphill' mode, and 'Downhill' mode. In the process of discovering the switching rules for these three modes, we also generate a model of a 30W PEM fuel cell. This study also proposes the optimum design of a 30W PEM fuel cell. The PEM fuel cell model and hybridization's switching rules are postulated

  17. A general hybrid radiation transport scheme for star formation simulations on an adaptive grid

    CERN Document Server

    Klassen, Mikhail; Pudritz, Ralph E; Peters, Thomas; Banerjee, Robi; Buntemeyer, Lars

    2014-01-01

    Radiation feedback plays a crucial role in the process of star formation. In order to simulate the thermodynamic evolution of disks, filaments, and the molecular gas surrounding clusters of young stars, we require an efficient and accurate method for solving the radiation transfer problem. We describe the implementation of a hybrid radiation transport scheme in the adaptive grid-based FLASH general magnetohydrodynamics code. The hybrid scheme splits the radiative transport problem into a raytracing step and a diffusion step. The raytracer captures the first absorption event, as stars irradiate their environments, while the evolution of the diffuse component of the radiation field is handled by a flux-limited diffusion (FLD) solver. We demonstrate the accuracy of our method through a variety of benchmark tests including the irradiation of a static disk, subcritical and supercritical radiative shocks, and thermal energy equilibration. We also demonstrate the capability of our method for casting shadows and calc...

  18. A New Hybrid Model of Amino Acid Substitution for Protein Functional Classification

    Institute of Scientific and Technical Information of China (English)

    Ke Long WANG; Zhi Ning WEN; Fu Sheng NIE; Meng Long LI

    2005-01-01

    In this paper, a new hybrid model of amino acid substitution is developed and compared with the others in previous works. The results show that the new hybrid model can characterize the protein sequences very well by calculating Fisher weights, which can denote how much the variants contribute to the classification.

  19. Multiscale modeling for classification of SAR imagery using hybrid EM algorithm and genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    Xianbin Wen; Hua Zhang; Jianguang Zhang; Xu Jiao; Lei Wang

    2009-01-01

    A novel method that hybridizes genetic algorithm (GA) and expectation maximization (EM) algorithm for the classification of syn-thetic aperture radar (SAR) imagery is proposed by the finite Gaussian mixtures model (GMM) and multiscale autoregressive (MAR)model. This algorithm is capable of improving the global optimality and consistency of the classification performance. The experiments on the SAR images show that the proposed algorithm outperforms the standard EM method significantly in classification accuracy.

  20. A new classification scheme of plastic wastes based upon recycling labels.

    Science.gov (United States)

    Özkan, Kemal; Ergin, Semih; Işık, Şahin; Işıklı, Idil

    2015-01-01

    results agree on. The proposed classification scheme provides high accuracy rate, and also it is able to run in real-time applications. It can automatically classify the plastic bottle types with approximately 90% recognition accuracy. Besides this, the proposed methodology yields approximately 96% classification rate for the separation of PET or non-PET plastic types. It also gives 92% accuracy for the categorization of non-PET plastic types into HPDE or PP. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. A novel fractal image compression scheme with block classification and sorting based on Pearson's correlation coefficient.

    Science.gov (United States)

    Wang, Jianji; Zheng, Nanning

    2013-09-01

    Fractal image compression (FIC) is an image coding technology based on the local similarity of image structure. It is widely used in many fields such as image retrieval, image denoising, image authentication, and encryption. FIC, however, suffers from the high computational complexity in encoding. Although many schemes are published to speed up encoding, they do not easily satisfy the encoding time or the reconstructed image quality requirements. In this paper, a new FIC scheme is proposed based on the fact that the affine similarity between two blocks in FIC is equivalent to the absolute value of Pearson's correlation coefficient (APCC) between them. First, all blocks in the range and domain pools are chosen and classified using an APCC-based block classification method to increase the matching probability. Second, by sorting the domain blocks with respect to APCCs between these domain blocks and a preset block in each class, the matching domain block for a range block can be searched in the selected domain set in which these APCCs are closer to APCC between the range block and the preset block. Experimental results show that the proposed scheme can significantly speed up the encoding process in FIC while preserving the reconstructed image quality well.

  2. A risk-based classification scheme for genetically modified foods. I: Conceptual development.

    Science.gov (United States)

    Chao, Eunice; Krewski, Daniel

    2008-12-01

    The predominant paradigm for the premarket assessment of genetically modified (GM) foods reflects heightened public concern by focusing on foods modified by recombinant deoxyribonucleic acid (rDNA) techniques, while foods modified by other methods of genetic modification are generally not assessed for safety. To determine whether a GM product requires less or more regulatory oversight and testing, we developed and evaluated a risk-based classification scheme (RBCS) for crop-derived GM foods. The results of this research are presented in three papers. This paper describes the conceptual development of the proposed RBCS that focuses on two categories of adverse health effects: (1) toxic and antinutritional effects, and (2) allergenic effects. The factors that may affect the level of potential health risks of GM foods are identified. For each factor identified, criteria for differentiating health risk potential are developed. The extent to which a GM food satisfies applicable criteria for each factor is rated separately. A concern level for each category of health effects is then determined by aggregating the ratings for the factors using predetermined aggregation rules. An overview of the proposed scheme is presented, as well as the application of the scheme to a hypothetical GM food.

  3. Climatological characteristics of the tropics in China: climate classification schemes between German scientists and Huang Bingwei

    Institute of Scientific and Technical Information of China (English)

    ManfredDomroes

    2003-01-01

    Reviewing some important German scientists who have developed climatic regionalization schemes either on a global or Chinese scale, their various definitions of the tropical climate characteristics in China are discussed and compared with Huang Bingwei's climate classification scheme and the identification of the tropical climate therein. It can be seen that, due to different methodological approaches of the climatic regionalization schemes, the definitions of the tropics vary and hence also their spatial distribution in China. However, it is found that the tropical climate type occupies only a peripheral part of southern China, though it firmly represents a distinctive type of climate that is subsequently associated with a great economic importance for China. As such, the tropical climate type was mostly identified with its agro-climatological significance, that is by giving favourable growing conditions all-year round for perennial crops with a great heat demand. Tropical climate is, hence, conventionally regarded to be governed by all-year round summer conditions "where winter never comes".

  4. A Novel Image Encryption Scheme Based on Multi-orbit Hybrid of Discrete Dynamical System

    Directory of Open Access Journals (Sweden)

    Ruisong Ye

    2014-10-01

    Full Text Available A multi-orbit hybrid image encryption scheme based on discrete chaotic dynamical systems is proposed. One generalized Arnold map is adopted to generate three orbits for three initial conditions. Another chaotic dynamical system, tent map, is applied to generate one pseudo-random sequence to determine the hybrid orbit points from which one of the three orbits of generalized Arnold map. The hybrid orbit sequence is then utilized to shuffle the pixels' positions of plain-image so as to get one permuted image. To enhance the encryption security, two rounds of pixel gray values' diffusion is employed as well. The proposed encryption scheme is simple and easy to manipulate. The security and performance of the proposed image encryption have been analyzed, including histograms, correlation coefficients, information entropy, key sensitivity analysis, key space analysis, differential analysis, etc. All the experimental results suggest that the proposed image encryption scheme is robust and secure and can be used for secure image and video communication applications.

  5. A Hybrid DGTD-MNA Scheme for Analyzing Complex Electromagnetic Systems

    KAUST Repository

    Li, Peng

    2015-01-07

    A hybrid electromagnetics (EM)-circuit simulator for analyzing complex systems consisting of EM devices loaded with nonlinear multi-port lumped circuits is described. The proposed scheme splits the computational domain into two subsystems: EM and circuit subsystems, where field interactions are modeled using Maxwell and Kirchhoff equations, respectively. Maxwell equations are discretized using a discontinuous Galerkin time domain (DGTD) scheme while Kirchhoff equations are discretized using a modified nodal analysis (MNA)-based scheme. The coupling between the EM and circuit subsystems is realized at the lumped ports, where related EM fields and circuit voltages and currents are allowed to “interact’’ via numerical flux. To account for nonlinear lumped circuit elements, the standard Newton-Raphson method is applied at every time step. Additionally, a local time-stepping scheme is developed to improve the efficiency of the hybrid solver. Numerical examples consisting of EM systems loaded with single and multiport linear/nonlinear circuit networks are presented to demonstrate the accuracy, efficiency, and applicability of the proposed solver.

  6. A comparison study of convective schemes in hybrid RANS-LES calculations

    Science.gov (United States)

    Basara, Branislav; Pavlovic, Zoran

    2016-11-01

    Nowadays it is commonly accepted to report on convections schemes in the case of Large Eddy Simulation (LES) calculations. However, in the case of hybrid RANS-LES calculations, the same discussion seems not to be relevant assuming that calculations are anyway performed on the coarser computational meshes and that the amount of unresolved and modelled turbulence impairs the calculation accuracy more than the error of convection schemes used in calculations. Therefore, we want to tackle this issue by using the Partially Averaged Navier-Stokes (PANS) model as the representative hybrid RANS-LES method but the conclusions derived in this work are equally applicable to other models. We will present results by using the central differencing (CD), MINMOD and SMART schemes but also using CD scheme only locally in the area of low unresolved-to-total ratios of kinetic energy (fk) . The paper will also show the performance of a step blending function, which depends on the prescribed constant value of the ratio fk and the performance of a smooth function which directly uses the ratio fk as the blending value. The results will be presented for the flow around the square cylinder.

  7. A gas kinetic scheme for hybrid simulation of partially rarefied flows

    Science.gov (United States)

    Colonia, S.; Steijl, R.; Barakos, G.

    2017-06-01

    Approaches to predict flow fields that display rarefaction effects incur a cost in computational time and memory considerably higher than methods commonly employed for continuum flows. For this reason, to simulate flow fields where continuum and rarefied regimes coexist, hybrid techniques have been introduced. In the present work, analytically defined gas-kinetic schemes based on the Shakhov and Rykov models for monoatomic and diatomic gas flows, respectively, are proposed and evaluated with the aim to be used in the context of hybrid simulations. This should reduce the region where more expensive methods are needed by extending the validity of the continuum formulation. Moreover, since for high-speed rare¦ed gas flows it is necessary to take into account the nonequilibrium among the internal degrees of freedom, the extension of the approach to employ diatomic gas models including rotational relaxation process is a mandatory first step towards realistic simulations. Compared to previous works of Xu and coworkers, the presented scheme is de¦ned directly on the basis of kinetic models which involve a Prandtl number correction. Moreover, the methods are defined fully analytically instead of making use of Taylor expansion for the evaluation of the required derivatives. The scheme has been tested for various test cases and Mach numbers proving to produce reliable predictions in agreement with other approaches for near-continuum flows. Finally, the performance of the scheme, in terms of memory and computational time, compared to discrete velocity methods makes it a compelling alternative in place of more complex methods for hybrid simulations of weakly rarefied flows.

  8. Using field theory to construct hybrid particle-continuum simulation schemes with adaptive resolution for soft matter systems

    OpenAIRE

    Qi, Shuanhu; Behringer, Hans; Schmid, Friederike

    2013-01-01

    We develop a multiscale hybrid scheme for simulations of soft condensed matter systems, which allows one to treat the system at the particle level in selected regions of space, and at the continuum level elsewhere. It is derived systematically from an underlying particle-based model by field theoretic methods. Particles in different representation regions can switch representations on the fly, controlled by a spatially varying tuning function. As a test case, the hybrid scheme is applied to s...

  9. A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment

    Science.gov (United States)

    Xiao, Min; Zhou, Jing; Liu, Xuejiao; Jiang, Mingda

    2017-01-01

    In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment. PMID:28629131

  10. Kernel Clustering with a Differential Harmony Search Algorithm for Scheme Classification

    Directory of Open Access Journals (Sweden)

    Yu Feng

    2017-01-01

    Full Text Available This paper presents a kernel fuzzy clustering with a novel differential harmony search algorithm to coordinate with the diversion scheduling scheme classification. First, we employed a self-adaptive solution generation strategy and differential evolution-based population update strategy to improve the classical harmony search. Second, we applied the differential harmony search algorithm to the kernel fuzzy clustering to help the clustering method obtain better solutions. Finally, the combination of the kernel fuzzy clustering and the differential harmony search is applied for water diversion scheduling in East Lake. A comparison of the proposed method with other methods has been carried out. The results show that the kernel clustering with the differential harmony search algorithm has good performance to cooperate with the water diversion scheduling problems.

  11. Power law classification scheme of time series correlations. On the example of G20 group

    Science.gov (United States)

    Miśkiewicz, Janusz

    2013-05-01

    A power law classification scheme (PLCS) of time series correlations is proposed. It is shown that PLCS provides the ability to classify nonlinear correlations and measure their stability. PLCS has been applied to gross domestic product (GDP) per capita of G20 members and their correlations analysed. It has been shown that the method does not only recognise linear correlations properly, but also allows to point out converging time series as well as to distinguish nonlinear correlations. PLCS is capable of crash recognition as it is shown in the Argentina example. Finally the strength of correlations and the stability of correlation matrices have been used to construct a minimum spanning tree (MST). The results were compared with those based on the ultrametric distance (UD). Comparing the structures of MST, UD and PLCS indicates that the latter one is more complicated, but better fits the expected economic relations within the G20.

  12. Sound classification of dwellings in the Nordic countries – Differences and similarities between the five national schemes

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    In all five Nordic countries, sound classification schemes for dwellings have been published in national standards being implemented and revised gradually since the late 1990s. The national classification criteria for dwellings originate from a common Nordic INSTA-B proposal from the 1990s, thus...... having several similarities. In 2012, status is that number and denotations of classes for dwellings are identical in the Nordic countries, but the structures of the standards and several details are quite different. Also the issues dealt with are different. Examples of differences are sound insulation...... for classification of such buildings. This paper presents and compares the main class criteria for sound insulation of dwellings and summarizes differences and similarities in criteria and in structures of standards. Classification schemes for dwellings also exist in several other countries in Europe...

  13. A New Hybrid Control Scheme for an Integrated Helicopter and Engine System

    Institute of Scientific and Technical Information of China (English)

    ZHANG Haibo; WANG Jiankang; CHEN Guoqiang; YAN Changkai

    2012-01-01

    A new hybrid control scheme is presented with a robust multiple model fusion control (RMMFC) law for a UH-60 helicopter and an active disturbance rejection control (ADRC) controller for its engines.This scheme is a control design method with every subsystem designed separately but fully considering the couplings between them.With three subspaces with respect to forward flight velocity,a RMMFC is proposed to devise a four-loop reference signal tracing control for the helicopter,which escapes the closed-loop system from unstable state due to the extreme complexity of this integrated nonlinear system.The engines are controlled by the proposed ADRC decoupling controller,which fully takes advantage of a good compensation ability for unmodeled dynamics and extra disturbances,so as to compensate torque disturbance in power turbine speed loop.By simulating a forward acceleration flight task,the RMMFC for the helicopter is validated.It is apparent that the integrated helicopter and engine system (IHES) has much better dynamic performance under the new control scheme.Especially in the switching process,the large transient is significantly weakened,and smooth transition among candidate controllers is achieved.Over the entire simulation task,the droop of power turbine speed with the proposed ADRC controller is significantly slighter than with the conventional PID controller,and the response time of the former is much faster than the latter.By simulating a rapid climb and descent flight task,the results also show the feasibility for the application of the proposed multiple model fusion control.Although there is aggressive power demand in this maneuver,the droop of power turbine speed with an ADRC controller is smaller than using a PID controller.The control performance for helicopter and engine is enhanced by adopting this hybrid control scheme,and simulation results in other envelope stale give proofs of robustness for this new scheme.

  14. Classification scheme for sedimentary and igneous rocks in Gale crater, Mars

    Science.gov (United States)

    Mangold, N.; Schmidt, M. E.; Fisk, M. R.; Forni, O.; McLennan, S. M.; Ming, D. W.; Sautter, V.; Sumner, D.; Williams, A. J.; Clegg, S. M.; Cousin, A.; Gasnault, O.; Gellert, R.; Grotzinger, J. P.; Wiens, R. C.

    2017-03-01

    Rocks analyzed by the Curiosity rover in Gale crater include a variety of clastic sedimentary rocks and igneous float rocks transported by fluvial and impact processes. To facilitate the discussion of the range of lithologies, we present in this article a petrological classification framework adapting terrestrial classification schemes to Mars compositions (such as Fe abundances typically higher than for comparable lithologies on Earth), to specific Curiosity observations (such as common alkali-rich rocks), and to the capabilities of the rover instruments. Mineralogy was acquired only locally for a few drilled rocks, and so it does not suffice as a systematic classification tool, in contrast to classical terrestrial rock classification. The core of this classification involves (1) the characterization of rock texture as sedimentary, igneous or undefined according to grain/crystal sizes and shapes using imaging from the ChemCam Remote Micro-Imager (RMI), Mars Hand Lens Imager (MAHLI) and Mastcam instruments, and (2) the assignment of geochemical modifiers based on the abundances of Fe, Si, alkali, and S determined by the Alpha Particle X-ray Spectrometer (APXS) and ChemCam instruments. The aims are to help understand Gale crater geology by highlighting the various categories of rocks analyzed by the rover. Several implications are proposed from the cross-comparisons of rocks of various texture and composition, for instance between in place outcrops and float rocks. All outcrops analyzed by the rover are sedimentary; no igneous outcrops have been observed. However, some igneous rocks are clasts in conglomerates, suggesting that part of them are derived from the crater rim. The compositions of in-place sedimentary rocks contrast significantly with the compositions of igneous float rocks. While some of the differences between sedimentary rocks and igneous floats may be related to physical sorting and diagenesis of the sediments, some of the sedimentary rocks (e

  15. A Hybrid Data Compression Scheme for Power Reduction in Wireless Sensors for IoT.

    Science.gov (United States)

    Deepu, Chacko John; Heng, Chun-Huat; Lian, Yong

    2017-04-01

    This paper presents a novel data compression and transmission scheme for power reduction in Internet-of-Things (IoT) enabled wireless sensors. In the proposed scheme, data is compressed with both lossy and lossless techniques, so as to enable hybrid transmission mode, support adaptive data rate selection and save power in wireless transmission. Applying the method to electrocardiogram (ECG), the data is first compressed using a lossy compression technique with a high compression ratio (CR). The residual error between the original data and the decompressed lossy data is preserved using entropy coding, enabling a lossless restoration of the original data when required. Average CR of 2.1 × and 7.8 × were achieved for lossless and lossy compression respectively with MIT/BIH database. The power reduction is demonstrated using a Bluetooth transceiver and is found to be reduced to 18% for lossy and 53% for lossless transmission respectively. Options for hybrid transmission mode, adaptive rate selection and system level power reduction make the proposed scheme attractive for IoT wireless sensors in healthcare applications.

  16. A conservative and a hybrid early rejection schemes for accelerating Monte Carlo molecular simulation

    KAUST Repository

    Kadoura, Ahmad Salim

    2014-03-17

    Molecular simulation could provide detailed description of fluid systems when compared to experimental techniques. They can also replace equations of state; however, molecular simulation usually costs considerable computational efforts. Several techniques have been developed to overcome such high computational costs. In this paper, two early rejection schemes, a conservative and a hybrid one, are introduced. In these two methods, undesired configurations generated by the Monte Carlo trials are rejected earlier than it would when using conventional algorithms. The methods are tested for structureless single-component Lennard-Jones particles in both canonical and NVT-Gibbs ensembles. The computational time reduction for both ensembles is observed at a wide range of thermodynamic conditions. Results show that computational time savings are directly proportional to the rejection rate of Monte Carlo trials. The proposed conservative scheme has shown to be successful in saving up to 40% of the computational time in the canonical ensemble and up to 30% in the NVT-Gibbs ensemble when compared to standard algorithms. In addition, it preserves the exact Markov chains produced by the Metropolis scheme. Further enhancement for NVT-Gibbs ensemble is achieved by combining this technique with the bond formation early rejection one. The hybrid method achieves more than 50% saving of the central processing unit (CPU) time.

  17. Active sway control of a gantry crane using hybrid input shaping and PID control schemes

    Science.gov (United States)

    Mohd Tumari, M. Z.; Shabudin, L.; Zawawi, M. A.; Shah, L. H. Ahmad

    2013-12-01

    This project presents investigations into the development of hybrid input-shaping and PID control schemes for active sway control of a gantry crane system. The application of positive input shaping involves a technique that can reduce the sway by creating a common signal that cancels its own vibration and used as a feed-forward control which is for controlling the sway angle of the pendulum, while the proportional integral derivative (PID) controller is used as a feedback control which is for controlling the crane position. The PID controller was tuned using Ziegler-Nichols method to get the best performance of the system. The hybrid input-shaping and PID control schemes guarantee a fast input tracking capability, precise payload positioning and very minimal sway motion. The modeling of gantry crane is used to simulate the system using MATLAB/SIMULINK software. The results of the response with the controllers are presented in time domains and frequency domains. The performances of control schemes are examined in terms of level of input tracking capability, sway angle reduction and time response specification.

  18. Hybrid microsystem with functionalized silicon substrate and PDMS sample operating microchannel: A reconfigurable microfluidics scheme

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    A hybrid microsystem with separately functioned temperature controlling substrate and sample operating fluidic microchannel was developed to demonstrate a reconfigurable microfluidics scheme.The temperature controlling substrate integrated a micro heater and a temperature sensor by using traditional silicon-based micromechanical system(MEMS)technique,which guaranteed high performance and robust reliability for repeatable usage.The sample operating fluidic microchannel was prepared by poly-(dimethylsiloxane) (PDMS)based soft lithography technique,which made it cheap enough for disposable applications.The PDMS microchannel chip was attached to the temperature controlling substrate for reconfigurable thermal applications.A thin PDMS film was used to seal the microchannel and bridge the functionalized substrate and the sample inside the channel,which facilitated heat transferring and prevented sample contaminating the temperature controlling substrate.Demonstrated by a one dimensional thermal resistance model,the thin PDMS film was important for the present reconfiguration applications.Thermal performance of this hybrid microsystem was examined,and the experimental results demonstrated that the chip system could work stably over hours with temperature variation less than 0.1oC.Multiple PDMS microchannel chips were tested on one heating substrate sequentially with a maximum intra-chip temperature difference of 1.0oC.DNA extracted from serum of a chronic hepatitis B virus(HBV)patient was amplified by this hybrid microsystem and the gel electrophoresis result indicated that the present reconfigurable microfluidic scheme worked successfully.

  19. Lexicon-enhanced sentiment analysis framework using rule-based classification scheme

    Science.gov (United States)

    Khan, Aurangzeb; Ahmad, Shakeel; Qasim, Maria; Khan, Imran Ali

    2017-01-01

    With the rapid increase in social networks and blogs, the social media services are increasingly being used by online communities to share their views and experiences about a particular product, policy and event. Due to economic importance of these reviews, there is growing trend of writing user reviews to promote a product. Nowadays, users prefer online blogs and review sites to purchase products. Therefore, user reviews are considered as an important source of information in Sentiment Analysis (SA) applications for decision making. In this work, we exploit the wealth of user reviews, available through the online forums, to analyze the semantic orientation of words by categorizing them into +ive and -ive classes to identify and classify emoticons, modifiers, general-purpose and domain-specific words expressed in the public’s feedback about the products. However, the un-supervised learning approach employed in previous studies is becoming less efficient due to data sparseness, low accuracy due to non-consideration of emoticons, modifiers, and presence of domain specific words, as they may result in inaccurate classification of users’ reviews. Lexicon-enhanced sentiment analysis based on Rule-based classification scheme is an alternative approach for improving sentiment classification of users’ reviews in online communities. In addition to the sentiment terms used in general purpose sentiment analysis, we integrate emoticons, modifiers and domain specific terms to analyze the reviews posted in online communities. To test the effectiveness of the proposed method, we considered users reviews in three domains. The results obtained from different experiments demonstrate that the proposed method overcomes limitations of previous methods and the performance of the sentiment analysis is improved after considering emoticons, modifiers, negations, and domain specific terms when compared to baseline methods. PMID:28231286

  20. Developing a visual sensitive image features based CAD scheme to assist classification of mammographic masses

    Science.gov (United States)

    Wang, Yunzhi; Aghaei, Faranak; Tan, Maxine; Qiu, Yuchen; Liu, Hong; Zheng, Bin

    2017-03-01

    Computer-aided diagnosis (CAD) schemes of mammograms have been previously developed and tested. However, due to using "black-box" approaches with a large number of complicated features, radiologists have lower confidence to accept or consider CAD-cued results. In order to help solve this issue, this study aims to develop and evaluate a new CAD scheme that uses visual sensitive image features to classify between malignant and benign mammographic masses. A dataset of 301 masses detected on both craniocaudal (CC) and mediolateraloblique (MLO) view images was retrospectively assembled. Among them, 152 were malignant and 149 were benign. An iterative region-growing algorithm was applied to the special Gaussian-kernel filtered images to segment mass regions. Total 13 Image features were computed to mimic 5 categories of visually sensitive features that are commonly used by radiologists in classifying suspicious mammographic masses namely, mass size, shape factor, contrast, homogeneity and spiculation. We then selected one optimal feature in each of 5 feature categories by using a student t-test, and applied two logistic regression classifiers using either CC or MLO view images to distinguish between malignant and benign masses. Last, a fusion method of combining two classification scores was applied and tested. By applying a 10-fold cross-validation method, the area under receiver operating characteristic curves was 0.806+/-0.025. This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a "visual-aid" interface, CAD results are much more easily explainable to the observers and may increase their confidence to consider CAD-cued results.

  1. Classification scheme for acid rock drainage detection - the Hamersley Basin, Western Australia

    Science.gov (United States)

    Skrzypek, Grzegorz; Dogramaci, Shawan; McLean, Laura

    2017-04-01

    In arid environment where precipitation and surface water are very limited, groundwater is the most important freshwater resource. For this reasons it is intensively exploited and needs to be managed wisely and protected from pollutants. Acid rock drainage often constitutes a serious risk to groundwater quality, particularly in catchments that are subject to mining, large scale groundwater injection or abstraction. However, assessment of the potential acid rock drainage risk can be challenging, especially in carbonate rich environment, where the decreasing pH that usually accompanies pyrite oxidation, can be masked by the high pH-neutralisation capacity of carbonate minerals. In this study, we analysed 73 surface and groundwater samples from different water bodies and aquifers located in the Hamersley Basin, Western Australia. Although the majority of samples had a neutral pH, there was a large spatial variability in the dissolved sulphate concentrations that ranged from 1 mg/L to 15,000 mg/L. Waters with high dissolved sulphate concentration were found in areas with a high percentage of sulphide minerals (e.g. pyrite) located within the aquifer matrix and were characterised by low δ34SSO4 values (+1.2‰ to +4.6) consistent with signatures of aquifer matrix pyritic rock samples (+1.9‰ to +4.4). It was also found that the SO4 concentrations and acidity levels were not only dependent on δ34SSO4 values and existence of pyrite but also on the presence of carbonate minerals in the aquifer matrix. Based on the results from this study, a classification scheme has been developed for identification of waters impacted by acid rock drainage that also encompasses numerous concomitant geochemical processes that often occur in aqueous systems. The classification uses five proxies: SO4, SO4/Cl, SI of calcite, δ34SSO4 and δ18OSO4 to improve assessment of the contribution that oxidation of sulphide minerals has to overall sulphate ion concentrations, regardless of acidity

  2. Hybrid numerical scheme for nonlinear two-dimensional phase-change problems with the irregular geometry

    Energy Technology Data Exchange (ETDEWEB)

    Lin Jaeyuh [Chang Jung Univ., Tainan (Taiwan, Province of China); Chen Hantaw [National Cheng Kung Univ., Tainan (Taiwan, Province of China). Dept. of Mechanical Engineering

    1997-09-01

    A hybrid numerical scheme combining the Laplace transform and control-volume methods is presented to solve nonlinear two-dimensional phase-change problems with the irregular geometry. The Laplace transform method is applied to deal with the time domain, and then the control-volume method is used to discretize the transformed system in the space domain. Nonlinear terms induced by the temperature-dependent thermal properties are linearized by using the Taylor series approximation. Control-volume meshes in the solid and liquid regions during simulations are generated by using the discrete transfinite mapping method. The location of the phase-change interface and the isothermal distributions are determined. Comparison of these results with previous results shows that the present numerical scheme has good accuracy for two-dimensional phase-change problems. (orig.). With 10 figs.

  3. Efficient scheme for hybrid teleportation via entangled coherent states in circuit quantum electrodynamics.

    Science.gov (United States)

    Joo, Jaewoo; Ginossar, Eran

    2016-06-01

    We propose a deterministic scheme for teleporting an unknown qubit state through continuous-variable entangled states in superconducting circuits. The qubit is a superconducting two-level system and the bipartite quantum channel is a microwave photonic entangled coherent state between two cavities. A Bell-type measurement performed on the hybrid state of solid and photonic states transfers a discrete-variable unknown electronic state to a continuous-variable photonic cat state in a cavity mode. In order to facilitate the implementation of such complex protocols we propose a design for reducing the self-Kerr nonlinearity in the cavity. The teleporation scheme enables quantum information processing operations with circuit-QED based on entangled coherent states. These include state verification and single-qubit operations with entangled coherent states. These are shown to be experimentally feasible with the state of the art superconducting circuits.

  4. Hybrid FPMS: A New Fairness Protocol Management Scheme for Community Wireless Mesh Networks

    CERN Document Server

    Widanapathirana, Chathuranga; Goi, Bok-Min

    2012-01-01

    Node cooperation during packet forwarding operations is critically important for fair resource utilization in Community Wireless Mesh Networks (CoWMNs). In a CoWMN, node cooperation is achieved by using fairness protocols specifically designed to detect and isolate malicious nodes, discourage unfair behavior, and encourage node participation in forwarding packets. In general, these protocols can be split into two groups: Incentive-based ones, which are managed centrally, and use credit allocation schemes. In contrast, reputation-based protocols that are decentralized, and rely on information exchange among neighboring nodes. Centrally managed protocols inevitably suffer from scalability problems. The decentralized, reputation-based protocols lacks in detection capability, suffer from false detections and error propagation compared to the centralized, incentive-based protocols. In this study, we present a new fairness protocol management scheme, called Hybrid FPMS that captures the superior detection capabilit...

  5. Efficient scheme for hybrid teleportation via entangled coherent states in circuit quantum electrodynamics

    Science.gov (United States)

    Joo, Jaewoo; Ginossar, Eran

    2016-06-01

    We propose a deterministic scheme for teleporting an unknown qubit state through continuous-variable entangled states in superconducting circuits. The qubit is a superconducting two-level system and the bipartite quantum channel is a microwave photonic entangled coherent state between two cavities. A Bell-type measurement performed on the hybrid state of solid and photonic states transfers a discrete-variable unknown electronic state to a continuous-variable photonic cat state in a cavity mode. In order to facilitate the implementation of such complex protocols we propose a design for reducing the self-Kerr nonlinearity in the cavity. The teleporation scheme enables quantum information processing operations with circuit-QED based on entangled coherent states. These include state verification and single-qubit operations with entangled coherent states. These are shown to be experimentally feasible with the state of the art superconducting circuits.

  6. A new ignition scheme using hybrid indirect-direct drive for inertial confinement fusion

    CERN Document Server

    Fan, Zhengfeng; Dai, Zhensheng; Cai, Hong-bo; Zhu, Shao-ping; Zhang, W Y; He, X T

    2013-01-01

    A new hybrid indirect-direct-drive ignition scheme is proposed for inertial confinement fusion: a cryogenic capsule encased in a hohlraum is first compressed symmetrically by indirect-drive x-rays, and then accelerated and ignited by both direct-drive lasers and x-rays. A steady high-density plateau newly formed between the radiation and electron ablation fronts suppresses the rarefaction at the radiation ablation front and greatly enhances the drive pressure. Meanwhile, multiple shock reflections at the fuel/hot-spot interface are prevented during capsule deceleration. Thus rapid ignition and burn are realized. In comparison with the conventional indirect drive, the hybrid drive implodes the capsule with a higher velocity ($\\sim4.3\\times10^7$ cm/s) and a much lower convergence ratio ($\\sim$25), and the growth of hydrodynamic instabilities is significantly reduced, especially at the fuel/hot-spot interface.

  7. A Hybrid Sensing Approach for Pure and Adulterated Honey Classification

    Directory of Open Access Journals (Sweden)

    Ammar Zakaria

    2012-10-01

    Full Text Available This paper presents a comparison between data from single modality and fusion methods to classify Tualang honey as pure or adulterated using Linear Discriminant Analysis (LDA and Principal Component Analysis (PCA statistical classification approaches. Ten different brands of certified pure Tualang honey were obtained throughout peninsular Malaysia and Sumatera, Indonesia. Various concentrations of two types of sugar solution (beet and cane sugar were used in this investigation to create honey samples of 20%, 40%, 60% and 80% adulteration concentrations. Honey data extracted from an electronic nose (e-nose and Fourier Transform Infrared Spectroscopy (FTIR were gathered, analyzed and compared based on fusion methods. Visual observation of classification plots revealed that the PCA approach able to distinct pure and adulterated honey samples better than the LDA technique. Overall, the validated classification results based on FTIR data (88.0% gave higher classification accuracy than e-nose data (76.5% using the LDA technique. Honey classification based on normalized low-level and intermediate-level FTIR and e-nose fusion data scored classification accuracies of 92.2% and 88.7%, respectively using the Stepwise LDA method. The results suggested that pure and adulterated honey samples were better classified using FTIR and e-nose fusion data than single modality data.

  8. HYBRID SYSTEM BASED FUZZY-PID CONTROL SCHEMES FOR UNPREDICTABLE PROCESS

    Directory of Open Access Journals (Sweden)

    M.K. Tan

    2011-07-01

    Full Text Available In general, the primary aim of polymerization industry is to enhance the process operation in order to obtain high quality and purity product. However, a sudden and large amount of heat will be released rapidly during the mixing process of two reactants, i.e. phenol and formalin due to its exothermic behavior. The unpredictable heat will cause deviation of process temperature and hence affect the quality of the product. Therefore, it is vital to control the process temperature during the polymerization. In the modern industry, fuzzy logic is commonly used to auto-tune PID controller to control the process temperature. However, this method needs an experienced operator to fine tune the fuzzy membership function and universe of discourse via trial and error approach. Hence, the setting of fuzzy inference system might not be accurate due to the human errors. Besides that, control of the process can be challenging due to the rapid changes in the plant parameters which will increase the process complexity. This paper proposes an optimization scheme using hybrid of Q-learning (QL and genetic algorithm (GA to optimize the fuzzy membership function in order to allow the conventional fuzzy-PID controller to control the process temperature more effectively. The performances of the proposed optimization scheme are compared with the existing fuzzy-PID scheme. The results show that the proposed optimization scheme is able to control the process temperature more effectively even if disturbance is introduced.

  9. Authentication and data hiding using a hybrid ROI-based watermarking scheme for DICOM images.

    Science.gov (United States)

    Al-Qershi, Osamah M; Khoo, Bee Ee

    2011-02-01

    Authenticating medical images using watermarking techniques has become a very popular area of research, and some works in this area have been reported worldwide recently. Besides authentication, many data-hiding techniques have been proposed to conceal patient's data into medical images aiming to reduce the cost needed to store data and the time needed to transmit data when required. In this paper, we present a new hybrid watermarking scheme for DICOM images. In our scheme, two well-known techniques are combined to gain the advantages of both and fulfill the requirements of authentication and data hiding. The scheme divides the images into two parts, the region of interest (ROI) and the region of non-interest (RONI). Patient's data are embedded into ROI using a reversible technique based on difference expansion, while tamper detection and recovery data are embedded into RONI using a robust technique based on discrete wavelet transform. The experimental results show the ability of hiding patient's data with a very good visual quality, while ROI, the most important area for diagnosis, is retrieved exactly at the receiver side. The scheme also shows some robustness against certain levels of salt and pepper and cropping noise.

  10. Hybrid ARQ Scheme with Autonomous Retransmission for Multicasting in Wireless Sensor Networks

    Science.gov (United States)

    Jung, Young-Ho; Choi, Jihoon

    2017-01-01

    A new hybrid automatic repeat request (HARQ) scheme for multicast service for wireless sensor networks is proposed in this study. In the proposed algorithm, the HARQ operation is combined with an autonomous retransmission method that ensure a data packet is transmitted irrespective of whether or not the packet is successfully decoded at the receivers. The optimal number of autonomous retransmissions is determined to ensure maximum spectral efficiency, and a practical method that adjusts the number of autonomous retransmissions for realistic conditions is developed. Simulation results show that the proposed method achieves higher spectral efficiency than existing HARQ techniques. PMID:28245604

  11. Sound insulation and reverberation time for classrooms - Criteria in regulations and classification schemes in the Nordic countries

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2016-01-01

    have become more extensive and stricter during the last two decades. The paper focuses on comparison of sound insulation and reverberation time criteria for classrooms in regulations and classification schemes in the Nordic countries. Limit values and changes over time will be discussed as well as how...

  12. Hybrid model based on Genetic Algorithms and SVM applied to variable selection within fruit juice classification.

    Science.gov (United States)

    Fernandez-Lozano, C; Canto, C; Gestal, M; Andrade-Garda, J M; Rabuñal, J R; Dorado, J; Pazos, A

    2013-01-01

    Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected.

  13. Hybrid Medical Image Classification Using Association Rule Mining with Decision Tree Algorithm

    OpenAIRE

    Rajendran, P.; M.Madheswaran

    2010-01-01

    The main focus of image mining in the proposed method is concerned with the classification of brain tumor in the CT scan brain images. The major steps involved in the system are: pre-processing, feature extraction, association rule mining and hybrid classifier. The pre-processing step has been done using the median filtering process and edge features have been extracted using canny edge detection technique. The two image mining approaches with a hybrid manner have been proposed in this paper....

  14. Hybrid advection scheme for 3-dimensional atmospheric models. Testing and application for a study of NO{sub x} transport

    Energy Technology Data Exchange (ETDEWEB)

    Zubov, V.A.; Rozanov, E.V. [Main Geophysical Observatory, St.Petersburg (Russian Federation); Schlesinger, M.E.; Andronova, N.G. [Illinois Univ., Urbana-Champaign, IL (United States). Dept. of Atmospheric Sciences

    1997-12-31

    The problems of ozone depletion, climate change and atmospheric pollution strongly depend on the processes of production, destruction and transport of chemical species. A hybrid transport scheme was developed, consisting of the semi-Lagrangian scheme for horizontal advection and the Prather scheme for vertical transport, which have been used for the Atmospheric Chemical Transport model to calculate the distributions of different chemical species. The performance of the new hybrid scheme has been evaluated in comparison with other transport schemes on the basis of specially designed tests. The seasonal cycle of the distribution of N{sub 2}O simulated by the model, as well as the dispersion of NO{sub x} exhausted from subsonic aircraft, are in a good agreement with published data. (author) 8 refs.

  15. Middle cerebral artery bifurcation aneurysms: an anatomic classification scheme for planning optimal surgical strategies.

    Science.gov (United States)

    Washington, Chad W; Ju, Tao; Zipfel, Gregory J; Dacey, Ralph G

    2014-03-01

    Changing landscapes in neurosurgical training and increasing use of endovascular therapy have led to decreasing exposure in open cerebrovascular neurosurgery. To ensure the effective transition of medical students into competent practitioners, new training paradigms must be developed. Using principles of pattern recognition, we created a classification scheme for middle cerebral artery (MCA) bifurcation aneurysms that allows their categorization into a small number of shape pattern groups. Angiographic data from patients with MCA aneurysms between 1995 and 2012 were used to construct 3-dimensional models. Models were then analyzed and compared objectively by assessing the relationship between the aneurysm sac, parent vessel, and branch vessels. Aneurysms were then grouped on the basis of the similarity of their shape patterns in such a way that the in-class similarities were maximized while the total number of categories was minimized. For each category, a proposed clip strategy was developed. From the analysis of 61 MCA bifurcation aneurysms, 4 shape pattern categories were created that allowed the classification of 56 aneurysms (91.8%). The number of aneurysms allotted to each shape cluster was 10 (16.4%) in category 1, 24 (39.3%) in category 2, 7 (11.5%) in category 3, and 15 (24.6%) in category 4. This study demonstrates that through the use of anatomic visual cues, MCA bifurcation aneurysms can be grouped into a small number of shape patterns with an associated clip solution. Implementing these principles within current neurosurgery training paradigms can provide a tool that allows more efficient transition from novice to cerebrovascular expert.

  16. An efficient hybrid protection scheme with shared/dedicated backup paths on elastic optical networks

    Directory of Open Access Journals (Sweden)

    Nogbou G. Anoh

    2017-02-01

    Full Text Available Fast recovery and minimum utilization of resources are the two main criteria for determining the protection scheme quality. We address the problem of providing a hybrid protection approach on elastic optical networks under contiguity and continuity of available spectrum constraints. Two main hypotheses are used in this paper for backup paths computation. In the first case, it is assumed that backup paths resources are dedicated. In the second case, the assumption is that backup paths resources are available shared resources. The objective of the study is to minimize spectrum utilization to reduce blocking probability on a network. For this purpose, an efficient survivable Hybrid Protection Lightpath (HybPL algorithm is proposed for providing shared or dedicated backup path protection based on the efficient energy calculation and resource availability. Traditional First-Fit and Best-Fit schemes are employed to search and assign the available spectrum resources. The simulation results show that HybPL presents better performance in terms of blocking probability, compared with the Minimum Resources Utilization Dedicated Protection (MRU-DP algorithm which offers better performance than the Dedicated Protection (DP algorithm.

  17. DSMC-LBM hybrid scheme for flows with variable rarefaction conditions

    Science.gov (United States)

    di Staso, Gianluca; Succi, Sauro; Toschi, Federico; Clercx, Herman

    2015-11-01

    The kinetic description of gases, based on the Boltzmann equation, allows to cover flow regimes ranging from the rarefied to the continuum limit. The two limits are traditionally studied by numerically approximating the Boltzmann equation via Direct Simulation Monte Carlo (DSMC) method or the Lattice Boltzmann Equation method (LBM). While DSMC is suitable for rarefied flows, its computational cost makes it unpractical to study hydrodynamic flows. The LBM has instead proved itself to be an efficient and accurate method in the hydrodynamic limit even though simulation of rarefied flows requires additional modeling. Here, results on the development of a hybrid scheme capable of coupling the LBM and the DSMC methods and able to efficiently simulate flows with variable rarefaction conditions are presented. The coupling scheme is based on Grad's moment method approach and the local single particle distribution function at a given order of truncation is built by using the Hermite polynomials expansion approach and Gauss-Hermite quadratures. The capabilities of the hybrid approach for simulating flows in the transition regime are illustrated in the case of planar Couette and Poiseuille flows.

  18. A Hybrid Scheme Based on Pipelining and Multitasking in Mobile Application Processors for Advanced Video Coding

    Directory of Open Access Journals (Sweden)

    Muhammad Asif

    2015-01-01

    Full Text Available One of the key requirements for mobile devices is to provide high-performance computing at lower power consumption. The processors used in these devices provide specific hardware resources to handle computationally intensive video processing and interactive graphical applications. Moreover, processors designed for low-power applications may introduce limitations on the availability and usage of resources, which present additional challenges to the system designers. Owing to the specific design of the JZ47x series of mobile application processors, a hybrid software-hardware implementation scheme for H.264/AVC encoder is proposed in this work. The proposed scheme distributes the encoding tasks among hardware and software modules. A series of optimization techniques are developed to speed up the memory access and data transferring among memories. Moreover, an efficient data reusage design is proposed for the deblock filter video processing unit to reduce the memory accesses. Furthermore, fine grained macroblock (MB level parallelism is effectively exploited and a pipelined approach is proposed for efficient utilization of hardware processing cores. Finally, based on parallelism in the proposed design, encoding tasks are distributed between two processing cores. Experiments show that the hybrid encoder is 12 times faster than a highly optimized sequential encoder due to proposed techniques.

  19. A general hybrid radiation transport scheme for star formation simulations on an adaptive grid

    Energy Technology Data Exchange (ETDEWEB)

    Klassen, Mikhail; Pudritz, Ralph E. [Department of Physics and Astronomy, McMaster University 1280 Main Street W, Hamilton, ON L8S 4M1 (Canada); Kuiper, Rolf [Max Planck Institute for Astronomy Königstuhl 17, D-69117 Heidelberg (Germany); Peters, Thomas [Institut für Computergestützte Wissenschaften, Universität Zürich Winterthurerstrasse 190, CH-8057 Zürich (Switzerland); Banerjee, Robi; Buntemeyer, Lars, E-mail: klassm@mcmaster.ca [Hamburger Sternwarte, Universität Hamburg Gojenbergsweg 112, D-21029 Hamburg (Germany)

    2014-12-10

    Radiation feedback plays a crucial role in the process of star formation. In order to simulate the thermodynamic evolution of disks, filaments, and the molecular gas surrounding clusters of young stars, we require an efficient and accurate method for solving the radiation transfer problem. We describe the implementation of a hybrid radiation transport scheme in the adaptive grid-based FLASH general magnetohydrodyanmics code. The hybrid scheme splits the radiative transport problem into a raytracing step and a diffusion step. The raytracer captures the first absorption event, as stars irradiate their environments, while the evolution of the diffuse component of the radiation field is handled by a flux-limited diffusion solver. We demonstrate the accuracy of our method through a variety of benchmark tests including the irradiation of a static disk, subcritical and supercritical radiative shocks, and thermal energy equilibration. We also demonstrate the capability of our method for casting shadows and calculating gas and dust temperatures in the presence of multiple stellar sources. Our method enables radiation-hydrodynamic studies of young stellar objects, protostellar disks, and clustered star formation in magnetized, filamentary environments.

  20. A General Hybrid Radiation Transport Scheme for Star Formation Simulations on an Adaptive Grid

    Science.gov (United States)

    Klassen, Mikhail; Kuiper, Rolf; Pudritz, Ralph E.; Peters, Thomas; Banerjee, Robi; Buntemeyer, Lars

    2014-12-01

    Radiation feedback plays a crucial role in the process of star formation. In order to simulate the thermodynamic evolution of disks, filaments, and the molecular gas surrounding clusters of young stars, we require an efficient and accurate method for solving the radiation transfer problem. We describe the implementation of a hybrid radiation transport scheme in the adaptive grid-based FLASH general magnetohydrodyanmics code. The hybrid scheme splits the radiative transport problem into a raytracing step and a diffusion step. The raytracer captures the first absorption event, as stars irradiate their environments, while the evolution of the diffuse component of the radiation field is handled by a flux-limited diffusion solver. We demonstrate the accuracy of our method through a variety of benchmark tests including the irradiation of a static disk, subcritical and supercritical radiative shocks, and thermal energy equilibration. We also demonstrate the capability of our method for casting shadows and calculating gas and dust temperatures in the presence of multiple stellar sources. Our method enables radiation-hydrodynamic studies of young stellar objects, protostellar disks, and clustered star formation in magnetized, filamentary environments.

  1. Spatial and Spectral Hybrid Image Classification for Rice Lodging Assessment through UAV Imagery

    Directory of Open Access Journals (Sweden)

    Ming-Der Yang

    2017-06-01

    Full Text Available Rice lodging identification relies on manual in situ assessment and often leads to a compensation dispute in agricultural disaster assessment. Therefore, this study proposes a comprehensive and efficient classification technique for agricultural lands that entails using unmanned aerial vehicle (UAV imagery. In addition to spectral information, digital surface model (DSM and texture information of the images was obtained through image-based modeling and texture analysis. Moreover, single feature probability (SFP values were computed to evaluate the contribution of spectral and spatial hybrid image information to classification accuracy. The SFP results revealed that texture information was beneficial for the classification of rice and water, DSM information was valuable for lodging and tree classification, and the combination of texture and DSM information was helpful in distinguishing between artificial surface and bare land. Furthermore, a decision tree classification model incorporating SFP values yielded optimal results, with an accuracy of 96.17% and a Kappa value of 0.941, compared with that of a maximum likelihood classification model (90.76%. The rice lodging ratio in paddies at the study site was successfully identified, with three paddies being eligible for disaster relief. The study demonstrated that the proposed spatial and spectral hybrid image classification technology is a promising tool for rice lodging assessment.

  2. An improved fault detection classification and location scheme based on wavelet transform and artificial neural network for six phase transmission line using single end data only.

    Science.gov (United States)

    Koley, Ebha; Verma, Khushaboo; Ghosh, Subhojit

    2015-01-01

    Restrictions on right of way and increasing power demand has boosted development of six phase transmission. It offers a viable alternative for transmitting more power, without major modification in existing structure of three phase double circuit transmission system. Inspite of the advantages, low acceptance of six phase system is attributed to the unavailability of a proper protection scheme. The complexity arising from large number of possible faults in six phase lines makes the protection quite challenging. The proposed work presents a hybrid wavelet transform and modular artificial neural network based fault detector, classifier and locator for six phase lines using single end data only. The standard deviation of the approximate coefficients of voltage and current signals obtained using discrete wavelet transform are applied as input to the modular artificial neural network for fault classification and location. The proposed scheme has been tested for all 120 types of shunt faults with variation in location, fault resistance, fault inception angles. The variation in power system parameters viz. short circuit capacity of the source and its X/R ratio, voltage, frequency and CT saturation has also been investigated. The result confirms the effectiveness and reliability of the proposed protection scheme which makes it ideal for real time implementation.

  3. An adaptive hybrid EnKF-OI scheme for efficient state-parameter estimation of reactive contaminant transport models

    KAUST Repository

    El Gharamti, Mohamad

    2014-09-01

    Reactive contaminant transport models are used by hydrologists to simulate and study the migration and fate of industrial waste in subsurface aquifers. Accurate transport modeling of such waste requires clear understanding of the system\\'s parameters, such as sorption and biodegradation. In this study, we present an efficient sequential data assimilation scheme that computes accurate estimates of aquifer contamination and spatially variable sorption coefficients. This assimilation scheme is based on a hybrid formulation of the ensemble Kalman filter (EnKF) and optimal interpolation (OI) in which solute concentration measurements are assimilated via a recursive dual estimation of sorption coefficients and contaminant state variables. This hybrid EnKF-OI scheme is used to mitigate background covariance limitations due to ensemble under-sampling and neglected model errors. Numerical experiments are conducted with a two-dimensional synthetic aquifer in which cobalt-60, a radioactive contaminant, is leached in a saturated heterogeneous clayey sandstone zone. Assimilation experiments are investigated under different settings and sources of model and observational errors. Simulation results demonstrate that the proposed hybrid EnKF-OI scheme successfully recovers both the contaminant and the sorption rate and reduces their uncertainties. Sensitivity analyses also suggest that the adaptive hybrid scheme remains effective with small ensembles, allowing to reduce the ensemble size by up to 80% with respect to the standard EnKF scheme. © 2014 Elsevier Ltd.

  4. A hybrid Eulerian Lagrangian numerical scheme for solving prognostic equations in fluid dynamics

    Directory of Open Access Journals (Sweden)

    E. Kaas

    2013-07-01

    Full Text Available A new hybrid Eulerian Lagrangian numerical scheme (HEL for solving prognostic equations in fluid dynamics is proposed. The basic idea is to use an Eulerian as well as a fully Lagrangian representation of all prognostic variables. The time step in Lagrangian space is obtained as a translation of irregularly spaced Lagrangian parcels along downstream trajectories. Tendencies due to other physical processes than advection are calculated in Eulerian space, interpolated, and added to the Lagrangian parcel values. A directionally biased mixing amongst neighboring Lagrangian parcels is introduced. The rate of mixing is proportional to the local deformation rate of the flow. The time stepping in Eulerian representation is achieved in two steps: first a mass conserving Eulerian or semi-Lagrangian scheme is used to obtain a provisional forecast. This forecast is then nudged towards target values defined from the irregularly spaced Lagrangian parcel values. The nudging procedure is defined in such a way that mass conservation and shape preservation is ensured in Eulerian space. The HEL scheme has been designed to be accurate, multi-tracer efficient, mass conserving, and shape preserving. In Lagrangian space only physically based mixing takes place, i.e., the problem of artificial numerical mixing is avoided. This property is desirable in atmospheric chemical transport models since spurious numerical mixing can impact chemical concentrations severely. The properties of HEL are here verified in two-dimensional tests. These include deformational passive transport on the sphere, and simulations with a semi-implicit shallow water model including topography.

  5. A Hybrid Sender- and Receiver-Initiated Protocol Scheme in Underwater Acoustic Sensor Networks.

    Science.gov (United States)

    Lee, Jae-Won; Cho, Ho-Shin

    2015-01-01

    In this paper, we propose a method for sharing the handshakes of control packets among multiple nodes, which we call a hybrid sender- and receiver-initiated (HSR) protocol scheme. Handshake-sharing can be achieved by inviting neighbors to join the current handshake and by allowing them to send their data packets without requiring extra handshakes. Thus, HSR can reduce the signaling overhead involved in control packet exchanges during handshakes, as well as resolve the spatial unfairness problem between nodes. From an operational perspective, HSR resembles the well-known handshake-sharing scheme referred to as the medium access control (MAC) protocol using reverse opportunistic packet appending (ROPA). However, in ROPA the waiting time is not controllable for the receiver's neighbors and thus unexpected collisions may occur at the receiver due to hidden neighbors, whereas the proposed scheme allows all nodes to avoid hidden-node-induced collisions according to an elaborately calculated waiting time. Our computer simulations demonstrated that HSR outperforms ROPA with respect to both the throughput and delay by around 9.65% and 11.36%, respectively.

  6. A Hybrid Sender- and Receiver-Initiated Protocol Scheme in Underwater Acoustic Sensor Networks

    Directory of Open Access Journals (Sweden)

    Jae-Won Lee

    2015-11-01

    Full Text Available In this paper, we propose a method for sharing the handshakes of control packets among multiple nodes, which we call a hybrid sender- and receiver-initiated (HSR protocol scheme. Handshake-sharing can be achieved by inviting neighbors to join the current handshake and by allowing them to send their data packets without requiring extra handshakes. Thus, HSR can reduce the signaling overhead involved in control packet exchanges during handshakes, as well as resolve the spatial unfairness problem between nodes. From an operational perspective, HSR resembles the well-known handshake-sharing scheme referred to as the medium access control (MAC protocol using reverse opportunistic packet appending (ROPA. However, in ROPA the waiting time is not controllable for the receiver’s neighbors and thus unexpected collisions may occur at the receiver due to hidden neighbors, whereas the proposed scheme allows all nodes to avoid hidden-node-induced collisions according to an elaborately calculated waiting time. Our computer simulations demonstrated that HSR outperforms ROPA with respect to both the throughput and delay by around 9.65% and 11.36%, respectively.

  7. A risk-based classification scheme for genetically modified foods. II: Graded testing.

    Science.gov (United States)

    Chao, Eunice; Krewski, Daniel

    2008-12-01

    This paper presents a graded approach to the testing of crop-derived genetically modified (GM) foods based on concern levels in a proposed risk-based classification scheme (RBCS) and currently available testing methods. A graded approach offers the potential for more efficient use of testing resources by focusing less on lower concern GM foods, and more on higher concern foods. In this proposed approach to graded testing, products that are classified as Level I would have met baseline testing requirements that are comparable to what is widely applied to premarket assessment of GM foods at present. In most cases, Level I products would require no further testing, or very limited confirmatory analyses. For products classified as Level II or higher, additional testing would be required, depending on the type of the substance, prior dietary history, estimated exposure level, prior knowledge of toxicity of the substance, and the nature of the concern related to unintended changes in the modified food. Level III testing applies only to the assessment of toxic and antinutritional effects from intended changes and is tailored to the nature of the substance in question. Since appropriate test methods are not currently available for all effects of concern, future research to strengthen the testing of GM foods is discussed.

  8. Evaluation of a 5-tier scheme proposed for classification of sequence variants using bioinformatic and splicing assay data

    DEFF Research Database (Denmark)

    Walker, Logan C; Whiley, Phillip J; Houdayer, Claude;

    2013-01-01

    of results, and the lack of quantitative data for the aberrant transcripts. We propose suggestions for minimum reporting guidelines for splicing assays, and improvements to the 5-tier splicing classification system to allow future evaluation of its performance as a clinical tool.......Splicing assays are commonly undertaken in the clinical setting to assess the clinical relevance of sequence variants in disease predisposition genes. A 5-tier classification system incorporating both bioinformatic and splicing assay information was previously proposed as a method to provide...... consistent clinical classification of such variants. Members of the ENIGMA Consortium Splicing Working Group undertook a study to assess the applicability of the scheme to published assay results, and the consistency of classifications across multiple reviewers. Splicing assay data were identified for 235...

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

    DEFF Research Database (Denmark)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

    2001-01-01

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

  10. Hybrid Multiagent System for Automatic Object Learning Classification

    Science.gov (United States)

    Gil, Ana; de La Prieta, Fernando; López, Vivian F.

    The rapid evolution within the context of e-learning is closely linked to international efforts on the standardization of learning object metadata, which provides learners in a web-based educational system with ubiquitous access to multiple distributed repositories. This article presents a hybrid agent-based architecture that enables the recovery of learning objects tagged in Learning Object Metadata (LOM) and provides individualized help with selecting learning materials to make the most suitable choice among many alternatives.

  11. 基于特征点分类的模糊金库方案%Fuzzy Vault Scheme Based on Classification of Fingerprint Features Scheme

    Institute of Scientific and Technical Information of China (English)

    孙方圆; 郑建德; 徐千惠

    2016-01-01

    For the purpose of solving fingerprint template leakage problem and the inability of combining fingerprints and traditional keys in the traditional fingerprintidentification,fuzzy vault scheme based on classification of fingerprint features scheme (CFM-FV) is proposed in this paper.In our scheme,singularities will be as helper data for pre-align the fingerprint,while the minutia features will be used to encode the vault in this scheme.In the stage of verification,singularities will be extracted as helper data for fingerprint pre-aligned,then the extracted minutia features will be used to reconstruct the polynomial.In this scheme,the problem that the tradi-tional scheme cannot align the fingerprint blind will be solved to some extent by combining classification method of fingerprint fea-tures with fuzzy vault scheme.%为解决传统指纹认证方案中指纹模板信息泄露以及指纹和密钥无法融合等问题,提出一种基于指纹特征点分类的模糊金库方案(CFM-FV).该方案中,使用指纹奇异点作为辅助数据对指纹图像进行预对齐,将指纹细节点特征应用于模糊金库方案进行密钥绑定.验证时,提取查询指纹奇异点作为辅助数据对指纹预对齐,然后提取指纹细节点特征信息进行多项式的重构.本方案将指纹特征点分类方法与模糊金库方案相结合,一定程度上解决了传统模糊金库方案中无法实现指纹盲对齐带来的影响问题.

  12. Hybrid Clustering-Classification Neural Network in the Medical Diagnostics of the Reactive Arthritis

    Directory of Open Access Journals (Sweden)

    Yevgeniy Bodyanskiy

    2016-08-01

    Full Text Available In the paper, the hybrid clustering-classification neural network is proposed. This network allows to increase a quality of information processing under the condition of overlapping classes due to the rational choice of learning rate parameter and introducing special procedure of fuzzy reasoning in the clustering-classification process, which occurs both with external learning signal ("supervised", and without one ("unsupervised". As similarity measure neighborhood function or membership one, cosine structures are used, which allow to provide a high flexibility due to self-learning-learning process and to provide some new useful properties. Many realized experiments have confirmed the efficiency of proposed hybrid clustering-classification neural network; also, this network was used for solving diagnostics task of reactive arthritis.

  13. A new hybrid-Lagrangian numerical scheme for gyrokinetic simulation of tokamak edge plasma

    Energy Technology Data Exchange (ETDEWEB)

    Ku, S. [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Hager, R. [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Chang, C. S. [Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States); Kwon, J. M. [National Fusion Research Institute, Republic of Korea; Parker, S. E. [University of Colorado Boulder, USA

    2016-06-01

    In order to enable kinetic simulation of non-thermal edge plasmas at a reduced computational cost, a new hybrid-Lagrangian δf scheme has been developed that utilizes the phase space grid in addition to the usual marker particles, taking advantage of the computational strengths from both sides. The new scheme splits the particle distribution function of a kinetic equation into two parts. Marker particles contain the fast space-time varying, δf, part of the distribution function and the coarse-grained phase-space grid contains the slow space-time varying part. The coarse-grained phase-space grid reduces the memory-requirement and the computing cost, while the marker particles provide scalable computing ability for the fine-grained physics. Weights of the marker particles are determined by a direct weight evolution equation instead of the differential form weight evolution equations that the conventional delta-f schemes use. The particle weight can be slowly transferred to the phase space grid, thereby reducing the growth of the particle weights. The non-Lagrangian part of the kinetic equation – e.g., collision operation, ionization, charge exchange, heat-source, radiative cooling, and others – can be operated directly on the phase space grid. Deviation of the particle distribution function on the velocity grid from a Maxwellian distribution function – driven by ionization, charge exchange and wall loss – is allowed to be arbitrarily large. The numerical scheme is implemented in the gyrokinetic particle code XGC1, which specializes in simulating the tokamak edge plasma that crosses the magnetic separatrix and is in contact with the material wall.

  14. A hybrid-drive nonisobaric-ignition scheme for inertial confinement fusion

    Energy Technology Data Exchange (ETDEWEB)

    He, X. T., E-mail: xthe@iapcm.ac.cn [Institute of Applied Physics and Computational Mathematics, P. O. Box 8009, Beijing 100094 (China); Center for Applied Physics and Technology, HEDPS, Peking University, Beijing 100871 (China); IFSA Collaborative Innovation Center of MoE, Shanghai Jiao-Tong University, Shanghai 200240 (China); Institute of Fusion Theory and Simulation, Zhejiang University, Hangzhou 310027 (China); Li, J. W.; Wang, L. F.; Liu, J.; Lan, K.; Ye, W. H. [Institute of Applied Physics and Computational Mathematics, P. O. Box 8009, Beijing 100094 (China); Center for Applied Physics and Technology, HEDPS, Peking University, Beijing 100871 (China); IFSA Collaborative Innovation Center of MoE, Shanghai Jiao-Tong University, Shanghai 200240 (China); Fan, Z. F.; Wu, J. F. [Institute of Applied Physics and Computational Mathematics, P. O. Box 8009, Beijing 100094 (China)

    2016-08-15

    A new hybrid-drive (HD) nonisobaric ignition scheme of inertial confinement fusion (ICF) is proposed, in which a HD pressure to drive implosion dynamics increases via increasing density rather than temperature in the conventional indirect drive (ID) and direct drive (DD) approaches. In this HD (combination of ID and DD) scheme, an assembled target of a spherical hohlraum and a layered deuterium-tritium capsule inside is used. The ID lasers first drive the shock to perform a spherical symmetry implosion and produce a large-scale corona plasma. Then, the DD lasers, whose critical surface in ID corona plasma is far from the radiation ablation front, drive a supersonic electron thermal wave, which slows down to a high-pressure electron compression wave, like a snowplow, piling up the corona plasma into high density and forming a HD pressurized plateau with a large width. The HD pressure is several times the conventional ID and DD ablation pressure and launches an enhanced precursor shock and a continuous compression wave, which give rise to the HD capsule implosion dynamics in a large implosion velocity. The hydrodynamic instabilities at imploding capsule interfaces are suppressed, and the continuous HD compression wave provides main pdV work large enough to hotspot, resulting in the HD nonisobaric ignition. The ignition condition and target design based on this scheme are given theoretically and by numerical simulations. It shows that the novel scheme can significantly suppress implosion asymmetry and hydrodynamic instabilities of current isobaric hotspot ignition design, and a high-gain ICF is promising.

  15. A hybrid-drive nonisobaric-ignition scheme for inertial confinement fusion

    Science.gov (United States)

    He, X. T.; Li, J. W.; Fan, Z. F.; Wang, L. F.; Liu, J.; Lan, K.; Wu, J. F.; Ye, W. H.

    2016-08-01

    A new hybrid-drive (HD) nonisobaric ignition scheme of inertial confinement fusion (ICF) is proposed, in which a HD pressure to drive implosion dynamics increases via increasing density rather than temperature in the conventional indirect drive (ID) and direct drive (DD) approaches. In this HD (combination of ID and DD) scheme, an assembled target of a spherical hohlraum and a layered deuterium-tritium capsule inside is used. The ID lasers first drive the shock to perform a spherical symmetry implosion and produce a large-scale corona plasma. Then, the DD lasers, whose critical surface in ID corona plasma is far from the radiation ablation front, drive a supersonic electron thermal wave, which slows down to a high-pressure electron compression wave, like a snowplow, piling up the corona plasma into high density and forming a HD pressurized plateau with a large width. The HD pressure is several times the conventional ID and DD ablation pressure and launches an enhanced precursor shock and a continuous compression wave, which give rise to the HD capsule implosion dynamics in a large implosion velocity. The hydrodynamic instabilities at imploding capsule interfaces are suppressed, and the continuous HD compression wave provides main pdV work large enough to hotspot, resulting in the HD nonisobaric ignition. The ignition condition and target design based on this scheme are given theoretically and by numerical simulations. It shows that the novel scheme can significantly suppress implosion asymmetry and hydrodynamic instabilities of current isobaric hotspot ignition design, and a high-gain ICF is promising.

  16. A new hybrid-Lagrangian numerical scheme for gyrokinetic simulation of tokamak edge plasma

    Energy Technology Data Exchange (ETDEWEB)

    Ku, S., E-mail: sku@pppl.gov [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Hager, R.; Chang, C.S. [Princeton Plasma Physics Laboratory, Princeton University, Princeton, NJ 08543 (United States); Kwon, J.M. [National Fusion Research Institute (Korea, Republic of); Parker, S.E. [University of Colorado Boulder (United States)

    2016-06-15

    In order to enable kinetic simulation of non-thermal edge plasmas at a reduced computational cost, a new hybrid-Lagrangian δf scheme has been developed that utilizes the phase space grid in addition to the usual marker particles, taking advantage of the computational strengths from both sides. The new scheme splits the particle distribution function of a kinetic equation into two parts. Marker particles contain the fast space-time varying, δf, part of the distribution function and the coarse-grained phase-space grid contains the slow space-time varying part. The coarse-grained phase-space grid reduces the memory-requirement and the computing cost, while the marker particles provide scalable computing ability for the fine-grained physics. Weights of the marker particles are determined by a direct weight evolution equation instead of the differential form weight evolution equations that the conventional delta-f schemes use. The particle weight can be slowly transferred to the phase space grid, thereby reducing the growth of the particle weights. The non-Lagrangian part of the kinetic equation – e.g., collision operation, ionization, charge exchange, heat-source, radiative cooling, and others – can be operated directly on the phase space grid. Deviation of the particle distribution function on the velocity grid from a Maxwellian distribution function – driven by ionization, charge exchange and wall loss – is allowed to be arbitrarily large. The numerical scheme is implemented in the gyrokinetic particle code XGC1, which specializes in simulating the tokamak edge plasma that crosses the magnetic separatrix and is in contact with the material wall.

  17. A new hybrid-Lagrangian numerical scheme for gyrokinetic simulation of tokamak edge plasma

    Science.gov (United States)

    Ku, S.; Hager, R.; Chang, C. S.; Kwon, J. M.; Parker, S. E.

    2016-06-01

    In order to enable kinetic simulation of non-thermal edge plasmas at a reduced computational cost, a new hybrid-Lagrangian δf scheme has been developed that utilizes the phase space grid in addition to the usual marker particles, taking advantage of the computational strengths from both sides. The new scheme splits the particle distribution function of a kinetic equation into two parts. Marker particles contain the fast space-time varying, δf, part of the distribution function and the coarse-grained phase-space grid contains the slow space-time varying part. The coarse-grained phase-space grid reduces the memory-requirement and the computing cost, while the marker particles provide scalable computing ability for the fine-grained physics. Weights of the marker particles are determined by a direct weight evolution equation instead of the differential form weight evolution equations that the conventional delta-f schemes use. The particle weight can be slowly transferred to the phase space grid, thereby reducing the growth of the particle weights. The non-Lagrangian part of the kinetic equation - e.g., collision operation, ionization, charge exchange, heat-source, radiative cooling, and others - can be operated directly on the phase space grid. Deviation of the particle distribution function on the velocity grid from a Maxwellian distribution function - driven by ionization, charge exchange and wall loss - is allowed to be arbitrarily large. The numerical scheme is implemented in the gyrokinetic particle code XGC1, which specializes in simulating the tokamak edge plasma that crosses the magnetic separatrix and is in contact with the material wall.

  18. Classification of basic facilities for high-rise residential: A survey from 100 housing scheme in Kajang area

    Science.gov (United States)

    Ani, Adi Irfan Che; Sairi, Ahmad; Tawil, Norngainy Mohd; Wahab, Siti Rashidah Hanum Abd; Razak, Muhd Zulhanif Abd

    2016-08-01

    High demand for housing and limited land in town area has increasing the provision of high-rise residential scheme. This type of housing has different owners but share the same land lot and common facilities. Thus, maintenance works of the buildings and common facilities must be well organized. The purpose of this paper is to identify and classify basic facilities for high-rise residential building hoping to improve the management of the scheme. The method adopted is a survey on 100 high-rise residential schemes that ranged from affordable housing to high cost housing by using a snowball sampling. The scope of this research is within Kajang area, which is rapidly developed with high-rise housing. The objective of the survey is to list out all facilities in every sample of the schemes. The result confirmed that pre-determined 11 classifications hold true and can provide the realistic classification for high-rise residential scheme. This paper proposed for redefinition of facilities provided to create a better management system and give a clear definition on the type of high-rise residential based on its facilities.

  19. The "chessboard" classification scheme of mineral deposits: Mineralogy and geology from aluminum to zirconium

    Science.gov (United States)

    Dill, Harald G.

    2010-06-01

    Economic geology is a mixtum compositum of all geoscientific disciplines focused on one goal, finding new mineral depsosits and enhancing their exploitation. The keystones of this mixtum compositum are geology and mineralogy whose studies are centered around the emplacement of the ore body and the development of its minerals and rocks. In the present study, mineralogy and geology act as x- and y-coordinates of a classification chart of mineral resources called the "chessboard" (or "spreadsheet") classification scheme. Magmatic and sedimentary lithologies together with tectonic structures (1 -D/pipes, 2 -D/veins) are plotted along the x-axis in the header of the spreadsheet diagram representing the columns in this chart diagram. 63 commodity groups, encompassing minerals and elements are plotted along the y-axis, forming the lines of the spreadsheet. These commodities are subjected to a tripartite subdivision into ore minerals, industrial minerals/rocks and gemstones/ornamental stones. Further information on the various types of mineral deposits, as to the major ore and gangue minerals, the current models and the mode of formation or when and in which geodynamic setting these deposits mainly formed throughout the geological past may be obtained from the text by simply using the code of each deposit in the chart. This code can be created by combining the commodity (lines) shown by numbers plus lower caps with the host rocks or structure (columns) given by capital letters. Each commodity has a small preface on the mineralogy and chemistry and ends up with an outlook into its final use and the supply situation of the raw material on a global basis, which may be updated by the user through a direct link to databases available on the internet. In this case the study has been linked to the commodity database of the US Geological Survey. The internal subdivision of each commodity section corresponds to the common host rock lithologies (magmatic, sedimentary, and

  20. Role of exact exchange in thermally-assisted-occupation density functional theory: A proposal of new hybrid schemes

    CERN Document Server

    Chai, Jeng-Da

    2016-01-01

    We propose hybrid schemes incorporating exact exchange into thermally-assisted-occupation density functional theory (TAO-DFT) [J.-D. Chai, J. Chem. Phys. 136, 154104 (2012)] for an improved description of nonlocal exchange effects. With a few simple modifications, global and range-separated hybrid functionals in Kohn-Sham density functional theory (KS-DFT) can be combined seamlessly with TAO-DFT. In comparison with global hybrid functionals in KS-DFT, the resulting global hybrid functionals in TAO-DFT yield promising performance for systems with strong static correlation effects (e.g., the H2 dissociation and electronic properties of linear acenes), while maintaining similar performance for systems without strong static correlation effects. Besides, a reasonably accurate description of noncovalent interactions can be efficiently achieved through the inclusion of dispersion corrections in hybrid TAO-DFT. Relative to TAO-DFAs (i.e., TAO-DFT with the conventional density functional approximations), global hybrid...

  1. A hybrid variational-ensemble data assimilation scheme with systematic error correction for limited-area ocean models

    Science.gov (United States)

    Oddo, Paolo; Storto, Andrea; Dobricic, Srdjan; Russo, Aniello; Lewis, Craig; Onken, Reiner; Coelho, Emanuel

    2016-10-01

    A hybrid variational-ensemble data assimilation scheme to estimate the vertical and horizontal parts of the background error covariance matrix for an ocean variational data assimilation system is presented and tested in a limited-area ocean model implemented in the western Mediterranean Sea. An extensive data set collected during the Recognized Environmental Picture Experiments conducted in June 2014 by the Centre for Maritime Research and Experimentation has been used for assimilation and validation. The hybrid scheme is used to both correct the systematic error introduced in the system from the external forcing (initialisation, lateral and surface open boundary conditions) and model parameterisation, and improve the representation of small-scale errors in the background error covariance matrix. An ensemble system is run offline for further use in the hybrid scheme, generated through perturbation of assimilated observations. Results of four different experiments have been compared. The reference experiment uses the classical stationary formulation of the background error covariance matrix and has no systematic error correction. The other three experiments account for, or not, systematic error correction and hybrid background error covariance matrix combining the static and the ensemble-derived errors of the day. Results show that the hybrid scheme when used in conjunction with the systematic error correction reduces the mean absolute error of temperature and salinity misfit by 55 and 42 % respectively, versus statistics arising from standard climatological covariances without systematic error correction.

  2. A Hybrid Global Minimization Scheme for Accurate Source Localization in Sensor Networks

    CERN Document Server

    Aghasi, Hamidreza

    2011-01-01

    We consider the localization problem of multiple wideband sources by coherently taking into account the attenuation characteristics and the time delays in the reception of the signal. Our proposed method leaves the space for unavailability of an accurate signal attenuation model in the environment by considering the model as an unknown function with reasonable prior assumptions about its functional space. Such approach is capable of enhancing the localization performance compared to only utilizing the signal attenuation information or the time delays. In this paper the localization problem is modelled as a cost function in terms of the source locations and the attenuation model parameters. To globally perform the minimization we propose a hybrid algorithm combining the differential evolution algorithm with the Levenberg-Marquardt algorithm. Beside the proposed combination scheme, supporting technical details such as closed forms of cost function sensitivity matrices are provided. Finally the validity of the p...

  3. Sensorless torque control scheme of induction motor for hybrid electric vehicle

    Institute of Scientific and Technical Information of China (English)

    Yan LIU; Cheng SHAO

    2007-01-01

    In this paper,the sensorless torque robust tracking problem of the induction motor for hybrid electric vehicle(HEV)applications is addressed.Because motor parameter variations in HEV applications are larger than in industrial drive system,the conventional field-oriented control(FOC)provides poor performance.Therefore,a new robust PI-based extension of the FOC controller and a speed-flux observer based on sliding mode and Lyapunov theory are developed in order to Improve the overall performance.Simulation results show that the proposed sensorless torque control scheme is robust with respect to motor parameter variations and loading disturbances.In addition,the operating flux of the motor is chosen optimally to minimize the consumption of electric energy,which results in a significant reduction in energy losses shown by simulations.

  4. Hybrid scheme of positron source at SPARC-LAB LNF facility

    Energy Technology Data Exchange (ETDEWEB)

    Abdrashitov, S.V., E-mail: abdsv@tpu.ru [National Research Tomsk Polytechnic University, Lenin Ave 30, 634050 Tomsk (Russian Federation); National Research Tomsk State University, Lenin Ave 36, 634050 Tomsk (Russian Federation); Bogdanov, O.V. [National Research Tomsk Polytechnic University, Lenin Ave 30, 634050 Tomsk (Russian Federation); Dabagov, S.B. [INFN Laboratori Nazionali di Frascati, Via E. Fermi 40, I-00044 Frascati, RM (Italy); RAS PN Lebedev Physical Institute, Leninskiy Prospekt 53, 119991 Moscow (Russian Federation); NRNU MEPhI, Kashirskoe Highway 31, 115409 Moscow (Russian Federation); Pivovarov, Yu.L.; Tukhfatullin, T.A. [National Research Tomsk Polytechnic University, Lenin Ave 30, 634050 Tomsk (Russian Federation)

    2015-07-15

    The hybrid scheme of the positron source for SPARC-LAB LNF facility (Frascati, Italy) is proposed. The comparison of the positron yield in a thin amorphous W converter of 0.1 mm thickness produced by bremsstrahlung, by axial 〈1 0 0〉 and planar (1 1 0) channeling radiations in a W crystal is performed for the positron energy range of 1 ÷ 3 MeV. It is shown that the radiation from 200 MeV electrons (parameters of SPARC-LAB LNF Frascati) in a 10 μm W crystal can produce positrons in the radiator of 0.1 mm thickness with the rate of 10–10{sup 2} s{sup −1} at planar channeling, of 10{sup 2}–10{sup 3} s{sup −1} at bremsstrahlung and of 10{sup 3}–10{sup 4} s{sup −1} at axial channeling.

  5. Hybrid Intrusion Detection Using Ensemble of Classification Methods

    Directory of Open Access Journals (Sweden)

    M.Govindarajan

    2014-01-01

    Full Text Available One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed for homogeneous ensemble classifiers using bagging and heterogeneous ensemble classifiers using arcing classifier and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF and Support Vector Machine (SVM as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of real and benchmark data sets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase and combining phase. A wide range of comparative experiments are conducted for real and benchmark data sets of intrusion detection. The accuracy of base classifiers is compared with homogeneous and heterogeneous models for data mining problem. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and also heterogeneous models exhibit better results than homogeneous models for real and benchmark data sets of intrusion detection.

  6. A Polar Fuzzy Control Scheme for Hybrid Power System Using Vehicle-To-Grid Technique

    Directory of Open Access Journals (Sweden)

    Mohammed Elsayed Lotfy

    2017-07-01

    Full Text Available A novel polar fuzzy (PF control approach for a hybrid power system is proposed in this research. The proposed control scheme remedies the issues of system frequency and the continuity of demand supply caused by renewable sources’ uncertainties. The hybrid power system consists of a wind turbine generator (WTG, solar photovoltaics (PV, a solar thermal power generator (STPG, a diesel engine generator (DEG, an aqua-electrolyzer (AE, an ultra-capacitor (UC, a fuel-cell (FC, and a flywheel (FW. Furthermore, due to the high cost of the battery energy storage system (BESS, a new idea of vehicle-to-grid (V2G control is applied to use the battery of the electric vehicle (EV as equivalent to large-scale energy storage units instead of small batteries to improve the frequency stability of the system. In addition, EV customers’ convenience is taken into account. A minimal-order observer is used to estimate the supply error. Then, the area control error (ACE signal is calculated in terms of the estimated supply error and the frequency deviation. ACE is considered in the frequency domain. Two PF approaches are utilized in the intended system. The mission of each controller is to mitigate one frequency component of ACE. The responsibility for ACE compensation is shared among all parts of the system according to their speed of response. The performance of the proposed control scheme is compared to the conventional fuzzy logic control (FLC. The effectiveness and robustness of the proposed control technique are verified by numerical simulations under various scenarios.

  7. Enhancing Access to Knowledge Management Literature — A Proposal for Domain-Based Classification Scheme and Thesaurus

    OpenAIRE

    Denise A. D. Bedford

    2015-01-01

    Knowledge organisation systems (KOS) include a variety of tools and methods for organising information and knowledge 'things'. When we refer to KOS we generally mean classification schemes, thesauri, semantic networks, and authority control systems. Most academic disciplines are supported by professionally developed and maintained KOS. This is not the case for knowledge management. Knowledge management is insufficiently treated in existing KOS. The research is exploratory in its approach to d...

  8. A New Hybrid Scheme for Simulations of Highly Collisional RF-Driven Plasmas

    CERN Document Server

    Eremin, Denis; Mussenbrock, Thomas

    2015-01-01

    This work describes a new 1D hybrid approach for modeling atmospheric pressure discharges featuring complex chemistry. In this approach electrons are described fully kinetically using Particle-In-Cell/Monte-Carlo (PIC/MCC) scheme, whereas the heavy species are modeled within a fluid description. Validity of the popular drift-diffusion approximation is verified against a "full" fluid model accounting for the ion inertia and a fully kinetic PIC/MCC code for ions as well as electrons. The fluid models require knowledge of the momentum exchange frequency and dependence of the ion mobilities on the electric field when the ions are in equilibrium with the latter. To this end an auxiliary Monte-Carlo scheme is constructed. It is demonstrated that the drift-diffusion approximation can overestimate ion transport in simulations of RF-driven discharges with heavy ion species operated in the $\\gamma$ mode at the atmospheric pressure or in all discharge simulations for lower pressures. This can lead to exaggerated plasma ...

  9. Hybrid (kinetic-fluid) simulation scheme based on method of characteristics

    CERN Document Server

    Javaheri, N; Abbasi, H

    2015-01-01

    Certain features of the method of characteristics are of considerable interest in relation with Vlasov simulation [H. Abbasi {\\it et al}, Phys. Rev. E \\textbf{84}, 036702 (2011)]. A Vlasov simulation scheme of this kind can be recurrence free providing initial phase points in velocity space are set randomly. Naturally, less filtering of fine-structures (arising from grid spacing) is possible as there is now a smaller scale than the grid spacing that is average distance between two phase points. Its interpolation scheme is very simple in form and carried out with less operations. In our previous report, the simplest model (immobile ions) was considered to merely demonstrate the important features. Now, a hybrid model is introduced that solves the coupled Vlasov-Fluid-Poisson system self-consistently. A possible application of the code is the study of ion-acoustic (IA) soliton attributes. To this end, a collisionless plasma with hot electrons and cold positive ions is considered. For electrons, the collisionles...

  10. Comparison of control schemes for a fuel cell hybrid tramway integrating two dc/dc converters

    Energy Technology Data Exchange (ETDEWEB)

    Fernandez, L.M.; Garcia, P.; Garcia, C.A. [Department of Electrical Engineering, EPS Algeciras, University of Cadiz, Avda. Ramon Puyol, s/n, 11202 Algeciras (Cadiz) (Spain); Torreglosa, J.P.; Jurado, F. [Department of Electrical Engineering, EPS Linares, University of Jaen, C/Alfonso X, n 28. 23700 Linares (Jaen) (Spain)

    2010-06-15

    This paper describes a comparative study of two control schemes for the energy management system of a hybrid tramway powered by a Polymer Electrolyte Membrane (PEM) Fuel Cell (FC) and an Ni-MH battery. The hybrid system was designed for a real surface tramway of 400 kW. It is composed of a PEM FC system with a unidirectional dc/dc boost converter (FC converter) and a rechargeable Ni-MH battery with a bidirectional dc/dc converter (battery converter), both of which are coupled to a traction dc bus. The PEM FC and Ni-MH battery models were designed from commercially available components. The function of the two control architectures was to effectively distribute the power of the electrical sources. One of these control architectures was a state machine control strategy, based on eight states. The other was a cascade control strategy which was used to validate the results obtained. The simulation results for the real driving cycle of the tramway reflected the optimal performance of the control systems compared in this study. (author)

  11. Hybrid Feature Selection for Myoelectric Signal Classification Using MICA

    Science.gov (United States)

    Naik, Ganesh R.; Kumar, Dinesh K.

    2010-03-01

    This paper presents a novel method to enhance the performance of Independent Component Analysis (ICA) of myoelectric signal by decomposing the signal into components originating from different muscles. First, we use Multi run ICA (MICA) algorithm to separate the muscle activities. Pattern classification of the separated signal is performed in the second step with a back propagation neural network. The focus of this work is to establish a simple, yet robust system that can be used to identify subtle complex hand actions and gestures for control of prosthesis and other computer assisted devices. Testing was conducted using several single shot experiments conducted with five subjects. The results indicate that the system is able to classify four different wrist actions with near 100% accuracy.

  12. Optical Image Classification Using Optical/digital Hybrid Image Processing Systems.

    Science.gov (United States)

    Li, Xiaoyang

    1990-01-01

    Offering parallel and real-time operations, optical image classification is becoming a general technique in the solution of real-life image classification problems. This thesis investigates several algorithms for optical realization. Compared to other statistical pattern recognition algorithms, the Kittler-Young transform can provide more discriminative feature spaces for image classification. We shall apply the Kittler-Young transform to image classification and implement it on optical systems. A feature selection criterion is designed for the application of the Kittler -Young transform to image classification. The realizations of the Kittler-Young transform on both a joint transform correlator and a matrix multiplier are successively conducted. Experiments of applying this technique to two-category and three-category problems are demonstrated. To combine the advantages of the statistical pattern recognition algorithms and the neural network models, processes using the two methods are studied. The Karhunen-Loeve Hopfield model is developed for image classification. This model has significant improvement in the system capacity and the capability of using image structures for more discriminative classification processes. As another such hybrid process, we propose the feature extraction perceptron. The application of feature extraction techniques to the perceptron shortens its learning time. An improved activation function of neurons (dynamic activation function), its design and updating rule for fast learning process and high space-bandwidth product image classification are also proposed. We have shortened by two-thirds the learning time on the feature extraction perceptron as compared with the original perceptron. By using this architecture, we have shown that the classification performs better than both the Kittler-Young transform and the original perceptron.

  13. Classification of Movement and Inhibition Using a Hybrid BCI.

    Science.gov (United States)

    Chmura, Jennifer; Rosing, Joshua; Collazos, Steven; Goodwin, Shikha J

    2017-01-01

    Brain-computer interfaces (BCIs) are an emerging technology that are capable of turning brain electrical activity into commands for an external device. Motor imagery (MI)-when a person imagines a motion without executing it-is widely employed in BCI devices for motor control because of the endogenous origin of its neural control mechanisms, and the similarity in brain activation to actual movements. Challenges with translating a MI-BCI into a practical device used outside laboratories include the extensive training required, often due to poor user engagement and visual feedback response delays; poor user flexibility/freedom to time the execution/inhibition of their movements, and to control the movement type (right arm vs. left leg) and characteristics (reaching vs. grabbing); and high false positive rates of motion control. Solutions to improve sensorimotor activation and user performance of MI-BCIs have been explored. Virtual reality (VR) motor-execution tasks have replaced simpler visual feedback (smiling faces, arrows) and have solved this problem to an extent. Hybrid BCIs (hBCIs) implementing an additional control signal to MI have improved user control capabilities to a limited extent. These hBCIs either fail to allow the patients to gain asynchronous control of their movements, or have a high false positive rate. We propose an immersive VR environment which provides visual feedback that is both engaging and immediate, but also uniquely engages a different cognitive process in the patient that generates event-related potentials (ERPs). These ERPs provide a key executive function for the users to execute/inhibit movements. Additionally, we propose signal processing strategies and machine learning algorithms to move BCIs toward developing long-term signal stability in patients with distinctive brain signals and capabilities to control motor signals. The hBCI itself and the VR environment we propose would help to move BCI technology outside laboratory

  14. Classification of Movement and Inhibition Using a Hybrid BCI

    Directory of Open Access Journals (Sweden)

    Jennifer Chmura

    2017-08-01

    Full Text Available Brain-computer interfaces (BCIs are an emerging technology that are capable of turning brain electrical activity into commands for an external device. Motor imagery (MI—when a person imagines a motion without executing it—is widely employed in BCI devices for motor control because of the endogenous origin of its neural control mechanisms, and the similarity in brain activation to actual movements. Challenges with translating a MI-BCI into a practical device used outside laboratories include the extensive training required, often due to poor user engagement and visual feedback response delays; poor user flexibility/freedom to time the execution/inhibition of their movements, and to control the movement type (right arm vs. left leg and characteristics (reaching vs. grabbing; and high false positive rates of motion control. Solutions to improve sensorimotor activation and user performance of MI-BCIs have been explored. Virtual reality (VR motor-execution tasks have replaced simpler visual feedback (smiling faces, arrows and have solved this problem to an extent. Hybrid BCIs (hBCIs implementing an additional control signal to MI have improved user control capabilities to a limited extent. These hBCIs either fail to allow the patients to gain asynchronous control of their movements, or have a high false positive rate. We propose an immersive VR environment which provides visual feedback that is both engaging and immediate, but also uniquely engages a different cognitive process in the patient that generates event-related potentials (ERPs. These ERPs provide a key executive function for the users to execute/inhibit movements. Additionally, we propose signal processing strategies and machine learning algorithms to move BCIs toward developing long-term signal stability in patients with distinctive brain signals and capabilities to control motor signals. The hBCI itself and the VR environment we propose would help to move BCI technology outside

  15. Hybrid SPR algorithm to select predictive genes for effectual cancer classification

    OpenAIRE

    2012-01-01

    Designing an automated system for classifying DNA microarray data is an extremely challenging problem because of its high dimension and low amount of sample data. In this paper, a hybrid statistical pattern recognition algorithm is proposed to reduce the dimensionality and select the predictive genes for the classification of cancer. Colon cancer gene expression profiles having 62 samples of 2000 genes were used for the experiment. A gene subset of 6 highly informative genes was selecte...

  16. A Discrete Wavelet Based Feature Extraction and Hybrid Classification Technique for Microarray Data Analysis

    Directory of Open Access Journals (Sweden)

    Jaison Bennet

    2014-01-01

    Full Text Available Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN, naive Bayes, and support vector machine (SVM. Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT and moving window technique (MWT is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.

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

    Science.gov (United States)

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

    2017-01-01

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

  18. Hybrid finite volume scheme for a two-phase flow in heterogeneous porous media*

    Directory of Open Access Journals (Sweden)

    Brenner Konstantin

    2012-04-01

    Full Text Available We propose a finite volume method on general meshes for the numerical simulation of an incompressible and immiscible two-phase flow in porous media. We consider the case that can be written as a coupled system involving a degenerate parabolic convection-diffusion equation for the saturation together with a uniformly elliptic equation for the global pressure. The numerical scheme, which is implicit in time, allows computations in the case of a heterogeneous and anisotropic permeability tensor. The convective fluxes, which are non monotone with respect to the unknown saturation and discontinuous with respect to the space variables, are discretized by means of a special Godunov scheme. We prove the existence of a discrete solution which converges, along a subsequence, to a solution of the continuous problem. We present a number of numerical results in space dimension two, which confirm the efficiency of the numerical method. Nous proposons un schéma de volumes finis hybrides pour la discrétisation d’un problème d’écoulement diphasique incompressible et immiscible en milieu poreux. On suppose que ce problème a la forme d’une équation parabolique dégénérée de convection-diffusion en saturation couplée à une équation uniformément elliptique en pression. On considère un schéma implicite en temps, où les flux diffusifs sont discrétisés par la méthode des volumes finis hybride, ce qui permet de pouvoir traiter le cas d’un tenseur de perméabilité anisotrope et hétérogène sur un maillage très général, et l’on s’appuie sur un schéma de Godunov pour la discrétisation des flux convectifs, qui peuvent être non monotones et discontinus par rapport aux variables spatiales. On démontre l’existence d’une solution discrète, dont une sous-suite converge vers une solution faible du problème continu. On présente finalement des cas test bidimensionnels.

  19. Fuzzy-logic-based hybrid locomotion mode classification for an active pelvis orthosis: Preliminary results.

    Science.gov (United States)

    Yuan, Kebin; Parri, Andrea; Yan, Tingfang; Wang, Long; Munih, Marko; Vitiello, Nicola; Wang, Qining

    2015-01-01

    In this paper, we present a fuzzy-logic-based hybrid locomotion mode classification method for an active pelvis orthosis. Locomotion information measured by the onboard hip joint angle sensors and the pressure insoles is used to classify five locomotion modes, including two static modes (sitting, standing still), and three dynamic modes (level-ground walking, ascending stairs, and descending stairs). The proposed method classifies these two kinds of modes first by monitoring the variation of the relative hip joint angle between the two legs within a specific period. Static states are then classified by the time-based absolute hip joint angle. As for dynamic modes, a fuzzy-logic based method is proposed for the classification. Preliminary experimental results with three able-bodied subjects achieve an off-line classification accuracy higher than 99.49%.

  20. Tissue classification by wavelet modified generic Fourier descriptor and their recognition using hybrid correlator

    Science.gov (United States)

    Yadav, Raj Bahadur; Gupta, Arun K.

    2010-02-01

    Segmentation in Magnetic resonance imaging (MRI) images is a widely studied problem, and techniques (supervised and unsupervised) are discussed in the literature. The basic approaches to image segmentation are based upon: (a) boundary representation, (b) regional characteristics and (c) a combination of boundary and region-based features. In this paper, we report classification of brain tissue based objects employing one of combination of boundary and region-based features as wavelet modified generic Fourier descriptor (WGFD) technique. This technique have been applied to a database consisting of 3 different class's tissues, each class consist of 50 shapes. The Euclidean distance has been calculated as a similarity measure parameter for tissue shape classification. The classification results have been carried out and it is inferred that WGFD performs for brain tissue classification. For brain tissue recognition, a simulation experiment employing hybrid correlator architecture has been carried out. We have used Wavelet modified maximum average correlation hight (MACH) filter for hybrid correlator. Mexican-hat wavelet has used to synthesize the wavelet MACH filter for simulation experiment.

  1. A Hybrid Key Management Scheme for WSNs Based on PPBR and a Tree-Based Path Key Establishment Method.

    Science.gov (United States)

    Zhang, Ying; Liang, Jixing; Zheng, Bingxin; Chen, Wei

    2016-04-09

    With the development of wireless sensor networks (WSNs), in most application scenarios traditional WSNs with static sink nodes will be gradually replaced by Mobile Sinks (MSs), and the corresponding application requires a secure communication environment. Current key management researches pay less attention to the security of sensor networks with MS. This paper proposes a hybrid key management schemes based on a Polynomial Pool-based key pre-distribution and Basic Random key pre-distribution (PPBR) to be used in WSNs with MS. The scheme takes full advantages of these two kinds of methods to improve the cracking difficulty of the key system. The storage effectiveness and the network resilience can be significantly enhanced as well. The tree-based path key establishment method is introduced to effectively solve the problem of communication link connectivity. Simulation clearly shows that the proposed scheme performs better in terms of network resilience, connectivity and storage effectiveness compared to other widely used schemes.

  2. Hybrid Architecture IPTV System Scheme%混合架构IPTV系统方案

    Institute of Scientific and Technical Information of China (English)

    于宏锦; 甘露; 刘新; 叶德建

    2011-01-01

    传统内容分发网络(CDN)互联协议电视(IPTV)系统的部署和维护成本较高.为此,提出采用CDN和对等(P2P)混合架构的IPTV系统方案.在原有系统基础上,加入P2P技术,对上海电信IPTV系统的实验数据加以分析,设计节目热门度模型.实验结果表明,该方案能降低系统开销,提高系统的可扩展性,使用该热门度模型后,降低约40%的系统负载.%Aiming at the problem that traditional Content Delivery Network(CDN) architecture Internet Protocol Television(IPTV) system is expensive to deploy and maintain. Hybrid architecture IPTV system project is proposed. The original IPTV system of CDN architecture is merged with Peer-to-Peer(P2P). This paper analyzes the real data of shanghai telecom IPTV system, designs an approximate model of program popular degree. Experimental results show that, this scheme can cut costs and enhance the scalability, the model of popular degree get about 40% system load reducement as a result.

  3. Hardwood species classification with DWT based hybrid texture feature extraction techniques

    Indian Academy of Sciences (India)

    Arvind R Yadav; R S Anand; M L Dewal; Sangeeta Gupta

    2015-12-01

    In this work, discrete wavelet transform (DWT) based hybrid texture feature extraction techniques have been used to categorize the microscopic images of hardwood species into 75 different classes. Initially, the DWT has been employed to decompose the image up to 7 levels using Daubechies (db3) wavelet as decomposition filter. Further, first-order statistics (FOS) and four variants of local binary pattern (LBP) descriptors are used to acquire distinct features of these images at various levels. The linear support vector machine (SVM), radial basis function (RBF) kernel SVM and random forest classifiers have been employed for classification. The classification accuracy obtained with state-of-the-art and DWT based hybrid texture features using various classifiers are compared. The DWT based FOS-uniform local binary pattern (DWTFOSLBPu2) texture features at the 4th level of image decomposition have produced best classification accuracy of 97.67 ± 0.79% and 98.40 ± 064% for grayscale and RGB images, respectively, using linear SVM classifier. Reduction in feature dataset by minimal redundancy maximal relevance (mRMR) feature selection method is achieved and the best classification accuracy of 99.00 ± 0.79% and 99.20 ± 0.42% have been obtained for DWT based FOS-LBP histogram Fourier features (DWTFOSLBP-HF) technique at the 5th and 6th levels of image decomposition for grayscale and RGB images, respectively, using linear SVM classifier. The DWTFOSLBP-HF features selected with mRMR method has also established superiority amongst the DWT based hybrid texture feature extraction techniques for randomly divided database into different proportions of training and test datasets.

  4. An efficient hybrid pseudospectral/finite-difference scheme for solving the TTI pure P-wave equation

    KAUST Repository

    Zhan, Ge

    2013-02-19

    The pure P-wave equation for modelling and migration in tilted transversely isotropic (TTI) media has attracted more and more attention in imaging seismic data with anisotropy. The desirable feature is that it is absolutely free of shear-wave artefacts and the consequent alleviation of numerical instabilities generally suffered by some systems of coupled equations. However, due to several forward-backward Fourier transforms in wavefield updating at each time step, the computational cost is significant, and thereby hampers its prevalence. We propose to use a hybrid pseudospectral (PS) and finite-difference (FD) scheme to solve the pure P-wave equation. In the hybrid solution, most of the cost-consuming wavenumber terms in the equation are replaced by inexpensive FD operators, which in turn accelerates the computation and reduces the computational cost. To demonstrate the benefit in cost saving of the new scheme, 2D and 3D reverse-time migration (RTM) examples using the hybrid solution to the pure P-wave equation are carried out, and respective runtimes are listed and compared. Numerical results show that the hybrid strategy demands less computation time and is faster than using the PS method alone. Furthermore, this new TTI RTM algorithm with the hybrid method is computationally less expensive than that with the FD solution to conventional TTI coupled equations. © 2013 Sinopec Geophysical Research Institute.

  5. How does the selection of landscape classification schemes affect the spatial pattern of natural landscapes? An assessment on a coastal wetland site in southern Italy.

    Science.gov (United States)

    Tomaselli, V; Veronico, G; Sciandrello, S; Blonda, P

    2016-06-01

    It is widely known that thematic resolution affects spatial pattern and landscape metrics performances. In literature, data dealing with this issue usually refer to a specific class scheme with its thematic levels. In this paper, the effects of different land cover (LC) and habitat classification schemes on the spatial pattern of a coastal landscape were compared. One of the largest components of the Mediterranean wetland system was considered as the study site, and different schemes widely used in the EU were selected and harmonized with a common thematic resolution, suitable for habitat discrimination and monitoring. For each scheme, a thematic map was produced and, for each map, 28 landscape metrics were calculated. The landscape composition, already in terms of number of classes, class area, and number of patches, changes significantly among different classification schemes. Landscape complexity varies according to the class scheme considered and its underlying semantics, depending on how the different types aggregate or split when changing class scheme. Results confirm that the selection of a specific class scheme affects the spatial pattern of the derived landscapes and consequently the landscape metrics, especially at class level. Moreover, among the classification schemes considered, EUNIS seems to be the best choice for a comprehensive representation of both natural and anthropogenic classes.

  6. Hybrid Feature Based War Scene Classification using ANN and SVM: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Shanmugam A

    2011-05-01

    Full Text Available In this paper we are proposing a hybrid feature extraction method for classifying the war scene from the natural scene. For this purpose two set of image categories are taken viz., opencountry & war tank. Byusing the hybrid method, features are extracted from the images/scenes. The extracted features are trained and tested with (i Artificial Neural Networks (ANN using feed forward back propagationalgorithm and (ii Support Vector Machines (SVM using Radial basis kernel functions with p=5. The results are also compared with the commonly used feature extraction methods such as haar wavelet,daubechies(db4 wavelet, Zernike moments, Invariant moments, co-occurrence features and statistical moments. The comparative results are proving efficiency of the proposed hybrid feature extraction method (i.e., the combination of GLCM & Statistical moments in war scene classification problems. It can be concluded that the proposed work significantly and directly contributes to scene classification and its new applications. The complete work is experimented in Matlab 7.6.0 using real world dataset.

  7. Optical tomographic detection of rheumatoid arthritis with computer-aided classification schemes

    Science.gov (United States)

    Klose, Christian D.; Klose, Alexander D.; Netz, Uwe; Beuthan, Jürgen; Hielscher, Andreas H.

    2009-02-01

    A recent research study has shown that combining multiple parameters, drawn from optical tomographic images, leads to better classification results to identifying human finger joints that are affected or not affected by rheumatic arthritis RA. Building up on the research findings of the previous study, this article presents an advanced computer-aided classification approach for interpreting optical image data to detect RA in finger joints. Additional data are used including, for example, maximum and minimum values of the absorption coefficient as well as their ratios and image variances. Classification performances obtained by the proposed method were evaluated in terms of sensitivity, specificity, Youden index and area under the curve AUC. Results were compared to different benchmarks ("gold standard"): magnet resonance, ultrasound and clinical evaluation. Maximum accuracies (AUC=0.88) were reached when combining minimum/maximum-ratios and image variances and using ultrasound as gold standard.

  8. Fast Schemes for Computing Similarities between Gaussian HMMs and Their Applications in Texture Image Classification

    Directory of Open Access Journals (Sweden)

    Chen Ling

    2005-01-01

    Full Text Available An appropriate definition and efficient computation of similarity (or distance measures between two stochastic models are of theoretical and practical interest. In this work, a similarity measure, that is, a modified "generalized probability product kernel," of Gaussian hidden Markov models is introduced. Two efficient schemes for computing this similarity measure are presented. The first scheme adopts a forward procedure analogous to the approach commonly used in probability evaluation of observation sequences on HMMs. The second scheme is based on the specially defined similarity transition matrix of two Gaussian hidden Markov models. Two scaling procedures are also proposed to solve the out-of-precision problem in the implementation. The effectiveness of the proposed methods has been evaluated on simulated observations with predefined model parameters, and on natural texture images. Promising experimental results have been observed.

  9. Classification of High-Rise Residential Building Facilities: A Descriptive Survey on 170 Housing Scheme in Klang Valley

    Directory of Open Access Journals (Sweden)

    Abd Wahab Siti Rashidah Hanum

    2016-01-01

    Full Text Available High-rise residential building is a type of housing that has multi-dwelling units built on the same land. This type of housing has become popular each year in urban area due to the increasing cost of land. There are several common facilities provided in high-rise residential building. For example playground, swimming pool, gymnasium, 24 hours security system such as CCTV, access card and so on. Thus, maintenance works of the common facilities must be well organised. The purpose of this paper is to identify the classification of facilities provided at high rise residential building. The survey was done on 170 high-rise residential schemes by using stratified random sampling technique. The scope of this research is within Klang Valley area. This area is rapidly developed with high-rise residential building. The objective of this survey is to list down all the facilities provided in each sample of the schemes. The result, there are nine classification of facilities provided for high-rise residential building.

  10. An Improved LU-SGS Implicit Scheme for High Reynolds Number Flow Computations on Hybrid Unstructured Mesh

    Institute of Scientific and Technical Information of China (English)

    WANG Gang; JIANG Yuewen; YE Zhengyin

    2012-01-01

    The lower-upper symmetric Gauss-Seidel (LU-SGS) implicit relaxation has been widely used because it has the merits of less dependency on grid topology,low numerical complexity and modest memory requirements.In original LU-SGS scheme,the implicit system matrix is construeted based on the splitting of convective flux Jacobian according to its spectral radius.Although this treatment has the merit of reducing computational complexity and helps to ensure the diagonally dominant property of the implicit system marx,it can also cause serious distortions on the implicit system matrix because too many approximations are introduced by this splitting method if the contravariant velocity is small or close to sonic speed.To overcome this shortcoming,an improved LU-SGS scheme with a hybrid construction method for the implicit system matrix is developed in this paper.The hybrid way is that:on the cell faces having small contravariant velocity or transonic contravariant velocity,the accurate derivative of the convective flux term is used to construct more accurate implicit system matrix,while the original Jacobian splitting method is adopted on the other cell faces to reduce computational complexity and ensure the diagonally dominant property of the implicit system matrix.To investigate the convergence performance of the improved LU-SGS scheme,2D and 3D turbulent flows around the NACA0012 airfoil,RAE2822 airfoil and LANN wing are simulated on hybrid unstructured meshes.The numerical results show that the improved LU-SGS scheme is significantly more efficient than the original LU-SGS scheme.

  11. An Energy-Aware Hybrid ARQ Scheme with Multi-ACKs for Data Sensing Wireless Sensor Networks.

    Science.gov (United States)

    Zhang, Jinhuan; Long, Jun

    2017-06-12

    Wireless sensor networks (WSNs) are one of the important supporting technologies of edge computing. In WSNs, reliable communications are essential for most applications due to the unreliability of wireless links. In addition, network lifetime is also an important performance metric and needs to be considered in many WSN studies. In the paper, an energy-aware hybrid Automatic Repeat-reQuest protocol (ARQ) scheme is proposed to ensure energy efficiency under the guarantee of network transmission reliability. In the scheme, the source node sends data packets continuously with the correct window size and it does not need to wait for the acknowledgement (ACK) confirmation for each data packet. When the destination receives K data packets, it will return multiple copies of one ACK for confirmation to avoid ACK packet loss. The energy consumption of each node in flat circle network applying the proposed scheme is statistical analyzed and the cases under which it is more energy efficiency than the original scheme is discussed. Moreover, how to select parameters of the scheme is addressed to extend the network lifetime under the constraint of the network reliability. In addition, the energy efficiency of the proposed schemes is evaluated. Simulation results are presented to demonstrate that a node energy consumption reduction could be gained and the network lifetime is prolonged.

  12. Classification of ETM+ Remote Sensing Image Based on Hybrid Algorithm of Genetic Algorithm and Back Propagation Neural Network

    Directory of Open Access Journals (Sweden)

    Haisheng Song

    2013-01-01

    Full Text Available The back propagation neural network (BPNN algorithm can be used as a supervised classification in the processing of remote sensing image classification. But its defects are obvious: falling into the local minimum value easily, slow convergence speed, and being difficult to determine intermediate hidden layer nodes. Genetic algorithm (GA has the advantages of global optimization and being not easy to fall into local minimum value, but it has the disadvantage of poor local searching capability. This paper uses GA to generate the initial structure of BPNN. Then, the stable, efficient, and fast BP classification network is gotten through making fine adjustments on the improved BP algorithm. Finally, we use the hybrid algorithm to execute classification on remote sensing image and compare it with the improved BP algorithm and traditional maximum likelihood classification (MLC algorithm. Results of experiments show that the hybrid algorithm outperforms improved BP algorithm and MLC algorithm.

  13. Wittgenstein's philosophy and a dimensional approach to the classification of mental disorders -- a preliminary scheme.

    Science.gov (United States)

    Mackinejad, Kioumars; Sharifi, Vandad

    2006-01-01

    In this paper the importance of Wittgenstein's philosophical ideas for the justification of a dimensional approach to the classification of mental disorders is discussed. Some of his basic concepts in his Philosophical Investigations, such as 'family resemblances', 'grammar' and 'language-game' and their relations to the concept of mental disorder are explored.

  14. Ensemble classification of colon biopsy images based on information rich hybrid features.

    Science.gov (United States)

    Rathore, Saima; Hussain, Mutawarra; Aksam Iftikhar, Muhammad; Jalil, Abdul

    2014-04-01

    In recent years, classification of colon biopsy images has become an active research area. Traditionally, colon cancer is diagnosed using microscopic analysis. However, the process is subjective and leads to considerable inter/intra observer variation. Therefore, reliable computer-aided colon cancer detection techniques are in high demand. In this paper, we propose a colon biopsy image classification system, called CBIC, which benefits from discriminatory capabilities of information rich hybrid feature spaces, and performance enhancement based on ensemble classification methodology. Normal and malignant colon biopsy images differ with each other in terms of the color distribution of different biological constituents. The colors of different constituents are sharp in normal images, whereas the colors diffuse with each other in malignant images. In order to exploit this variation, two feature types, namely color components based statistical moments (CCSM) and Haralick features have been proposed, which are color components based variants of their traditional counterparts. Moreover, in normal colon biopsy images, epithelial cells possess sharp and well-defined edges. Histogram of oriented gradients (HOG) based features have been employed to exploit this information. Different combinations of hybrid features have been constructed from HOG, CCSM, and Haralick features. The minimum Redundancy Maximum Relevance (mRMR) feature selection method has been employed to select meaningful features from individual and hybrid feature sets. Finally, an ensemble classifier based on majority voting has been proposed, which classifies colon biopsy images using the selected features. Linear, RBF, and sigmoid SVM have been employed as base classifiers. The proposed system has been tested on 174 colon biopsy images, and improved performance (=98.85%) has been observed compared to previously reported studies. Additionally, the use of mRMR method has been justified by comparing the

  15. A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression

    Science.gov (United States)

    2014-01-01

    Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting. PMID:25045738

  16. A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression

    Directory of Open Access Journals (Sweden)

    Chi-Jie Lu

    2014-01-01

    Full Text Available Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA with K-means clustering and support vector regression (SVR. The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting.

  17. A Hybrid Reduction Approach for Enhancing Cancer Classification of Microarray Data

    Directory of Open Access Journals (Sweden)

    Abeer M. Mahmoud

    2014-10-01

    Full Text Available This paper presents a novel hybrid machine learning (MLreduction approach to enhance cancer classification accuracy of microarray data based on two ML gene ranking techniques (T-test and Class Separability (CS. The proposed approach is integrated with two ML classifiers; K-nearest neighbor (KNN and support vector machine (SVM; for mining microarray gene expression profiles. Four public cancer microarray databases are used for evaluating the proposed approach and successfully accomplish the mining process. These are Lymphoma, Leukemia SRBCT, and Lung Cancer. The strategy to select genes only from the training samples and totally excluding the testing samples from the classifier building process is utilized for more accurate and validated results. Also, the computational experiments are illustrated in details and comprehensively presented with literature related results. The results showed that the proposed reduction approach reached promising results of the number of genes supplemented to the classifiers as well as the classification accuracy.

  18. A hybrid Evolutionary Functional Link Artificial Neural Network for Data mining and Classification

    Directory of Open Access Journals (Sweden)

    Faissal MILI

    2012-08-01

    Full Text Available This paper presents a specific structure of neural network as the functional link artificial neural network (FLANN. This technique has been employed for classification tasks of data mining. In fact, there are a few studies that used this tool for solving classification problems. In this present research, we propose a hybrid FLANN (HFLANN model, where the optimization process is performed using 3 known population based techniques such as genetic algorithms, particle swarm and differential evolution. This model will be empirically compared to FLANN based back-propagation algorithm and to others classifiers as decision tree, multilayer perceptron based back-propagation algorithm, radical basic function, support vector machine, and K-nearest Neighbor. Our results proved that the proposed model outperforms the other single model. (Abstract

  19. Comparison of hybrid schemes for the combination of shallow approximations in numerical simulations of the Antarctic Ice Sheet

    Science.gov (United States)

    Bernales, Jorge; Rogozhina, Irina; Greve, Ralf; Thomas, Maik

    2017-01-01

    The shallow ice approximation (SIA) is commonly used in ice-sheet models to simplify the force balance equations within the ice. However, the SIA cannot adequately reproduce the dynamics of the fast flowing ice streams usually found at the margins of ice sheets. To overcome this limitation, recent studies have introduced heuristic hybrid combinations of the SIA and the shelfy stream approximation. Here, we implement four different hybrid schemes into a model of the Antarctic Ice Sheet in order to compare their performance under present-day conditions. For each scheme, the model is calibrated using an iterative technique to infer the spatial variability in basal sliding parameters. Model results are validated against topographic and velocity data. Our analysis shows that the iterative technique compensates for the differences between the schemes, producing similar ice-sheet configurations through quantitatively different results of the sliding coefficient calibration. Despite this we observe a robust agreement in the reconstructed patterns of basal sliding parameters. We exchange the calibrated sliding parameter distributions between the schemes to demonstrate that the results of the model calibration cannot be straightforwardly transferred to models based on different approximations of ice dynamics. However, easily adaptable calibration techniques for the potential distribution of basal sliding coefficients can be implemented into ice models to overcome such incompatibility, as shown in this study.

  20. Review and comparison study of hybrid diesel/solar/hydro/fuel cell energy schemes for a rural ICT Telecenter

    Energy Technology Data Exchange (ETDEWEB)

    Abdullah, M.O.; Yung, V.C.; Anyi, M.; Othman, A.K.; Ab. Hamid, K.B. [Universiti Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Sarawak (Malaysia); Tarawe, J. [e-Bario ICT Telecenter, Bario, Sarawak (Malaysia)

    2010-02-15

    In this paper, the rural electrification study of an ICT Telecenter in particular reference to the Kelabit Highland of Sarawak is presented. The use of diesel generator and its associated environmental implications is first discussed. The cost-effectiveness of the present solar PV system and the solar/hydro schemes for rural electrification of the rural ICT are evaluated employing the HOMER simulation software, considering sustainability factors such as system efficiency, weather, fuel costs, operating and maintaining costs. Subsequently, simple novel Hybrid Energy Performance Equations and the associated Energy Performance Curves are derived and introduced, respectively, which provide a visualization model, simplifying hybrid system analysis. Results obtained in this study have shown that combined power schemes is more sustainable in terms of supplying electricity to the Telecenter compared to a stand-alone PV system due to prolong cloudy and dense haze periods. The hybrid systems can have efficiency range of {proportional_to}15%-75% compared to PV stand-alone of only {proportional_to}10%, indicating hybrid systems are more reliable and sustainable - in minimizing both energy losses and excess energy. (author)

  1. A Self-Consistent Scheme for Optical Response of large Hybrid Networks of Semiconductor Quantum Dots and Plasmonic Metal Nanoparticles

    Science.gov (United States)

    Barbiellini, Bernardo; Hayati, L.; Lane, C.; Bansil, A.; Mosallaei, H.

    We discuss a self-consistent scheme for treating the optical response of large, hybrid networks of semiconducting quantum dots (SQDs) and plasmonic metallic nanoparticles (MNPs). Our method is efficient and scalable and becomes exact in the limiting case of weakly interacting SQDs. The self-consistent equations obtained for the steady state are analogous to the Heisenberg equations of motion for the density matrix of a SQD placed in an effective electric field computed within the discrete dipole approximation (DDA). Illustrative applications of the theory to square and honeycomb SQD, MNP and hybrid SDQ/MNP lattices as well as SQD-MNP dimers are presented. Our results demonstrate that hybrid SQD-MNP lattices can provide flexible platforms for light manipulation with tunable resonant characteristics.

  2. Self-consistent scheme for optical response of large hybrid networks of semiconductor quantum dots and plasmonic metal nanoparticles

    Science.gov (United States)

    Hayati, L.; Lane, C.; Barbiellini, B.; Bansil, A.; Mosallaei, H.

    2016-06-01

    We discuss a self-consistent scheme for treating the optical response of large, hybrid networks of semiconducting quantum dots (SQDs) and plasmonic metallic nanoparticles (MNPs). Our method is efficient and scalable and becomes exact in the limiting case of weakly interacting SQDs. The self-consistent equations obtained for the steady state are analogous to the von Neumann equations of motion for the density matrix of a SQD placed in an effective electric field computed within the discrete dipole approximation. Illustrative applications of the theory to square and honeycomb SQD, MNP, and hybrid SDQ-MNP lattices as well as SQD-MNP dimers are presented. Our results demonstrate that hybrid SQD-MNP lattices can provide flexible platforms for light manipulation with tunable resonant characteristics.

  3. Hybrid fNIRS-EEG based classification of auditory and visual perception processes

    Directory of Open Access Journals (Sweden)

    Felix ePutze

    2014-11-01

    Full Text Available For multimodal Human-Computer Interaction (HCI, it is very useful to identify the modalities on which the user is currently processing information. This would enable a system to select complementary output modalities to reduce the user's workload. In this paper, we develop a hybrid Brain-Computer Interface (BCI which uses Electroencephalography (EEG and functional Near Infrared Spectroscopy (fNIRS to discriminate and detect visual and auditory stimulus processing. We describe the experimental setup we used for collection of our data corpus with 12 subjects. We present cross validation evaluation results for different classification conditions. We show that our subject-dependent systems achieved a classification accuracy of 97.8% for discriminating visual and auditory perception processes from each other and a classification accuracy of up to 94.8% for detecting modality-specific processes independently of other cognitive activity. The same classification conditions could also be discriminated in a subject-independent fashion with accuracy of up to 94.6% and 86.7%, respectively. We also look at the contributions of the two signal types and show that the fusion of classifiers using different features significantly increases accuracy.

  4. Landmine detection and classification with complex-valued hybrid neural network using scattering parameters dataset.

    Science.gov (United States)

    Yang, Chih-Chung; Bose, N K

    2005-05-01

    Neural networks have been applied to landmine detection from data generated by different kinds of sensors. Real-valued neural networks have been used for detecting landmines from scattering parameters measured by ground penetrating radar (GPR) after disregarding phase information. This paper presents results using complex-valued neural networks, capable of phase-sensitive detection followed by classification. A two-layer hybrid neural network structure incorporating both supervised and unsupervised learning is proposed to detect and then classify the types of landmines. Tests are also reported on a benchmark data.

  5. DCT domain feature extraction scheme based on motor unit action potential of EMG signal for neuromuscular disease classification.

    Science.gov (United States)

    Doulah, Abul Barkat Mollah Sayeed Ud; Fattah, Shaikh Anowarul; Zhu, Wei-Ping; Ahmad, M Omair

    2014-01-01

    A feature extraction scheme based on discrete cosine transform (DCT) of electromyography (EMG) signals is proposed for the classification of normal event and a neuromuscular disease, namely the amyotrophic lateral sclerosis. Instead of employing DCT directly on EMG data, it is employed on the motor unit action potentials (MUAPs) extracted from the EMG signal via a template matching-based decomposition technique. Unlike conventional MUAP-based methods, only one MUAP with maximum dynamic range is selected for DCT-based feature extraction. Magnitude and frequency values of a few high-energy DCT coefficients corresponding to the selected MUAP are used as the desired feature which not only reduces computational burden, but also offers better feature quality with high within-class compactness and between-class separation. For the purpose of classification, the K-nearest neighbourhood classifier is employed. Extensive analysis is performed on clinical EMG database and it is found that the proposed method provides a very satisfactory performance in terms of specificity, sensitivity and overall classification accuracy.

  6. Partial imputation to improve predictive modelling in insurance risk classification using a hybrid positive selection algorithm and correlation-based feature selection

    CSIR Research Space (South Africa)

    Duma, M

    2013-09-01

    Full Text Available We propose a hybrid missing data imputation technique using positive selection and correlation-based feature selection for insurance data. The hybrid is used to help supervised learning methods improve their classification accuracy and resilience...

  7. A classification scheme of Amino Acids in the Genetic Code by Group Theory

    CERN Document Server

    Sachse, Sebastian

    2012-01-01

    We derive the amino acid assignment to one codon representation (typical 64-dimensional irreducible representation) of the basic classical Lie superalgebra osp(5|2) from biochemical arguments. We motivate the approach of mathematical symmetries to the classification of the building constituents of the biosphere by analogy of its success in particle physics and chemistry. The model enables to calculate polarity and molecular volume of amino acids to a good approximation.

  8. WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python

    OpenAIRE

    Christopher Beckham; Mark Hall; Eibe Frank

    2016-01-01

    WekaPyScript is a package for the machine learning software WEKA that allows learning algorithms and preprocessing methods for classification and regression to be written in Python, as opposed to WEKA’s implementation language, Java. This opens up WEKA to its machine learning and scientific computing ecosystem. Furthermore, due to Python’s minimalist syntax, learning algorithms and preprocessing methods can be prototyped easily and utilised from within WEKA. WekaPyScript works by running a lo...

  9. A sixth order hybrid finite difference scheme based on the minimized dispersion and controllable dissipation technique

    Science.gov (United States)

    Sun, Zhen-sheng; Luo, Lei; Ren, Yu-xin; Zhang, Shi-ying

    2014-08-01

    The dispersion and dissipation properties of a scheme are of great importance for the simulation of flow fields which involve a broad range of length scales. In order to improve the spectral properties of the finite difference scheme, the authors have previously proposed the idea of optimizing the dispersion and dissipation properties separately and a fourth order scheme based on the minimized dispersion and controllable dissipation (MDCD) technique is thus constructed [29]. In the present paper, we further investigate this technique and extend it to a sixth order finite difference scheme to solve the Euler and Navier-Stokes equations. The dispersion properties of the scheme is firstly optimized by minimizing an elaborately designed integrated error function. Then the dispersion-dissipation condition which is newly derived by Hu and Adams [30] is introduced to supply sufficient dissipation to damp the unresolved wavenumbers. Furthermore, the optimized scheme is blended with an optimized Weighted Essentially Non-Oscillation (WENO) scheme to make it possible for the discontinuity-capturing. In this process, the approximation-dispersion-relation (ADR) approach is employed to optimize the spectral properties of the nonlinear scheme to yield the true wave propagation behavior of the finite difference scheme. Several benchmark test problems, which include broadband fluctuations and strong shock waves, are solved to validate the high-resolution, the good discontinuity-capturing capability and the high-efficiency of the proposed scheme.

  10. Classification Scheme for Random Longitudinal Road Unevenness Considering Road Waviness and Vehicle Response

    Directory of Open Access Journals (Sweden)

    Oldřich Kropáč

    2009-01-01

    Full Text Available A novel approach to the road unevenness classification based on the power spectral density with consideration of vehicle vibration response and broad interval of road waviness (road elevation PSD slope is presented. This approach enables transformation of two basic parameters of road profile elevation PSD (unevenness index, C, and waviness, w into a single-number indicator Cw when using a correction factor Kw accounting for w. For the road classification proposal two planar vehicle models (passenger car and truck, ten responses (reflecting ride comfort, dynamic load of road and cargo, ride safety and three different vehicle velocities have been considered. The minimum of ten estimated vibration response ranges sum for a broad waviness interval typical for real road sections (w = 1.5 to 3.5 has been used for the correction factor estimation. The introduced unevenness indicator, Cw, reflects the vehicle vibration response and seems to be a suitable alternative to the other currently used single-number indicators or as an extension of the road classification according to the ISO 8608: 1995, which is based on constant waviness value, w = 2.

  11. Intelligent Video Object Classification Scheme using Offline Feature Extraction and Machine Learning based Approach

    Directory of Open Access Journals (Sweden)

    Chandra Mani Sharma

    2012-01-01

    Full Text Available Classification of objects in video stream is important because of its application in many emerging areas such as visual surveillance, content based video retrieval and indexing etc. The task is far more challenging because the video data is of heavy and highly variable nature. The processing of video data is required to be in real-time. This paper presents a multiclass object classification technique using machine learning approach. Haar-like features are used for training the classifier. The feature calculation is performed using Integral Image representation and we train the classifier offline using a Stage-wise Additive Modeling using a Multiclass Exponential loss function (SAMME. The validity of the method has been verified from the implementation of a real-time human-car detector. Experimental results show that the proposed method can accurately classify objects, in video, into their respective classes. The proposed object classifier works well in outdoor environment in presence of moderate lighting conditions and variable scene background. The proposed technique is compared, with other object classification techniques, based on various performance parameters.

  12. Parallel Implementation of Morphological Profile Based Spectral-Spatial Classification Scheme for Hyperspectral Imagery

    Science.gov (United States)

    Kumar, B.; Dikshit, O.

    2016-06-01

    Extended morphological profile (EMP) is a good technique for extracting spectral-spatial information from the images but large size of hyperspectral images is an important concern for creating EMPs. However, with the availability of modern multi-core processors and commodity parallel processing systems like graphics processing units (GPUs) at desktop level, parallel computing provides a viable option to significantly accelerate execution of such computations. In this paper, parallel implementation of an EMP based spectralspatial classification method for hyperspectral imagery is presented. The parallel implementation is done both on multi-core CPU and GPU. The impact of parallelization on speed up and classification accuracy is analyzed. For GPU, the implementation is done in compute unified device architecture (CUDA) C. The experiments are carried out on two well-known hyperspectral images. It is observed from the experimental results that GPU implementation provides a speed up of about 7 times, while parallel implementation on multi-core CPU resulted in speed up of about 3 times. It is also observed that parallel implementation has no adverse impact on the classification accuracy.

  13. Classifying Obstructive and Nonobstructive Code Clones of Type I Using Simplified Classification Scheme: A Case Study

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    Miroslaw Staron

    2015-01-01

    Full Text Available Code cloning is a part of many commercial and open source development products. Multiple methods for detecting code clones have been developed and finding the clones is often used in modern quality assurance tools in industry. There is no consensus whether the detected clones are negative for the product and therefore the detected clones are often left unmanaged in the product code base. In this paper we investigate how obstructive code clones of Type I (duplicated exact code fragments are in large software systems from the perspective of the quality of the product after the release. We conduct a case study at Ericsson and three of its large products, which handle mobile data traffic. We show how to use automated analogy-based classification to decrease the classification effort required to determine whether a clone pair should be refactored or remain untouched. The automated method allows classifying 96% of Type I clones (both algorithms and data declarations leaving the remaining 4% for the manual classification. The results show that cloning is common in the studied commercial software, but that only 1% of these clones are potentially obstructive and can jeopardize the quality of the product if left unmanaged.

  14. A new classification scheme for deep geothermal systems based on geologic controls

    Science.gov (United States)

    Moeck, I.

    2012-04-01

    A key element in the characterization, assessment and development of geothermal energy systems is the resource classification. Throughout the past 30 years many classifications and definitions were published mainly based on temperature and thermodynamic properties. In the past classification systems, temperature has been the essential measure of the quality of the resource and geothermal systems have been divided into three different temperature (or enthalpy) classes: low-temperature, moderate-temperature and high-temperature. There are, however, no uniform temperature ranges for these classes. It is still a key requirement of a geothermal classification that resource assessment provides logical and consistent frameworks simplified enough to communicate important aspects of geothermal energy potential to both non-experts and general public. One possible solution may be to avoid classifying geothermal resources by temperature and simply state the range of temperatures at the individual site. Due to technological development, in particular in EGS (Enhanced Geothermal Systems or Engineered Geothermal Systems; both terms are considered synonymously in this thesis) technology, currently there are more geothermal systems potentially economic than 30 years ago. An alternative possibility is to classify geothermal energy systems by their geologic setting. Understanding and characterizing the geologic controls on geothermal systems has been an ongoing focus on different scales from plate tectonics to local tectonics/structural geology. In fact, the geologic setting has a fundamental influence on the potential temperature, on the fluid composition, the reservoir characteristics and whether the system is a predominantly convective or conductive system. The key element in this new classification for geothermal systems is the recognition that a geothermal system is part of a geological system. The structural geological and plate tectonic setting has a fundamental influence on

  15. A TVD-WAF-based hybrid finite volume and finite difference scheme for nonlinearly dispersive wave equations

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    Jing Yin

    2015-07-01

    Full Text Available A total variation diminishing-weighted average flux (TVD-WAF-based hybrid numerical scheme for the enhanced version of nonlinearly dispersive Boussinesq-type equations was developed. The one-dimensional governing equations were rewritten in the conservative form and then discretized on a uniform grid. The finite volume method was used to discretize the flux term while the remaining terms were approximated with the finite difference method. The second-order TVD-WAF method was employed in conjunction with the Harten-Lax-van Leer (HLL Riemann solver to calculate the numerical flux, and the variables at the cell interface for the local Riemann problem were reconstructed via the fourth-order monotone upstream-centered scheme for conservation laws (MUSCL. The time marching scheme based on the third-order TVD Runge-Kutta method was used to obtain numerical solutions. The model was validated through a series of numerical tests, in which wave breaking and a moving shoreline were treated. The good agreement between the computed results, documented analytical solutions, and experimental data demonstrates the correct discretization of the governing equations and high accuracy of the proposed scheme, and also conforms the advantages of the proposed shock-capturing scheme for the enhanced version of the Boussinesq model, including the convenience in the treatment of wave breaking and moving shorelines and without the need for a numerical filter.

  16. Hyperspectral hybrid method classification for detecting altered mucosa of the human larynx

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    Martin Ron

    2012-06-01

    Full Text Available Abstract Background In the field of earth observation, hyperspectral detector systems allow precise target detections of surface components from remote sensing platforms. This enables specific land covers to be identified without the need to physically travel to the areas examined. In the medical field, efforts are underway to develop optical technologies that detect altering tissue surfaces without the necessity to perform an excisional biopsy. With the establishment of expedient classification procedures, hyperspectral imaging may provide a non-invasive diagnostic method that allows determination of pathological tissue with high reliability. In this study, we examined the performance of a hyperspectral hybrid method classification for the automatic detection of altered mucosa of the human larynx. Materials and methods Hyperspectral Imaging was performed in vivo and 30 bands from 390 to 680 nm for 5 cases of laryngeal disorders (2x hemorrhagic polyp, 3x leukoplakia were obtained. Image stacks were processed with unsupervised clustering (linear spectral unmixing, spectral signatures were extracted from unlabeled cluster maps and subsequently applied as end-members for supervised classification (spectral angle mapper of further medical cases with identical diagnosis. Results Linear spectral unmixing clearly highlighted altered mucosa as single spectral clusters in all cases. Matching classes were identified, and extracted spectral signatures could readily be applied for supervised classifications. Automatic target detection performed well, as the considered classes showed notable correspondence with pathological tissue locations. Conclusions Using hyperspectral classification procedures derived from remote sensing applications for diagnostic purposes can create concrete benefits for the medical field. The approach shows that it would be rewarding to collect spectral signatures from histologically different lesions of laryngeal disorders in

  17. Clinical presentation and outcome prediction of clinical, serological, and histopathological classification schemes in ANCA-associated vasculitis with renal involvement.

    Science.gov (United States)

    Córdova-Sánchez, Bertha M; Mejía-Vilet, Juan M; Morales-Buenrostro, Luis E; Loyola-Rodríguez, Georgina; Uribe-Uribe, Norma O; Correa-Rotter, Ricardo

    2016-07-01

    Several classification schemes have been developed for anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), with actual debate focusing on their clinical and prognostic performance. Sixty-two patients with renal biopsy-proven AAV from a single center in Mexico City diagnosed between 2004 and 2013 were analyzed and classified under clinical (granulomatosis with polyangiitis [GPA], microscopic polyangiitis [MPA], renal limited vasculitis [RLV]), serological (proteinase 3 anti-neutrophil cytoplasmic antibodies [PR3-ANCA], myeloperoxidase anti-neutrophil cytoplasmic antibodies [MPO-ANCA], ANCA negative), and histopathological (focal, crescenteric, mixed-type, sclerosing) categories. Clinical presentation parameters were compared at baseline between classification groups, and the predictive value of different classification categories for disease and renal remission, relapse, renal, and patient survival was analyzed. Serological classification predicted relapse rate (PR3-ANCA hazard ratio for relapse 2.93, 1.20-7.17, p = 0.019). There were no differences in disease or renal remission, renal, or patient survival between clinical and serological categories. Histopathological classification predicted response to therapy, with a poorer renal remission rate for sclerosing group and those with less than 25 % normal glomeruli; in addition, it adequately delimited 24-month glomerular filtration rate (eGFR) evolution, but it did not predict renal nor patient survival. On multivariate models, renal replacement therapy (RRT) requirement (HR 8.07, CI 1.75-37.4, p = 0.008) and proteinuria (HR 1.49, CI 1.03-2.14, p = 0.034) at presentation predicted renal survival, while age (HR 1.10, CI 1.01-1.21, p = 0.041) and infective events during the induction phase (HR 4.72, 1.01-22.1, p = 0.049) negatively influenced patient survival. At present, ANCA-based serological classification may predict AAV relapses, but neither clinical nor serological

  18. A Hybrid Optimization Framework with POD-based Order Reduction and Design-Space Evolution Scheme

    Science.gov (United States)

    Ghoman, Satyajit S.

    The main objective of this research is to develop an innovative multi-fidelity multi-disciplinary design, analysis and optimization suite that integrates certain solution generation codes and newly developed innovative tools to improve the overall optimization process. The research performed herein is divided into two parts: (1) the development of an MDAO framework by integration of variable fidelity physics-based computational codes, and (2) enhancements to such a framework by incorporating innovative features extending its robustness. The first part of this dissertation describes the development of a conceptual Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment (M3 DOE), in context of aircraft wing optimization. M 3 DOE provides the user a capability to optimize configurations with a choice of (i) the level of fidelity desired, (ii) the use of a single-step or multi-step optimization strategy, and (iii) combination of a series of structural and aerodynamic analyses. The modularity of M3 DOE allows it to be a part of other inclusive optimization frameworks. The M 3 DOE is demonstrated within the context of shape and sizing optimization of the wing of a Generic Business Jet aircraft. Two different optimization objectives, viz. dry weight minimization, and cruise range maximization are studied by conducting one low-fidelity and two high-fidelity optimization runs to demonstrate the application scope of M3 DOE. The second part of this dissertation describes the development of an innovative hybrid optimization framework that extends the robustness of M 3 DOE by employing a proper orthogonal decomposition-based design-space order reduction scheme combined with the evolutionary algorithm technique. The POD method of extracting dominant modes from an ensemble of candidate configurations is used for the design-space order reduction. The snapshot of candidate population is updated iteratively using evolutionary algorithm technique of

  19. A hybrid surface layer parameterization scheme for the two-way fully coupled atmosphere-ocean wave system WEW

    Science.gov (United States)

    Katsafados, Petros; Papadopoulos, Anastasios; Varlas, George; Korres, Gerasimos

    2015-04-01

    The two-way fully coupled atmosphere-ocean wave system WEW has been recently developed in order to study the factors that contribute to the air-sea interaction processes and feedbacks. The coupled system consists of two components: the atmospheric component which is based on the Workstation Eta non-hydrostatic limited area model and the ocean-wave component which is based on the fourth generation OpenMP (OMP) version of the WAM model. The WEW has been already evaluated in a number of high-impact weather and sea state events where generally a more realistic representation of the momentum exchanges in the ocean wind-wave system has been shown However, the new developed wind-wave parameterization scheme reduces both the near surface wind speed and the significant wave height as a response to the increased aerodynamic drag considered by the atmospheric model over rough sea surfaces. Such behavior is mainly attributed to the surface layer parameterization scheme of the atmospheric component which is based on the Mellor-Yamada-Janjic (MYJ) scheme. It is noted that this scheme has been adjusted to support independent atmospheric simulations. Therefore, we proceed to develop a new hybrid surface layer parameterization based on the MYJ and the Janssen schemes that operate in the atmospheric and ocean wave components of the WEW, respectively. In this case the roughness length depends on the wave age instead of the Charnock parameter following the formulation proposed by Vickers and Mahrt. The spatial variability of the wave age is estimated at each ocean wave component time step and it is directly provided to the MYJ scheme. The parameterization of the viscous sublayer and the universal functions for the estimation of the near surface wind speed have been also revised accordingly. In this study, a test version of the new hybrid scheme of WEW has been statistically evaluated against a number of buoys and satellite retrievals over the Mediterranean Sea in a case study of high

  20. Development of a classification scheme for disease-related enzyme information

    Directory of Open Access Journals (Sweden)

    Söhngen Carola

    2011-08-01

    Full Text Available Abstract Background BRENDA (BRaunschweig ENzyme DAtabase, http://www.brenda-enzymes.org is a major resource for enzyme related information. First and foremost, it provides data which are manually curated from the primary literature. DRENDA (Disease RElated ENzyme information DAtabase complements BRENDA with a focus on the automatic search and categorization of enzyme and disease related information from title and abstracts of primary publications. In a two-step procedure DRENDA makes use of text mining and machine learning methods. Results Currently enzyme and disease related references are biannually updated as part of the standard BRENDA update. 910,897 relations of EC-numbers and diseases were extracted from titles or abstracts and are included in the second release in 2010. The enzyme and disease entity recognition has been successfully enhanced by a further relation classification via machine learning. The classification step has been evaluated by a 5-fold cross validation and achieves an F1 score between 0.802 ± 0.032 and 0.738 ± 0.033 depending on the categories and pre-processing procedures. In the eventual DRENDA content every category reaches a classification specificity of at least 96.7% and a precision that ranges from 86-98% in the highest confidence level, and 64-83% for the smallest confidence level associated with higher recall. Conclusions The DRENDA processing chain analyses PubMed, locates references with disease-related information on enzymes and categorises their focus according to the categories causal interaction, therapeutic application, diagnostic usage and ongoing research. The categorisation gives an impression on the focus of the located references. Thus, the relation categorisation can facilitate orientation within the rapidly growing number of references with impact on diseases and enzymes. The DRENDA information is available as additional information in BRENDA.

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

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    Charles R. Lane

    2014-12-01

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

  2. The Hybrid of Classification Tree and Extreme Learning Machine for Permeability Prediction in Oil Reservoir

    KAUST Repository

    Prasetyo Utomo, Chandra

    2011-06-01

    Permeability is an important parameter connected with oil reservoir. Predicting the permeability could save millions of dollars. Unfortunately, petroleum engineers have faced numerous challenges arriving at cost-efficient predictions. Much work has been carried out to solve this problem. The main challenge is to handle the high range of permeability in each reservoir. For about a hundred year, mathematicians and engineers have tried to deliver best prediction models. However, none of them have produced satisfying results. In the last two decades, artificial intelligence models have been used. The current best prediction model in permeability prediction is extreme learning machine (ELM). It produces fairly good results but a clear explanation of the model is hard to come by because it is so complex. The aim of this research is to propose a way out of this complexity through the design of a hybrid intelligent model. In this proposal, the system combines classification and regression models to predict the permeability value. These are based on the well logs data. In order to handle the high range of the permeability value, a classification tree is utilized. A benefit of this innovation is that the tree represents knowledge in a clear and succinct fashion and thereby avoids the complexity of all previous models. Finally, it is important to note that the ELM is used as a final predictor. Results demonstrate that this proposed hybrid model performs better when compared with support vector machines (SVM) and ELM in term of correlation coefficient. Moreover, the classification tree model potentially leads to better communication among petroleum engineers concerning this important process and has wider implications for oil reservoir management efficiency.

  3. Si-29 NMR spectroscopy of naturally-shocked quartz from Meteor Crater, Arizona: Correlation to Kieffer's classification scheme

    Science.gov (United States)

    Boslough, M. B.; Cygan, R. T.; Kirkpatrick, R. J.

    1993-01-01

    We have applied solid state Si-29 nuclear magnetic resonance (NMR) spectroscopy to five naturally-shocked Coconino Sandstone samples from Meteor Crater, Arizona, with the goal of examining possible correlations between NMR spectral characteristics and shock level. This work follows our observation of a strong correlation between the width of a Si-29 resonance and peak shock pressure for experimentally shocked quartz powders. The peak width increase is due to the shock-induced formation of amorphous silica, which increases as a function of shock pressure over the range that we studied (7.5 to 22 GPa). The Coconino Sandstone spectra are in excellent agreement with the classification scheme of Kieffer in terms of presence and approximate abundances of quartz, coesite, stishovite, and glass. We also observe a new resonance in two moderately shocked samples that we have tentatively identified with silicon in tetrahedra with one hydroxyl group in a densified form of amorphous silica.

  4. Per pixel uncertainty modelling and its spatial representation on land cover maps obtained by hybrid classification.

    Science.gov (United States)

    Pons, Xavier; Sevillano, Eva; Moré, Gerard; Serra, Pere; Cornford, Dan; Ninyerola, Miquel

    2013-04-01

    The usage of remote sensing imagery combined with statistical classifiers to obtain categorical cartography is now common practice. As in many other areas of geographic information quality assessment, knowing the accuracy of these maps is crucial, and the spatialization of quality information is becoming ever more important for a large range of applications. Whereas some classifiers (e.g., maximum likelihood, linear discriminant analysis, naive Bayes, etc) permit the estimation and spatial representation of the uncertainty through a pixel level probabilistic estimator (and, from that, to compute a global accuracy estimator for the whole map), for other methods such a direct estimator does not exist. Regardless of the classification method applied, ground truth data is almost always available (to train the classifier and/or to compute the global accuracy and, usually, a confusion matrix). Our research is devoted to the development of a protocol to spatialize the error on a general framework based on the classifier parameters, and some ground truth reference data. In the methodological experiment presented here we provide an insight into uncertainty modelling for a hybrid classifier that combines unsupervised and supervised stages (implemented in the MiraMon GIS). In this work we describe what we believe is the first attempt to characterise pixel level uncertainty in a two stage classification process. We describe the model setup, show the preliminary results and identify future work that will be undertaken. The study area is a Landsat full frame located at the North-eastern region of the Iberian Peninsula. The six non-thermal bands + NDVI of a multi-temporal set of six geometrically and radiometrically corrected Landsat-5 images (between 2005 and 2007) were submitted to a hybrid classification process, together with some ancillary data (climate, slopes, etc). Training areas were extracted from the Land Cover Map of Catalonia (MCSC), a 0.5 m resolution map created by

  5. A Hybrid Multiobjective Differential Evolution Algorithm and Its Application to the Optimization of Grinding and Classification

    Directory of Open Access Journals (Sweden)

    Yalin Wang

    2013-01-01

    Full Text Available The grinding-classification is the prerequisite process for full recovery of the nonrenewable minerals with both production quality and quantity objectives concerned. Its natural formulation is a constrained multiobjective optimization problem of complex expression since the process is composed of one grinding machine and two classification machines. In this paper, a hybrid differential evolution (DE algorithm with multi-population is proposed. Some infeasible solutions with better performance are allowed to be saved, and they participate randomly in the evolution. In order to exploit the meaningful infeasible solutions, a functionally partitioned multi-population mechanism is designed to find an optimal solution from all possible directions. Meanwhile, a simplex method for local search is inserted into the evolution process to enhance the searching strategy in the optimization process. Simulation results from the test of some benchmark problems indicate that the proposed algorithm tends to converge quickly and effectively to the Pareto frontier with better distribution. Finally, the proposed algorithm is applied to solve a multiobjective optimization model of a grinding and classification process. Based on the technique for order performance by similarity to ideal solution (TOPSIS, the satisfactory solution is obtained by using a decision-making method for multiple attributes.

  6. A microarray gene expression data classification using hybrid back propagation neural network

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    Vimaladevi M.

    2014-01-01

    Full Text Available Classification of cancer establishes appropriate treatment and helps to decide the diagnosis. Cancer expands progressively from an alteration in a cell's genetic structure. This change (mutation results in cells with uncontrolled growth patterns. In cancer classification, the approach, Back propagation is sufficient and also it is a universal technique of training artificial neural networks. It is also called supervised learning method. It needs many dataset for input and output for making up the training set. The back propagation method may execute the function of collaborate multiple parties. In existing method, collaborative learning is limited and it considers only two parties. The proposed collaborative function can perform well and problems can be solved by utilizing the power of cloud computing. This technical note applies hybrid models of Back Propagation Neural networks (BPN and fast Genetic Algorithms (GA to estimate the feature selection in gene expression data. The proposed research work examines many feature selection algorithms which are “fragile”; that is, the superiority of their results varies broadly over data sets. By this research, it is suggested that this is due to higherorder interactions between features causing restricted minima in search space in which the algorithm becomes attentive. GAs may escape from such minima by chance, because works are highly stochastic. A neural net classifier with a genetic algorithm, using the GA to select features for classification by the neural net and incorporating the net as part of the objective function of the GA.

  7. New Hybrid Iterative Schemes for an Infinite Family of Nonexpansive Mappings in Hilbert Spaces

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    Guo Baohua

    2010-01-01

    Full Text Available We propose some new iterative schemes for finding common fixed point of an infinite family of nonexpansive mappings in a Hilbert space and prove the strong convergence of the proposed schemes. Our results extend and improve ones of Nakajo and Takahashi (2003.

  8. Three hybridization models based on local search scheme for job shop scheduling problem

    Science.gov (United States)

    Balbi Fraga, Tatiana

    2015-05-01

    This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

  9. A new stylolite classification scheme to estimate compaction and local permeability variations

    Science.gov (United States)

    Koehn, D.; Rood, M. P.; Beaudoin, N.; Chung, P.; Bons, P. D.; Gomez-Rivas, E.

    2016-12-01

    We modeled the geometrical roughening of bedding-parallel, mainly layer-dominated stylolites in order to understand their structural evolution, to present an advanced classification of stylolite shapes and to relate this classification to chemical compaction and permeability variations at stylolites. Stylolites are rough dissolution seams that develop in sedimentary basins during chemical compaction. In the Zechstein 2 carbonate units, an important lean gas reservoir in the southern Permian Zechstein basin in Germany, stylolites influence local fluid flow, mineral replacement reactions and hence the permeability of the reservoir. Our simulations demonstrate that layer-dominated stylolites can grow in three distinct stages: an initial slow nucleation phase, a fast layer-pinning phase and a final freezing phase if the layer is completely dissolved during growth. Dissolution of the pinning layer and thus destruction of the stylolite's compaction tracking capabilities is a function of the background noise in the rock and the dissolution rate of the layer itself. Low background noise needs a slower dissolving layer for pinning to be successful but produces flatter teeth than higher background noise. We present an advanced classification based on our simulations and separate stylolites into four classes: (1) rectangular layer type, (2) seismogram pinning type, (3) suture/sharp peak type and (4) simple wave-like type. Rectangular layer type stylolites are the most appropriate for chemical compaction estimates because they grow linearly and record most of the actual compaction (up to 40 mm in the Zechstein example). Seismogram pinning type stylolites also provide good tracking capabilities, with the largest teeth tracking most of the compaction. Suture/sharp peak type stylolites grow in a non-linear fashion and thus do not record most of the actual compaction. However, when a non-linear growth law is used, the compaction estimates are similar to those making use of the

  10. Developing Land Surface Type Map with Biome Classification Scheme Using Suomi NPP/JPSS VIIRS Data

    Science.gov (United States)

    Zhang, Rui; Huang, Chengquan; Zhan, Xiwu; Jin, Huiran

    2016-08-01

    Accurate representation of actual terrestrial surface types at regional to global scales is an important element for a wide range of applications, such as land surface parameterization, modeling of biogeochemical cycles, and carbon cycle studies. In this study, in order to meet the requirement of the retrieval of global leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by the vegetation (fPAR) and other studies, a global map generated from Suomi National Polar- orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) surface reflectance data in six major biome classes based on their canopy structures, which include: Grass/Cereal Crops, Shrubs, Broadleaf Crops, Savannas, Broadleaf Forests, and Needleleaf Forests, was created. The primary biome classes were converted from an International Geosphere-Biosphere Program (IGBP) legend global surface type data that was created in previous study, and the separation of two crop types are based on a secondary classification.

  11. WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python

    Directory of Open Access Journals (Sweden)

    Christopher Beckham

    2016-08-01

    Full Text Available WekaPyScript is a package for the machine learning software WEKA that allows learning algorithms and preprocessing methods for classification and regression to be written in Python, as opposed to WEKA’s implementation language, Java. This opens up WEKA to its machine learning and scientific computing ecosystem. Furthermore, due to Python’s minimalist syntax, learning algorithms and preprocessing methods can be prototyped easily and utilised from within WEKA. WekaPyScript works by running a local Python server using the host’s installation of Python; as a result, any libraries installed in the host installation can be leveraged when writing a script for WekaPyScript. Three example scripts (two learning algorithms and one preprocessing method are presented.

  12. [Evaluation of interventions intended to reduce psychosocial work stress. Proposal for a classification scheme].

    Science.gov (United States)

    Neuner, R; Bauer, J; Nübling, M; Rose, U; Krause, A

    2011-08-01

    Evidence for the effectiveness of measures aiming to reduce psychosocial work stress is sporadic. This is contradictory to the requirement identified by the German Social Security Code (SGB VII) that interventions constitute the most important method of maintaining and improving employees' health. Reasons for this can be seen in the complexity of the subject and methodological issues concerning scientific standards. In addition, agreed quality standards are nonexistent for the evaluation of intervention measures. For this reason, a synopsis of existing audit and evaluation schemes was performed, thus, resulting in refined and adapted quality standards for intervention measures aiming to reduce psychosocial work stress. The quality criteria presented in this paper comprise aims, effectiveness, and facilitators, each being composed of several indicators. The criteria are designed as quality indicators which translate the outcome of an evaluation into quality figures. The process is transparent and offers a rational basis for communication, planning, and decision-making in health promotion.

  13. A New Approach to Develop Computer-Aided Diagnosis Scheme of Breast Mass Classification Using Deep Learning Technology.

    Science.gov (United States)

    Qiu, Yuchen; Yan, Shiju; Gundreddy, Rohith Reddy; Wang, Yunzhi; Cheng, Samuel; Liu, Hong; Zheng, Bin

    2017-04-18

    To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses. An image dataset involving 560 regions of interest (ROIs) extracted from digital mammograms was used. After down-sampling each ROI from 512×512 to 64×64 pixel size, we applied an 8 layer deep learning network that involves 3 pairs of convolution-max-pooling layers for automatic feature extraction and a multiple layer perceptron (MLP) classifier for feature categorization to process ROIs. The 3 pairs of convolution layers contain 20, 10, and 5 feature maps, respectively. Each convolution layer is connected with a max-pooling layer to improve the feature robustness. The output of the sixth layer is fully connected with a MLP classifier, which is composed of one hidden layer and one logistic regression layer. The network then generates a classification score to predict the likelihood of ROI depicting a malignant mass. A four-fold cross validation method was applied to train and test this deep learning network. The results revealed that this CAD scheme yields an area under the receiver operation characteristic curve (AUC) of 0.696±0.044, 0.802±0.037, 0.836±0.036, and 0.822±0.035 for fold 1 to 4 testing datasets, respectively. The overall AUC of the entire dataset is 0.790±0.019. This study demonstrates the feasibility of applying a deep learning based CAD scheme to classify between malignant and benign breast masses without a lesion segmentation, image feature computation and selection process.

  14. Critical rotation of general-relativistic polytropic models simulating neutron stars: a post-Newtonian hybrid approximative scheme

    CERN Document Server

    Geroyannis, Vassilis S

    2014-01-01

    We develop a "hybrid approximative scheme" in the framework of the post-Newtonian approximation for computing general-relativistic polytropic models simulating neutron stars in critical rigid rotation. We treat the differential equations governing such a model as a "complex initial value problem", and we solve it by using the so-called "complex-plane strategy". We incorporate into the computations the complete solution for the relativistic effects, this issue representing a significant improvement with regard to the classical post-Newtonian approximation, as verified by extended comparisons of the numerical results.

  15. A scheme for detecting the atom-field coupling constant in the Dicke superradiation regime using hybrid cavity optomechanical system.

    Science.gov (United States)

    Wang, Yueming; Liu, Bin; Lian, Jinling; Liang, Jiuqing

    2012-04-23

    We proposed a scheme for detecting the atom-field coupling constant in the Dicke superradiation regime based on a hybrid cavity optomechanical system assisted by an atomic gas. The critical behavior of the Dicke model was obtained analytically using the spin-coherent-state representation. Without regard to the dynamics of cavity field an analytical formula of one-to-one correspondence between movable mirror's steady position and atom-field coupling constant for a given number of atoms is obtained. Thus the atom-field coupling constant can be probed by measuring the movable mirror's steady position, which is another effect of the cavity optomechanics. © 2012 Optical Society of America

  16. Multi-agent system-based event-triggered hybrid control scheme for energy internet

    DEFF Research Database (Denmark)

    Dou, Chunxia; Yue, Dong; Han, Qing Long

    2017-01-01

    This paper is concerned with an event-triggered hybrid control for the energy Internet based on a multi-agent system approach with which renewable energy resources can be fully utilized to meet load demand with high security and well dynamical quality. In the design of control, a multi-agent system...... framework is first constructed. Then, to describe fully the hybrid behaviors of all distributed energy resources and logical relationships between them, a differential hybrid Petri-net model is established, which is an original work. The most important contributions based on this model propose four types...

  17. A hybrid numerical prediction scheme for solar radiation estimation in un-gauged catchments.

    Science.gov (United States)

    Shamim, M. A.; Bray, M.; Ishak, A. M.; Remesan, R.; Han, D.

    2009-09-01

    The importance of solar radiation on earth's surface is depicted in its wide range of applications in the fields of meteorology, agricultural sciences, engineering, hydrology, crop water requirements, climatic changes and energy assessment. It is quite random in nature as it has to go through different processes of assimilation and dispersion while on its way to earth. Compared to other meteorological parameters, solar radiation is quite infrequently measured, for example, the worldwide ratio of stations collecting solar radiation to those collecting temperature is 1:500 (Badescu, 2008). Researchers, therefore, have to rely on indirect techniques of estimation that include nonlinear models, artificial intelligence (e.g. neural networks), remote sensing and numerical weather predictions (NWP). This study proposes a hybrid numerical prediction scheme for solar radiation estimation in un-gauged catchments. It uses the PSU/NCAR's Mesoscale Modelling system (MM5) (Grell et al., 1995) to parameterise the cloud effect on extraterrestrial radiation by dividing the atmosphere into four layers of very high (6-12 km), high (3-6 km), medium (1.5-3) and low (0-1.5) altitudes from earth. It is believed that various cloud forms exist within each of these layers. An hourly time series of upper air pressure and relative humidity data sets corresponding to all of these layers is determined for the Brue catchment, southwest UK, using MM5. Cloud Index (CI) was then determined using (Yang and Koike, 2002): 1 p?bi [ (Rh - Rh )] ci =------- max 0.0,---------cri dp pbi - ptipti (1- Rhcri) where, pbi and pti represent the air pressure at the top and bottom of each layer and Rhcri is the critical value of relative humidity at which a certain cloud type is formed. Output from a global clear sky solar radiation model (MRM v-5) (Kambezidis and Psiloglu, 2008) is used along with meteorological datasets of temperature and precipitation and astronomical information. The analysis is aided by the

  18. A 3D Automated Classification Scheme for the TAUVEX data pipeline

    CERN Document Server

    Bora, Archana; Singh, Harinder P; Murthy, Jayant; Mohan, Rekhesh

    2007-01-01

    In order to develop a pipeline for automated classification of stars to be observed by the TAUVEX ultraviolet space Telescope, we employ an artificial neural network (ANN) technique for classifying stars by using synthetic spectra in the UV region from 1250\\AA to 3220\\AA as the training set and International Ultraviolet Explorer (IUE) low resolution spectra as the test set. Both the data sets have been pre-processed to mimic the observations of the TAUVEX ultraviolet imager. We have successfully classified 229 stars from the IUE low resolution catalog to within 3-4 spectral sub-class using two different simulated training spectra, the TAUVEX spectra of 286 spectral types and UVBLUE spectra of 277 spectral types. Further, we have also been able to obtain the colour excess (i.e. E(B-V) in magnitude units) or the interstellar reddening for those IUE spectra which have known reddening to an accuracy of better than 0.1 magnitudes. It has been shown that even with the limitation of data from just photometric bands,...

  19. A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network.

    Science.gov (United States)

    Salari, Nader; Shohaimi, Shamarina; Najafi, Farid; Nallappan, Meenakshii; Karishnarajah, Isthrinayagy

    2014-01-01

    Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. In the present study, the results of the implementation of a novel hybrid feature selection-classification model using the above mentioned methods are presented. The purpose is benefitting from the synergies obtained from combining these technologies for the development of classification models. Such a combination creates an opportunity to invest in the strength of each algorithm, and is an approach to make up for their deficiencies. To develop proposed model, with the aim of obtaining the best array of features, first, feature ranking techniques such as the Fisher's discriminant ratio and class separability criteria were used to prioritize features. Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. The performance of the proposed model was compared with thirteen well-known classification models based on seven datasets. Furthermore, the statistical analysis was performed using the Friedman test followed by post-hoc tests. The experimental findings indicated that the novel proposed hybrid model resulted in significantly better classification performance compared with all 13 classification methods. Finally, the performance results of the proposed model was benchmarked against the best ones reported as the state-of-the-art classifiers in terms of classification accuracy for the same data sets. The substantial findings of the comprehensive comparative study revealed that performance of the

  20. Staggering behavior of the first excited 2{sup +} states of even-even nuclei in a Sp(4, R) classification scheme

    Energy Technology Data Exchange (ETDEWEB)

    Drenska, S.; Georgieva, A.; Minkov, N. [Bulgarian Academy of Sciences, Inst. for Nuclear Research and Nuclear Energy, Sofia (Bulgaria)

    2002-12-01

    We implement a high order discrete derivative analysis of the lowest nuclear collective excitations in terms of the quantum numbers of an algebraic Sp(4, R) classification scheme. The results reveal a fine systematic behavior of nuclear collectivity in terms of nucleon pairing and high order quartetting correlations. (author)

  1. Hybrid Ant Bee Algorithm for Fuzzy Expert System Based Sample Classification.

    Science.gov (United States)

    GaneshKumar, Pugalendhi; Rani, Chellasamy; Devaraj, Durairaj; Victoire, T Aruldoss Albert

    2014-01-01

    Accuracy maximization and complexity minimization are the two main goals of a fuzzy expert system based microarray data classification. Our previous Genetic Swarm Algorithm (GSA) approach has improved the classification accuracy of the fuzzy expert system at the cost of their interpretability. The if-then rules produced by the GSA are lengthy and complex which is difficult for the physician to understand. To address this interpretability-accuracy tradeoff, the rule set is represented using integer numbers and the task of rule generation is treated as a combinatorial optimization task. Ant colony optimization (ACO) with local and global pheromone updations are applied to find out the fuzzy partition based on the gene expression values for generating simpler rule set. In order to address the formless and continuous expression values of a gene, this paper employs artificial bee colony (ABC) algorithm to evolve the points of membership function. Mutual Information is used for idenfication of informative genes. The performance of the proposed hybrid Ant Bee Algorithm (ABA) is evaluated using six gene expression data sets. From the simulation study, it is found that the proposed approach generated an accurate fuzzy system with highly interpretable and compact rules for all the data sets when compared with other approaches.

  2. The Hybrid KICA-GDA-LSSVM Method Research on Rolling Bearing Fault Feature Extraction and Classification

    Directory of Open Access Journals (Sweden)

    Jiyong Li

    2015-01-01

    Full Text Available Rolling element bearings are widely used in high-speed rotating machinery; thus proper monitoring and fault diagnosis procedure to avoid major machine failures is necessary. As feature extraction and classification based on vibration signals are important in condition monitoring technique, and superfluous features may degrade the classification performance, it is needed to extract independent features, so LSSVM (least square support vector machine based on hybrid KICA-GDA (kernel independent component analysis-generalized discriminate analysis is presented in this study. A new method named sensitive subband feature set design (SSFD based on wavelet packet is also presented; using proposed variance differential spectrum method, the sensitive subbands are selected. Firstly, independent features are obtained by KICA; the feature redundancy is reduced. Secondly, feature dimension is reduced by GDA. Finally, the projected feature is classified by LSSVM. The whole paper aims to classify the feature vectors extracted from the time series and magnitude of spectral analysis and to discriminate the state of the rolling element bearings by virtue of multiclass LSSVM. Experimental results from two different fault-seeded bearing tests show good performance of the proposed method.

  3. A HYBRID CLASSIFICATION ALGORITHM TO CLASSIFY ENGINEERING STUDENTS’ PROBLEMS AND PERKS

    Directory of Open Access Journals (Sweden)

    Mitali Desai

    2016-03-01

    Full Text Available The social networking sites have brought a new horizon for expressing views and opinions of individuals. Moreover, they provide medium to students to share their sentiments including struggles and joy during the learning process. Such informal information has a great venue for decision making. The large and growing scale of information needs automatic classification techniques. Sentiment analysis is one of the automated techniques to classify large data. The existing predictive sentiment analysis techniques are highly used to classify reviews on E-commerce sites to provide business intelligence. However, they are not much useful to draw decisions in education system since they classify the sentiments into merely three pre-set categories: positive, negative and neutral. Moreover, classifying the students’ sentiments into positive or negative category does not provide deeper insight into their problems and perks. In this paper, we propose a novel Hybrid Classification Algorithm to classify engineering students’ sentiments. Unlike traditional predictive sentiment analysis techniques, the proposed algorithm makes sentiment analysis process descriptive. Moreover, it classifies engineering students’ perks in addition to problems into several categories to help future students and education system in decision making.

  4. Partition-Based Hybrid Decoding (PHD: A Class of ML Decoding Schemes for MIMO Signals Based on Tree Partitioning and Combined Depth- and Breadth-First Search

    Directory of Open Access Journals (Sweden)

    J. I. Park

    2013-03-01

    Full Text Available In this paper, we propose a hybrid maximum likelihood (ML decoding scheme for multiple-input multiple-output(MIMO systems. After partitioning the searching tree into several stages, the proposed scheme adopts thecombination of depth- and breadth-first search methods in an organized way. Taking the number of stages, the size ofsignal constellation, and the number of antennas as the parameter of the scheme, we provide extensive simulationresults for various MIMO communication conditions. Numerical results indicate that, when the depth- and breadth-firstsearch methods are employed appropriately, the proposed scheme exhibits substantially lower computationalcomplexity than conventional ML decoders while maintaining the ML bit error performance.

  5. Programming scheme based optimization of hybrid 4T-2R OxRAM NVSRAM

    Science.gov (United States)

    Majumdar, Swatilekha; Kingra, Sandeep Kaur; Suri, Manan

    2017-09-01

    In this paper, we present a novel single-cycle programming scheme for 4T-2R NVSRAM, exploiting pulse engineered input signals. OxRAM devices based on 3 nm thick bi-layer active switching oxide and 90 nm CMOS technology node were used for all simulations. The cell design is implemented for real-time non-volatility rather than last-bit, or power-down non-volatility. Detailed analysis of the proposed single-cycle, parallel RRAM device programming scheme is presented in comparison to the two-cycle sequential RRAM programming used for similar 4T-2R NVSRAM bit-cells. The proposed single-cycle programming scheme coupled with the 4T-2R architecture leads to several benefits such as- possibility of unconventional transistor sizing, 50% lower latency, 20% improvement in SNM and ∼20× reduced energy requirements, when compared against two-cycle programming approach.

  6. A hybrid scheme for absorbing edge reflections in numerical modeling of wave propagation

    KAUST Repository

    Liu, Yang

    2010-03-01

    We propose an efficient scheme to absorb reflections from the model boundaries in numerical solutions of wave equations. This scheme divides the computational domain into boundary, transition, and inner areas. The wavefields within the inner and boundary areas are computed by the wave equation and the one-way wave equation, respectively. The wavefields within the transition area are determined by a weighted combination of the wavefields computed by the wave equation and the one-way wave equation to obtain a smooth variation from the inner area to the boundary via the transition zone. The results from our finite-difference numerical modeling tests of the 2D acoustic wave equation show that the absorption enforced by this scheme gradually increases with increasing width of the transition area. We obtain equally good performance using pseudospectral and finite-element modeling with the same scheme. Our numerical experiments demonstrate that use of 10 grid points for absorbing edge reflections attains nearly perfect absorption. © 2010 Society of Exploration Geophysicists.

  7. Development and application of a new comprehensive image-based classification scheme for coastal and benthic environments along the southeast Florida continental shelf

    Science.gov (United States)

    Makowski, Christopher

    The coastal (terrestrial) and benthic environments along the southeast Florida continental shelf show a unique biophysical succession of marine features from a highly urbanized, developed coastal region in the north (i.e. northern Miami-Dade County) to a protective marine sanctuary in the southeast (i.e. Florida Keys National Marine Sanctuary). However, the establishment of a standard bio-geomorphological classification scheme for this area of coastal and benthic environments is lacking. The purpose of this study was to test the hypothesis and answer the research question of whether new parameters of integrating geomorphological components with dominant biological covers could be developed and applied across multiple remote sensing platforms for an innovative way to identify, interpret, and classify diverse coastal and benthic environments along the southeast Florida continental shelf. An ordered manageable hierarchical classification scheme was developed to incorporate the categories of Physiographic Realm, Morphodynamic Zone, Geoform, Landform, Dominant Surface Sediment, and Dominant Biological Cover. Six different remote sensing platforms (i.e. five multi-spectral satellite image sensors and one high-resolution aerial orthoimagery) were acquired, delineated according to the new classification scheme, and compared to determine optimal formats for classifying the study area. Cognitive digital classification at a nominal scale of 1:6000 proved to be more accurate than autoclassification programs and therefore used to differentiate coastal marine environments based on spectral reflectance characteristics, such as color, tone, saturation, pattern, and texture of the seafloor topology. In addition, attribute tables were created in conjugation with interpretations to quantify and compare the spatial relationships between classificatory units. IKONOS-2 satellite imagery was determined to be the optimal platform for applying the hierarchical classification scheme

  8. A HYBRID APPROACH BASED MEDICAL IMAGE RETRIEVAL SYSTEM USING FEATURE OPTIMIZED CLASSIFICATION SIMILARITY FRAMEWORK

    Directory of Open Access Journals (Sweden)

    Yogapriya Jaganathan

    2013-01-01

    Full Text Available For the past few years, massive upgradation is obtained in the pasture of Content Based Medical Image Retrieval (CBMIR for effective utilization of medical images based on visual feature analysis for the purpose of diagnosis and educational research. The existing medical image retrieval systems are still not optimal to solve the feature dimensionality reduction problem which increases the computational complexity and decreases the speed of a retrieval process. The proposed CBMIR is used a hybrid approach based on Feature Extraction, Optimization of Feature Vectors, Classification of Features and Similarity Measurements. This type of CBMIR is called Feature Optimized Classification Similarity (FOCS framework. The selected features are Textures using Gray level Co-occurrence Matrix Features (GLCM and Tamura Features (TF in which extracted features are formed as feature vector database. The Fuzzy based Particle Swarm Optimization (FPSO technique is used to reduce the feature vector dimensionality and classification is performed using Fuzzy based Relevance Vector Machine (FRVM to form groups of relevant image features that provide a natural way to classify dimensionally reduced feature vectors of images. The Euclidean Distance (ED is used as similarity measurement to measure the significance between the query image and the target images. This FOCS approach can get the query from the user and has retrieved the needed images from the databases. The retrieval algorithm performances are estimated in terms of precision and recall. This FOCS framework comprises several benefits when compared to existing CBMIR. GLCM and TF are used to extract texture features and form a feature vector database. Fuzzy-PSO is used to reduce the feature vector dimensionality issues while selecting the important features in the feature vector database in which computational complexity is decreased. Fuzzy based RVM is used for feature classification in which it increases the

  9. Staggering behavior of the low lying excited states of even-even nuclei in a Sp(4,R) classification scheme

    CERN Document Server

    Drenska, S B; Minkov, N

    2002-01-01

    We implement a high order discrete derivative analysis of the low lying collective energies of even-even nuclei with respect to the total number of valence nucleon pairs N in the framework of F- spin multiplets appearing in a symplectic sp(4,R) classification scheme. We find that for the nuclei of any given F- multiplet the respective experimental energies exhibit a Delta N=2 staggering behavior and for the nuclei of two united neighboring F- multiplets well pronounced Delta N=1 staggering patterns are observed. Those effects have been reproduced successfully through a generalized sp(4,R) model energy expression and explained in terms of the step-like changes in collective modes within the F- multiplets and the alternation of the F-spin projection in the united neighboring multiplets. On this basis we suggest that the observed Delta N=2 and Delta N=1 staggering effects carry detailed information about the respective systematic manifestation of both high order alpha - particle like quartetting of nucleons and ...

  10. Gemstones and geosciences in space and time. Digital maps to the "Chessboard classification scheme of mineral deposits"

    Science.gov (United States)

    Dill, Harald G.; Weber, Berthold

    2013-12-01

    The gemstones, covering the spectrum from jeweler's to showcase quality, have been presented in a tripartite subdivision, by country, geology and geomorphology realized in 99 digital maps with more than 2600 mineralized sites. The various maps were designed based on the "Chessboard classification scheme of mineral deposits" proposed by Dill (2010a, 2010b) to reveal the interrelations between gemstone deposits and mineral deposits of other commodities and direct our thoughts to potential new target areas for exploration. A number of 33 categories were used for these digital maps: chromium, nickel, titanium, iron, manganese, copper, tin-tungsten, beryllium, lithium, zinc, calcium, boron, fluorine, strontium, phosphorus, zirconium, silica, feldspar, feldspathoids, zeolite, amphibole (tiger's eye), olivine, pyroxenoid, garnet, epidote, sillimanite-andalusite, corundum-spinel - diaspore, diamond, vermiculite-pagodite, prehnite, sepiolite, jet, and amber. Besides the political base map (gems by country) the mineral deposit is drawn on a geological map, illustrating the main lithologies, stratigraphic units and tectonic structure to unravel the evolution of primary gemstone deposits in time and space. The geomorphological map is to show the control of climate and subaerial and submarine hydrography on the deposition of secondary gemstone deposits. The digital maps are designed so as to be plotted as a paper version of different scale and to upgrade them for an interactive use and link them to gemological databases.

  11. Hybrid mathematical and rule-based system for transmission network planning in open access schemes

    Energy Technology Data Exchange (ETDEWEB)

    Kandil, M. S. [Electrical Department, Mansura University, (Egypt); EI-Debeiky, S. M. [Electrical Department, Ain Shams University, (Egypt); Hasanien, N. E. [Egyptian Electricity Authority, Studies and Researches Department, (Egypt)

    2001-09-01

    The paper presents a planning methodology using an application of a mathematical and a rule-based expert system (ES) to expand the transmission network in open access schemes. In this methodology, the ES suggests a realistic set of generation additions with proper economic signals to the participants, before proceeding with the transmission expansion. A feasible list of transmission alternatives is then assumed to accommodate the proposals for generation. A mathematical method is performed based on marginal cost allocation to optimise the location for the new generation and its transmission expansion scheme simultaneously for each alternative. The optimum alternative, which minimises the overall system's cost function and satisfies the future demand under different operating conditions, is obtained. The ES interacts with the power system planning tools to produce the optimum expansion plan. A practical application is given to demonstrate the effectiveness of the developed prototype system. (Author)

  12. Hybrid Iterative Scheme for Triple Hierarchical Variational Inequalities with Mixed Equilibrium, Variational Inclusion, and Minimization Constraints

    Directory of Open Access Journals (Sweden)

    Lu-Chuan Ceng

    2014-01-01

    Full Text Available We introduce and analyze a hybrid iterative algorithm by combining Korpelevich's extragradient method, the hybrid steepest-descent method, and the averaged mapping approach to the gradient-projection algorithm. It is proven that, under appropriate assumptions, the proposed algorithm converges strongly to a common element of the fixed point set of finitely many nonexpansive mappings, the solution set of a generalized mixed equilibrium problem (GMEP, the solution set of finitely many variational inclusions, and the solution set of a convex minimization problem (CMP, which is also a unique solution of a triple hierarchical variational inequality (THVI in a real Hilbert space. In addition, we also consider the application of the proposed algorithm to solving a hierarchical variational inequality problem with constraints of the GMEP, the CMP, and finitely many variational inclusions.

  13. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  14. Prediction of “Aggregation-Prone” Peptides with Hybrid Classification Approach

    Directory of Open Access Journals (Sweden)

    Bo Liu

    2015-01-01

    Full Text Available Protein aggregation is a biological phenomenon caused by misfolding proteins aggregation and is associated with a wide variety of diseases, such as Alzheimer’s, Parkinson’s, and prion diseases. Many studies indicate that protein aggregation is mediated by short “aggregation-prone” peptide segments. Thus, the prediction of aggregation-prone sites plays a crucial role in the research of drug targets. Compared with the labor-intensive and time-consuming experiment approaches, the computational prediction of aggregation-prone sites is much desirable due to their convenience and high efficiency. In this study, we introduce two computational approaches Aggre_Easy and Aggre_Balance for predicting aggregation residues from the sequence information; here, the protein samples are represented by the composition of k-spaced amino acid pairs (CKSAAP. And we use the hybrid classification approach to predict aggregation-prone residues, which integrates the naïve Bayes classification to reduce the number of features, and two undersampling approaches EasyEnsemble and BalanceCascade to deal with samples imbalance problem. The Aggre_Easy achieves a promising performance with a sensitivity of 79.47%, a specificity of 80.70% and a MCC of 0.42; the sensitivity, specificity, and MCC of Aggre_Balance reach 70.32%, 80.70% and 0.42. Experimental results show that the performance of Aggre_Easy and Aggre_Balance predictor is better than several other state-of-the-art predictors. A user-friendly web server is built for prediction of aggregation-prone which is freely accessible to public at the website.

  15. Analysis of the classification of US and Canadian intensive test sites using the Image 100 hybrid classification system

    Science.gov (United States)

    Hocutt, W. T. (Principal Investigator)

    1978-01-01

    The author has identified the following significant results. Labeling of wheat rather than total grains, particularly with only one acquisition, led to significant overestimates in some segments. The Image-100 software and procedures were written to facilitate classification of the LACIE segments but were not designed to record data for later accuracy assessment. A much better evaluation would have been possible if accuracy assessment data had been collected following each satisfactory classification.

  16. A hybrid configuration interaction treatment based on seniority number and excitation schemes

    Energy Technology Data Exchange (ETDEWEB)

    Alcoba, Diego R.; Capuzzi, Pablo [Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires and Instituto de Física de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas, Ciudad Universitaria, 1428 Buenos Aires (Argentina); Torre, Alicia; Lain, Luis, E-mail: qfplapel@lg.ehu.es [Departamento de Química Física, Facultad de Ciencia y Tecnología, Universidad del País Vasco, Apdo. 644 E-48080 Bilbao (Spain); Oña, Ofelia B. [Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas, Universidad Nacional de La Plata, CCT La Plata, Consejo Nacional de Investigaciones Científicas y Técnicas, Diag. 113 y 64 (S/N), Sucursal 4, CC 16, 1900 La Plata (Argentina); Van Raemdonck, Mario; Bultinck, Patrick [Department of Inorganic and Physical Chemistry, Ghent University, Krijgslaan 281 (S3), 9000 Gent (Belgium); Van Neck, Dimitri [Center for Molecular Modelling, Ghent University, Technologiepark 903, 9052 Zwijnaarde (Belgium)

    2014-12-28

    We present a configuration interaction method in which the Hamiltonian of an N-electron system is projected on Slater determinants selected according to the seniority-number criterion along with the traditional excitation-based procedure. This proposed method is especially useful to describe systems which exhibit dynamic (weak) correlation at determined geometric arrangements (where the excitation-based procedure is more suitable) but show static (strong) correlation at other arrangements (where the seniority-number technique is preferred). The hybrid method amends the shortcomings of both individual determinant selection procedures, yielding correct shapes of potential energy curves with results closer to those provided by the full configuration interaction method.

  17. Likelihood Inference under Generalized Hybrid Censoring Scheme with Comp eting Risks

    Institute of Scientific and Technical Information of China (English)

    MAO Song; SHI Yi-min

    2016-01-01

    Statistical inference is developed for the analysis of generalized type-II hybrid censoring data under exponential competing risks model. In order to solve the problem that approximate methods make unsatisfactory performances in the case of small sample size, we establish the exact conditional distributions of estimators for parameters by conditional moment generating function(CMGF). Furthermore, confidence intervals(CIs) are constructed by exact distributions, approximate distributions as well as bootstrap method respectively, and their performances are evaluated by Monte Carlo simulations. And finally, a real data set is analyzed to illustrate all the methods developed here.

  18. Efficient Mooring Line Fatigue Analysis Using a Hybrid Method Time Domain Simulation Scheme

    DEFF Research Database (Denmark)

    Christiansen, Niels Hørbye; Voie, Per Erlend Torbergsen; Høgsberg, Jan Becker;

    2013-01-01

    Dynamic analyses of mooring line systems are computationally expensive. Over the last decades an extensive variety of methods to reduce this computational cost have been suggested. One method that has shown promising preliminary results is a hybrid method which combines finite element analysis...... and slow drift motion. The method is tested on a mooring line system of a floating offshore platform. After training a full fatigue analysis is carried out. The results show that the ANN with high precision provides top tension force histories two orders of magnitude faster than a full dynamic analysis...

  19. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  20. An efficient and stable hybrid extended Lagrangian/self-consistent field scheme for solving classical mutual induction

    Energy Technology Data Exchange (ETDEWEB)

    Albaugh, Alex [Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720 (United States); Demerdash, Omar [Department of Chemistry, University of California, Berkeley, California 94720 (United States); Head-Gordon, Teresa, E-mail: thg@berkeley.edu [Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720 (United States); Department of Chemistry, University of California, Berkeley, California 94720 (United States); Department of Bioengineering, University of California, Berkeley, California 94720 (United States); Chemical Sciences Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, California 94720 (United States)

    2015-11-07

    We have adapted a hybrid extended Lagrangian self-consistent field (EL/SCF) approach, developed for time reversible Born Oppenheimer molecular dynamics for quantum electronic degrees of freedom, to the problem of classical polarization. In this context, the initial guess for the mutual induction calculation is treated by auxiliary induced dipole variables evolved via a time-reversible velocity Verlet scheme. However, we find numerical instability, which is manifested as an accumulation in the auxiliary velocity variables, that in turn results in an unacceptable increase in the number of SCF cycles to meet even loose convergence tolerances for the real induced dipoles over the course of a 1 ns trajectory of the AMOEBA14 water model. By diagnosing the numerical instability as a problem of resonances that corrupt the dynamics, we introduce a simple thermostating scheme, illustrated using Berendsen weak coupling and Nose-Hoover chain thermostats, applied to the auxiliary dipole velocities. We find that the inertial EL/SCF (iEL/SCF) method provides superior energy conservation with less stringent convergence thresholds and a correspondingly small number of SCF cycles, to reproduce all properties of the polarization model in the NVT and NVE ensembles accurately. Our iEL/SCF approach is a clear improvement over standard SCF approaches to classical mutual induction calculations and would be worth investigating for application to ab initio molecular dynamics as well.

  1. A Hybrid Secure Scheme for Wireless Sensor Networks against Timing Attacks Using Continuous-Time Markov Chain and Queueing Model

    Directory of Open Access Journals (Sweden)

    Tianhui Meng

    2016-09-01

    Full Text Available Wireless sensor networks (WSNs have recently gained popularity for a wide spectrum of applications. Monitoring tasks can be performed in various environments. This may be beneficial in many scenarios, but it certainly exhibits new challenges in terms of security due to increased data transmission over the wireless channel with potentially unknown threats. Among possible security issues are timing attacks, which are not prevented by traditional cryptographic security. Moreover, the limited energy and memory resources prohibit the use of complex security mechanisms in such systems. Therefore, balancing between security and the associated energy consumption becomes a crucial challenge. This paper proposes a secure scheme for WSNs while maintaining the requirement of the security-performance tradeoff. In order to proceed to a quantitative treatment of this problem, a hybrid continuous-time Markov chain (CTMC and queueing model are put forward, and the tradeoff analysis of the security and performance attributes is carried out. By extending and transforming this model, the mean time to security attributes failure is evaluated. Through tradeoff analysis, we show that our scheme can enhance the security of WSNs, and the optimal rekeying rate of the performance and security tradeoff can be obtained.

  2. A new encoding scheme-based hybrid algorithm for minimising two-machine flow-shop group scheduling problem

    Science.gov (United States)

    Liou, Cheng-Dar; Hsieh, Yi-Chih; Chen, Yin-Yann

    2013-01-01

    This article investigates the two-machine flow-shop group scheduling problem (GSP) with sequence-dependent setup and removal times, and job transportation times between machines. The objective is to minimise the total completion time. As known, this problem is an NP-hard problem and generalises the typical two-machine GSPs. In this article, a new encoding scheme based on permutation representation is proposed to transform a random job permutation to a feasible permutation for GSPs. The proposed encoding scheme simultaneously determines both the sequence of jobs in each group and the sequence of groups. By reasonably combining particle swarm optimisation (PSO) and genetic algorithm (GA), we develop a fast and easily implemented hybrid algorithm (HA) for solving the considered problems. The effectiveness and efficiency of the proposed HA are demonstrated and compared with those of standard PSO and GA by numerical results of various tested instances with group numbers up to 20. In addition, three different lower bounds are developed to evaluate the solution quality of the HA. Limited numerical results indicate that the proposed HA is a viable and effective approach for the studied two-machine flow-shop group scheduling problem.

  3. A robust cluster-based dynamic-super-node scheme for hybrid peer-to-peer network

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Hybrid peer-to-peer (P2P) system can improve the performance of the entire system using super-peer. But it is difficult to measure a peer's capability exactly and ensure high reliability of the network. This paper proposes a scheme to solve these problems. Firstly, we present a hybrid P2P network in which the upper layer is Chord network and the lower layer is cluster. Then we provide a strategy to measure a peer's capability so that a cluster can be organized to be a sorting network in which peers are classified into three types: dynamic-super-node (DSN), backup-node (BN) and ordinary-node (ON). In a cluster, DSN and BNs are strongly connected. And based on this, we present an algorithm DSN flood min (DSNFM) to select DSN BN and maintain consensus of the cluster. Furthermore, we do a reliability analysis of the cluster based on churn rate of the network and gathered three rules of thumb from our simulations.

  4. A Muscle Synergy-inspired Adaptive Control Scheme for a Hybrid Walking Neuroprosthesis

    Directory of Open Access Journals (Sweden)

    Naji A Alibeji

    2015-12-01

    Full Text Available Abstract--- Abstract--- A hybrid neuroprosthesis that uses an electric motor-based wearable exoskeleton and functional electrical stimulation (FES has a promising potential to restore walking in persons with paraplegia. A hybrid actuation structure introduces effector redundancy, making its automatic control a challenging task because multiple muscles and additional electric motor need to be coordinated. Inspired by the muscle synergy principle, we designed a low dimensional controller to control multiple effectors: FES of multiple muscles and electric motors. The resulting control system may be less complex and easier to control. To obtain the muscle synergy-inspired low dimensional control, a subject-specific gait model was optimized to compute optimal control signals for the multiple effectors. The optimal control signals were then dimensionally reduced by using principal component analysis to extract synergies. Then, an adaptive feedforward controller with an update law for the synergy activation was designed. In addition, feedback control was used to provide stability and robustness to the control design. The adaptive-feedforward and feedback control structure makes the low dimensional controller more robust to disturbances and variations in the model parameters and may help to compensate for other time-varying phenomena (e.g., muscle fatigue. This is proven by using a Lyapunov stability analysis, which yielded semi-global uniformly ultimately bounded tracking. Computer simulations were performed to test the new controller on a 4 degree of freedom gait model.

  5. Classification of magnetic inhomogeneities and 0 -π transitions in superconducting-magnetic hybrid structures

    Science.gov (United States)

    Baker, Thomas E.; Richie-Halford, Adam; Bill, Andreas

    2016-09-01

    We present a comparative study of pair correlations and currents through superconducting-magnetic hybrid systems with a particular emphasis on the tunable Bloch domain wall of an exchange spring. This study of the Gor'kov functions contrasts magnetic systems with domain walls that change at discrete points in the magnetic region with those that change continuously throughout. We present results for misaligned homogeneous magnetic multilayers, including spin valves, for discrete domain walls, as well as exchange springs and helical domain walls—such as Holmium—for the continuous case. Introducing a rotating basis to disentangle the role of singlet and triplet correlations, we demonstrate that substantial amounts of (so-called short-range) singlet correlations are generated throughout the magnetic system in a continuous domain wall via the cascade effect. We propose a classification of 0 -π transitions of the Josephson current into three types, according to the predominant pair correlations symmetries involved in the current. Properties of exchange springs for an experimental study of the proposed effects are discussed. The interplay between components of the Gor'kov function that are parallel and perpendicular to the local magnetization lead to a novel prediction about their role in a proximity system with a progressively twisting helix that is experimentally measurable.

  6. Distinguishing real from fake ivory products by elemental analyses: A Bayesian hybrid classification method.

    Science.gov (United States)

    Buddhachat, Kittisak; Brown, Janine L; Thitaram, Chatchote; Klinhom, Sarisa; Nganvongpanit, Korakot

    2017-03-01

    As laws tighten to limit commercial ivory trading and protect threatened species like whales and elephants, increased sales of fake ivory products have become widespread. This study describes a method, handheld X-ray fluorescence (XRF) as a noninvasive technique for elemental analysis, to differentiate quickly between ivory (Asian and African elephant, mammoth) from non-ivory (bones, teeth, antler, horn, wood, synthetic resin, rock) materials. An equation consisting of 20 elements and light elements from a stepwise discriminant analysis was used to classify samples, followed by Bayesian binary regression to determine the probability of a sample being 'ivory', with complementary log log analysis to identify the best fit model for this purpose. This Bayesian hybrid classification model was 93% accurate with 92% precision in discriminating ivory from non-ivory materials. The method was then validated by scanning an additional ivory and non-ivory samples, correctly identifying bone as not ivory with >95% accuracy, except elephant bone, which was 72%. It was less accurate for wood and rock (25-85%); however, a preliminary screening to determine if samples are not Ca-dominant could eliminate inorganic materials. In conclusion, elemental analyses by XRF can be used to identify several forms of fake ivory samples, which could have forensic application.

  7. Automated segmentation of the quadratus lumborum muscle from magnetic resonance images using a hybrid atlas based - geodesic active contour scheme.

    Science.gov (United States)

    Jurcak, V; Fripp, J; Engstrom, C; Walker, D; Salvado, O; Ourselin, S; Crozier, S

    2008-01-01

    This study presents a novel method for the automatic segmentation of the quadratus lumborum (QL) muscle from axial magnetic resonance (MR) images using a hybrid scheme incorporating the use of non-rigid registration with probabilistic atlases (PAs) and geodesic active contours (GACs). The scheme was evaluated on an MR database of 7mm axial images of the lumbar spine from 20 subjects (fast bowlers and athletic controls). This scheme involved several steps, including (i) image pre-processing, (ii) generation of PAs for the QL, psoas (PS) and erector spinae+multifidus (ES+MT) muscles and (iii) segmentation, using 3D GACs initialized and constrained by the propagation of the PAs using non-rigid registration. Pre-processing of the images involved bias field correction based on local entropy minimization with a bicubic spline model and a reverse diffusion interpolation algorithm to increase the slice resolution to 0.98 x 0.98 x 1.75mm. The processed images were then registered (affine and non-rigid) and used to generate an average atlas. The PAs for the QL, PS and ES+MT were then generated by propagation of manual segmentations. These atlases were further analysed with specialised filtering to constrain the QL segmentation from adjacent non-muscle tissues (kidney, fat). This information was then used in 3D GACs to obtain the final segmentation of the QL. The automatic segmentation results were compared with the manual segmentations using the Dice similarity metric (DSC), with a median DSC for the right and left QL muscles of 0.78 (mean = 0.77, sd=0.07) and 0.75 (mean =0.74, sd=0.07), respectively.

  8. An ensemble training scheme for machine-learning classification of Hyperion satellite imagery with independent hyperspectral libraries

    Science.gov (United States)

    Friedel, Michael; Buscema, Massimo

    2016-04-01

    A training scheme is proposed for the real-time classification of soil and vegetation (landscape) components in EO-1 Hyperion hyperspectral images. First, an auto-contractive map is used to compute connectivity of reflectance values for spectral bands (N=200) from independent laboratory spectral library components. Second, a minimum spanning tree is used to identify optimal grouping of training components from connectivity values. Third, the reflectance values for optimal landscape component signatures are sorted. Fourth, empirical distribution functions (EDF) are computed for each landscape component. Fifth, the Monte-Carlo technique is used to generate realizations (N=30) for each landscape EDF. The correspondence of component realizations to original signatures validates the stochastic procedure. Presentation of the realizations to the self-organizing map (SOM) is done using three different map sizes: 14x10, 28x20, and 40 x 30. In each case, the SOM training proceeds first with a rough phase (20 iterations using a Gaussian neighborhood with an initial and final radius of 11 units and 3 units) and then fine phase (400 iterations using a Gaussian neighborhood with an initial and final radius of 3 units and 1 unit). The initial and final learning rates of 0.5 and 0.05 decay linearly down to 10-5, and the Gaussian neighborhood function decreases exponentially (decay rate of 10-3 iteration-1) providing reasonable convergence. Following training of the three networks, each corresponding SOM is used to independently classify the original spectral library signatures. In comparing the different SOM networks, the 28x20 map size is chosen for independent reproducibility and processing speed. The corresponding universal distance matrix reveals separation of the seven component classes for this map size thereby supporting it use as a Hyperion classifier.

  9. A classification scheme for alternative oxidases reveals the taxonomic distribution and evolutionary history of the enzyme in angiosperms.

    Science.gov (United States)

    Costa, José Hélio; McDonald, Allison E; Arnholdt-Schmitt, Birgit; Fernandes de Melo, Dirce

    2014-11-01

    A classification scheme based on protein phylogenies and sequence harmony method was used to clarify the taxonomic distribution and evolutionary history of the alternative oxidase (AOX) in angiosperms. A large data set analyses showed that AOX1 and AOX2 subfamilies were distributed into 4 phylogenetic clades: AOX1a-c/1e, AOX1d, AOX2a-c and AOX2d. High diversity in AOX family compositions was found. While the AOX2 subfamily was not detected in monocots, the AOX1 subfamily has expanded (AOX1a-e) in the large majority of these plants. In addition, Poales AOX1b and 1d were orthologous to eudicots AOX1d and then renamed as AOX1d1 and 1d2. AOX1 or AOX2 losses were detected in some eudicot plants. Several AOX2 duplications (AOX2a-c) were identified in eudicot species, mainly in the asterids. The AOX2b originally identified in eudicots in the Fabales order (soybean, cowpea) was divergent from AOX2a-c showing some specific amino acids with AOX1d and then it was renamed as AOX2d. AOX1d and AOX2d seem to be stress-responsive, facultative and mutually exclusive among species suggesting a complementary role with an AOX1(a) in stress conditions. Based on the data collected, we present a model for the evolutionary history of AOX in angiosperms and highlight specific areas where further research would be most beneficial. Copyright © 2014 Elsevier B.V. All rights reserved.

  10. Dynamic Simulation of a Trigeneration Scheme for Domestic Purposes Based on Hybrid Techniques

    Directory of Open Access Journals (Sweden)

    Luis Acevedo

    2016-11-01

    Full Text Available In this paper, the design of a system providing electricity by coupling photovoltaic/thermal (PVT collectors and a wind turbine (WT, sanitary hot water (SHW coming from the PVT and evacuated tube collectors (ETCs and fresh water (FW produced in two seawater desalting facilities (membrane distillation, MD, and reverse osmosis, RO, has been carefully analyzed by means of a dynamic model developed in TRNSYS®. This analysis is compulsory to operate a lab-scale pilot plant that is being erected at Zaragoza, Spain. A new model-type has been included in TRNSYS® in order to include the MD unit in the scheme. A sensitivity analysis of some free-design variables, such that the ETC surface, PVT and ETC tilt, water storage tank, batteries capacities, and mass flow rates delivered to the SHW service and/or feeding the MD unit has been performed in order to propose the definite design of the scheme. The proposed base case was able to produce up to 15,311 L per year in the MD system and cover an electric energy demand of 1890 kWh. Coverage of SHW, water (including RO and MD and power is respectively 99.3%, 100% and 70%. However, daily and yearly assessment of FW, SHW and power produced with the optimized design gave a better coverage of water and energy demands for a typical single family home. The improved and definite design was able to increase its MD production in 35% and the electric energy in 7% compared with base case.

  11. Hybrid control scheme for distributed energy resource management in a market context

    DEFF Research Database (Denmark)

    Han, Xue; Bindner, Henrik W.; Mehmedalic, Jasmin;

    2015-01-01

    flexibility to meet regular demand from the distribution system operator (DSO). By considering both their physical constraints and the economical system operation, this paper proposes a realtime hybrid management system for DER units in a market environment, which considers both the request from the DSO......In modernizing the electricity grid, distributed energy resources (DERs) can play an important role in accommodating intermittent energy sources, assisting system operation and the transition to a smart grid. Proper aggregation and coordination of the available DER units is required to provide...... and their local conditions. Voltage regulation service is formulated and implemented in the control frame. The performance is evaluated through simulation on an existing Danish MV and LV distribution grid and is compared with a local control method and the passive operation condition....

  12. A Faster Routing Scheme for Stationary Wireless Sensor Networks - A Hybrid Approach

    CERN Document Server

    Norman, Jasmine; Roja, P Prapoorna; 10.5121/ijasuc.2010.1101

    2010-01-01

    A wireless sensor network consists of light-weight, low power, small size sensor nodes. Routing in wireless sensor networks is a demanding task. This demand has led to a number of routing protocols which efficiently utilize the limited resources available at the sensor nodes. Most of these protocols are either based on single hop routing or multi hop routing and typically find the minimum energy path without addressing other issues such as time delay in delivering a packet, load balancing, and redundancy of data. Response time is very critical in environment monitoring sensor networks where typically the sensors are stationary and transmit data to a base station or a sink node. In this paper a faster load balancing routing protocol based on location with a hybrid approach is proposed.

  13. A new hybrid jpeg image compression scheme using symbol reduction technique

    CERN Document Server

    Kumar, Bheshaj; Sinha, G R

    2012-01-01

    Lossy JPEG compression is a widely used compression technique. Normally the JPEG standard technique uses three process mapping reduces interpixel redundancy, quantization, which is lossy process and entropy encoding, which is considered lossless process. In this paper, a new technique has been proposed by combining the JPEG algorithm and Symbol Reduction Huffman technique for achieving more compression ratio. The symbols reduction technique reduces the number of symbols by combining together to form a new symbol. As a result of this technique the number of Huffman code to be generated also reduced. It is simple fast and easy to implement. The result shows that the performance of standard JPEG method can be improved by proposed method. This hybrid approach achieves about 20% more compression ratio than the Standard JPEG.

  14. a Cabinet Level Thermal Test Vehicle to Evaluate Hybrid Double-Sided Cooling Schemes

    Science.gov (United States)

    Nie, Qihong; Joshi, Yogendra

    Packaging of power semiconductor devices presents some of the greatest thermal design challenges due to the resulting high heat fluxes. Advanced cooling techniques are desired to help meet these demands for current and future devices. A hybrid double-sided approach combining micro-channel liquid cooling, thermoelectric cooling, and forced air convection is investigated via a test vehicle for the thermal management of electronic cabinets. A reduction of 74% in the chip junction temperature rise was achieved by using double-sided cooling, compared to single-sided air convection. Further reduction can be achieved by utilizing thermoelectric cooling (TEC). Additional reductions of 22.4% and 6.5% were achieved by utilizing TEC in single-sided air cooling and double-sided cooling, respectively. The effect of water flow rates through the air-to-liquid heat exchanger and the microchannel heat sink on the chip junction temperature rise was insignificant, compared to the effect of TEC, and cooling configuration.

  15. Wastewater treatment using hybrid treatment schemes based on cavitation and Fenton chemistry: a review.

    Science.gov (United States)

    Bagal, Manisha V; Gogate, Parag R

    2014-01-01

    Advanced oxidation processes such as cavitation and Fenton chemistry have shown considerable promise for wastewater treatment applications due to the ease of operation and simple reactor design. In this review, hybrid methods based on cavitation coupled with Fenton process for the treatment of wastewater have been discussed. The basics of individual processes (Acoustic cavitation, Hydrodynamic cavitation, Fenton chemistry) have been discussed initially highlighting the need for combined processes. The different types of reactors used for the combined processes have been discussed with some recommendations for large scale operation. The effects of important operating parameters such as solution temperature, initial pH, initial pollutant concentration and Fenton's reagent dosage have been discussed with guidelines for selection of optimum parameters. The optimization of power density is necessary for ultrasonic processes (US) and combined processes (US/Fenton) whereas the inlet pressure needs to be optimized in the case of Hydrodynamic cavitation (HC) based processes. An overview of different pollutants degraded under optimized conditions using HC/Fenton and US/Fenton process with comparison with individual processes have been presented. It has been observed that the main mechanism for the synergy of the combined process depends on the generation of additional hydroxyl radicals and its proper utilization for the degradation of the pollutant, which is strongly dependent on the loading of hydrogen peroxide. Overall, efficient wastewater treatment with high degree of energy efficiency can be achieved using combined process operating under optimized conditions, as compared to the individual process.

  16. A hybrid multi-scale computational scheme for advection-diffusion-reaction equation

    Science.gov (United States)

    Karimi, S.; Nakshatrala, K. B.

    2016-12-01

    Simulation of transport and reaction processes in porous media and subsurface science has become more vital than ever. Over the past few decades, a variety of mathematical models and numerical methodologies for porous media simulations have been developed. As the demand for higher accuracy and validity of the models grows, the issue of disparate temporal and spatial scales becomes more problematic. The variety of reaction processes and complexity of pore geometry poses a huge computational burden in a real-world or reservoir scale simulation. Meanwhile, methods based on averaging or up- scaling techniques do not provide reliable estimates to pore-scale processes. To overcome this problem, development of hybrid and multi-scale computational techniques is considered a promising approach. In these methods, pore-scale and continuum-scale models are combined, hence, a more reliable estimate to pore-scale processes is obtained without having to deal with the tremendous computational overhead of pore-scale methods. In this presentation, we propose a computational framework that allows coupling of lattice Boltzmann method (for pore-scale simulation) and finite element method (for continuum-scale simulation) for advection-diffusion-reaction equations. To capture disparate in time and length events, non-matching grid and time-steps are allowed. Apart from application of this method to benchmark problems, multi-scale simulation of chemical reactions in porous media is also showcased.

  17. EMOTION INTERACTION WITH VIRTUAL REALITY USING HYBRID EMOTION CLASSIFICATION TECHNIQUE TOWARD BRAIN SIGNALS

    National Research Council Canada - National Science Library

    Faris A. Abuhashish; Jamal Zraqou; Wesam Alkhodour; Mohd S. Sunar; Hoshang Kolivand

    2015-01-01

    .... Last decade many researchers focused on emotion classification in order to employ emotion in interaction with virtual reality, the classification will be done based on Electroencephalogram (EEG) brain signals...

  18. VERIFICATION OF HYBRID NUMERICAL SCHEME FOR THE CASE OF COMPRESSIBLE JET IMPINGIMENT ON FLAT PLATE

    Directory of Open Access Journals (Sweden)

    2016-01-01

    Full Text Available The article deals with the questions of mathematical modeling of compressible jet outflow from model nozzle and jet impingiment on flat plate at various values of n. pisoCentralFoam solver which is based on the Kurganov-Tadmor hy- brid numerical scheme, PISO algorithm and finite volume method, is used for the solution of this problem. The model, based on unsteady Reynolds equation and K-omega SST turbulence model with boundary functions is used for compressi- ble jet calculation. The problem definition for calculation of jet impingiment on flat plate is given. The simulation domainwas selected as a rectangle. Only a half of the nozzle was considered for simplification. The mixed boundary condition for pressure setting in case of free jet was used on the outlet of simulation domain. The special condition for the pressure with table data, allowed to increase the value of pressure gradually, was used on the inlet of simulation domain. The value of the jet pressure degree was selected as n = 2.5 and n = 5.0. The results of distribution of the velocity magnitude, field pressure, upon symmetry axes were received. The simulations were done with grids 100 000-500 000 cells. The average value of y+ was equal to 270. The calculations were done for the end time Tend = 0.01 s. Comparison of the results of pressure distribution calculation based on nozzle length on different grids with the results of the experiment is carried out. The coin- cidence to engineering accuracy of 5 % is received.

  19. Data of NODDI diffusion metrics in the brain and computer simulation of hybrid diffusion imaging (HYDI acquisition scheme

    Directory of Open Access Journals (Sweden)

    Chandana Kodiweera

    2016-06-01

    Full Text Available This article provides NODDI diffusion metrics in the brains of 52 healthy participants and computer simulation data to support compatibility of hybrid diffusion imaging (HYDI, “Hybrid diffusion imaging” [1] acquisition scheme in fitting neurite orientation dispersion and density imaging (NODDI model, “NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain” [2]. HYDI is an extremely versatile diffusion magnetic resonance imaging (dMRI technique that enables various analyzes methods using a single diffusion dataset. One of the diffusion data analysis methods is the NODDI computation, which models the brain tissue with three compartments: fast isotropic diffusion (e.g., cerebrospinal fluid, anisotropic hindered diffusion (e.g., extracellular space, and anisotropic restricted diffusion (e.g., intracellular space. The NODDI model produces microstructural metrics in the developing brain, aging brain or human brain with neurologic disorders. The first dataset provided here are the means and standard deviations of NODDI metrics in 48 white matter region-of-interest (ROI averaging across 52 healthy participants. The second dataset provided here is the computer simulation with initial conditions guided by the first dataset as inputs and gold standard for model fitting. The computer simulation data provide a direct comparison of NODDI indices computed from the HYDI acquisition [1] to the NODDI indices computed from the originally proposed acquisition [2]. These data are related to the accompanying research article “Age Effects and Sex Differences in Human Brain White Matter of Young to Middle-Aged Adults: A DTI, NODDI, and q-Space Study” [3].

  20. Hybrid schemes based on quantum mechanics/molecular mechanics simulations goals to success, problems, and perspectives.

    Science.gov (United States)

    Ferrer, Silvia; Ruiz-Pernía, Javier; Martí, Sergio; Moliner, Vicent; Tuñón, Iñaki; Bertrán, Juan; Andrés, Juan

    2011-01-01

    active site can be optimized to improve the transition state analogues (TSA) and to enhance the catalytic activity, even improve the active site to favor a desired direction of some promiscuous enzymes. In this chapter, we give a brief introduction, the state of the art, and future prospects and implications of enzyme design. Current computational tools to assist experimentalists for the design and engineering of proteins with desired catalytic properties are described. The interplay between enzyme design, molecular simulations, and experiments will be presented to emphasize the interdisciplinary nature of this research field. This text highlights the recent advances and examples selected from our laboratory are shown, of how the applications of these tools are a first attempt to de novo design of protein active sites. Identification of neutral/advantageous/deleterious mutation platforms can be exploited to penetrate some of Nature's closely guarded secrets of chemical reactivity. In this chapter, we give a brief introduction, the state of the art, and future prospects and implications of enzyme design. The first part describes briefly how the molecular modeling is carried out. Then, we discuss the requirements of hybrid quantum mechanical/molecular mechanics molecular dynamics (QM/MM MD) simulations, analyzing what are the basis of these theoretical methodologies, how we can use them with a view to its application in the study of enzyme catalysis, and what are the best methodologies for assessing its catalytic potential. In the second part, we focus on some selected examples, taking as a common guide the chorismate to prephenate rearrangement, studying the corresponding molecular mechanism in vacuo, in solution and in an enzyme environment. In addition, examples involving catalytic antibodies (CAs) and promiscuous enzymes will be presented. Finally, a special emphasis is made to provide some hints about the logical evolution that can be anticipated in this research

  1. 基于误差模型的混合分类算法%Error-based Hybrid Classification Algorithm

    Institute of Scientific and Technical Information of China (English)

    丛雪燕

    2014-01-01

    A new error-based approach of hybrid classification is presented , when data sets with binary objective variables are classified and it could increase the accuracy of classification .The paper also uses data sets to test the proposed approach and compares with the single classification .The results show that this method greatly improve the property , especially when it is pre-dicted by two methods and the rate of variance is higher , this hybrid approach had demonstrated impressive capacities to improve the prediction accuracy .%针对目标变量为二进制的数据集合进行分类,提出一种新的基于误差模型的混合分类方法,可以提高分类的精度。采用实际数据集作为测试数据,结果表明本文提出的算法性能优于其他的混合算法以及现有的单一使用的分类方法,尤其是当2种方法预测不一致的比率较高时,利用该方法能够显著地改善预测的准确性。

  2. A Comparison of the Astronomy and Astrophysics Abstracts (A&AA) and the American Institute of Physics (AIP) Physics and Astronomy Classification Schemes (PACS)

    Science.gov (United States)

    Warren, W. H., Jr.; Lubowic, D. A.

    The astronomy and astrophysics sections of the PACS are used by AIP to classify articles published in AIP, AIP member-society, and Russian translation journals for inclusion in abstract journals or computerized databases, and to prepare subject indexes. PACS has been extensively revised and enhanced over the last several years to become a detailed and flexible scheme designed for simplified and efficient retrieval of published papers from computerized bibliographical databases. We demonstrate the increased resolution and flexibility of the cur- rent PACS by mapping it to the presently-employed A&A classification scheme. We have prepared a concordance table between PACS (and the variant of PACS used for Physics Abstracts) and the A&AA classification scheme. The present PACS is well-suited for database retrieval and will be revised frequently to keep it current with the continuously changing fields of astronomy and astrophysics. We also compare and contrast the 250 PACS categories in astronomy and astrophysics with the alphabetical keyword lists used by A&AA or ApJ (ApJ, MNRAS, and A&A use a unified keyword list) to prepare their subject indexes. An electronic version of our concordance tables will be made available to the astronomical community.

  3. Effect of the size of the quantum region in a hybrid embedded-cluster scheme for zeolite systems

    Energy Technology Data Exchange (ETDEWEB)

    Shor, Alexei M., E-mail: as@icct.ru [Institute of Chemistry and Chemical Technology, Russian Academy of Sciences, 660049 Krasnoyarsk (Russian Federation); Shor, Elena A. Ivanova [Institute of Chemistry and Chemical Technology, Russian Academy of Sciences, 660049 Krasnoyarsk (Russian Federation)] [Siberian Federal University, 660041 Krasnoyarsk (Russian Federation); Laletina, Svetlana [Institute of Chemistry and Chemical Technology, Russian Academy of Sciences, 660049 Krasnoyarsk (Russian Federation); Nasluzov, Vladimir A. [Institute of Chemistry and Chemical Technology, Russian Academy of Sciences, 660049 Krasnoyarsk (Russian Federation)] [Siberian Federal University, 660041 Krasnoyarsk (Russian Federation); Vayssilov, Georgi N., E-mail: gnv@chem.uni-sofia.bg [Faculty of Chemistry, University of Sofia, 1126 Sofia (Bulgaria); Roesch, Notker, E-mail: roesch@mytum.de [Technische Universitaet Muenchen, Department Chemie and Catalysis Research Center, 85747 Garching (Germany)

    2009-09-18

    Recently we presented an improved scheme for constructing the border region within the covEPE hybrid quantum mechanics/molecular mechanics (QM/MM) embedded cluster approach for zeolites and covalent oxides in the framework of the elastic polarizable environment method. In the present study we explored how size and shape of the embedded QM cluster affect the results for structural features, energies, and characteristic vibrational frequencies of two model systems, adsorption complexes of H{sub 2}O and Rh{sub 6} in faujasite frameworks that contain Bronsted acid sites. Comparison of calculated characteristics of different QM cluster models suggests that the local structure and vibrational frequencies of acid sites in adsorbate-free zeolite are well reproduced with all embedded QM clusters, which contain from 5T to 14T atoms. A proper description of systems with an H{sub 2}O adsorbate requires larger QM clusters, with at least 8T atoms, whereas vibrational frequencies of OH groups participating in hydrogen bonds demand even larger quantum clusters, preferably with 12T or 14T atoms. The structure of the metal particle in adsorbed rhodium species is well reproduced with all QM clusters scrutinized, from 12T atoms. Larger QM models, with 18T or 24T atoms, are recommended when one aims at a high accuracy of Rh-O and Rh-H distances and characteristic energies.

  4. A hybrid cascade control scheme for the VFA and COD regulation in two-stage anaerobic digestion processes.

    Science.gov (United States)

    Méndez-Acosta, H O; Campos-Rodríguez, A; González-Álvarez, V; García-Sandoval, J P; Snell-Castro, R; Latrille, E

    2016-10-01

    A hybrid (continuous-discrete) cascade control is proposed to regulate both, volatile fatty acids (VFA) and chemical oxygen demand (COD) concentrations in two-stage (acidogenic-methanogenic) anaerobic digestion (TSAD) processes. The outer loop is a discrete controller that regulates the COD concentration of the methanogenic bioreactor by using a daily off-line measurement and that modifies the set-point tracked by inner loop, which manipulates the dilution rate to regulate the VFA concentration of the acidogenic bioreactor, estimated by continuous on-line conductivity measurements, avoiding acidification. The experimental validation was conducted in a TSAD process for the treatment of tequila vinasses during 110days. Results showed that the proposed cascade control scheme was able to achieve the VFA and COD regulation by using conventional measurements under different set-point values in spite of adverse common scenarios in full-scale anaerobic digestion processes. Microbial composition analysis showed that the controller also favors the abundance and diversity toward methane production.

  5. Efficient active feedback scheme of image multi-class classification%结合主动反馈的图像多分类框架

    Institute of Scientific and Technical Information of China (English)

    刘君; 王银辉; 李黎; 张宇

    2011-01-01

    为了解决图像语义分类中的训练数据不对称、小样本训练和噪声数据这3个难题,提出结合主动反馈的图像多分类框架.该框架将主动选择的策略应用到图像的多分类中,通过主动的选择出不确定的图片给用户手动标记,扩大训练图片集,提高分类的精度.为了验证该框架的有效性,提出一种有效的结合主动选择的图像多分类算法,即结合投票的DDAG SVM(decision directed acyclic graph support vector machine)算法.该算法提出了新的主动选择策略,即结合投票和旁移机制的主动选择策略.实验结果表明,该算法能有效应用到图像多分类中,比DDAGSVM和采用普通主动选择策略的DDAGSVM具有更高的分类的精度.%In order to solve three difficulties of image classification, including asymmetry of training data, small sample issue and noise sample problem, efficient active feedback scheme of image multi-class classification which introduce active selecting technique into image multi-class classification is proposed. By actively selecting doubtful images for users to label, more training samples can be gotten and more accurate classification can be done. In order to validate the scheme, an image multi-class classification algorithm combining with active selecting is fulfilled, which is named as DDAG SVM (decision directed acyclic graph support vector machine) with voting.Experiments show that the algorithm has more accuracy than DDAG SVM and DDAG SVM with normal selecting strategy, so it is efficient and the proposed scheme is also good for image multi-class classification.

  6. Text Classification using Association Rule with a Hybrid Concept of Naive Bayes Classifier and Genetic Algorithm

    CERN Document Server

    Kamruzzaman, S M; Hasan, Ahmed Ryadh

    2010-01-01

    Text classification is the automated assignment of natural language texts to predefined categories based on their content. Text classification is the primary requirement of text retrieval systems, which retrieve texts in response to a user query, and text understanding systems, which transform text in some way such as producing summaries, answering questions or extracting data. Now a day the demand of text classification is increasing tremendously. Keeping this demand into consideration, new and updated techniques are being developed for the purpose of automated text classification. This paper presents a new algorithm for text classification. Instead of using words, word relation i.e. association rules is used to derive feature set from pre-classified text documents. The concept of Naive Bayes Classifier is then used on derived features and finally a concept of Genetic Algorithm has been added for final classification. A system based on the proposed algorithm has been implemented and tested. The experimental ...

  7. Hybrid Brain–Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review

    Directory of Open Access Journals (Sweden)

    Keum-Shik Hong

    2017-07-01

    Full Text Available In this article, non-invasive hybrid brain–computer interface (hBCI technologies for improving classification accuracy and increasing the number of commands are reviewed. Hybridization combining more than two modalities is a new trend in brain imaging and prosthesis control. Electroencephalography (EEG, due to its easy use and fast temporal resolution, is most widely utilized in combination with other brain/non-brain signal acquisition modalities, for instance, functional near infrared spectroscopy (fNIRS, electromyography (EMG, electrooculography (EOG, and eye tracker. Three main purposes of hybridization are to increase the number of control commands, improve classification accuracy and reduce the signal detection time. Currently, such combinations of EEG + fNIRS and EEG + EOG are most commonly employed. Four principal components (i.e., hardware, paradigm, classifiers, and features relevant to accuracy improvement are discussed. In the case of brain signals, motor imagination/movement tasks are combined with cognitive tasks to increase active brain–computer interface (BCI accuracy. Active and reactive tasks sometimes are combined: motor imagination with steady-state evoked visual potentials (SSVEP and motor imagination with P300. In the case of reactive tasks, SSVEP is most widely combined with P300 to increase the number of commands. Passive BCIs, however, are rare. After discussing the hardware and strategies involved in the development of hBCI, the second part examines the approaches used to increase the number of control commands and to enhance classification accuracy. The future prospects and the extension of hBCI in real-time applications for daily life scenarios are provided.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. Power Budget Analysis of Colorless Hybrid WDM/TDM-PON Scheme Using Downstream DPSK and Re-modulated Upstream OOK Data Signals

    Science.gov (United States)

    Khan, Yousaf; Afridi, Muhammad Idrees; Khan, Ahmed Mudassir; Rehman, Waheed Ur; Khan, Jahanzeb

    2014-09-01

    Hybrid wavelength-division multiplexed/time-division multiplexed passive optical access networks (WDM/TDM-PONs) combine the advance features of both WDM and TDM PONs to provide a cost-effective access network solution. We demonstrate and analyze the transmission performances and power budget issues of a colorless hybrid WDM/TDM-PON scheme. A 10-Gb/s downstream differential phase shift keying (DPSK) and remodulated upstream on/off keying (OOK) data signals are transmitted over 25 km standard single mode fiber. Simulation results show error free transmission having adequate power margins in both downstream and upstream transmission, which prove the applicability of the proposed scheme to future passive optical access networks. The power budget confines both the PON splitting ratio and the distance between the Optical Line Terminal (OLT) and Optical Network Unit (ONU).

  10. Development of a continuum/rarefied hybrid scheme for flows with thermal and chemical non-equilibrium

    Science.gov (United States)

    Michaelis, Christopher Harold

    2001-07-01

    The motion of a gas may be studied from the microscopic or macroscopic point of view. At the microscopic level, molecules are constantly moving and colliding, and occasionally reacting to form new species. The accepted model for describing gases at the microscopic level is the Boltzmann equation. In contrast, macroscopic models rely on the conservation laws, combined with constitutive relations, which approximate the molecular relaxation in a gas. The resulting set of equations, called the Navier- Stokes equations, represent an approximation to the Boltzmann equation for small non-equilibrium. For flows that are sufficiently rarefied, the Navier- Stokes equations no longer represent an accurate approximation of the Boltzmann equation. Numerical solutions of the Boltzmann equation may be obtained through the direct simulation of molecular motion. Such approaches are termed Monte Carlo, or particle methods. In principle, particle methods can be used to simulate all flows, regardless of the degree of non-equilibrium. There are many instances where neither approach is ideal. One such example is the reentry of a blunt body through the atmosphere. Ahead of the body, there is a very strong shock wave that cannot be adequately modeled by the Navier-Stokes equations, due to the degree of non- equilibrium. At the surface of the blunt body, the temperature is substantially colder than the surrounding flow, resulting in a large increase in the density next to the surface. In this region, where the flow is near- continuum, particle methods are not computationally efficient. A numerical method that utilizes the Navier-Stokes equations in regions of near-continuum flow and a particle method everywhere else is ideal. In this study, a hybrid scheme, for the efficient numerical simulation of flows with thermal and chemical non-equilibrium, is successfully demonstrated. The hybrid method was applied to extreme, high Mach number flows, where vibrational and chemical relaxation are

  11. Novel Reactor Relevant RF Actuator Schemes for the Lower Hybrid and the Ion Cyclotron Range of Frequencies

    Science.gov (United States)

    Bonoli, Paul

    2014-10-01

    This paper presents a fresh physics perspective on the onerous problem of coupling and successfully utilizing ion cyclotron range of frequencies (ICRF) and lower hybrid range of frequencies (LHRF) actuators in the harsh environment of a nuclear fusion reactor. The ICRF and LH launchers are essentially first wall components in a fusion reactor and as such will be subjected to high heat fluxes. The high field side (HFS) of the plasma offers a region of reduced heat flux together with a quiescent scrape off layer (SOL). Placement of the ICRF and LHRF launchers on the tokamak HFS also offers distinct physics advantages: The higher toroidal magnetic field makes it possible to couple faster phase velocity LH waves that can penetrate farther into the plasma core and be absorbed by higher energy electrons, thereby increasing the current drive efficiency. In addition, re-location of the LH launcher off the mid-plane (i.e., poloidal ``steering'') allows further control of the deposition location. Also ICRF waves coupled from the HFS couple strongly to mode converted ion Bernstein waves and ion cyclotron waves waves as the minority density is increased, thus opening the possibility of using this scheme for flow drive and pressure control. Finally the quiescent nature of the HFS scrape off layer should minimize the effects of RF wave scattering from density fluctuations. Ray tracing / Fokker Planck simulations will be presented for LHRF applications in devices such as the proposed Advanced Divertor Experiment (ADX) and extending to ITER and beyond. Full-wave simulations will also be presented which demonstrate the possible combinations of electron and ion heating via ICRF mode conversion. Work supported by the US DoE under Contract Numbers DE-FC02-01ER54648 and DE-FC02-99ER54512.

  12. AN UNCONDITIONALLY STABLE HYBRID FE-FD SCHEME FOR SOLVING A 3-D HEAT TRANSPORT EQUATION IN A CYLINDRICAL THIN FILM WITH SUB-MICROSCALE THICKNESS

    Institute of Scientific and Technical Information of China (English)

    Wei-zhong Dai; Raja Nassar

    2003-01-01

    Heat transport at the microscale is of vital importance in microtechnology applications.The heat transport equation is different from the traditional heat transport equation sincea second order derivative of temperature with respect to time and a third-order mixedderivative of temperature with respect to space and time are introduced. In this study,we develop a hybrid finite element-finite difference (FE-FD) scheme with two levels intime for the three dimensional heat transport equation in a cylindrical thin film with sub-microscale thickness. It is shown that the scheme is unconditionally stable. The scheme isthen employed to obtain the temperature rise in a sub-microscale cylindrical gold film. Themethod can be applied to obtain the temperature rise in any thin films with sub-microscalethickness, where the geometry in the planar direction is arbitrary.

  13. EFFECTIVE AND SECURE CERTIFICATELESS HYBRID SIGNCRYPTION SCHEME%高效安全的无证书混合签密方案

    Institute of Scientific and Technical Information of China (English)

    冯巧娟; 沙锋

    2013-01-01

    Cryptanalysis is carried out on two new certificateless hybrid signcryption schemes , the correctness and security flaws of their own respectively are pointed out in the paper .Then we propose a more secure and efficient certificateless hybrid signcryption scheme .The use of exponential operations are eluded in new signcryption scheme through introducing the vBNN -IBS signature algorithm , and this also further reduces the computational costs of the new scheme .In random oracle model , the new scheme has been verified safe enough to achieve the un-forgeability and confidentiality .Comparative analysis shows that the new scheme has strong security with low computation overhead .%对两种新提出的无证书混合签密方案进行密码学分析,指出它们各自存在的正确性和安全性缺陷,进而提出一种更加安全和高效的无证书混合签密方案。通过引入vBNN-IBS签名算法,从而避免使用幂指数运算,进一步降低新方案的计算开销。在随机预言机模型下,新方案被证明是安全的,满足不可伪造性和机密性。对比分析表明,新方案在确保强安全性的同时具有更低的计算开销。

  14. Design and simulation of a fuel cell hybrid emergency power system for a more electric aircraft: Evaluation of energy management schemes

    Science.gov (United States)

    Njoya Motapon, Souleman

    As the aircraft industries are moving toward more electric aircraft (MEA), the electrical peak load seen by the main and emergency generators becomes higher than in conventional aircraft. Consequently, there is a major concern regarding the aircraft emergency system, which consists of a ram air turbine (RAT) or air driven generator (ADG), to fulfill the load demand during critical situations; particularly at low aircraft speed where the output power is very low. A potential solution under study by most aircraft manufacturers is to replace the air turbine by a fuel cell hybrid system, consisting of fuel cell combined with other high power density sources such as supercapacitors or lithium-ion batteries. To ensure the fuel cell hybrid system will be able to meet the load demand, it must be properly designed and an effective energy management strategy must be tested with real situations load profile. This work aims at designing a fuel cell emergency power system of a more electric aircraft and comparing different energy management schemes (EMS); with the goal to ensure the load demand is fully satisfied within the constraints of each energy source. The fuel cell hybrid system considered in this study consists of fuel cell, lithium-ion batteries and supercapacitors, along with associated DC-DC and DC-AC converters. The energy management schemes addressed are state-of-the-art, most commonly used energy management techniques in fuel cell vehicle applications and include: the state machine control strategy, the rule based fuzzy logic strategy, the classical PI control strategy, the frequency decoupling/fuzzy logic control strategy and the equivalent consumption minimization strategy (ECMS). Moreover, a new optimal scheme based on maximizing the instantaneous energy of batteries/supercapacitors, to improve the fuel economy is proposed. An off-line optimization based scheme is also developed to ascertain the validity of the proposed strategy in terms of fuel consumption

  15. The classification of frequencies in the {\\gamma} Doradus / {\\delta} Scuti hybrid star HD 49434

    OpenAIRE

    Brunsden, E.; Pollard, K.R.; Cottrell, P. L.; Uytterhoeven, K.; Wright, D J; De Cat, P.

    2014-01-01

    Hybrid stars of the {\\gamma} Doradus and {\\delta} Scuti pulsation types have great potential for asteroseismic analysis to explore their interior structure. To achieve this, mode identi- fications of pulsational frequencies observed in the stars must be made, a task which is far from simple. In this work we begin the analysis by scrutinizing the frequencies found in the CoRoT photometric satellite measurements and ground-based high-resolution spectroscopy of the hybrid star HD 49434. The resu...

  16. A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression

    Directory of Open Access Journals (Sweden)

    Hilario Gómez-Moreno

    2014-01-01

    Full Text Available We present a new impulse noise removal technique based on Support Vector Machines (SVM. Both classification and regression were used to reduce the “salt and pepper” noise found in digital images. Classification enables identification of noisy pixels, while regression provides a means to determine reconstruction values. The training vectors necessary for the SVM were generated synthetically in order to maintain control over quality and complexity. A modified median filter based on a previous noise detection stage and a regression-based filter are presented and compared to other well-known state-of-the-art noise reduction algorithms. The results show that the filters proposed achieved good results, outperforming other state-of-the-art algorithms for low and medium noise ratios, and were comparable for very highly corrupted images.

  17. The XMM large scale structure survey: optical vs. X-ray classifications of active galactic nuclei and the unified scheme

    CERN Document Server

    Garcet, O; Gosset, E; Sprimont, P G; Surdej, J; Borkowski, V; Tajer, M; Pacaud, F; Pierre, M; Chiappetti, L; MacCagni, D; Page, M J; Carrera, F J; Tedds, J A; Mateos, S; Krumpe, M; Contini, T; Corral, A; Ebrero, J; Gavignaud, I; Schwope, A; Le Fèvre, O; Polletta, M; Rosen, S; Lonsdale, C; Watson, M; Borczyk, W; Väisänen, P

    2007-01-01

    Our goal is to characterize AGN populations by comparing their X-ray and optical classifications. We present a sample of 99 spectroscopically identified X-ray point sources in the XMM-LSS survey which are significantly detected in the [2-10] keV band, and with more than 80 counts. We performed an X-ray spectral analysis for all of these 99 X-ray sources. Introducing the fourfold point correlation coefficient, we find only a mild correlation between the X-ray and the optical classifications, as up to 30% of the sources have differing X-ray and optical classifications: on one hand, 10% of the type 1 sources present broad emission lines in their optical spectra and strong absorption in the X-rays. These objects are highly luminous AGN lying at high redshift and thus dilution effects are totally ruled out, their discrepant nature being an intrinsic property. Their X-ray luminosities and redshifts distributions are consistent with those of the unabsorbed X-ray sources with broad emission lines. On the other hand, ...

  18. Classification of Eucalyptus urograndis hybrids under different water availability based on biometric traits

    Directory of Open Access Journals (Sweden)

    Claudia D. Silva

    2014-08-01

    Full Text Available Aim of study: The eucalyptus grows rapidly and is well suitable to edaphic and bioclimatic conditions in several regions of of the world. The aim of this study was to assess the performance of Eucalyptus urograndis hybrids grown under different water availability conditions.Area of study: The study was performed in south-eastern of BrazilMaterial and Methods: We evaluated five commercial hybrids cultivated in pots with the substrate maintained at 65, 50, 35 and 20% maximum water retention capacity. The evaluation was based on the following characteristics: total height (cm, diameter (mm, number of leaves, leaf area (dm2, and dry weight (g plant-1 of leaf, stem + branches,   root, shoot and total and root/shoot ratio.Main results: All the characteristics evaluated were adversely affected by reduced availability of water in the substrate. The hybrids assessed performed differently in terms of biometric characteristics, irrespective of water availability. Water deficit resulted in a greater reduction in the dry weight production compared to number of leaves, diameter and height. Hybrids H2 and H5 have favorable traits for tolerating drought. The hybrid H2 shows a stronger slowdown in growth as soil moisture levels drop, although its growth rate is low, and H5 increases the root/shoot ratio but maintains growth in terms of height, even under drought conditions.Research highlights: The results obtained in our experiment show that productive hybrids sensitive to drought could also perform better under water deficit conditions, maintaining satisfactory growth despite significant drops in these characteristics.Keywords: Eucalyptus urograndis; water deficit; drought tolerance. 

  19. A hybrid approach to software repository retrieval: Blending faceted classification and type signatures

    Science.gov (United States)

    Eichmann, David A.

    1992-01-01

    We present a user interface for software reuse repository that relies both on the informal semantics of faceted classification and the formal semantics of type signatures for abstract data types. The result is an interface providing both structural and qualitative feedback to a software reuser.

  20. A Hybrid LDA+gCCA Model for fMRI Data Classification and Visualization.

    Science.gov (United States)

    Afshin-Pour, Babak; Shams, Seyed-Mohammad; Strother, Stephen

    2015-05-01

    Linear predictive models are applied to functional MRI (fMRI) data to estimate boundaries that predict experimental task states for scans. These boundaries are visualized as statistical parametric maps (SPMs) and range from low to high spatial reproducibility across subjects (e.g., Strother , 2004; LaConte , 2003). Such inter-subject pattern reproducibility is an essential characteristic of interpretable SPMs that generalize across subjects. Therefore, we introduce a flexible hybrid model that optimizes reproducibility by simultaneously enhancing the prediction power and reproducibility. This hybrid model is formed by a weighted summation of the optimization functions of a linear discriminate analysis (LDA) model and a generalized canonical correlation (gCCA) model (Afshin-Pour , 2012). LDA preserves the model's ability to discriminate the fMRI scans of multiple brain states while gCCA finds a linear combination for each subject's scans such that the estimated boundary map is reproducible. The hybrid model is implemented in a split-half resampling framework (Strother , 2010) which provides reproducibility (r) and prediction (p) quality metrics. Then the model was compared with LDA, and Gaussian Naive Bayes (GNB). For simulated fMRI data, the hybrid model outperforms the other two techniques in terms of receiver operating characteristic (ROC) curves, particularly for detecting less predictable but spatially reproducible networks. These techniques were applied to real fMRI data to estimate the maps for two task contrasts. Our results indicate that compared to LDA and GNB, the hybrid model can provide maps with large increases in reproducibility for small reductions in prediction, which are jointly closer to the ideal performance point of (p=1, r=1).

  1. Use of conventional taxonomy, electrophoretic karyotyping and DNA-DNA hybridization for the classification of fermentative apiculate yeasts.

    Science.gov (United States)

    Vaughan-Martini, A; Angelini, P; Cardinali, G

    2000-07-01

    A taxonomic study was conducted that considered strains of the genera Hanseniaspora/Kloeckera held in the Industrial Yeasts Collection (DBVPG) of the Dipartimento di Biologia Vegetale of the Università di Perugia, Italy. Standard phenotypic as well as molecular criteria were considered in a effort to revisit the classification of these strains, some of which have been in the collection for about 50 years. Results of salient physiological tests showed that some of the DBVPG and type strains could not be identified by current taxonomic keys. Electrophoretic karyotypes were identical for some species, with the type strains of the seven accepted species showing only five distinct chromosomal patterns. DNA-DNA hybridization analyses, using a non-radioactive dot-blot technique, allowed for the distinction of taxa. The taxonomic implications of these results are discussed.

  2. Improved Transceive Scheme for Hybrid Multiple Input Multiple Output System%改进的混合多输入多输出系统收发方案

    Institute of Scientific and Technical Information of China (English)

    张建忠; 李宏伟; 邓冬虎; 耿耿

    2011-01-01

    In order to seek tradeoffs between spectral efficiency and data reliability, this paper presents an efficient and low-complexity transceiver scheme for the hybrid STBC-VBLAST(Vertical Bell Labs layered Space-Time) systems. The hybrid Multiple lnput Multiple Output(MIMO)communication systems can achieve multiplexing gain and diversity gain. The symbols are transmitted as VBLAST coding systems by exploiting the linear dispersion codes. An Ordered, Successive Interference Cancellation(OSIC) decoding algorithm based on sorted QR decomposition is proposed. Simulation results show the scheme outperforms other hybrid schemes in Bit Error Rate(BER) and computing complexity.%为在频谱利用率和可靠性之间取得折中,提出一种高效低复杂度的发射接收方案,将空间复用和空间分集相结合,形成一个STBC-VBLAST混合编码的多输入多输出系统.利用线性疏散码的结构特点,在发射端以等效的垂直分层空时码子层发送信号,接收端使用基于排序的QR分解的连续干扰抵消的算法进行译码,同样可以获得较好的复用和分集增益.仿真结果表明,该方案的误码率性能优于其他检测方案,可降低计算复杂度.

  3. OPTIMIZATION ABOUT COMBINED HYBRID SCHEME WITH 5-PARAMETER STRESS MODE%5参数应力组合杂交格式优化

    Institute of Scientific and Technical Information of China (English)

    聂玉峰; 尹云辉; 周天孝

    2004-01-01

    It is posed in paper [1] that Zero energy-error can be used to realize the optimization of Combined hybrid finite element methods through adjusting the combined factor. In this paper, the optimization method is used to plane 4-node quadrilateral Combined hybrid scheme CH(0-1) which own 5 stress parameters with energy compatibility characteristic. Based on the optimization results, the analysis of components of element stiffness matrix, and the conclusions about numerical stability and convergence, this paper deduces that the optimal form of CH(0-1) element, is let the combined factor take 1, i.e., just base on Hellinger-Reissner variational principle, and take bilinear compatible displacement interpolation instead of enrich-strain Wilson's displacements interpolation for the orthgonality of 5-parameter stresses mode with the derived strain from Wilson bubble displacements and the weak force balance.

  4. Pap Smear Diagnosis Using a Hybrid Intelligent Scheme Focusing on Genetic Algorithm Based Feature Selection and Nearest Neighbor Classification

    DEFF Research Database (Denmark)

    Marinakis, Yannis; Dounias, Georgios; Jantzen, Jan

    2009-01-01

    The term pap-smear refers to samples of human cells stained by the so-called Papanicolaou method. The purpose of the Papanicolaou method is to diagnose pre-cancerous cell changes before they progress to invasive carcinoma. In this paper a metaheuristic algorithm is proposed in order to classify t...... other previously applied intelligent approaches....

  5. Design Hybrid method for intrusion detection using Ensemble cluster classification and SOM network

    OpenAIRE

    Deepak Rathore; Anurag Jain

    2012-01-01

    In current scenario of internet technology security is big challenge. Internet network threats by various cyber-attack and loss the system data and degrade the performance of host computer. In this sense intrusion detection are challenging field of research in concern of network security based on firewall and some rule based detection technique. In this paper we proposed an Ensemble Cluster Classification technique using som network for detection of mixed variable data generated by malicious ...

  6. Hybrid three-dimensional and support vector machine approach for automatic vehicle tracking and classification using a single camera

    Science.gov (United States)

    Kachach, Redouane; Cañas, José María

    2016-05-01

    Using video in traffic monitoring is one of the most active research domains in the computer vision community. TrafficMonitor, a system that employs a hybrid approach for automatic vehicle tracking and classification on highways using a simple stationary calibrated camera, is presented. The proposed system consists of three modules: vehicle detection, vehicle tracking, and vehicle classification. Moving vehicles are detected by an enhanced Gaussian mixture model background estimation algorithm. The design includes a technique to resolve the occlusion problem by using a combination of two-dimensional proximity tracking algorithm and the Kanade-Lucas-Tomasi feature tracking algorithm. The last module classifies the shapes identified into five vehicle categories: motorcycle, car, van, bus, and truck by using three-dimensional templates and an algorithm based on histogram of oriented gradients and the support vector machine classifier. Several experiments have been performed using both real and simulated traffic in order to validate the system. The experiments were conducted on GRAM-RTM dataset and a proper real video dataset which is made publicly available as part of this work.

  7. The classification of frequencies in the {\\gamma} Doradus / {\\delta} Scuti hybrid star HD 49434

    CERN Document Server

    Brunsden, E; Cottrell, P L; Uytterhoeven, K; Wright, D J; De Cat, P

    2014-01-01

    Hybrid stars of the {\\gamma} Doradus and {\\delta} Scuti pulsation types have great potential for asteroseismic analysis to explore their interior structure. To achieve this, mode identi- fications of pulsational frequencies observed in the stars must be made, a task which is far from simple. In this work we begin the analysis by scrutinizing the frequencies found in the CoRoT photometric satellite measurements and ground-based high-resolution spectroscopy of the hybrid star HD 49434. The results show almost no consistency between the frequencies found using the two techniques and no characteristic period spacings or couplings were identified in either dataset. The spectroscopic data additionally show no evidence for any long term (5 year) variation in the dominant frequency. The 31 spectroscopic frequencies identified have standard deviation profiles suggesting multiple modes sharing (l, m) in the {\\delta} Scuti frequency region and several skewed modes sharing the same (l, m) in the {\\gamma} Doradus frequenc...

  8. A HYBRID APPROACH USING C MEAN AND CART FOR CLASSIFICATION IN DATA MINING

    Directory of Open Access Journals (Sweden)

    Jasbir Malik

    2012-09-01

    Full Text Available Data Mining is a field of search and researches ofdata. Mining the data means fetching out a piece ofdata from a huge data block. The basic work in thedata mining can be categorized in two subsequentways. One is called classification and the other iscalled clustering. Although both refers to some kind ofsame region but still there are differences in both theterms. The classification of the data is only possible ifyou have modified and identified the clusters. In thepresented research paper, our aim is to find out themaximum number of clusters in a specified region byapplying the area searching algorithms. Classificationis always based on two things. aThe area which youchoose for the classification that is the cluster region.bThe kind of dataset which you are going to apply onthe selected region .To increase the accuracy of thesearching technique, any one would need to focus ontwo things . aWhether the data set has been cauterizedin proper manner or not .bIf the clusters are defined ,whether they fit into the appropriate classified area ornot .

  9. Applicability of in vitro tests for skin irritation and corrosion to regulatory classification schemes: substantiating test strategies with data from routine studies.

    Science.gov (United States)

    Kolle, Susanne N; Sullivan, Kristie M; Mehling, Annette; van Ravenzwaay, Bennard; Landsiedel, Robert

    2012-12-01

    Skin corrosion or irritation refers to the production of irreversible or reversible damage to the skin following the application of a test substance, respectively. Traditionally, hazard assessments are conducted using the in vivo Draize skin test, but recently in vitro tests using reconstructed human epidermis (RhE) models have gained regulatory acceptance. In this study, skin corrosion (SCT) and irritation tests (SIT) using a RhE model were implemented to reduce the number of in vivo tests required by regulatory bodies. One hundred and thirty-four materials were tested from a wide range of substance classes included 46 agrochemical formulations. Results were assessed according to UN GHS, EU-CLP, ANVISA and US EPA classification schemes. There was high correlation between the two in vitro tests. Assessment of the SCT sensitivity was not possible due to the limited number of corrosives in the data set; SCT specificity and accuracy were 89% for all classification systems. Accuracy (63-76%) and sensitivity (53-67%) were low in the SIT. Specificity and concordance for agrochemical formulations alone in both the SCT and SIT were comparable to the values for the complete data set (SCT: 91% vs. 89% specificity, 91% vs. 89% accuracy and SIT: 64-88% vs. 70-85% specificity, 56-75% vs. 63-76% accuracy).

  10. Classification of Medical Datasets Using SVMs with Hybrid Evolutionary Algorithms Based on Endocrine-Based Particle Swarm Optimization and Artificial Bee Colony Algorithms.

    Science.gov (United States)

    Lin, Kuan-Cheng; Hsieh, Yi-Hsiu

    2015-10-01

    The classification and analysis of data is an important issue in today's research. Selecting a suitable set of features makes it possible to classify an enormous quantity of data quickly and efficiently. Feature selection is generally viewed as a problem of feature subset selection, such as combination optimization problems. Evolutionary algorithms using random search methods have proven highly effective in obtaining solutions to problems of optimization in a diversity of applications. In this study, we developed a hybrid evolutionary algorithm based on endocrine-based particle swarm optimization (EPSO) and artificial bee colony (ABC) algorithms in conjunction with a support vector machine (SVM) for the selection of optimal feature subsets for the classification of datasets. The results of experiments using specific UCI medical datasets demonstrate that the accuracy of the proposed hybrid evolutionary algorithm is superior to that of basic PSO, EPSO and ABC algorithms, with regard to classification accuracy using subsets with a reduced number of features.

  11. Hybrid Data Hiding Scheme Using Right-Most Digit Replacement and Adaptive Least Significant Bit for Digital Images

    Directory of Open Access Journals (Sweden)

    Mehdi Hussain

    2016-05-01

    Full Text Available The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR with an adaptive least significant bit (ALSB is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns and higher texture (asymmetry patterns areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images are conducted with recent least significant bit (LSB-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR.

  12. Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification

    Directory of Open Access Journals (Sweden)

    R. Rajesh Sharma

    2015-01-01

    algorithm (RGSA. Support vector machines, over backpropagation network, and k-nearest neighbor are used to evaluate the goodness of classifier approach. The preliminary evaluation of the system is performed using 320 real-time brain MRI images. The system is trained and tested by using a leave-one-case-out method. The performance of the classifier is tested using the receiver operating characteristic curve of 0.986 (±002. The experimental results demonstrate the systematic and efficient feature extraction and feature selection algorithm to the performance of state-of-the-art feature classification methods.

  13. Design Hybrid method for intrusion detection using Ensemble cluster classification and SOM network

    Directory of Open Access Journals (Sweden)

    Deepak Rathore

    2012-09-01

    Full Text Available In current scenario of internet technology security is bigchallenge. Internet network threats by various cyber-attackand loss the system data and degrade the performance ofhost computer. In this sense intrusion detection arechallenging field of research in concern of networksecurity based on firewall and some rule based detectiontechnique. In this paper we proposed an Ensemble ClusterClassification technique using som network for detectionof mixed variable data generated by malicious software forattack purpose in host system. In our methodology SOMnetwork control the iteration of distance of differentparameters of ensembling our experimental result showthat better empirical evaluation on KDD data set 99 incomparison of existing ensemble classifier.

  14. CLASSIFICATION OF NEURAL NETWORK FOR TECHNICAL CONDITION OF TURBOFAN ENGINES BASED ON HYBRID ALGORITHM

    Directory of Open Access Journals (Sweden)

    Valentin Potapov

    2016-12-01

    Full Text Available Purpose: This work presents a method of diagnosing the technical condition of turbofan engines using hybrid neural network algorithm based on software developed for the analysis of data obtained in the aircraft life. Methods: allows the engine diagnostics with deep recognition to the structural assembly in the presence of single structural damage components of the engine running and the multifaceted damage. Results: of the optimization of neural network structure to solve the problems of evaluating technical state of the bypass turbofan engine, when used with genetic algorithms.

  15. Modeling and Analysis of Hybrid Cellular/WLAN Systems with Integrated Service-Based Vertical Handoff Schemes

    Science.gov (United States)

    Xia, Weiwei; Shen, Lianfeng

    We propose two vertical handoff schemes for cellular network and wireless local area network (WLAN) integration: integrated service-based handoff (ISH) and integrated service-based handoff with queue capabilities (ISHQ). Compared with existing handoff schemes in integrated cellular/WLAN networks, the proposed schemes consider a more comprehensive set of system characteristics such as different features of voice and data services, dynamic information about the admitted calls, user mobility and vertical handoffs in two directions. The code division multiple access (CDMA) cellular network and IEEE 802.11e WLAN are taken into account in the proposed schemes. We model the integrated networks by using multi-dimensional Markov chains and the major performance measures are derived for voice and data services. The important system parameters such as thresholds to prioritize handoff voice calls and queue sizes are optimized. Numerical results demonstrate that the proposed ISHQ scheme can maximize the utilization of overall bandwidth resources with the best quality of service (QoS) provisioning for voice and data services.

  16. Hybrid wide-band, low-phase-noise scheme for Raman lasers in atom interferometry by integrating an acousto-optic modulator and a feedback loop.

    Science.gov (United States)

    Wang, Kai; Yao, Zhanwei; Li, Runbing; Lu, Sibin; Chen, Xi; Wang, Jin; Zhan, Mingsheng

    2016-02-10

    We report a hybrid scheme for phase-coherent Raman lasers with low phase noise in a wide frequency range. In this scheme, a pair of Raman lasers with a frequency difference of 3.04 GHz is generated by the ±1-order diffracted lights of an acousto-optic modulator (1.52 GHz), where a feedback loop is simultaneously applied for suppressing the phase noise. The beat width of the Raman lasers is narrower than 3 Hz. In the low-frequency range, the phase noise of the Raman lasers is suppressed by 35 dB with the feedback. The phase noise is less than -109  dBc/Hz in the high-frequency range. The sensitivity of an atom gyroscope employing the hybrid Raman lasers can be implicitly improved 10 times. Due to the better high-frequency response, the sensitivity is not limited by the durations of Raman pulses. This work is important for improving the performance of atom-interferometer-based measurements.

  17. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  18. A hybrid particle swarm optimization-SVM classification for automatic cardiac auscultation

    Directory of Open Access Journals (Sweden)

    Prasertsak Charoen

    2017-04-01

    Full Text Available Cardiac auscultation is a method for a doctor to listen to heart sounds, using a stethoscope, for examining the condition of the heart. Automatic cardiac auscultation with machine learning is a promising technique to classify heart conditions without need of doctors or expertise. In this paper, we develop a classification model based on support vector machine (SVM and particle swarm optimization (PSO for an automatic cardiac auscultation system. The model consists of two parts: heart sound signal processing part and a proposed PSO for weighted SVM (WSVM classifier part. In this method, the PSO takes into account the degree of importance for each feature extracted from wavelet packet (WP decomposition. Then, by using principle component analysis (PCA, the features can be selected. The PSO technique is used to assign diverse weights to different features for the WSVM classifier. Experimental results show that both continuous and binary PSO-WSVM models achieve better classification accuracy on the heart sound samples, by reducing system false negatives (FNs, compared to traditional SVM and genetic algorithm (GA based SVM.

  19. Classification of Human Emotion from Deap EEG Signal Using Hybrid Improved Neural Networks with Cuckoo Search

    Directory of Open Access Journals (Sweden)

    M. Sreeshakthy

    2016-01-01

    Full Text Available Department of Computer Science and Engineering,Anna University Regional Centre, Coimbatore, Indiam.sribtechit@gmail.comJ. PreethiDepartment of Computer Science and EngineeringAnna University Regional Centre, Coimbatore, Indiapreethi17j@yahoo.comEmotions are very important in human decision handling, interaction and cognitive process. In this paper describes that recognize the human emotions from DEAP EEG dataset with different kind of methods. Audio – video based stimuli is used to extract the emotions. EEG signal is divided into different bands using discrete wavelet transformation with db8 wavelet function for further process. Statistical and energy based features are extracted from the bands, based on the features emotions are classified with feed forward neural network with weight optimized algorithm like PSO. Before that the particular band has to be selected based on the training performance of neural networks and then the emotions are classified. In this experimental result describes that the gamma and alpha bands are provides the accurate classification result with average classification rate of 90.3% of using NNRBF, 90.325% of using PNN, 96.3% of using PSO trained NN, 98.1 of using Cuckoo trained NN. At last the emotions are classified into two different groups like valence and arousal. Based on that identifies the person normal and abnormal behavioral using classified emotion.

  20. Classification of Human Emotion from Deap EEG Signal Using Hybrid Improved Neural Networks with Cuckoo Search

    Directory of Open Access Journals (Sweden)

    M. Sreeshakthy

    2016-01-01

    Full Text Available Department of Computer Science and Engineering,Anna University Regional Centre, Coimbatore, Indiam.sribtechit@gmail.comJ. PreethiDepartment of Computer Science and EngineeringAnna University Regional Centre, Coimbatore, Indiapreethi17j@yahoo.comEmotions are very important in human decision handling, interaction and cognitive process. In this paper describes that recognize the human emotions from DEAP EEG dataset with different kind of methods. Audio – video based stimuli is used to extract the emotions. EEG signal is divided into different bands using discrete wavelet transformation with db8 wavelet function for further process. Statistical and energy based features are extracted from the bands, based on the features emotions are classified with feed forward neural network with weight optimized algorithm like PSO. Before that the particular band has to be selected based on the training performance of neural networks and then the emotions are classified. In this experimental result describes that the gamma and alpha bands are provides the accurate classification result with average classification rate of 90.3% of using NNRBF, 90.325% of using PNN, 96.3% of using PSO trained NN, 98.1 of using Cuckoo trained NN. At last the emotions are classified into two different groups like valence and arousal. Based on that identifies the person normal and abnormal behavioral using classified emotion.

  1. 'Tropicalisation' of feed-in tariffs. A custom-made support scheme for hybrid PV/diesel systems in isolated regions

    Energy Technology Data Exchange (ETDEWEB)

    Solano-Peralta, Mauricio; Van Sark, Wilfried G.J.H.M. [Department of Science, Technology and Society, Copernicus Institute for Sustainable Development and Innovation, Utrecht University, Heidelberglaan 2, 3584 CS Utrecht (Netherlands); Moner-Girona, Magda [Renewable Energies Unit, Institute for Energy, European Commission-Joint Research Centre, Via E. Fermi 2749 - TP 450 I-21027 Ispra (Italy); Vallve, Xavier [Trama Tecnoambiental, Ripolles 46, 08026 Barcelona (Spain)

    2009-12-15

    The interest and actions towards introducing renewables for off-grid regions has increased due to their ostensible cost-effectiveness, eco-friendliness and quality services provided. Nevertheless, in many isolated areas diesel generators appear as a common option, confirming that there is a need for financial support mechanisms that aid the introduction of renewables due to their higher initial investment costs. This paper proposes a so-called 'tropicalisation' of the Feed-in Tariff scheme to promote the introduction of hybrid systems in isolated communities based on the idea of awarding for each kWh produced by renewable energies a premium value during a guaranteed period of time. The proposed Renewable Energy Premium Tariff (RPT) scheme is an alternative mechanism to the usual initial investment donation for off-grid energy development projects by recognising the production of renewable electricity and opting for a long-term sustainability of the projects. Ecuador presents ideal conditions to study the introduction of such a 'tropicalised' scheme since a Feed-in Law including off-grid projects was established in 2002 and since there are governmental and local efforts for the introduction of renewable hybrids in isolated regions. Modelling of the introduction of photovoltaics (PVs) into diesel systems for several mini-grids located in isolated regions of Ecuador has been performed, and included a detailed financial analysis for optimisation of RPT values and a comparison with existing stand-alone diesel systems. The results show the cost-effectiveness of PV/diesel hybrids over diesel gensets, taking into account present and future diesel prices. To obtain long-term sustainability of the project, the RPT values are set at 0.70-1.20$kWh covering the operability of the whole system for 20 years, where the renewable fraction should have the largest share in the hybrid system. The proposed mechanism is expected to aid the introduction of renewable

  2. Application of the linear/exponential hybrid force field scaling scheme to the bond length alternation modes of polyacetylene

    Science.gov (United States)

    Yang, Shujiang; Kertesz, Miklos

    2006-12-01

    The two bond length alternation related backbone carbon-carbon stretching Raman active normal modes of polyacetylene are notoriously difficulty to predict theoretically. We apply our new linear/exponential scaled quantum mechanical force field scheme to tackle this problem by exponentially adjusting the decay of the coupling force constants between backbone stretchings based on their distance which extends over many neighbors. With transferable scaling parameters optimized by least squares fitting to the experimental vibrational frequencies of short oligoenes, the scaled frequencies of trans-polyacetylene and its isotopic analogs agree very well with experiments. The linear/exponential scaling scheme is also applicable to the cis-polyacetylene case.

  3. Secure Cooperative Spectrum Sensing via a Novel User-Classification Scheme in Cognitive Radios for Future Communication Technologies

    Directory of Open Access Journals (Sweden)

    Muhammad Usman

    2015-05-01

    Full Text Available Future communication networks would be required to deliver data on a far greater scale than is known to us today, thus mandating the maximal utilization of the available radio spectrum using cognitive radios. In this paper, we have proposed a novel cooperative spectrum sensing approach for cognitive radios. In cooperative spectrum sensing, the fusion center relies on reports of the cognitive users to make a global decision. The global decision is obtained by assigning weights to the reports received from cognitive users. Computation of such weights requires prior information of the probability of detection and the probability of false alarms, which are not readily available in real scenarios. Further, the cognitive users are divided into reliable and unreliable categories based on their weighted energy by using some empirical threshold. In this paper, we propose a method to classify the cognitive users into reliable, neutral and unreliable categories without using any pre-defined or empirically-obtained threshold. Moreover, the computation of weights does not require the detection, or false alarm probabilities, or an estimate of these probabilities. Reliable cognitive users are assigned the highest weights; neutral cognitive users are assigned medium weights (less than the reliable and higher than the unreliable cognitive users’ weights; and unreliable users are assigned the least weights. We show the performance improvement of our proposed method through simulations by comparing it with the conventional cooperative spectrum sensing scheme through different metrics, like receiver operating characteristic (ROC curve and mean square error. For clarity, we also show the effect of malicious users on detection probability and false alarm probability individually through simulations.

  4. Analysis and numerical study of a hybrid BGM-3DVAR data assimilation scheme using satellite radiance data for heavy rain forecasts

    Institute of Scientific and Technical Information of China (English)

    XIONG Chun-hui; ZHANG Li-feng; GUAN Ji-ping; PENG Jun; ZHANG Bin

    2013-01-01

    A fine heavy rain forecast plays an important role in the accurate flood forecast,the urban rainstorm waterlogging and the secondary hydrological disaster preventions.To improve the heavy rain forecast skills,a hybrid Breeding Growing Mode (BGM)-three-dimensional variational (3DVAR) Data Assimilation (DA) scherne is designed on running the Advanced Research WRF (ARW WRF) model using the Advanced Microwave Sounder Unit A (AMSU-A) satellite radiance data.Results show that:the BGM ensemble prediction method can provide an effective background field and a flow dependent background error covariance for the BGM-3DVAR scheme.The BGM-3DVAR scheme adds some effective mesoscale information with similar scales as the heavy rain clusters to the initial field in the heavy rain area,which improves the heavy rain forecast significantly,while the 3DVAR scheme adds information with relatively larger scales than the heavy rain clusters to the initial field outside of the heavy rain area,which does not help the heavy rain forecast improvement.Sensitive experiments demonstrate that the flow dependent background error covariance and the ensemble mean background field are both the key factors for adding effective mesoscale information to the heavy rain area,and they are both essential for improving the heavy rain forecasts.

  5. Design Hybrid method for intrusion detection using Ensemble cluster classification and SOM network

    Directory of Open Access Journals (Sweden)

    Deepak Rathore

    2012-09-01

    Full Text Available In current scenario of internet technology security is big challenge. Internet network threats by various cyber-attack and loss the system data and degrade the performance of host computer. In this sense intrusion detection are challenging field of research in concern of network security based on firewall and some rule based detection technique. In this paper we proposed an Ensemble Cluster Classification technique using som network for detection of mixed variable data generated by malicious software for attack purpose in host system. In our methodology SOM network control the iteration of distance of different parameters of ensembling our experimental result show that better empirical evaluation on KDD data set 99 in comparison of existing ensemble classifier.

  6. Hybrid Indoor-Based WLAN-WSN Localization Scheme for Improving Accuracy Based on Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Zahid Farid

    2016-01-01

    Full Text Available In indoor environments, WiFi (RSS based localization is sensitive to various indoor fading effects and noise during transmission, which are the main causes of localization errors that affect its accuracy. Keeping in view those fading effects, positioning systems based on a single technology are ineffective in performing accurate localization. For this reason, the trend is toward the use of hybrid positioning systems (combination of two or more wireless technologies in indoor/outdoor localization scenarios for getting better position accuracy. This paper presents a hybrid technique to implement indoor localization that adopts fingerprinting approaches in both WiFi and Wireless Sensor Networks (WSNs. This model exploits machine learning, in particular Artificial Natural Network (ANN techniques, for position calculation. The experimental results show that the proposed hybrid system improved the accuracy, reducing the average distance error to 1.05 m by using ANN. Applying Genetic Algorithm (GA based optimization technique did not incur any further improvement to the accuracy. Compared to the performance of GA optimization, the nonoptimized ANN performed better in terms of accuracy, precision, stability, and computational time. The above results show that the proposed hybrid technique is promising for achieving better accuracy in real-world positioning applications.

  7. Glaucoma detection using novel optic disc localization, hybrid feature set and classification techniques.

    Science.gov (United States)

    Akram, M Usman; Tariq, Anam; Khalid, Shehzad; Javed, M Younus; Abbas, Sarmad; Yasin, Ubaid Ullah

    2015-12-01

    Glaucoma is a chronic and irreversible neuro-degenerative disease in which the neuro-retinal nerve that connects the eye to the brain (optic nerve) is progressively damaged and patients suffer from vision loss and blindness. The timely detection and treatment of glaucoma is very crucial to save patient's vision. Computer aided diagnostic systems are used for automated detection of glaucoma that calculate cup to disc ratio from colored retinal images. In this article, we present a novel method for early and accurate detection of glaucoma. The proposed system consists of preprocessing, optic disc segmentation, extraction of features from optic disc region of interest and classification for detection of glaucoma. The main novelty of the proposed method lies in the formation of a feature vector which consists of spatial and spectral features along with cup to disc ratio, rim to disc ratio and modeling of a novel mediods based classier for accurate detection of glaucoma. The performance of the proposed system is tested using publicly available fundus image databases along with one locally gathered database. Experimental results using a variety of publicly available and local databases demonstrate the superiority of the proposed approach as compared to the competitors.

  8. 台湾植被分类方案%A Scheme of Vegetation Classification of Taiwan, China

    Institute of Scientific and Technical Information of China (English)

    宋永昌; 徐国士

    2003-01-01

    The complexity of natural conditions leads to the complexity of vegetation types of Taiwan ofChina, which has both tropical and cold-temperate vegetation types, and could be depicted as the vegeta-tion miniature of China or even for the world. The physiognomic-floristic principle was adopted for thevegetation classification of Taiwan. The units of rank from top to bottom are: class of vegetation-type,order of vegetation-type, vegetation-type, alliance group, alliance and association. The high-rank units(class,order and vegetation-type) are classified by ecological physiognomy, while the median and lowerunits by the species composition of community. At the same time the role of dominant species andcharacter species will also be considered. The dominant species are the major factor concerned with themedian ranks (alliance group,and alliance) because they are the chief components of community, addition-ally their remarkable appearance is easy to identify; the character species (or diagnostic species) are forrelatively low ranks (association) because they will clearly show the interspecies relation-ship and thecharacteristics of community. According to this principle, vegetation of Taiwan is classi-fied into fiveclasses of vegetation-types (forests, thickets, herbaceous vegetation, rock fields vegetation, swamps andaquatic vegetation), 29 orders of vegetation-types (cold-temperate needle-leaved forests, cool-temper-ate needle-leaved forests, warm-temperate needle-leaved forests, warm needle-leaved forests, deciduousbroad-leaved forests, mixed evergreen and deciduous broad-leaved forests, evergreen mossy forests, ev-ergreen sclerophyllous forests, evergreen broad-leaved forests, tropical rain forests, tropical monsoonforests, coastal forests, warm bamboo forests, evergreen needle-leaved thickets, sclerophyllous thickets,deciduous broad-leaved thickets, evergreen broad-leaved thickets, xerothermic thorn-succulent thickets,bamboo thickets, meadows, sparse shrub grasslands

  9. Frequency Resource Sharing and Allocation Scheme Based on Coalition Formation Game in Hybrid D2D-Cellular Network

    Directory of Open Access Journals (Sweden)

    Qing Ou

    2015-01-01

    Full Text Available A distributed cooperation scheme on frequency resource sharing is proposed to improve the quality of service (QoS in device-to-device (D2D communications underlaying cellular networks. Specifically, we formulate the resource allocation problem as a coalition formation game with transferable utility, in which all users have the incentive to cooperate with some others and form a competitive group to maximize the probability of obtaining their favorite spectrum resources. Taking the cost for coalition formation into account, such as the path loss for data sharing, we prove that the core of the proposed game is empty, which shows the impossibility of grand coalition. Hence, we propose a distributed merge-and-split based coalition formation algorithm based on a new defined Max-Coalition order to effectively solve the coalition game. Compared with the exhaustive search, our algorithm has much lower computer complexity. In addition, we prove that stability and convergence of the proposed algorithm using the concept of a defection function. Finally, the simulation results show that the proposed scheme achieves a suboptimal performance in terms of network sum rate compared with the centralized optimal resource allocation scheme obtained via exhaustive search.

  10. Staggering behavior of the first excited 2 sup + states of even-even nuclei in a Sp(4,R) classification scheme

    CERN Document Server

    Drenska, S B; Minkov, N

    2002-01-01

    Authors implement a high order discrete derivative analysis of the low lying collective energies of even-even nuclei in respect to the total number of valence nucleon pairs N in the framework of F-spin multiplets unified in a symplectic sp(4, R) classification scheme. It has been found that for the nuclei of any given F- multiplet the respective experimental energies exhibit a DELTA N = 2 staggering behavior, while for the nuclei of two neighboring F-multiplets with DELTA F sub 0 = +1/2, -1/2 stronger and more regular DELTA N = 1 staggering patterns are observed. This behavior is reproduced by the theoretical energies of the considered nuclei, obtained by the generalized phenomenological expression for them. This result has been explained on the basis of the sharp transitions trough the collective modes and the oscillation of the valence isospin in symplectic multiplets. It is suggested that the observed DELTA N = 2 and DELTA N = 1 staggering effects can be interpreted as the respective systematic manifestati...

  11. A Classification Scheme for Young Stellar Objects Using the WIDE-FIELD INFRARED SURVEY EXPLORER ALLWISE Catalog: Revealing Low-Density Star Formation in the Outer Galaxy

    Science.gov (United States)

    Koening, X. P.; Leisawitz, D. T.

    2014-01-01

    We present an assessment of the performance of WISE and the AllWISE data release in a section of the Galactic Plane. We lay out an approach to increasing the reliability of point source photometry extracted from the AllWISE catalog in Galactic Plane regions using parameters provided in the catalog. We use the resulting catalog to construct a new, revised young star detection and classification scheme combining WISE and 2MASS near and mid-infrared colors and magnitudes and test it in a section of the Outer Milky Way. The clustering properties of the candidate Class I and II stars using a nearest neighbor density calculation and the two-point correlation function suggest that the majority of stars do form in massive star forming regions, and any isolated mode of star formation is at most a small fraction of the total star forming output of the Galaxy. We also show that the isolated component may be very small and could represent the tail end of a single mechanism of star formation in line with models of molecular cloud collapse with supersonic turbulence and not a separate mode all to itself.

  12. 混合型三阶格式及关于两种DES算法的比较计算研究%A hybrid third order scheme and the comparative investigations on two DES methods by computations

    Institute of Scientific and Technical Information of China (English)

    孙东; 陈江涛; 李沁; 张涵信

    2013-01-01

    为开展RANS/LES混合模拟,在传统三阶迎风偏置格式的基础上,提出一类混合型的三阶计算格式,格式在中高波数范围具有可调的耗散水平.在此基础上,文中通过计算比较研究两种RANS/LES混合算法:一种是基于Spalart-Allmaras一方程模型的DES模型(DES-SA),另一种是基于混合长度模型的DES模型(DES-ML),使用 发展的三阶格式对圆柱绕流进行模拟,并将得到的结果与文献比较,对计算格式、DES-ML算法进行了初步探讨.%In order to make numerical simulations using Detached-Eddy Simulation (DES) hybrid method,a third-order hybrid scheme has been proposed on the basis of the traditional third-order upwind-biased scheme.The dissipation of the new hybrid scheme can be adjusted in moderate and higher band of the scaled wave number.Based on the aforementioned works,comparative numerical studies have been made on two RANS/LES hybrid methods,i.e.,DES-SA based on the S-A turbulent model and DES-ML based on the mixing length model.The computations choose the low-speed flow around three-dimensional cylinder as an example,while using several difference schemes including the developed third-order scheme.Comparisons have been made between the obtained results and that from references,and discussions have been made about the new hybrid scheme and DES-ML method also.

  13. A novel Z-scheme BiPO4-Bi2O2(OH)(NO3) heterojunction structured hybrid for synergistic photocatalysis.

    Science.gov (United States)

    Liu, Guoshuai; You, Shijie; Huang, Hong; Ma, Ming; Ren, Nanqi

    2017-03-01

    Photocatalysis has been gaining a growing popularity in water treatment, and their engineered applications inspire the development of effective photocatalyst materials. To develop photocatalyst that is effective for degradation of organic pollutants, we fabricate a novel direct solid Z-scheme BiPO4-Bi2O2(OH)(NO3) (BPO-BHN) heterojunction structured hybrid. The results demonstrate an enhanced photocatalytic activity of BPO-BHN to produce OH radicals, according to diffuse reflectance spectroscopy (DRS), electron spin-resonance resonance (ESR), photoelectrochemical measurements, and theoretical calculation results. The BPO-BHN is shown to greatly promote the degradation of 2,4-dichlorophenol (2,4-DCP) under ultraviolet light. On the basis of pseudo-first-order kinetics, the apparent degradation rate constant (kapp) of 0.050 min(-1) obtained for BPO-BHN is approximately 3.33 and 12.5 times of that for individual BPO (kapp = 0.015 min(-1)) and BHN (kapp = 0.004 min(-1)), respectively. This suggests a virtually synergistic photocatalysis of BPO and BHN when they form a direct solid Z-scheme heterojunction structure, which is favorable for improving UV-light harvesting, hole/electron separation and oxidizing capability. In particular, as a novel non-linear optical (NLO) material, the BHN plays a significant role in the formation of Z-scheme structure for its unique ability of capturing photo-electrons from BPO by high-potential C(+) face in valence band. This study provides a proof-of-concept strategy to develop more effective photocatalysts for degradation of organic pollutants in water.

  14. A Hybrid Scheme Motion Controller by Sliding Mode and Two-Degree-of-Freedom Controls to Minimize the Chattering

    Directory of Open Access Journals (Sweden)

    Chiu-Keng Lai

    2014-01-01

    Full Text Available Sliding mode control (SMC is rapped for the chattering due to high gain control. However, high gain control causes the system robust. For developing a system with robustness of SMC, a servo motor motion controller combining the two-degree-of-freedom (2DOF system and SMC is proposed. The discussed motion type is point-to-point control with the constraint of trapezoid velocity profile. SMC is designed to guide the motor motion to follow a predefined trail, and the inner 2DOF system is used to compensate the deterioration due to the adoption of load observer. The proposed hybrid system is realized on a PC-based motion controller, and the validness is verified by simulation and experimental results.

  15. A Dynamic Feature-Based Method for Hybrid Blurred/Multiple Object Detection in Manufacturing Processes

    Directory of Open Access Journals (Sweden)

    Tsun-Kuo Lin

    2016-01-01

    Full Text Available Vision-based inspection has been applied for quality control and product sorting in manufacturing processes. Blurred or multiple objects are common causes of poor performance in conventional vision-based inspection systems. Detecting hybrid blurred/multiple objects has long been a challenge in manufacturing. For example, single-feature-based algorithms might fail to exactly extract features when concurrently detecting hybrid blurred/multiple objects. Therefore, to resolve this problem, this study proposes a novel vision-based inspection algorithm that entails selecting a dynamic feature-based method on the basis of a multiclassifier of support vector machines (SVMs for inspecting hybrid blurred/multiple object images. The proposed algorithm dynamically selects suitable inspection schemes for classifying the hybrid images. The inspection schemes include discrete wavelet transform, spherical wavelet transform, moment invariants, and edge-feature-descriptor-based classification methods. The classification methods for single and multiple objects are adaptive region growing- (ARG- based and local adaptive region growing- (LARG- based learning approaches, respectively. The experimental results demonstrate that the proposed algorithm can dynamically select suitable inspection schemes by applying a selection algorithm, which uses SVMs for classifying hybrid blurred/multiple object samples. Moreover, the method applies suitable feature-based schemes on the basis of the classification results for employing the ARG/LARG-based method to inspect the hybrid objects. The method improves conventional methods for inspecting hybrid blurred/multiple objects and achieves high recognition rates for that in manufacturing processes.

  16. Hybrid Quantum Mechanics/Molecular Mechanics Solvation Scheme for Computing Free Energies of Reactions at Metal-Water Interfaces.

    Science.gov (United States)

    Faheem, Muhammad; Heyden, Andreas

    2014-08-12

    We report the development of a quantum mechanics/molecular mechanics free energy perturbation (QM/MM-FEP) method for modeling chemical reactions at metal-water interfaces. This novel solvation scheme combines planewave density function theory (DFT), periodic electrostatic embedded cluster method (PEECM) calculations using Gaussian-type orbitals, and classical molecular dynamics (MD) simulations to obtain a free energy description of a complex metal-water system. We derive a potential of mean force (PMF) of the reaction system within the QM/MM framework. A fixed-size, finite ensemble of MM conformations is used to permit precise evaluation of the PMF of QM coordinates and its gradient defined within this ensemble. Local conformations of adsorbed reaction moieties are optimized using sequential MD-sampling and QM-optimization steps. An approximate reaction coordinate is constructed using a number of interpolated states and the free energy difference between adjacent states is calculated using the QM/MM-FEP method. By avoiding on-the-fly QM calculations and by circumventing the challenges associated with statistical averaging during MD sampling, a computational speedup of multiple orders of magnitude is realized. The method is systematically validated against the results of ab initio QM calculations and demonstrated for C-C cleavage in double-dehydrogenated ethylene glycol on a Pt (111) model surface.

  17. A Hybrid Waveform Inversion Scheme for the Determination of Locations and Moment Tensors of the Microseismic Events and the uncertainty and Sensitivity Analysis

    Science.gov (United States)

    Li, J.; Droujinine, A.; Shen, P.

    2011-12-01

    In this research, we developed a new hybrid waveform inversion scheme to determine the hypocenters, origin times and moment tensors of the microseismic events induced by hydraulic fracturing. To overcome the nonlinearity in the determination of the hypocenter and origin time of a microseismic event, we perform a global search for the hypocenter (x,y,z) and origin time (t0) in a gridded four-dimensional model space, and at each grid point of the four-dimensional model space, we perform a linear inversion for the moment tensor components (M11, M22, M33, M12, M13, M23) in a six-dimensional model subspace. By this two-step approach, we find a global estimate optimum solution in the four- plus six-dimensional total model space. Then we further perform a nonlinear, gradient-based inversion for a better hypocenter and origin time of the microseismic event starting from the global estimate optimum solution. The linear inversion for the moment tensor can also be performed at each iteration of the nonlinear inversion for the hypocenter and origin time. In the grid-linear-nonlinear hybrid approach, we avoid being trapped in the local minima in the inverse problem while reducing the computational cost. The Green's functions between a monitored regions and receivers are computed by the elastic wave reciprocity. We also have performed a systematic study of the uncertainty, resolution and sensitivity of the method and found that it has superior performance in determining the hypocenter and origin time of a microseismic event over the traditional travel time methods, while being able to deliver the focal mechanism solution for the event as well. The method is tested on a dataset from a hydraulic fracturing practice in an oil reservoir.

  18. Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data.

    Science.gov (United States)

    Chatterjee, Sankhadeep; Dey, Nilanjan; Shi, Fuqian; Ashour, Amira S; Fong, Simon James; Sen, Soumya

    2017-09-11

    Dengue fever detection and classification have a vital role due to the recent outbreaks of different kinds of dengue fever. Recently, the advancement in the microarray technology can be employed for such classification process. Several studies have established that the gene selection phase takes a significant role in the classifier performance. Subsequently, the current study focused on detecting two different variations, namely, dengue fever (DF) and dengue hemorrhagic fever (DHF). A modified bag-of-features method has been proposed to select the most promising genes in the classification process. Afterward, a modified cuckoo search optimization algorithm has been engaged to support the artificial neural (ANN-MCS) to classify the unknown subjects into three different classes namely, DF, DHF, and another class containing convalescent and normal cases. The proposed method has been compared with other three well-known classifiers, namely, multilayer perceptron feed-forward network (MLP-FFN), artificial neural network (ANN) trained with cuckoo search (ANN-CS), and ANN trained with PSO (ANN-PSO). Experiments have been carried out with different number of clusters for the initial bag-of-features-based feature selection phase. After obtaining the reduced dataset, the hybrid ANN-MCS model has been employed for the classification process. The results have been compared in terms of the confusion matrix-based performance measuring metrics. The experimental results indicated a highly statistically significant improvement with the proposed classifier over the traditional ANN-CS model.

  19. Wetlands & Deepwater Habitats, Wetlands; s44wwt93. Wetlands as interpreted from 1988 aerial photography to one quarter acre polygon resolution by Cowardin 16 classification scheme. Wetlands identified on photos were manually transferred onto mylar sheets and digitized by hand, Published in 1993, 1:24000 (1in=2000ft) scale, State of Rhode Island and Providence Plantations.

    Data.gov (United States)

    NSGIC GIS Inventory (aka Ramona) — This Wetlands s44wwt93. Wetlands as interpreted from 1988 aerial photography to one quarter acre polygon resolution by Cowardin 16 classification scheme. Wetlands...

  20. A Novel Hybrid Dimension Reduction Technique for Undersized High Dimensional Gene Expression Data Sets Using Information Complexity Criterion for Cancer Classification

    Directory of Open Access Journals (Sweden)

    Esra Pamukçu

    2015-01-01

    Full Text Available Gene expression data typically are large, complex, and highly noisy. Their dimension is high with several thousand genes (i.e., features but with only a limited number of observations (i.e., samples. Although the classical principal component analysis (PCA method is widely used as a first standard step in dimension reduction and in supervised and unsupervised classification, it suffers from several shortcomings in the case of data sets involving undersized samples, since the sample covariance matrix degenerates and becomes singular. In this paper we address these limitations within the context of probabilistic PCA (PPCA by introducing and developing a new and novel approach using maximum entropy covariance matrix and its hybridized smoothed covariance estimators. To reduce the dimensionality of the data and to choose the number of probabilistic PCs (PPCs to be retained, we further introduce and develop celebrated Akaike’s information criterion (AIC, consistent Akaike’s information criterion (CAIC, and the information theoretic measure of complexity (ICOMP criterion of Bozdogan. Six publicly available undersized benchmark data sets were analyzed to show the utility, flexibility, and versatility of our approach with hybridized smoothed covariance matrix estimators, which do not degenerate to perform the PPCA to reduce the dimension and to carry out supervised classification of cancer groups in high dimensions.

  1. Repetitive Learning Control for Time-varying Robotic Systems: A Hybrid Learning Scheme%时变机器人系统的重复学习控制:一种混合学习方案

    Institute of Scientific and Technical Information of China (English)

    孙明轩; 何熊熊; 陈冰玉

    2007-01-01

    Repetitive learning control is presented for finitetime-trajectory tracking of uncertain time-varying robotic systems. A hybrid learning scheme is given to cope with the constant and time-varying unknowns in system dynamics, where the time functions are learned in an iterative learning way, without the aid of Taylor expression, while the conventional differential learning method is suggested for estimating the constant ones.It is distinct that the presented repetitive learning control avoids the requirement for initial repositioning at the beginning of each cycle, and the time-varying unknowns are not necessary to be periodic. It is shown that with the adoption of hybrid learning,the boundedness of state variables of the closed-loop system is guaranteed and the tracking error is ensured to converge to zero as iteration increases. The effectiveness of the proposed scheme is demonstrated through numerical simulation.

  2. Classification of cyber attacks in South Africa

    CSIR Research Space (South Africa)

    Van Heerden, R

    2016-05-01

    Full Text Available This paper introduces a classification scheme for the visual classification of cyber attacks. Through the use of the scheme, the impact of various cyber attacks throughout the history of South Africa are investigated and classified. The goal...

  3. Renoprotection and the Bardoxolone Methyl Story - Is This the Right Way Forward A Novel View of Renoprotection in CKD Trials: A New Classification Scheme for Renoprotective Agents

    Directory of Open Access Journals (Sweden)

    Macaulay Onuigbo

    2013-04-01

    , and many more others yet to be identified, do concurrently and asymmetrically contribute to CKD initiation and propagation to end-stage renal disease (ESRD in our CKD patients. We conclude that current knowledge of CKD initiation and progression to ESRD, the natural history of CKD and the impacts of acute kidney injury on this continuum remain in their infancy and call for more research. Finally, we suggest a new classification scheme for renoprotective agents: (1 the single-pathway blockers that block a single putative pathogenetic pathway involved in CKD progression, as typified by ACE inhibitors and/or ARBs, and (2 the multiple-pathway blockers that are able to block or antagonize the effects of multiple pathogenetic pathways through their ability to simultaneously block, downstream, the effects of several pathways or mechanisms of CKD to ESRD progression and could therefore concurrently interfere with several unrelated upstream pathways or mechanisms. We surmise that maybe the ideal and truly renoprotective agent, clearly a multiple-pathway blocker, is on the horizon. This calls for more research efforts from all.

  4. Mathematics Subject Classification and related schemes in the OAI framework. In: Find and Post Mathematics in the Web A workshop on Electronic Information and Communication in Mathematics

    OpenAIRE

    De Robbio, Antonella; Maguolo, Dario; Marini, Alberto

    2002-01-01

    This paper aims to give a feeling of the roles that discipline-oriented subject classifications can play in the Open Archive movement for the free dissemination of information in research activities. Mathematics, and Mathematics Subject Classification, will be the focuses around which we will move to discover a variety of presentation modes, protocols and tools for human and machine interoperability. The Open Archives Initiative (OAI) is intended to be the effective framework for such a...

  5. Listing Dangerously: Taxonomies, Typologies, and Classifications--Part II.

    Science.gov (United States)

    Hauptman, Robert; Berman, Sanford

    1987-01-01

    The second of two articles examines some modern classification schemes and the logic behind them. Examples of unusual classification within the Dewey Decimal system are given, and social and political influences on classification schemes are noted. (MES)

  6. A PWM Buck Converter With Load-Adaptive Power Transistor Scaling Scheme Using Analog-Digital Hybrid Control for High Energy Efficiency in Implantable Biomedical Systems.

    Science.gov (United States)

    Park, Sung-Yun; Cho, Jihyun; Lee, Kyuseok; Yoon, Euisik

    2015-12-01

    We report a pulse width modulation (PWM) buck converter that is able to achieve a power conversion efficiency (PCE) of > 80% in light loads 100 μA) for implantable biomedical systems. In order to achieve a high PCE for the given light loads, the buck converter adaptively reconfigures the size of power PMOS and NMOS transistors and their gate drivers in accordance with load currents, while operating at a fixed frequency of 1 MHz. The buck converter employs the analog-digital hybrid control scheme for coarse/fine adjustment of power transistors. The coarse digital control generates an approximate duty cycle necessary for driving a given load and selects an appropriate width of power transistors to minimize redundant power dissipation. The fine analog control provides the final tuning of the duty cycle to compensate for the error from the coarse digital control. The mode switching between the analog and digital controls is accomplished by a mode arbiter which estimates the average of duty cycles for the given load condition from limit cycle oscillations (LCO) induced by coarse adjustment. The fabricated buck converter achieved a peak efficiency of 86.3% at 1.4 mA and > 80% efficiency for a wide range of load conditions from 45 μA to 4.1 mA, while generating 1 V output from 2.5-3.3 V supply. The converter occupies 0.375 mm(2) in 0.18 μm CMOS processes and requires two external components: 1.2 μF capacitor and 6.8 μH inductor.

  7. A Scheme for Current-limiting Hybrid DC Circuit Breaker%一种限流式混合直流断路器方案

    Institute of Scientific and Technical Information of China (English)

    江道灼; 张弛; 郑欢; 叶李心; 严玉婷

    2014-01-01

    for high-voltage DC-breakers. Furthermore,a scheme of hybrid DC-breakers with fault current limiting is proposed, its feasibility verified through simulation.In this scheme the DC-breaker adopts the hybrid solid-state switch (composed of half and full gate-controlled devices in series connection) which is paralleled with a mechanical breaker involving the fault-current-limiting technology. Therefore the rising rate of short-circuit current can be effectively restrained,relieving the requirement on fault diagnosis sensitivity and mechanical breaker speed.Moreover,the series quantities of solid-state switching devices (especially the expensive full gate-controlled devices such as the insulated gate bipolar transistor)in high voltage application,and the technical difficulty and production costs etc will be reduced.

  8. Solution of the transport equation in stationary state and X Y geometry, using continuous and discontinuous hybrid nodal schemes; Solucion de la ecuacion de transporte en estado estacionario y geometria X Y, usando esquemas nodales hibridos continuos y discontinuos

    Energy Technology Data Exchange (ETDEWEB)

    Xolocostli M, V.; Valle G, E. del [IPN-ESFM, 07738 Mexico D.F. (Mexico); Alonso V, G. [ININ, 52045 Ocoyoacac, Estado de Mexico (Mexico)]. e-mail: xvicente@hotmail.com

    2003-07-01

    In this work it is described the development and the application of the NH-FEM schemes, Hybrid Nodal schemes using the Finite Element method in the solution of the neutron transport equation in stationary state and X Y geometry, of which two families of schemes were developed, one of which corresponds to the continuous and the other to the discontinuous ones, inside those first its are had the Bi-Quadratic Bi Q, and to the Bi-cubic BiC, while for the seconds the Discontinuous Bi-lineal DBiL and the Discontinuous Bi-quadratic DBiQ. These schemes were implemented in a program to which was denominated TNHXY, Transport of neutrons with Hybrid Nodal schemes in X Y geometry. One of the immediate applications of the schemes NH-FEM it will be in the analysis of assemblies of nuclear fuel, particularly of the BWR type. The validation of the TNHXY program was made with two test problems or benchmark, already solved by other authors with numerical techniques and to compare results. The first of them consists in an it BWR fuel assemble in an arrangement 7x7 without rod and with control rod providing numerical results. The second is a fuel assemble of mixed oxides (MOX) in an arrangement 10x10. This last problem it is known as the Benchmark problem WPPR of the NEA Data Bank and the results are compared with those of other commercial codes as HELIOS, MCNP-4B and CPM-3. (Author)

  9. A Combined Random Forest and OBIA Classification Scheme for Mapping Smallholder Agriculture at Different Nomenclature Levels Using Multisource Data (Simulated Sentinel-2 Time Series, VHRS and DEM

    Directory of Open Access Journals (Sweden)

    Valentine Lebourgeois

    2017-03-01

    Full Text Available Sentinel-2 images are expected to improve global crop monitoring even in challenging tropical small agricultural systems that are characterized by high intra- and inter-field spatial variability and where satellite observations are disturbed by the presence of clouds. To overcome these constraints, we analyzed and optimized the performance of a combined Random Forest (RF classifier/object-based approach and applied it to multisource satellite data to produce land use maps of a smallholder agricultural zone in Madagascar at five different nomenclature levels. The RF classifier was first optimized by reducing the number of input variables. Experiments were then carried out to (i test cropland masking prior to the classification of more detailed nomenclature levels, (ii analyze the importance of each data source (a high spatial resolution (HSR time series, a very high spatial resolution (VHSR coverage and a digital elevation model (DEM and data type (spectral, textural or other, and (iii quantify their contributions to classification accuracy levels. The results show that RF classifier optimization allowed for a reduction in the number of variables by 1.5- to 6-fold (depending on the classification level and thus a reduction in the data processing time. Classification results were improved via the hierarchical approach at all classification levels, achieving an overall accuracy of 91.7% and 64.4% for the cropland and crop subclass levels, respectively. Spectral variables derived from an HSR time series were shown to be the most discriminating, with a better score for spectral indices over the reflectances. VHSR data were only found to be essential when implementing the segmentation of the area into objects and not for the spectral or textural features they can provide during classification.

  10. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on soun...... exchanging experiences about constructions fulfilling different classes, reducing trade barriers, and finally increasing the sound insulation of dwellings.......Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on sound...... insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms...

  11. Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database

    NARCIS (Netherlands)

    Thompson, Bryony A.; Spurdle, Amanda B.; Plazzer, John-Paul; Greenblatt, Marc S.; Akagi, Kiwamu; Al-Mulla, Fahd; Bapat, Bharati; Bernstein, Inge; Capella, Gabriel; den Dunnen, Johan T.; du Sart, Desiree; Fabre, Aurelie; Farrell, Michael P.; Farrington, Susan M.; Frayling, Ian M.; Frebourg, Thierry; Goldgar, David E.; Heinen, Christopher D.; Holinski-Feder, Elke; Kohonen-Corish, Maija; Robinson, Kristina Lagerstedt; Leung, Suet Yi; Martins, Alexandra; Moller, Pal; Morak, Monika; Nystrom, Minna; Peltomaki, Paivi; Pineda, Marta; Qi, Ming; Ramesar, Rajkumar; Rasmussen, Lene Juel; Royer-Pokora, Brigitte; Scott, Rodney J.; Sijmons, Rolf; Tavtigian, Sean V.; Tops, Carli M.; Weber, Thomas; Wijnen, Juul; Woods, Michael O.; Macrae, Finlay; Genuardi, Maurizio

    2014-01-01

    The clinical classification of hereditary sequence variants identified in disease-related genes directly affects clinical management of patients and their relatives. The International Society for Gastrointestinal Hereditary Tumours (InSiGHT) undertook a collaborative effort to develop, test and appl

  12. Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database

    DEFF Research Database (Denmark)

    Thompson, Bryony A; Spurdle, Amanda B; Plazzer, John-Paul

    2014-01-01

    The clinical classification of hereditary sequence variants identified in disease-related genes directly affects clinical management of patients and their relatives. The International Society for Gastrointestinal Hereditary Tumours (InSiGHT) undertook a collaborative effort to develop, test and a...

  13. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms...... of descriptors, number of classes, and class intervals occurred between national schemes. However, a proposal “acoustic classification scheme for dwellings” has been developed recently in the European COST Action TU0901 with 32 member countries. This proposal has been accepted as an ISO work item. This paper...

  14. Secure Identity-authentication Scheme Based on Minutiae Classification%基于指纹多生物特征的安全身份认证方案

    Institute of Scientific and Technical Information of China (English)

    黄家斌; 曹珍富

    2013-01-01

    由于多生物特征身份认证的安全稳定性,美国司法部引入指纹汗孔信息来帮助身份认证.然而指纹汗孔信息的泄露可以充分还原出指纹纹路信息.本文提出一种保护指纹汗孔等个人隐私信息的方案.方案采用高分辨率指纹仪提取带有汗孔的指纹数字图像,使用指纹细节点进行预对齐,指纹汗孔进行密钥绑定.现有的模糊金库方案在应用上都假设指纹预先对齐或采用一些准确率不高的对齐方法,本文首次将指纹第三层汗孔信息与模糊金库方案相结合.%As multi-biometric feature identification can get higher accuracy,the U.S.department of justice launched the next generation identification (NGI) project which will add the fingerprint pore information to help the identification.However,the leaking of personal fingerprint pore information can make it easy to restore the fingerprint ridges.The paper presents a scheme which can protect personal private pore information.The scheme uses high-resolution fingerprint scan device to capture fingerprint digital image with pores,aligns fingerprints by using minutiae,and binds key by using pore.Existing Fuzzy Vault scheme assumes fingerprints are pre-aligned or uses inaccurate methods to align fingerprints.The paper firstly combines fingerprint level3 information with Fuzzy Vault scheme.

  15. Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering

    Directory of Open Access Journals (Sweden)

    Suraj

    2015-01-01

    Full Text Available Transferring the brain computer interface (BCI from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG signal reasons us to look toward evolutionary algorithm (EA. Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA and particle swarm optimization (PSO based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD and desynchronization (ERD feature vector is formed.

  16. An Evaluation of Different Training Sample Allocation Schemes for Discrete and Continuous Land Cover Classification Using Decision Tree-Based Algorithms

    Directory of Open Access Journals (Sweden)

    René Roland Colditz

    2015-07-01

    Full Text Available Land cover mapping for large regions often employs satellite images of medium to coarse spatial resolution, which complicates mapping of discrete classes. Class memberships, which estimate the proportion of each class for every pixel, have been suggested as an alternative. This paper compares different strategies of training data allocation for discrete and continuous land cover mapping using classification and regression tree algorithms. In addition to measures of discrete and continuous map accuracy the correct estimation of the area is another important criteria. A subset of the 30 m national land cover dataset of 2006 (NLCD2006 of the United States was used as reference set to classify NADIR BRDF-adjusted surface reflectance time series of MODIS at 900 m spatial resolution. Results show that sampling of heterogeneous pixels and sample allocation according to the expected area of each class is best for classification trees. Regression trees for continuous land cover mapping should be trained with random allocation, and predictions should be normalized with a linear scaling function to correctly estimate the total area. From the tested algorithms random forest classification yields lower errors than boosted trees of C5.0, and Cubist shows higher accuracies than random forest regression.

  17. A hybrid classifier using the parallelepiped and Bayesian techniques. [for multispectral image data

    Science.gov (United States)

    Addington, J. D.

    1975-01-01

    A versatile classification scheme is developed which uses the best features of the parallelepiped algorithm and the Bayesian maximum likelihood algorithm. The parallelepiped technique has the advantage of being very fast, especially when implemented into a table look-up scheme; its disadvantage is its inability to distinguish and classify spectral signatures which are similar in nature. This disadvantage is eliminated by the Bayesian technique which is capable of distinguishing subtle differences very well. The hybrid algorithm developed reduces computer time by as much as 90%. A two- and n-dimensional description of the hybrid classifier is given.

  18. The interplay of descriptor-based computational analysis with pharmacophore modeling builds the basis for a novel classification scheme for feruloyl esterases

    DEFF Research Database (Denmark)

    Udatha, D.B.R.K. Gupta; Kouskoumvekaki, Irene; Olsson, Lisbeth

    2011-01-01

    on amino acid composition and physico-chemical composition descriptors derived from the respective amino acid sequence. A Support Vector Machine model was subsequently constructed for the classification of new FAEs into the pre-assigned clusters. The model successfully recognized 98.2% of the training...... sequences and all the sequences of the blind test. The underlying functionality of the 12 proposed FAE families was validated against a combination of prediction tools and published experimental data. Another important aspect of the present work involves the development of pharmacophore models for the new...

  19. Hybrid artificial neural network segmentation and classification of dynamic contrast-enhanced MR imaging (DEMRI) of osteosarcoma.

    Science.gov (United States)

    Glass, J O; Reddick, W E

    1998-11-01

    The evaluation of pediatric osteosarcoma has suffered from the lack of an accurate imaging measure of response. One major problem is that osteosarcoma do not shrink in response to chemotherapy; instead, viable tumor is replaced by necrotic tissue. Currently available techniques that use dynamic contrast-enhanced magnetic resonance imaging to quantitatively evaluate tumor response fail to assess the percentage of necrosis. At present, histopathologic evaluation of resected tissue is the only means of measuring the percentage of necrosis in treated osteosarcoma. The current study presents a non-invasive method to visualize necrotic and viable tumor and quantitatively assess the response of osteosarcoma. Our technique uses a hybrid neural network consisting of a Kohonen self-organizing map to segment dynamic contrast-enhanced magnetic resonance images and a multi-layer backpropagation neural network to classify the segmented images. Because the hybrid neural network is completely automated, our technique removes both inter- and intra-operator error. An analysis comparing the percentage of necrosis from our technique to the histopathologic analysis revealed a highly significant Spearman correlation coefficient of 0.617 with p < 0.001.

  20. Evaluation of the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) classification scheme for diagnosis of cutaneous melanocytic neoplasms: Results from the International Melanoma Pathology Study Group.

    Science.gov (United States)

    Lott, Jason P; Elmore, Joann G; Zhao, Ge A; Knezevich, Stevan R; Frederick, Paul D; Reisch, Lisa M; Chu, Emily Y; Cook, Martin G; Duncan, Lyn M; Elenitsas, Rosalie; Gerami, Pedram; Landman, Gilles; Lowe, Lori; Messina, Jane L; Mihm, Martin C; van den Oord, Joost J; Rabkin, Michael S; Schmidt, Birgitta; Shea, Christopher R; Yun, Sook Jung; Xu, George X; Piepkorn, Michael W; Elder, David E; Barnhill, Raymond L

    2016-08-01

    Pathologists use diverse terminology when interpreting melanocytic neoplasms, potentially compromising quality of care. We sought to evaluate the Melanocytic Pathology Assessment Tool and Hierarchy for Diagnosis (MPATH-Dx) scheme, a 5-category classification system for melanocytic lesions. Participants (n = 16) of the 2013 International Melanoma Pathology Study Group Workshop provided independent case-level diagnoses and treatment suggestions for 48 melanocytic lesions. Individual diagnoses (including, when necessary, least and most severe diagnoses) were mapped to corresponding MPATH-Dx classes. Interrater agreement and correlation between MPATH-Dx categorization and treatment suggestions were evaluated. Most participants were board-certified dermatopathologists (n = 15), age 50 years or older (n = 12), male (n = 9), based in the United States (n = 11), and primary academic faculty (n = 14). Overall, participants generated 634 case-level diagnoses with treatment suggestions. Mean weighted kappa coefficients for diagnostic agreement after MPATH-Dx mapping (assuming least and most severe diagnoses, when necessary) were 0.70 (95% confidence interval 0.68-0.71) and 0.72 (95% confidence interval 0.71-0.73), respectively, whereas correlation between MPATH-Dx categorization and treatment suggestions was 0.91. This was a small sample size of experienced pathologists in a testing situation. Varying diagnostic nomenclature can be classified into a concise hierarchy using the MPATH-Dx scheme. Further research is needed to determine whether this classification system can facilitate diagnostic concordance in general pathology practice and improve patient care. Copyright © 2016 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

  1. A fast and efficient segmentation scheme for cell microscopic image.

    Science.gov (United States)

    Lebrun, G; Charrier, C; Lezoray, O; Meurie, C; Cardot, H

    2007-04-27

    Microscopic cellular image segmentation schemes must be efficient for reliable analysis and fast to process huge quantity of images. Recent studies have focused on improving segmentation quality. Several segmentation schemes have good quality but processing time is too expensive to deal with a great number of images per day. For segmentation schemes based on pixel classification, the classifier design is crucial since it is the one which requires most of the processing time necessary to segment an image. The main contribution of this work is focused on how to reduce the complexity of decision functions produced by support vector machines (SVM) while preserving recognition rate. Vector quantization is used in order to reduce the inherent redundancy present in huge pixel databases (i.e. images with expert pixel segmentation). Hybrid color space design is also used in order to improve data set size reduction rate and recognition rate. A new decision function quality criterion is defined to select good trade-off between recognition rate and processing time of pixel decision function. The first results of this study show that fast and efficient pixel classification with SVM is possible. Moreover posterior class pixel probability estimation is easy to compute with Platt method. Then a new segmentation scheme using probabilistic pixel classification has been developed. This one has several free parameters and an automatic selection must dealt with, but criteria for evaluate segmentation quality are not well adapted for cell segmentation, especially when comparison with expert pixel segmentation must be achieved. Another important contribution in this paper is the definition of a new quality criterion for evaluation of cell segmentation. The results presented here show that the selection of free parameters of the segmentation scheme by optimisation of the new quality cell segmentation criterion produces efficient cell segmentation.

  2. The Hybrid MPI and OpenMP Parallel Scheme of GRAPES Global Model%GRAPES 全球模式 MPI 与 OpenMP 混合并行方案

    Institute of Scientific and Technical Information of China (English)

    蒋沁谷; 金之雁

    2014-01-01

    decomposition method and loop-level parallelization.In horizontal domain decomposition method,a patch is uniformly divided into several tiles while patches are obtained by dividing the whole forecasting domain.There are two main advantages in performing parallel operations on tiles.Firstly,tile-level parallelization which applies OpenMP at a high level,to some extent,is coarse grained parallelism. Compared to computing work associated with each tile,OpenMP thread overhead is negligible.Secondly, implementation of this method is relative simple,and the subroutine thread safety is the only thing to en-sure.Loop-level parallelization which can improve load imbalance by adopting different thread scheduling policies is fine grained parallelism.The main computational loops are applied OpenMP’s parallel directives in loop-level parallelization method.The preferred method is horizontal domain decomposition for uniform grid computing,while loop-level parallelization method is preferred for non-uniform grid computing and the thread unsafe procedures.Experiments with 1°×1°dataset are performed and timing on main subrou-tines of integral computation are compared.The hybrid parallel performance is superior to single MPI scheme in terms of long wave radiation process,microphysics and land surface process while Helmholtz e-quation generalized conjugate residual (GCR)solution has some difficulty in thread parallelism for incom-plete LU factorization preconditioner part.ILU part with tile-level parallelization can improve GCR’s hy-brid parallelization.Short wave process hybrid parallel performance is close to single MPI scheme under the same computing cores.It requires less elapsed time with increase of the number of threads under cer-tain MPI processes in hybrid parallel scheme.And hybrid parallel scheme within four threads is superior to single MPI scheme under large-scale experiment.Hybrid parallel scheme can also achieve better scalability than single MPI scheme.The experiment shows

  3. Erratum to "Applicability of in vitro tests for skin irritation and corrosion to regulatory classification schemes: substantiating test strategies with data from routine studies" [Regul. Toxicol. Pharmacol. (2012) 402-414].

    Science.gov (United States)

    Kolle, Susanne N; Sullivan, Kristie M; Mehling, Annette; van Ravenzwaay, Bennard; Landsiedel, Robert

    2013-04-01

    Skin corrosion or irritation refers to the production of irreversible or reversible damage to the skin following the application of a test substance, respectively. Traditionally, hazard assessments are conducted using the in vivo Draize skin test, but recently in vitro tests using reconstructed human epidermis (RhE) models have gained regulatory acceptance. In this study, skin corrosion (SCT) and irritation tests (SIT) using a RhE model were implemented to reduce the number of in vivo tests required by regulatory bodies. One hundred and thirty-four materials were tested from a wide range of substance classes included 46 agrochemical formulations. Results were assessed according to UN GHS, EU-CLP, ANVISA and US EPA classification schemes. There was high correlation between the two in vitro tests. Assessment of the SCT sensitivity was not possible due to the limited number of corrosives in the data set; SCT specificity and accuracy were 89% for all classification systems. Accuracy (63–76%) and sensitivity (53–67%) were low in the SIT. Specificity and concordance for agrochemical formulations alone in both the SCT and SIT were comparable to the values for the complete data set (SCT: 91% vs. 89% specificity, 91% vs. 89% accuracy and SIT: 64–88% vs. 70–85% specificity, 56–75% vs. 63–76% accuracy).

  4. The Chemical Abundances of Stars in the Halo (CASH) Project. III. A New Classification Scheme for Carbon-Enhanced Metal-poor Stars with S-process Element Enhancement

    CERN Document Server

    Hollek, Julie K; Placco, Vinicius M; Karakas, Amanda I; Shetrone, Matthew; Sneden, Christopher; Christlieb, Norbert

    2015-01-01

    We present a detailed abundance analysis of 23 elements for a newly discovered carbon-enhanced metal-poor (CEMP) star, HE 0414-0343, from the Chemical Abundances of Stars in the Halo (CASH) Project. Its spectroscopic stellar parameters are Teff = 4863 K, log g = 1.25, vmic = 2.20 km/s, and [Fe/H] = -2.24. Radial velocity measurements covering seven years indicate HE 0414-0343 to be a binary. HE 0414-0343 has [C/Fe] = 1.44 and is strongly enhanced in neutron-capture elements but its abundances cannot be reproduced by a solar-type s-process pattern alone. Traditionally, it could be classified as "CEMP-r/s" star. Based on abundance comparisons with AGB star nucleosynthesis models, we suggest a new physically-motivated origin and classification scheme for CEMP-s stars and the still poorly-understood CEMP-r/s. The new scheme describes a continuous transition between these two so-far distinctly treated subgroups: CEMP-sA, CEMP-sB, and CEMP-sC. Possible causes for a continuous transition include the number of therma...

  5. How to Develop the Pig Hybrids/Commercial Line and Make the Breeding Scheme%如何培育猪的配套系和制定培育方案

    Institute of Scientific and Technical Information of China (English)

    彭中镇; 刘榜; 樊斌; 赵书红; 徐学文; 李长春; 朱猛进

    2015-01-01

    This paper gives the definition of hybrids/commercial line, analyzes the people's conceptual misunderstandings, expounds why do you want to develop the hybrid swine, and assesses the advantage and superiority of the hybrids.The developmental methods of commercial line including the work programme(steps),work flow and existing problems were discussed, the style and form of writing the"hybrid swine breeding scheme"was recommended. Some opinions and suggestions that relates to future breeding works of hybrid swine were also put forward.%文章给出了“配套系”的定义,引证了中国学者提出的“配套系”一词相对应的英语表达词为hybrids和commercial line,分析了对配套系概念上的误解;阐明了为何要培育配套系,评价了配套系商品畜禽优势所在;借鉴国外经验,参照国家法规,结合作者见解,从培育程序(步骤)、工作流程与当前培育方法上存在问题三方面阐述了配套系的培育方法;提出了撰写猪配套系培育方案的参考体例;对今后猪配套系培育工作提出了建议。

  6. A Hybrid Fuzzy-SVM classifier for automated lung diseases diagnosis

    Science.gov (United States)

    Ben Hassen, Donia; Ben Zakour, Sihem; Taleb, Hassen

    2016-12-01

    A novel scheme for lesions classification in chest radiographs is presented in this paper. Features are extracted from detected lesions from lung regions which are segmented automatically. Then, we needed to eliminate redundant variables from the subset extracted because they affect the performance of the classification. We used Stepwise Forward Selection and Principal Components Analysis. Then, we obtained two subsets of features. We finally experimented the Stepwise/FCM/SVM classification and the PCA/FCM/SVM one. The ROC curves show that the hybrid PCA/FCM/SVM has relatively better accuracy and remarkable higher efficiency. Experimental results suggest that this approach may be helpful to radiologists for reading chest images.

  7. An Exact and Grid-free Numerical Scheme for the Hybrid Two Phase Traffic Flow Model Based on the Lighthill-Whitham-Richards Model with Bounded Acceleration

    KAUST Repository

    Qiu, Shanwen

    2012-07-01

    In this article, we propose a new grid-free and exact solution method for computing solutions associated with an hybrid traffic flow model based on the Lighthill- Whitham-Richards (LWR) partial differential equation. In this hybrid flow model, the vehicles satisfy the LWR equation whenever possible, and have a fixed acceleration otherwise. We first present a grid-free solution method for the LWR equation based on the minimization of component functions. We then show that this solution method can be extended to compute the solutions to the hybrid model by proper modification of the component functions, for any concave fundamental diagram. We derive these functions analytically for the specific case of a triangular fundamental diagram. We also show that the proposed computational method can handle fixed or moving bottlenecks.

  8. Modeling cloud microphysics using a two-moments hybrid bulk/bin scheme for use in Titan’s climate models: Application to the annual and diurnal cycles

    Science.gov (United States)

    Burgalat, J.; Rannou, P.; Cours, T.; Rivière, E. D.

    2014-03-01

    Microphysical models describe the way aerosols and clouds behave in the atmosphere. Two approaches are generally used to model these processes. While the first approach discretizes processes and aerosols size distributions on a radius grid (bin scheme), the second uses bulk parameters of the size distribution law (its mathematical moments) to represent the evolution of the particle population (moment scheme). However, with the latter approach, one needs to have an a priori knowledge of the size distributions. Moments scheme for Cloud microphysics modeling have been used and enhanced since decades for climate studies of the Earth. Most of the tools are based on Log-Normal law which are suitable for Earth, Mars or Venus. On Titan, due to the fractal structure of the aerosols, the size distributions do not follow a log-normal law. Then using a moment scheme in that case implies to define the description of the size distribution and to review the equations that are widely published in the literature. Our objective is to enable the use of a fully described microphysical model using a moment scheme within a Titan's Global Climate Model. As a first step in this direction, we present here a moment scheme dedicated to clouds microphysics adapted for Titan's atmosphere conditions. We perform comparisons between the two kinds of schemes (bin and moments) using an annual and a diurnal cycle, to check the validity of our moment description. The various forcing produce a time-variable cloud layer in relation with the temperature cycle. We compare the column opacities and the temperature for the two schemes, for each cycles. We also compare more detailed quantities as the opacity distribution of the cloud events at different periods of these cycles. Results show that differences between the two approaches have a small impact on the temperature (less than 1 K) and range between 1% and 10% for haze and clouds opacities. Both models behave in similar way when forced by an annual and

  9. Estimation of source location and ground impedance using a hybrid multiple signal classification and Levenberg-Marquardt approach

    Science.gov (United States)

    Tam, Kai-Chung; Lau, Siu-Kit; Tang, Shiu-Keung

    2016-07-01

    A microphone array signal processing method for locating a stationary point source over a locally reactive ground and for estimating ground impedance is examined in detail in the present study. A non-linear least square approach using the Levenberg-Marquardt method is proposed to overcome the problem of unknown ground impedance. The multiple signal classification method (MUSIC) is used to give the initial estimation of the source location, while the technique of forward backward spatial smoothing is adopted as a pre-processer of the source localization to minimize the effects of source coherence. The accuracy and robustness of the proposed signal processing method are examined. Results show that source localization in the horizontal direction by MUSIC is satisfactory. However, source coherence reduces drastically the accuracy in estimating the source height. The further application of Levenberg-Marquardt method with the results from MUSIC as the initial inputs improves significantly the accuracy of source height estimation. The present proposed method provides effective and robust estimation of the ground surface impedance.

  10. Hybrid evolutionary techniques in feed forward neural network with distributed error for classification of handwritten Hindi `SWARS'

    Science.gov (United States)

    Kumar, Somesh; Pratap Singh, Manu; Goel, Rajkumar; Lavania, Rajesh

    2013-12-01

    In this work, the performance of feedforward neural network with a descent gradient of distributed error and the genetic algorithm (GA) is evaluated for the recognition of handwritten 'SWARS' of Hindi curve script. The performance index for the feedforward multilayer neural networks is considered here with distributed instantaneous unknown error i.e. different error for different layers. The objective of the GA is to make the search process more efficient to determine the optimal weight vectors from the population. The GA is applied with the distributed error. The fitness function of the GA is considered as the mean of square distributed error that is different for each layer. Hence the convergence is obtained only when the minimum of different errors is determined. It has been analysed that the proposed method of a descent gradient of distributed error with the GA known as hybrid distributed evolutionary technique for the multilayer feed forward neural performs better in terms of accuracy, epochs and the number of optimal solutions for the given training and test pattern sets of the pattern recognition problem.

  11. The novel block encryption scheme based on hybrid chaotic maps for the wireless sensor networks%基于无线传感器网络的混合混沌新分组加密算法

    Institute of Scientific and Technical Information of China (English)

    佟晓筠; 左科; 王翥

    2012-01-01

    Traditional encryption schemes are not suitable for the Wireless sensor networks(WSNS) due to some intrinsic features of nodes in WSNS such as low energy,limited computation ability and storage resources.In this paper,we present a novel block encryption scheme based on hybrid chaotic maps dynamically and propose an integer digital random method,and the Feistel network structure, which is a kind of fast,secure,low resource consumption and suited for WSNS nodes encryption scheme.The experimental tests show the new encryption scheme has the following prefect performances:large key space,very good diffusion and disrupt performance, strict avalanche effect,excellent statistical balance and fast encryption speed of the new scheme,and the encryption scheme passes the SP800-22 test;meanwhile,the analysis and the testing of speed,time and storage space on the simulator platform show that this new encryption scheme is well able to hide the data information about the node in WSNS.%针对无线传感器网络(WSNS)中节点配备的能源少、节点计算能力低、存储资源有限以及化统的加密方法不适用于WSNS中等问题,提出了一种新的基于动态迭代的混合混沌方程及其整型数值化方法.并结合Feistel网络结构设计了一种快速、安全且资源消耗低的适用于WSNS节点的分组加密算法.通过对混合混沌分组加密算法进行了大量的实验测试之后,发现该算法具有密钥空间大、严格的雪崩效应、扩散及扰乱性高以及均等的统计平衡性等优点,同时该算法还成功地通过了SP800-22的严格测试;算法经过仿真器平台上运行的速度、时间及所占存储空间的测试分析,结果表明设计的混合混沌分组加密算法是完全能够通用于WSNS节点的数据加密.

  12. Realizing the Hybrid Library.

    Science.gov (United States)

    Pinfield, Stephen; Eaton, Jonathan; Edwards, Catherine; Russell, Rosemary; Wissenburg, Astrid; Wynne, Peter

    1998-01-01

    Outlines five projects currently funded by the United Kingdom's Electronic Libraries Program (eLib): HyLiFe (Hybrid Library of the Future), MALIBU (MAnaging the hybrid Library for the Benefit of Users), HeadLine (Hybrid Electronic Access and Delivery in the Library Networked Environment), ATHENS (authentication scheme), and BUILDER (Birmingham…

  13. 面向对象的航空高光谱图像混合分类方法%A Hybrid of Object-based and Pixel-based Classification Method with Airborne Hyperspectral Imagery

    Institute of Scientific and Technical Information of China (English)

    李雪轲; 王晋年; 张立福; 杨杭; 刘凯

    2014-01-01

    Hyperspectral imagery generally contains hundreds of contiguous narrow bands, which could provide detailed spectral information for target detection and image classification. Traditional hyperspectral classification fails to generate expected results since it simply considers spectral or textural properties at the pixel scale in the context of natural complexity. In this article, a hybrid classification method was proposed which takes full advan-tages of spectral and spatial features by fusing object-based segmentation results with traditional per-pixel classi-fication results. Based on this concept, two specific hybrid classification approaches were employed:(1) the mix-ture of multi-scale segmentation and SVM classification and (2) the mixture of multi-band watershed segmenta-tion and SVM classification. In the first proposed method, spectral variations were attenuated by converting them into homogenous image objects at multiple scales;while, the latter method aggregates spatial information and morphological profiles into the segmented objects to achieve the homogeneous classification. The two classi-fication algorithms were applied to airborne hyperspectral imagery and the results show that the overall accuracy based on traditional pixel-wise classification reaches about 82.49%, relatively lower compared with the hybrid object-based classification methods, which are 92.63%(Method 1) and 96.13%(Method 2) respectively. In addi-tion, Method 2 performs better than Method 1 since it produced a smoother boundary, partly because Method 2 needs less user-defined parameters, and the iterative“trial-and-error”of which may affect the classification re-sults. In conclusion, this study demonstrates that the hybrid of object-based classification is a significantly more robust approach than the traditional per-pixel classifier. The proposed method overcomes the spectral confusion, solves the problem of land fragmentation, and provides a solution to map complex environments

  14. A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

    Science.gov (United States)

    Robertson, D.M.; Saad, D.A.; Heisey, D.M.

    2006-01-01

    Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

  15. A research on dynamic and hybrid key management scheme of heterogeneous sensor network%异构无线传感器网络动态混合密钥管理方案研究

    Institute of Scientific and Technical Information of China (English)

    刘梦君; 刘树波; 刘泓晖; 蔡朝晖; 涂国庆

    2012-01-01

    In the application of Wireless Sensor Networks (WSN) needing secure communications, asymmetric key scheme is supposed difficult to be implemented on resources limited sensor node, and the symmetric key scheme based on probability pre-distribution possess the disadvantages of weak nodes connectivity, big memory consuming, compli- cated and inflexible key agreement. Hence, a dynamic hybrid key management scheme associated asymmetric and sym- metric scheme (DHKAS) was proposed based on the heterogeneous wireless sensor networks. The scheme solved the Node Authentication problem in key management with a simple and reliable way. The analysis result shows that the pro- posed scheme effectively improves the connectivity of the node, reduces memory consuming and enhances the network secure ability.%在需要进行安全通信的无线传感器网络应用中,复杂的公钥系统难以在资源有限的传感节点上实现,而基于随机预分配的对称密钥系统有节点连通性不强、密钥存储空间过大、密钥协商过程复杂且不灵活等问题。因此,在畀构无线传感器网络基础上,提出一种联合公钥机制与私钥机制的混合密钥管理方案(DHKAS)。该方案使用一种简便可靠的方法,以较小的代价解决了密钥管理中最关键的节点认证问题。分析结果显示,所提方案有效提高了节点的连通性、减少了密钥存储空间,并增强了网络抗攻击能力。

  16. The Chemical Abundances of Stars in the Halo (CASH) Project. III. A New Classification Scheme for Carbon-enhanced Metal-poor Stars with s-process Element Enhancement

    Science.gov (United States)

    Hollek, Julie K.; Frebel, Anna; Placco, Vinicius M.; Karakas, Amanda I.; Shetrone, Matthew; Sneden, Christopher; Christlieb, Norbert

    2015-12-01

    We present a detailed abundance analysis of 23 elements for a newly discovered carbon-enhanced metal-poor (CEMP) star, HE 0414-0343, from the Chemical Abundances of Stars in the Halo Project. Its spectroscopic stellar parameters are Teff = 4863 K, {log}g=1.25,\\ξ = 2.20 km s-1, and [Fe/H] = -2.24. Radial velocity measurements covering seven years indicate HE 0414-0343 to be a binary. HE 0414-0343 has {{[C/Fe]}}=1.44 and is strongly enhanced in neutron-capture elements but its abundances cannot be reproduced by a solar-type s-process pattern alone. Traditionally, it could be classified as a “CEMP-r/s” star. Based on abundance comparisons with asymptotic giant branch (AGB) star nucleosynthesis models, we suggest a new physically motivated origin and classification scheme for CEMP-s stars and the still poorly understood CEMP-r/s. The new scheme describes a continuous transition between these two so-far distinctly treated subgroups: CEMP-sA, CEMP-sB, and CEMP-sC. Possible causes for a continuous transition include the number of thermal pulses the AGB companion underwent, the effect of different AGB star masses on their nucleosynthetic yields, and physics that is not well approximated in 1D stellar models such as proton ingestion episodes and rotation. Based on a set of detailed AGB models, we suggest the abundance signature of HE 0414-0343 to have arisen from a >1.3 M⊙ mass AGB star and a late-time mass transfer that transformed HE 0414-0343 into a CEMP-sC star. We also find that the [Y/Ba] ratio well parametrizes the classification and can thus be used to easily classify any future such stars. Based on observations obtained with the Hobby-Eberly Telescope, which is a joint project of the University of Texas at Austin, the Pennsylvania State University, Stanford University, Ludwig-Maximilians-Universität München, and Georg-August-Universität Göttingen.

  17. The Development and Current Status of an Occupational Classification.

    Science.gov (United States)

    Holland, John L.

    The author summarizes the origin of his occupational classification scheme, the main events in its development, and its present form. A number of deficiencies in this classification scheme are addressed, and the virtues of the scheme are enumerated. Although the present classification is the outcome of much empirical work, individual…

  18. Colour schemes

    DEFF Research Database (Denmark)

    van Leeuwen, Theo

    2013-01-01

    This chapter presents a framework for analysing colour schemes based on a parametric approach that includes not only hue, value and saturation, but also purity, transparency, luminosity, luminescence, lustre, modulation and differentiation....

  19. A Classification Scheme for Young Stellar Objects Using the WIDE-FIELD INFRARED SURVEY EXPLORER AllWISE Catalog: Revealing Low-Density Star Formation in the Outer Galaxy

    CERN Document Server

    Koenig, Xavier

    2014-01-01

    We present an assessment of the performance of WISE and the AllWISE data release in a section of the Galactic Plane. We lay out an approach to increasing the reliability of point source photometry extracted from the AllWISE catalog in Galactic Plane regions using parameters provided in the catalog. We use the resulting catalog to construct a new, revised young star detection and classification scheme combining WISE and 2MASS near and mid-infrared colors and magnitudes and test it in a section of the Outer Milky Way. The clustering properties of the candidate Class I and II stars using a nearest neighbor density calculation and the two-point correlation function suggest that the majority of stars do form in massive star forming regions, and any isolated mode of star formation is at most a small fraction of the total star forming output of the Galaxy. We also show that the isolated component may be very small and could represent the tail end of a single mechanism of star formation in line with models of molecul...

  20. Evolution of Debris of a Tidally Disrupted Star by a Massive Black Hole Development of a Hybrid Scheme of the SPH and TVD Methods

    CERN Document Server

    Lee, H M; Lee, Hyung Mok; Kim, Sungsoo S.

    1996-01-01

    The evolution of the stellar debris after tidal disruption due to the super massive black hole's tidal force is difficult to solve numerically because of the large dynamical range of the problem. We developed an SPH (Smoothed Particle Hydrodynamics) - TVD (Total Variation Diminishing) hybrid code in which the SPH is used to cover a widely spread debris and the TVD is used to compute the stream collision more accurately. While the code in the present form is not sufficient to obtain desired resoultion, it could provide a useful tool in studying the aftermath of the stellar disruption by a massive black hole.

  1. 命名数据网络中一种基于节点分类的数据存储策略%A Data Caching Scheme Based on Node Classification in Named Data Networking

    Institute of Scientific and Technical Information of China (English)

    黄胜; 滕明埝; 吴震; 许江华; 季瑞军

    2016-01-01

    Compared with the traditional Internet , in‐networking caching is one of the most distinguishable features in named data networking (NDN) .In NDN ,a node caches every passing data packet as a default model . The caching scheme generates a large number of redundant data in in‐networking .As a consequence , the networking cache resource is wasted seriously . To solve the problem ,a caching scheme based on node classification (BNC) is proposed firstly in this paper .Based on different node positions ,the nodes that data packet passes through are divided into two types :“edge” type and “core” type .When data packet passes through the “core” type nodes ,by considering location and data popularity distribution at different nodes ,it is cached in a node which is beneficial to other nodes .When the data packet passes through the “edge” nodes ,a node is selected through data popularity to be beneficial to the client .The simulation results show that the proposed scheme can efficiently improve the in‐network hit ratio and reduce the delay and hops of getting the data packet .%缓存是命名数据网络(named data networking ,NDN )有别于传统网络最突出的特性之一, NDN 中默认所有节点都具有缓存所有经过数据的功能。这种“处处缓存”策略导致网内大量冗余数据的产生,使网内缓存被严重浪费。针对上述问题,首次提出了一种基于节点分类(based on node classification ,BNC)的数据存储策略。基于节点位置的不同,将数据返回客户端所经过的节点分为“边缘”类节点与“核心”类节点。当数据经过“核心”类节点时,通过权衡该类节点的位置与数据在不同节点的流行度分布,将数据存储在对其他节点最有利的节点中;当数据经过“边缘”类节点时,通过该数据流行度来选择最有利于客户端的位置。仿真结果表明,提出的策略将有效提高数据命中率,

  2. In-situ preparation of Z-scheme AgI/Bi5O7I hybrid and its excellent photocatalytic activity

    Science.gov (United States)

    Cui, Min; Yu, Jingxiong; Lin, Hongjun; Wu, Ying; Zhao, Leihong; He, Yiming

    2016-11-01

    The aim of this work was to synthesize, characterize and evaluate the photocatalytic activity of AgI/Bi5O7I composite photocatalyst under visible light irradiation. The photocatalyst was prepared by a simple one-step ionic reaction between Bi5O7I microrods and AgNO3 solutions, and was characterized by various techniques including X-ray diffraction (XRD), Raman spectroscopy (Raman), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), UV-vis diffuse reflectance spectroscopy (DRS), and photoluminescence spectroscopy (PL). The characterizations indicate that AgI particles were closely anchored on Bi5O7I micronods. During the photocataytic reaction, the composite was actually an Ag-AgI-Bi5O7I ternary system. The plasmonic effect of the formed Ag nanoparticles improved the visible light absorption performance, which benefits the photocatalytic reaction. However, more important was the formed heterojunction structure in the composite, which efficiently promoted the separation of electron-hole pairs by a plasmonic Z-scheme mechanism, and ultimately enhanced the photocatalytic activity. The optimal AgI/Bi5O7I composite showed a RhB degradation rate of 0.046 min-1, which was 3.83 and 6.57 times higher than those of Bi5O7I and AgI, respectively. This work may provide some insight into the design of novel and highly efficient Z-scheme visible-light photocatalysts.

  3. A solar PV augmented hybrid scheme for enhanced wind power generation through improved control strategy for grid connected doubly fed induction generator

    Directory of Open Access Journals (Sweden)

    Adikanda Parida

    2016-12-01

    Full Text Available In this paper, a wind power generation scheme using a grid connected doubly fed induction generator (DFIG augmented with solar PV has been proposed. A reactive power-based rotor speed and position estimation technique with reduced machine parameter sensitivity is also proposed to improve the performance of the DFIG controller. The estimation algorithm is based on model reference adaptive system (MRAS, which uses the air gap reactive power as the adjustable variable. The overall generation reliability of the wind energy conversion system can be considerably improved as both solar and wind energy can supplement each other during lean periods of either of the sources. The rotor-side DC-link voltage and active power generation at the stator terminals of the DFIG are maintained constant with minimum storage battery capacity using single converter arrangement without grid-side converter (GSC. The proposed scheme has been simulated and experimentally validated with a practical 2.5 kW DFIG using dSPACE CP1104 module which produced satisfactory results.

  4. A novel scheme of hybrid entanglement swapping and teleportation using cavity QED in the small and large detuning regimes and quasi-Bell state measurement method

    Science.gov (United States)

    Pakniat, R.; Tavassoly, M. K.; Zandi, M. H.

    2016-10-01

    We outline a scheme for entanglement swapping based on cavity QED as well as quasi-Bell state measurement (quasi-BSM) methods. The atom-field interaction in the cavity QED method is performed in small and large detuning regimes. We assume two atoms are initially entangled together and, distinctly two cavities are prepared in an entangled coherent-coherent state. In this scheme, we want to transform entanglement to the atom-field system. It is observed that, the fidelities of the swapped entangled state in the quasi-BSM method can be compatible with those obtained in the small and large detuning regimes in the cavity QED method (the condition of this compatibility will be discussed). In addition, in the large detuning regime, the swapped entangled state is obtained by detecting and quasi-BSM approaches. In the continuation, by making use of the atom-field entangled state obtained in both approaches in a large detuning regime, we show that the atomic as well as field states teleportation with complete fidelity can be achieved.

  5. For a VHF radio access network hybrid channel access scheme%一种针对超短波电台接入网的混合信道接入方案

    Institute of Scientific and Technical Information of China (English)

    黄伟强; 谢映海

    2016-01-01

    For the VHF radio access network provides a hybrid channel access scheme,the method uses the civilian access technology of some advanced concepts,combined with military frequency hopping radio network of the special requirements of business applications, using a static TDMA,dynamic TDMA and frequency division multiple access FDMA hybrid channel access strategy, realize the multi-user and multi service transmission QoS guarantee,to meet the special transmission requirement of military operations.%为超短波电台接入网提供了一种混合信道接入方案,方案借鉴了民用接入技术的一些先进理念,并结合军用跳频电台网络的特殊业务应用需求,采用了一种静态TDMA、动态TDMA和频分多址FDMA的混合信道接入策略,实现了多用户多业务传输的QOS保障,满足了军用业务的特殊传输需求。

  6. The Dewey Decimal Scheme and Mathematics

    Science.gov (United States)

    Donovan, Peter W.; And Others

    1973-01-01

    This essay criticizes the mathematical schedules of the 18th edition of the Dewey Decimal Classification Scheme and offers two alternatives suitable for college libraries that use this system. (Authors)

  7. 超声速化学反应流场迎风格式数值模拟及并行计算%PARALLELIZED UPWIND FLUX SPLITTING SCHEME FOR SUPERSONIC REACTING FLOWS ON UNSTRUCTURED HYBRID MESHES

    Institute of Scientific and Technical Information of China (English)

    王江峰; 伍贻兆

    2007-01-01

    A parallelized upwind flux splitting scheme for supersonic reacting flows on hybrid meshes is presented. The complexity of super/hyper-sonic combustion flows makes it necessary to establish solvers with higher resolution and efficiency for multi-component Euler/N-S equations. Hence, a spatial second-order van Leer type flux vector splitting scheme is established by introducing auxiliary points in interpolation, and a domain decomposition method used on unstructured hybrid meshes for obtaining high calculating efficiency. The numerical scheme with five-stage Runge-Kutta time step method is implemented to the simulation of combustion flows, including the supersonic hydrogen/air combustion and the normal injection of hydrogen into reacting flows. Satisfying results are obtained compared with limited references.%基于有限体积迎风格式对超声速燃烧流场进行了的数值模拟.由于超声速燃烧流场绕流的复杂性,要求对多组分Euler/N-S方程求解的数值模拟方法应具有较高的计算精度及效率.本文引用辅助点方法建立了具有空间二阶精度的van Leer迎风矢通量分裂格式,并应用于超声速燃烧流场绕流的数值模拟.化学反应为氢气/空气十反应模型,采用考虑了化学反应特征时间的当地时间步长显式Runge-Kutta时间推进格式.对钝头体模型爆轰现象、后向台阶氢气喷射及二维内外流超声速燃烧流场模型进行了区域分裂技术的并行计算.计算结果与参考文献作了对比,得到了满意的结果.

  8. Analysis of Pareto Distribution under Progressive Type-II Hybrid Censoring Scheme%逐步II型混合截尾下Pareto分布的统计分析

    Institute of Scientific and Technical Information of China (English)

    卫超; 师义民

    2014-01-01

    In this paper,statistical analysis of Pareto distribution is presented under progressive type-II hybrid censored data. The maximum likelihood estimators (MLEs)and Bayes estimator under different prior distributions of Pareto distribution are obtained by using maximum likelihood method and Bayes estimation theory. Finally,Monte-Carlo simulation is performed for illustrative purposes.%基于逐步II型混合截尾寿命试验数据,研究了Pareto分布的统计分析问题。利用极大似然方法和Bayes 估计理论,导出了 Pareto 分布参数的极大似然估计和基于不同先验分布下的 Bayes 估计。最后利用Monte-Carlo模拟方法对估计的结果进行了对比分析。

  9. Update on diabetes classification.

    Science.gov (United States)

    Thomas, Celeste C; Philipson, Louis H

    2015-01-01

    This article highlights the difficulties in creating a definitive classification of diabetes mellitus in the absence of a complete understanding of the pathogenesis of the major forms. This brief review shows the evolving nature of the classification of diabetes mellitus. No classification scheme is ideal, and all have some overlap and inconsistencies. The only diabetes in which it is possible to accurately diagnose by DNA sequencing, monogenic diabetes, remains undiagnosed in more than 90% of the individuals who have diabetes caused by one of the known gene mutations. The point of classification, or taxonomy, of disease, should be to give insight into both pathogenesis and treatment. It remains a source of frustration that all schemes of diabetes mellitus continue to fall short of this goal.

  10. The Influence of Second-Hand Cigarette Smoke Exposure during Childhood and Active Cigarette Smoking on Crohn's Disease Phenotype Defined by the Montreal Classification Scheme in a Western Cape Population, South Africa.

    Directory of Open Access Journals (Sweden)

    Tawanda Chivese

    Full Text Available Smoking may worsen the disease outcomes in patients with Crohn's disease (CD, however the effect of exposure to second-hand cigarette smoke during childhood is unclear. In South Africa, no such literature exists. The aim of this study was to investigate whether disease phenotype, at time of diagnosis of CD, was associated with exposure to second-hand cigarette during childhood and active cigarette smoking habits.A cross sectional examination of all consecutive CD patients seen during the period September 2011-January 2013 at 2 large inflammatory bowel disease centers in the Western Cape, South Africa was performed. Data were collected via review of patient case notes, interviewer-administered questionnaire and clinical examination by the attending gastroenterologist. Disease phenotype (behavior and location was evaluated at time of diagnosis, according to the Montreal Classification scheme. In addition, disease behavior was stratified as 'complicated' or 'uncomplicated', using predefined definitions. Passive cigarette smoke exposure was evaluated during 3 age intervals: 0-5, 6-10, and 11-18 years.One hundred and ninety four CD patients were identified. Cigarette smoking during the 6 months prior to, or at time of diagnosis was significantly associated with ileo-colonic (L3 disease (RRR = 3.63; 95% CI, 1.32-9.98, p = 0.012 and ileal (L1 disease (RRR = 3.54; 95% CI, 1.06-11.83, p = 0.040 compared with colonic disease. In smokers, childhood passive cigarette smoke exposure during the 0-5 years age interval was significantly associated with ileo-colonic CD location (RRR = 21.3; 95% CI, 1.16-391.55, p = 0.040. No significant association between smoking habits and disease behavior at diagnosis, whether defined by the Montreal scheme, or stratified as 'complicated' vs 'uncomplicated', was observed.Smoking habits were associated with ileo-colonic (L3 and ileal (L1 disease at time of diagnosis in a South African cohort.

  11. Twitter content classification

    OpenAIRE

    2010-01-01

    This paper delivers a new Twitter content classification framework based sixteen existing Twitter studies and a grounded theory analysis of a personal Twitter history. It expands the existing understanding of Twitter as a multifunction tool for personal, profession, commercial and phatic communications with a split level classification scheme that offers broad categorization and specific sub categories for deeper insight into the real world application of the service.

  12. In-situ preparation of Z-scheme AgI/Bi{sub 5}O{sub 7}I hybrid and its excellent photocatalytic activity

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Min; Yu, Jingxiong [Department of Materials Physics, Zhejiang Normal University, Jinhua 321004 (China); Lin, Hongjun [College of Chemistry and Life Sciences, Zhejiang Normal University, Jinhua 321004 (China); Wu, Ying, E-mail: ying-wu@zjnu.cn [Institute of Physical Chemistry, Zhejiang Normal University, Jinhua 321004 (China); Zhao, Leihong [Institute of Physical Chemistry, Zhejiang Normal University, Jinhua 321004 (China); He, Yiming, E-mail: hym@zjnu.cn [Department of Materials Physics, Zhejiang Normal University, Jinhua 321004 (China)

    2016-11-30

    Highlights: • High-efficient AgI/Bi{sub 5}O{sub 7}I composite was prepared via a simple method. • The AgI/Bi{sub 5}O{sub 7}I can degrade RhB 3.83 times faster than Bi{sub 5}O{sub 7}I. • The influence factors on the photoactivity of AgI/Bi{sub 5}O{sub 7}I were investigated. - Abstract: The aim of this work was to synthesize, characterize and evaluate the photocatalytic activity of AgI/Bi{sub 5}O{sub 7}I composite photocatalyst under visible light irradiation. The photocatalyst was prepared by a simple one-step ionic reaction between Bi{sub 5}O{sub 7}I microrods and AgNO{sub 3} solutions, and was characterized by various techniques including X-ray diffraction (XRD), Raman spectroscopy (Raman), scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), UV–vis diffuse reflectance spectroscopy (DRS), and photoluminescence spectroscopy (PL). The characterizations indicate that AgI particles were closely anchored on Bi{sub 5}O{sub 7}I micronods. During the photocataytic reaction, the composite was actually an Ag-AgI-Bi{sub 5}O{sub 7}I ternary system. The plasmonic effect of the formed Ag nanoparticles improved the visible light absorption performance, which benefits the photocatalytic reaction. However, more important was the formed heterojunction structure in the composite, which efficiently promoted the separation of electron-hole pairs by a plasmonic Z-scheme mechanism, and ultimately enhanced the photocatalytic activity. The optimal AgI/Bi{sub 5}O{sub 7}I composite showed a RhB degradation rate of 0.046 min{sup −1}, which was 3.83 and 6.57 times higher than those of Bi{sub 5}O{sub 7}I and AgI, respectively. This work may provide some insight into the design of novel and highly efficient Z-scheme visible-light photocatalysts.

  13. On-Line Dynamic Index Hybrid Update Scheme Based on Self-Learning of Allocated Space%基于分配空间自学习的在线动态索引混合更新机制

    Institute of Scientific and Technical Information of China (English)

    刘小珠; 彭智勇

    2012-01-01

    To improve time and space efficiencies of index maintenance, an on-line dynamic index hybrid update (ODIHU) technique is proposed based on self-learning of allocated space. Based on Zipf theorem, ODIHU appropriately estimates the number of short and long lists with theoretical analysis, and manages short and long lists with uniform storage model of distinguishing long and short lists based on link. ODIHU manages long list space with history-based adaptive learning allocation (HALA) , and manages short list space with linear allocation (LA), exponential allocation (EA) , and uniform allocation (UA). To decrease index and retrieval cost, ODIHU divides index data set into limited sections and controls index merge with schemes. Then ODIHU merges short lists with immediate merge, and merges long lists with improved Y-limited contiguous multiple merge scheme, which balances the trade-off of the time and space efficiencies effectively. Based on the proposed RABIF, ODIHU not only considers both index level and inverted list level updating, but also effectively improves time and space efficiencies of index updating.%针对索引维护时间和空间效率低的问题,提出了一种基于分配空间自学习的在线动态索引混合更新机制(on-line dynamic index hybrid update,ODIHU).ODIHU根据Zipf分布原理对长短列表数量分布进行估计,并采用基于历史分配空间的自适应学习机制对长短列表空间进行有效管理,然后对短列表采用立即合并更新方式,长列表采用上限Y相邻多路合并的更新方式维护,实现索引更新与查询性能的有效折中.理论分析及实验结果表明,ODIHU能有效地提高索引维护与更新过程中的空间效率、索引合并与查询时间效率.

  14. 基于Relief F和PSO混合特征选择的面向对象土地利用分类%Object basedland-use classification based on hybrid feature selection method of combining Relief F and PSO

    Institute of Scientific and Technical Information of China (English)

    肖艳; 姜琦刚; 王斌; 李远华; 刘舒; 崔璨

    2016-01-01

    针对面向对象土地利用分类存在特征维数过高的问题,提出了一种结合Relief F和粒子群优化算法(particle swarm optimization,PSO)的混合特征选择方法,即首先利用Relief F作为特征预选器滤除相关性小的特征,然后以PSO作为搜索算法,以支持向量机(support vector machine,SVM)的分类精度作为评估函数在剩余特征中选择出最优特征子集。该文以吉林省长春市部分区域为研究区,采用Landsat8遥感影像为数据源,首先对其进行多尺度分割,然后提取影像对象的光谱、纹理、形状和空间关系特征,利用提出的混合特征选择方法选取最优特征子集,最后使用SVM分类器对研究区进行土地利用分类,总体分类精度和Kappa系数分别为85.88%和0.8036,与基于4种其他特征选择方法的土地利用分类结果进行比较,基于Relief F和PSO的混合特征选择方法利用最少的特征获得最高的分类精度,能够有效地用于面向对象土地利用分类。%In recent years, object-based methods have been increasingly used for the land-use classification of remote sensing data. However, the availability of numerous features with object-based image analysis renders the selection of optimal features. In this study, a hybrid feature selection method that combined filter approach and wrapper approach was proposed. In the filter approach, the Relief F algorithm was employed to select features that had the higher relevance with land-use classes. The wrapper approach used the particle swarm optimization (PSO) algorithm as a search method and the classification accuracy of support vector machine (SVM) as an evaluator to search for an optimal feature subset from the selected features. The objective of this research was to examine the effectiveness of the proposed feature selection method on object-based classification. The study site was located in the southeastern part of Changchun City

  15. Sea-floor classification using multibeam echo-sounding angular backscatter data: A real-time approach employing hybrid neural network architecture

    Digital Repository Service at National Institute of Oceanography (India)

    Chakraborty, B.; Kodagali, V.N.; Baracho, J.

    The presently studied numerical model, e.g., composite roughness, is successful for the purpose of sea-floor classification employing processed multibeam angular backscatter data from manganese-nodule-bearing locations of the Central Indian Ocean...

  16. Sound classification of dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    dwellings, facade sound insulation and installation noise. The schemes have been developed, implemented and revised gradually since the early 1990s. However, due to lack of coordination between countries, there are significant discrepancies, and new standards and revisions continue to increase the diversity....... Descriptors, range of quality levels, number of quality classes, class intervals, denotations and descriptions vary across Europe. The diversity is an obstacle for exchange of experience about constructions fulfilling different classes, implying also trade barriers. Thus, a harmonized classification scheme...... is needed, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", has been established and runs 2009-2013, one of the main objectives being to prepare a proposal for a European sound classification scheme with a number of quality...

  17. Phylogeny and putative hybridization in the subtribe Paranepheliinae (Liabeae, Asteraceae), implications for classification, biogeography, and Andean orogeny%Paranepheliinae亚族(菊科,Liabeae族)的系统发育和可能的属间杂交

    Institute of Scientific and Technical Information of China (English)

    Akiko SOEJIMA; 文军; Mario ZAPATA; Michael O. DILLON

    2008-01-01

    The nuclear ribosomal ITS region and the chloroplast trnL-trnF (trnLF) intergenic region were sequenced for 45 accessions of Paranephelius and six accessions of Pseudonoseris, the two genera of the subtribe Paranepheliinae (Liabeae, Asteraceae) distributed in the alpine regions of the Andes. This data set was used to estimate relationships between these genera and within each genus to aid in evaluating morphological variation and classification. Our results with both ITS and trnLF markers support the monophyly of subtribe Paranepheliinae, and place Pseudonoseris discolor as the first diverged taxon sister to the clade containing Paranephelius. Pseudonoseris szyszylowiczii exhibited intraspecific divergence supporting intergeneric hybridization between Pseudonoseris and Paranephelius. Within Paranephelius, genetic divergence is low and not adequate to fully resolve phylogenetic relationships at the species level, but two genetically and morphologically recognizable groups were revealed by the ITS data. Several accessions possessing multiple ITS sequences represent putative hybrids between the two groups. These putative hybrids have caused some taxonomic confusion and difficulties in establishing species boundaries in Paranephelius. The divergence time estimates based on ITS sequences indicated that the stem of subtribe Paranepheliinae dates to 13 million years ago, but the diversification of the crown clade of the extant members began in the early Pleistocene or late Pliocene, perhaps associated with the uplift of the Andes and the climatic changes of global cooling.

  18. Audio Classification from Time-Frequency Texture

    CERN Document Server

    Yu, Guoshen

    2008-01-01

    Time-frequency representations of audio signals often resemble texture images. This paper derives a simple audio classification algorithm based on treating sound spectrograms as texture images. The algorithm is inspired by an earlier visual classification scheme particularly efficient at classifying textures. While solely based on time-frequency texture features, the algorithm achieves surprisingly good performance in musical instrument classification experiments.

  19. Algorithm of remote sensing image classification improved by bands selection and hybrid kernel functions%改进的波段选择混合核函数遥感图像分类算法

    Institute of Scientific and Technical Information of China (English)

    徐倩; 何建农

    2012-01-01

    针对遥感图像多波段不易成像、其图像信息冗余不适合图像分类以及传统LMBP算法迭代次数多且分类不够精确的问题,改进了OIF指数和可分性距离公式,分组并选出遥感图像最佳波段组合,并运用改进的LMBP混合核函数算法进行分类.仿真实验表明,改进算法对各波段信息分析更加全面客观,波段选择更加优化;与传统算法相比,网络训练迭代次数有明显减少,分类精度及Kappa系数分别提高了5%和6.625%,遥感图像分类更有效.%As the multi-band of remote sensing image is not easy to imaging, ila redundancy image information is not suitable for image classification, what's more, ihe traditional LMBP algorithm has. large iteration number and classification imprecise problems. This paper improved the formula of the OIF index number and separability distance, separated to chose the best band combination, and then used the LMBP algorithm refinement of hybrid kernel function to classify. The simulation results show that the improved method can analyze information of the bands more comprehensive and objective, comparing with the traditional algorithm,the network training iterations are significantly reduced,the classification accuracy and Kappa coefficient can be increased by 5% and 6. 625% , the classification of remote sensing image more effectively.

  20. A new classification of glaucomas

    Directory of Open Access Journals (Sweden)

    Bordeianu CD

    2014-09-01

    Full Text Available Constantin-Dan Bordeianu Private Practice, Ploiesti, Prahova, Romania Purpose: To suggest a new glaucoma classification that is pathogenic, etiologic, and clinical.Methods: After discussing the logical pathway used in criteria selection, the paper presents the new classification and compares it with the classification currently in use, that is, the one issued by the European Glaucoma Society in 2008.Results: The paper proves that the new classification is clear (being based on a coherent and consistently followed set of criteria, is comprehensive (framing all forms of glaucoma, and helps in understanding the sickness understanding (in that it uses a logical framing system. The great advantage is that it facilitates therapeutic decision making in that it offers direct therapeutic suggestions and avoids errors leading to disasters. Moreover, the scheme remains open to any new development.Conclusion: The suggested classification is a pathogenic, etiologic, and clinical classification that fulfills the conditions of an ideal classification. The suggested classification is the first classification in which the main criterion is consistently used for the first 5 to 7 crossings until its differentiation capabilities are exhausted. Then, secondary criteria (etiologic and clinical pick up the relay until each form finds its logical place in the scheme. In order to avoid unclear aspects, the genetic criterion is no longer used, being replaced by age, one of the clinical criteria. The suggested classification brings only benefits to all categories of ophthalmologists: the beginners will have a tool to better understand the sickness and to ease their decision making, whereas the experienced doctors will have their practice simplified. For all doctors, errors leading to therapeutic disasters will be less likely to happen. Finally, researchers will have the object of their work gathered in the group of glaucoma with unknown or uncertain pathogenesis, whereas

  1. 混合云存储环境下的数据访问隐私保护方案%Scheme of data access privacy protection in hybrid cloud storage

    Institute of Scientific and Technical Information of China (English)

    张卓奇; 郭卫斌

    2014-01-01

    为了保护混合云存储中公有云端数据的安全,尤其是数据访问隐私,提出了一个混合云存储方案。在企业私有云环境中对数据进行加密、合并、分割等处理,将文件元数据存放于组织内部的数据库中,将处理后的数据存放于公共云存储空间,实现数据内容和元数据的分离,提高公有云端数据的安全性和数据访问的隐私性。根据原型系统获得的实验结果表明了该方案在数据访问隐私保护中的作用。%To protect the security and privacy of access of out-sourced data,a hybrid cloud storage system was proposed to solve these problems.The system process data were stored out-sourced by using encryption,combination and fragment.The metadata of original data files were stored in local devices and the processed data were upload to public cloud storage.In this way,the safe and private access of original data was guaranteed by separating processed data and metadata.According to the result of experi-ment on the system prototype,the validity of proposed scheme was demonstrated.

  2. 基于混合熵和L_1范数的遥感图像分类%Remote sensing image classification based on hybrid entropy and L1 norm

    Institute of Scientific and Technical Information of China (English)

    王雪松; 高阳; 程玉虎; 汪婵

    2012-01-01

    Aiming at remote sensing image data having properties of high-dimension, nonlinearity, and massive unlabeled samples, a kind of probability least squares support vector machine (PLSSVM) classification method based on hybrid entroy and Ll-norm was proposed. At first, a hybrid entroy was designed by combining quasi-entropy with entropy difference, which was used to select the most 'valuable' unlabeled samples from the massive unlabeled sample set. In the second step, a L~-norm distance mectric was used to further select and to remove outliers and redundant data from the most 'valuable' unlabeled samples. At last, the original labeled and the selected unlabeled samples were adopted to train the PLSSVM. Experimental results on ROSIS hyperspectral remote sensing image show that the overall accuracy and Kappa coeffi- cient of the proposed classification method reach 89.90% and 0. 868 5 respectively. The pro- posed method can obtain higher classification accuracy with few training samples, which is much applicable for classification problem of remote sensing image.%针对遥感图像数据具有的高维数、非线性以及海量无标记样本的特性,提出了一种基于混合熵和L1范数的概率型最小二乘支持向量机分类方法.将准熵和熵差分融合,构造一种混合熵用以从海量无标记样本集中选出最有"价值"的待标记样本;基于L1范数距离度量,进一步从待标记样本集中筛选出孤立点和冗余点加以剔除;基于初始已标记样本以及筛选得到的样本,训练得到概率型最小二乘支持向量机.对反射光学系统的成像光谱仪(ROSIS)高光谱遥感图像进行了分类实验.结果表明:所提分类方法的总精度和Kappa系数分别达到了89.90%和0.868 5,能够以较少的训练样本得到较高的分类精度,其更适于处理遥感图像分类问题.

  3. Human lymphocyte markers defined by antibodies derived from somatic cell hybrids. III. A marker defining a subpopulation of lymphocytes which cuts across the normal T-B-null classification.

    Science.gov (United States)

    Zola, H; Beckman, I G; Bradley, J; Brooks, D A; Kupa, A; McNamara, P J; Smart, I J; Thomas, M E

    1980-06-01

    A somatic cell hybrid line which secreted antibody reacting selectively with a proportion of the white cells in human blood was prepared. The hybridoma appeared to be monoclonal, and the antibody secreted stained 67% of the lymphocyte population in blood. It reacted less well with granulocytes and monocytes. The lymphocytes stained comprised 80% of the T cells and 50% of the B cells. The antibody showed no recognizable pattern in its reactivity with cell lines and leukaemic cells, although B cells tended to react less well than T cells, null cells, or myeloid leukaemic cells. The expression of the antigenic determinant is discussed in relation to the classification of leucocytes. This determinant and certain other markers exhibited differential expression on closely related cells, and yet were shared by more distantly related cells.

  4. A-D-E Classification of Conformal Field Theories

    CERN Document Server

    Cappelli, Andrea

    2009-01-01

    The ADE classification scheme is encountered in many areas of mathematics, most notably in the study of Lie algebras. Here such a scheme is shown to describe families of two-dimensional conformal field theories.

  5. An Experimental Comparative Study on Three Classification Algorithms

    Institute of Scientific and Technical Information of China (English)

    蔡巍; 王永成; 李伟; 尹中航

    2003-01-01

    Classification algorithm is one of the key techniques to affect text automatic classification system's performance, play an important role in automatic classification research area. This paper comparatively analyzed k-NN. VSM and hybrid classification algorithm presented by our research group. Some 2000 pieces of Internet news provided by ChinaInfoBank are used in the experiment. The result shows that the hybrid algorithm's performance presented by the groups is superior to the other two algorithms.

  6. A fast and efficient hybrid fractal-wavelet image coder.

    Science.gov (United States)

    Iano, Yuzo; da Silva, Fernando Silvestre; Cruz, Ana Lúcia Mendes

    2006-01-01

    The excellent visual quality and compression rate of fractal image coding have limited applications due to exhaustive inherent encoding time. This paper presents a new fast and efficient image coder that applies the speed of the wavelet transform to the image quality of the fractal compression. Fast fractal encoding using Fisher's domain classification is applied to the lowpass subband of wavelet transformed image and a modified set partitioning in hierarchical trees (SPIHT) coding, on the remaining coefficients. Furthermore, image details and wavelet progressive transmission characteristics are maintained, no blocking effects from fractal techniques are introduced, and the encoding fidelity problem common in fractal-wavelet hybrid coders is solved. The proposed scheme promotes an average of 94% reduction in encoding-decoding time comparing to the pure accelerated Fractal coding results. The simulations also compare the results to the SPIHT wavelet coding. In both cases, the new scheme improves the subjective quality of pictures for high-medium-low bitrates.

  7. Classification of nanopolymers

    Energy Technology Data Exchange (ETDEWEB)

    Larena, A; Tur, A [Department of Chemical Industrial Engineering and Environment, Universidad Politecnica de Madrid, E.T.S. Ingenieros Industriales, C/ Jose Gutierrez Abascal, Madrid (Spain); Baranauskas, V [Faculdade de Engenharia Eletrica e Computacao, Departamento de Semicondutores, Instrumentos e Fotonica, Universidade Estadual de Campinas, UNICAMP, Av. Albert Einstein N.400, 13 083-852 Campinas SP Brasil (Brazil)], E-mail: alarena@etsii.upm.es

    2008-03-15

    Nanopolymers with different structures, shapes, and functional forms have recently been prepared using several techniques. Nanopolymers are the most promising basic building blocks for mounting complex and simple hierarchical nanosystems. The applications of nanopolymers are extremely broad and polymer-based nanotechnologies are fast emerging. We propose a nanopolymer classification scheme based on self-assembled structures, non self-assembled structures, and on the number of dimensions in the nanometer range (nD)

  8. Decimal Classification Editions

    Directory of Open Access Journals (Sweden)

    Zenovia Niculescu

    2009-01-01

    Full Text Available The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  9. A hybrid multibreath wash-in wash-out lung function quantification scheme in human subjects using hyperpolarized (3) He MRI for simultaneous assessment of specific ventilation, alveolar oxygen tension, oxygen uptake, and air trapping.

    Science.gov (United States)

    Hamedani, Hooman; Kadlecek, Stephen; Xin, Yi; Siddiqui, Sarmad; Gatens, Heather; Naji, Joseph; Ishii, Masaru; Cereda, Maurizio; Rossman, Milton; Rizi, Rahim

    2017-08-01

    To present a method for simultaneous acquisition of alveolar oxygen tension (PA O2 ), specific ventilation (SV), and apparent diffusion coefficient (ADC) of hyperpolarized (HP) gas in the human lung, allowing reinterpretation of the PA O2 and SV maps to produce a map of oxygen uptake (R). An imaging scheme was designed with a series of identical normoxic HP gas wash-in breaths to measure ADC, SV, PA O2 , and R in less than 2 min. Signal dynamics were fit to an iterative recursive model that regionally solved for these parameters. This measurement was successfully performed in 12 subjects classified in three healthy, smoker, and chronic obstructive pulmonary disease (COPD) cohorts. The overall whole lung ADC, SV, PA O2 , and R in healthy, smoker, and COPD subjects was 0.20 ± 0.03 cm(2) /s, 0.39 ± 0.06,113 ± 2 Torr, and 1.55 ± 0.35 Torr/s, respectively, in healthy subjects; 0.21 ± 0.03 cm(2) /s, 0.33 ± 0.06, 115.9 ± 4 Torr, and 0.97 ± 0.2 Torr/s, respectively, in smokers; and 0.25 ± 0.06 cm(2) /s, 0.23 ± 0.08, 114.8 ± 6.0Torr, and 0.94 ± 0.12 Torr/s, respectively, in subjects with COPD. Hetrogeneity of SV, PA O2 , and R were indicators of both smoking-related changes and disease, and the severity of the disease correlated with the degree of this heterogeneity. Subjects with symptoms showed reduced oxygen uptake and specific ventilation. High-resolution, nearly coregistered and quantitative measures of lung function and structure were obtained with less than 1 L of HP gas. This hybrid multibreath technique produced measures of lung function that revealed clear differences among the cohorts and subjects and were confirmed by correlations with global lung measurements. Magn Reson Med 78:611-624, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  10. SMRT交直分网混合实时仿真接口关键技术与实现%Key Techniques and Implementation of SMRT Hybrid Real-time Simulation Employing AC/DC Partitioning Scheme

    Institute of Scientific and Technical Information of China (English)

    张树卿; 童陆园; 郭琦; 李伟; 欧开健; 胡云

    2015-01-01

    Based on super mixed real-time simulation ( SMRT) , which interfaces real-time digital simulation ( RTDS) and digital com-puter, this paper presents the architecture design and basic implementation, and the difficulties and key techniques for utilization of hy-brid simulation in AC and DC power system. Key techniques on how to smoothly interface the electromagnetic and electromechanical tran-sient simulation modes are studied and described in detail, including stability analysis and stabilizing method for the computational sys-tem. practical equivalent interface impedance in low frequency band, leading estimation of interface states based interface and interaction protocol, asymmetric interface method by three-sequence current injection, and three-sequence fundamental power calculation with close-loop auto calibration correction. Finally, the overall scheme and key techniques are verified by case analysis. More tests and practices have proven that SMRT basically meets the requirement of synthesis transient processes simulation of large AC and DC power system.%基于实时数字仿真( real-time digital simulation, RTDS)和数字计算机接口的电磁暂态、机电暂态混合实时仿真( super mixed real-time simulation, SMRT),深入阐述了电磁暂态、机电暂态两种模式的仿真平滑接口的关键技术,包括接口交互系统稳定性分析与稳定方法、实用低频段接口等效阻抗、基于超前估算的接口交互方法、三序分立电流注入不对称接口方法和闭环自校正三序基波功率计算方法。案例分析和方案整体验证证明SMRT已基本满足交直流大系统暂态综合过程仿真分析的需求。

  11. Assembly and offset assignment scheme for self-similar traffic in optical burst switched networks

    CSIR Research Space (South Africa)

    Muwonge, KB

    2007-10-01

    Full Text Available This paper proposes a Forward Equivalence Classification (FEC) assembly scheme to efficiently assemble selfsimilar traffic and a Pareto-offset assignment scheme for offset assignment. Two buffers, a packet buffer and a burst buffer, are implemented...

  12. The EpiOcular™ Eye Irritation Test is the Method of Choice for the In Vitro Eye Irritation Testing of Agrochemical Formulations: Correlation Analysis of EpiOcular Eye Irritation Test and BCOP Test Data According to the UN GHS, US EPA and Brazil ANVISA Classification Schemes.

    Science.gov (United States)

    Kolle, Susanne N; Rey Moreno, Maria Cecilia; Mayer, Winfried; van Cott, Andrew; van Ravenzwaay, Bennard; Landsiedel, Robert

    2015-07-01

    The Bovine Corneal Opacity and Permeability (BCOP) test is commonly used for the identification of severe ocular irritants (GHS Category 1), but it is not recommended for the identification of ocular irritants (GHS Category 2). The incorporation of human reconstructed tissue model-based tests into a tiered test strategy to identify ocular non-irritants and replace the Draize rabbit eye irritation test has been suggested (OECD TG 405). The value of the EpiOcular™ Eye Irritation Test (EIT) for the prediction of ocular non-irritants (GHS No Category) has been demonstrated, and an OECD Test Guideline (TG) was drafted in 2014. The purpose of this study was to evaluate whether the BCOP test, in conjunction with corneal histopathology (as suggested for the evaluation of the depth of the injury( and/or the EpiOcular-EIT, could be used to predict the eye irritation potential of agrochemical formulations according to the UN GHS, US EPA and Brazil ANVISA classification schemes. We have assessed opacity, permeability and histopathology in the BCOP assay, and relative tissue viability in the EpiOcular-EIT, for 97 agrochemical formulations with available in vivo eye irritation data. By using the OECD TG 437 protocol for liquids, the BCOP test did not result in sufficient correct predictions of severe ocular irritants for any of the three classification schemes. The lack of sensitivity could be improved somewhat by the inclusion of corneal histopathology, but the relative viability in the EpiOcular-EIT clearly outperformed the BCOP test for all three classification schemes. The predictive capacity of the EpiOcular-EIT for ocular non-irritants (UN GHS No Category) for the 97 agrochemical formulations tested (91% sensitivity, 72% specificity and 82% accuracy for UN GHS classification) was comparable to that obtained in the formal validation exercise underlying the OECD draft TG. We therefore conclude that the EpiOcular-EIT is currently the best in vitro method for the prediction

  13. Optimal sampling schemes for vegetation and geological field visits

    CSIR Research Space (South Africa)

    Debba, Pravesh

    2012-07-01

    Full Text Available The presentation made to Wits Statistics Department was on common classification methods used in the field of remote sensing, and the use of remote sensing to design optimal sampling schemes for field visits with applications in vegetation...

  14. Land Cover - Minnesota Land Cover Classification System

    Data.gov (United States)

    Minnesota Department of Natural Resources — Land cover data set based on the Minnesota Land Cover Classification System (MLCCS) coding scheme. This data was produced using a combination of aerial photograph...

  15. Wavelet features in motion data classification

    Science.gov (United States)

    Szczesna, Agnieszka; Świtoński, Adam; Słupik, Janusz; Josiński, Henryk; Wojciechowski, Konrad

    2016-06-01

    The paper deals with the problem of motion data classification based on result of multiresolution analysis implemented in form of quaternion lifting scheme. Scheme processes directly on time series of rotations coded in form of unit quaternion signal. In the work new features derived from wavelet energy and entropy are proposed. To validate the approach gait database containing data of 30 different humans is used. The obtained results are satisfactory. The classification has over than 91% accuracy.

  16. Four-state discrimination scheme beyond the heterodyne limit

    DEFF Research Database (Denmark)

    Muller, C. R.; Castaneda, Mario A. Usuga; Wittmann, C.

    2012-01-01

    We propose and experimentally demonstrate a hybrid discrimination scheme for the quadrature phase shift keying protocol, which outperforms heterodyne detection for any signal power. The discrimination is composed of a quadrature measurement, feed forward and photon detection.......We propose and experimentally demonstrate a hybrid discrimination scheme for the quadrature phase shift keying protocol, which outperforms heterodyne detection for any signal power. The discrimination is composed of a quadrature measurement, feed forward and photon detection....

  17. Four-state discrimination scheme beyond the heterodyne limit

    DEFF Research Database (Denmark)

    Muller, C. R.; Castaneda, Mario A. Usuga; Wittmann, C.

    2012-01-01

    We propose and experimentally demonstrate a hybrid discrimination scheme for the quadrature phase shift keying protocol, which outperforms heterodyne detection for any signal power. The discrimination is composed of a quadrature measurement, feed forward and photon detection.......We propose and experimentally demonstrate a hybrid discrimination scheme for the quadrature phase shift keying protocol, which outperforms heterodyne detection for any signal power. The discrimination is composed of a quadrature measurement, feed forward and photon detection....

  18. 混合值不完备决策信息系统的粗糙分类方法%Rough classification method in incomplete decision information system with hybrid value.

    Institute of Scientific and Technical Information of China (English)

    黄恒秋; 曾玲

    2011-01-01

    A classification method is presented based on the combination of neighborhood connection degree rough set and Bayesian theory in incomplete decision information system with hybrid value.A new attribute discernibility matrix-identical-discrepancy-contrary discernibility matrix is defined, /-assignment reduction algorithm based on identical-discrepancy-contrary discernibility matrix is proposed.In addition,a Bayesian decision criterion of minimum error rate based on neighborhood connection degree rough set is established to classify the object with hybrid attribute value and incomplete data in reduction decision information system.Experiments show that new method is objective and feasible.%针对混合值不完备决策信息系统,提出一种将邻域联系度粗糙集与贝叶斯理论相结合的分类方法.定义了一种新的属性辨识矩阵——同异反辨识矩阵,给出了基于同异反辨识矩阵的t分配约简算法,以及对约简后的决策信息系统建立基于邻域联系度粗糙集的最小错误率贝叶斯决策准则,用于对含有混合属性值以及不完备数据的对象进行分类.实验表明所提出的方法是客观有效的.

  19. An improved unsupervised classification scheme for polarimetric SAR image with MCSM-Wishart%一种改进的全极化SAR图像MCSM-Wishart非监督分类方法

    Institute of Scientific and Technical Information of China (English)

    陈军; 杜培军; 谭琨

    2015-01-01

    针对H/Alpha/A-Wishart非监督分类算法存在的未充分提取SAR图像极化信息和分类精度低等问题,引入多分量散射模型( multiple-component scattering model,MCSM)分解,提出了一个适用于全极化SAR图像非监督分类的MCSM-Wishart算法。首先对全极化SAR图像进行MCSM分解,提取体散射、二次散射、螺旋体散射、表面散射和线散射极化信息,采用迭代自组织数据分析技术( iterative self-organizing data analysis technique,ISODATA)的非监督分类算法进行聚类;然后通过基于描述多视协方差矩阵的复Wishart分布的迭代分类得到分类结果。以南京溧水和盐城滨海湿地的ALOS PALSAR图像为研究数据,比较了H/Alpha-Wishart算法、H/Alpha/A-Wishart算法、MCSM-Wishart算法和监督-Wishart算法4种分类方法。研究结果表明,MCSM-Wishart分类算法在效率、总体准确率和Kappa系数等指标上均较原始分类器有一定的提高;将ISODATA聚类算法应用于复Wishart分布的迭代分类器中,可有效提高分类的精度。%To tackle the problems of insufficiently extracting polarimetric information from PolSAR image and low classification accuracy of H/Alpha/A - Wishart unsupervised classification algorithm, this paper proposes an adapted algorithm named MCSM - Wishart by imposing multiple - component scattering model ( MCSM ) decomposition to fit unsupervised classification of polarimetric SAR image. Firstly, various kinds of polarimetric information such as volume scatter, double scatter, helix scatter, surface scatter and wire scatter can be extracted from the image by MCSM decomposition, and iterative self-organizing data analysis( ISODATA) technique is used for clustering. Then iterative classification based on complex Wishart distribution is used to obtain the final result. H/Alpha-Wishart, H/Alpha/A-Wishart, MCSM-Wishart and supervised-Wishart algorithms are compared with each other based on two research plots conducted

  20. Position list word aligned hybrid

    DEFF Research Database (Denmark)

    Deliege, Francois; Pedersen, Torben Bach

    2010-01-01

    Compressed bitmap indexes are increasingly used for efficiently querying very large and complex databases. The Word Aligned Hybrid (WAH) bitmap compression scheme is commonly recognized as the most efficient compression scheme in terms of CPU efficiency. However, WAH compressed bitmaps use a lot...... of storage space. This paper presents the Position List Word Aligned Hybrid (PLWAH) compression scheme that improves significantly over WAH compression by better utilizing the available bits and new CPU instructions. For typical bit distributions, PLWAH compressed bitmaps are often half the size of WAH...

  1. Agriculture classification using POLSAR data

    DEFF Research Database (Denmark)

    Skriver, Henning; Dall, Jørgen; Ferro-Famil, Laurent

    2005-01-01

    in the crop canopy, particularly between the response of the canopy itself and soil response. It is expected that PolInSAR data will add to the classification potential of POLSAR data by their sensitivity to the vertical distribution of scatterers. Different approaches have been used to classify SAR data...... content of the SAR data they attempt to generate robust, widely applicable methods, which are nonetheless capable of taking local conditions into account. In this paper a classification approach is presented, that uses a knowledge-based approach, where the crops are first classified into broad classes, i...... of the classification process is not as well established as the first part, and both a supervised approach and a knowledge-based approach have been evaluated. Both POLSAR and PolInSAR data may be included in the classification scheme. The classification approach has been evaluated using data from the Danish EMISAR...

  2. The Classification of Theological Literature: A Commentary and Annotated Bibliography.

    Science.gov (United States)

    Gorman, G. E.

    1985-01-01

    This survey lists and comments upon recent classificatory writings which focus on various facets of the Christian tradition and identifies 179 articles and schemes devoted to theological classification: generalia, specific classifications (Dewey Decimal, Library of Congress, Roman Catholic, Union Theological Seminary, special schemes and…

  3. Proposed Classification of Software for CAMAC

    DEFF Research Database (Denmark)

    Christensen, Palle; Moszczynskii, J. J.; Nicolaysen, O. P.

    1974-01-01

    This proposed classification of CAMAC software is an extension of the scheme used for the CAMAC hardware product guide. An example of a CAMAC software guide illustrates the use of this classification. A form summarising the data needed for the exchange of software documentation is included...

  4. A Novel Classification of Concentration Units.

    Science.gov (United States)

    MacCarthy, Patrick

    1983-01-01

    Presents a classification scheme that organizes concentration units (such as molarity) into four logical classes. These classes clearly illustrate relationships and differences between the various units. The scheme is operationally simple to apply and removes the apparent arbitrariness of definitions as normally presented. (Author/JN)

  5. Hybridized tetraquarks

    Directory of Open Access Journals (Sweden)

    A. Esposito

    2016-07-01

    Full Text Available We propose a new interpretation of the neutral and charged X,Z exotic hadron resonances. Hybridized-tetraquarks are neither purely compact tetraquark states nor bound or loosely bound molecules but rather a manifestation of the interplay between the two. While meson molecules need a negative or zero binding energy, its counterpart for h-tetraquarks is required to be positive. The formation mechanism of this new class of hadrons is inspired by that of Feshbach metastable states in atomic physics. The recent claim of an exotic resonance in the Bs0π± channel by the D0 Collaboration and the negative result presented subsequently by the LHCb Collaboration are understood in this scheme, together with a considerable portion of available data on X,Z particles. Considerations on a state with the same quantum numbers as the X(5568 are also made.

  6. Hybridized Tetraquarks

    CERN Document Server

    Esposito, A.; Polosa, A.D.

    2016-01-01

    We propose a new interpretation of the neutral and charged X, Z exotic hadron resonances. Hybridized-tetraquarks are neither purely compact tetraquark states nor bound or loosely bound molecules. The latter would require a negative or zero binding energy whose counterpart in h-tetraquarks is a positive quantity. The formation mechanism of this new class of hadrons is inspired by that of Feshbach metastable states in atomic physics. The recent claim of an exotic resonance in the Bs pi+- channel by the D0 collaboration and the negative result presented subsequently by the LHCb collaboration are understood in this scheme, together with a considerable portion of available data on X, Z particles. Considerations on a state with the same quantum numbers as the X(5568) are also made.

  7. Development of a two-stage gene selection method that incorporates a novel hybrid approach using the cuckoo optimization algorithm and harmony search for cancer classification.

    Science.gov (United States)

    Elyasigomari, V; Lee, D A; Screen, H R C; Shaheed, M H

    2017-03-01

    For each cancer type, only a few genes are informative. Due to the so-called 'curse of dimensionality' problem, the gene selection task remains a challenge. To overcome this problem, we propose a two-stage gene selection method called MRMR-COA-HS. In the first stage, the minimum redundancy and maximum relevance (MRMR) feature selection is used to select a subset of relevant genes. The selected genes are then fed into a wrapper setup that combines a new algorithm, COA-HS, using the support vector machine as a classifier. The method was applied to four microarray datasets, and the performance was assessed by the leave one out cross-validation method. Comparative performance assessment of the proposed method with other evolutionary algorithms suggested that the proposed algorithm significantly outperforms other methods in selecting a fewer number of genes while maintaining the highest classification accuracy. The functions of the selected genes were further investigated, and it was confirmed that the selected genes are biologically relevant to each cancer type.

  8. A Heuristic Hierarchical Scheme for Academic Search and Retrieval

    DEFF Research Database (Denmark)

    Amolochitis, Emmanouil; Christou, Ioannis T.; Tan, Zheng-Hua

    2013-01-01

    We present PubSearch, a hybrid heuristic scheme for re-ranking academic papers retrieved from standard digital libraries such as the ACM Portal. The scheme is based on the hierarchical combination of a custom implementation of the term frequency heuristic, a time-depreciated citation score...

  9. A repeat-until-success quantum computing scheme

    Energy Technology Data Exchange (ETDEWEB)

    Beige, A [School of Physics and Astronomy, University of Leeds, Leeds LS2 9JT (United Kingdom); Lim, Y L [DSO National Laboratories, 20 Science Park Drive, Singapore 118230, Singapore (Singapore); Kwek, L C [Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore 117542, Singapore (Singapore)

    2007-06-15

    Recently we proposed a hybrid architecture for quantum computing based on stationary and flying qubits: the repeat-until-success (RUS) quantum computing scheme. The scheme is largely implementation independent. Despite the incompleteness theorem for optical Bell-state measurements in any linear optics set-up, it allows for the implementation of a deterministic entangling gate between distant qubits. Here we review this distributed quantum computation scheme, which is ideally suited for integrated quantum computation and communication purposes.

  10. [Susceptibility to strategy of the drug component of the IPHCC+RxGroups classification system in a risk-adjusted morbidity compensation scheme--a conceptional and data-supported analysis].

    Science.gov (United States)

    Behrend, C; Felder, S; Busse, R

    2007-01-01

    A report commissioned by the German Ministry of Health recommends to the existing scheme for calculating risk-adjusted transfers to sickness funds supplement with the IPHCC+RxGroups method. The method is based on inpatient diagnoses and prescribed drugs as health status measures deduced from prior use. The present study investigates the sickness fund's expected net return from gaming based on the drug component of the risk adjuster. The study explores three possible strategies using the RxGroups method. For the stimulations, insurees are assigned to additional indications or to higher valued RxGroups within the same indication. Then, costs and financial benefits attributable to the altered drug use are estimated and compared with the status quo. The study uses 2000 and 2001 sample data of more than 370,000 insurees of Germany's company-based sickness funds system (BKK). While upgrading increases overall costs, it can be beneficial for the individual sickness funds. Their net return crucially depends on the number of sickness funds gaming the system: the more participating in the game, the smaller is the average net return. Moreover, not participating often is even worse, which in turn points to a prisoner's dilemma. When extending the risk adjustment scheme in social health insurance, the German legislator should take into account the perverse incentives of risk adjusters such as the described prescription drug model.

  11. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  12. Classification of Bacteriocins from Gram-Positive Bacteria

    Science.gov (United States)

    Rea, Mary C.; Ross, R. Paul; Cotter, Paul D.; Hill, Colin

    Bacteriocins are ribosomally synthesised antimicrobial peptides produced by bacteria, including many Gram-positive species. The classification of bacteriocins from Gram-positive bacteria is complicated by their heterogeneity and thus, as the number of Gram-positive bacteriocins identified has continued to increase, classification schemes have had to continuously evolve. Here, we review the various classification approaches, both historical and current, their underlying scientific basis and their relative merit, and suggest a rational scheme given the state of the art.

  13. Generalized Group Signature Scheme

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    The concept of generalized group signature scheme will bepresent. Based on the generalized secret sharing scheme proposed by Lin and Ha rn, a non-interactive approach is designed for realizing such generalized group signature scheme. Using the new scheme, the authorized subsets of the group in w hich the group member can cooperate to produce the valid signature for any messa ge can be randomly specified

  14. Finite Boltzmann schemes

    NARCIS (Netherlands)

    Sman, van der R.G.M.

    2006-01-01

    In the special case of relaxation parameter = 1 lattice Boltzmann schemes for (convection) diffusion and fluid flow are equivalent to finite difference/volume (FD) schemes, and are thus coined finite Boltzmann (FB) schemes. We show that the equivalence is inherent to the homology of the

  15. MIDI Programming in Scheme

    DEFF Research Database (Denmark)

    Nørmark, Kurt

    2010-01-01

    A Scheme representation of Standard MIDI Files is proposed. The Scheme expressions are defined and constrained by an XML-language, which in the starting point is inspired by a MIDI XML event language made by the MIDI Manufactures Association. The representation of Standard MIDI Files in Scheme ma...

  16. MIDI Programming in Scheme

    DEFF Research Database (Denmark)

    Nørmark, Kurt

    2010-01-01

    A Scheme representation of Standard MIDI Files is proposed. The Scheme expressions are defined and constrained by an XML-language, which in the starting point is inspired by a MIDI XML event language made by the MIDI Manufactures Association. The representation of Standard MIDI Files in Scheme ma...

  17. Scheme Program Documentation Tools

    DEFF Research Database (Denmark)

    Nørmark, Kurt

    2004-01-01

    This paper describes and discusses two different Scheme documentation tools. The first is SchemeDoc, which is intended for documentation of the interfaces of Scheme libraries (APIs). The second is the Scheme Elucidator, which is for internal documentation of Scheme programs. Although the tools...... are separate and intended for different documentation purposes they are related to each other in several ways. Both tools are based on XML languages for tool setup and for documentation authoring. In addition, both tools rely on the LAML framework which---in a systematic way---makes an XML language available...

  18. Stand-off detection and classification of CBRNe using a Lidar system based on a high power femtosecond laser

    Science.gov (United States)

    Izawa, Jun; Yokozawa, Takeshi; Kurata, Takao; Yoshida, Akihiro; Mastunaga, Yasushi; Somekawa, Toshihiro; Eto, Shuzo; Manago, Naohiro; Horisawa, Hideyuki; Yamaguchi, Shigeru; Fujii, Takashi; Kuze, Hiroaki

    2014-10-01

    We propose a stand-off system that enables detection and classification of CBRNe (Chemical, Biological, Radioactive, Nuclear aerosol and explosive solids). The system is an integrated lidar using a high-power (terawatt) femtosecond laser. The detection and classification of various hazardous targets with stand-off distances from several hundred meters to a few kilometers are achieved by means of laser-induced breakdown spectroscopy (LIBS) and two-photon fluorescence (TPF) techniques. In this work, we report on the technical considerations on the system design of the present hybrid lidar system consisting of a nanosecond laser and a femtosecond laser. Also, we describe the current progress in our laboratory experiments that have demonstrated the stand-off detection and classification of various simulants. For the R and N detection scheme, cesium chloride aerosols have successfully been detected by LIBS using a high-power femtosecond laser. For the B detection scheme, TPF signals of organic aerosols such as riboflavin have clearly been recorded. In addition, a compact femtosecond laser has been employed for the LIBS classification of organic plastics employed as e-simulants.

  19. Elucidation of molecular kinetic schemes from macroscopic traces using system identification.

    Science.gov (United States)

    Fribourg, Miguel; Logothetis, Diomedes E; González-Maeso, Javier; Sealfon, Stuart C; Galocha-Iragüen, Belén; Las-Heras Andrés, Fernando; Brezina, Vladimir

    2017-02-01

    Overall cellular responses to biologically-relevant stimuli are mediated by networks of simpler lower-level processes. Although information about some of these processes can now be obtained by visualizing and recording events at the molecular level, this is still possible only in especially favorable cases. Therefore the development of methods to extract the dynamics and relationships between the different lower-level (microscopic) processes from the overall (macroscopic) response remains a crucial challenge in the understanding of many aspects of physiology. Here we have devised a hybrid computational-analytical method to accomplish this task, the SYStems-based MOLecular kinetic scheme Extractor (SYSMOLE). SYSMOLE utilizes system-identification input-output analysis to obtain a transfer function between the stimulus and the overall cellular response in the Laplace-transformed domain. It then derives a Markov-chain state molecular kinetic scheme uniquely associated with the transfer function by means of a classification procedure and an analytical step that imposes general biological constraints. We first tested SYSMOLE with synthetic data and evaluated its performance in terms of its rate of convergence to the correct molecular kinetic scheme and its robustness to noise. We then examined its performance on real experimental traces by analyzing macroscopic calcium-current traces elicited by membrane depolarization. SYSMOLE derived the correct, previously known molecular kinetic scheme describing the activation and inactivation of the underlying calcium channels and correctly identified the accepted mechanism of action of nifedipine, a calcium-channel blocker clinically used in patients with cardiovascular disease. Finally, we applied SYSMOLE to study the pharmacology of a new class of glutamate antipsychotic drugs and their crosstalk mechanism through a heteromeric complex of G protein-coupled receptors. Our results indicate that our methodology can be successfully

  20. Elucidation of molecular kinetic schemes from macroscopic traces using system identification

    Science.gov (United States)

    González-Maeso, Javier; Sealfon, Stuart C.; Galocha-Iragüen, Belén; Brezina, Vladimir

    2017-01-01

    Overall cellular responses to biologically-relevant stimuli are mediated by networks of simpler lower-level processes. Although information about some of these processes can now be obtained by visualizing and recording events at the molecular level, this is still possible only in especially favorable cases. Therefore the development of methods to extract the dynamics and relationships between the different lower-level (microscopic) processes from the overall (macroscopic) response remains a crucial challenge in the understanding of many aspects of physiology. Here we have devised a hybrid computational-analytical method to accomplish this task, the SYStems-based MOLecular kinetic scheme Extractor (SYSMOLE). SYSMOLE utilizes system-identification input-output analysis to obtain a transfer function between the stimulus and the overall cellular response in the Laplace-transformed domain. It then derives a Markov-chain state molecular kinetic scheme uniquely associated with the transfer function by means of a classification procedure and an analytical step that imposes general biological constraints. We first tested SYSMOLE with synthetic data and evaluated its performance in terms of its rate of convergence to the correct molecular kinetic scheme and its robustness to noise. We then examined its performance on real experimental traces by analyzing macroscopic calcium-current traces elicited by membrane depolarization. SYSMOLE derived the correct, previously known molecular kinetic scheme describing the activation and inactivation of the underlying calcium channels and correctly identified the accepted mechanism of action of nifedipine, a calcium-channel blocker clinically used in patients with cardiovascular disease. Finally, we applied SYSMOLE to study the pharmacology of a new class of glutamate antipsychotic drugs and their crosstalk mechanism through a heteromeric complex of G protein-coupled receptors. Our results indicate that our methodology can be successfully

  1. Hybrid detection of lung nodules on CT scan images

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Lin; Tan, Yongqiang; Schwartz, Lawrence H.; Zhao, Binsheng, E-mail: bz2166@columbia.edu [Department of Radiology, Columbia University Medical Center, 630 West 168th Street, New York, New York 10032 (United States)

    2015-09-15

    Purpose: The diversity of lung nodules poses difficulty for the current computer-aided diagnostic (CAD) schemes for lung nodule detection on computed tomography (CT) scan images, especially in large-scale CT screening studies. We proposed a novel CAD scheme based on a hybrid method to address the challenges of detection in diverse lung nodules. Methods: The hybrid method proposed in this paper integrates several existing and widely used algorithms in the field of nodule detection, including morphological operation, dot-enhancement based on Hessian matrix, fuzzy connectedness segmentation, local density maximum algorithm, geodesic distance map, and regression tree classification. All of the adopted algorithms were organized into tree structures with multi-nodes. Each node in the tree structure aimed to deal with one type of lung nodule. Results: The method has been evaluated on 294 CT scans from the Lung Image Database Consortium (LIDC) dataset. The CT scans were randomly divided into two independent subsets: a training set (196 scans) and a test set (98 scans). In total, the 294 CT scans contained 631 lung nodules, which were annotated by at least two radiologists participating in the LIDC project. The sensitivity and false positive per scan for the training set were 87% and 2.61%. The sensitivity and false positive per scan for the testing set were 85.2% and 3.13%. Conclusions: The proposed hybrid method yielded high performance on the evaluation dataset and exhibits advantages over existing CAD schemes. We believe that the present method would be useful for a wide variety of CT imaging protocols used in both routine diagnosis and screening studies.

  2. 關於圖書分類法的修訂 Concerning the Revision of Classification System

    Directory of Open Access Journals (Sweden)

    Ho-chin Chen

    1999-03-01

    Full Text Available 無For reviewing a classification scheme, we usually look in much detail at its traditional features such as detailed schedules, hospital notation, a supportive index and its adaptability. Yet another desirable feature, a good and financially secure revision programme, is a key point to the success of classification scheme. The author traces the history of revision processes of three successful classification systems (Dewey Decimal Classification, Library of Congress Classification and Universal Decimal Classification , and attempt to recommend the better revision mechanism for Lai's New Classification Scheme for Chinese Libraries ( 中國 圖書分類法in Taiwan

  3. Feature Extraction and Selection Scheme for Intelligent Engine Fault Diagnosis Based on 2DNMF, Mutual Information, and NSGA-II

    Directory of Open Access Journals (Sweden)

    Peng-yuan Liu

    2016-01-01

    Full Text Available A novel feature extraction and selection scheme is presented for intelligent engine fault diagnosis by utilizing two-dimensional nonnegative matrix factorization (2DNMF, mutual information, and nondominated sorting genetic algorithms II (NSGA-II. Experiments are conducted on an engine test rig, in which eight different engine operating conditions including one normal condition and seven fault conditions are simulated, to evaluate the presented feature extraction and selection scheme. In the phase of feature extraction, the S transform technique is firstly utilized to convert the engine vibration signals to time-frequency domain, which can provide richer information on engine operating conditions. Then a novel feature extraction technique, named two-dimensional nonnegative matrix factorization, is employed for characterizing the time-frequency representations. In the feature selection phase, a hybrid filter and wrapper scheme based on mutual information and NSGA-II is utilized to acquire a compact feature subset for engine fault diagnosis. Experimental results by adopted three different classifiers have demonstrated that the proposed feature extraction and selection scheme can achieve a very satisfying classification performance with fewer features for engine fault diagnosis.

  4. Convertible Proxy Signcryption Scheme

    Institute of Scientific and Technical Information of China (English)

    李继国; 李建中; 曹珍富; 张亦辰

    2004-01-01

    In 1996, Mambo et al introduced the concept of proxy signature. However, proxy signature can only provide the delegated authenticity and cannot provide confidentiality. Recently, Gamage et al and Chan and Wei proposed different proxy signcryption schemes respectively, which extended the concept of proxy signature.However, only the specified receiver can decrypt and verify the validity of proxy signcryption in their schemes.To protect the receiver' s benefit in case of a later dispute, Wu and Hsu proposed a convertible authenticated encryption scheme, which carn enable the receiver to convert signature into an ordinary one that can be verified by anyone. Based on Wu and Hsu' s scheme and improved Kim' s scheme, we propose a convertible proxy signcryption scheme. The security of the proposed scheme is based on the intractability of reversing the one-way hash function and solving the discrete logarithm problem. The proposed scheme can satisfy all properties of strong proxy signature and withstand the public key substitution attack and does not use secure channel. In addition, the proposed scheme can be extended to convertible threshold proxy signcryption scheme.

  5. Discriminant forest classification method and system

    Science.gov (United States)

    Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

    2012-11-06

    A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

  6. A MULTI-CRC SELECTIVE HARQ SCHEME FOR MIMO SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A multi-Cyclic Redundancy Check (CRC) selective Hybrid Automatic-Repeat-reQuest (HARQ) scheme for improving the throughput efficiency of Multiple Input Multiple Output (MIMO) systems is proposed in this paper. According to different feedback information from the receiver, the proposed HARQ scheme employs two strategies, referred to as retransmission frame selection and space diversity. These two strategies decrease the successive frame errors upon retransmission. Theoretic analysis and computer simulation results show that this HARQ scheme achieves higher throughput than the existing HARQ schemes even in poor conditions of low Signal-to-Noise Ratio (SNR).

  7. 光伏和储能并网物理数字混合仿真实验系统方案%A Physical Digital Hybrid Simulation Experimental Scheme for Photovoltaic and Energy Storage Grid-connected System

    Institute of Scientific and Technical Information of China (English)

    孟超; 吴涛; 刘平; 沈宇; 刘辉; 王丰

    2013-01-01

    分析了物理数字混合仿真的原理,介绍了一种由光伏阵列、储能电池和RTDS实时数字仿真系统等设备共同组成的仿真实验平台.将实际的光伏电站特征信息接入数字仿真系统,研究光伏电站接入电网后系统稳定特性的变化.对混合仿真系统中物理数字接口进行了详细说明,提出了混合仿真实验的流程,通过实例验证了方案的正确性.%This paper analyzes the principle of hybrid simulation, and introduces an experiment simulation environment which is composed of the photovoltaic array, storage batteries and the real-time digital simulation (RTDS) system. The aim of this environment is to study the changes in grid stability characteristics after the access of photovoltaic (PV) power station to the grid by transmitting the real attribute information of PV power station to RTDS. The interface between real equipment and RTDS in the hybrid simulation system is explained in detail. The process of hybrid simulation experiment is proposed. The solution is verified by experimental results.

  8. Efficient Fingercode Classification

    Science.gov (United States)

    Sun, Hong-Wei; Law, Kwok-Yan; Gollmann, Dieter; Chung, Siu-Leung; Li, Jian-Bin; Sun, Jia-Guang

    In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e. g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

  9. Difference Schemes and Applications

    Science.gov (United States)

    2015-02-06

    of the shallow water equations that is well suited for complex geometries and moving boundaries. Another (similar) regularization of...the solid wall extrapolation followed by the interpolation in the phase space (by solving the Riemann problem between the internal cell averages and...scheme. This Godunov-type scheme enjoys all major advantages of Riemann -problem-solver-free, non-oscillatory central schemes and, at the same time, have

  10. Efficient Threshold Signature Scheme

    Directory of Open Access Journals (Sweden)

    Sattar J Aboud

    2012-01-01

    Full Text Available In this paper, we introduce a new threshold signature RSA-typed scheme. The proposed scheme has the characteristics of un-forgeable and robustness in random oracle model. Also, signature generation and verification is entirely non-interactive. In addition, the length of the entity signature participate is restricted by a steady times of the length of the RSA signature modulus. Also, the signing process of the proposed scheme is more efficient in terms of time complexity and interaction.

  11. Stateless Transitive Signature Schemes

    Institute of Scientific and Technical Information of China (English)

    MA Chun-guang; CAI Man-chun; YANG Yi-xian

    2004-01-01

    A new practical method is introduced to transform the stateful transitive signature scheme to stateless one without the loss of security. According to the approach, two concrete stateless transitive signature schemes based on Factoring and RSA are presented respectively. Under the assumption of the hardness of factoring and one-more- RSA-inversion problem, both two schemes are secure under the adaptive chosen-message attacks in random oracle model.

  12. Simplification of the unified gas kinetic scheme

    Science.gov (United States)

    Chen, Songze; Guo, Zhaoli; Xu, Kun

    2016-08-01

    The unified gas kinetic scheme (UGKS) is an asymptotic preserving (AP) scheme for kinetic equations. It is superior for transition flow simulation and has been validated in the past years. However, compared to the well-known discrete ordinate method (DOM), which is a classical numerical method solving the kinetic equations, the UGKS needs more computational resources. In this study, we propose a simplification of the unified gas kinetic scheme. It allows almost identical numerical cost as the DOM, but predicts numerical results as accurate as the UGKS. In the simplified scheme, the numerical flux for the velocity distribution function and the numerical flux for the macroscopic conservative quantities are evaluated separately. The equilibrium part of the UGKS flux is calculated by analytical solution instead of the numerical quadrature in velocity space. The simplification is equivalent to a flux hybridization of the gas kinetic scheme for the Navier-Stokes (NS) equations and the conventional discrete ordinate method. Several simplification strategies are tested, through which we can identify the key ingredient of the Navier-Stokes asymptotic preserving property. Numerical tests show that, as long as the collision effect is built into the macroscopic numerical flux, the numerical scheme is Navier-Stokes asymptotic preserving, regardless the accuracy of the microscopic numerical flux for the velocity distribution function.

  13. Comparison of Classification Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery

    OpenAIRE

    Congcong Li; Jie Wang; Lei Wang; Luanyun Hu; Peng Gong

    2014-01-01

    Although a large number of new image classification algorithms have been developed, they are rarely tested with the same classification task. In this research, with the same Landsat Thematic Mapper (TM) data set and the same classification scheme over Guangzhou City, China, we tested two unsupervised and 13 supervised classification algorithms, including a number of machine learning algorithms that became popular in remote sensing during the past 20 years. Our analysis focused primarily on ...

  14. An analysis platform for multiscale hydrogeologic modeling with emphasis on hybrid multiscale methods.

    Science.gov (United States)

    Scheibe, Timothy D; Murphy, Ellyn M; Chen, Xingyuan; Rice, Amy K; Carroll, Kenneth C; Palmer, Bruce J; Tartakovsky, Alexandre M; Battiato, Ilenia; Wood, Brian D

    2015-01-01

    One of the most significant challenges faced by hydrogeologic modelers is the disparity between the spatial and temporal scales at which fundamental flow, transport, and reaction processes can best be understood and quantified (e.g., microscopic to pore scales and seconds to days) and at which practical model predictions are needed (e.g., plume to aquifer scales and years to centuries). While the multiscale nature of hydrogeologic problems is widely recognized, technological limitations in computation and characterization restrict most practical modeling efforts to fairly coarse representations of heterogeneous properties and processes. For some modern problems, the necessary level of simplification is such that model parameters may lose physical meaning and model predictive ability is questionable for any conditions other than those to which the model was calibrated. Recently, there has been broad interest across a wide range of scientific and engineering disciplines in simulation approaches that more rigorously account for the multiscale nature of systems of interest. In this article, we review a number of such approaches and propose a classification scheme for defining different types of multiscale simulation methods and those classes of problems to which they are most applicable. Our classification scheme is presented in terms of a flowchart (Multiscale Analysis Platform), and defines several different motifs of multiscale simulation. Within each motif, the member methods are reviewed and example applications are discussed. We focus attention on hybrid multiscale methods, in which two or more models with different physics described at fundamentally different scales are directly coupled within a single simulation. Very recently these methods have begun to be applied to groundwater flow and transport simulations, and we discuss these applications in the context of our classification scheme. As computational and characterization capabilities continue to improve

  15. Hybrid undulator numerical optimization

    Energy Technology Data Exchange (ETDEWEB)

    Hairetdinov, A.H. [Kurchatov Institute, Moscow (Russian Federation); Zukov, A.A. [Solid State Physics Institute, Chernogolovka (Russian Federation)

    1995-12-31

    3D properties of the hybrid undulator scheme arc studied numerically using PANDIRA code. It is shown that there exist two well defined sets of undulator parameters which provide either maximum on-axis field amplitude or minimal higher harmonics amplitude of the basic undulator field. Thus the alternative between higher field amplitude or pure sinusoidal field exists. The behavior of the undulator field amplitude and harmonics structure for a large set of (undulator gap)/(undulator wavelength) values is demonstrated.

  16. Observational and Physical Classification of Supernovae

    CERN Document Server

    Gal-Yam, Avishay

    2016-01-01

    This chapter describes the current classification scheme of supernovae (SNe). This scheme has evolved over many decades and now includes numerous SN Types and sub-types. Many of these are universally recognized, while there are controversies regarding the definitions, membership and even the names of some sub-classes; we will try to review here the commonly-used nomenclature, noting the main variants when possible. SN Types are defined according to observational properties; mostly visible-light spectra near maximum light, as well as according to their photometric properties. However, a long-term goal of SN classification is to associate observationally-defined classes with specific physical explosive phenomena. We show here that this aspiration is now finally coming to fruition, and we establish the SN classification scheme upon direct observational evidence connecting SN groups with specific progenitor stars. Observationally, the broad class of Type II SNe contains objects showing strong spectroscopic signat...

  17. Multiresolution signal decomposition schemes

    NARCIS (Netherlands)

    J. Goutsias (John); H.J.A.M. Heijmans (Henk)

    1998-01-01

    textabstract[PNA-R9810] Interest in multiresolution techniques for signal processing and analysis is increasing steadily. An important instance of such a technique is the so-called pyramid decomposition scheme. This report proposes a general axiomatic pyramid decomposition scheme for signal analysis

  18. Multiresolution signal decomposition schemes

    NARCIS (Netherlands)

    Goutsias, J.; Heijmans, H.J.A.M.

    1998-01-01

    [PNA-R9810] Interest in multiresolution techniques for signal processing and analysis is increasing steadily. An important instance of such a technique is the so-called pyramid decomposition scheme. This report proposes a general axiomatic pyramid decomposition scheme for signal analysis and synthes

  19. Sleep stage classification with cross frequency coupling.

    Science.gov (United States)

    Sanders, Teresa H; McCurry, Mark; Clements, Mark A

    2014-01-01

    Sleep is a key requirement for an individual's health, though currently the options to study sleep rely largely on manual visual classification methods. In this paper we propose a new scheme for automated offline classification based upon cross-frequency-coupling (CFC) and compare it to the traditional band power estimation and the more recent preferential frequency band information estimation. All three approaches allowed sleep stage classification and provided whole-night visualization of sleep stages. Surprisingly, the simple average power in band classification achieved better overall performance than either the preferential frequency band information estimation or the CFC approach. However, combined classification with both average power and CFC features showed improved classification over either approach used singly.

  20. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  1. Hybrid Baryons

    CERN Document Server

    Page, P R

    2003-01-01

    We review the status of hybrid baryons. The only known way to study hybrids rigorously is via excited adiabatic potentials. Hybrids can be modelled by both the bag and flux-tube models. The low-lying hybrid baryon is N 1/2^+ with a mass of 1.5-1.8 GeV. Hybrid baryons can be produced in the glue-rich processes of diffractive gamma N and pi N production, Psi decays and p pbar annihilation.

  2. Use of adaptive hybrid filtering process in Crohn's disease lesion detection from real capsule endoscopy videos.

    Science.gov (United States)

    Charisis, Vasileios S; Hadjileontiadis, Leontios J

    2016-03-01

    The aim of this Letter is to present a new capsule endoscopy (CE) image analysis scheme for the detection of small bowel ulcers that relate to Crohn's disease. More specifically, this scheme is based on: (i) a hybrid adaptive filtering (HAF) process, that utilises genetic algorithms to the curvelet-based representation of images for efficient extraction of the lesion-related morphological characteristics, (ii) differential lacunarity (DL) analysis for texture feature extraction from the HAF-filtered images and (iii) support vector machines for robust classification performance. For the training of the proposed scheme, namely HAF-DL, an 800-image database was used and the evaluation was based on ten 30-second long endoscopic videos. Experimental results, along with comparison with other related efforts, have shown that the HAF-DL approach evidently outperforms the latter in the field of CE image analysis for automated lesion detection, providing higher classification results. The promising performance of HAF-DL paves the way for a complete computer-aided diagnosis system that could support the physicians' clinical practice.

  3. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  4. A Fuzzy Commitment Scheme

    CERN Document Server

    Al-saggaf, Alawi A

    2008-01-01

    This paper attempt has been made to explain a fuzzy commitment scheme. In the conventional Commitment schemes, both committed string m and valid opening key are required to enable the sender to prove the commitment. However there could be many instances where the transmission involves noise or minor errors arising purely because of the factors over which neither the sender nor the receiver have any control. The fuzzy commitment scheme presented in this paper is to accept the opening key that is close to the original one in suitable distance metric, but not necessarily identical. The concept itself is illustrated with the help of simple situation.

  5. Xenolog classification.

    Science.gov (United States)

    Darby, Charlotte A; Stolzer, Maureen; Ropp, Patrick J; Barker, Daniel; Durand, Dannie

    2017-03-01

    Orthology analysis is a fundamental tool in comparative genomics. Sophisticated methods have been developed to distinguish between orthologs and paralogs and to classify paralogs into subtypes depending on the duplication mechanism and timing, relative to speciation. However, no comparable framework exists for xenologs: gene pairs whose history, since their divergence, includes a horizontal transfer. Further, the diversity of gene pairs that meet this broad definition calls for classification of xenologs with similar properties into subtypes. We present a xenolog classification that uses phylogenetic reconciliation to assign each pair of genes to a class based on the event responsible for their divergence and the historical association between genes and species. Our classes distinguish between genes related through transfer alone and genes related through duplication and transfer. Further, they separate closely-related genes in distantly-related species from distantly-related genes in closely-related species. We present formal rules that assign gene pairs to specific xenolog classes, given a reconciled gene tree with an arbitrary number of duplications and transfers. These xenology classification rules have been implemented in software and tested on a collection of ∼13 000 prokaryotic gene families. In addition, we present a case study demonstrating the connection between xenolog classification and gene function prediction. The xenolog classification rules have been implemented in N otung 2.9, a freely available phylogenetic reconciliation software package. http://www.cs.cmu.edu/~durand/Notung . Gene trees are available at http://dx.doi.org/10.7488/ds/1503 . durand@cmu.edu. Supplementary data are available at Bioinformatics online.

  6. Detecting Urban Transport Modes Using a Hybrid Knowledge Driven Framework from GPS Trajectory

    Directory of Open Access Journals (Sweden)

    Rahul Deb Das

    2016-11-01

    Full Text Available Transport mode information is essential for understanding people’s movement behavior and travel demand estimation. Current approaches extract travel information once the travel is complete. Such approaches are limited in terms of generating just-in-time information for a number of mobility based applications, e.g., real time mode specific patronage estimation. In order to detect the transport modalities from GPS trajectories, various machine learning approaches have already been explored. However, the majority of them produce only a single conclusion from a given set of evidences, ignoring the uncertainty of any mode classification. Also, the existing machine learning approaches fall short in explaining their reasoning scheme. In contrast, a fuzzy expert system can explain its reasoning scheme in a human readable format along with a provision of inferring different outcome possibilities, but lacks the adaptivity and learning ability of machine learning. In this paper, a novel hybrid knowledge driven framework is developed by integrating a fuzzy logic and a neural network to complement each other’s limitations. Thus the aim of this paper is to automate the tuning process in order to generate an intelligent hybrid model that can perform effectively in near-real time mode detection using GPS trajectory. Tests demonstrate that a hybrid knowledge driven model works better than a purely knowledge driven model and at per the machine learning models in the context of transport mode detection.

  7. Using Simulations to Investigate the Longitudinal Stability of Alternative Schemes for Classifying and Identifying Children with Reading Disabilities

    Science.gov (United States)

    Schatschneider, Christopher; Wagner, Richard K.; Hart, Sara A.; Tighe, Elizabeth L.

    2016-01-01

    The present study employed data simulation techniques to investigate the 1-year stability of alternative classification schemes for identifying children with reading disabilities. Classification schemes investigated include low performance, unexpected low performance, dual-discrepancy, and a rudimentary form of constellation model of reading…

  8. Fish Creek Watershed Lake Classification; NPRA, Alaska, 2016

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This study focuses on the development of a 20 attribute lake cover classification scheme for the Fish Creek Watershed (FCW), which is located in the National...

  9. CSR schemes in agribusiness

    DEFF Research Database (Denmark)

    Pötz, Katharina Anna; Haas, Rainer; Balzarova, Michaela

    2013-01-01

    Purpose – The rise of CSR followed a demand for CSR standards and guidelines. In a sector already characterized by a large number of standards, the authors seek to ask what CSR schemes apply to agribusiness, and how they can be systematically compared and analysed. Design....../methodology/approach – Following a deductive-inductive approach the authors develop a model to compare and analyse CSR schemes based on existing studies and on coding qualitative data on 216 CSR schemes. Findings – The authors confirm that CSR standards and guidelines have entered agribusiness and identify a complex landscape...... of schemes that can be categorized on focus areas, scales, mechanisms, origins, types and commitment levels. Research limitations/implications – The findings contribute to conceptual and empirical research on existing models to compare and analyse CSR standards. Sampling technique and depth of analysis limit...

  10. Tabled Execution in Scheme

    Energy Technology Data Exchange (ETDEWEB)

    Willcock, J J; Lumsdaine, A; Quinlan, D J

    2008-08-19

    Tabled execution is a generalization of memorization developed by the logic programming community. It not only saves results from tabled predicates, but also stores the set of currently active calls to them; tabled execution can thus provide meaningful semantics for programs that seemingly contain infinite recursions with the same arguments. In logic programming, tabled execution is used for many purposes, both for improving the efficiency of programs, and making tasks simpler and more direct to express than with normal logic programs. However, tabled execution is only infrequently applied in mainstream functional languages such as Scheme. We demonstrate an elegant implementation of tabled execution in Scheme, using a mix of continuation-passing style and mutable data. We also show the use of tabled execution in Scheme for a problem in formal language and automata theory, demonstrating that tabled execution can be a valuable tool for Scheme users.

  11. Nationwide classification of forest types of India using remote sensing and GIS.

    Science.gov (United States)

    Reddy, C Sudhakar; Jha, C S; Diwakar, P G; Dadhwal, V K

    2015-12-01

    India, a mega-diverse country, possesses a wide range of climate and vegetation types along with a varied topography. The present study has classified forest types of India based on multi-season IRS Resourcesat-2 Advanced Wide Field Sensor (AWiFS) data. The study has characterized 29 land use/land cover classes including 14 forest types and seven scrub types. Hybrid classification approach has been used for the classification of forest types. The classification of vegetation has been carried out based on the ecological rule bases followed by Champion and Seth's (1968) scheme of forest types in India. The present classification scheme has been compared with the available global and national level land cover products. The natural vegetation cover was estimated to be 29.36% of total geographical area of India. The predominant forest types of India are tropical dry deciduous and tropical moist deciduous. Of the total forest cover, tropical dry deciduous forests occupy an area of 2,17,713 km(2) (34.80%) followed by 2,07,649 km(2) (33.19%) under tropical moist deciduous forests, 48,295 km(2) (7.72%) under tropical semi-evergreen forests and 47,192 km(2) (7.54%) under tropical wet evergreen forests. The study has brought out a comprehensive vegetation cover and forest type maps based on inputs critical in defining the various categories of vegetation and forest types. This spatially explicit database will be highly useful for the studies related to changes in various forest types, carbon stocks, climate-vegetation modeling and biogeochemical cycles.

  12. Classification of debris flow phenomena in the Faroe Islands

    DEFF Research Database (Denmark)

    Dahl, Mads-Peter Jakob; E. Mortensen, Lis; Jensen, Niels H.

    2012-01-01

    Landslides and debris flow phenomena in particular constitute a threat to human activities in the Faroe Islands. As a contribution to ongoing landslide risk management research, this paper proposes a classification scheme for debris flow phenomena in the Faroe Islands. The scheme, produced through...... with international landslide classification systems, significantly increases the knowledge of debris flow phenomena and promotes a consistent terminology of these within the Faroe Islands....

  13. Spectral Classification Beyond M

    CERN Document Server

    Leggett, S K; Burgasser, A J; Jones, H R A; Marley, M S; Tsuji, T

    2004-01-01

    Significant populations of field L and T dwarfs are now known, and we anticipate the discovery of even cooler dwarfs by Spitzer and ground-based infrared surveys. However, as the number of known L and T dwarfs increases so does the range in their observational properties, and difficulties have arisen in interpreting the observations. Although modellers have made significant advances, the complexity of the very low temperature, high pressure, photospheres means that problems remain such as the treatment of grain condensation as well as incomplete and non-equilibrium molecular chemistry. Also, there are several parameters which control the observed spectral energy distribution - effective temperature, grain sedimentation efficiency, metallicity and gravity - and their effects are not well understood. In this paper, based on a splinter session, we discuss classification schemes for L and T dwarfs, their dependency on wavelength, and the effects of the parameters T_eff, f_sed, [m/H] and log g on optical and infra...

  14. Designing Z-scheme 2D-C{sub 3}N{sub 4}/Ag{sub 3}VO{sub 4} hybrid structures for improved photocatalysis and photocatalytic mechanism insight

    Energy Technology Data Exchange (ETDEWEB)

    She, Xiaojie; Yi, Jianjian; Xu, Yuanguo; Huang, Liying; Ji, Haiyan; Xu, Hui; Li, Huaming [School of the Environment and Safety Engineering, Institute for Energy Research, Jiangsu University, Zhenjiang 212013 (China); Song, Yanhua [School of Environmental and Chemical, Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003 (China)

    2017-06-15

    The two-dimensional oxygen-modified g-C{sub 3}N{sub 4} nanosheets-loaded Ag{sub 3}VO{sub 4} (2D-C{sub 3}N{sub 4}/Ag{sub 3}VO{sub 4}) photocatalysts were synthesized successfully via a facile in situ deposition method. The comprehensive characterizations were employed to characterize the morphologies, structures, chemical states, optical and electronic properties and photocatalytic performances of the samples. The 20% 2D-C{sub 3}N{sub 4}/Ag{sub 3}VO{sub 4} showed the best photocatalytic activity on the degradation of RhB and BPA. The enhanced photocatalytic activity is ascribed to the effective electron-hole separation efficiency and the larger specific surface area. The photogenerated electrons and holes can quickly separate by Z-scheme passageway in composite. Through ESR analysis, the photocatalytic mechanism was also researched in detail. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  15. XTR-Kurosawa-Desmedt Scheme

    Institute of Scientific and Technical Information of China (English)

    DING XIU-HUAN; FU ZHI-GUO; ZHANG SHU-GONG

    2009-01-01

    This paper proposes an XTR version of the Kurosawa-Desmedt scheme. Our scheme is secure against adaptive choeen-ciphertext attack under the XTR version of the Decisional Diffie-Hellman assumption in the standard model. Comparing efficiency between the Kurosawa-Desmedt scheme and the proposed XTR-Kurosawa-Desmedt scheme, we find that the proposed scheme is more efficient than the Kurosawa-Desmedt scheme both in communication and computation without compromising security.

  16. Joint detection and combining schemes in MIMO-HARQ systems

    Institute of Scientific and Technical Information of China (English)

    XIE Gang; XIONG Fang; ZHAO Yi; LIU Yuan-an

    2007-01-01

    This article mainly investigates the combining schemes for hybrid automatic retransmission request (HARQ) protocols in multiple-input multiple-output (MIMO) wireless communication systems. A novel scheme, which joins MIMO detection and HARQ combining, called mid-combining, is presented in this article. Based on the position of HARQ combining, we classify the HARQ combining schemes into three types, named pre-combining, mid-combining, and post-combining. The simulation results show that mid- combining can increase the system throughput for all SNRs.

  17. HDG schemes for stationary convection-diffusion problems

    Science.gov (United States)

    Dautov, R. Z.; Fedotov, E. M.

    2016-11-01

    For stationary linear convection-diffusion problems, we construct and study a hybridized scheme of the discontinuous Galerkin method on the basis of an extended mixed statement of the problem. Discrete schemes can be used for the solution of equations degenerating in the leading part and are stated via approximations to the solution of the problem, its gradient, the flow, and the restriction of the solution to the boundaries of elements. For the spaces of finite elements, we represent minimal conditions responsible for the solvability, stability and accuracy of the schemes.

  18. Development of a Regional Habitat Classification Scheme for the ...

    African Journals Online (AJOL)

    Cambridge Coastal Research Unit, Department of Geography, University of. Cambridge ... distribution and abundance of shallow water benthic ... for coastal zone management. To map .... pattern over each island at an altitude of 1,000 m. .... this way, a statistical population of reflectance .... World Scientific. Publishing ...

  19. Taxonomy and Classification Scheme for Artificial Space Objects

    Science.gov (United States)

    2013-09-01

    also in each orbital region separately, with different numbers of inhabitants in the different categories. The attitude state is the characteristic...asteroid spectra using a neural net- work. Journal of Geophysical Research: Planets (19912012), 99(E5):10847–10865, 1994. 11. E. Mayr. Systematics and

  20. The software invention cube: A classification scheme for software inventions

    NARCIS (Netherlands)

    Bergstra, J.A.; Klint, P.

    2008-01-01

    The patent system protects inventions. The requirement that a software invention should make ‘a technical contribution’ turns out to be untenable in practice and this raises the question, what constitutes an invention in the realm of software. The authors developed the Software Invention Cube (SWIC)