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Sample records for hybrids discriminant analysis

  1. Liquid contrabands classification based on energy dispersive X-ray diffraction and hybrid discriminant analysis

    International Nuclear Information System (INIS)

    YangDai, Tianyi; Zhang, Li

    2016-01-01

    Energy dispersive X-ray diffraction (EDXRD) combined with hybrid discriminant analysis (HDA) has been utilized for classifying the liquid materials for the first time. The XRD spectra of 37 kinds of liquid contrabands and daily supplies were obtained using an EDXRD test bed facility. The unique spectra of different samples reveal XRD's capability to distinguish liquid contrabands from daily supplies. In order to create a system to detect liquid contrabands, the diffraction spectra were subjected to HDA which is the combination of principal components analysis (PCA) and linear discriminant analysis (LDA). Experiments based on the leave-one-out method demonstrate that HDA is a practical method with higher classification accuracy and lower noise sensitivity than the other methods in this application. The study shows the great capability and potential of the combination of XRD and HDA for liquid contrabands classification.

  2. Liquid contrabands classification based on energy dispersive X-ray diffraction and hybrid discriminant analysis

    Energy Technology Data Exchange (ETDEWEB)

    YangDai, Tianyi [Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education (China); Zhang, Li, E-mail: zhangli@nuctech.com [Department of Engineering Physics, Tsinghua University, Beijing 100084 (China); Key Laboratory of Particle & Radiation Imaging (Tsinghua University), Ministry of Education (China)

    2016-02-01

    Energy dispersive X-ray diffraction (EDXRD) combined with hybrid discriminant analysis (HDA) has been utilized for classifying the liquid materials for the first time. The XRD spectra of 37 kinds of liquid contrabands and daily supplies were obtained using an EDXRD test bed facility. The unique spectra of different samples reveal XRD's capability to distinguish liquid contrabands from daily supplies. In order to create a system to detect liquid contrabands, the diffraction spectra were subjected to HDA which is the combination of principal components analysis (PCA) and linear discriminant analysis (LDA). Experiments based on the leave-one-out method demonstrate that HDA is a practical method with higher classification accuracy and lower noise sensitivity than the other methods in this application. The study shows the great capability and potential of the combination of XRD and HDA for liquid contrabands classification.

  3. Liquid contrabands classification based on energy dispersive X-ray diffraction and hybrid discriminant analysis

    Science.gov (United States)

    YangDai, Tianyi; Zhang, Li

    2016-02-01

    Energy dispersive X-ray diffraction (EDXRD) combined with hybrid discriminant analysis (HDA) has been utilized for classifying the liquid materials for the first time. The XRD spectra of 37 kinds of liquid contrabands and daily supplies were obtained using an EDXRD test bed facility. The unique spectra of different samples reveal XRD's capability to distinguish liquid contrabands from daily supplies. In order to create a system to detect liquid contrabands, the diffraction spectra were subjected to HDA which is the combination of principal components analysis (PCA) and linear discriminant analysis (LDA). Experiments based on the leave-one-out method demonstrate that HDA is a practical method with higher classification accuracy and lower noise sensitivity than the other methods in this application. The study shows the great capability and potential of the combination of XRD and HDA for liquid contrabands classification.

  4. Femtomolar detection of single mismatches by discriminant analysis of DNA hybridization events using gold nanoparticles.

    Science.gov (United States)

    Ma, Xingyi; Sim, Sang Jun

    2013-03-21

    Even though DNA-based nanosensors have been demonstrated for quantitative detection of analytes and diseases, hybridization events have never been numerically investigated for further understanding of DNA mediated interactions. Here, we developed a nanoscale platform with well-designed capture and detection gold nanoprobes to precisely evaluate the hybridization events. The capture gold nanoprobes were mono-laid on glass and the detection probes were fabricated via a novel competitive conjugation method. The two kinds of probes combined in a suitable orientation following the hybridization with the target. We found that hybridization efficiency was markedly dependent on electrostatic interactions between DNA strands, which can be tailored by adjusting the salt concentration of the incubation solution. Due to the much lower stability of the double helix formed by mismatches, the hybridization efficiencies of single mismatched (MMT) and perfectly matched DNA (PMT) were different. Therefore, we obtained an optimized salt concentration that allowed for discrimination of MMT from PMT without stringent control of temperature or pH. The results indicated this to be an ultrasensitive and precise nanosensor for the diagnosis of genetic diseases.

  5. Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern

    Science.gov (United States)

    Friedel, M. J.; Asch, T. H.; Oden, C.

    2012-08-01

    The remediation of land containing munitions and explosives of concern, otherwise known as unexploded ordnance, is an ongoing problem facing the U.S. Department of Defense and similar agencies worldwide that have used or are transferring training ranges or munitions disposal areas to civilian control. The expense associated with cleanup of land previously used for military training and war provides impetus for research towards enhanced discrimination of buried unexploded ordnance. Towards reducing that expense, a multiaxis electromagnetic induction data collection and software system, called ALLTEM, was designed and tested with support from the U.S. Department of Defense Environmental Security Technology Certification Program. ALLTEM is an on-time time-domain system that uses a continuous triangle-wave excitation to measure the target-step response rather than traditional impulse response. The system cycles through three orthogonal transmitting loops and records a total of 19 different transmitting and receiving loop combinations with a nominal spatial data sampling interval of 20 cm. Recorded data are pre-processed and then used in a hybrid discrimination scheme involving both data-driven and numerical classification techniques. The data-driven classification scheme is accomplished in three steps. First, field observations are used to train a type of unsupervised artificial neural network, a self-organizing map (SOM). Second, the SOM is used to simultaneously estimate target parameters (depth, azimuth, inclination, item type and weight) by iterative minimization of the topographic error vectors. Third, the target classification is accomplished by evaluating histograms of the estimated parameters. The numerical classification scheme is also accomplished in three steps. First, the Biot-Savart law is used to model the primary magnetic fields from the transmitter coils and the secondary magnetic fields generated by currents induced in the target materials in the

  6. Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern

    Science.gov (United States)

    Friedel, M.J.; Asch, T.H.; Oden, C.

    2012-01-01

    The remediation of land containing munitions and explosives of concern, otherwise known as unexploded ordnance, is an ongoing problem facing the U.S. Department of Defense and similar agencies worldwide that have used or are transferring training ranges or munitions disposal areas to civilian control. The expense associated with cleanup of land previously used for military training and war provides impetus for research towards enhanced discrimination of buried unexploded ordnance. Towards reducing that expense, a multiaxis electromagnetic induction data collection and software system, called ALLTEM, was designed and tested with support from the U.S. Department of Defense Environmental Security Technology Certification Program. ALLTEM is an on-time time-domain system that uses a continuous triangle-wave excitation to measure the target-step response rather than traditional impulse response. The system cycles through three orthogonal transmitting loops and records a total of 19 different transmitting and receiving loop combinations with a nominal spatial data sampling interval of 20 cm. Recorded data are pre-processed and then used in a hybrid discrimination scheme involving both data-driven and numerical classification techniques. The data-driven classification scheme is accomplished in three steps. First, field observations are used to train a type of unsupervised artificial neural network, a self-organizing map (SOM). Second, the SOM is used to simultaneously estimate target parameters (depth, azimuth, inclination, item type and weight) by iterative minimization of the topographic error vectors. Third, the target classification is accomplished by evaluating histograms of the estimated parameters. The numerical classification scheme is also accomplished in three steps. First, the Biot–Savart law is used to model the primary magnetic fields from the transmitter coils and the secondary magnetic fields generated by currents induced in the target materials in the

  7. Tomato (Solanum lycopersicum) variety discrimination and hybridization analysis based on the 5S rRNA region.

    Science.gov (United States)

    Sun, Yan-Lin; Kang, Ho-Min; Kim, Young-Sik; Baek, Jun-Pill; Zheng, Shi-Lin; Xiang, Jin-Jun; Hong, Soon-Kwan

    2014-05-04

    The tomato ( Solanum lycopersicum ) is a major vegetable crop worldwide. To satisfy popular demand, more than 500 tomato varieties have been bred. However, a clear variety identification has not been found. Thorough understanding of the phylogenetic relationship and hybridization information of tomato varieties is very important for further variety breeding. Thus, in this study, we collected 26 tomato varieties and attempted to distinguish them based on the 5S rRNA region, which is widely used in the determination of phylogenetic relations. Sequence analysis of the 5S rRNA region suggested that a large number of nucleotide variations exist among tomato varieties. These variable nucleotide sites were also informative regarding hybridization. Chromas sequencing of Yellow Mountain View and Seuwiteuking varieties indicated three and one variable nucleotide sites in the non-transcribed spacer (NTS) of the 5S rRNA region showing hybridization, respectively. Based on a phylogenetic tree constructed using the 5S rRNA sequences, we observed that 16 tomato varieties were divided into three groups at 95% similarity. Rubiking and Sseommeoking, Lang Selection Procedure and Seuwiteuking, and Acorn Gold and Yellow Mountain View exhibited very high identity with their partners. This work will aid variety authentication and provides a basis for further tomato variety breeding.

  8. Validation of microsatellite multiplexes for parentage analysis and species discrimination in two hybridizing species of coral reef fish (Plectropomus spp., Serranidae)

    KAUST Repository

    Harrison, H.B.

    2014-04-24

    Microsatellites are often considered ideal markers to investigate ecological processes in animal populations. They are regularly used as genetic barcodes to identify species, individuals, and infer familial relationships. However, such applications are highly sensitive the number and diversity of microsatellite markers, which are also prone to error. Here, we propose a novel framework to assess the suitability of microsatellite datasets for parentage analysis and species discrimination in two closely related species of coral reef fish, Plectropomus leopardus and P. maculatus (Serranidae). Coral trout are important fisheries species throughout the Indo-Pacific region and have been shown to hybridize in parts of the Great Barrier Reef, Australia. We first describe the development of 25 microsatellite loci and their integration to three multiplex PCRs that co-amplify in both species. Using simulations, we demonstrate that the complete suite of markers provides appropriate power to discriminate between species, detect hybrid individuals, and resolve parent-offspring relationships in natural populations, with over 99.6% accuracy in parent-offspring assignments. The markers were also tested on seven additional species within the Plectropomus genus with polymorphism in 28-96% of loci. The multiplex PCRs developed here provide a reliable and cost-effective strategy to investigate evolutionary and ecological dynamics and will be broadly applicable in studies of wild populations and aquaculture brood stocks for these closely related fish species. 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

  9. Validation of microsatellite multiplexes for parentage analysis and species discrimination in two hybridizing species of coral reef fish (Plectropomus spp., Serranidae)

    KAUST Repository

    Harrison, H.B.; Feldheim, K.A.; Jones, G.P.; Ma, K.; Mansour, H.; Perumal, S.; Williamson, D.H.; Berumen, Michael L.

    2014-01-01

    Microsatellites are often considered ideal markers to investigate ecological processes in animal populations. They are regularly used as genetic barcodes to identify species, individuals, and infer familial relationships. However, such applications are highly sensitive the number and diversity of microsatellite markers, which are also prone to error. Here, we propose a novel framework to assess the suitability of microsatellite datasets for parentage analysis and species discrimination in two closely related species of coral reef fish, Plectropomus leopardus and P. maculatus (Serranidae). Coral trout are important fisheries species throughout the Indo-Pacific region and have been shown to hybridize in parts of the Great Barrier Reef, Australia. We first describe the development of 25 microsatellite loci and their integration to three multiplex PCRs that co-amplify in both species. Using simulations, we demonstrate that the complete suite of markers provides appropriate power to discriminate between species, detect hybrid individuals, and resolve parent-offspring relationships in natural populations, with over 99.6% accuracy in parent-offspring assignments. The markers were also tested on seven additional species within the Plectropomus genus with polymorphism in 28-96% of loci. The multiplex PCRs developed here provide a reliable and cost-effective strategy to investigate evolutionary and ecological dynamics and will be broadly applicable in studies of wild populations and aquaculture brood stocks for these closely related fish species. 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

  10. An example of multidimensional analysis: Discriminant analysis

    International Nuclear Information System (INIS)

    Lutz, P.

    1990-01-01

    Among the approaches on the data multi-dimensional analysis, lectures on the discriminant analysis including theoretical and practical aspects are presented. The discrimination problem, the analysis steps and the discrimination categories are stressed. Examples on the descriptive historical analysis, the discrimination for decision making, the demonstration and separation of the top quark are given. In the linear discriminant analysis the following subjects are discussed: Huyghens theorem, projection, discriminant variable, geometrical interpretation, case for g=2, classification method, separation of the top events. Criteria allowing the obtention of relevant results are included [fr

  11. Hierarchical Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Di Lu

    2018-01-01

    Full Text Available The Internet of Things (IoT generates lots of high-dimensional sensor intelligent data. The processing of high-dimensional data (e.g., data visualization and data classification is very difficult, so it requires excellent subspace learning algorithms to learn a latent subspace to preserve the intrinsic structure of the high-dimensional data, and abandon the least useful information in the subsequent processing. In this context, many subspace learning algorithms have been presented. However, in the process of transforming the high-dimensional data into the low-dimensional space, the huge difference between the sum of inter-class distance and the sum of intra-class distance for distinct data may cause a bias problem. That means that the impact of intra-class distance is overwhelmed. To address this problem, we propose a novel algorithm called Hierarchical Discriminant Analysis (HDA. It minimizes the sum of intra-class distance first, and then maximizes the sum of inter-class distance. This proposed method balances the bias from the inter-class and that from the intra-class to achieve better performance. Extensive experiments are conducted on several benchmark face datasets. The results reveal that HDA obtains better performance than other dimensionality reduction algorithms.

  12. A hybrid generative-discriminative approach to speaker diarization

    NARCIS (Netherlands)

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

    2008-01-01

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

  13. Orthogonal sparse linear discriminant analysis

    Science.gov (United States)

    Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun

    2018-03-01

    Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.

  14. Discriminant analysis of plasma fusion data

    International Nuclear Information System (INIS)

    Kardaun, O.J.W.F.; Kardaun, J.W.P.F.; Itoh, S.; Itoh, K.

    1992-06-01

    Several discriminant analysis methods has been applied and compared to predict the type of ELM's in H-mode discharges: (a) quadratic discriminant analysis (linear discriminant analysis being a special case), (b) discrimination by non-parametric (kernel-) density estimates, and (c) discrimination by a product multinomial model on a discretised scale. Practical evaluation was performed using SAS in the first two cases, and INDEP, a standard FORTRAN program, initially developed for medical applications, in the last case. We give here a flavour of the approach and its results. In summary, discriminant analysis can be used as a useful descriptive method of specifying regions where particular types of plasma discharges can be produced. Parametric methods have the advantage of a rather compact mathematical formulation . Pertinent graphical representations are useful to make the theory and the results more palatable to the experimental physicists. (J.P.N.)

  15. Discriminant Analysis of Student Loan Applications

    Science.gov (United States)

    Dyl, Edward A.; McGann, Anthony F.

    1977-01-01

    The use of discriminant analysis in identifying potentially "good" versus potentially "bad" student loans is explained. The technique is applied to a sample of 200 student loan applications at the University of Wyoming. (LBH)

  16. USING DISCRIMINANT ANALYSIS IN RELATIONSHIP MARKETING

    OpenAIRE

    Iacob Catoiu; Mihai Èšichindelean; Simona Vinerean

    2013-01-01

    The purpose of the present paper is to describe and apply discriminant analysis withina relationship marketing context. The paper is structured into two parts; the first part contains aliterature review regarding the value chain concept and the dimensions it is built on, while thesecond part includes the results of applying discriminant analysis on several value chaindimensions. The authors have considered the client-company relationships of the gas-station marketas proper for studying the di...

  17. Credit scoring analysis using kernel discriminant

    Science.gov (United States)

    Widiharih, T.; Mukid, M. A.; Mustafid

    2018-05-01

    Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

  18. High affinity γPNA sandwich hybridization assay for rapid detection of short nucleic acid targets with single mismatch discrimination.

    Science.gov (United States)

    Goldman, Johnathan M; Zhang, Li Ang; Manna, Arunava; Armitage, Bruce A; Ly, Danith H; Schneider, James W

    2013-07-08

    Hybridization analysis of short DNA and RNA targets presents many challenges for detection. The commonly employed sandwich hybridization approach cannot be implemented for these short targets due to insufficient probe-target binding strengths for unmodified DNA probes. Here, we present a method capable of rapid and stable sandwich hybridization detection for 22 nucleotide DNA and RNA targets. Stable hybridization is achieved using an n-alkylated, polyethylene glycol γ-carbon modified peptide nucleic acid (γPNA) amphiphile. The γPNA's exceptionally high affinity enables stable hybridization of a second DNA-based probe to the remaining bases of the short target. Upon hybridization of both probes, an electrophoretic mobility shift is measured via interaction of the n-alkane modification on the γPNA with capillary electrophoresis running buffer containing nonionic surfactant micelles. We find that sandwich hybridization of both probes is stable under multiple binding configurations and demonstrate single base mismatch discrimination. The binding strength of both probes is also stabilized via coaxial stacking on adjacent hybridization to targets. We conclude with a discussion on the implementation of the proposed sandwich hybridization assay as a high-throughput microRNA detection method.

  19. Lithological discrimination of accretionary complex (Sivas, northern Turkey) using novel hybrid color composites and field data

    Science.gov (United States)

    Özkan, Mutlu; Çelik, Ömer Faruk; Özyavaş, Aziz

    2018-02-01

    One of the most appropriate approaches to better understand and interpret geologic evolution of an accretionary complex is to make a detailed geologic map. The fact that ophiolite sequences consist of various rock types may require a unique image processing method to map each ophiolite body. The accretionary complex in the study area is composed mainly of ophiolitic and metamorphic rocks along with epi-ophiolitic sedimentary rocks. This paper attempts to map the Late Cretaceous accretionary complex in detail in northern Sivas (within İzmir-Ankara-Erzincan Suture Zone in Turkey) by the analysis of all of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) bands and field study. The new two hybrid color composite images yield satisfactory results in delineating peridotite, gabbro, basalt, and epi-ophiolitic sedimentary rocks of the accretionary complex in the study area. While the first hybrid color composite image consists of one principle component (PC) and two band ratios (PC1, 3/4, 4/6 in the RGB), the PC5, the original ASTER band 4 and the 3/4 band ratio images were assigned to the RGB colors to generate the second hybrid color composite image. In addition to that, the spectral indices derived from the ASTER thermal infrared (TIR) bands discriminate clearly ultramafic, siliceous, and carbonate rocks from adjacent lithologies at a regional scale. Peridotites with varying degrees of serpentinization illustrated as a single color were best identified in the spectral indices map. Furthermore, the boundaries of ophiolitic rocks based on fieldwork were outlined in detail in some parts of the study area by superimposing the resultant maps of ASTER maps on Google Earth images of finer spatial resolution. Eventually, the encouraging geologic map generated by the image analysis of ASTER data strongly correlates with lithological boundaries from a field survey.

  20. Linear discriminant analysis for welding fault detection

    International Nuclear Information System (INIS)

    Li, X.; Simpson, S.W.

    2010-01-01

    This work presents a new method for real time welding fault detection in industry based on Linear Discriminant Analysis (LDA). A set of parameters was calculated from one second blocks of electrical data recorded during welding and based on control data from reference welds under good conditions, as well as faulty welds. Optimised linear combinations of the parameters were determined with LDA and tested with independent data. Short arc welds in overlap joints were studied with various power sources, shielding gases, wire diameters, and process geometries. Out-of-position faults were investigated. Application of LDA fault detection to a broad range of welding procedures was investigated using a similarity measure based on Principal Component Analysis. The measure determines which reference data are most similar to a given industrial procedure and the appropriate LDA weights are then employed. Overall, results show that Linear Discriminant Analysis gives an effective and consistent performance in real-time welding fault detection.

  1. Regularized Discriminant Analysis: A Large Dimensional Study

    KAUST Repository

    Yang, Xiaoke

    2018-04-28

    In this thesis, we focus on studying the performance of general regularized discriminant analysis (RDA) classifiers. The data used for analysis is assumed to follow Gaussian mixture model with different means and covariances. RDA offers a rich class of regularization options, covering as special cases the regularized linear discriminant analysis (RLDA) and the regularized quadratic discriminant analysis (RQDA) classi ers. We analyze RDA under the double asymptotic regime where the data dimension and the training size both increase in a proportional way. This double asymptotic regime allows for application of fundamental results from random matrix theory. Under the double asymptotic regime and some mild assumptions, we show that the asymptotic classification error converges to a deterministic quantity that only depends on the data statistical parameters and dimensions. This result not only implicates some mathematical relations between the misclassification error and the class statistics, but also can be leveraged to select the optimal parameters that minimize the classification error, thus yielding the optimal classifier. Validation results on the synthetic data show a good accuracy of our theoretical findings. We also construct a general consistent estimator to approximate the true classification error in consideration of the unknown previous statistics. We benchmark the performance of our proposed consistent estimator against classical estimator on synthetic data. The observations demonstrate that the general estimator outperforms others in terms of mean squared error (MSE).

  2. A Computational Discriminability Analysis on Twin Fingerprints

    Science.gov (United States)

    Liu, Yu; Srihari, Sargur N.

    Sharing similar genetic traits makes the investigation of twins an important study in forensics and biometrics. Fingerprints are one of the most commonly found types of forensic evidence. The similarity between twins’ prints is critical establish to the reliability of fingerprint identification. We present a quantitative analysis of the discriminability of twin fingerprints on a new data set (227 pairs of identical twins and fraternal twins) recently collected from a twin population using both level 1 and level 2 features. Although the patterns of minutiae among twins are more similar than in the general population, the similarity of fingerprints of twins is significantly different from that between genuine prints of the same finger. Twins fingerprints are discriminable with a 1.5%~1.7% higher EER than non-twins. And identical twins can be distinguished by examine fingerprint with a slightly higher error rate than fraternal twins.

  3. An Engineered Kinetic Amplification Mechanism for Single Nucleotide Variant Discrimination by DNA Hybridization Probes.

    Science.gov (United States)

    Chen, Sherry Xi; Seelig, Georg

    2016-04-20

    Even a single-nucleotide difference between the sequences of two otherwise identical biological nucleic acids can have dramatic functional consequences. Here, we use model-guided reaction pathway engineering to quantitatively improve the performance of selective hybridization probes in recognizing single nucleotide variants (SNVs). Specifically, we build a detection system that combines discrimination by competition with DNA strand displacement-based catalytic amplification. We show, both mathematically and experimentally, that the single nucleotide selectivity of such a system in binding to single-stranded DNA and RNA is quadratically better than discrimination due to competitive hybridization alone. As an additional benefit the integrated circuit inherits the property of amplification and provides at least 10-fold better sensitivity than standard hybridization probes. Moreover, we demonstrate how the detection mechanism can be tuned such that the detection reaction is agnostic to the position of the SNV within the target sequence. in contrast, prior strand displacement-based probes designed for kinetic discrimination are highly sensitive to position effects. We apply our system to reliably discriminate between different members of the let-7 microRNA family that differ in only a single base position. Our results demonstrate the power of systematic reaction network design to quantitatively improve biotechnology.

  4. Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

    Directory of Open Access Journals (Sweden)

    Araceli Sanchis

    2013-04-01

    Full Text Available Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network and SVM (Support Vector Machines, within the framework of HMM (Hidden Markov Model in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0:05, proving that the hybrid approach is better suited for the addressed domain.

  5. DISCRIMINANT ANALYSIS OF BANK PROFITABILITY LEVELS

    Directory of Open Access Journals (Sweden)

    Ante Rozga

    2013-02-01

    Full Text Available Discriminant analysis has been employed in this paper in order to identify and explain key features of bank profitability levels. Bank profitability is set up in the form of two categorical variables: profit or loss recorded and above or below average return on equity. Predictor variables are selected from various groups of financial indicators usually included in the empirical work on microeconomic determinants of bank profitability. The data from the Croatian banking sector is analyzed using the Enter method. General recommendations for a more profitable business of banking found in the bank management literature and existing empirical framework such as rationalization of overhead costs, asset growth, increase of non-interest income by expanding scale and scope of financial products proved to be important for classification of banks in different profitability levels. A higher market share may bring additional advantages. Classification results, canonical correlation and Wilks’ Lambda test confirm statistical significance of research results. Altogether, discriminant analysis turns out to be a suitable statistical method for solving presented research problem and moving forward from the bankruptcy, credit rating or default issues in finance.

  6. Hybrid methods for cybersecurity analysis :

    Energy Technology Data Exchange (ETDEWEB)

    Davis, Warren Leon,; Dunlavy, Daniel M.

    2014-01-01

    Early 2010 saw a signi cant change in adversarial techniques aimed at network intrusion: a shift from malware delivered via email attachments toward the use of hidden, embedded hyperlinks to initiate sequences of downloads and interactions with web sites and network servers containing malicious software. Enterprise security groups were well poised and experienced in defending the former attacks, but the new types of attacks were larger in number, more challenging to detect, dynamic in nature, and required the development of new technologies and analytic capabilities. The Hybrid LDRD project was aimed at delivering new capabilities in large-scale data modeling and analysis to enterprise security operators and analysts and understanding the challenges of detection and prevention of emerging cybersecurity threats. Leveraging previous LDRD research e orts and capabilities in large-scale relational data analysis, large-scale discrete data analysis and visualization, and streaming data analysis, new modeling and analysis capabilities were quickly brought to bear on the problems in email phishing and spear phishing attacks in the Sandia enterprise security operational groups at the onset of the Hybrid project. As part of this project, a software development and deployment framework was created within the security analyst work ow tool sets to facilitate the delivery and testing of new capabilities as they became available, and machine learning algorithms were developed to address the challenge of dynamic threats. Furthermore, researchers from the Hybrid project were embedded in the security analyst groups for almost a full year, engaged in daily operational activities and routines, creating an atmosphere of trust and collaboration between the researchers and security personnel. The Hybrid project has altered the way that research ideas can be incorporated into the production environments of Sandias enterprise security groups, reducing time to deployment from months and

  7. The Discriminant Analysis Flare Forecasting System (DAFFS)

    Science.gov (United States)

    Leka, K. D.; Barnes, Graham; Wagner, Eric; Hill, Frank; Marble, Andrew R.

    2016-05-01

    The Discriminant Analysis Flare Forecasting System (DAFFS) has been developed under NOAA/Small Business Innovative Research funds to quantitatively improve upon the NOAA/SWPC flare prediction. In the Phase-I of this project, it was demonstrated that DAFFS could indeed improve by the requested 25% most of the standard flare prediction data products from NOAA/SWPC. In the Phase-II of this project, a prototype has been developed and is presently running autonomously at NWRA.DAFFS uses near-real-time data from NOAA/GOES, SDO/HMI, and the NSO/GONG network to issue both region- and full-disk forecasts of solar flares, based on multi-variable non-parametric Discriminant Analysis. Presently, DAFFS provides forecasts which match those provided by NOAA/SWPC in terms of thresholds and validity periods (including 1-, 2-, and 3- day forecasts), although issued twice daily. Of particular note regarding DAFFS capabilities are the redundant system design, automatically-generated validation statistics and the large range of customizable options available. As part of this poster, a description of the data used, algorithm, performance and customizable options will be presented, as well as a demonstration of the DAFFS prototype.DAFFS development at NWRA is supported by NOAA/SBIR contracts WC-133R-13-CN-0079 and WC-133R-14-CN-0103, with additional support from NASA contract NNH12CG10C, plus acknowledgment to the SDO/HMI and NSO/GONG facilities and NOAA/SWPC personnel for data products, support, and feedback. DAFFS is presently ready for Phase-III development.

  8. Application of Discriminant Analysis on Romanian Insurance Market

    OpenAIRE

    Constantin Anghelache; Dan Armeanu

    2008-01-01

    Discriminant analysis is a supervised learning technique that can be used in order to determine which variables are the best predictors of the classification of objects belonging to a population into predetermined classes. At the same time, discriminant analysis provides a powerful tool that enables researchers to make predictions regarding the classification of new objects into predefined classes. The main goal of discriminant analysis is to determine which of the N descrip...

  9. Using discriminant analysis for credit decision

    Directory of Open Access Journals (Sweden)

    Gheorghiţa DINCĂ

    2015-12-01

    Full Text Available This paper follows to highlight the link between the results obtained applying discriminant analysis and lending decision. For this purpose, we have carried out the research on a sample of 24 Romanian private companies, pertaining to 12 different economic sectors, from I and II categories of Bucharest Stock Exchange, for the period 2010-2012. Our study works with two popular bankruptcy risk’s prediction models, the Altman model and the Anghel model. We have double-checked and confirmed the results of our research by comparing the results from applying the two fore-mentioned models as well as by checking existing debt commitments of each analyzed company to credit institutions during the 2010-2012 period. The aim of this paper was the classification of studied companies into potential bankrupt and non-bankrupt, to assist credit institutions in their decision to grant credit, understanding the approval or rejection algorithm of loan applications and even help potential investors in these ompanies.

  10. Contributions to sensitivity analysis and generalized discriminant analysis

    International Nuclear Information System (INIS)

    Jacques, J.

    2005-12-01

    Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)

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

    Science.gov (United States)

    Sajid, Muhammad; Shafique, Tamoor

    2018-03-01

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

  12. PRICE DISCRIMINATION AND MARKET POWER: A THEORETICAL ANALYSIS

    Directory of Open Access Journals (Sweden)

    Olga Smirnova

    2015-07-01

    Full Text Available This paper analyzes the contemporary theoretical and empirical research in the field of impact assessment of market power and conclusions about the possibilities of the company to implement price discrimination in different market structures. The results of the analysis allow to evaluate current approaches to antitrust regulation of price discrimination.

  13. Parametric systems analysis for ICF hybrid reactors

    International Nuclear Information System (INIS)

    Berwald, D.H.; Maniscalco, J.A.; Chapin, D.L.

    1981-01-01

    Parametric design and systems analysis for inertial confinement fusion-fission hybrids are presented. These results were generated as part of the Electric Power Research Institute (EPRI) sponsored Feasibility Assessment of Fusion-Fission Hybrids, using an Inertial Confinement Fusion (ICF) hybrid power plant design code developed in conjunction with the feasibility assessment. The SYMECON systems analysis code, developed by Westinghouse, was used to generate economic results for symbiotic electricity generation systems consisting of the hybrid and its client Light Water Reactors (LWRs). These results explore the entire fusion parameter space for uranium fast fission blanket hybrids, thorium fast fission blanket hybrids, and thorium suppressed fission blanket types are discussed, and system sensitivities to design uncertainties are explored

  14. Stochastic Reachability Analysis of Hybrid Systems

    CERN Document Server

    Bujorianu, Luminita Manuela

    2012-01-01

    Stochastic reachability analysis (SRA) is a method of analyzing the behavior of control systems which mix discrete and continuous dynamics. For probabilistic discrete systems it has been shown to be a practical verification method but for stochastic hybrid systems it can be rather more. As a verification technique SRA can assess the safety and performance of, for example, autonomous systems, robot and aircraft path planning and multi-agent coordination but it can also be used for the adaptive control of such systems. Stochastic Reachability Analysis of Hybrid Systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then...

  15. Use of linear discriminant function analysis in seed morphotype ...

    African Journals Online (AJOL)

    Use of linear discriminant function analysis in seed morphotype relationship study in 31 ... Data were collected on 100-seed weight, seed length and seed width. ... to the Mesoamerican gene pool, comprising the cultigroups Sieva-Big Lima, ...

  16. Dimensional Analysis with space discrimination applied to Fickian difussion phenomena

    International Nuclear Information System (INIS)

    Diaz Sanchidrian, C.; Castans, M.

    1989-01-01

    Dimensional Analysis with space discrimination is applied to Fickian difussion phenomena in order to transform its partial differen-tial equations into ordinary ones, and also to obtain in a dimensionl-ess fom the Ficks second law. (Author)

  17. Discrimination between smiling faces: Human observers vs. automated face analysis.

    Science.gov (United States)

    Del Líbano, Mario; Calvo, Manuel G; Fernández-Martín, Andrés; Recio, Guillermo

    2018-05-11

    This study investigated (a) how prototypical happy faces (with happy eyes and a smile) can be discriminated from blended expressions with a smile but non-happy eyes, depending on type and intensity of the eye expression; and (b) how smile discrimination differs for human perceivers versus automated face analysis, depending on affective valence and morphological facial features. Human observers categorized faces as happy or non-happy, or rated their valence. Automated analysis (FACET software) computed seven expressions (including joy/happiness) and 20 facial action units (AUs). Physical properties (low-level image statistics and visual saliency) of the face stimuli were controlled. Results revealed, first, that some blended expressions (especially, with angry eyes) had lower discrimination thresholds (i.e., they were identified as "non-happy" at lower non-happy eye intensities) than others (especially, with neutral eyes). Second, discrimination sensitivity was better for human perceivers than for automated FACET analysis. As an additional finding, affective valence predicted human discrimination performance, whereas morphological AUs predicted FACET discrimination. FACET can be a valid tool for categorizing prototypical expressions, but is currently more limited than human observers for discrimination of blended expressions. Configural processing facilitates detection of in/congruence(s) across regions, and thus detection of non-genuine smiling faces (due to non-happy eyes). Copyright © 2018 Elsevier B.V. All rights reserved.

  18. The use of the discriminant analysis method for e π μ separation in BES

    International Nuclear Information System (INIS)

    Jiang Zhijin; Wang Taijie; Xie Yigang; Huang Tao

    1994-01-01

    We use the discriminant analysis method in multivariate statistical theory to handle the e π μ separation in BES, describing the principle of the discriminant analysis method, deriving the unstandardized discriminant functions (responsible for particle separation), giving the discriminant efficiency for e π μ and comparing the results from the discriminant analysis method with those obtained in a conventional way. ((orig.))

  19. Fγ: A new observable for photon-hadron discrimination in hybrid air shower events

    Science.gov (United States)

    Niechciol, M.; Risse, M.; Ruehl, P.; Settimo, M.; Younk, P. W.; Yushkov, A.

    2018-01-01

    To search for ultra-high-energy photons in primary cosmic rays, air shower observables are needed that allow a good separation between primary photons and primary hadrons. We present a new observable, Fγ, which can be extracted from ground-array data in hybrid events, where simultaneous measurements of the longitudinal and the lateral shower profile are performed. The observable is based on a template fit to the lateral distribution measured by the ground array with the template taking into account the complementary information from the measurement of the longitudinal profile, i.e. the primary energy and the geometry of the shower. Fγ shows a very good photon-hadron separation, which is even superior to the separation given by the well-known Xmax observable (the atmospheric depth of the shower maximum). At energies around 1 EeV (10 EeV), Fγ provides a background rejection better than 97.8 % (99.9 %) at a signal efficiency of 50 %. Advantages of the observable Fγ are its technical stability with respect to irregularities in the ground array (i.e. missing or temporarily non-operating stations) and that it can be applied over the full energy range accessible to the air shower detector, down to its threshold energy. Furthermore, Fγ complements nicely to Xmax such that both observables can well be combined to achieve an even better discrimination power, exploiting the rich information available in hybrid events.

  20. Discrete Discriminant analysis based on tree-structured graphical models

    DEFF Research Database (Denmark)

    Perez de la Cruz, Gonzalo; Eslava, Guillermina

    The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant a...... analysis based on tree{structured graphical models is a simple nonlinear method competitive with, and sometimes superior to, other well{known linear methods like those assuming mutual independence between variables and linear logistic regression.......The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant...

  1. A Large Dimensional Analysis of Regularized Discriminant Analysis Classifiers

    KAUST Repository

    Elkhalil, Khalil

    2017-11-01

    This article carries out a large dimensional analysis of standard regularized discriminant analysis classifiers designed on the assumption that data arise from a Gaussian mixture model with different means and covariances. The analysis relies on fundamental results from random matrix theory (RMT) when both the number of features and the cardinality of the training data within each class grow large at the same pace. Under mild assumptions, we show that the asymptotic classification error approaches a deterministic quantity that depends only on the means and covariances associated with each class as well as the problem dimensions. Such a result permits a better understanding of the performance of regularized discriminant analsysis, in practical large but finite dimensions, and can be used to determine and pre-estimate the optimal regularization parameter that minimizes the misclassification error probability. Despite being theoretically valid only for Gaussian data, our findings are shown to yield a high accuracy in predicting the performances achieved with real data sets drawn from the popular USPS data base, thereby making an interesting connection between theory and practice.

  2. Application of Discriminant Analysis on Romanian Insurance Market

    Directory of Open Access Journals (Sweden)

    Constantin Anghelache

    2008-11-01

    Full Text Available Discriminant analysis is a supervised learning technique that can be used in order to determine which variables are the best predictors of the classification of objects belonging to a population into predetermined classes. At the same time, discriminant analysis provides a powerful tool that enables researchers to make predictions regarding the classification of new objects into predefined classes. The main goal of discriminant analysis is to determine which of the N descriptive variables have the most discriminatory power, that is, which of them are the most relevant for the classification of objects into classes. In order to classify objects, we need a mathematical model that provides the rules for optimal allocation. This is the classifier. In this paper we will discuss three of the most important models of classification: the Bayesian criterion, the Mahalanobis criterion and the Fisher criterion. In this paper, we will use discriminant analysis to classify the insurance companies that operated on the Romanian market in 2006. We have selected a number of eigth (8 relevant variables: gross written premium (GR_WRI_PRE, net mathematical reserves (NET_M_PES, gross claims paid (GR_CL_PAID, net premium reserves (NET_PRE_RES, net claim reserves (NET_CL_RES, net income (NE—_INCOME, share capital (SHARE_CAP and gross written premium ceded in Reinsurance (GR_WRI_PRE_CED. Before proceeding to discriminant analysis, we performed cluster analysis on the initial data in order to identify classes (clusters that emerge from the data.

  3. Discriminant Function Analysis as a Proof for Sexual Dimorphism ...

    African Journals Online (AJOL)

    Background: Forensic scientists study human skeleton in legal setting. Discriminant function analysis has become important in forensic anthropology. The aim of this study was to determine the sex of adolescent Yoruba ethnic group of Nigeria using iscriminant function analysis. Methodology: One thousand (500 males and ...

  4. Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

    Science.gov (United States)

    Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan

    2016-01-01

    Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…

  5. Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

    Directory of Open Access Journals (Sweden)

    Cheng-Yuan Shih

    2010-01-01

    Full Text Available This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA and quadratic discriminant analysis (QDA. It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.

  6. Pharmacokinetic-Pharmacodynamic (PKPD) Analysis with Drug Discrimination.

    Science.gov (United States)

    Negus, S Stevens; Banks, Matthew L

    2016-08-30

    Discriminative stimulus and other drug effects are determined by the concentration of drug at its target receptor and by the pharmacodynamic consequences of drug-receptor interaction. For in vivo procedures such as drug discrimination, drug concentration at receptors in a given anatomical location (e.g., the brain) is determined both by the dose of drug administered and by pharmacokinetic processes of absorption, distribution, metabolism, and excretion that deliver drug to and from that anatomical location. Drug discrimination data are often analyzed by strategies of dose-effect analysis to determine parameters such as potency and efficacy. Pharmacokinetic-Pharmacodynamic (PKPD) analysis is an alternative to conventional dose-effect analysis, and it relates drug effects to a measure of drug concentration in a body compartment (e.g., venous blood) rather than to drug dose. PKPD analysis can yield insights on pharmacokinetic and pharmacodynamic determinants of drug action. PKPD analysis can also facilitate translational research by identifying species differences in pharmacokinetics and providing a basis for integrating these differences into interpretation of drug effects. Examples are discussed here to illustrate the application of PKPD analysis to the evaluation of drug effects in rhesus monkeys trained to discriminate cocaine from saline.

  7. Enamel surface topography analysis for diet discrimination. A methodology to enhance and select discriminative parameters

    Science.gov (United States)

    Francisco, Arthur; Blondel, Cécile; Brunetière, Noël; Ramdarshan, Anusha; Merceron, Gildas

    2018-03-01

    Tooth wear and, more specifically, dental microwear texture is a dietary proxy that has been used for years in vertebrate paleoecology and ecology. DMTA, dental microwear texture analysis, relies on a few parameters related to the surface complexity, anisotropy and heterogeneity of the enamel facets at the micrometric scale. Working with few but physically meaningful parameters helps in comparing published results and in defining levels for classification purposes. Other dental microwear approaches are based on ISO parameters and coupled with statistical tests to find the more relevant ones. The present study roughly utilizes most of the aforementioned parameters in their more or less modified form. But more than parameters, we here propose a new approach: instead of a single parameter characterizing the whole surface, we sample the surface and thus generate 9 derived parameters in order to broaden the parameter set. The identification of the most discriminative parameters is performed with an automated procedure which is an extended and refined version of the workflows encountered in some studies. The procedure in its initial form includes the most common tools, like the ANOVA and the correlation analysis, along with the required mathematical tests. The discrimination results show that a simplified form of the procedure is able to more efficiently identify the desired number of discriminative parameters. Also highlighted are some trends like the relevance of working with both height and spatial parameters, as well as the potential benefits of dimensionless surfaces. On a set of 45 surfaces issued from 45 specimens of three modern ruminants with differences in feeding preferences (grazing, leaf-browsing and fruit-eating), it is clearly shown that the level of wear discrimination is improved with the new methodology compared to the other ones.

  8. Analysis of Linear Hybrid Systems in CLP

    DEFF Research Database (Denmark)

    Banda, Gourinath; Gallagher, John Patrick

    2009-01-01

    In this paper we present a procedure for representing the semantics of linear hybrid automata (LHAs) as constraint logic programs (CLP); flexible and accurate analysis and verification of LHAs can then be performed using generic CLP analysis and transformation tools. LHAs provide an expressive...

  9. Discrimination analysis of ononis repens and ononis spinosa of the ...

    African Journals Online (AJOL)

    Discrimination analysis of ononis repens and ononis spinosa of the British Isles. CE Stephens. Abstract. No Abstract. Journal of the Ghana Association Vol. 2 (3) 1999: pp.88-94. Full Text: EMAIL FULL TEXT EMAIL FULL TEXT · DOWNLOAD FULL TEXT DOWNLOAD FULL TEXT · http://dx.doi.org/10.4314/jgsa.v2i3.17997.

  10. Discriminant analysis of functional optical topography for schizophrenia diagnosis

    Science.gov (United States)

    Chuang, Ching-Cheng; Nakagome, Kazuyuki; Pu, Shenghong; Lan, Tsuo-Hung; Lee, Chia-Yen; Sun, Chia-Wei

    2014-01-01

    Abnormal prefrontal function plays a central role in the cognition deficits of schizophrenic patients; however, the character of the relationship between discriminant analysis and prefrontal activation remains undetermined. Recently, evidence of low prefrontal cortex (PFC) activation in individuals with schizophrenia has also been found during verbal fluency tests (VFT) and other cognitive tests with several neuroimaging methods. The purpose of this study is to assess the hemodynamic changes of the PFC and discriminant analysis between schizophrenia patients and healthy controls during VFT task by utilizing functional optical topography. A total of 99 subjects including 53 schizophrenic patients and 46 age- and gender-matched healthy controls were studied. The results showed that the healthy group had larger activation in the right and left PFC than in the middle PFC. Besides, the schizophrenic group showed weaker task performance and lower activation in the whole PFC than the healthy group. The result of the discriminant analysis showed a significant difference with P value <0.001 in six channels (CH 23, 29, 31, 40, 42, 52) between the schizophrenic and healthy groups. Finally, 68.69% and 71.72% of subjects are correctly classified as being schizophrenic or healthy with all 52 channels and six significantly different channels, respectively. Our findings suggest that the left PFC can be a feature region for discriminant analysis of schizophrenic diagnosis.

  11. Linear discriminant analysis of structure within African eggplant 'Shum'

    African Journals Online (AJOL)

    A MANOVA preceded linear discriminant analysis, to model each of 61 variables, as predicted by clusters and experiment to filter out non-significant traits. Four distinct clusters emerged, with a cophenetic relation coefficient of 0.87 (P<0.01). Canonical variates that best predicted the observed clusters include petiole length, ...

  12. Multi spectral imaging analysis for meat spoilage discrimination

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga

    classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat......In the present study, fresh beef fillets were purchased from a local butcher shop and stored aerobically and in modified atmosphere packaging (MAP, CO2 40%/O2 30%/N2 30%) at six different temperatures (0, 4, 8, 12, 16 and 20°C). Microbiological analysis in terms of total viable counts (TVC......) was performed in parallel with videometer image snapshots and sensory analysis. Odour and colour characteristics of meat were determined by a test panel and attributed into three pre-characterized quality classes, namely Fresh; Semi Fresh and Spoiled during the days of its shelf life. So far, different...

  13. Fish otoliths analysis by PIXE: application to stock discrimination

    International Nuclear Information System (INIS)

    Arai, Nobuaki; Takai, Noriyuki; Sakamoto, Wataru; Yoshida, Koji; Maeda, Kuniko.

    1996-01-01

    Fish otoliths are continuously deposited from fish birth to its death along with encoding environmental information. In order to decode the information, PIXE was adopted as trace elemental analysis of the otoliths. Strontium to calcium concentration ratios of red sea bream otoliths varied among rearing stations. The Sr/Ca ratios of Lake Biwa catfishes also varied between male and female and among fishing grounds. The PIXE analysis was applied to the fish stock discrimination. (author)

  14. Analysis and design of hybrid control systems

    Energy Technology Data Exchange (ETDEWEB)

    Malmborg, J.

    1998-05-01

    Different aspects of hybrid control systems are treated: analysis, simulation, design and implementation. A systematic methodology using extended Lyapunov theory for design of hybrid systems is developed. The methodology is based on conventional control designs in separate regions together with a switching strategy. Dynamics are not well defined if the control design methods lead to fast mode switching. The dynamics depend on the salient features of the implementation of the mode switches. A theorem for the stability of second order switching together with the resulting dynamics is derived. The dynamics on an intersection of two sliding sets are defined for two relays working on different time scales. The current simulation packages have problems modeling and simulating hybrid systems. It is shown how fast mode switches can be found before or during simulation. The necessary analysis work is a very small overhead for a modern simulation tool. To get some experience from practical problems with hybrid control the switching strategy is implemented in two different software environments. In one of them a time-optimal controller is added to an existing PID controller on a commercial control system. Successful experiments with this hybrid controller shows the practical use of the method 78 refs, 51 figs, 2 tabs

  15. Parametric systems analysis for tandem mirror hybrids

    International Nuclear Information System (INIS)

    Lee, J.D.; Chapin, D.L.; Chi, J.W.H.

    1980-09-01

    Fusion fission systems, consisting of fissile producing fusion hybrids combining a tandem mirror fusion driver with various blanket types and net fissile consuming LWR's, have been modeled and analyzed parametrically. Analysis to date indicates that hybrids can be competitive with mined uranium when U 3 O 8 cost is about 100 $/lb., adding less than 25% to present day cost of power from LWR's. Of the three blanket types considered, uranium fast fission (UFF), thorium fast fission (ThFF), and thorium fission supressed (ThFS), the ThFS blanket has a modest economic advantage under most conditions but has higher support ratios and potential safety advantages under all conditions

  16. Discrimination of Species and Hybrid Detection in Myriophyllum Spp.: an Introduction to Biodiversity Conservation and Invasion Avoidance

    Directory of Open Access Journals (Sweden)

    R Ghahramanzadeh

    2014-03-01

    Full Text Available Minimizing economical loss through introduction of invasive alien species (IAS in local ecosystem is one of the most important issues in biosecurity. The hybridization potential between non-indigenous and native species has raised concerns due mainly to introgression, which can cause extirpation of native species through gene contamination. In the present study, 71 samples belonging to 12 species from Myriophyllum genus were assessed in Plant Breeding group of Wageningen University. Internal transcribed spacer (ITS was used for identification of invasive species from related native and possible hybrid plants. The result showed that based on universal application, high sequence divergence and species discrimination, ITS is a powerful sequence for the identification of invasive species from related non-invasive foreign and native species. In contrast to morphological data, ITS grouped suspected hybrid plants in to M. heterophyllum and demonstrated that they have not resulted from hybridization. These observations suggest that multiple introduction and genetic recombination among different introduced genotypes or genetic pools could be reasons of non-flowering in suspected hybrid plants. Results showed that molecular markers enable to distinguish invasive plant species from their most closely related congeners. This could be helpful with enforcing a ban on important of such invasive which can help to plant ecosystem and biodiversity stability.

  17. Quark/gluon jet discrimination: a reproducible analysis using R

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    The power to discriminate between light-quark jets and gluon jets would have a huge impact on many searches for new physics at CERN and beyond. This talk will present a walk-through of the development of a prototype machine learning classifier for differentiating between quark and gluon jets at experiments like those at the Large Hadron Collider at CERN. A new fast feature selection method that combines information theory and graph analytics will be outlined. This method has found new variables that promise significant improvements in discrimination power. The prototype jet tagger is simple, interpretable, parsimonious, and computationally extremely cheap, and therefore might be suitable for use in trigger systems for real-time data processing. Nested stratified k-fold cross validation was used to generate robust estimates of model performance. The data analysis was performed entirely in the R statistical programming language, and is fully reproducible. The entire analysis workflow is data-driven, automated a...

  18. Multivariable Discriminant Analysis for the Differential Diagnosis of Microcytic Anemia

    Directory of Open Access Journals (Sweden)

    Eloísa Urrechaga

    2013-01-01

    Full Text Available Introduction. Iron deficiency anemia and thalassemia are the most common causes of microcytic anemia. Powerful statistical computer programming enables sensitive discriminant analyses to aid in the diagnosis. We aimed at investigating the performance of the multiple discriminant analysis (MDA to the differential diagnosis of microcytic anemia. Methods. The training group was composed of 200 β-thalassemia carriers, 65 α-thalassemia carriers, 170 iron deficiency anemia (IDA, and 45 mixed cases of thalassemia and acute phase response or iron deficiency. A set of potential predictor parameters that could detect differences among groups were selected: Red Blood Cells (RBC, hemoglobin (Hb, mean cell volume (MCV, mean cell hemoglobin (MCH, and RBC distribution width (RDW. The functions obtained with MDA analysis were applied to a set of 628 consecutive patients with microcytic anemia. Results. For classifying patients into two groups (genetic anemia and acquired anemia, only one function was needed; 87.9% β-thalassemia carriers, and 83.3% α-thalassemia carriers, and 72.1% in the mixed group were correctly classified. Conclusion. Linear discriminant functions based on hemogram data can aid in differentiating between IDA and thalassemia, so samples can be efficiently selected for further analysis to confirm the presence of genetic anemia.

  19. Mismatch discrimination of lipidated DNA and LNA-probes (LiNAs) in hybridization-controlled liposome assembly

    DEFF Research Database (Denmark)

    Jakobsen, Ulla; Vogel, Stefan

    2016-01-01

    Assays for mismatch discrimination and detection of single nucleotide variations by hybridization-controlled assembly of liposomes, which do not require tedious surface chemistry, are versatile for both DNA and RNA targets. We report herein a comprehensive study on different DNA and LNA (locked...... assay in the context of mismatch discrimination and SNP detection are presented. The advantages of membrane-anchored LiNA-probes compared to chemically attached probes on solid nanoparticles (e.g. gold nanoparticles) are described. Key functionalities such as non-covalent attachment of LiNA probes...... without the need for long spacers and the inherent mobility of membrane-anchored probes in lipid-bilayer membranes will be described for several different probe designs....

  20. Fluid Dynamic Models for Bhattacharyya-Based Discriminant Analysis.

    Science.gov (United States)

    Noh, Yung-Kyun; Hamm, Jihun; Park, Frank Chongwoo; Zhang, Byoung-Tak; Lee, Daniel D

    2018-01-01

    Classical discriminant analysis attempts to discover a low-dimensional subspace where class label information is maximally preserved under projection. Canonical methods for estimating the subspace optimize an information-theoretic criterion that measures the separation between the class-conditional distributions. Unfortunately, direct optimization of the information-theoretic criteria is generally non-convex and intractable in high-dimensional spaces. In this work, we propose a novel, tractable algorithm for discriminant analysis that considers the class-conditional densities as interacting fluids in the high-dimensional embedding space. We use the Bhattacharyya criterion as a potential function that generates forces between the interacting fluids, and derive a computationally tractable method for finding the low-dimensional subspace that optimally constrains the resulting fluid flow. We show that this model properly reduces to the optimal solution for homoscedastic data as well as for heteroscedastic Gaussian distributions with equal means. We also extend this model to discover optimal filters for discriminating Gaussian processes and provide experimental results and comparisons on a number of datasets.

  1. Phylogenetic comparative methods complement discriminant function analysis in ecomorphology.

    Science.gov (United States)

    Barr, W Andrew; Scott, Robert S

    2014-04-01

    In ecomorphology, Discriminant Function Analysis (DFA) has been used as evidence for the presence of functional links between morphometric variables and ecological categories. Here we conduct simulations of characters containing phylogenetic signal to explore the performance of DFA under a variety of conditions. Characters were simulated using a phylogeny of extant antelope species from known habitats. Characters were modeled with no biomechanical relationship to the habitat category; the only sources of variation were body mass, phylogenetic signal, or random "noise." DFA on the discriminability of habitat categories was performed using subsets of the simulated characters, and Phylogenetic Generalized Least Squares (PGLS) was performed for each character. Analyses were repeated with randomized habitat assignments. When simulated characters lacked phylogenetic signal and/or habitat assignments were random, ecomorphology. Copyright © 2013 Wiley Periodicals, Inc.

  2. Analysis of fuel cell hybrid locomotives

    Energy Technology Data Exchange (ETDEWEB)

    Miller, Arnold R. [Vehicle Projects LLC, 621, 17th Street, Suite 2131, Denver, CO 80293 (United States); Peters, John; Smith, Brian E. [Transportation Technology Center Inc., 55500 DOT Road, Pueblo, CO 81007 (United States); Velev, Omourtag A. [AeroVironment Inc., 232 West Maple Avenue, Monrovia, CA 91016 (United States)

    2006-07-03

    Led by Vehicle Projects LLC, an international industry-government consortium is developing a 109t, 1.2MW road-switcher locomotive for commercial and military railway applications. As part of the feasibility and conceptual-design analysis, a study has been made of the potential benefits of a hybrid power plant in which fuel cells comprise the prime mover and a battery or flywheel provides auxiliary power. The potential benefits of a hybrid power plant are: (i) enhancement of transient power and hence tractive effort; (ii) regenerative braking; (iii) reduction of capital cost. Generally, the tractive effort of a locomotive at low speed is limited by wheel adhesion and not by available power. Enhanced transient power is therefore unlikely to benefit a switcher locomotive, but could assist applications that require high acceleration, e.g. subway trains with all axles powered. In most cases, the value of regeneration in locomotives is minimal. For low-speed applications such as switchers, the available kinetic energy and the effectiveness of traction motors as generators are both minimal. For high-speed heavy applications such as freight, the ability of the auxiliary power device to absorb a significant portion of the available kinetic energy is low. Moreover, the hybrid power plant suffers a double efficiency penalty, namely, losses occur in both absorbing and then releasing energy from the auxiliary device, which result in a net storage efficiency of no more than 50% for present battery technology. Capital cost in some applications may be reduced. Based on an observed locomotive duty cycle, a cost model shows that a hybrid power plant for a switcher may indeed reduce capital cost. Offsetting this potential benefit are the increased complexity, weight and volume of the power plant, as well as 20-40% increased fuel consumption that results from lower efficiency. Based on this analysis, the consortium has decided to develop a pure fuel cell road-switcher locomotive, that

  3. Discriminant analysis in Polish manufacturing sector performance assessment

    Directory of Open Access Journals (Sweden)

    Józef Dziechciarz

    2004-01-01

    Full Text Available This is a presentation of the preliminary results of a larger project on the determination of the attractiveness of manufacturing branches. Results of the performance assessment of Polish manufacturing branches in 2000 (section D „Manufacturing” – based on NACE – Nomenclatures des Activites de Communite Europeene are shown. In the research, the classical (Fisher’s linear discriminant analysis technique was used for the analysis of the profit generation ability by the firms belonging to a certain production branch. For estimation, the data describing group level was used – for cross-validation, the classes data.

  4. Probabilistic Analysis Methods for Hybrid Ventilation

    DEFF Research Database (Denmark)

    Brohus, Henrik; Frier, Christian; Heiselberg, Per

    This paper discusses a general approach for the application of probabilistic analysis methods in the design of ventilation systems. The aims and scope of probabilistic versus deterministic methods are addressed with special emphasis on hybrid ventilation systems. A preliminary application...... of stochastic differential equations is presented comprising a general heat balance for an arbitrary number of loads and zones in a building to determine the thermal behaviour under random conditions....

  5. Visual Tracking via Feature Tensor Multimanifold Discriminate Analysis

    Directory of Open Access Journals (Sweden)

    Ting-quan Deng

    2014-01-01

    Full Text Available In the visual tracking scenarios, if there are multiple objects, due to the interference of similar objects, tracking may fail in the progress of occlusion to separation. To address this problem, this paper proposed a visual tracking algorithm with discrimination through multimanifold learning. Color-gradient-based feature tensor was used to describe object appearance for accommodation of partial occlusion. A prior multimanifold tensor dataset is established through the template matching tracking algorithm. For the purpose of discrimination, tensor distance was defined to determine the intramanifold and intermanifold neighborhood relationship in multimanifold space. Then multimanifold discriminate analysis was employed to construct multilinear projection matrices of submanifolds. Finally, object states were obtained by combining with sequence inference. Meanwhile, the multimanifold dataset and manifold learning embedded projection should be updated online. Experiments were conducted on two real visual surveillance sequences to evaluate the proposed algorithm with three state-of-the-art tracking methods qualitatively and quantitatively. Experimental results show that the proposed algorithm can achieve effective and robust effect in multi-similar-object mutual occlusion scenarios.

  6. Robust linear discriminant analysis with distance based estimators

    Science.gov (United States)

    Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina

    2017-11-01

    Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.

  7. Isokinetic evaluation of knee muscles in soccer players: discriminant analysis

    Directory of Open Access Journals (Sweden)

    Bruno Fles Mazuquin

    2015-10-01

    Full Text Available ABSTRACTIntroduction:Muscle activity in soccer players can be measured by isokinetic dynamometer, which is a reliable tool for assessing human performance.Objectives:To perform isokinetic analyses and to determine which variables differentiate the under-17 (U17 soccer category from the professional (PRO.Methods:Thirty four players were assessed (n=17 for each category. The isokinetic variables used for the knee extension-flexion analysis were: peak torque (Nm, total work (J, average power (W, angle of peak torque (deg., agonist/ antagonist ratio (%, measured for three velocities (60°/s, 120°/s and 300°/s, with each series containing five repetitions. Three Wilks' Lambda discriminant analyses were performed, to identify which variables were more significant for the definition of each of the categories.Results:The discriminative variables at 60°/s in the PRO category were: extension peak torque, flexion total work, extension average power and agonist/antagonist ratio; and for the U17s were: extension total work, flexion peak torque and flexion average power. At 120°/s for the PRO category the discriminant variables were: flexion peak torque and extension average power; for the U17s they were: extension total work and flexion average power. Finally at 300°/s, the variables found in the PRO and U17 categories respectively were: extension average power and extension total work.Conclusion:Isokinetic variables for flexion and extension knee muscles were able to significantly discriminate between PRO and U17 soccer players.

  8. Genetic molecular analysis of Coffea arabica (Rubiaceae hybrids using SRAP markers

    Directory of Open Access Journals (Sweden)

    Manoj Kumar Mishra

    2011-06-01

    Full Text Available In Coffea arabica (arabica coffee, the phenotypic as well as genetic variability has been found low because of the narrow genetic basis and self fertile nature of the species. Because of high similarity in phenotypic appearance among the majority of arabica collections, selection of parental lines for inter-varietals hybridization and identification of resultant hybrids at an early stage of plant growth is difficult. DNA markers are known to be reliable in identifying closely related cultivars and hybrids. Sequence Related Amplified Polymorphism (SRAP is a new molecular marker technology developed based on PCR. In this paper, sixty arabica-hybrid progenies belonging to six crosses were analyzed using 31 highly polymorphic SRAP markers. The analysis revealed seven types of SRAP marker profiles which are useful in discriminating the parents and hybrids. The number of bands amplified per primer pair ranges from 6.13 to 8.58 with average number of seven bands. Among six hybrid combinations, percentage of bands shared between hybrids and their parents ranged from 66.29% to 85.71% with polymorphic bands varied from 27.64% to 60.0%. Percentage of hybrid specific fragments obtained in various hybrid combinations ranged from 0.71% to 10.86% and ascribed to the consequence of meiotic recombination. Based on the similarity index calculation, it was observed that F1 hybrids share maximum number of bands with the female parent compared to male parent. The results obtained in the present study revealed the effectiveness of SRAP technique in cultivar identification and hybrid analysis in this coffee species. Rev. Biol. Trop. 59 (2: 607-617. Epub 2011 June 01.

  9. A new kernel discriminant analysis framework for electronic nose recognition

    International Nuclear Information System (INIS)

    Zhang, Lei; Tian, Feng-Chun

    2014-01-01

    Graphical abstract: - Highlights: • This paper proposes a new discriminant analysis framework for feature extraction and recognition. • The principle of the proposed NDA is derived mathematically. • The NDA framework is coupled with kernel PCA for classification. • The proposed KNDA is compared with state of the art e-Nose recognition methods. • The proposed KNDA shows the best performance in e-Nose experiments. - Abstract: Electronic nose (e-Nose) technology based on metal oxide semiconductor gas sensor array is widely studied for detection of gas components. This paper proposes a new discriminant analysis framework (NDA) for dimension reduction and e-Nose recognition. In a NDA, the between-class and the within-class Laplacian scatter matrix are designed from sample to sample, respectively, to characterize the between-class separability and the within-class compactness by seeking for discriminant matrix to simultaneously maximize the between-class Laplacian scatter and minimize the within-class Laplacian scatter. In terms of the linear separability in high dimensional kernel mapping space and the dimension reduction of principal component analysis (PCA), an effective kernel PCA plus NDA method (KNDA) is proposed for rapid detection of gas mixture components by an e-Nose. The NDA framework is derived in this paper as well as the specific implementations of the proposed KNDA method in training and recognition process. The KNDA is examined on the e-Nose datasets of six kinds of gas components, and compared with state of the art e-Nose classification methods. Experimental results demonstrate that the proposed KNDA method shows the best performance with average recognition rate and total recognition rate as 94.14% and 95.06% which leads to a promising feature extraction and multi-class recognition in e-Nose

  10. General tensor discriminant analysis and gabor features for gait recognition.

    Science.gov (United States)

    Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

    2007-10-01

    The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not. We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine

  11. Sustainable process design & analysis of hybrid separations

    DEFF Research Database (Denmark)

    Kumar Tula, Anjan; Befort, Bridgette; Garg, Nipun

    2016-01-01

    Distillation is an energy intensive operation in chemical process industries. There are around 40,000 distillation columns in operation in the US, requiring approximately 40% of the total energy consumption in US chemical process industries. However, analysis of separations by distillation has...... shown that more than 50% of energy is spent in purifying the last 5-10% of the distillate product. Membrane modules on the other hand can achieve high purity separations at lower energy costs, but if the flux is high, it requires large membrane area. A hybrid scheme where distillation and membrane...... modules are combined such that each operates at its highest efficiency, has the potential for significant energy reduction without significant increase of capital costs. This paper presents a method for sustainable design of hybrid distillation-membrane schemes with guaranteed reduction of energy...

  12. A Hybrid System for Subjectivity Analysis

    Directory of Open Access Journals (Sweden)

    Samir Rustamov

    2018-01-01

    Full Text Available We suggested different structured hybrid systems for the sentence-level subjectivity analysis based on three supervised machine learning algorithms, namely, Hidden Markov Model, Fuzzy Control System, and Adaptive Neuro-Fuzzy Inference System. The suggested feature extraction algorithm in our experiment computes a feature vector using statistical textual terms frequencies in a training dataset not having the use of any lexical knowledge except tokenization. Taking into consideration this fact, the above-mentioned methods may be employed in other languages as these methods do not utilize the morphological, syntactical, and lexical analysis in the classification problems.

  13. Using discriminant analysis as a nucleation event classification method

    Directory of Open Access Journals (Sweden)

    S. Mikkonen

    2006-01-01

    Full Text Available More than three years of measurements of aerosol size-distribution and different gas and meteorological parameters made in Po Valley, Italy were analysed for this study to examine which of the meteorological and trace gas variables effect on the emergence of nucleation events. As the analysis method, we used discriminant analysis with non-parametric Epanechnikov kernel, included in non-parametric density estimation method. The best classification result in our data was reached with the combination of relative humidity, ozone concentration and a third degree polynomial of radiation. RH appeared to have a preventing effect on the new particle formation whereas the effects of O3 and radiation were more conductive. The concentration of SO2 and NO2 also appeared to have significant effect on the emergence of nucleation events but because of the great amount of missing observations, we had to exclude them from the final analysis.

  14. Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

    Science.gov (United States)

    Santoso, Noviyanti; Wibowo, Wahyu

    2018-03-01

    A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

  15. Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

    Science.gov (United States)

    Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo

    2017-10-12

    Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

  16. Sustainable Production and Trade Discrimination: An Analysis of the WTO

    Directory of Open Access Journals (Sweden)

    María Alejandra Calle Saldarriaga

    2018-02-01

    Full Text Available This article aims to examine the legality of trade measures addressing environmental conditions of production (PPMs in the context of non-discrimination provisions under the General Agreement on Tariffs and Trade (GATT  and the Agreement on Technical Barriers to Trade (TBT Agreement.  It shows that the notion of de facto discrimination is still a sensitive subject in the analysis of origin-neutral measures, including those based on environmental PPMs. Much of the discussion regarding PPMs focuses on the issue of ‘like products’. The interpretation of ‘likeness’ has also served to classify PPMs into the two categories of product related and non-product related. Such distinction rests on how the PPM affects the final product. However, it is important to analyse to what extent these measures can accord less favourable treatment to like products. The author argues that this requires a competition analysis. This article also elucidates how depending upon the applicable law (the TBT Agreement or the GATT PPMs are likely to face different legal challenges, particularly in terms of less favourable treatment. The author also assesses the possibility of transposing concepts such as ‘legitimate regulatory distinctions’ stemming from the TBT jurisprudence into GATT cases involving PPMs, and whether there will be an additional ‘test’ for PPMs characterised as TBT measures. This article is based on an extensive literature review and doctrinal legal research

  17. Frontotemporal Dysfunction in Amyotrophic Lateral Sclerosis: A Discriminant Function Analysis.

    Science.gov (United States)

    Nidos, Andreas; Kasselimis, Dimitrios S; Simos, Panagiotis G; Rentzos, Michael; Alexakis, Theodoros; Zalonis, Ioannis; Zouvelou, Vassiliki; Potagas, Constantin; Evdokimidis, Ioannis; Woolley, Susan C

    2016-01-01

    There is growing evidence for extramotor dysfunction (EMd) in amyotrophic lateral sclerosis (ALS), with a reported prevalence of up to 52%. In the present study, we explore the clinical utility of a brief neuropsychological battery for the investigation of cognitive, behavioral, and language deficits in patients with ALS. Thirty-four consecutive ALS patients aged 44-89 years were tested with a brief neuropsychological battery, including executive, behavioral, and language measures. Patients were initially classified as EMd or non-EMd based on their scores on the frontal assessment battery (FAB). Between-group comparisons revealed significant differences in all measures (p < 0.01). Discriminant analysis resulted in a single canonical function, with all tests serving as significant predictors. This function agreed with the FAB in 13 of 17 patients screened as EMd and identified extramotor deficits in 2 additional patients. Overall sensitivity and specificity estimates against FAB were 88.2%. We stress the importance of discriminant function analysis in clinical neuropsychological assessment and argue that the proposed neuropsychological battery may be of clinical value, especially when the option of extensive and comprehensive neuropsychological testing is limited. The psychometric validity of an ALS-frontotemporal dementia diagnosis using neuropsychological tests is also discussed. © 2015 S. Karger AG, Basel.

  18. Anti-discrimination Analysis Using Privacy Attack Strategies

    KAUST Repository

    Ruggieri, Salvatore; Hajian, Sara; Kamiran, Faisal; Zhang, Xiangliang

    2014-01-01

    Social discrimination discovery from data is an important task to identify illegal and unethical discriminatory patterns towards protected-by-law groups, e.g., ethnic minorities. We deploy privacy attack strategies as tools for discrimination

  19. [Development of Tianma HPLC fingerprint and discriminant analysis].

    Science.gov (United States)

    Xiao, Jia-Jia; Huang, Hong; Lei, You-Cheng; Lin, Ting-Wen; Ma, Yue; Zhang, Jing; Zhang, Xing-Guo; Zhang, Da-Quan; Lv, Guang-Hua

    2017-07-01

    Tianma(the tuber of Gastrodia eleta) is a widely used and pricy Chinese herb. Its counterfeits are often found in herbal markets, which are the plant materials with similar macroscopic characteristics of Tianma. Moreover, the prices of Winter Tianma(cultivated Tianma) and Spring Tianma(mostly wild Tianma) have significant difference. However, it is difficult to identify the true or false, good or bad quality of Tianma samples. Thus, a total of 48 Tianma samples with different characteristics(including Winter Tianma, Spring Tianma, slice, powder, etc.) and 9 plant species 10 samples of Tianma counterfeits were collected and analyzed by HPLC-DAD-MS techniques. After optimizing the procedure of sample preparation, chromatographic and mass-spectral conditions, the HPLC chromatograms of all those samples were collected and compared. The similarities and Fisher discriminant analysis were further conducted between the HPLC chromatograms of Tianma and counterfeit, Winter Tianma and Spring Tianma. The results showed the HPLC chromatograms of 48 Tianma samples were similar at the correlation coefficient more than 0.848(n=48). Their mean chromatogram was simulated and used as Tianma HPLC fingerprint. There were 11 common peaks on the HPLC chromatograms of Tianma, in which 6 main peaks were chosen as characteristic peaks and identified as gastrodin, p-hydroxybenzyl alcohol, parishin A, parishin B, parishin C, parishin E, respectively by comparison of the retention time, UV and MS data with those of standard chemical compounds. All the six chemical compounds are bioactive in Tianma. However, the HPLC chromatograms of the 10 counterfeit samples were significantly different from Tianma fingerprint. The correlation coefficients between HPLC fingerprints of Tianma with the HPLC chromatograms of counterfeits were less than 0.042 and the characteristic peaks were not observed on the HPLC chromatograms of these counterfeit samples. It indicated the true or false Tianma can be

  20. The intersectionality of discrimination attributes and bullying among youth: an applied latent class analysis.

    Science.gov (United States)

    Garnett, Bernice Raveche; Masyn, Katherine E; Austin, S Bryn; Miller, Matthew; Williams, David R; Viswanath, Kasisomayajula

    2014-08-01

    Discrimination is commonly experienced among adolescents. However, little is known about the intersection of multiple attributes of discrimination and bullying. We used a latent class analysis (LCA) to illustrate the intersections of discrimination attributes and bullying, and to assess the associations of LCA membership to depressive symptoms, deliberate self harm and suicidal ideation among a sample of ethnically diverse adolescents. The data come from the 2006 Boston Youth Survey where students were asked whether they had experienced discrimination based on four attributes: race/ethnicity, immigration status, perceived sexual orientation and weight. They were also asked whether they had been bullied or assaulted for these attributes. A total of 965 (78%) students contributed to the LCA analytic sample (45% Non-Hispanic Black, 29% Hispanic, 58% Female). The LCA revealed that a 4-class solution had adequate relative and absolute fit. The 4-classes were characterized as: low discrimination (51%); racial discrimination (33%); sexual orientation discrimination (7%); racial and weight discrimination with high bullying (intersectional class) (7%). In multivariate models, compared to the low discrimination class, individuals in the sexual orientation discrimination class and the intersectional class had higher odds of engaging in deliberate self-harm. Students in the intersectional class also had higher odds of suicidal ideation. All three discrimination latent classes had significantly higher depressive symptoms compared to the low discrimination class. Multiple attributes of discrimination and bullying co-occur among adolescents. Research should consider the co-occurrence of bullying and discrimination.

  1. Discrimination against Latina/os: A Meta-Analysis of Individual-Level Resources and Outcomes

    Science.gov (United States)

    Lee, Debbiesiu L.; Ahn, Soyeon

    2012-01-01

    This meta-analysis synthesizes the findings of 60 independent samples from 51 studies examining racial/ethnic discrimination against Latina/os in the United States. The purpose was to identify individual-level resources and outcomes that most strongly relate to discrimination. Discrimination against Latina/os significantly results in outcomes…

  2. Linear discriminant analysis of character sequences using occurrences of words

    KAUST Repository

    Dutta, Subhajit; Chaudhuri, Probal; Ghosh, Anil

    2014-01-01

    Classification of character sequences, where the characters come from a finite set, arises in disciplines such as molecular biology and computer science. For discriminant analysis of such character sequences, the Bayes classifier based on Markov models turns out to have class boundaries defined by linear functions of occurrences of words in the sequences. It is shown that for such classifiers based on Markov models with unknown orders, if the orders are estimated from the data using cross-validation, the resulting classifier has Bayes risk consistency under suitable conditions. Even when Markov models are not valid for the data, we develop methods for constructing classifiers based on linear functions of occurrences of words, where the word length is chosen by cross-validation. Such linear classifiers are constructed using ideas of support vector machines, regression depth, and distance weighted discrimination. We show that classifiers with linear class boundaries have certain optimal properties in terms of their asymptotic misclassification probabilities. The performance of these classifiers is demonstrated in various simulated and benchmark data sets.

  3. Linear discriminant analysis of character sequences using occurrences of words

    KAUST Repository

    Dutta, Subhajit

    2014-02-01

    Classification of character sequences, where the characters come from a finite set, arises in disciplines such as molecular biology and computer science. For discriminant analysis of such character sequences, the Bayes classifier based on Markov models turns out to have class boundaries defined by linear functions of occurrences of words in the sequences. It is shown that for such classifiers based on Markov models with unknown orders, if the orders are estimated from the data using cross-validation, the resulting classifier has Bayes risk consistency under suitable conditions. Even when Markov models are not valid for the data, we develop methods for constructing classifiers based on linear functions of occurrences of words, where the word length is chosen by cross-validation. Such linear classifiers are constructed using ideas of support vector machines, regression depth, and distance weighted discrimination. We show that classifiers with linear class boundaries have certain optimal properties in terms of their asymptotic misclassification probabilities. The performance of these classifiers is demonstrated in various simulated and benchmark data sets.

  4. Semi-supervised learning for ordinal Kernel Discriminant Analysis.

    Science.gov (United States)

    Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

    2016-12-01

    Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Anti-discrimination Analysis Using Privacy Attack Strategies

    KAUST Repository

    Ruggieri, Salvatore

    2014-09-15

    Social discrimination discovery from data is an important task to identify illegal and unethical discriminatory patterns towards protected-by-law groups, e.g., ethnic minorities. We deploy privacy attack strategies as tools for discrimination discovery under hard assumptions which have rarely tackled in the literature: indirect discrimination discovery, privacy-aware discrimination discovery, and discrimination data recovery. The intuition comes from the intriguing parallel between the role of the anti-discrimination authority in the three scenarios above and the role of an attacker in private data publishing. We design strategies and algorithms inspired/based on Frèchet bounds attacks, attribute inference attacks, and minimality attacks to the purpose of unveiling hidden discriminatory practices. Experimental results show that they can be effective tools in the hands of anti-discrimination authorities.

  6. A hybrid approach for global sensitivity analysis

    International Nuclear Information System (INIS)

    Chakraborty, Souvik; Chowdhury, Rajib

    2017-01-01

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

  7. On discriminant analysis techniques and correlation structures in high dimensions

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder

    This paper compares several recently proposed techniques for performing discriminant analysis in high dimensions, and illustrates that the various sparse methods dier in prediction abilities depending on their underlying assumptions about the correlation structures in the data. The techniques...... the methods in two: Those who assume independence between the variables and thus use a diagonal estimate of the within-class covariance matrix, and those who assume dependence between the variables and thus use an estimate of the within-class covariance matrix, which also estimates the correlations between...... variables. The two groups of methods are compared and the pros and cons are exemplied using dierent cases of simulated data. The results illustrate that the estimate of the covariance matrix is an important factor with respect to choice of method, and the choice of method should thus be driven by the nature...

  8. Analysis of product efficiency of hybrid vehicles and promotion policies

    International Nuclear Information System (INIS)

    Choi, Hyundo; Oh, Inha

    2010-01-01

    The key aim of this study is to evaluate the product efficiency of current hybrid vehicles and suggest effective policies to promote hybrid vehicles in the Korean automobile market and development trends of hybrid vehicles. The efficiency levels for car models sold in Korea, including hybrid ones, were measured using the recently developed discrete additive data envelopment analysis (DEA) model that reflects consumer preference. The result of the analysis shows that current hybrid vehicles on the market are still at lower competitive advantage than traditional car models with conventional combustion engines and we can suggest a mix of incentive policies to promote the competitiveness of hybrid vehicles. In addition, we also identify two distinctive trends of hybrid vehicle development: environment-oriented hybrid vehicles and performance-oriented hybrid vehicles. It implies that the government should take account of development trends of hybrid vehicles to achieve the policy goals in designing support schemes and automobile companies that are willing to develop hybrid vehicles can also gain some insights for making strategic decisions. (author)

  9. Asymptotic performance of regularized quadratic discriminant analysis based classifiers

    KAUST Repository

    Elkhalil, Khalil

    2017-12-13

    This paper carries out a large dimensional analysis of the standard regularized quadratic discriminant analysis (QDA) classifier designed on the assumption that data arise from a Gaussian mixture model. The analysis relies on fundamental results from random matrix theory (RMT) when both the number of features and the cardinality of the training data within each class grow large at the same pace. Under some mild assumptions, we show that the asymptotic classification error converges to a deterministic quantity that depends only on the covariances and means associated with each class as well as the problem dimensions. Such a result permits a better understanding of the performance of regularized QDA and can be used to determine the optimal regularization parameter that minimizes the misclassification error probability. Despite being valid only for Gaussian data, our theoretical findings are shown to yield a high accuracy in predicting the performances achieved with real data sets drawn from popular real data bases, thereby making an interesting connection between theory and practice.

  10. An Analysis of Discrimination by Real Estate Brokers.

    Science.gov (United States)

    Yinger, John

    This paper focuses on designing policies to eliminate discrimination in the sale of single-family houses by analyzing the behavior of the agents who actually do most of the discriminating, namely real estate agents. Discriminatory practices are said to be supported by policies of house builders, lending institutions, and government, and by the…

  11. Discriminant analysis of maintaining a vertical position in the water

    Directory of Open Access Journals (Sweden)

    Bratuša Zoran

    2015-01-01

    Full Text Available Water polo is the only sports game that takes place in the water. During the outplay, a vertical body position with the two basic mechanisms of the leg work - a breaststroke leg kick and an eggbeater leg kick, prevails. Starting from the significance of a vertical position during the game play, the methods of assessing physical preparedness of the athletes of all the categories also include the evaluation of maintaining a vertical position and consequently the load of the leg muscles. The measurements are performed during the maintenance of a vertical position (swimming in place through one of the specified mechanisms of leg work, i.e. a vertical position technique. The aim of this paper was to determine the application of different mechanisms of the leg kicks in maintaining a vertical position with young water polo players in relation to their position. The study included 29 selected junior water polo players (age_15.8 ± 0.8 years; BH_185.2 ± 5.3cm and BW_81.7 ± 7.7kg. The measurements were performed during the tests of swimming in place at the maximum intensity lasting 10 seconds, by the breaststroke and eggbeater leg kicks. The isometric tensiometry tests were used for the measurements. The results were analysed by the application of descriptive statistics, and the kinetic selection characteristic was defined by the application of discriminant analysis. Higher average values were achieved with the breaststroke leg kick technique Fmax, ImpF and RFD (avgFmaxLEGGBK =157.46±19.93N; avgImpF_LEGGBK =45.43±10.64Ns; avgRFD_LEGGBK=337.85±80.73N/s; avgFmaxLBKICK=227.18±49.17N; avgImpF_LBKICK=55.99±14.59Ns; avgRFD_LBKICK=545.47±159.15N/s. After discriminant analysis, the results have shown that the eggbeater leg kick is a selection technique, whereas the force - Fmax is a kinetic selection variable. Based on the obtained results and the analyses performed it may be concluded that a training factor dominant for maintaining a vertical position by

  12. Sparse Regression by Projection and Sparse Discriminant Analysis

    KAUST Repository

    Qi, Xin

    2015-04-03

    © 2015, © American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America. Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high-dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths and the tuning parameters are determined by a cross-validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares, and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared with the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplementary materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.

  13. Simulation and Analysis of the Hybrid Operating Mode in ITER

    International Nuclear Information System (INIS)

    Kessel, C.E.; Budny, R.V.; Indireshkumar, K.

    2005-01-01

    The hybrid operating mode in ITER is examined with 0D systems analysis, 1.5D discharge scenario simulations using TSC and TRANSP, and the ideal MHD stability is discussed. The hybrid mode has the potential to provide very long pulses and significant neutron fluence if the physics regime can be produced in ITER. This paper reports progress in establishing the physics basis and engineering limitation for the hybrid mode in ITER

  14. Discrimination of ginseng cultivation regions using light stable isotope analysis.

    Science.gov (United States)

    Kim, Kiwook; Song, Joo-Hyun; Heo, Sang-Cheol; Lee, Jin-Hee; Jung, In-Woo; Min, Ji-Sook

    2015-10-01

    Korean ginseng is considered to be a precious health food in Asia. Today, thieves frequently compromise ginseng farms by pervasive theft. Thus, studies regarding the characteristics of ginseng according to growth region are required in order to deter ginseng thieves and prevent theft. In this study, 6 regions were selected on the basis of Korea regional criteria (si, gun, gu), and two ginseng-farms were randomly selected from each of the 6 regions. Then 4-6 samples of ginseng were acquired from each ginseng farm. The stable isotopic compositions of H, O, C, and N of the collected ginseng samples were analyzed. As a result, differences in the hydrogen isotope ratios could be used to distinguish regional differences, and differences in the nitrogen isotope ratios yielded characteristic information regarding the farms from which the samples were obtained. Thus, stable isotope values could be used to differentiate samples according to regional differences. Therefore, stable isotope analysis serves as a powerful tool to discriminate the regional origin of Korean ginseng samples from across Korea. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. ANALYSIS ON WOMEN DISCRIMINATION IN THE LABOUR MARKET IN ROMANIA

    OpenAIRE

    Victoria-Mihaela Brînzea

    2011-01-01

    Eliminating gender-based discrimination is one of the important prerequisite for building a fair society; this can be achieved only through the active involvement of the authorities and of each person. Although during recent years there have been positive changes in the relationships between men and women, improving women's situation to some extent, it can be said that discrimination based on social gender was reduced but not eliminated entirely, equality of chances having not been achieved e...

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

    Science.gov (United States)

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

    2018-01-01

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

  17. Stability Analysis for Hybrid Automata Using Conservative Gains

    NARCIS (Netherlands)

    Langerak, Romanus; Engell, S.; Guegen, H.; Polderman, Jan W.; Krilavicius, T.; Zaytoon, J.

    2003-01-01

    This paper presents a stability analysis approach for a class of hybrid automata. It is assumed that the dynamics in each location of the hybrid automaton is linear and asymptotically stable, and that the guards on the transitions are hyperplanes in the state space. For each pair of ingoing and

  18. Impact of hybrid GSI analysis using ETR ensembles

    Indian Academy of Sciences (India)

    Impact of hybrid GSI analysis using ETR ensembles. V S Prasad∗ and C J .... In this study, impact of hybrid ..... of water between vapour, clouds and ice (Damrath et al. 2000). ... flooding – June 2013; Weather and Climate Extremes 4. 22–34.

  19. Stability analysis of maize hybrids across north west of Pakistan

    International Nuclear Information System (INIS)

    Rahman, H.; Durreshawar; Ali, S.; Iftikhar, F.; Khalil, I.H.; Shah, S.M.A.; Ahmad, H.

    2010-01-01

    Stability analysis was carried out to study stability in performance and genotype x environment interactions for 18 maize hybrids across three locations of NWFP i.e., Agricultural University Peshawar (AUP), Agricultural Research Station (ARS), Baffa, (Mansehra) and Cereal Crops Research Institute (CCRI), Pirsabak (Nowshera), during 2006. Data were recorded on different morphological and yield parameters. Analysis of variance indicated significant differences among the three locations for all the traits studied. Hybrids showed significant differences for all parameters except anthesis silking interval (ASI) and ear height, which were non significant across the three locations. The hybrid x location interactions also revealed significant differences for days to 50% silking, days to 50% anthesis, ASI, grain moisture at harvest and grain yield per hectare while non significant differences were observed for plant height and ear height. Based on yield performance of hybrids across the three locations, Baffa ranked first as compared to the other two locations. Hybrid DK-1 x EV-9806 was the highest yielding across the three locations followed by hybrid AGB-108, while the lowest yield was observed for hybrid CSCY. Stability in performance was evident for hybrid CS-2Y2 with regard to days required for silking and anthesis. Stability in anthesis silking interval (ASI) was manifested for hybrid CS-222. Hybrid AGB-108 was comparatively stable for grain yield across the tested locations. Remaining hybrids seemed to be considerably influenced by Genotype x environment interactions encountered at the tested locations and location specific selection has to be made while selecting a maize hybrid for a particular location. (author)

  20. Hybrid Threat Center of Gravity Analysis: Cutting the Gordian Knot

    Science.gov (United States)

    2016-04-04

    19b. TELEPHONE NUMBER (Include area code) 04/04/2016 Master’s Thesis 22-7-2015 to 04-04-2016 HYBRID THREAT CENTER OF GRAVITY ANALYSIS: CUTTING THE...CENTER OF GRAVITY ANALYSIS: CUTTING THE GORDIAN KNOT By Michael D. Reilly LtCol, USMC Intentionally left blank...HYBRID THREAT CENTER OF GRAVITY ANALYSIS: CUTTING THE GORDIAN KNOT By Michael D. Reilly LtCol, USMC A paper submitted to the Faculty of the Joint Advanced

  1. Thyroid nodule classification using ultrasound elastography via linear discriminant analysis.

    Science.gov (United States)

    Luo, Si; Kim, Eung-Hun; Dighe, Manjiri; Kim, Yongmin

    2011-05-01

    The non-surgical diagnosis of thyroid nodules is currently made via a fine needle aspiration (FNA) biopsy. It is estimated that somewhere between 250,000 and 300,000 thyroid FNA biopsies are performed in the United States annually. However, a large percentage (approximately 70%) of these biopsies turn out to be benign. Since the aggressive FNA management of thyroid nodules is costly, quantitative risk assessment and stratification of a nodule's malignancy is of value in triage and more appropriate healthcare resources utilization. In this paper, we introduce a new method for classifying the thyroid nodules based on the ultrasound (US) elastography features. Unlike approaches to assess the stiffness of a thyroid nodule by visually inspecting the pseudo-color pattern in the strain image, we use a classification algorithm to stratify the nodule by using the power spectrum of strain rate waveform extracted from the US elastography image sequence. Pulsation from the carotid artery was used to compress the thyroid nodules. Ultrasound data previously acquired from 98 thyroid nodules were used in this retrospective study to evaluate our classification algorithm. A classifier was developed based on the linear discriminant analysis (LDA) and used to differentiate the thyroid nodules into two types: (I) no FNA (observation-only) and (II) FNA. Using our method, 62 nodules were classified as type I, all of which were benign, while 36 nodules were classified as Type-II, 16 malignant and 20 benign, resulting in a sensitivity of 100% and specificity of 75.6% in detecting malignant thyroid nodules. This indicates that our triage method based on US elastography has the potential to substantially reduce the number of FNA biopsies (63.3%) by detecting benign nodules and managing them via follow-up observations rather than an FNA biopsy. Published by Elsevier B.V.

  2. 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.

  3. Analysis of Hybrid Hydrogen Systems: Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Dean, J.; Braun, R.; Munoz, D.; Penev, M.; Kinchin, C.

    2010-01-01

    Report on biomass pathways for hydrogen production and how they can be hybridized to support renewable electricity generation. Two hybrid systems were studied in detail for process feasibility and economic performance. The best-performing system was estimated to produce hydrogen at costs ($1.67/kg) within Department of Energy targets ($2.10/kg) for central biomass-derived hydrogen production while also providing value-added energy services to the electric grid.

  4. WOMEN RESISTANCE TOWARD DISCRIMINATIONS: A MODERN LITERARY WORK ANALYSIS ON FEMINISM REVIEW IN BEKISAR MERAH

    Directory of Open Access Journals (Sweden)

    Mujiono .

    2016-02-01

    Full Text Available This study was conducted to discover the discriminations against women in the Bekisar Merah novel and how they formulate resistance to those discriminations. To address the above objective, this study used descriptive qualitative research design with a feminism approach. Source of the data in this study was the second edition of Bekisar Merah novel written by Ahmad Tohari. The data included were words, phrases, sentences, and paragraphs on Bekisar Merah which portray womens discrimination toward Lasi, the women figure in the novel, and power types formulated by her who resisted the discrimination. To analyze the data, content analysis was applied. Triangulation was used to ensure the trustworthiness of the data. The result of the study showed eight forms of discriminations and three resistances. The discriminations were domestic abuse, molestation, gender harassment, seduction behavior, imposition, coercion, bribery, and subordination. The resistances were physically, mentally, and verbally.

  5. Discriminant analysis of normal and malignant breast tissue based upon INAA investigation of elemental concentration

    International Nuclear Information System (INIS)

    Kwanhoong Ng; Senghuat Ong; Bradley, D.A.; Laimeng Looi

    1997-01-01

    Discriminant analysis of six trace element concentrations measured by instrumental neutron activation analysis (INAA) in 26 paired-samples of malignant and histologically normal human breast tissues shows the technique to be a potentially valuable clinical tool for making malignant-normal classification. Nonparametric discriminant analysis is performed for the data obtained. Linear and quadratic discriminant analyses are also carried out for comparison. For this data set a formal analysis shows that the elements which may be useful in distinguishing between malignant and normal tissues are Ca, Rb and Br, providing correct classification for 24 out of 26 normal samples and 22 out of 26 malignant samples. (Author)

  6. A Hybrid Feature Subset Selection Algorithm for Analysis of High Correlation Proteomic Data

    Science.gov (United States)

    Kordy, Hussain Montazery; Baygi, Mohammad Hossein Miran; Moradi, Mohammad Hassan

    2012-01-01

    Pathological changes within an organ can be reflected as proteomic patterns in biological fluids such as plasma, serum, and urine. The surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF MS) has been used to generate proteomic profiles from biological fluids. Mass spectrometry yields redundant noisy data that the most data points are irrelevant features for differentiating between cancer and normal cases. In this paper, we have proposed a hybrid feature subset selection algorithm based on maximum-discrimination and minimum-correlation coupled with peak scoring criteria. Our algorithm has been applied to two independent SELDI-TOF MS datasets of ovarian cancer obtained from the NCI-FDA clinical proteomics databank. The proposed algorithm has used to extract a set of proteins as potential biomarkers in each dataset. We applied the linear discriminate analysis to identify the important biomarkers. The selected biomarkers have been able to successfully diagnose the ovarian cancer patients from the noncancer control group with an accuracy of 100%, a sensitivity of 100%, and a specificity of 100% in the two datasets. The hybrid algorithm has the advantage that increases reproducibility of selected biomarkers and able to find a small set of proteins with high discrimination power. PMID:23717808

  7. Non-Discrimination à la Cour: the ECJ’s (lack of) Comparability Analysis in Direct Tax Cases

    NARCIS (Netherlands)

    Wattel, P.

    2015-01-01

    The ECJ’s discrimination analysis in direct tax cases is inconsistent. It sometimes creates discrimination, condemns non-existent discrimination or fails to address discrimination. Only one comparability standard makes sense: to be (subject to tax) or not to be (subject to tax). The ECJ is not

  8. Discrimination of Transgenic Rice Based on Near Infrared Reflectance Spectroscopy and Partial Least Squares Regression Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    ZHANG Long

    2015-09-01

    Full Text Available Near infrared reflectance spectroscopy (NIRS, a non-destructive measurement technique, was combined with partial least squares regression discrimiant analysis (PLS-DA to discriminate the transgenic (TCTP and mi166 and wild type (Zhonghua 11 rice. Furthermore, rice lines transformed with protein gene (OsTCTP and regulation gene (Osmi166 were also discriminated by the NIRS method. The performances of PLS-DA in spectral ranges of 4 000–8 000 cm-1 and 4 000–10 000 cm-1 were compared to obtain the optimal spectral range. As a result, the transgenic and wild type rice were distinguished from each other in the range of 4 000–10 000 cm-1, and the correct classification rate was 100.0% in the validation test. The transgenic rice TCTP and mi166 were also distinguished from each other in the range of 4 000–10 000 cm-1, and the correct classification rate was also 100.0%. In conclusion, NIRS combined with PLS-DA can be used for the discrimination of transgenic rice.

  9. Regularized generalized eigen-decomposition with applications to sparse supervised feature extraction and sparse discriminant analysis

    DEFF Research Database (Denmark)

    Han, Xixuan; Clemmensen, Line Katrine Harder

    2015-01-01

    We propose a general technique for obtaining sparse solutions to generalized eigenvalue problems, and call it Regularized Generalized Eigen-Decomposition (RGED). For decades, Fisher's discriminant criterion has been applied in supervised feature extraction and discriminant analysis, and it is for...

  10. Declining Bias and Gender Wage Discrimination? A Meta-Regression Analysis

    Science.gov (United States)

    Jarrell, Stephen B.; Stanley, T. D.

    2004-01-01

    The meta-regression analysis reveals that there is a strong tendency for discrimination estimates to fall and wage discrimination exist against the woman. The biasing effect of researchers' gender of not correcting for selection bias has weakened and changes in labor market have made it less important.

  11. Cost analysis of hybrid adaptive routing protocol for heterogeneous ...

    Indian Academy of Sciences (India)

    NONITA SHARMA

    Event detection; wireless sensor networks; hybrid routing; cost benefit analysis; proactive routing; reactive routing. 1. ... additional energy, high processing power, etc. are deployed to extend the .... transmit to its parent node. (2) Reactive ...

  12. Statistical analysis of agarwood oil compounds in discriminating the ...

    African Journals Online (AJOL)

    Enhancing and improving the discrimination technique is the main aim to determine or grade the good quality of agarwood oil. In this paper, all statistical works were performed via SPSS software. Two parameters involved are abundance of compound (%) and quality of t agarwood oil either low or high quality. The result ...

  13. Logistic discriminant analysis of breast cancer using ultrasound measurement

    International Nuclear Information System (INIS)

    Abdolmaleki, P.; Mokhtari Dizaji, M.; Vahead, M.R.; Gity, M.

    2004-01-01

    Background: Logistic discriminant method was applied to differentiate malignant from benign in a group of patients with proved breast lesions of the basis of ultrasonic parameters. Materials and methods: Our database include 273 patients' ultrasonographic pictures consisting of 14 quantitative variables. The measured variables were ultrasound propagation velocity, acoustic impedance and attenuation coefficient at 10 MHz in breast lesions at 20, 25, 30 and 35 d ig c temperature, physical density and age. This database was randomly divided into the estimation of 201 and validation of 72 samples. The estimation samples were used to build the logistic discriminant model, and validation samples were used to validate the performance. Finally important criteria such as sensitivity, specificity, accuracy and area under the receiver operating characteristic curve were evaluated. Results: Our results showed that the logistic discriminant method was able to classify correctly 67 out of 72 cases presented in the validation sample. The results indicate a remarkable diagnostic accuracy of 93%. Conclusion: A logistic discriminator approach is capable of predicting the probability of malignancy of breast cancer. Features from ultrasonic measurement on ultrasound imaging is used in this approach

  14. An Application of Monte-Carlo-Based Sensitivity Analysis on the Overlap in Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    S. Razmyan

    2012-01-01

    Full Text Available Discriminant analysis (DA is used for the measurement of estimates of a discriminant function by minimizing their group misclassifications to predict group membership of newly sampled data. A major source of misclassification in DA is due to the overlapping of groups. The uncertainty in the input variables and model parameters needs to be properly characterized in decision making. This study combines DEA-DA with a sensitivity analysis approach to an assessment of the influence of banks’ variables on the overall variance in overlap in a DA in order to determine which variables are most significant. A Monte-Carlo-based sensitivity analysis is considered for computing the set of first-order sensitivity indices of the variables to estimate the contribution of each uncertain variable. The results show that the uncertainties in the loans granted and different deposit variables are more significant than uncertainties in other banks’ variables in decision making.

  15. Classification of astrocyto-mas and meningiomas using statistical discriminant analysis on MRI data

    International Nuclear Information System (INIS)

    Siromoney, Anna; Prasad, G.N.S.; Raghuram, Lakshminarayan; Korah, Ipeson; Siromoney, Arul; Chandrasekaran, R.

    2001-01-01

    The objective of this study was to investigate the usefulness of Multivariate Discriminant Analysis for classifying two groups of primary brain tumours, astrocytomas and meningiomas, from Magnetic Resonance Images. Discriminant analysis is a multivariate technique concerned with separating distinct sets of objects and with allocating new objects to previously defined groups. Allocation or classification rules are usually developed from learning examples in a supervised learning environment. Data from signal intensity measurements in the multiple scan performed on each patient in routine clinical scanning was analysed using Fisher's Classification, which is one method of discriminant analysis

  16. A Theoretical Analysis of Why Hybrid Ensembles Work

    Directory of Open Access Journals (Sweden)

    Kuo-Wei Hsu

    2017-01-01

    Full Text Available Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.

  17. DNA hybridization sensing for cytogenetic analysis

    DEFF Research Database (Denmark)

    Kwasny, Dorota; Dapra, Johannes; Brøgger, Anna Line

    2013-01-01

    are rearrangements between two chromosome arms that results in two derivative chromosomes having a mixed DNA sequence. The current detection method is a Fluorescent In situ Hybridization, which requires a use of expensive, fluorescently labeled probes that target the DNA sequences of two chromosomes involved...... in the translocation (Kwasny et al., 2012). We have developed a new double hybridization assay that allows for sorting of the DNA chromosomal fragments into separate compartment, moreover allowing for detection of the translocation. To detect the translocation it is necessary to determine that the two DNA sequences...... forming a derivative chromosome are connected, which is achieved by two subsequent hybridization steps. The first example of the translocation detection was presented on lab-on-a-disc using fluorescently labeled DNA fragments, representing the derivative chromosome (Brøgger et al., 2012). To allow...

  18. Analysis of Synchronization for Coupled Hybrid Systems

    DEFF Research Database (Denmark)

    Li, Zheng; Wisniewski, Rafal

    2006-01-01

    In the control systems with coupled multi-subsystem, the subsystems might be synchronized (i.e. all the subsystems have the same operation states), which results in negative influence to the whole system. For example, in the supermarket refrigeration systems, the synchronized switch of each...... subsystem will cause low efficiency, inferior control performance and a high wear on the compressor. This paper takes the supermarket refrigeration systems as an example to analyze the synchronization and its coupling strengths of coupled hybrid systems, which may provide a base for further research...... of control strategies. This paper combines topology and section mapping theories together to show a new way of analyzing hybrid systems...

  19. Mars Hybrid Propulsion System Trajectory Analysis. Part II; Cargo Missions

    Science.gov (United States)

    Chai, Patrick R.; Merrill, Raymond G.; Qu, Min

    2015-01-01

    NASA's Human Spaceflight Architecture Team is developing a reusable hybrid transportation architecture in which both chemical and electric propulsion systems are used to send crew and cargo to Mars destinations such as Phobos, Deimos, the surface of Mars, and other orbits around Mars. By combining chemical and electrical propulsion into a single spaceship and applying each where it is more effective, the hybrid architecture enables a series of Mars trajectories that are more fuel-efficient than an all chemical architecture without significant increases in flight times. This paper shows the feasibility of the hybrid transportation architecture to pre-deploy cargo to Mars and Phobos in support of the Evolvable Mars Campaign crew missions. The analysis shows that the hybrid propulsion stage is able to deliver all of the current manifested payload to Phobos and Mars through the first three crew missions. The conjunction class trajectory also allows the hybrid propulsion stage to return to Earth in a timely fashion so it can be reused for additional cargo deployment. The 1,100 days total trip time allows the hybrid propulsion stage to deliver cargo to Mars every other Earth-Mars transit opportunity. For the first two Mars surface mission in the Evolvable Mars Campaign, the short trip time allows the hybrid propulsion stage to be reused for three round-trip journeys to Mars, which matches the hybrid propulsion stage's designed lifetime for three round-trip crew missions to the Martian sphere of influence.

  20. Advanced Coal Wind Hybrid: Economic Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Phadke, Amol; Goldman, Charles; Larson, Doug; Carr, Tom; Rath, Larry; Balash, Peter; Yih-Huei, Wan

    2008-11-28

    Growing concern over climate change is prompting new thinking about the technologies used to generate electricity. In the future, it is possible that new government policies on greenhouse gas emissions may favor electric generation technology options that release zero or low levels of carbon emissions. The Western U.S. has abundant wind and coal resources. In a world with carbon constraints, the future of coal for new electrical generation is likely to depend on the development and successful application of new clean coal technologies with near zero carbon emissions. This scoping study explores the economic and technical feasibility of combining wind farms with advanced coal generation facilities and operating them as a single generation complex in the Western US. The key questions examined are whether an advanced coal-wind hybrid (ACWH) facility provides sufficient advantages through improvements to the utilization of transmission lines and the capability to firm up variable wind generation for delivery to load centers to compete effectively with other supply-side alternatives in terms of project economics and emissions footprint. The study was conducted by an Analysis Team that consists of staff from the Lawrence Berkeley National Laboratory (LBNL), National Energy Technology Laboratory (NETL), National Renewable Energy Laboratory (NREL), and Western Interstate Energy Board (WIEB). We conducted a screening level analysis of the economic competitiveness and technical feasibility of ACWH generation options located in Wyoming that would supply electricity to load centers in California, Arizona or Nevada. Figure ES-1 is a simple stylized representation of the configuration of the ACWH options. The ACWH consists of a 3,000 MW coal gasification combined cycle power plant equipped with carbon capture and sequestration (G+CC+CCS plant), a fuel production or syngas storage facility, and a 1,500 MW wind plant. The ACWH project is connected to load centers by a 3,000 MW

  1. Discrimination based on HIV/AIDS status: A comparative analysis of ...

    African Journals Online (AJOL)

    Discrimination based on HIV/AIDS status: A comparative analysis of the Nigerian court's decision in Festus Odaife & Ors v Attorney General of the Federation & Ors with other Commonwealth jurisdictions.

  2. Analysis of Financial Ratio to Distinguish Indonesia Joint Venture General Insurance Company Performance using Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Subiakto Soekarno

    2012-01-01

    Full Text Available Insurance industry stands as a service business that plays a significant role in Indonesiaeconomical condition. The development of insurance industry in Indonesia, both of generalinsurance and life insurance, has increased very fast. The general insurance industry itselfdivided into two major players which are local private company and Joint Venture Company.Lately, the use of statistical techniques and financial ratios models to asses financial institutionsuch as insurance company have been used as one of the appropriate combination inpredicting the performance of an industry. This research aims to distinguish between JointVenture General Insurance Companies that have a good performance and those who are lessperforming well using Discriminant Analysis. Further, the findings led that DiscriminantAnalysis is able to distinguish Joint Venture General Insurance Companies that have a goodperformance and those who are not performing well. There are also six ratios which are RBC,Technical Reserve to Investment Ratio, Debt Ratio, Return on Equity, Loss Ratio, and ExpenseRatio that stand as the most influential ratios to distinguish the performance of joint venturegeneral insurance companies. In addition, the result suggest business people to be concernedtoward those six ratios, to increase their companies’ performance.Key words: general insurance, financial ratio, discriminant analysis

  3. Research on n-γ discrimination method based on spectrum gradient analysis of signals

    International Nuclear Information System (INIS)

    Luo Xiaoliang; Liu Guofu; Yang Jun; Wang Yueke

    2013-01-01

    Having discovered that there are distinct differences between the spectrum gradient of the output neutron and γ-ray signal from liquid scintillator detectors, this paper presented a n-γ discrimination method called spectrum gradient analysis (SGA) based on frequency-domain features of the pulse signals. The basic principle and feasibility of SGA method were discussed and the validity of n-γ discrimination results of SGA was verified by the associated particle neutron flight experiment. The discrimination performance of SGA was evaluated under different conditions of sampling rates ranging from 5 G/s to 250 M/s. The results show that SGA method exhibits insensitivity to noise, strong anti-interference ability, stable discrimination performance and lower amount of calculation in contrast with time-domain n-γ discrimination methods. (authors)

  4. Application of discriminant analysis and generalized distance measures to uranium exploration

    International Nuclear Information System (INIS)

    Beauchamp, J.J.; Begovich, C.L.; Kane, V.E.; Wolf, D.A.

    1980-01-01

    The National Uranium Resource Evaluation (NURE) Program has as its goal the estimation of the nation's uranium resources. It is possile to use discriminant analysis methods on hydrogeochemical data collected in the NURE Program to aid in fomulating geochemical models that can be used to identify the anomalous areas used in resource estimation. Discriminant' analysis methods have been applied to data from the Plainview, Texas Quadrangle which has approximately 850 groundwater samples with more than 40 quantitative measurements per sample. Discriminant analysis topics involving estimation of misclassification probabilities, variable selection, and robust discrimination are applied. A method using generalized distance measures is given which enables the assignment of samples to a background population or a mineralized population whose parameters were estimated from separate studies. Each topic is related to its relevance in identifying areas of possible interest to uranium exploration. However, the methodology presented here is applicable to the identification of regions associated with other types of resources. 8 figures, 3 tables

  5. Application of discriminant analysis and generalized distance measures to uranium exploration

    International Nuclear Information System (INIS)

    Beauchamp, J.J.; Begovich, C.L.; Kane, V.E.; Wolf, D.A.

    1979-10-01

    The National Uranium Resource Evaluation (NURE) Project has as its goal estimation of the nation's uranium resources. It is possible to use discriminant analysis methods on hydrogeochemical data collected in the NURE Program to aid in formulating geochemical models which can be used to identify the anomalous regions necessary for resource estimation. Discriminant analysis methods have been applied to data from the Plainview, Texas Quadrangle which has approximately 850 groundwater samples with more than 40 quantitative measurements per sample. Discriminant analysis topics involving estimation of misclassification probabilities, variable selection, and robust discrimination are applied. A method using generalized distance measures is given which enables assigning samples to a background population or a mineralized population whose parameters were estimated from separate studies. Each topic is related to its relevance in identifying areas of possible interest to uranium exploration

  6. Key parameters analysis of hybrid HEMP simulator

    International Nuclear Information System (INIS)

    Mao Congguang; Zhou Hui

    2009-01-01

    According to the new standards on the high-altitude electromagnetic pulse (HEMP) developed by International Electrotechnical Commission (IEC), the target parameter requirements of the key structure of the hybrid HEMP simulator are decomposed. Firstly, the influences of the different excitation sources and biconical structures to the key parameters of the radiated electric field wave shape are investigated and analyzed. Then based on the influence curves the target parameter requirements of the pulse generator are proposed. Finally the appropriate parameters of the biconical structure and the excitation sources are chosen, and the computational result of the electric field in free space is presented. The results are of great value for the design of the hybrid HEMP simulator. (authors)

  7. PIXE analysis of fish otoliths. Application to fish stock discrimination

    International Nuclear Information System (INIS)

    Arai, Nobuaki; Sakamoto, Wataru; Tateno, Koji; Yoshida, Koji.

    1996-01-01

    PIXE was adopted to analyze trace elements in otoliths of Japanese flounder to discriminate among several local fish stocks. The otoliths were removed from samples caught at five different sea areas along with the coast of the Sea of Japan: Akita, Ishikawa, Kyoto (2 stations), and Fukuoka. Besides calcium as main component, strontium, manganese, and zinc were detected. Especially Sr concentrations were different among 4 areas except between 2 stations in Kyoto. It suggested that the fish in the 2 stations in Kyoto were the same stock differed to the others. (author)

  8. Hybrid chemical and nondestructive-analysis technique

    International Nuclear Information System (INIS)

    Hsue, S.T.; Marsh, S.F.; Marks, T.

    1982-01-01

    A hybrid chemical/NDA technique has been applied at the Los Alamos National Laboratory to the assay of plutonium in ion-exchange effluents. Typical effluent solutions contain low concentrations of plutonium and high concentrations of americium. A simple trioctylphosphine oxide (TOPO) separation can remove 99.9% of the americium. The organic phase that contains the separated plutonium can be accurately assayed by monitoring the uranium L x-ray intensities

  9. Multimodal Discrimination of Schizophrenia Using Hybrid Weighted Feature Concatenation of Brain Functional Connectivity and Anatomical Features with an Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Muhammad Naveed Iqbal Qureshi

    2017-09-01

    Full Text Available Multimodal features of structural and functional magnetic resonance imaging (MRI of the human brain can assist in the diagnosis of schizophrenia. We performed a classification study on age, sex, and handedness-matched subjects. The dataset we used is publicly available from the Center for Biomedical Research Excellence (COBRE and it consists of two groups: patients with schizophrenia and healthy controls. We performed an independent component analysis and calculated global averaged functional connectivity-based features from the resting-state functional MRI data for all the cortical and subcortical anatomical parcellation. Cortical thickness along with standard deviation, surface area, volume, curvature, white matter volume, and intensity measures from the cortical parcellation, as well as volume and intensity from sub-cortical parcellation and overall volume of cortex features were extracted from the structural MRI data. A novel hybrid weighted feature concatenation method was used to acquire maximal 99.29% (P < 0.0001 accuracy which preserves high discriminatory power through the weight of the individual feature type. The classification was performed by an extreme learning machine, and its efficiency was compared to linear and non-linear (radial basis function support vector machines, linear discriminant analysis, and random forest bagged tree ensemble algorithms. This article reports the predictive accuracy of both unimodal and multimodal features after 10-by-10-fold nested cross-validation. A permutation test followed the classification experiment to assess the statistical significance of the classification results. It was concluded that, from a clinical perspective, this feature concatenation approach may assist the clinicians in schizophrenia diagnosis.

  10. Label-free DNA hybridization detection and single base-mismatch discrimination using CE-ICP-MS assay.

    Science.gov (United States)

    Li, Yan; Sun, Shao-kai; Yang, Jia-lin; Jiang, Yan

    2011-12-07

    Detecting a specific DNA sequence and discriminating single base-mismatch is critical to clinical diagnosis, paternity testing, forensic sciences, food and drug industry, pathology, genetics, environmental monitoring, and anti-bioterrorism. To this end, capillary electrophoresis (CE) coupled with the inductively coupled plasma mass spectrometry (ICP-MS) method is developed using the displacing interaction between the target ssDNA and the competitor Hg(2+) for the first time. The thymine-rich capture ssDNA 1 is interacted with the competitor Hg(2+), forming an assembled complex in a hairpin-structure between the thymine bases arrangement at both sides of the capture ssDNA 1. In the presence of a target ssDNA with stronger affinity than that of the competitor Hg(2+), the energetically favorable hybridization between capture ssDNA 1 and the target ssDNA destroys the hairpin-structure and releases the competitor as free Hg(2+), which was then read out and accurately quantified by CE-ICP-MS assay. Under the optimal CE separation conditions, free Hg(2+) ions and its capture ssDNA 1 adduct were baseline separated and detected on-line by ICP-MS; the increased peak intensity of free Hg(2+) against the concentration of perfectly complementary target ssDNA was linear over the concentration range of 30-600 nmol L(-1) with a limit of detection of 8 nmol L(-1) (3s, n = 11) in the pre-incubated mixture containing 1 μmol L(-1) Hg(2+) and 0.2 μmol L(-1) capture ssDNA 1. This new assay method is simple in design since any target ssDNA binding can in principle result in free Hg(2+) release by 6-fold Hg(2+) signal amplification, avoiding oligonucleotide labeling or assistance by excess signal transducer and signal reporter to read out the target. Due to element-specific detection of ICP-MS in our assay procedure, the interference from the autofluorescence of substrata was eliminated.

  11. Gas Classification Using Combined Features Based on a Discriminant Analysis for an Electronic Nose

    Directory of Open Access Journals (Sweden)

    Sang-Il Choi

    2016-01-01

    Full Text Available This paper proposes a gas classification method for an electronic nose (e-nose system, for which combined features that have been configured through discriminant analysis are used. First, each global feature is extracted from the entire measurement section of the data samples, while the same process is applied to the local features of the section that corresponds to the stabilization, exposure, and purge stages. The discriminative information amounts in the individual features are then measured based on the discriminant analysis, and the combined features are subsequently composed by selecting the features that have a large amount of discriminative information. Regarding a variety of volatile organic compound data, the results of the experiment show that, in a noisy environment, the proposed method exhibits classification performance that is relatively excellent compared to the other feature types.

  12. Discrimination of handlebar grip samples by fourier transform infrared microspectroscopy analysis and statistics

    Directory of Open Access Journals (Sweden)

    Zeyu Lin

    2017-01-01

    Full Text Available In this paper, the authors presented a study on the discrimination of handlebar grip samples, to provide effective forensic science service for hit and run traffic cases. 50 bicycle handlebar grip samples, 49 electric bike handlebar grip samples, and 96 motorcycle handlebar grip samples have been randomly collected by the local police in Beijing (China. Fourier transform infrared microspectroscopy (FTIR was utilized as analytical technology. Then, target absorption selection, data pretreatment, and discrimination of linked samples and unlinked samples were chosen as three steps to improve the discrimination of FTIR spectrums collected from different handlebar grip samples. Principal component analysis and receiver operating characteristic curve were utilized to evaluate different data selection methods and different data pretreatment methods, respectively. It is possible to explore the evidential value of handlebar grip residue evidence through instrumental analysis and statistical treatments. It will provide a universal discrimination method for other forensic science samples as well.

  13. Stability analysis of hybrid-driven underwater glider

    Science.gov (United States)

    Niu, Wen-dong; Wang, Shu-xin; Wang, Yan-hui; Song, Yang; Zhu, Ya-qiang

    2017-10-01

    Hybrid-driven underwater glider is a new type of unmanned underwater vehicle, which combines the advantages of autonomous underwater vehicles and traditional underwater gliders. The autonomous underwater vehicles have good maneuverability and can travel with a high speed, while the traditional underwater gliders are highlighted by low power consumption, long voyage, long endurance and good stealth characteristics. The hybrid-driven underwater gliders can realize variable motion profiles by their own buoyancy-driven and propeller propulsion systems. Stability of the mechanical system determines the performance of the system. In this paper, the Petrel-II hybrid-driven underwater glider developed by Tianjin University is selected as the research object and the stability of hybrid-driven underwater glider unitedly controlled by buoyancy and propeller has been targeted and evidenced. The dimensionless equations of the hybrid-driven underwater glider are obtained when the propeller is working. Then, the steady speed and steady glide path angle under steady-state motion have also been achieved. The steady-state operating conditions can be calculated when the hybrid-driven underwater glider reaches the desired steady-state motion. And the steadystate operating conditions are relatively conservative at the lower bound of the velocity range compared with the range of the velocity derived from the method of the composite Lyapunov function. By calculating the hydrodynamic coefficients of the Petrel-II hybrid-driven underwater glider, the simulation analysis has been conducted. In addition, the results of the field trials conducted in the South China Sea and the Danjiangkou Reservoir of China have been presented to illustrate the validity of the analysis and simulation, and to show the feasibility of the method of the composite Lyapunov function which verifies the stability of the Petrel-II hybrid-driven underwater glider.

  14. Analysis and design of hybrid electric regional turboprop aircraft

    NARCIS (Netherlands)

    Voskuijl, M.; van Bogaert, J.; Gangoli Rao, A.

    2017-01-01

    The potential environmental benefits of hybrid electric regional turboprop aircraft in terms of fuel consumption are investigated. Lithium–air batteries are used as energy source in combination with conventional fuel. A validated design and analysis framework is extended with sizing and analysis

  15. Women ministers' experiences of gender discrimination in the Lutheran Church : a discourse analysis

    OpenAIRE

    2011-01-01

    M.A. The aim of this psychological study was to uncover women minister’s experiences of gender discrimination in the Lutheran Church by using a discourse analysis. Three female participants, who are involved in ministry in the Lutheran Church, were interviewed about their experiences and perceptions of gender discrimination. The resultant texts were analysed using Parker’s (2005) steps to discourse analytic reading. The discourses that were discovered indicate that power struggles are prev...

  16. Vehicle surge detection and pathway discrimination by pedestrians who are blind: Effect of adding an alert sound to hybrid electric vehicles on performance.

    Science.gov (United States)

    Kim, Dae Shik; Emerson, Robert Wall; Naghshineh, Koorosh; Pliskow, Jay; Myers, Kyle

    2012-05-01

    This study examined the effect of adding an artificially generated alert sound to a quiet vehicle on its detectability and localizability with 15 visually impaired adults. When starting from a stationary position, the hybrid electric vehicle with an alert sound was significantly more quickly and reliably detected than either the identical vehicle without such added sound or the comparable internal combustion engine vehicle. However, no significant difference was found between the vehicles in respect to how accurately the participants could discriminate the path of a given vehicle (straight vs. right turn). These results suggest that adding an artificial sound to a hybrid electric vehicle may help reduce delay in street crossing initiation by a blind pedestrian, but the benefit of such alert sound may not be obvious in determining whether the vehicle in his near parallel lane proceeds straight through the intersection or turns right in front of him.

  17. DNA content analysis allows discrimination between Trypanosoma cruzi and Trypanosoma rangeli.

    Science.gov (United States)

    Naves, Lucila Langoni; da Silva, Marcos Vinícius; Fajardo, Emanuella Francisco; da Silva, Raíssa Bernardes; De Vito, Fernanda Bernadelli; Rodrigues, Virmondes; Lages-Silva, Eliane; Ramírez, Luis Eduardo; Pedrosa, André Luiz

    2017-01-01

    Trypanosoma cruzi, a human protozoan parasite, is the causative agent of Chagas disease. Currently the species is divided into six taxonomic groups. The genome of the CL Brener clone has been estimated to be 106.4-110.7 Mb, and DNA content analyses revealed that it is a diploid hybrid clone. Trypanosoma rangeli is a hemoflagellate that has the same reservoirs and vectors as T. cruzi; however, it is non-pathogenic to vertebrate hosts. The haploid genome of T. rangeli was previously estimated to be 24 Mb. The parasitic strains of T. rangeli are divided into KP1(+) and KP1(-). Thus, the objective of this study was to investigate the DNA content in different strains of T. cruzi and T. rangeli by flow cytometry. All T. cruzi and T. rangeli strains yielded cell cycle profiles with clearly identifiable G1-0 (2n) and G2-M (4n) peaks. T. cruzi and T. rangeli genome sizes were estimated using the clone CL Brener and the Leishmania major CC1 as reference cell lines because their genome sequences have been previously determined. The DNA content of T. cruzi strains ranged from 87,41 to 108,16 Mb, and the DNA content of T. rangeli strains ranged from 63,25 Mb to 68,66 Mb. No differences in DNA content were observed between KP1(+) and KP1(-) T. rangeli strains. Cultures containing mixtures of the epimastigote forms of T. cruzi and T. rangeli strains resulted in cell cycle profiles with distinct G1 peaks for strains of each species. These results demonstrate that DNA content analysis by flow cytometry is a reliable technique for discrimination between T. cruzi and T. rangeli isolated from different hosts.

  18. Theoretical remarks on the statistics of three discriminants in Piety's automated signature analysis of PSD [Power Spectral Density] data

    International Nuclear Information System (INIS)

    Behringer, K.; Spiekerman, G.

    1984-01-01

    Piety (1977) proposed an automated signature analysis of power spectral density data. Eight statistical decision discriminants are introduced. For nearly all the discriminants, improved confidence statements can be made. The statistical characteristics of the last three discriminants, which are applications of non-parametric tests, are considered. (author)

  19. [Comparison of Discriminant Analysis and Decision Trees for the Detection of Subclinical Keratoconus].

    Science.gov (United States)

    Kleinhans, Sonja; Herrmann, Eva; Kohnen, Thomas; Bühren, Jens

    2017-08-15

    Background Iatrogenic keratectasia is one of the most dreaded complications of refractive surgery. In most cases, keratectasia develops after refractive surgery of eyes suffering from subclinical stages of keratoconus with few or no signs. Unfortunately, there has been no reliable procedure for the early detection of keratoconus. In this study, we used binary decision trees (recursive partitioning) to assess their suitability for discrimination between normal eyes and eyes with subclinical keratoconus. Patients and Methods The method of decision tree analysis was compared with discriminant analysis which has shown good results in previous studies. Input data were 32 eyes of 32 patients with newly diagnosed keratoconus in the contralateral eye and preoperative data of 10 eyes of 5 patients with keratectasia after laser in-situ keratomileusis (LASIK). The control group was made up of 245 normal eyes after LASIK and 12-month follow-up without any signs of iatrogenic keratectasia. Results Decision trees gave better accuracy and specificity than did discriminant analysis. The sensitivity of decision trees was lower than the sensitivity of discriminant analysis. Conclusion On the basis of the patient population of this study, decision trees did not prove to be superior to linear discriminant analysis for the detection of subclinical keratoconus. Georg Thieme Verlag KG Stuttgart · New York.

  20. Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

    Science.gov (United States)

    Nasution, D. H.; Bangun, P.; Sitepu, H. R.

    2018-04-01

    In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.

  1. Stakeholder acceptance analysis: Tunable hybrid plasma

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, T.

    1995-12-01

    This report resents evaluations, recommendations, and requirements concerning Tunable Hybrid Plasma (THP) derived from a three-year program of stake holder involvement. THP destroys volatile organic compounds by directing a moderate energy electron beam into a flow of air containing organic contaminants. This report is for technology developers and for those responsible for making decisions about the use of technology to remediate contamination by volatile organic compounds. Stakeholders` perspectives help those responsible for technology deployment make good decisions concerning the acceptability and applicability of THP to the remediation problems the face. In addition, this report presents data requirements for the technology`s field demonstration defined by stakeholders associated with the Hanford site in Washington State, as well as detailed comments on THP from stakeholders from four other sites throughout the western United States.

  2. Stakeholder acceptance analysis: Tunable hybrid plasma

    International Nuclear Information System (INIS)

    Peterson, T.

    1995-12-01

    This report resents evaluations, recommendations, and requirements concerning Tunable Hybrid Plasma (THP) derived from a three-year program of stake holder involvement. THP destroys volatile organic compounds by directing a moderate energy electron beam into a flow of air containing organic contaminants. This report is for technology developers and for those responsible for making decisions about the use of technology to remediate contamination by volatile organic compounds. Stakeholders' perspectives help those responsible for technology deployment make good decisions concerning the acceptability and applicability of THP to the remediation problems the face. In addition, this report presents data requirements for the technology's field demonstration defined by stakeholders associated with the Hanford site in Washington State, as well as detailed comments on THP from stakeholders from four other sites throughout the western United States

  3. Global classification of human facial healthy skin using PLS discriminant analysis and clustering analysis.

    Science.gov (United States)

    Guinot, C; Latreille, J; Tenenhaus, M; Malvy, D J

    2001-04-01

    Today's classifications of healthy skin are predominantly based on a very limited number of skin characteristics, such as skin oiliness or susceptibility to sun exposure. The aim of the present analysis was to set up a global classification of healthy facial skin, using mathematical models. This classification is based on clinical, biophysical skin characteristics and self-reported information related to the skin, as well as the results of a theoretical skin classification assessed separately for the frontal and the malar zones of the face. In order to maximize the predictive power of the models with a minimum of variables, the Partial Least Square (PLS) discriminant analysis method was used. The resulting PLS components were subjected to clustering analyses to identify the plausible number of clusters and to group the individuals according to their proximities. Using this approach, four PLS components could be constructed and six clusters were found relevant. So, from the 36 hypothetical combinations of the theoretical skin types classification, we tended to a strengthened six classes proposal. Our data suggest that the association of the PLS discriminant analysis and the clustering methods leads to a valid and simple way to classify healthy human skin and represents a potentially useful tool for cosmetic and dermatological research.

  4. Numerical analysis of stiffener for hybrid drive unite

    Directory of Open Access Journals (Sweden)

    Jakubovičová Lenka

    2018-01-01

    Full Text Available The matter of this article is a stress-strain analysis of hybrid drive prototype unit connected directly to convention Concrete Transit Mixer Gearbox. The unite was developed with intention to do field test on existing convection machines with possibility to use existing interfaces. The hybrid drive unit consists from electric and hydrostatic motor connected through addition mechanical transmission gearbox. The question is if today standard interface is good enough or need additional support a “stiffener”. Two engineering design were analysed. The first one includes using the stiffener to fixate the construction of hybrid drive unite connected to the planetary gear. The second one is without the stiffener. For strain-stress analysis, a finite element software ANSYS Workbench was used.

  5. Hybrid Ventilation with Innovative Heat Recovery—A System Analysis

    Directory of Open Access Journals (Sweden)

    Bengt Hellström

    2013-02-01

    Full Text Available One of the most important factors when low energy houses are built is to have good heat recovery on the ventilation system. However, standard ventilation units use a considerable amount of electricity. This article discusses the consequences on a system level of using hybrid ventilation with heat recovery. The simulation program TRNSYS was used in order to investigate a ventilation system with heat recovery. The system also includes a ground source storage and waste water heat recovery system. The result of the analysis shows that the annual energy gain from ground source storage is limited. However, this is partly a consequence of the fact that the well functioning hybrid ventilation system leaves little room for improvements. The analysis shows that the hybrid ventilation system has potential to be an attractive solution for low energy buildings with a very low need for electrical energy.

  6. Analysis of hybrid energy systems for application in southern Ghana

    International Nuclear Information System (INIS)

    Adaramola, Muyiwa S.; Agelin-Chaab, Martin; Paul, Samuel S.

    2014-01-01

    Highlights: • The option of using hybrid energy for electricity in remote areas of Ghana is examined. • The cost of electricity produced by the hybrid system is found to be $0.281/kW h. • The levelized cost of electricity increase by 9% when the PV price is increased from $3000/kW to $7500/kW. - Abstract: Due to advances in renewable energy technologies and increase in oil price, hybrid renewable energy systems are becoming increasingly attractive for power generation applications in remote areas. This paper presents an economic analysis of the feasibility of utilizing a hybrid energy system consisting of solar, wind and diesel generators for application in remote areas of southern Ghana using levelized cost of electricity (LCOE) and net present cost of the system. The annual daily average solar global radiation at the selected site is 5.4 kW h/m 2 /day and the annual mean wind speed is 5.11 m/s. The National Renewable Energy Laboratory’s Hybrid Optimization Model for Electric Renewable (HOMER) software was employed to carry out the present study. Both wind data and the actual load data have been used in the simulation model. It was found that a PV array of 80 kW, a 100 kW wind turbine, two generators with combined capacity of 100 kW, a 60 kW converter/inverter and a 60 Surrette 4KS25P battery produced a mix of 791.1 MW h of electricity annually. The cost of electricity for this hybrid system is found to be $0.281/kW h. Sensitivity analysis on the effect of changes in wind speed, solar global radiation and diesel price on the optimal energy was investigated and the impact of solar PV price on the LCOE for a selected hybrid energy system was also presented

  7. Mars Hybrid Propulsion System Trajectory Analysis. Part I; Crew Missions

    Science.gov (United States)

    Chai, Patrick R.; Merrill, Raymond G.; Qu, Min

    2015-01-01

    NASAs Human spaceflight Architecture team is developing a reusable hybrid transportation architecture in which both chemical and electric propulsion systems are used to send crew and cargo to Mars destinations such as Phobos, Deimos, the surface of Mars, and other orbits around Mars. By combining chemical and electrical propulsion into a single space- ship and applying each where it is more effective, the hybrid architecture enables a series of Mars trajectories that are more fuel-efficient than an all chemical architecture without significant increases in flight times. This paper provides the analysis of the interplanetary segments of the three Evolvable Mars Campaign crew missions to Mars using the hybrid transportation architecture. The trajectory analysis provides departure and arrival dates and propellant needs for the three crew missions that are used by the campaign analysis team for campaign build-up and logistics aggregation analysis. Sensitivity analyses were performed to investigate the impact of mass growth, departure window, and propulsion system performance on the hybrid transportation architecture. The results and system analysis from this paper contribute to analyses of the other human spaceflight architecture team tasks and feed into the definition of the Evolvable Mars Campaign.

  8. Modelling and analysis of real-time and hybrid systems

    Energy Technology Data Exchange (ETDEWEB)

    Olivero, A

    1994-09-29

    This work deals with the modelling and analysis of real-time and hybrid systems. We first present the timed-graphs as model for the real-time systems and we recall the basic notions of the analysis of real-time systems. We describe the temporal properties on the timed-graphs using TCTL formulas. We consider two methods for property verification: in one hand we study the symbolic model-checking (based on backward analysis) and in the other hand we propose a verification method derived of the construction of the simulation graph (based on forward analysis). Both methods have been implemented within the KRONOS verification tool. Their application for the automatic verification on several real-time systems confirms the practical interest of our approach. In a second part we study the hybrid systems, systems combining discrete components with continuous ones. As in the general case the analysis of this king of systems is not decidable, we identify two sub-classes of hybrid systems and we give a construction based method for the generation of a timed-graph from an element into the sub-classes. We prove that in one case the timed-graph obtained is bi-similar with the considered system and that there exists a simulation in the other case. These relationships allow the application of the described technics on the hybrid systems into the defined sub-classes. (authors). 60 refs., 43 figs., 8 tabs., 2 annexes.

  9. Optical selection of trace elements for discriminant analysis

    International Nuclear Information System (INIS)

    Rasmussen, S.E.; Erasmus, C.S.; Watterson, J.I.W.; Sellschop, J.P.F.

    This report describes different methods of element selection; a combination of stepwise multivariate analysis of variance for primary element selection, and principle component analysis regression for the element interrelationship analysis. These offer a satisfactory solution to the problem of element selection

  10. Stock discrimination in Great Lakes Walleye using mitochondrial DNA restriction analysis

    International Nuclear Information System (INIS)

    Billington, N.; Hebert, P.D.N.

    1986-01-01

    Over the past two years it has become evident that because of its strict maternal inheritance and rapid rate of evolutionary differentiation, mitochondrial (mt) DNA diversity offers exceptional promise in the discrimination of fish stocks. The current project aims to determine the extent of mt DNA variation among stocks of walleye (Stizostedion vitreum) from the Great Lakes. At this point, mt DNA has been isolated from 68 walleye representing the Thames River stock and a reef breeding stock from western Lake Erie, as well as from individuals of S. canadense, a species which hybridizes with S. vitreum. Mitochondrial DNA was extracted from livers of these fish, purified by CsCl density gradient centrifugation and digested using 20 endonucleases. Polymorphisms were detected with 8 of the enzymes. There was a great deal of variation among fish from both spawning populations, so much so that individual fish could be identified by this technique. No single enzyme allowed discrimination of the two stocks, but restriction pattern variation following Dde I digestion permitted separation of 50% of Lake Erie fish from Thames River stock. Comparison of mt DNA restriction patterns of walleye and sauger showed that two species are easily separable, setting the stage for a more detailed study of hybridization between the taxa

  11. Sizing Analysis for Aircraft Utilizing Hybrid-Electric Propulsion Systems

    Science.gov (United States)

    2011-03-18

    world, the paragon of animals -William Shakespeare I would not have made it this far without the love and support of my parents. Their work-ethic...xiii  I.  Introduction ...Condition 1 SIZING ANALYSIS FOR AIRCRAFT UTILIZING HYBRID- ELECTRIC PROPULSION SYSTEMS I. Introduction 1. Background Physically

  12. Nuclear-Renewable Hybrid Energy System Market Analysis Plans

    Energy Technology Data Exchange (ETDEWEB)

    Ruth, Mark

    2016-06-09

    This presentation describes nuclear-renewable hybrid energy systems (N-R HESs), states their potential benefits, provides figures for the four tightly coupled N-R HESs that NREL is currently analyzing, and outlines the analysis process that is underway.

  13. Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

    Directory of Open Access Journals (Sweden)

    Laszlo Papp

    2018-06-01

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

  14. Meta-analysis of field experiments shows no change in racial discrimination in hiring over time.

    Science.gov (United States)

    Quillian, Lincoln; Pager, Devah; Hexel, Ole; Midtbøen, Arnfinn H

    2017-10-10

    This study investigates change over time in the level of hiring discrimination in US labor markets. We perform a meta-analysis of every available field experiment of hiring discrimination against African Americans or Latinos ( n = 28). Together, these studies represent 55,842 applications submitted for 26,326 positions. We focus on trends since 1989 ( n = 24 studies), when field experiments became more common and improved methodologically. Since 1989, whites receive on average 36% more callbacks than African Americans, and 24% more callbacks than Latinos. We observe no change in the level of hiring discrimination against African Americans over the past 25 years, although we find modest evidence of a decline in discrimination against Latinos. Accounting for applicant education, applicant gender, study method, occupational groups, and local labor market conditions does little to alter this result. Contrary to claims of declining discrimination in American society, our estimates suggest that levels of discrimination remain largely unchanged, at least at the point of hire.

  15. L1-norm kernel discriminant analysis via Bayes error bound optimization for robust feature extraction.

    Science.gov (United States)

    Zheng, Wenming; Lin, Zhouchen; Wang, Haixian

    2014-04-01

    A novel discriminant analysis criterion is derived in this paper under the theoretical framework of Bayes optimality. In contrast to the conventional Fisher's discriminant criterion, the major novelty of the proposed one is the use of L1 norm rather than L2 norm, which makes it less sensitive to the outliers. With the L1-norm discriminant criterion, we propose a new linear discriminant analysis (L1-LDA) method for linear feature extraction problem. To solve the L1-LDA optimization problem, we propose an efficient iterative algorithm, in which a novel surrogate convex function is introduced such that the optimization problem in each iteration is to simply solve a convex programming problem and a close-form solution is guaranteed to this problem. Moreover, we also generalize the L1-LDA method to deal with the nonlinear robust feature extraction problems via the use of kernel trick, and hereafter proposed the L1-norm kernel discriminant analysis (L1-KDA) method. Extensive experiments on simulated and real data sets are conducted to evaluate the effectiveness of the proposed method in comparing with the state-of-the-art methods.

  16. Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

    Science.gov (United States)

    Cao, Longlong; Guo, Shuixia; Xue, Zhimin; Hu, Yong; Liu, Haihong; Mwansisya, Tumbwene E; Pu, Weidan; Yang, Bo; Liu, Chang; Feng, Jianfeng; Chen, Eric Y H; Liu, Zhening

    2014-02-01

    Aberrant brain functional connectivity patterns have been reported in major depressive disorder (MDD). It is unknown whether they can be used in discriminant analysis for diagnosis of MDD. In the present study we examined the efficiency of discriminant analysis of MDD by individualized computer-assisted diagnosis. Based on resting-state functional magnetic resonance imaging data, a new approach was adopted to investigate functional connectivity changes in 39 MDD patients and 37 well-matched healthy controls. By using the proposed feature selection method, we identified significant altered functional connections in patients. They were subsequently applied to our analysis as discriminant features using a support vector machine classification method. Furthermore, the relative contribution of functional connectivity was estimated. After subset selection of high-dimension features, the support vector machine classifier reached up to approximately 84% with leave-one-out training during the discrimination process. Through summarizing the classification contribution of functional connectivities, we obtained four obvious contribution modules: inferior orbitofrontal module, supramarginal gyrus module, inferior parietal lobule-posterior cingulated gyrus module and middle temporal gyrus-inferior temporal gyrus module. The experimental results demonstrated that the proposed method is effective in discriminating MDD patients from healthy controls. Functional connectivities might be useful as new biomarkers to assist clinicians in computer auxiliary diagnosis of MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

  17. Performance analysis of a photovoltaic-thermochemical hybrid system prototype

    International Nuclear Information System (INIS)

    Li, Wenjia; Ling, Yunyi; Liu, Xiangxin; Hao, Yong

    2017-01-01

    Highlights: •A modular photovoltaic-thermochemical hybrid system prototype is proposed. •Net solar-electric efficiency up to 41% is achievable. •Stable solar power supply is achievable via convenient energy storage. •The modular design facilitates the scalability of the hybrid system. -- Abstract: A solar photovoltaic (PV) thermochemical hybrid system consisting of a point-focus Fresnel concentrator, a PV cell and a methanol thermochemical reactor is proposed. In particular, a reactor capable of operating under high solar concentration is designed, manufactured and tested. Studies on both kinetic and thermodynamic characteristics of the reactor and the system are performed. Analysis of numerical and experimental results shows that with cascaded solar energy utilization and synergy among different forms of energy, the hybrid system has the advantages of high net solar-electric efficiency (up to 41%), stable solar energy power supply, solar energy storage (via syngas) and flexibility in application scale. The hybrid system proposed in this work provides a potential solution to some key challenges of current solar energy utilization technologies.

  18. Proteomic Analysis of Pachytene Spermatocytes of Sterile Hybrid Male Mice.

    Science.gov (United States)

    Wang, Lu; Guo, Yueshuai; Liu, Wenjing; Zhao, Weidong; Song, Gendi; Zhou, Tao; Huang, Hefeng; Guo, Xuejiang; Sun, Fei

    2016-09-01

    Incompatibilities in interspecific hybrids, such as reduced hybrid fertility and lethality, are common features resulting from reproductive isolation that lead to speciation. Subspecies crosses of house mice produce offspring in which one sex is infertile or absent, yet the molecular mechanisms of hybrid sterility are poorly understood. In this study, we observed extensive asynapsis of chromosomes and disturbance of the sex body in pachytene spermatocytes of sterile F1 males (PWK/Ph female × C57BL/6J male). We report the high-confidence identification of 4005 proteins in the pachytene spermatocytes of fertile F1 males (PWK/Ph male × C57BL/6J female) and sterile F1 males (PWK/Ph female × C57BL/6J male), of which 215 were upregulated and 381 were downregulated. Bioinformatics analysis of the proteome led to the identification of 43 and 59 proteins known to be essential for male meiosis and spermatogenesis in mice, respectively. Characterization of the proteome of pachytene spermatocytes associated with hybrid male sterility provides an inventory of proteins that is useful for understanding meiosis and the mechanisms of hybrid male infertility. © 2016 by the Society for the Study of Reproduction, Inc.

  19. Hybrid vehicle assessment. Phase 1: Petroleum savings analysis

    Science.gov (United States)

    Levin, R.; Liddle, S.; Deshpande, G.; Trummel, M.; Vivian, H. C.

    1984-01-01

    The results of a comprehensive analysis of near term electric hybrid vehicles are presented, with emphasis on their potential to save significant amounts of petroleum on a national scale in the 1990s. Performance requirements and expected annual usage patterns of these vehicles are first modeled. The projected U.S. fleet composition is estimated, and conceptual hybrid vehicle designs are conceived and analyzed for petroleum use when driven in the expected annual patterns. These petroleum consumption estimates are then compared to similar estimates for projected 1990 conventional vehicles having the same performance and driven in the same patterns. Results are presented in the form of three utility functions and comparisons of sevral conceptual designs are made. The Hybrid Vehicle (HV) design and assessment techniques are discussed and a general method is explained for selecting the optimum energy management strategy for any vehicle mission battery combination. Conclusions and recommendations are presented, and development recommendations are identified.

  20. On the difficulties of discriminating between major and minor hybrid male sterility factors in Drosophila by examining the segregation ratio of sterile and fertile sons in backcrossing experiments.

    Science.gov (United States)

    Maside, X R; Naveira, H F

    1996-10-01

    The observation of segregation ratios of sterile and fertile males in offspring samples from backcrossed hybrid females is, in principle, a valid method to unveil the genetic basis of hybrid male sterility in Drosophila. When the female parent is heterozygous (hybrid) for a sterility factor with major effects, equal proportions of fertile and sterile sons are expected in her offspring. However, intact (not recombined) chromosome segments of considerable length are expected to give segregation ratios that can not be easily differentiated from the 1:1 ratio expected from a single factor. When the phenotypic character under analysis can be determined by combinations of minor factors from the donor species spanning a certain chromosome length, very large offspring samples may be needed to test this alternative hypothesis against the null hypothesis of a single major factor. This is particularly the case of hybrid male sterility determinants in Drosophila.

  1. Harmonic analysis and suppression in hybrid wind & PV solar system

    Science.gov (United States)

    Gupta, Tripti; Namekar, Swapnil

    2018-04-01

    The growing demand of electricity has led to produce power through non-conventional source of energy such as solar energy, wind energy, hydro power, energy through biogas and biomass etc. Hybrid system is taken to complement the shortcoming of either sources of energy. The proposed system is grid connected hybrid wind and solar system. A 2.1 MW Doubly fed Induction Generator (DFIG) has been taken for analysis of wind farm whose rotor part is connected to two back-to-back converters. A 250 KW Photovoltaic (PV) array taken to analyze solar farm where inverter is required to convert power from DC to AC since electricity generated through solar PV is in the form of DC. Stability and reliability of the system is very important when the system is grid connected. Harmonics is the major Power quality issue which degrades the quality of power at load side. Harmonics in hybrid system arise through the use of power conversion unit. The other causes of harmonics are fluctuation in wind speed and solar irradiance. The power delivered to grid must be free from harmonics and within the limits specified by Indian grid codes. In proposed work, harmonic analysis of the hybrid system is performed in Electrical Transient Analysis program (ETAP) and single tuned harmonic filter is designed to maintain the utility grid harmonics within limits.

  2. Discrimination of whisky brands and counterfeit identification by UV-Vis spectroscopy and multivariate data analysis.

    Science.gov (United States)

    Martins, Angélica Rocha; Talhavini, Márcio; Vieira, Maurício Leite; Zacca, Jorge Jardim; Braga, Jez Willian Batista

    2017-08-15

    The discrimination of whisky brands and counterfeit identification were performed by UV-Vis spectroscopy combined with partial least squares for discriminant analysis (PLS-DA). In the proposed method all spectra were obtained with no sample preparation. The discrimination models were built with the employment of seven whisky brands: Red Label, Black Label, White Horse, Chivas Regal (12years), Ballantine's Finest, Old Parr and Natu Nobilis. The method was validated with an independent test set of authentic samples belonging to the seven selected brands and another eleven brands not included in the training samples. Furthermore, seventy-three counterfeit samples were also used to validate the method. Results showed correct classification rates for genuine and false samples over 98.6% and 93.1%, respectively, indicating that the method can be helpful for the forensic analysis of whisky samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Identification of roselle varieties through simple discriminating physicochemical characteristics using multivariate analysis

    Directory of Open Access Journals (Sweden)

    Alé KANE

    2018-01-01

    Full Text Available Abstract The objective of this work is to study the feasibility of a more objective and rigorous classification of the calices of Hibiscus sabdariffa based on their physicochemical profile. To do so, 19 analyses were carried out on 4 varieties of calices cultivated in Senegal: Vimto, Koor, Thaï and CLT92. Principal component analysis results showed that 15 physicochemical and biochemical parameters could be potentially used to discriminate the varieties of calices. Polyphenolic and anthocyanin contents were anti-correlated to protein content and could be used to differentiate the Vimto/CLT92 and the Koor/Thaï varieties. Within these two clusters, pH and lipid content could discriminate each variety. Finally, factorial discriminant analysis showed that total anthocyanin content, lipid content and chromaticity C* were the 3 parameters enabling the most efficient classification of calices according to variety and led to 100% classification accuracy.

  4. Sub-pattern based multi-manifold discriminant analysis for face recognition

    Science.gov (United States)

    Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

    2018-04-01

    In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

  5. Feature extraction with deep neural networks by a generalized discriminant analysis.

    Science.gov (United States)

    Stuhlsatz, André; Lippel, Jens; Zielke, Thomas

    2012-04-01

    We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used.

  6. Combined approach based on principal component analysis and canonical discriminant analysis for investigating hyperspectral plant response

    Directory of Open Access Journals (Sweden)

    Anna Maria Stellacci

    2012-07-01

    Full Text Available Hyperspectral (HS data represents an extremely powerful means for rapidly detecting crop stress and then aiding in the rational management of natural resources in agriculture. However, large volume of data poses a challenge for data processing and extracting crucial information. Multivariate statistical techniques can play a key role in the analysis of HS data, as they may allow to both eliminate redundant information and identify synthetic indices which maximize differences among levels of stress. In this paper we propose an integrated approach, based on the combined use of Principal Component Analysis (PCA and Canonical Discriminant Analysis (CDA, to investigate HS plant response and discriminate plant status. The approach was preliminary evaluated on a data set collected on durum wheat plants grown under different nitrogen (N stress levels. Hyperspectral measurements were performed at anthesis through a high resolution field spectroradiometer, ASD FieldSpec HandHeld, covering the 325-1075 nm region. Reflectance data were first restricted to the interval 510-1000 nm and then divided into five bands of the electromagnetic spectrum [green: 510-580 nm; yellow: 581-630 nm; red: 631-690 nm; red-edge: 705-770 nm; near-infrared (NIR: 771-1000 nm]. PCA was applied to each spectral interval. CDA was performed on the extracted components to identify the factors maximizing the differences among plants fertilised with increasing N rates. Within the intervals of green, yellow and red only the first principal component (PC had an eigenvalue greater than 1 and explained more than 95% of total variance; within the ranges of red-edge and NIR, the first two PCs had an eigenvalue higher than 1. Two canonical variables explained cumulatively more than 81% of total variance and the first was able to discriminate wheat plants differently fertilised, as confirmed also by the significant correlation with aboveground biomass and grain yield parameters. The combined

  7. Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes.

    Science.gov (United States)

    De Luca, Michele; Restuccia, Donatella; Clodoveo, Maria Lisa; Puoci, Francesco; Ragno, Gaetano

    2016-07-01

    Chemometric discrimination of extra virgin olive oils (EVOO) from whole and stoned olive pastes was carried out by using Fourier transform infrared (FTIR) data and partial least squares-discriminant analysis (PLS1-DA) approach. Four Italian commercial EVOO brands, all in both whole and stoned version, were considered in this study. The adopted chemometric methodologies were able to describe the different chemical features in phenolic and volatile compounds contained in the two types of oil by using unspecific IR spectral information. Principal component analysis (PCA) was employed in cluster analysis to capture data patterns and to highlight differences between technological processes and EVOO brands. The PLS1-DA algorithm was used as supervised discriminant analysis to identify the different oil extraction procedures. Discriminant analysis was extended to the evaluation of possible adulteration by addition of aliquots of oil from whole paste to the most valuable oil from stoned olives. The statistical parameters from external validation of all the PLS models were very satisfactory, with low root mean square error of prediction (RMSEP) and relative error (RE%). Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. linear discriminant analysis of structure within african eggplant 'shum'

    African Journals Online (AJOL)

    ACSS

    observed clusters include petiole length, sepal length (or seed color), fruit calyx length, seeds per fruit, leaf fresh .... obtain means. A table of means per trait for each accession was then imported into R statistical software for UPGMA reordered hierarchical cluster analysis. ..... Mwale, S.E., Ssemakula, M.O., Sadik, K.,.

  9. Use of linear discriminant function analysis in seed morphotype ...

    African Journals Online (AJOL)

    Variation in seed morphology of the Lima bean in 31 accessions was studied. Data were collected on 100-seed weight, seed length and seed width. The differences among the accessions were significant, based on the three seed characteristics. K-means cluster analysis grouped the 31 accessions into four distinct groups, ...

  10. Use of Linear Discriminant Function Analysis in Five Yield Sub ...

    African Journals Online (AJOL)

    K-means cluster analysis grouped the 134 accessions into four distinct groups. Pairwise Mahalanobis 2 distance (D) among some of the groups was highly significant. From the study the yield sub-characters pod length, pod width, peduncle length and 100-seed weight contributed most to group separation in the cowpea ...

  11. Harassment and discrimination in medical training: a systematic review and meta-analysis.

    Science.gov (United States)

    Fnais, Naif; Soobiah, Charlene; Chen, Maggie Hong; Lillie, Erin; Perrier, Laure; Tashkhandi, Mariam; Straus, Sharon E; Mamdani, Muhammad; Al-Omran, Mohammed; Tricco, Andrea C

    2014-05-01

    Harassment and discrimination include a wide range of behaviors that medical trainees perceive as being humiliating, hostile, or abusive. To understand the significance of such mistreatment and to explore potential preventive strategies, the authors conducted a systematic review and meta-analysis to examine the prevalence, risk factors, and sources of harassment and discrimination among medical trainees. In 2011, the authors identified relevant studies by searching MEDLINE and EMBASE, scanning reference lists of relevant studies, and contacting experts. They included studies that reported the prevalence, risk factors, and sources of harassment and discrimination among medical trainees. Two reviewers independently screened all articles and abstracted study and participant characteristics and study results. The authors assessed the methodological quality in individual studies using the Newcastle-Ottawa Scale. They also conducted a meta-analysis. The authors included 57 cross-sectional and 2 cohort studies in their review. The meta-analysis of 51 studies demonstrated that 59.4% of medical trainees had experienced at least one form of harassment or discrimination during their training (95% confidence interval [CI]: 52.0%-66.7%). Verbal harassment was the most commonly cited form of harassment (prevalence: 63.0%; 95% CI: 54.8%-71.2%). Consultants were the most commonly cited source of harassment and discrimination, followed by patients or patients' families (34.4% and 21.9%, respectively). This review demonstrates the surprisingly high prevalence of harassment and discrimination among medical trainees that has not declined over time. The authors recommend both drafting policies and promoting cultural change within academic institutions to prevent future abuse.

  12. Use of discriminant analysis to determine black shales of the Lesser Carpathian crystal field

    Energy Technology Data Exchange (ETDEWEB)

    Khun, M.

    1980-01-01

    Discriminant analysis of results from geochemical testing was used to separate black shales of the ore level from the nonproductive deposits. Based on a large number of experiments, the accuracy of isolating the black shales according to content of vandium, copper and nickel reached 78%. These elements have basic importance for separation of productive shales from nonproductive.

  13. Comparison of cranial sex determination by discriminant analysis and logistic regression.

    Science.gov (United States)

    Amores-Ampuero, Anabel; Alemán, Inmaculada

    2016-04-05

    Various methods have been proposed for estimating dimorphism. The objective of this study was to compare sex determination results from cranial measurements using discriminant analysis or logistic regression. The study sample comprised 130 individuals (70 males) of known sex, age, and cause of death from San José cemetery in Granada (Spain). Measurements of 19 neurocranial dimensions and 11 splanchnocranial dimensions were subjected to discriminant analysis and logistic regression, and the percentages of correct classification were compared between the sex functions obtained with each method. The discriminant capacity of the selected variables was evaluated with a cross-validation procedure. The percentage accuracy with discriminant analysis was 78.2% for the neurocranium (82.4% in females and 74.6% in males) and 73.7% for the splanchnocranium (79.6% in females and 68.8% in males). These percentages were higher with logistic regression analysis: 85.7% for the neurocranium (in both sexes) and 94.1% for the splanchnocranium (100% in females and 91.7% in males).

  14. Discrimination of bromodeoxyuridine labelled and unlabelled mitotic cells in flow cytometric bromodeoxyuridine/DNA analysis

    DEFF Research Database (Denmark)

    Jensen, P O; Larsen, J K; Christensen, I J

    1994-01-01

    Bromodeoxyuridine (BrdUrd) labelled and unlabelled mitotic cells, respectively, can be discriminated from interphase cells using a new method, based on immunocytochemical staining of BrdUrd and flow cytometric four-parameter analysis of DNA content, BrdUrd incorporation, and forward and orthogona...

  15. Development and Validation of Discriminant Analysis Models for Student Loan Defaultees and Non-Defaultees.

    Science.gov (United States)

    Myers, Greeley; Siera, Steven

    1980-01-01

    Default on guaranteed student loans has been increasing. The use of discriminant analysis as a technique to identify "good" v "bad" student loans based on information available from the loan application is discussed. Research to test the ability of models to such predictions is reported. (Author/MLW)

  16. An Application of Discriminant Analysis to Pattern Recognition of Selected Contaminated Soil Features in Thin Sections

    DEFF Research Database (Denmark)

    Ribeiro, Alexandra B.; Nielsen, Allan Aasbjerg

    1997-01-01

    qualitative microprobe results: present elements Al, Si, Cr, Fe, As (associated with others). Selected groups of calibrated images (same light conditions and magnification) submitted to discriminant analysis, in order to find a pattern of recognition in the soil features corresponding to contamination already...

  17. Prediction Model of Collapse Risk Based on Information Entropy and Distance Discriminant Analysis Method

    Directory of Open Access Journals (Sweden)

    Hujun He

    2017-01-01

    Full Text Available The prediction and risk classification of collapse is an important issue in the process of highway construction in mountainous regions. Based on the principles of information entropy and Mahalanobis distance discriminant analysis, we have produced a collapse hazard prediction model. We used the entropy measure method to reduce the influence indexes of the collapse activity and extracted the nine main indexes affecting collapse activity as the discriminant factors of the distance discriminant analysis model (i.e., slope shape, aspect, gradient, and height, along with exposure of the structural face, stratum lithology, relationship between weakness face and free face, vegetation cover rate, and degree of rock weathering. We employ postearthquake collapse data in relation to construction of the Yingxiu-Wolong highway, Hanchuan County, China, as training samples for analysis. The results were analyzed using the back substitution estimation method, showing high accuracy and no errors, and were the same as the prediction result of uncertainty measure. Results show that the classification model based on information entropy and distance discriminant analysis achieves the purpose of index optimization and has excellent performance, high prediction accuracy, and a zero false-positive rate. The model can be used as a tool for future evaluation of collapse risk.

  18. A Comparative Analysis of the Evolution of Gender Wage Discrimination: Spain Versus Galicia

    OpenAIRE

    Pena-Boquete, Yolanda

    2006-01-01

    The aim of this paper is to analyze the degree of female wage discrimination in the Spanish region of Galicia relative to the rest of Spain. The analysis starts from an established fact: women's average earnings are lower than men's. First, we try to show the causes behind this wage differential. Next, we discuss the evolution of the wage gap between 1995 and 2002, in order to bring some light on the factors potentially accounting for wage discrimination persistence in Galicia and Spain. We w...

  19. A Comparative Analysis of the Evolution of Gender Wage Discrimination: Spain Versus Galicia.

    OpenAIRE

    Yolanda Pena-Boquete

    2006-01-01

    The aim of this paper is to analyze the degree of female wage discrimination in the Spanish region of Galicia relative to the rest of Spain. The analysis starts from an established fact: women’s average earnings are lower than men’s. First, we try to show the causes behind this wage differential. Next, we discuss the evolution of the wage gap between 1995 and 2002, in order to bring some light on the factors potentially accounting for wage discrimination persistence in Galicia and Spain. We w...

  20. Sensitivity analysis of hybrid thermoelastic techniques

    Science.gov (United States)

    W.A. Samad; J.M. Considine

    2017-01-01

    Stress functions have been used as a complementary tool to support experimental techniques, such as thermoelastic stress analysis (TSA) and digital image correlation (DIC), in an effort to evaluate the complete and separate full-field stresses of loaded structures. The need for such coupling between experimental data and stress functions is due to the fact that...

  1. Baseline drift effect on the performance of neutron and γ ray discrimination using frequency gradient analysis

    International Nuclear Information System (INIS)

    Liu Guofu; Luo Xiaoliang; Yang Jun; Lin Cunbao; Hu Qingqing; Peng Jinxian

    2013-01-01

    Frequency gradient analysis (FGA) effectively discriminates neutrons and γ rays by examining the frequency-domain features of the photomultiplier tube anode signal. This approach is insensitive to noise but is inevitably affected by the baseline drift similar to other pulse shape discrimination methods. The baseline drift effect is attributed to factors such as power line fluctuation, dark current, noise disturbances, hum, and pulse tail in front-end electronics. This effect needs to be elucidated and quantified before the baseline shift can be estimated and removed from the captured signal. Therefore, the effect of baseline shift on the discrimination performance of neutrons and γ rays with organic scintillation detectors using FGA is investigated in this paper. The relationship between the baseline shift and discrimination parameters of FGA is derived and verified by an experimental system consisting of an americium—beryllium source, a BC501A liquid scintillator detector, and a 5 GSample/s 8-bit oscilloscope. The theoretical and experimental results both show that the estimation of the baseline shift is necessary, and the removal of baseline drift from the pulse shapes can improve the discrimination performance of FGA. (authors)

  2. Discrimination of Temperature and Strain in Brillouin Optical Time Domain Analysis Using a Multicore Optical Fiber.

    Science.gov (United States)

    Zaghloul, Mohamed A S; Wang, Mohan; Milione, Giovanni; Li, Ming-Jun; Li, Shenping; Huang, Yue-Kai; Wang, Ting; Chen, Kevin P

    2018-04-12

    Brillouin optical time domain analysis is the sensing of temperature and strain changes along an optical fiber by measuring the frequency shift changes of Brillouin backscattering. Because frequency shift changes are a linear combination of temperature and strain changes, their discrimination is a challenge. Here, a multicore optical fiber that has two cores is fabricated. The differences between the cores' temperature and strain coefficients are such that temperature (strain) changes can be discriminated with error amplification factors of 4.57 °C/MHz (69.11 μ ϵ /MHz), which is 2.63 (3.67) times lower than previously demonstrated. As proof of principle, using the multicore optical fiber and a commercial Brillouin optical time domain analyzer, the temperature (strain) changes of a thermally expanding metal cylinder are discriminated with an error of 0.24% (3.7%).

  3. Discrimination of Temperature and Strain in Brillouin Optical Time Domain Analysis Using a Multicore Optical Fiber

    Directory of Open Access Journals (Sweden)

    Mohamed A. S. Zaghloul

    2018-04-01

    Full Text Available Brillouin optical time domain analysis is the sensing of temperature and strain changes along an optical fiber by measuring the frequency shift changes of Brillouin backscattering. Because frequency shift changes are a linear combination of temperature and strain changes, their discrimination is a challenge. Here, a multicore optical fiber that has two cores is fabricated. The differences between the cores’ temperature and strain coefficients are such that temperature (strain changes can be discriminated with error amplification factors of 4.57 °C/MHz (69.11 μ ϵ /MHz, which is 2.63 (3.67 times lower than previously demonstrated. As proof of principle, using the multicore optical fiber and a commercial Brillouin optical time domain analyzer, the temperature (strain changes of a thermally expanding metal cylinder are discriminated with an error of 0.24% (3.7%.

  4. Applicability of supervised discriminant analysis models to analyze astigmatism clinical trial data.

    Science.gov (United States)

    Sedghipour, Mohammad Reza; Sadeghi-Bazargani, Homayoun

    2012-01-01

    In astigmatism clinical trials where more complex measurements are common, especially in nonrandomized small sized clinical trials, there is a demand for the development and application of newer statistical methods. The source data belonged to a project on astigmatism treatment. Data were used regarding a total of 296 eyes undergoing different astigmatism treatment modalities: wavefront-guided photorefractive keratectomy, cross-cylinder photorefractive keratectomy, and monotoric (single) photorefractive keratectomy. Astigmatism analysis was primarily done using the Alpins method. Prior to fitting partial least squares regression discriminant analysis, a preliminary principal component analysis was done for data overview. Through fitting the partial least squares regression discriminant analysis statistical method, various model validity and predictability measures were assessed. The model found the patients treated by the wavefront method to be different from the two other treatments both in baseline and outcome measures. Also, the model found that patients treated with the cross-cylinder method versus the single method didn't appear to be different from each other. This analysis provided an opportunity to compare the three methods while including a substantial number of baseline and outcome variables. Partial least squares regression discriminant analysis had applicability for the statistical analysis of astigmatism clinical trials and it may be used as an adjunct or alternative analysis method in small sized clinical trials.

  5. Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Jongguk Lim

    2017-09-01

    Full Text Available The purpose of this study is to use near-infrared reflectance (NIR spectroscopy equipment to nondestructively and rapidly discriminate Fusarium-infected hulled barley. Both normal hulled barley and Fusarium-infected hulled barley were scanned by using a NIR spectrometer with a wavelength range of 1175 to 2170 nm. Multiple mathematical pretreatments were applied to the reflectance spectra obtained for Fusarium discrimination and the multivariate analysis method of partial least squares discriminant analysis (PLS-DA was used for discriminant prediction. The PLS-DA prediction model developed by applying the second-order derivative pretreatment to the reflectance spectra obtained from the side of hulled barley without crease achieved 100% accuracy in discriminating the normal hulled barley and the Fusarium-infected hulled barley. These results demonstrated the feasibility of rapid discrimination of the Fusarium-infected hulled barley by combining multivariate analysis with the NIR spectroscopic technique, which is utilized as a nondestructive detection method.

  6. Fuel cell hybrid taxi life cycle analysis

    Energy Technology Data Exchange (ETDEWEB)

    Baptista, Patricia, E-mail: patricia.baptista@ist.utl.pt [IDMEC-Instituto Superior Tecnico, Universidade Tecnica de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa (Portugal); Ribau, Joao; Bravo, Joao; Silva, Carla [IDMEC-Instituto Superior Tecnico, Universidade Tecnica de Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa (Portugal); Adcock, Paul; Kells, Ashley [Intelligent Energy, Charnwood Building, HolywellPark, Ashby Road, Loughborough, LE11 3GR (United Kingdom)

    2011-09-15

    A small fleet of classic London Taxis (Black cabs) equipped with hydrogen fuel cell power systems is being prepared for demonstration during the 2012 London Olympics. This paper presents a Life Cycle Analysis for these vehicles in terms of energy consumption and CO{sub 2} emissions, focusing on the impacts of alternative vehicle technologies for the Taxi, combining the fuel life cycle (Tank-to-Wheel and Well-to-Tank) and vehicle materials Cradle-to-Grave. An internal combustion engine diesel taxi was used as the reference vehicle for the currently available technology. This is compared to battery and fuel cell vehicle configurations. Accordingly, the following energy pathways are compared: diesel, electricity and hydrogen (derived from natural gas steam reforming). Full Life Cycle Analysis, using the PCO-CENEX drive cycle, (derived from actual London Taxi drive cycles) shows that the fuel cell powered vehicle configurations have lower energy consumption (4.34 MJ/km) and CO{sub 2} emissions (235 g/km) than both the ICE Diesel (9.54 MJ/km and 738 g/km) and the battery electric vehicle (5.81 MJ/km and 269 g/km). - Highlights: > A Life Cycle Analysis of alternative vehicle technologies for the London Taxi was performed. > The hydrogen powered vehicles have the lowest energy consumption and CO{sub 2} emissions results. > A hydrogen powered solution can be a sustainable alternative in a full life cycle framework.

  7. Fuel cell hybrid taxi life cycle analysis

    International Nuclear Information System (INIS)

    Baptista, Patricia; Ribau, Joao; Bravo, Joao; Silva, Carla; Adcock, Paul; Kells, Ashley

    2011-01-01

    A small fleet of classic London Taxis (Black cabs) equipped with hydrogen fuel cell power systems is being prepared for demonstration during the 2012 London Olympics. This paper presents a Life Cycle Analysis for these vehicles in terms of energy consumption and CO 2 emissions, focusing on the impacts of alternative vehicle technologies for the Taxi, combining the fuel life cycle (Tank-to-Wheel and Well-to-Tank) and vehicle materials Cradle-to-Grave. An internal combustion engine diesel taxi was used as the reference vehicle for the currently available technology. This is compared to battery and fuel cell vehicle configurations. Accordingly, the following energy pathways are compared: diesel, electricity and hydrogen (derived from natural gas steam reforming). Full Life Cycle Analysis, using the PCO-CENEX drive cycle, (derived from actual London Taxi drive cycles) shows that the fuel cell powered vehicle configurations have lower energy consumption (4.34 MJ/km) and CO 2 emissions (235 g/km) than both the ICE Diesel (9.54 MJ/km and 738 g/km) and the battery electric vehicle (5.81 MJ/km and 269 g/km). - Highlights: → A Life Cycle Analysis of alternative vehicle technologies for the London Taxi was performed. → The hydrogen powered vehicles have the lowest energy consumption and CO 2 emissions results. → A hydrogen powered solution can be a sustainable alternative in a full life cycle framework.

  8. Performance Analysis of a Hybrid Power Cutting System for Roadheader

    Directory of Open Access Journals (Sweden)

    Yang Yang

    2017-01-01

    Full Text Available An electrohydraulic hybrid power cutting transmission system for roadheader under specific working condition was proposed in this paper. The overall model for the new system composed of an electric motor model, a hydraulic pump-motor model, a torsional planetary set model, and a hybrid power train model was established. The working mode characteristics were simulated under the conditions of taking the effect of cutting picks into account. The advantages of new hybrid power cutting system about the dynamic response under shock load were investigated compared with the traditional cutting system. The results illustrated that the hybrid power system had an obvious cushioning in terms of the dynamic load of cutting electric motor and planetary gear set. Besides, the hydraulic motor could provide an auxiliary power to improve the performance of the electric motor. With further analysis, a dynamic load was found to have a high relation to the stiffness and damping of coupling in the transmission train. The results could be a useful guide for the design of cutting transmission of roadheader.

  9. Hybrid vehicle assessment. Phase I. Petroleum savings analysis

    Energy Technology Data Exchange (ETDEWEB)

    Levin, R.; Liddle, S.; Deshpande, G.; Trummel, M.; Vivian, H.

    1984-03-01

    This report presents the results of a comprehensive analysis of near-term electric-hybrid vehicles. Its purpose was to estimate their potential to save significant amounts of petroleum on a national scale in the 1990s. Performance requirements and expected annual usage patterns of these vehicles were first modeled. The projected US fleet composition was estimated, and conceptual hybrid vehicle designs were conceived and analyzed for petroleum use when driven in the expected annual patterns. These petroleum consumption estimates were then compared to similar estimates for projected 1990 conventional vehicles having the same performance and driven in the same patterns. Results are presented in the form of three utility functions and comparisons of several conceptual designs are made. The Hybrid Vehicle (HV) design and assessment techniques are discussed and a general method is explained for selecting the optimum energy management strategy for any vehicle-mission-battery combination. A discussion of lessons learned during the construction and test of the General Electric Hybrid Test Vehicle is also presented. Conclusions and recommendations are presented, and development recommendations are identified.

  10. Going hybrid: An analysis of consumer purchase motivations

    International Nuclear Information System (INIS)

    Ozaki, Ritsuko; Sevastyanova, Katerina

    2011-01-01

    What makes consumers adopt energy-sustainable innovations? The uptake of such products and technologies is of importance, particularly at a time when climate change, diminishing energy resources and energy security are urgent issues. This paper reports on a case study of consumer adoption of hybrid vehicles, a green innovation that has been in the market since the late 1990s. The study is based on a questionnaire survey, conducted in 2009 in collaboration with Toyota GB, to investigate the dimensions that constitute motivations to purchase the Prius and to examine how policy can encourage hybrid adoption. The survey yielded 1484 responses, 1263 of which were used for the analysis; the results of the exploratory factor analyses provide information on consumer purchase motivations. The financial benefits related to transport policy are an important factor in consumer hybrid purchase motivations, and social norms and consumers' willingness to comply with the norms of their groups influence the purchase decision. We also find that various meanings are attached to hybrid vehicle ownership, and practical, experiential and affective values need to be communicated to consumers in terms of value added.

  11. Analysis of a Hybrid Mechanical Regenerative Braking System

    Directory of Open Access Journals (Sweden)

    Toh Xiang Wen Matthew

    2018-01-01

    Full Text Available Regenerative braking systems for conventional vehicles are gaining attention as fossil fuels continue to be depleted. The major forms of regenerative braking systems include electrical and mechanical systems, with the former being more widely adopted at present. However mechanical systems are still feasible, including the possible hybrid systems of two mechanical energy recovery systems. A literature study was made to compare the various mechanical energy recovery systems. These systems were compared based on their advantages and disadvantages with regards to energy storage, usage, and maintenance. Based on the comparison, the most promising concept appeared to be one that combined the flywheel and the pneumatic energy recovery systems. A CAD model of this hybrid system was produced to better visualise the design. This was followed by analytical modelling of the energy recovery systems. The analysis indicated that the angular velocity had an extremely significant impact on the power loss and energy efficiency. The results showed that the hybrid system can provide better efficiency but only when operating within certain parameters. Future work is required to further improve the efficiency of this hybrid system.

  12. Applicability of supervised discriminant analysis models to analyze astigmatism clinical trial data

    Directory of Open Access Journals (Sweden)

    Sedghipour MR

    2012-09-01

    Full Text Available Mohammad Reza Sedghipour,1 Homayoun Sadeghi-Bazargani2,31Nikoukari Ophthalmology University Hospital, Tabriz, Iran; 2Department of Statistics and Epidemiology, Neuroscience Research Center, Tabriz University of Medical Sciences, Tabriz, Iran; 3Department of Public Health Sciences, Karolinska Institute, Stockholm, SwedenBackground: In astigmatism clinical trials where more complex measurements are common, especially in nonrandomized small sized clinical trials, there is a demand for the development and application of newer statistical methods.Methods: The source data belonged to a project on astigmatism treatment. Data were used regarding a total of 296 eyes undergoing different astigmatism treatment modalities: wavefront-guided photorefractive keratectomy, cross-cylinder photorefractive keratectomy, and monotoric (single photorefractive keratectomy. Astigmatism analysis was primarily done using the Alpins method. Prior to fitting partial least squares regression discriminant analysis, a preliminary principal component analysis was done for data overview. Through fitting the partial least squares regression discriminant analysis statistical method, various model validity and predictability measures were assessed.Results: The model found the patients treated by the wavefront method to be different from the two other treatments both in baseline and outcome measures. Also, the model found that patients treated with the cross-cylinder method versus the single method didn't appear to be different from each other. This analysis provided an opportunity to compare the three methods while including a substantial number of baseline and outcome variables.Conclusion: Partial least squares regression discriminant analysis had applicability for the statistical analysis of astigmatism clinical trials and it may be used as an adjunct or alternative analysis method in small sized clinical trials.Keywords: astigmatism, regression, partial least squares regression

  13. Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques.

    Science.gov (United States)

    Tahir, Haroon Elrasheid; Xiaobo, Zou; Xiaowei, Huang; Jiyong, Shi; Mariod, Abdalbasit Adam

    2016-09-01

    Aroma profiles of six honey varieties of different botanical origins were investigated using colorimetric sensor array, gas chromatography-mass spectrometry (GC-MS) and descriptive sensory analysis. Fifty-eight aroma compounds were identified, including 2 norisoprenoids, 5 hydrocarbons, 4 terpenes, 6 phenols, 7 ketones, 9 acids, 12 aldehydes and 13 alcohols. Twenty abundant or active compounds were chosen as key compounds to characterize honey aroma. Discrimination of the honeys was subsequently implemented using multivariate analysis, including hierarchical clustering analysis (HCA) and principal component analysis (PCA). Honeys of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS and colorimetric sensor array were able to discriminate the honeys effectively with the advantages of being rapid, simple and low-cost. Moreover, partial least squares regression (PLSR) was applied to indicate the relationship between sensory descriptors and aroma compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Mammogram CAD, hybrid registration and iconic analysis

    Science.gov (United States)

    Boucher, A.; Cloppet, F.; Vincent, N.

    2013-03-01

    This paper aims to develop a computer aided diagnosis (CAD) based on a two-step methodology to register and analyze pairs of temporal mammograms. The concept of "medical file", including all the previous medical information on a patient, enables joint analysis of different acquisitions taken at different times, and the detection of significant modifications. The developed registration method aims to superimpose at best the different anatomical structures of the breast. The registration is designed in order to get rid of deformation undergone by the acquisition process while preserving those due to breast changes indicative of malignancy. In order to reach this goal, a referent image is computed from control points based on anatomical features that are extracted automatically. Then the second image of the couple is realigned on the referent image, using a coarse-to-fine approach according to expert knowledge that allows both rigid and non-rigid transforms. The joint analysis detects the evolution between two images representing the same scene. In order to achieve this, it is important to know the registration error limits in order to adapt the observation scale. The approach used in this paper is based on an image sparse representation. Decomposed in regular patterns, the images are analyzed under a new angle. The evolution detection problem has many practical applications, especially in medical images. The CAD is evaluated using recall and precision of differences in mammograms.

  15. Variations in students' perceived reasons for, sources of, and forms of in-school discrimination: A latent class analysis.

    Science.gov (United States)

    Byrd, Christy M; Carter Andrews, Dorinda J

    2016-08-01

    Although there exists a healthy body of literature related to discrimination in schools, this research has primarily focused on racial or ethnic discrimination as perceived and experienced by students of color. Few studies examine students' perceptions of discrimination from a variety of sources, such as adults and peers, their descriptions of the discrimination, or the frequency of discrimination in the learning environment. Middle and high school students in a Midwestern school district (N=1468) completed surveys identifying whether they experienced discrimination from seven sources (e.g., peers, teachers, administrators), for seven reasons (e.g., gender, race/ethnicity, religion), and in eight forms (e.g., punished more frequently, called names, excluded from social groups). The sample was 52% White, 15% Black/African American, 14% Multiracial, and 17% Other. Latent class analysis was used to cluster individuals based on reported sources of, reasons for, and forms of discrimination. Four clusters were found, and ANOVAs were used to test for differences between clusters on perceptions of school climate, relationships with teachers, perceptions that the school was a "good school," and engagement. The Low Discrimination cluster experienced the best outcomes, whereas an intersectional cluster experienced the most discrimination and the worst outcomes. The results confirm existing research on the negative effects of discrimination. Additionally, the paper adds to the literature by highlighting the importance of an intersectional approach to examining students' perceptions of in-school discrimination. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  16. Robust hybrid pitch detector for pathologic voice analysis

    OpenAIRE

    Boyanov, B.; Hadjitodorov, S.; Teston, B.; Doskov, D.

    1997-01-01

    International audience; A hybrid speech period (To) detector characterizided by parallel analyses of three speech signals in temporal spectral and cepstral domains and preprocessing for periodic/aperiodic (unvoiced) separation (PAS) is proposed. The preprocessing is realized by analysis in these three domains and PAS by multi layer Perceptron neural network.Two phonations of the wowel "a" of 40 speakers and 62 patients were analyzed. For the proposed detector errors were significantly minimized.

  17. Predicting Insolvency : A comparison between discriminant analysis and logistic regression using principal components

    OpenAIRE

    Geroukis, Asterios; Brorson, Erik

    2014-01-01

    In this study, we compare the two statistical techniques logistic regression and discriminant analysis to see how well they classify companies based on clusters – made from the solvency ratio ­– using principal components as independent variables. The principal components are made with different financial ratios. We use cluster analysis to find groups with low, medium and high solvency ratio of 1200 different companies found on the NASDAQ stock market and use this as an apriori definition of ...

  18. Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

    Science.gov (United States)

    Wen, Zaidao; Hou, Biao; Jiao, Licheng

    2017-05-03

    Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

  19. Discriminant analysis method to determine the power of the boys 11-12 year

    Directory of Open Access Journals (Sweden)

    Mirosława Cieślicka

    2016-10-01

    Full Text Available Purpose: To determine the model of power in boys 11-12 years old. Material and methods: To achieve the objectives, the following methods: analysis of scientific literature, statistical methods for analysis of results. The study involved 35 boys 11 year (n = 35 and 32 boys 12 year (n = 32. Results: Analysis of the results shows that the statistical significance of differences in the test results of boys 11 and 12 years there has been research jump from the place of execution and the amount of squats (the amount of execution time (p <0.001, p <0. Conclusions: Structural factors discriminant function suggest that more attention is paid to training of speed and endurance, the more likely to increase the force to prepare the boys. The canonical discriminant function can  be used to assess and forecast the development of motor skills in boys.

  20. Analysis of pulse-shape discrimination techniques for BC501A using GHz digital signal processing

    International Nuclear Information System (INIS)

    Rooney, B.D.; Dinwiddie, D.R.; Nelson, M.A.; Rawool-Sullivan, Mohini W.

    2001-01-01

    A comparison study of pulse-shape analysis techniques was conducted for a BC501A scintillator using digital signal processing (DSP). In this study, output signals from a preamplifier were input directly into a 1 GHz analog-to-digital converter. The digitized data obtained with this method was post-processed for both pulse-height and pulse-shape information. Several different analysis techniques were evaluated for neutron and gamma-ray pulse-shape discrimination. It was surprising that one of the simplest and fastest techniques resulted in some of the best pulse-shape discrimination results. This technique, referred to here as the Integral Ratio technique, was able to effectively process several thousand detector pulses per second. This paper presents the results and findings of this study for various pulse-shape analysis techniques with digitized detector signals.

  1. Financial consumer protection and customer satisfaction. A relationship study by using factor analysis and discriminant analysis

    Directory of Open Access Journals (Sweden)

    Marimuthu SELVAKUMAR

    2015-11-01

    Full Text Available This paper tries to make an attempt to study the relationship between the financial consumer protection and customer satisfaction by using factor analysis and discriminant analysis. The main objectives of the study are to analyze the financial consumer protection in commercial banks, to examine the customer satisfaction of commercial banks and to identify the factors of financial consumer protection lead customer satisfaction. There are many research work carried out on financial consumer protection in financial literacy, but the identification of factors which lead the financial consumer protection and the relationship between financial consumer protection and the customer satisfaction is very important, Particularly for banks to improve its quality and increase the customer satisfaction. Therefore this study is carried out with the aim of identifying the factors of financial consumer protection and its influence on customer satisfaction. This study is both descriptive and analytical in nature. It covers both primary and secondary data. The primary data has been collected from the customers of commercial banks using pre-tested interview schedule and the secondary data has been collected from standard books, journals, magazines, websites and so on.

  2. A novel electroencephalographic analysis method discriminates alcohol effects from those of other sedative/hypnotics.

    Science.gov (United States)

    Steffensen, Scott C; Lee, Rong-Sheng; Henriksen, Steven J; Packer, Thomas L; Cook, Daniel R

    2002-04-15

    Here we describe a mathematical and statistical signal processing strategy termed event resolution imaging (ERI). Our principal objective was to determine if the acute intoxicating effects of ethanol on spontaneous EEG activity could be discriminated from those of other sedative/hypnotics. We employed ERI to combine and integrate standard analysis methods to learn multiple signal features of time-varying EEG signals. We recorded cortical EEG, electromyographic activity, and motor activity during intravenous administration of saline, ethanol (1.0 g/kg), chlordiazepoxide (10 mg/kg), pentobarbital (6 mg/kg), heroin (0.3 mg/kg), and methamphetamine (2 mg/kg) administered on separate days in six rats. A blind treatment of one of the drugs was readministered to validate the efficacy of ERI analysis. Significant changes in spontaneous EEG activity produced by all five drugs were detected by ERI analysis with a time resolution of 5-10 s. ERI analysis of spontaneous EEG activity also discriminated, with 90-95% accuracy, an ataxic dose of ethanol versus equivalent ataxic doses of chlordiazepoxide or pentobarbital, as well as the effects of saline, a reinforcing dose of heroin, or a locomotor activating dose of methamphetamine. ERI correctly matched the 'blind drug' as ethanol. These findings indicate that ERI analysis can detect the central nervous system effects of various psychoactive drugs and accurately discriminate the electrocortical effects of select sedative/hypnotics, with similar behavioral endpoints, but with dissimilar mechanisms of action.

  3. Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

    Science.gov (United States)

    Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

    2012-03-01

    Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

  4. Overview of hybrid subspace methods for uncertainty quantification, sensitivity analysis

    International Nuclear Information System (INIS)

    Abdel-Khalik, Hany S.; Bang, Youngsuk; Wang, Congjian

    2013-01-01

    Highlights: ► We overview the state-of-the-art in uncertainty quantification and sensitivity analysis. ► We overview new developments in above areas using hybrid methods. ► We give a tutorial introduction to above areas and the new developments. ► Hybrid methods address the explosion in dimensionality in nonlinear models. ► Representative numerical experiments are given. -- Abstract: The role of modeling and simulation has been heavily promoted in recent years to improve understanding of complex engineering systems. To realize the benefits of modeling and simulation, concerted efforts in the areas of uncertainty quantification and sensitivity analysis are required. The manuscript intends to serve as a pedagogical presentation of the material to young researchers and practitioners with little background on the subjects. We believe this is important as the role of these subjects is expected to be integral to the design, safety, and operation of existing as well as next generation reactors. In addition to covering the basics, an overview of the current state-of-the-art will be given with particular emphasis on the challenges pertaining to nuclear reactor modeling. The second objective will focus on presenting our own development of hybrid subspace methods intended to address the explosion in the computational overhead required when handling real-world complex engineering systems.

  5. DYNAMIC HYBRIDS UNDER SOLVENCY II: RISK ANALYSIS AND MODIFICATION POSSIBILITIES

    Directory of Open Access Journals (Sweden)

    Christian Maier

    2017-06-01

    Full Text Available In this study, we investigate the new and standardized European system of supervisory called Solvency II. In essence, asymmetric distribution of information between policyholder and insurer triggered this new regulation which aims at better protecting policyholders. Its three-pillar model is about to challenge both, insurers as well as policyholders. The first pillar includes quantitative aspects, the second pillar contains qualitative aspects and the third pillar comprises market transparency and reporting obligations. Underwriting risks, the default risk of a bank and market risks can be identified for the dynamic hybrid. Solvency II covers all these risks in the first pillar and insurers shall deposit sufficient risk-bearing capital. In our analysis, we first identify the dynamic hybrid specific risks under the Solvency II regime und then develop product modifications to reduce this risk.

  6. Plug-In Hybrid Vehicle Analysis (Milestone Report)

    Energy Technology Data Exchange (ETDEWEB)

    Markel, T.; Brooker, A.; Gonder, J.; O' Keefe, M.; Simpson, A.; Thornton, M.

    2006-11-01

    NREL's plug-in hybrid electric vehicle (PHEV) analysis activities made great strides in FY06 to objectively assess PHEV technology, support the larger U.S. Department of Energy PHEV assessment effort, and share technical knowledge with the vehicle research community and vehicle manufacturers. This report provides research papers and presentations developed in FY06 to support these efforts. The report focuses on the areas of fuel economy reporting methods, cost and consumption benefit analysis, real-world performance expectations, and energy management strategies.

  7. Statistics that learn: can logistic discriminant analysis improve diagnosis in brain SPECT?

    International Nuclear Information System (INIS)

    Behin-Ain, S.; Barnden, L.; Kwiatek, R.; Del Fante, P.; Casse, R.; Burnet, R.; Chew, G.; Kitchener, M.; Boundy, K.; Unger, S.

    2002-01-01

    Full text: Logistic discriminant analysis (LDA) is a statistical technique capable of discriminating individuals within a diseased group against normals. It also enables classification of various diseases within a group of patients. This technique provides a quantitative, automated and non-subjective clinical diagnostic tool. Based on a population known to have the disease and a normal control group, an algorithm was developed and trained to identify regions in the human brain responsible for the disease in question. The algorithm outputs a statistical map representing diseased or normal probability on a voxel or cluster basis from which an index is generated for each subject. The algorithm also generates a set of coefficients which is used to generate an index for the purpose of classification of new subjects. The results are comparable and complement those of Statistical Parametric Mapping (SPM) which employs a more common linear discriminant technique. The results are presented for brain SPECT studies of two diseases: chronic fatigue syndrome (CFS) and fibromyalgia (FM). A 100% specificity and 94% sensitivity is achieved for the CFS study (similar to SPM results) and for the FM study 82% specificity and 94% sensitivity is achieved with corresponding SPM results showing 90% specificity and 82% sensitivity. The results encourages application of LDA for discrimination of new single subjects as well as of diseased and normal groups. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

  8. Optical spectroscopic analysis for the discrimination of extra-virgin olive-oil (Conference Presentation)

    Science.gov (United States)

    McReynolds, Naomi; Auñón Garcia, Juan M.; Guengerich, Zoe; Smith, Terry K.; Dholakia, Kishan

    2017-02-01

    We present an optical spectroscopic technique, making use of both Raman signals and fluorescence spectroscopy, for the identification of five brands of commercially available extra-virgin olive-oil (EVOO). We demonstrate our technique on both a `bulk-optics' free-space system and a compact device. Using the compact device, which is capable of recording both Raman and fluorescence signals, we achieved an average sensitivity and specificity of 98.4% and 99.6% for discrimination, respectively. Our approach demonstrates that both Raman and fluorescence spectroscopy can be used for portable discrimination of EVOOs which obviates the need to use centralised laboratories and opens up the prospect of in-field testing. This technique may enable detection of EVOO that has undergone counterfeiting or adulteration. One of the main challenges facing Raman spectroscopy for use in quality control of EVOOs is that the oxidation of EVOO, which naturally occurs due to aging, causes shifts in Raman spectra with time, which implies regular retraining would be necessary. We present a potential method of analysis to minimize the effect that aging has on discrimination efficiency; we show that by discarding the first principal component, which contains information on the variations due to oxidation, we can improve discrimination efficiency thus improving the robustness of our technique.

  9. Electric and Hybrid Vehicle System Research and Development Project: Hybrid Vehicle Potential Assessment. Volume VI. Cost analysis

    Energy Technology Data Exchange (ETDEWEB)

    Hardy, K.S.

    1979-09-30

    The purpose of the cost analysis is to determine the economic feasibility of a variety of hybrid vehicles with respect to conventional vehicles specifically designed for the same duty cycle defined by the mission analysis. Several different hybrid configurations including parallel, parallel-flywheel, and series vehicles were evaluated. The ramifications of incorporating examples of advanced batteries, these being the advanced lead-acid, nickel-zinc, and sodium sulfur were also investigated. Vehicles were specifically designed with these batteries and for the driving cycles specified by the mission. Simulated operation on the missions yielded the energy consumption (petroleum and/or electricity) over the driving cycles. It was concluded that: in the event that gasoline prices reach $2.50 to $3.00/gal, hybrid vehicles in many applications will become economically competitive with conventional vehicles without subsidization; in some commercial applications hybrid vehicles could be economically competitive, when the gasoline price ranges from $1.20 to $1.50/gal. The cost per kWh per cycle of the advanced batteries is much more important economically than the specific energy; the series hybrid vehicles were found to be more expensive in comparison to the parallel or parallel-flywheel hybrids when designed as passenger vehicles; and hybrid vehicles designed for private use could become economically competitive and displace up to 50% of the fuel normally used on that mission if subsidies of $500 to $2000 were supplied to the owner/operator. (LCL)

  10. Hybrid Information Flow Analysis for Programs with Arrays

    Directory of Open Access Journals (Sweden)

    Gergö Barany

    2016-07-01

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

  11. Dimensionality Reduction of Hyperspectral Image with Graph-Based Discriminant Analysis Considering Spectral Similarity

    Directory of Open Access Journals (Sweden)

    Fubiao Feng

    2017-03-01

    Full Text Available Recently, graph embedding has drawn great attention for dimensionality reduction in hyperspectral imagery. For example, locality preserving projection (LPP utilizes typical Euclidean distance in a heat kernel to create an affinity matrix and projects the high-dimensional data into a lower-dimensional space. However, the Euclidean distance is not sufficiently correlated with intrinsic spectral variation of a material, which may result in inappropriate graph representation. In this work, a graph-based discriminant analysis with spectral similarity (denoted as GDA-SS measurement is proposed, which fully considers curves changing description among spectral bands. Experimental results based on real hyperspectral images demonstrate that the proposed method is superior to traditional methods, such as supervised LPP, and the state-of-the-art sparse graph-based discriminant analysis (SGDA.

  12. Cross coherence independent component analysis in resting and action states EEG discrimination

    International Nuclear Information System (INIS)

    Almurshedi, A; Ismail, A K

    2014-01-01

    Cross Coherence time frequency transform and independent component analysis (ICA) method were used to analyse the electroencephalogram (EEG) signals in resting and action states during open and close eyes conditions. From the topographical scalp distributions of delta, theta, alpha, and beta power spectrum can clearly discriminate between the signal when the eyes were open or closed, but it was difficult to distinguish between resting and action states when the eyes were closed. In open eyes condition, the frontal area (Fp1, Fp2) was activated (higher power) in delta and theta bands whilst occipital (O1, O2) and partial (P3, P4, Pz) area of brain was activated alpha band in closed eyes condition. The cross coherence method of time frequency analysis is capable of discrimination between rest and action brain signals in closed eyes condition

  13. Z-score linear discriminant analysis for EEG based brain-computer interfaces.

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    Full Text Available Linear discriminant analysis (LDA is one of the most popular classification algorithms for brain-computer interfaces (BCI. LDA assumes Gaussian distribution of the data, with equal covariance matrices for the concerned classes, however, the assumption is not usually held in actual BCI applications, where the heteroscedastic class distributions are usually observed. This paper proposes an enhanced version of LDA, namely z-score linear discriminant analysis (Z-LDA, which introduces a new decision boundary definition strategy to handle with the heteroscedastic class distributions. Z-LDA defines decision boundary through z-score utilizing both mean and standard deviation information of the projected data, which can adaptively adjust the decision boundary to fit for heteroscedastic distribution situation. Results derived from both simulation dataset and two actual BCI datasets consistently show that Z-LDA achieves significantly higher average classification accuracies than conventional LDA, indicating the superiority of the new proposed decision boundary definition strategy.

  14. Using discriminant analysis to detect intrusions in external communication for self-driving vehicles

    Directory of Open Access Journals (Sweden)

    Khattab M.Ali Alheeti

    2017-08-01

    Full Text Available Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoc networks is crucial to the reliable exchange of information and control data. In this paper, we propose an intelligent Intrusion Detection System (IDS to protect the external communication of self-driving and semi self-driving vehicles. This technology has the ability to detect Denial of Service (DoS and black hole attacks on vehicular ad hoc networks (VANETs. The advantage of the proposed IDS over existing security systems is that it detects attacks before they causes significant damage. The intrusion prediction technique is based on Linear Discriminant Analysis (LDA and Quadratic Discriminant Analysis (QDA which are used to predict attacks based on observed vehicle behavior. We perform simulations using Network Simulator 2 to demonstrate that the IDS achieves a low rate of false alarms and high accuracy in detection.

  15. Marine Fish Hybridization

    KAUST Repository

    He, Song

    2017-04-01

    Natural hybridization is reproduction (without artificial influence) between two or more species/populations which are distinguishable from each other by heritable characters. Natural hybridizations among marine fishes were highly underappreciated due to limited research effort; it seems that this phenomenon occurs more often than is commonly recognized. As hybridization plays an important role in biodiversity processes in the marine environment, detecting hybridization events and investigating hybridization is important to understand and protect biodiversity. The first chapter sets the framework for this disseration study. The Cohesion Species Concept was selected as the working definition of a species for this study as it can handle marine fish hybridization events. The concept does not require restrictive species boundaries. A general history and background of natural hybridization in marine fishes is reviewed during in chapter as well. Four marine fish hybridization cases were examed and documented in Chapters 2 to 5. In each case study, at least one diagnostic nuclear marker, screened from among ~14 candidate markers, was found to discriminate the putative hybridizing parent species. To further investigate genetic evidence to support the hybrid status for each hybrid offspring in each case, haploweb analysis on diagnostic markers (nuclear and/or mitochondrial) and the DAPC/PCA analysis on microsatellite data were used. By combining the genetic evidences, morphological traits, and ecological observations together, the potential reasons that triggered each hybridization events and the potential genetic/ecology effects could be discussed. In the last chapter, sequences from 82 pairs of hybridizing parents species (for which COI barcoding sequences were available either on GenBank or in our lab) were collected. By comparing the COI fragment p-distance between each hybridizing parent species, some general questions about marine fish hybridization were discussed: Is

  16. Hybrid soft computing systems for electromyographic signals analysis: a review

    Science.gov (United States)

    2014-01-01

    Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis. PMID:24490979

  17. Hybrid soft computing systems for electromyographic signals analysis: a review.

    Science.gov (United States)

    Xie, Hong-Bo; Guo, Tianruo; Bai, Siwei; Dokos, Socrates

    2014-02-03

    Electromyographic (EMG) is a bio-signal collected on human skeletal muscle. Analysis of EMG signals has been widely used to detect human movement intent, control various human-machine interfaces, diagnose neuromuscular diseases, and model neuromusculoskeletal system. With the advances of artificial intelligence and soft computing, many sophisticated techniques have been proposed for such purpose. Hybrid soft computing system (HSCS), the integration of these different techniques, aims to further improve the effectiveness, efficiency, and accuracy of EMG analysis. This paper reviews and compares key combinations of neural network, support vector machine, fuzzy logic, evolutionary computing, and swarm intelligence for EMG analysis. Our suggestions on the possible future development of HSCS in EMG analysis are also given in terms of basic soft computing techniques, further combination of these techniques, and their other applications in EMG analysis.

  18. The application of sparse estimation of covariance matrix to quadratic discriminant analysis

    OpenAIRE

    Sun, Jiehuan; Zhao, Hongyu

    2015-01-01

    Background Although Linear Discriminant Analysis (LDA) is commonly used for classification, it may not be directly applied in genomics studies due to the large p, small n problem in these studies. Different versions of sparse LDA have been proposed to address this significant challenge. One implicit assumption of various LDA-based methods is that the covariance matrices are the same across different classes. However, rewiring of genetic networks (therefore different covariance matrices) acros...

  19. Measurement and Analysis of Power in Hybrid System

    Directory of Open Access Journals (Sweden)

    Vartika Keshri

    2016-12-01

    Full Text Available Application with renewable energy  sources  such   as solar cell array, wind turbines, or fuel cells have increased significantly during the past decade. To obtain the clean energy, we are using the hybrid solar-wind power generation. Consumers prefer quality power from suppliers. The quality of power can be measured by using parameters such as voltage sag, harmonic and power factor.   To   obtain   quality   power   we   have different topologies. In our paper we present a new possible topology which improves power quality. This paper presents modeling analysis and design of a pulse width modulation voltage source inverter (PWM-VSI to be connected between sources, which supplies energy from a hybrid solar wind energy system to the ac grid. The objective of this paper is to show that, with an adequate control, the converter not only can transfer the dc from hybrid solar wind energy system, but also can improve the power factor and quality power of electrical system. Whenever a disturbance occurs on load side, this disturbance can be minimized using open loop and closed loop control systems.

  20. Analysis of a Hybrid Wing Body Center Section Test Article

    Science.gov (United States)

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

    2013-01-01

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

  1. Analysis of Non-binary Hybrid LDPC Codes

    OpenAIRE

    Sassatelli, Lucile; Declercq, David

    2008-01-01

    In this paper, we analyse asymptotically a new class of LDPC codes called Non-binary Hybrid LDPC codes, which has been recently introduced. We use density evolution techniques to derive a stability condition for hybrid LDPC codes, and prove their threshold behavior. We study this stability condition to conclude on asymptotic advantages of hybrid LDPC codes compared to their non-hybrid counterparts.

  2. Discriminant analysis on the treatment results of interstitial radium tongue implants

    International Nuclear Information System (INIS)

    Hoshina, Masao; Shibuya, Hitoshi; Horiuchi, Jun-Ichi; Matsubara, Sho; Suzuki, Soji; Takeda, Masamune

    1989-01-01

    Discriminant analysis was carried out for 48 tongue cancer patients who were treated with radium single-plane implantation. The 48 patients were grouped into 32 successfully cured without complications, five successfully cured with complications, six successfully cured but requiring additional boost therapy and five with local recurrence. To evaluate the relation between the dose distribution and the local treatment results, the analysis was based on a volume-dose relationship. The functions introduced by this discriminant analysis were linear, and the parameters used were modal dose, average dose and shape factors of histograms. Each group of treatment results had a correction rate of >80%, except for the successfully cured group with ulcers. The discriminant functions were useful as an index to obtain a final clinical treatment result at the early time of implantation, and these functions could be used as a criterion for the optimal treatment of tongue carcinoma. We were also able to recognize the limitation of the actual arrangement of sources in the single-plane implant. (author)

  3. Differentiation of free-ranging chicken using discriminant analysis of phenotypic traits

    Directory of Open Access Journals (Sweden)

    Raed M. Al-Atiyat

    Full Text Available ABSTRACT In this study, we investigated the differentiation of five different chicken ecotypes - Center, North, South, West, and East - of Saudi Arabia using discriminate analysis. The analysis was based on nine important morphological and phenotypic traits: body color, beak color, earlobe color, eye color, shank color, comb color, comb type, comb size, and feather distribution. There was a strong significant relationship between the phenotype and effect of geographic height in terms of comb type and earlobe color in males as well as body, beak, eye, and shank color. In particular, the comb type and earlobe color differentiated the ecotypes of males. Among the females, the beak, earlobe, eye, shank color, and feather distribution had more differentiating power. Moreover, the discriminant analysis revealed that the five ecotypes were grouped into three clusters; the Center and the North in one cluster, the West and the South ecotypes in the second for males, and the East ecotype in the last cluster. The female dendogram branching was similar to the male dendrogram branching, except that the Center ecotype was grouped with the North instead of the South. The East ecotype was highly discriminated from the other ecotypes. Nevertheless, the potential of recent individual migration between ecotypes was also noted. Accordingly, the results of the utilized traits in this study might be effective in characterization and conservation of the genetic resources of the Saudi chicken.

  4. Spike detection, characterization, and discrimination using feature analysis software written in LabVIEW.

    Science.gov (United States)

    Stewart, C M; Newlands, S D; Perachio, A A

    2004-12-01

    Rapid and accurate discrimination of single units from extracellular recordings is a fundamental process for the analysis and interpretation of electrophysiological recordings. We present an algorithm that performs detection, characterization, discrimination, and analysis of action potentials from extracellular recording sessions. The program was entirely written in LabVIEW (National Instruments), and requires no external hardware devices or a priori information about action potential shapes. Waveform events are detected by scanning the digital record for voltages that exceed a user-adjustable trigger. Detected events are characterized to determine nine different time and voltage levels for each event. Various algebraic combinations of these waveform features are used as axis choices for 2-D Cartesian plots of events. The user selects axis choices that generate distinct clusters. Multiple clusters may be defined as action potentials by manually generating boundaries of arbitrary shape. Events defined as action potentials are validated by visual inspection of overlain waveforms. Stimulus-response relationships may be identified by selecting any recorded channel for comparison to continuous and average cycle histograms of binned unit data. The algorithm includes novel aspects of feature analysis and acquisition, including higher acquisition rates for electrophysiological data compared to other channels. The program confirms that electrophysiological data may be discriminated with high-speed and efficiency using algebraic combinations of waveform features derived from high-speed digital records.

  5. Machinery fault diagnosis using joint global and local/nonlocal discriminant analysis with selective ensemble learning

    Science.gov (United States)

    Yu, Jianbo

    2016-11-01

    The vibration signals of faulty machine are generally non-stationary and nonlinear under those complicated working conditions. Thus, it is a big challenge to extract and select the effective features from vibration signals for machinery fault diagnosis. This paper proposes a new manifold learning algorithm, joint global and local/nonlocal discriminant analysis (GLNDA), which aims to extract effective intrinsic geometrical information from the given vibration data. Comparisons with other regular methods, principal component analysis (PCA), local preserving projection (LPP), linear discriminant analysis (LDA) and local LDA (LLDA), illustrate the superiority of GLNDA in machinery fault diagnosis. Based on the extracted information by GLNDA, a GLNDA-based Fisher discriminant rule (FDR) is put forward and applied to machinery fault diagnosis without additional recognizer construction procedure. By importing Bagging into GLNDA score-based feature selection and FDR, a novel manifold ensemble method (selective GLNDA ensemble, SE-GLNDA) is investigated for machinery fault diagnosis. The motivation for developing ensemble of manifold learning components is that it can achieve higher accuracy and applicability than single component in machinery fault diagnosis. The effectiveness of the SE-GLNDA-based fault diagnosis method has been verified by experimental results from bearing full life testers.

  6. Dynamic performance analysis of two regional Nuclear Hybrid Energy Systems

    International Nuclear Information System (INIS)

    Garcia, Humberto E.; Chen, Jun; Kim, Jong S.; Vilim, Richard B.; Binder, William R.; Bragg Sitton, Shannon M.; Boardman, Richard D.; McKellar, Michael G.; Paredis, Christiaan J.J.

    2016-01-01

    In support of more efficient utilization of clean energy generation sources, including renewable and nuclear options, HES (hybrid energy systems) can be designed and operated as FER (flexible energy resources) to meet both electrical and thermal energy needs in the electric grid and industrial sectors. These conceptual systems could effectively and economically be utilized, for example, to manage the increasing levels of dynamic variability and uncertainty introduced by VER (variable energy resources) such as renewable sources (e.g., wind, solar), distributed energy resources, demand response schemes, and modern energy demands (e.g., electric vehicles) with their ever changing usage patterns. HES typically integrate multiple energy inputs (e.g., nuclear and renewable generation) and multiple energy outputs (e.g., electricity, gasoline, fresh water) using complementary energy conversion processes. This paper reports a dynamic analysis of two realistic HES including a nuclear reactor as the main baseload heat generator and to assess the local (e.g., HES owners) and system (e.g., the electric grid) benefits attainable by their application in scenarios with multiple commodity production and high renewable penetration. It is performed for regional cases – not generic examples – based on available resources, existing infrastructure, and markets within the selected regions. This study also briefly addresses the computational capabilities developed to conduct such analyses. - Highlights: • Hybrids including renewables can operate as dispatchable flexible energy resources. • Nuclear energy can address high variability and uncertainty in energy systems. • Nuclear hybrids can reliably provide grid services over various time horizons. • Nuclear energy can provide operating reserves and grid inertia under high renewables. • Nuclear hybrids can greatly reduce GHG emissions and support grid and industry needs.

  7. Using Dynamic Fourier Analysis to Discriminate Between Seismic Signals from Natural Earthquakes and Mining Explosions

    Directory of Open Access Journals (Sweden)

    Maria C. Mariani

    2017-08-01

    Full Text Available A sequence of intraplate earthquakes occurred in Arizona at the same location where miningexplosions were carried out in previous years. The explosions and some of the earthquakes generatedvery similar seismic signals. In this study Dynamic Fourier Analysis is used for discriminating signalsoriginating from natural earthquakes and mining explosions. Frequency analysis of seismogramsrecorded at regional distances shows that compared with the mining explosions the earthquake signalshave larger amplitudes in the frequency interval ~ 6 to 8 Hz and significantly smaller amplitudes inthe frequency interval ~ 2 to 4 Hz. This type of analysis permits identifying characteristics in theseismograms frequency yielding to detect potentially risky seismic events.

  8. [Etiological analysis and establishment of a discriminant model for lower respiratory tract infections in hospitalized patients].

    Science.gov (United States)

    Chen, Y S; Lin, X H; Li, H R; Hua, Z D; Lin, M Q; Huang, W S; Yu, T; Lyu, H Y; Mao, W P; Liang, Y Q; Peng, X R; Chen, S J; Zheng, H; Lian, S Q; Hu, X L; Yao, X Q

    2017-12-12

    Objective: To analyze the pathogens of lower respiratory tract infection(LRTI) including bacterial, viral and mixed infection, and to establish a discriminant model based on clinical features in order to predict the pathogens. Methods: A total of 243 hospitalized patients with lower respiratory tract infections were enrolled in Fujian Provincial Hospital from April 2012 to September 2015. The clinical data and airway (sputum and/or bronchoalveolar lavage) samples were collected. Microbes were identified by traditional culture (for bacteria), loop-mediated isothermal amplification(LAMP) and gene sequencing (for bacteria and atypical pathogen), or Real-time quantitative polymerase chain reaction (Real-time PCR)for viruses. Finally, a discriminant model was established by using the discriminant analysis methods to help to predict bacterial, viral and mixed infections. Results: Pathogens were detected in 53.9% (131/243) of the 243 cases.Bacteria accounted for 23.5%(57/243, of which 17 cases with the virus, 1 case with Mycoplasma pneumoniae and virus), mainly Pseudomonas Aeruginosa and Klebsiella Pneumonia. Atypical pathogens for 4.9% (12/243, of which 3 cases with the virus, 1 case of bacteria and viruses), all were mycoplasma pneumonia. Viruses for 34.6% (84/243, of which 17 cases of bacteria, 3 cases with Mycoplasma pneumoniae, 1 case with Mycoplasma pneumoniae and bacteria) of the cases, mainly Influenza A virus and Human Cytomegalovirus, and other virus like adenovirus, human parainfluenza virus, respiratory syncytial virus, human metapneumovirus, human boca virus were also detected fewly. Seven parameters including mental status, using antibiotics prior to admission, complications, abnormal breath sounds, neutrophil alkaline phosphatase (NAP) score, pneumonia severity index (PSI) score and CRUB-65 score were enrolled after univariate analysis, and discriminant analysis was used to establish the discriminant model by applying the identified pathogens as the

  9. The contribution of cluster and discriminant analysis to the classification of complex aquifer systems.

    Science.gov (United States)

    Panagopoulos, G P; Angelopoulou, D; Tzirtzilakis, E E; Giannoulopoulos, P

    2016-10-01

    This paper presents an innovated method for the discrimination of groundwater samples in common groups representing the hydrogeological units from where they have been pumped. This method proved very efficient even in areas with complex hydrogeological regimes. The proposed method requires chemical analyses of water samples only for major ions, meaning that it is applicable to most of cases worldwide. Another benefit of the method is that it gives a further insight of the aquifer hydrogeochemistry as it provides the ions that are responsible for the discrimination of the group. The procedure begins with cluster analysis of the dataset in order to classify the samples in the corresponding hydrogeological unit. The feasibility of the method is proven from the fact that the samples of volcanic origin were separated into two different clusters, namely the lava units and the pyroclastic-ignimbritic aquifer. The second step is the discriminant analysis of the data which provides the functions that distinguish the groups from each other and the most significant variables that define the hydrochemical composition of the aquifer. The whole procedure was highly successful as the 94.7 % of the samples were classified to the correct aquifer system. Finally, the resulted functions can be safely used to categorize samples of either unknown or doubtful origin improving thus the quality and the size of existing hydrochemical databases.

  10. Detection of non-milk fat in milk fat by gas chromatography and linear discriminant analysis.

    Science.gov (United States)

    Gutiérrez, R; Vega, S; Díaz, G; Sánchez, J; Coronado, M; Ramírez, A; Pérez, J; González, M; Schettino, B

    2009-05-01

    Gas chromatography was utilized to determine triacylglycerol profiles in milk and non-milk fat. The values of triacylglycerol were subjected to linear discriminant analysis to detect and quantify non-milk fat in milk fat. Two groups of milk fat were analyzed: A) raw milk fat from the central region of Mexico (n = 216) and B) ultrapasteurized milk fat from 3 industries (n = 36), as well as pork lard (n = 2), bovine tallow (n = 2), fish oil (n = 2), peanut (n = 2), corn (n = 2), olive (n = 2), and soy (n = 2). The samples of raw milk fat were adulterated with non-milk fats in proportions of 0, 5, 10, 15, and 20% to form 5 groups. The first function obtained from the linear discriminant analysis allowed the correct classification of 94.4% of the samples with levels <10% of adulteration. The triacylglycerol values of the ultrapasteurized milk fats were evaluated with the discriminant function, demonstrating that one industry added non-milk fat to its product in 80% of the samples analyzed.

  11. An intelligent hybrid system for surface coal mine safety analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lilic, N.; Obradovic, I.; Cvjetic, A. [University of Belgrade, Belgrade (Serbia)

    2010-06-15

    Analysis of safety in surface coal mines represents a very complex process. Published studies on mine safety analysis are usually based on research related to accidents statistics and hazard identification with risk assessment within the mining industry. Discussion in this paper is focused on the application of AI methods in the analysis of safety in mining environment. Complexity of the subject matter requires a high level of expert knowledge and great experience. The solution was found in the creation of a hybrid system PROTECTOR, whose knowledge base represents a formalization of the expert knowledge in the mine safety field. The main goal of the system is the estimation of mining environment as one of the significant components of general safety state in a mine. This global goal is subdivided into a hierarchical structure of subgoals where each subgoal can be viewed as the estimation of a set of parameters (gas, dust, climate, noise, vibration, illumination, geotechnical hazard) which determine the general mine safety state and category of hazard in mining environment. Both the hybrid nature of the system and the possibilities it offers are illustrated through a case study using field data related to an existing Serbian surface coal mine.

  12. Background reduction and noise discrimination in the proportional counting of tritium using pulse-shape analysis

    Energy Technology Data Exchange (ETDEWEB)

    Hochel, R C; Hayes, D W [Du Pont de Nemours (E.I.) and Co., Aiken, S.C. (USA). Savannah River Lab.

    1975-12-01

    A pulse-shape analysis (PSA) unit of commercial design has been incorporated into a proportional counting system to determine the effectiveness of pulse-shape discrimination in increasing the sensitivity of tritium counting. It was found that a quantitative determination of tritium could be obtained directly from the PSA time spectrum eliminating the need for beta-ray energy selection used in the pulse-shape discrimination (PSD) technique. The performance of the proportional counting system was tested using the PSA unit and anticoincidence shielding, both singly and combined, under several types of background. A background reduction factor of 169 was obtained from the combined PSA-anticoincidence system with only a 2% loss in tritium counting efficiency. The PSA method was also found to offer significant reductions in noise background.

  13. Background reduction and noise discrimination in the proportional counting of tritium using pulse-shape analysis

    International Nuclear Information System (INIS)

    Hochel, R.C.; Hayes, D.W.

    1975-01-01

    A pulse-shape analysis (PSA) unit of commercial design has been incorporated into a proportional counting system to determine the effectiveness of pulse-shape discrimination in increasing the sensitivity of tritium counting. It was found that a quantitative determination of tritium could be obtained directly from the PSA time spectrum eliminating the need for beta-ray energy selection used in the pulse-shape discrimination (PSD) technique. The performance of the proportional counting system was tested using the PSA unit and anticoincidence shielding, both singly and combined, under several types of background. A background reduction factor of 169 was obtained from the combined PSA-anticoincidence system with only a 2% loss in tritium counting efficiency. The PSA method was also found to offer significant reductions in noise background. (Auth.)

  14. INCOME INEQUALITY IN SOME MAJOR EUROPEAN UNION ECONOMIES A DISCRIMINANT ANALYSIS

    Directory of Open Access Journals (Sweden)

    JYOTIRMAYEE KAR

    2012-12-01

    Full Text Available This exercise is an attempt to assess the importance of some social, economic, demographic and infrastructural factors which account for the prevailing income inequality across some of the EU countries. Using discriminant analysis the study suggests that crime recorded by police is the most important predictor in discriminating between the group of countries with relatively more equitable distribution of income from those with less. This variable is followed by number of students in the country. Reduction in the level of crime and improvement in the student strength could help in reducing income inequality. Quite intuitively, improvement in all the economic factors like GDP per capita and agricultural index will help to reduce income inequality. Identical is the case of the demographic factors. This calls for implementation of developmental policies towards improvement in these areas.

  15. Principal component analysis for neural electron/jet discrimination in highly segmented calorimeters

    International Nuclear Information System (INIS)

    Vassali, M.R.; Seixas, J.M.

    2001-01-01

    A neural electron/jet discriminator based on calorimetry is developed for the second-level trigger system of the ATLAS detector. As preprocessing of the calorimeter information, a principal component analysis is performed on each segment of the two sections (electromagnetic and hadronic) of the calorimeter system, in order to reduce significantly the dimension of the input data space and fully explore the detailed energy deposition profile, which is provided by the highly-segmented calorimeter system. It is shown that projecting calorimeter data onto 33 segmented principal components, the discrimination efficiency of the neural classifier reaches 98.9% for electrons (with only 1% of false alarm probability). Furthermore, restricting data projection onto only 9 components, an electron efficiency of 99.1% is achieved (with 3% of false alarm), which confirms that a fast triggering system may be designed using few components

  16. A hybrid correlation analysis with application to imaging genetics

    Science.gov (United States)

    Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

    2018-03-01

    Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding

  17. Sex assessment from carpals bones: discriminant function analysis in a contemporary Mexican sample.

    Science.gov (United States)

    Mastrangelo, Paola; De Luca, Stefano; Sánchez-Mejorada, Gabriela

    2011-06-15

    Sex assessment is one of the first essential steps in human identification, in both medico-legal cases and bio-archaeological contexts. Fragmentary human remains compromised by different types of burial or physical insults may frustrate the use of the traditional sex estimation methods, such as the analysis of the skull and pelvis. Currently, the application of discriminant functions to sex unidentified skeletal remains is steadily increasing. However, several studies have demonstrated that, due to variation in size and patterns of sexual dimorphism, discriminant functions are population-specific. In this study, in order to improve sex assessment from skeletal remains and to establish population-specific discriminant functions, the diagnostic values of the carpal bones were considered. A sample of 136 individuals (78 males, 58 females) of known sex and age was analyzed. They belong to a contemporary identified collection from the Laboratory of Physical Anthropology, Faculty of Medicine, UNAM (Universidad Nacional Autónoma de México, Mexico City). The age of the individuals ranged between 25 and 85 years. Between four and nine measurements of each carpal bone were taken. Independent t-tests confirm that all carpals are sexually dimorphic. Univariate measurements produce accuracy levels that range from 61.8% to 90.8%. Classification accuracies ranged between 81.3% and 92.3% in the multivariate stepwise discriminant analysis. In addition, intra- and inter-observer error tests were performed. These indicated that replication of measurements was satisfactory for the same observer over time and between observers. These results suggest that carpal bones can be used for assessing sex in both forensic and bio-archaeological identification procedures and that bone dimensions are population specific. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  18. Electromagnetic Properties Analysis on Hybrid-driven System of Electromagnetic Motor

    Science.gov (United States)

    Zhao, Jingbo; Han, Bingyuan; Bei, Shaoyi

    2018-01-01

    The hybrid-driven system made of permanent-and electromagnets applied in the electromagnetic motor was analyzed, equivalent magnetic circuit was used to establish the mathematical models of hybrid-driven system, based on the models of hybrid-driven system, the air gap flux, air-gap magnetic flux density, electromagnetic force was proposed. Taking the air-gap magnetic flux density and electromagnetic force as main research object, the hybrid-driven system was researched. Electromagnetic properties of hybrid-driven system with different working current modes is studied preliminary. The results shown that analysis based on hybrid-driven system can improve the air-gap magnetic flux density and electromagnetic force more effectively and can also guarantee the output stability, the effectiveness and feasibility of the hybrid-driven system are verified, which proved theoretical basis for the design of hybrid-driven system.

  19. Study on discriminant analysis by military mental disorder prediction scale for mental disorder of new recruits

    Directory of Open Access Journals (Sweden)

    Li-yi ZHANG

    2011-11-01

    Full Text Available Objective To examine the predictive role of the Military Mental Disorder Prediction Scale on the mental disorder of new recruits.Methods The present study examined 115 new recruits diagnosed with mental disorder and 115 healthy new recruits.The recruits were tested using the Military Mental Disorder Prediction Scale.The discriminant function was built by discriminant analysis method.The current study analyzed the predictive value of 11 factors(family medical record and past medical record(X1,growth experience(X2,introversion(X3,stressor(X4,poor mental defense(X5,social support(X6,psychosis(X7,depression(X8,mania(X9,neurosis(X10,and personality disorder(X11 aside from lie factor on the mental disorder of new recruits.Results The mental disorder group has higher total score and factor score in family medical record and past medical record,introversion,stressor,poor mental defense,social support,psychosis,depression,mania,neurosis,personality disorder,and lie than those of the contrast group(P < 0.01.For the score of growth experience factor,that of the mental disorder group is higher than the score of the contrast group(P < 0.05.All 11 factors except the lie factor in the Mental Disorder Prediction Scale are taken as independent variables by enforced introduction to obtain the Fisher linear discriminant function as follows: The mental disorder group=-7.014-0.278X1+1.556X2+1.563X3+0.878X4+0.183X5-0.845X6-0.562X7-0.353X8+1.246X9-0.505X10+1.029X11.The contrast group=-2.971+0.056X1+2.194X2+0.707X3+0.592X4-0.086X5-0.888X6-0.133X7-0.360X8+0.654X9-0.467X10+0.308X11.The discriminant function has an accuracy rate of 76.5% on the new recruits with mental disorders and 100% on the healthy new recruits.The total accurate discrimination rate is 88.3% and the total inaccurate discrimination rate is 11.7%.Conclusion The Military Mental Disorder Prediction Scale has a high accuracy rate on the prediction of mental disorder of new recruits and is worthy of

  20. Development and Analysis of Hybrid Thermoelectric Refrigerator Systems

    Science.gov (United States)

    Saifizi, M.; Zakaria, M. S.; Yaacob, Sazali; Wan, Khairunizam

    2018-03-01

    Thermoelectric module (TEM) is a type of solid-state devices which has the capability to maintain the accuracy of small temperature variation application. In this study, a hybrid thermoelectric refrigerator system is introduced by utilizing TEMs; direct and air to air thermoelectric heat pump to cool down and maintain low temperature for vaccines storage. Two different materials which are aluminum and stainless steel are used as container in hybrid thermoelectric refrigerator (HTER) configuration to investigate the response of every system in transient and steady state mode. A proper temperature sensor calibration technique is implemented to make certain real time data acquisition of the systems are not affected very much from the noise generated. From step response analysis, it is indicated that HTER I (aluminum) has rapid settling time from transient to steady state than HTER II (stainless steel) since aluminum has better thermal conductivity as compared to stainless steel. It is found that HTER I is better in cooling capability with the same input current instead of HTER II which required a longer time to achieve steady state mode. Besides, in Pseudo Random Binary Sequence (PRBS) response analysis injected to both systems shows HTER I is very sensitive to current input as the sequence length of HTER I is shorter than HTER II. However both systems depict the varying temperature in the range of 4 oC due to differences in thermal conductivity of container.

  1. Textural Maturity Analysis and Sedimentary Environment Discrimination Based on Grain Shape Data

    Science.gov (United States)

    Tunwal, M.; Mulchrone, K. F.; Meere, P. A.

    2017-12-01

    Morphological analysis of clastic sedimentary grains is an important source of information regarding the processes involved in their formation, transportation and deposition. However, a standardised approach for quantitative grain shape analysis is generally lacking. In this contribution we report on a study where fully automated image analysis techniques were applied to loose sediment samples collected from glacial, aeolian, beach and fluvial environments. A range of shape parameters are evaluated for their usefulness in textural characterisation of populations of grains. The utility of grain shape data in ranking textural maturity of samples within a given sedimentary environment is evaluated. Furthermore, discrimination of sedimentary environment on the basis of grain shape information is explored. The data gathered demonstrates a clear progression in textural maturity in terms of roundness, angularity, irregularity, fractal dimension, convexity, solidity and rectangularity. Textural maturity can be readily categorised using automated grain shape parameter analysis. However, absolute discrimination between different depositional environments on the basis of shape parameters alone is less certain. For example, the aeolian environment is quite distinct whereas fluvial, glacial and beach samples are inherently variable and tend to overlap each other in terms of textural maturity. This is most likely due to a collection of similar processes and sources operating within these environments. This study strongly demonstrates the merit of quantitative population-based shape parameter analysis of texture and indicates that it can play a key role in characterising both loose and consolidated sediments. This project is funded by the Irish Petroleum Infrastructure Programme (www.pip.ie)

  2. Prediction of Depression in Cancer Patients With Different Classification Criteria, Linear Discriminant Analysis versus Logistic Regression.

    Science.gov (United States)

    Shayan, Zahra; Mohammad Gholi Mezerji, Naser; Shayan, Leila; Naseri, Parisa

    2015-11-03

    Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups.

  3. Attractor structure discriminates sleep states: recurrence plot analysis applied to infant breathing patterns.

    Science.gov (United States)

    Terrill, Philip Ian; Wilson, Stephen James; Suresh, Sadasivam; Cooper, David M; Dakin, Carolyn

    2010-05-01

    Breathing patterns are characteristically different between infant active sleep (AS) and quiet sleep (QS), and statistical quantifications of interbreath interval (IBI) data have previously been used to discriminate between infant sleep states. It has also been identified that breathing patterns are governed by a nonlinear controller. This study aims to investigate whether nonlinear quantifications of infant IBI data are characteristically different between AS and QS, and whether they may be used to discriminate between these infant sleep states. Polysomnograms were obtained from 24 healthy infants at six months of age. Periods of AS and QS were identified, and IBI data extracted. Recurrence quantification analysis (RQA) was applied to each period, and recurrence calculated for a fixed radius in the range of 0-8 in steps of 0.02, and embedding dimensions of 4, 6, 8, and 16. When a threshold classifier was trained, the RQA variable recurrence was able to correctly classify 94.3% of periods in a test dataset. It was concluded that RQA of IBI data is able to accurately discriminate between infant sleep states. This is a promising step toward development of a minimal-channel automatic sleep state classification system.

  4. Applying linear discriminant analysis to predict groundwater redox conditions conducive to denitrification

    Science.gov (United States)

    Wilson, S. R.; Close, M. E.; Abraham, P.

    2018-01-01

    Diffuse nitrate losses from agricultural land pollute groundwater resources worldwide, but can be attenuated under reducing subsurface conditions. In New Zealand, the ability to predict where groundwater denitrification occurs is important for understanding the linkage between land use and discharges of nitrate-bearing groundwater to streams. This study assesses the application of linear discriminant analysis (LDA) for predicting groundwater redox status for Southland, a major dairy farming region in New Zealand. Data cases were developed by assigning a redox status to samples derived from a regional groundwater quality database. Pre-existing regional-scale geospatial databases were used as training variables for the discriminant functions. The predictive accuracy of the discriminant functions was slightly improved by optimising the thresholds between sample depth classes. The models predict 23% of the region as being reducing at shallow depths (water table, and low-permeability clastic sediments. The coastal plains are an area of widespread groundwater discharge, and the soil and hydrology characteristics require the land to be artificially drained to render the land suitable for farming. For the improvement of water quality in coastal areas, it is therefore important that land and water management efforts focus on understanding hydrological bypassing that may occur via artificial drainage systems.

  5. Accurate palm vein recognition based on wavelet scattering and spectral regression kernel discriminant analysis

    Science.gov (United States)

    Elnasir, Selma; Shamsuddin, Siti Mariyam; Farokhi, Sajad

    2015-01-01

    Palm vein recognition (PVR) is a promising new biometric that has been applied successfully as a method of access control by many organizations, which has even further potential in the field of forensics. The palm vein pattern has highly discriminative features that are difficult to forge because of its subcutaneous position in the palm. Despite considerable progress and a few practical issues, providing accurate palm vein readings has remained an unsolved issue in biometrics. We propose a robust and more accurate PVR method based on the combination of wavelet scattering (WS) with spectral regression kernel discriminant analysis (SRKDA). As the dimension of WS generated features is quite large, SRKDA is required to reduce the extracted features to enhance the discrimination. The results based on two public databases-PolyU Hyper Spectral Palmprint public database and PolyU Multi Spectral Palmprint-show the high performance of the proposed scheme in comparison with state-of-the-art methods. The proposed approach scored a 99.44% identification rate and a 99.90% verification rate [equal error rate (EER)=0.1%] for the hyperspectral database and a 99.97% identification rate and a 99.98% verification rate (EER=0.019%) for the multispectral database.

  6. Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA).

    Science.gov (United States)

    Kassouf, Amine; Maalouly, Jacqueline; Rutledge, Douglas N; Chebib, Hanna; Ducruet, Violette

    2014-11-01

    Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of the proposed approach was also tested using two spectrometers with considerable differences in their sensitivities. Discrimination rates were not affected proving that the developed approach could be extrapolated to different spectrometers. MIR combined with ICA is a promising tool for plastic waste separation that can help improve performance in this field; however further technological improvements and developments are required before it can be applied

  7. BIOMETRIC ANALYSIS OF THE ARTIFICIAL HYBRIDIZATION BETWEEN Pangasius djambal BLEEKER, 1846 AND Pangasianodon hypophthalmus SAUVAGE, 1878

    Directory of Open Access Journals (Sweden)

    Rudhy Gustiano

    2016-10-01

    Full Text Available It is really important, since the possible use of these pangasiid hybrids in aquaculture faces the problem of potential impact on wild population. Therefore, it is urgently needed to provide quick identification tools in the field. This study investigated morphological characters of Pangasius djambal and Pangasianodon hypophthalmus and their hybrids. A detailed morphological analysis using 32 morphometric measurements and five meristic counts was done on the hybridization of P. djambal and P. hypophthalmus. Morphometric analysis and meristic counts showed that the reciprocal hybrids have intermediate characters except for gill raker number in which lower than that of parental species. In general, the hybrids have tendency to be like P. hypophthalmus rather than P. djambal. The only typical character of P. djambal appeared on hybrids is teeth shape, both vomerine and palatine. It is clearly defined that the true hybrids have seven pelvic fin rays.

  8. Performance Analysis of Hybrid Electric Vehicle over Different Driving Cycles

    Science.gov (United States)

    Panday, Aishwarya; Bansal, Hari Om

    2017-02-01

    Article aims to find the nature and response of a hybrid vehicle on various standard driving cycles. Road profile parameters play an important role in determining the fuel efficiency. Typical parameters of road profile can be reduced to a useful smaller set using principal component analysis and independent component analysis. Resultant data set obtained after size reduction may result in more appropriate and important parameter cluster. With reduced parameter set fuel economies over various driving cycles, are ranked using TOPSIS and VIKOR multi-criteria decision making methods. The ranking trend is then compared with the fuel economies achieved after driving the vehicle over respective roads. Control strategy responsible for power split is optimized using genetic algorithm. 1RC battery model and modified SOC estimation method are considered for the simulation and improved results compared with the default are obtained.

  9. Analysis of Network Parameters Influencing Performance of Hybrid Multimedia Networks

    Directory of Open Access Journals (Sweden)

    Dominik Kovac

    2013-10-01

    Full Text Available Multimedia networks is an emerging subject that currently attracts the attention of research and industrial communities. This environment provides new entertainment services and business opportunities merged with all well-known network services like VoIP calls or file transfers. Such a heterogeneous system has to be able satisfy all network and end-user requirements which are increasing constantly. Therefore the simulation tools enabling deep analysis in order to find the key performance indicators and factors which influence the overall quality for specific network service the most are highly needed. This paper provides a study on the network parameters like communication technology, routing protocol, QoS mechanism, etc. and their effect on the performance of hybrid multimedia network. The analysis was performed in OPNET Modeler environment and the most interesting results are discussed at the end of this paper

  10. Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng [Jiangnan University, Wuxi (China)

    2014-11-15

    The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy.

  11. Hyperplane distance neighbor clustering based on local discriminant analysis for complex chemical processes monitoring

    International Nuclear Information System (INIS)

    Lu, Chunhong; Xiao, Shaoqing; Gu, Xiaofeng

    2014-01-01

    The collected training data often include both normal and faulty samples for complex chemical processes. However, some monitoring methods, such as partial least squares (PLS), principal component analysis (PCA), independent component analysis (ICA) and Fisher discriminant analysis (FDA), require fault-free data to build the normal operation model. These techniques are applicable after the preliminary step of data clustering is applied. We here propose a novel hyperplane distance neighbor clustering (HDNC) based on the local discriminant analysis (LDA) for chemical process monitoring. First, faulty samples are separated from normal ones using the HDNC method. Then, the optimal subspace for fault detection and classification can be obtained using the LDA approach. The proposed method takes the multimodality within the faulty data into account, and thus improves the capability of process monitoring significantly. The HDNC-LDA monitoring approach is applied to two simulation processes and then compared with the conventional FDA based on the K-nearest neighbor (KNN-FDA) method. The results obtained in two different scenarios demonstrate the superiority of the HDNC-LDA approach in terms of fault detection and classification accuracy

  12. Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI.

    Science.gov (United States)

    Keith, Verna M; Nguyen, Ann W; Taylor, Robert Joseph; Mouzon, Dawne M; Chatters, Linda M

    2017-05-01

    Data from the 2001-2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.

  13. Allele specific hybridization using oligonucleotide probes of very high specific activity: Discrimination of the human β/sup A/ and β/sup S/-globin genes

    International Nuclear Information System (INIS)

    Studencki, A.B.; Wallace, R.B.

    1984-01-01

    The repair activity of E. coli DNA polymerase I (Klenow fragment) was used to prepare nonadecanucleotide hybridization probes which were complementary either to the normal human β-globin (β/sup A/) or to the sickle cell human β-globin (β/sup S/) gene. Template directed polymerization of highly radiolabeled α-/sup 32/P-deoxyribonucleoside triphosphates (3200, 5000 and/or 7800 Ci/mmol) onto nonamer and decamer primers produced probes with specific activities ranging from 1.0 - 2.0 x 10/sup 10/ dpm/μg. The extremely high specific activities of these probes made it possible to detect the β/sup A/ and β/sup S/ single copy gene sequences in as little as 1 μg of total human genomic DNA as well as to discriminate between the homozygous and heterozygous states. This means that it was possible to detect 0.5 - 1.0 x 10/sup -18/ moles of a given single copy sequence

  14. Rapid discrimination of bergamot essential oil by paper spray mass spectrometry and chemometric analysis.

    Science.gov (United States)

    Taverna, Domenico; Di Donna, Leonardo; Mazzotti, Fabio; Tagarelli, Antonio; Napoli, Anna; Furia, Emilia; Sindona, Giovanni

    2016-09-01

    A novel approach for the rapid discrimination of bergamot essential oil from other citrus fruits oils is presented. The method was developed using paper spray mass spectrometry (PS-MS) allowing for a rapid molecular profiling coupled with a statistic tool for a precise and reliable discrimination between the bergamot complex matrix and other similar matrices, commonly used for its reconstitution. Ambient mass spectrometry possesses the ability to record mass spectra of ordinary samples, in their native environment, without sample preparation or pre-separation by creating ions outside the instrument. The present study reports a PS-MS method for the determination of oxygen heterocyclic compounds such as furocoumarins, psoralens and flavonoids present in the non-volatile fraction of citrus fruits essential oils followed by chemometric analysis. The volatile fraction of Bergamot is one of the most known and fashionable natural products, which found applications in flavoring industry as ingredient in beverages and flavored foodstuff. The development of the presented method employed bergamot, sweet orange, orange, cedar, grapefruit and mandarin essential oils. PS-MS measurements were carried out in full scan mode for a total run time of 2 min. The capability of PS-MS profiling to act as marker for the classification of bergamot essential oils was evaluated by using multivariate statistical analysis. Two pattern recognition techniques, linear discriminant analysis and soft independent modeling of class analogy, were applied to MS data. The cross-validation procedure has shown excellent results in terms of the prediction ability because both models have correctly classified all samples for each category. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  15. Regulatory pathway analysis by high-throughput in situ hybridization.

    Directory of Open Access Journals (Sweden)

    Axel Visel

    2007-10-01

    Full Text Available Automated in situ hybridization enables the construction of comprehensive atlases of gene expression patterns in mammals. Such atlases can become Web-searchable digital expression maps of individual genes and thus offer an entryway to elucidate genetic interactions and signaling pathways. Towards this end, an atlas housing approximately 1,000 spatial gene expression patterns of the midgestation mouse embryo was generated. Patterns were textually annotated using a controlled vocabulary comprising >90 anatomical features. Hierarchical clustering of annotations was carried out using distance scores calculated from the similarity between pairs of patterns across all anatomical structures. This process ordered hundreds of complex expression patterns into a matrix that reflects the embryonic architecture and the relatedness of patterns of expression. Clustering yielded 12 distinct groups of expression patterns. Because of the similarity of expression patterns within a group, members of each group may be components of regulatory cascades. We focused on the group containing Pax6, an evolutionary conserved transcriptional master mediator of development. Seventeen of the 82 genes in this group showed a change of expression in the developing neocortex of Pax6-deficient embryos. Electromobility shift assays were used to test for the presence of Pax6-paired domain binding sites. This led to the identification of 12 genes not previously known as potential targets of Pax6 regulation. These findings suggest that cluster analysis of annotated gene expression patterns obtained by automated in situ hybridization is a novel approach for identifying components of signaling cascades.

  16. Fatigue Life Analysis of Tapered Hybrid Composite Flexbeams

    Science.gov (United States)

    Murri, Gretchen B.; Schaff, Jeffery R.; Dobyns, Alan L.

    2002-01-01

    Nonlinear-tapered flexbeam laminates from a full-size composite helicopter rotor hub flexbeam were tested under combined constant axial tension and cyclic bending loads. The two different graphite/glass hybrid configurations tested under cyclic loading failed by delamination in the tapered region. A 2-D finite element model was developed which closely approximated the flexbeam geometry, boundary conditions, and loading. The analysis results from two geometrically nonlinear finite element codes, ANSYS and ABAQUS, are presented and compared. Strain energy release rates (G) obtained from the above codes using the virtual crack closure technique (VCCT) at a resin crack location in the flexbeams are presented for both hybrid material types. These results compare well with each other and suggest that the initial delamination growth from the resin crack toward the thick region of the flexbeam is strongly mode II. The peak calculated G values were used with material characterization data to calculate fatigue life curves and compared with test data. A curve relating maximum surface strain to number of loading cycles at delamination onset compared reasonably well with the test results.

  17. Estimating the causes of traffic accidents using logistic regression and discriminant analysis.

    Science.gov (United States)

    Karacasu, Murat; Ergül, Barış; Altin Yavuz, Arzu

    2014-01-01

    Factors that affect traffic accidents have been analysed in various ways. In this study, we use the methods of logistic regression and discriminant analysis to determine the damages due to injury and non-injury accidents in the Eskisehir Province. Data were obtained from the accident reports of the General Directorate of Security in Eskisehir; 2552 traffic accidents between January and December 2009 were investigated regarding whether they resulted in injury. According to the results, the effects of traffic accidents were reflected in the variables. These results provide a wealth of information that may aid future measures toward the prevention of undesired results.

  18. Lameness detection challenges in automated milking systems addressed with partial least squares discriminant analysis

    DEFF Research Database (Denmark)

    Garcia, Emanuel; Klaas, Ilka Christine; Amigo Rubio, Jose Manuel

    2014-01-01

    Lameness is prevalent in dairy herds. It causes decreased animal welfare and leads to higher production costs. This study explored data from an automatic milking system (AMS) to model on-farm gait scoring from a commercial farm. A total of 88 cows were gait scored once per week, for 2 5-wk periods......). The reference gait scoring error was estimated in the first week of the study and was, on average, 15%. Two partial least squares discriminant analysis models were fitted to parity 1 and parity 2 groups, respectively, to assign the lameness class according to the predicted probability of being lame (score 3...

  19. Discrimination of bromodeoxyuridine labelled and unlabelled mitotic cells in flow cytometric bromodeoxyuridine/DNA analysis

    DEFF Research Database (Denmark)

    Jensen, P O; Larsen, J K; Christensen, I J

    1994-01-01

    Bromodeoxyuridine (BrdUrd) labelled and unlabelled mitotic cells, respectively, can be discriminated from interphase cells using a new method, based on immunocytochemical staining of BrdUrd and flow cytometric four-parameter analysis of DNA content, BrdUrd incorporation, and forward and orthogonal...... light scatter. The method was optimized using the human leukemia cell lines HL-60 and K-562. Samples of 10(5) ethanol-fixed cells were treated with pepsin/HCl and stained as a nuclear suspension with anti-BrdUrd antibody, FITC-conjugated secondary antibody, and propidium iodide. Labelled mitoses could...

  20. Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Zhigao Zeng

    2016-01-01

    Full Text Available This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. As demonstrated by the experimental results, our method is fast and can achieve a high classification accuracy rate with an added benefit of robustness in tackling noise.

  1. Event tree analysis for the system of hybrid reactor

    International Nuclear Information System (INIS)

    Yang Yongwei; Qiu Lijian

    1993-01-01

    The application of probabilistic risk assessment for fusion-fission hybrid reactor is introduced. A hybrid reactor system has been analysed using event trees. According to the character of the conceptual design of Hefei Fusion-fission Experimental Hybrid Breeding Reactor, the probabilities of the event tree series induced by 4 typical initiating events were calculated. The results showed that the conceptual design is safe and reasonable. through this paper, the safety character of hybrid reactor system has been understood more deeply. Some suggestions valuable to safety design for hybrid reactor have been proposed

  2. Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA)

    Energy Technology Data Exchange (ETDEWEB)

    Kassouf, Amine, E-mail: amine.kassouf@agroparistech.fr [ER004 “Lebanese Food Packaging”, Faculty of Sciences II, Lebanese University, 90656 Jdeideth El Matn, Fanar (Lebanon); INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy (France); AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris (France); Maalouly, Jacqueline, E-mail: j_maalouly@hotmail.com [ER004 “Lebanese Food Packaging”, Faculty of Sciences II, Lebanese University, 90656 Jdeideth El Matn, Fanar (Lebanon); Rutledge, Douglas N., E-mail: douglas.rutledge@agroparistech.fr [INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy (France); AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris (France); Chebib, Hanna, E-mail: hchebib@hotmail.com [ER004 “Lebanese Food Packaging”, Faculty of Sciences II, Lebanese University, 90656 Jdeideth El Matn, Fanar (Lebanon); Ducruet, Violette, E-mail: violette.ducruet@agroparistech.fr [INRA, UMR1145 Ingénierie Procédés Aliments, 1 Avenue des Olympiades, 91300 Massy (France); AgroParisTech, UMR1145 Ingénierie Procédés Aliments, 16 rue Claude Bernard, 75005 Paris (France)

    2014-11-15

    Highlights: • An innovative technique, MIR-ICA, was applied to plastic packaging separation. • This study was carried out on PE, PP, PS, PET and PLA plastic packaging materials. • ICA was applied to discriminate plastics and 100% separation rates were obtained. • Analyses performed on two spectrometers proved the reproducibility of the method. • MIR-ICA is a simple and fast technique allowing plastic identification/classification. - Abstract: Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of

  3. Rapid discrimination of plastic packaging materials using MIR spectroscopy coupled with independent components analysis (ICA)

    International Nuclear Information System (INIS)

    Kassouf, Amine; Maalouly, Jacqueline; Rutledge, Douglas N.; Chebib, Hanna; Ducruet, Violette

    2014-01-01

    Highlights: • An innovative technique, MIR-ICA, was applied to plastic packaging separation. • This study was carried out on PE, PP, PS, PET and PLA plastic packaging materials. • ICA was applied to discriminate plastics and 100% separation rates were obtained. • Analyses performed on two spectrometers proved the reproducibility of the method. • MIR-ICA is a simple and fast technique allowing plastic identification/classification. - Abstract: Plastic packaging wastes increased considerably in recent decades, raising a major and serious public concern on political, economical and environmental levels. Dealing with this kind of problems is generally done by landfilling and energy recovery. However, these two methods are becoming more and more expensive, hazardous to the public health and the environment. Therefore, recycling is gaining worldwide consideration as a solution to decrease the growing volume of plastic packaging wastes and simultaneously reduce the consumption of oil required to produce virgin resin. Nevertheless, a major shortage is encountered in recycling which is related to the sorting of plastic wastes. In this paper, a feasibility study was performed in order to test the potential of an innovative approach combining mid infrared (MIR) spectroscopy with independent components analysis (ICA), as a simple and fast approach which could achieve high separation rates. This approach (MIR-ICA) gave 100% discrimination rates in the separation of all studied plastics: polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), polystyrene (PS) and polylactide (PLA). In addition, some more specific discriminations were obtained separating plastic materials belonging to the same polymer family e.g. high density polyethylene (HDPE) from low density polyethylene (LDPE). High discrimination rates were obtained despite the heterogeneity among samples especially differences in colors, thicknesses and surface textures. The reproducibility of

  4. The NWRA Classification Infrastructure: description and extension to the Discriminant Analysis Flare Forecasting System (DAFFS)

    Science.gov (United States)

    Leka, K. D.; Barnes, Graham; Wagner, Eric

    2018-04-01

    A classification infrastructure built upon Discriminant Analysis (DA) has been developed at NorthWest Research Associates for examining the statistical differences between samples of two known populations. Originating to examine the physical differences between flare-quiet and flare-imminent solar active regions, we describe herein some details of the infrastructure including: parametrization of large datasets, schemes for handling "null" and "bad" data in multi-parameter analysis, application of non-parametric multi-dimensional DA, an extension through Bayes' theorem to probabilistic classification, and methods invoked for evaluating classifier success. The classifier infrastructure is applicable to a wide range of scientific questions in solar physics. We demonstrate its application to the question of distinguishing flare-imminent from flare-quiet solar active regions, updating results from the original publications that were based on different data and much smaller sample sizes. Finally, as a demonstration of "Research to Operations" efforts in the space-weather forecasting context, we present the Discriminant Analysis Flare Forecasting System (DAFFS), a near-real-time operationally-running solar flare forecasting tool that was developed from the research-directed infrastructure.

  5. The application of sparse estimation of covariance matrix to quadratic discriminant analysis.

    Science.gov (United States)

    Sun, Jiehuan; Zhao, Hongyu

    2015-02-18

    Although Linear Discriminant Analysis (LDA) is commonly used for classification, it may not be directly applied in genomics studies due to the large p, small n problem in these studies. Different versions of sparse LDA have been proposed to address this significant challenge. One implicit assumption of various LDA-based methods is that the covariance matrices are the same across different classes. However, rewiring of genetic networks (therefore different covariance matrices) across different diseases has been observed in many genomics studies, which suggests that LDA and its variations may be suboptimal for disease classifications. However, it is not clear whether considering differing genetic networks across diseases can improve classification in genomics studies. We propose a sparse version of Quadratic Discriminant Analysis (SQDA) to explicitly consider the differences of the genetic networks across diseases. Both simulation and real data analysis are performed to compare the performance of SQDA with six commonly used classification methods. SQDA provides more accurate classification results than other methods for both simulated and real data. Our method should prove useful for classification in genomics studies and other research settings, where covariances differ among classes.

  6. Discriminant analysis of Social Work’s performance in licensure examination

    Directory of Open Access Journals (Sweden)

    Jonel R. Alonzo

    2017-12-01

    Full Text Available Many research studies have examined academic factors as predictors of success in licensure examination. The purpose of this descriptive discriminant analysis was to explore possible factors in passing social work licensure examination. Data were examined from academic records of 69 (37 passed and 32 failed Social Work graduates of the University of Mindanao who took Social Work Licensure Examination 2014. This can be used as a basis of Social Work program in planning and administering strategies to improve its national passing rates. Discriminant analysis was employed along five academic factors which are Human Behavior and Social Environment (HBSE, Social Work Programs and Policies (SWPP, Social Work Methods (SWM, Field Practice (FP and Grade Point Average (GPA. The analysis generated three significant predictors accounting for 76.22% of between group variability. The function had a hit ratio of 100%. Structure matrix revealed that three cluster subjects were identified as good factors of passing the social work licensure examination: HBSE, SWPP and SWM had a correlation value of 0.713, 0.768 and 0.840, respectively.

  7. Quantization of liver tissue in dual kVp computed tomography using linear discriminant analysis

    Science.gov (United States)

    Tkaczyk, J. Eric; Langan, David; Wu, Xiaoye; Xu, Daniel; Benson, Thomas; Pack, Jed D.; Schmitz, Andrea; Hara, Amy; Palicek, William; Licato, Paul; Leverentz, Jaynne

    2009-02-01

    Linear discriminate analysis (LDA) is applied to dual kVp CT and used for tissue characterization. The potential to quantitatively model both malignant and benign, hypo-intense liver lesions is evaluated by analysis of portal-phase, intravenous CT scan data obtained on human patients. Masses with an a priori classification are mapped to a distribution of points in basis material space. The degree of localization of tissue types in the material basis space is related to both quantum noise and real compositional differences. The density maps are analyzed with LDA and studied with system simulations to differentiate these factors. The discriminant analysis is formulated so as to incorporate the known statistical properties of the data. Effective kVp separation and mAs relates to precision of tissue localization. Bias in the material position is related to the degree of X-ray scatter and partial-volume effect. Experimental data and simulations demonstrate that for single energy (HU) imaging or image-based decomposition pixel values of water-like tissues depend on proximity to other iodine-filled bodies. Beam-hardening errors cause a shift in image value on the scale of that difference sought between in cancerous and cystic lessons. In contrast, projection-based decomposition or its equivalent when implemented on a carefully calibrated system can provide accurate data. On such a system, LDA may provide novel quantitative capabilities for tissue characterization in dual energy CT.

  8. Design, analysis and modeling of a novel hybrid powertrain system based on hybridized automated manual transmission

    Science.gov (United States)

    Wu, Guang; Dong, Zuomin

    2017-09-01

    Hybrid electric vehicles are widely accepted as a promising short to mid-term technical solution due to noticeably improved efficiency and lower emissions at competitive costs. In recent years, various hybrid powertrain systems were proposed and implemented based on different types of conventional transmission. Power-split system, including Toyota Hybrid System and Ford Hybrid System, are well-known examples. However, their relatively low torque capacity, and the drive of alternative and more advanced designs encouraged other innovative hybrid system designs. In this work, a new type of hybrid powertrain system based hybridized automated manual transmission (HAMT) is proposed. By using the concept of torque gap filler (TGF), this new hybrid powertrain type has the potential to overcome issue of torque gap during gearshift. The HAMT design (patent pending) is described in details, from gear layout and design of gear ratios (EV mode and HEV mode) to torque paths at different gears. As an analytical tool, mutli-body model of vehicle equipped with this HAMT was built to analyze powertrain dynamics at various steady and transient modes. A gearshift was decomposed and analyzed based basic modes. Furthermore, a Simulink-SimDriveline hybrid vehicle model was built for the new transmission, driveline and vehicle modular. Control strategy has also been built to harmonically coordinate different powertrain components to realize TGF function. A vehicle launch simulation test has been completed under 30% of accelerator pedal position to reveal details during gearshift. Simulation results showed that this HAMT can eliminate most torque gap that has been persistent issue of traditional AMT, improving both drivability and performance. This work demonstrated a new type of transmission that features high torque capacity, high efficiency and improved drivability.

  9. NBLDA: negative binomial linear discriminant analysis for RNA-Seq data.

    Science.gov (United States)

    Dong, Kai; Zhao, Hongyu; Tong, Tiejun; Wan, Xiang

    2016-09-13

    RNA-sequencing (RNA-Seq) has become a powerful technology to characterize gene expression profiles because it is more accurate and comprehensive than microarrays. Although statistical methods that have been developed for microarray data can be applied to RNA-Seq data, they are not ideal due to the discrete nature of RNA-Seq data. The Poisson distribution and negative binomial distribution are commonly used to model count data. Recently, Witten (Annals Appl Stat 5:2493-2518, 2011) proposed a Poisson linear discriminant analysis for RNA-Seq data. The Poisson assumption may not be as appropriate as the negative binomial distribution when biological replicates are available and in the presence of overdispersion (i.e., when the variance is larger than or equal to the mean). However, it is more complicated to model negative binomial variables because they involve a dispersion parameter that needs to be estimated. In this paper, we propose a negative binomial linear discriminant analysis for RNA-Seq data. By Bayes' rule, we construct the classifier by fitting a negative binomial model, and propose some plug-in rules to estimate the unknown parameters in the classifier. The relationship between the negative binomial classifier and the Poisson classifier is explored, with a numerical investigation of the impact of dispersion on the discriminant score. Simulation results show the superiority of our proposed method. We also analyze two real RNA-Seq data sets to demonstrate the advantages of our method in real-world applications. We have developed a new classifier using the negative binomial model for RNA-seq data classification. Our simulation results show that our proposed classifier has a better performance than existing works. The proposed classifier can serve as an effective tool for classifying RNA-seq data. Based on the comparison results, we have provided some guidelines for scientists to decide which method should be used in the discriminant analysis of RNA-Seq data

  10. Discriminant analysis to predict the occurrence of ELMs in H-mode discharges

    International Nuclear Information System (INIS)

    Kardaun, O.J.W.F.; Itoh, S.; Itoh, K.; Kardaun, J.W.P.F.

    1993-08-01

    After an exposition of its theoretical background, discriminant analysis is applied to the H-mode confinement database to find the region in plasma parameter space in which H-mode with small ELMs (Edge Localized Modes) is likely to occur. The boundary of this region is determined by the condition that the probability of appearance of such a type of H-mode, as a function of the plasma parameters, should be (1) larger than some threshold value and (2) larger than the corresponding probability for other types of H-mode (i.e., H-mode without ELMs or with giant ELMs). In practice, the discrimination has been performed for the ASDEX, JET and JFT-2M tokamaks (a) using four instantaneous plasma parameters (injected power P inj , magnetic field B t , plasma current I p and line averaged electron density (n-bar e ) and (b) taking also memory effects of the plasma and the distance between the plasma and the wall into account, while using variables that are normalised with respect to machine size. Generally speaking, it is found that there is a substantial overlap between the region of H-mode with small ELMs and the region of the two other types of H-mode. However, the ELM-free and the giant ELM H-modes relatively rarely appear in the region, that, according to the analysis, is allocated to small ELMs. A reliable production of H-mode with only small ELMs seems well possible by choosing this regime in parameter space. In the present study, it was not attempted to arrive at a unified discrimination across the machines. So, projection from one machine to another remains difficult, and a reliable determination of the region where small ELMs occur still requires a training sample from the device under consideration. (author) 53 refs

  11. Local analysis of hybrid systems on polyhedral sets with state-dependent switching

    Directory of Open Access Journals (Sweden)

    Leth John

    2014-06-01

    Full Text Available This paper deals with stability analysis of hybrid systems. Various stability concepts related to hybrid systems are introduced. The paper advocates a local analysis. It involves the equivalence relation generated by reset maps of a hybrid system. To establish a tangible method for stability analysis, we introduce the notion of a chart, which locally reduces the complexity of the hybrid system. In a chart, a hybrid system is particularly simple and can be analyzed with the use of methods borrowed from the theory of differential inclusions. Thus, the main contribution of this paper is to show how stability of a hybrid system can be reduced to a specialization of the well established stability theory of differential inclusions. A number of examples illustrate the concepts introduced in the paper.

  12. Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy.

    Science.gov (United States)

    Zhu, Ying; Tan, Tuck Lee

    2016-04-15

    An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

    Science.gov (United States)

    Zhu, Ying; Tan, Tuck Lee

    2016-04-01

    An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects.

  14. Performance Analysis of a Hybrid District Heating System

    DEFF Research Database (Denmark)

    Mikulandric, Robert; Krajačić, Goran; Duic, Neven

    2015-01-01

    Hybridisation of district heating systems can contribute to more efficient heat generation through cogeneration power plants or through the share increase of renewable energy sources in total energy consumption while reducing negative aspects of particular energy source utilisation. In this work......, the performance of a hybrid district energy system for a small town in Croatia has been analysed. Mathematical model for process analysis and optimisation algorithm for optimal system configuration has been developed and described. The main goal of the system optimisation is to reduce heat production costs....... Several energy sources for heat production have been considered in 8 different simulation cases. Simulation results show that the heat production costs could be reduced with introduction of different energy systems into an existing district heating system. Renewable energy based district heating systems...

  15. Functional efficiency comparison between split- and parallel-hybrid using advanced energy flow analysis methods

    Energy Technology Data Exchange (ETDEWEB)

    Guttenberg, Philipp; Lin, Mengyan [Romax Technology, Nottingham (United Kingdom)

    2009-07-01

    The following paper presents a comparative efficiency analysis of the Toyota Prius versus the Honda Insight using advanced Energy Flow Analysis methods. The sample study shows that even very different hybrid concepts like a split- and a parallel-hybrid can be compared in a high level of detail and demonstrates the benefit showing exemplary results. (orig.)

  16. Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

    Science.gov (United States)

    Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

    2015-02-01

    Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides

  17. A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

    Science.gov (United States)

    Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

    2015-12-01

    This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

  18. Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

    Science.gov (United States)

    Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

    2015-01-01

    Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

  19. Forensic analysis of Salvia divinorum using multivariate statistical procedures. Part I: discrimination from related Salvia species.

    Science.gov (United States)

    Willard, Melissa A Bodnar; McGuffin, Victoria L; Smith, Ruth Waddell

    2012-01-01

    Salvia divinorum is a hallucinogenic herb that is internationally regulated. In this study, salvinorin A, the active compound in S. divinorum, was extracted from S. divinorum plant leaves using a 5-min extraction with dichloromethane. Four additional Salvia species (Salvia officinalis, Salvia guaranitica, Salvia splendens, and Salvia nemorosa) were extracted using this procedure, and all extracts were analyzed by gas chromatography-mass spectrometry. Differentiation of S. divinorum from other Salvia species was successful based on visual assessment of the resulting chromatograms. To provide a more objective comparison, the total ion chromatograms (TICs) were subjected to principal components analysis (PCA). Prior to PCA, the TICs were subjected to a series of data pretreatment procedures to minimize non-chemical sources of variance in the data set. Successful discrimination of S. divinorum from the other four Salvia species was possible based on visual assessment of the PCA scores plot. To provide a numerical assessment of the discrimination, a series of statistical procedures such as Euclidean distance measurement, hierarchical cluster analysis, Student's t tests, Wilcoxon rank-sum tests, and Pearson product moment correlation were also applied to the PCA scores. The statistical procedures were then compared to determine the advantages and disadvantages for forensic applications.

  20. Combined use of correlation dimension and entropy as discriminating measures for time series analysis

    Science.gov (United States)

    Harikrishnan, K. P.; Misra, R.; Ambika, G.

    2009-09-01

    We show that the combined use of correlation dimension (D2) and correlation entropy (K2) as discriminating measures can extract a more accurate information regarding the different types of noise present in a time series data. For this, we make use of an algorithmic approach for computing D2 and K2 proposed by us recently [Harikrishnan KP, Misra R, Ambika G, Kembhavi AK. Physica D 2006;215:137; Harikrishnan KP, Ambika G, Misra R. Mod Phys Lett B 2007;21:129; Harikrishnan KP, Misra R, Ambika G. Pramana - J Phys, in press], which is a modification of the standard Grassberger-Proccacia scheme. While the presence of white noise can be easily identified by computing D2 of data and surrogates, K2 is a better discriminating measure to detect colored noise in the data. Analysis of time series from a real world system involving both white and colored noise is presented as evidence. To our knowledge, this is the first time that such a combined analysis is undertaken on a real world data.

  1. Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control

    Science.gov (United States)

    Eshak, Peter B.

    Research efforts have increased in recent years toward the development of intelligent fault tolerant control laws, which are capable of helping the pilot to safely maintain aircraft control at post failure conditions. Researchers at West Virginia University (WVU) have been actively involved in the development of fault tolerant adaptive control laws in all three major categories: direct, indirect, and hybrid. The first implemented design to provide adaptation was a direct adaptive controller, which used artificial neural networks to generate augmentation commands in order to reduce the modeling error. Indirect adaptive laws were implemented in another controller, which utilized online PID to estimate and update the controller parameter. Finally, a new controller design was introduced, which integrated both direct and indirect control laws. This controller is known as hybrid adaptive controller. This last control design outperformed the two earlier designs in terms of less NNs effort and better tracking quality. The performance of online PID has an important role in the quality of the hybrid controller; therefore, the quality of the estimation will be of a great importance. Unfortunately, PID is not perfect and the online estimation process has some inherited issues; the online PID estimates are primarily affected by delays and biases. In order to ensure updating reliable estimates to the controller, the estimator consumes some time to converge. Moreover, the estimator will often converge to a biased value. This thesis conducts a sensitivity analysis for the estimation issues, delay and bias, and their effect on the tracking quality. In addition, the performance of the hybrid controller as compared to direct adaptive controller is explored. In order to serve this purpose, a simulation environment in MATLAB/SIMULINK has been created. The simulation environment is customized to provide the user with the flexibility to add different combinations of biases and delays to

  2. Analysis of cytoplasmic genomes in somatic hybrids between navel orange (Citrus sinensis Osb.) and 'Murcott' tangor.

    Science.gov (United States)

    Kobayashi, S; Ohgawara, T; Fujiwara, K; Oiyama, I

    1991-07-01

    Somatic hybrid plants were produced by protoplast fusion of navel orange and 'Murcott' tangor. Hybridity of the plants was confirmed by the restriction endonuclease analysis of nuclear ribosomal DNA. All of the plants (16 clones) were normal, uniform, and had the amphidiploid chromosome number of 36 (2n=2x=18 for each parent). The cpDNA analysis showed that each of the 16 somatic hybrids contained either one parental chloroplast genome or the other. In all cases, the mitochondrial genomes of the regenerated somatic hybrids were of the navel orange type.

  3. Concept analysis of moral courage in nursing: A hybrid model.

    Science.gov (United States)

    Sadooghiasl, Afsaneh; Parvizy, Soroor; Ebadi, Abbas

    2018-02-01

    Moral courage is one of the most fundamental virtues in the nursing profession, however, little attention has been paid to it. As a result, no exact and clear definition of moral courage has ever been accessible. This study is carried out for the purposes of defining and clarifying its concept in the nursing profession. This study used a hybrid model of concept analysis comprising three phases, namely, a theoretical phase, field work phase, and a final analysis phase. To find relevant literature, electronic search of valid databases was utilized using keywords related to the concept of courage. Field work data were collected over an 11 months' time period from 2013 to 2014. In the field work phase, in-depth interviews were performed with 10 nurses. The conventional content analysis was used in two theoretical and field work phases using Graneheim and Lundman stages, and the results were combined in the final analysis phase. Ethical consideration: Permission for this study was obtained from the ethics committee of Tehran University of Medical Sciences. Oral and written informed consent was received from the participants. From the sum of 750 gained titles in theoretical phase, 26 texts were analyzed. The analysis resulted in 494 codes in text analysis and 226 codes in interview analysis. The literature review in the theoretical phase revealed two features of inherent-transcendental characteristics, two of which possessed a difficult nature. Working in the field phase added moral self-actualization characteristic, rationalism, spiritual beliefs, and scientific-professional qualifications to the feature of the concept. Moral courage is a pure and prominent characteristic of human beings. The antecedents of moral courage include model orientation, model acceptance, rationalism, individual excellence, acquiring academic and professional qualification, spiritual beliefs, organizational support, organizational repression, and internal and external personal barriers

  4. Limit Cycle Analysis in a Class of Hybrid Systems

    Directory of Open Access Journals (Sweden)

    Antonio Favela-Contreras

    2016-01-01

    Full Text Available Hybrid systems are those that inherently combine discrete and continuous dynamics. This paper considers the hybrid system model to be an extension of the discrete automata associating a continuous evolution with each discrete state. This model is called the hybrid automaton. In this work, we achieve a mathematical formulation of the steady state and we show a way to obtain the initial conditions region to reach a specific limit cycle for a class of uncoupled and coupled continuous-linear hybrid systems. The continuous-linear term is used in the sense of the system theory and, in this sense, continuous-linear hybrid automata will be defined. Thus, some properties and theorems that govern the hybrid automata dynamic behavior to evaluate a limit cycle existence have been established; this content is explained under a theoretical framework.

  5. Discrimination Against State and Local Government LGBT Employees: An Analysis of Administrative Complaints

    OpenAIRE

    Mallory, Christy; Sears, Brad

    2014-01-01

    This article documents evidence of recent discrimination against lesbian, gay, bisexual, and transgender (LGBT) public sector workers by analyzing employment discrimination complaints filed with state and local administrative agencies. We present information about 589 complaints of sexual orientation and gender identity discrimination filed by public sector workers in 123 jurisdictions. We find that discrimination against LGBT people in the public sector is pervasive and occurs nearly as freq...

  6. Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics.

    Science.gov (United States)

    Melucci, Dora; Bendini, Alessandra; Tesini, Federica; Barbieri, Sara; Zappi, Alessandro; Vichi, Stefania; Conte, Lanfranco; Gallina Toschi, Tullia

    2016-08-01

    At present, the geographical origin of extra virgin olive oils can be ensured by documented traceability, although chemical analysis may add information that is useful for possible confirmation. This preliminary study investigated the effectiveness of flash gas chromatography electronic nose and multivariate data analysis to perform rapid screening of commercial extra virgin olive oils characterized by a different geographical origin declared in the label. A comparison with solid phase micro extraction coupled to gas chromatography mass spectrometry was also performed. The new method is suitable to verify the geographic origin of extra virgin olive oils based on principal components analysis and discriminant analysis applied to the volatile profile of the headspace as a fingerprint. The selected variables were suitable in discriminating between "100% Italian" and "non-100% Italian" oils. Partial least squares discriminant analysis also allowed prediction of the degree of membership of unknown samples to the classes examined. Copyright © 2016. Published by Elsevier Ltd.

  7. Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

    Directory of Open Access Journals (Sweden)

    I. Crawford

    2015-11-01

    Full Text Available In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4 where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio–hydro–atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen–Rocky Mountain Biogenic Aerosol Study ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the

  8. Analysis of a diesel-electric hybrid urban bus system

    Science.gov (United States)

    Marr, W. W.; Sekar, R. R.; Ahlheim, M. C.

    A hybrid bus powered by a diesel engine and a battery pack was analyzed over an idealized bus-driving cycle in Chicago. Three hybrid configurations, two parallel and one series, were evaluated. The results indicate that the fuel economy of a hybrid bus, taking into account the regenerative braking, is comparable with that of a conventional diesel bus. Life-cycle costs are slightly higher because of the added weight and cost of the battery.

  9. Analysis of chromosome aberration data by hybrid-scale models

    International Nuclear Information System (INIS)

    Indrawati, Iwiq; Kumazawa, Shigeru

    2000-02-01

    This paper presents a new methodology for analyzing data of chromosome aberrations, which is useful to understand the characteristics of dose-response relationships and to construct the calibration curves for the biological dosimetry. The hybrid scale of linear and logarithmic scales brings a particular plotting paper, where the normal section paper, two types of semi-log papers and the log-log paper are continuously connected. The hybrid-hybrid plotting paper may contain nine kinds of linear relationships, and these are conveniently called hybrid scale models. One can systematically select the best-fit model among the nine models by among the conditions for a straight line of data points. A biological interpretation is possible with some hybrid-scale models. In this report, the hybrid scale models were applied to separately reported data on chromosome aberrations in human lymphocytes as well as on chromosome breaks in Tradescantia. The results proved that the proposed models fit the data better than the linear-quadratic model, despite the demerit of the increased number of model parameters. We showed that the hybrid-hybrid model (both variables of dose and response using the hybrid scale) provides the best-fit straight lines to be used as the reliable and readable calibration curves of chromosome aberrations. (author)

  10. Colored inks analysis and differentiation: A first step in artistic contemporary prints discrimination

    International Nuclear Information System (INIS)

    Vila, Anna; Ferrer, Nuria; Garcia, Jose F.

    2007-01-01

    Prints are the most popular artistic technique. Due to their manufacturing procedure, they are also one of the most frequently falsified types of artwork. In terms of their economic and historic value, the chemical analysis and characterisation of coloured inks and their principal constituent materials (pigments), together with the historical and aesthetic information available in the Catalogues Raisonees, are important tools in distinguishing originals from non-original prints. The chemical characterisation and discrimination of coloured inks has test in this study. Analysis using Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM) and X-ray diffraction (XRD) has been done on blue pigments and inks, due to this colour is one of the most representative for the presence of organic and inorganic materials in their composition. Conclusion obtained for this colour would demonstrate the capability of the approach when it is applied to any other coloured set of inks

  11. Bioelectric signal classification using a recurrent probabilistic neural network with time-series discriminant component analysis.

    Science.gov (United States)

    Hayashi, Hideaki; Shima, Keisuke; Shibanoki, Taro; Kurita, Yuichi; Tsuji, Toshio

    2013-01-01

    This paper outlines a probabilistic neural network developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower-dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model that incorporates a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into a neural network so that parameters can be obtained appropriately as network coefficients according to backpropagation-through-time-based training algorithm. The network is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. In the experiments conducted during the study, the validity of the proposed network was demonstrated for EEG signals.

  12. Colored inks analysis and differentiation: A first step in artistic contemporary prints discrimination

    Energy Technology Data Exchange (ETDEWEB)

    Vila, Anna [Department de Pintura, Conservacio-Restauracio, Facultat de Belles Arts, Universitat de Barcelona, C/Pau Gargallo 4, 08028 Barcelona (Spain)]. E-mail: avila@sct.ub.es; Ferrer, Nuria [Serveis Cientificotecnics, Universitat de Barcelona, C/Lluis Sole i Sabaris 1, 08028 Barcelona (Spain)]. E-mail: nferrer@sctub.es; Garcia, Jose F. [Department de Pintura, Conservacio-Restauracio, Facultat de Belles Arts, Universitat de Barcelona, C/Pau Gargallo 4, 08028 Barcelona (Spain)]. E-mail: ifgarcia@ub.edu

    2007-04-04

    Prints are the most popular artistic technique. Due to their manufacturing procedure, they are also one of the most frequently falsified types of artwork. In terms of their economic and historic value, the chemical analysis and characterisation of coloured inks and their principal constituent materials (pigments), together with the historical and aesthetic information available in the Catalogues Raisonees, are important tools in distinguishing originals from non-original prints. The chemical characterisation and discrimination of coloured inks has test in this study. Analysis using Fourier transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM) and X-ray diffraction (XRD) has been done on blue pigments and inks, due to this colour is one of the most representative for the presence of organic and inorganic materials in their composition. Conclusion obtained for this colour would demonstrate the capability of the approach when it is applied to any other coloured set of inks.

  13. Discrimination of Aurantii Fructus Immaturus and Fructus Poniciri Trifoliatae Immaturus by Flow Injection UV Spectroscopy (FIUV) and 1H NMR using Partial Least-squares Discriminant Analysis (PLS-DA)

    Science.gov (United States)

    Two simple fingerprinting methods, flow-injection UV spectroscopy (FIUV) and 1H nuclear magnetic resonance (NMR), for discrimination of Aurantii FructusImmaturus and Fructus Poniciri TrifoliataeImmaturususing were described. Both methods were combined with partial least-squares discriminant analysis...

  14. Promises of silent salesman to the FMCG industry: an investigation using linear discriminant analysis approach

    Directory of Open Access Journals (Sweden)

    Shekhar Suraj Kushe

    2015-12-01

    Full Text Available Packaging which is often called as the ‘silent salesman’ is an important component of marketing. Today the importance of packaging has risen to such an extent that product packaging is rightly called as the fifth ‘P’ of marketing mix. FMCG are products which are utilized by large number of people. The present study examined the discriminating power of five selected FMCG packaging variables namely ‘picture’, ‘colour’, ‘size’, ‘shape’ and ‘material’ amidst those who purchased FMCG based on these packaging variables and for those who purchased FMCG not based on these packaging variables. Descriptive research was carried out in the study. Respondents (students were asked to rate four packaging variable on a five point Likert’s scale. Discriminant analysis showed that only two variables namely ‘Colour’ (.706 and ‘Shape’ (–.527 were good predictors. Variables ‘Picture’, ‘size’ and ‘material’ were considered as poor predictors as far as the student communities were considered. The cross validated classification showed that out of the 240 samples drawn, 91.8% of the cases were correctly classified.

  15. Image analysis of food particles can discriminate deficient mastication of mixed foodstuffs simulating daily meal.

    Science.gov (United States)

    Sugimoto, K; Hashimoto, Y; Fukuike, C; Kodama, N; Minagi, S

    2014-03-01

    Because food texture is regarded as an important factor for smooth deglutition, identification of objective parameters that could provide a basis for food texture selection for elderly or dysphagic patients is of great importance. We aimed to develop an objective evaluation method of mastication using a mixed test food comprising foodstuffs, simulating daily dietary life. The particle size distribution (>2 mm in diameter) in a bolus was analysed using a digital image under dark-field illumination. Ten female participants (mean age ± s.d., 27·6 ± 2·6 years) masticated a mixed test food comprising prescribed amounts of rice, sausage, hard omelette, raw cabbage and raw cucumber with 100%, 75%, 50% and 25% of the number of their masticatory strokes. A single set of coefficient thresholds of 0·10 for the homogeneity index and 1·62 for the particle size index showed excellent discrimination of deficient masticatory conditions with high sensitivity (0·90) and specificity (0·77). Based on the results of this study, normal mastication was discriminated from deficient masticatory conditions using a large particle analysis of mixed foodstuffs, thus showing the possibility of future application of this method for objective decision-making regarding the properties of meals served to dysphagic patients. © 2014 John Wiley & Sons Ltd.

  16. Two-Stage Regularized Linear Discriminant Analysis for 2-D Data.

    Science.gov (United States)

    Zhao, Jianhua; Shi, Lei; Zhu, Ji

    2015-08-01

    Fisher linear discriminant analysis (LDA) involves within-class and between-class covariance matrices. For 2-D data such as images, regularized LDA (RLDA) can improve LDA due to the regularized eigenvalues of the estimated within-class matrix. However, it fails to consider the eigenvectors and the estimated between-class matrix. To improve these two matrices simultaneously, we propose in this paper a new two-stage method for 2-D data, namely a bidirectional LDA (BLDA) in the first stage and the RLDA in the second stage, where both BLDA and RLDA are based on the Fisher criterion that tackles correlation. BLDA performs the LDA under special separable covariance constraints that incorporate the row and column correlations inherent in 2-D data. The main novelty is that we propose a simple but effective statistical test to determine the subspace dimensionality in the first stage. As a result, the first stage reduces the dimensionality substantially while keeping the significant discriminant information in the data. This enables the second stage to perform RLDA in a much lower dimensional subspace, and thus improves the two estimated matrices simultaneously. Experiments on a number of 2-D synthetic and real-world data sets show that BLDA+RLDA outperforms several closely related competitors.

  17. A New Method for Improving the Discrimination Power and Weights Dispersion in the Data Envelopment Analysis

    Directory of Open Access Journals (Sweden)

    S. Kordrostami

    2013-06-01

    Full Text Available The appropriate choice of input-output weights is necessary to have a successful DEA model. Generally, if the number of DMUs i.e., n, is less than number of inputs and outputs i.e., m+s, then many of DMUs are introduced as efficient then the discrimination between DMUs is not possible. Besides, DEA models are free to choose the best weights. For resolving the problems that are resulted from freedom of weights, some constraints are set on the input-output weights. Symmetric weight constraints are a kind of weight constrains. In this paper, we represent a new model based on a multi-criterion data envelopment analysis (MCDEA are developed to moderate the homogeneity of weights distribution by using symmetric weight constrains.Consequently, we show that the improvement of the dispersal of unrealistic input-output weights and the increasing discrimination power for our suggested models. Finally, as an application of the new model, we use this model to evaluate and ranking guilan selected hospitals.

  18. Forensic analysis of explosives using isotope ratio mass spectrometry (IRMS)--discrimination of ammonium nitrate sources.

    Science.gov (United States)

    Benson, Sarah J; Lennard, Christopher J; Maynard, Philip; Hill, David M; Andrew, Anita S; Roux, Claude

    2009-06-01

    An evaluation was undertaken to determine if isotope ratio mass spectrometry (IRMS) could assist in the investigation of complex forensic cases by providing a level of discrimination not achievable utilising traditional forensic techniques. The focus of the research was on ammonium nitrate (AN), a common oxidiser used in improvised explosive mixtures. The potential value of IRMS to attribute Australian AN samples to the manufacturing source was demonstrated through the development of a preliminary AN classification scheme based on nitrogen isotopes. Although the discrimination utilising nitrogen isotopes alone was limited and only relevant to samples from the three Australian manufacturers during the evaluated time period, the classification scheme has potential as an investigative aid. Combining oxygen and hydrogen stable isotope values permitted the differentiation of AN prills from three different Australian manufacturers. Samples from five different overseas sources could be differentiated utilising a combination of the nitrogen, oxygen and hydrogen isotope values. Limited differentiation between Australian and overseas prills was achieved for the samples analysed. The comparison of nitrogen isotope values from intact AN prill samples with those from post-blast AN prill residues highlighted that the nitrogen isotopic composition of the prills was not maintained post-blast; hence, limiting the technique to analysis of un-reacted explosive material.

  19. Hyperspectral image analysis for rapid and accurate discrimination of bacterial infections: A benchmark study.

    Science.gov (United States)

    Arrigoni, Simone; Turra, Giovanni; Signoroni, Alberto

    2017-09-01

    With the rapid diffusion of Full Laboratory Automation systems, Clinical Microbiology is currently experiencing a new digital revolution. The ability to capture and process large amounts of visual data from microbiological specimen processing enables the definition of completely new objectives. These include the direct identification of pathogens growing on culturing plates, with expected improvements in rapid definition of the right treatment for patients affected by bacterial infections. In this framework, the synergies between light spectroscopy and image analysis, offered by hyperspectral imaging, are of prominent interest. This leads us to assess the feasibility of a reliable and rapid discrimination of pathogens through the classification of their spectral signatures extracted from hyperspectral image acquisitions of bacteria colonies growing on blood agar plates. We designed and implemented the whole data acquisition and processing pipeline and performed a comprehensive comparison among 40 combinations of different data preprocessing and classification techniques. High discrimination performance has been achieved also thanks to improved colony segmentation and spectral signature extraction. Experimental results reveal the high accuracy and suitability of the proposed approach, driving the selection of most suitable and scalable classification pipelines and stimulating clinical validations. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Bearing Performance Degradation Assessment Using Linear Discriminant Analysis and Coupled HMM

    International Nuclear Information System (INIS)

    Liu, T; Chen, J; Zhou, X N; Xiao, W B

    2012-01-01

    Bearing is one of the most important units in rotary machinery, its performance may vary significantly under different working stages. Thus it is critical to choose the most effective features for bearing performance degradation prediction. Linear Discriminant Analysis (LDA) is a useful method in finding few feature's dimensions that best discriminate a set of features extracted from original vibration signals. Another challenge in bearing performance degradation is how to build a model to recognize the different conditions with the data coming from different monitoring channels. In this paper, coupled hidden Markov models (CHMM) is presented to model interacting processes which can overcome the defections of the HMM. Because the input data in CHMM are collected by several sensors, and the interacting information can be fused by coupled modalities, it is more effective than HMM which used only one state chain. The model can be used in estimating the bearing performance degradation states according to several observation data. When becoming degradation pattern recognition, the new observation features should be input into the pre-trained CHMM and calculate the performance index (PI) of the outputs, the changing of PI could be used to describe the different degradation level of the bearings. The results show that PI will decline with the increase of the bearing degradation. Assessment results of the whole life time experimental bearing signals validate the feasibility and effectiveness of this method.

  1. Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Nathalie André

    2018-01-01

    Full Text Available Background. Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Methods. Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. Results. A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers’ self-efficacy, internal memory, and attentional control strategies of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. Conclusions. This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control, to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging.

  2. Is it really organic? – Multi-isotopic analysis as a tool to discriminate between organic and conventional plants

    DEFF Research Database (Denmark)

    Laursen, K.H.; Mihailova, A.; Kelly, S.D.

    2013-01-01

    for discrimination of organically and conventionally grown plants. The study was based on wheat, barley, faba bean and potato produced in rigorously controlled long-term field trials comprising 144 experimental plots. Nitrogen isotope analysis revealed the use of animal manure, but was unable to discriminate between......Novel procedures for analytical authentication of organic plant products are urgently needed. Here we present the first study encompassing stable isotopes of hydrogen, carbon, nitrogen, oxygen, magnesium and sulphur as well as compound-specific nitrogen and oxygen isotope analysis of nitrate...... plants that were fertilised with synthetic nitrogen fertilisers or green manures from atmospheric nitrogen fixing legumes. This limitation was bypassed using oxygen isotope analysis of nitrate in potato tubers, while hydrogen isotope analysis allowed complete discrimination of organic and conventional...

  3. Analysis of load balance in hybrid partitioning | Talib | Botswana ...

    African Journals Online (AJOL)

    In information retrieval systems, there are three types of index partitioning schemes - term partitioning, document partitioning, and hybrid partitioning. The hybrid-partitioning scheme combines both term and document partitioning schemes. Term partitioning provides high concurrency, which means that queries can be ...

  4. Simultaneous thermal analysis and thermodilatometry of hybrid fiber reinforced UHPC

    Science.gov (United States)

    Scheinherrová, Lenka; Fořt, Jan; Pavlík, Zbyšek; Černý, Robert

    2017-07-01

    Development of concrete technology and the availability of variety of materials such as silica fume, mineral microfillers and high-range water-reducing admixtures make possible to produce Ultra-High Performance Concrete (UHPC) with compressive strength higher than 160 MPa. However, UHPC is prone to spall under high temperatures what limits its use for special applications only, such as offshore and marine structures, industrial floors, security barriers etc. The spalling is caused by the thermal stresses due to the temperature gradient during heating, and by the splitting force owing to the release of water vapour. Hybrid fibre reinforcement based on combination of steel and polymer fibres is generally accepted by concrete community as a functional solution preventing spalling. In this way, Ultra-High Performance Fibre Reinforced Concrete (UHPFRC) is produced possessing high mechanical strength, durability and resistance to water and salt ingress. Since UHPFRC find use in construction industry in tunnel linings, precast tunnel segments, and high-rise buildings, its behaviour during the high-temperature exposure and its residual parameters are of the particular importance. On this account, Simultaneous Thermal Analysis (STA) and Thermodilatometry Analysis (TDA) were done in the paper to identify the structural and chemical changes in UHPFRC during its high-temperature load. Based on the experimental results, several physical and chemical processes that studied material underwent at high-temperatures were recognized. The obtained data revealed changes in the composition of the studied material and allowed identification of critical temperatures for material damage.

  5. Design Method and Cost-Benefit Analysis of Hybrid Fiber Used in Asphalt Concrete

    Directory of Open Access Journals (Sweden)

    Haiwei Zhang

    2016-01-01

    Full Text Available Fiber, as an additive, can improve the performance of asphalt concrete and be widely studied, but only a few works have been done for hybrid fiber. This paper presents a new and convenient method to design hybrid fiber and verifies hybrid fiber’s superiority in asphalt pavement engineering. Firstly, this paper expounds the design method used as its applied example with the hybrid fiber composed of lignin, polyester, and polypropylene fibers. In this method, a direct shear device (DSD is used to measure the shear damage energy density (SDED of hybrid fiber modified asphalts, and range and variance statistical analysis are applied to determine the composition proportion of hybrid fiber. Then, the engineering property of hybrid fiber reinforced asphalt concrete (AC-13 is investigated. Finally, a cost-benefit model is developed to analyze the advantage of hybrid fiber compared to single fibers. The results show that the design method employed in this paper can offer a beneficial reference. A combination of 1.8% of lignin fiber and 2.4% of polyester fiber plus 3.0% polypropylene fiber presented the best reinforcement of the hybrid fiber. The cost-benefit model verifies that the hybrid fiber can bring about comprehensive pavement performance and good economy.

  6. On Kolmogorov asymptotics of estimators of the misclassification error rate in linear discriminant analysis

    KAUST Repository

    Zollanvari, Amin

    2013-05-24

    We provide a fundamental theorem that can be used in conjunction with Kolmogorov asymptotic conditions to derive the first moments of well-known estimators of the actual error rate in linear discriminant analysis of a multivariate Gaussian model under the assumption of a common known covariance matrix. The estimators studied in this paper are plug-in and smoothed resubstitution error estimators, both of which have not been studied before under Kolmogorov asymptotic conditions. As a result of this work, we present an optimal smoothing parameter that makes the smoothed resubstitution an unbiased estimator of the true error. For the sake of completeness, we further show how to utilize the presented fundamental theorem to achieve several previously reported results, namely the first moment of the resubstitution estimator and the actual error rate. We provide numerical examples to show the accuracy of the succeeding finite sample approximations in situations where the number of dimensions is comparable or even larger than the sample size.

  7. A discrimination technique for extensive air showers based on multiscale, lacunarity and neural network analysis

    International Nuclear Information System (INIS)

    Pagliaro, Antonio; D'Ali Staiti, G.; D'Anna, F.

    2011-01-01

    We present a new method for the identification of extensive air showers initiated by different primaries. The method uses the multiscale concept and is based on the analysis of multifractal behaviour and lacunarity of secondary particle distributions together with a properly designed and trained artificial neural network. In the present work the method is discussed and applied to a set of fully simulated vertical showers, in the experimental framework of ARGO-YBJ, to obtain hadron to gamma primary separation. We show that the presented approach gives very good results, leading, in the 1-10 TeV energy range, to a clear improvement of the discrimination power with respect to the existing figures for extended shower detectors.

  8. Detection of feigned mental disorders on the personality assessment inventory: a discriminant analysis.

    Science.gov (United States)

    Rogers, R; Sewell, K W; Morey, L C; Ustad, K L

    1996-12-01

    Psychological assessment with multiscale inventories is largely dependent on the honesty and forthrightness of those persons evaluated. We investigated the effectiveness of the Personality Assessment Inventory (PAI) in detecting participants feigning three specific disorders: schizophrenia, major depression, and generalized anxiety disorder. With a simulation design, we tested the PAI validity scales on 166 naive (undergraduates with minimal preparation) and 80 sophisticated (doctoral psychology students with 1 week preparation) participants. We compared their results to persons with the designated disorders: schizophrenia (n = 45), major depression (n = 136), and generalized anxiety disorder (n = 40). Although moderately effective with naive simulators, the validity scales evidenced only modest positive predictive power with their sophisticated counterparts. Therefore, we performed a two-stage discriminant analysis that yielded a moderately high hit rate (> 80%) that was maintained in the cross-validation sample, irrespective of the feigned disorder or the sophistication of the simulators.

  9. Quantitative Classification of Quartz by Laser Induced Breakdown Spectroscopy in Conjunction with Discriminant Function Analysis

    Directory of Open Access Journals (Sweden)

    A. Ali

    2016-01-01

    Full Text Available A responsive laser induced breakdown spectroscopic system was developed and improved for utilizing it as a sensor for the classification of quartz samples on the basis of trace elements present in the acquired samples. Laser induced breakdown spectroscopy (LIBS in conjunction with discriminant function analysis (DFA was applied for the classification of five different types of quartz samples. The quartz plasmas were produced at ambient pressure using Nd:YAG laser at fundamental harmonic mode (1064 nm. We optimized the detection system by finding the suitable delay time of the laser excitation. This is the first study, where the developed technique (LIBS+DFA was successfully employed to probe and confirm the elemental composition of quartz samples.

  10. On Kolmogorov asymptotics of estimators of the misclassification error rate in linear discriminant analysis

    KAUST Repository

    Zollanvari, Amin; Genton, Marc G.

    2013-01-01

    We provide a fundamental theorem that can be used in conjunction with Kolmogorov asymptotic conditions to derive the first moments of well-known estimators of the actual error rate in linear discriminant analysis of a multivariate Gaussian model under the assumption of a common known covariance matrix. The estimators studied in this paper are plug-in and smoothed resubstitution error estimators, both of which have not been studied before under Kolmogorov asymptotic conditions. As a result of this work, we present an optimal smoothing parameter that makes the smoothed resubstitution an unbiased estimator of the true error. For the sake of completeness, we further show how to utilize the presented fundamental theorem to achieve several previously reported results, namely the first moment of the resubstitution estimator and the actual error rate. We provide numerical examples to show the accuracy of the succeeding finite sample approximations in situations where the number of dimensions is comparable or even larger than the sample size.

  11. Non-destructive Testing of Wood Defects Based on Discriminant Analysis Method

    Directory of Open Access Journals (Sweden)

    Wenshu LIN

    2015-09-01

    Full Text Available The defects of wood samples were tested by the technique of stress wave and ultrasonic technology, and the testing results were comparatively analyzed by using the Fisher discriminant analysis in the statistic software of SPSS. The differences of defect detection sensitivity and accuracy for stress wave and ultrasonic under different wood properties and defects were concluded. Therefore, in practical applications, according to different situations the corresponding wood non- destructive testing method should be used, or the two detection methods are applied at the same time in order to compensate for its shortcomings with each other to improve the ability to distinguish the timber defects. The results can provide a reference for further improvement of the reliability of timber defects detection.

  12. Photospheric Magnetic Field Properties of Flaring versus Flare-quiet Active Regions. II. Discriminant Analysis

    Science.gov (United States)

    Leka, K. D.; Barnes, G.

    2003-10-01

    We apply statistical tests based on discriminant analysis to the wide range of photospheric magnetic parameters described in a companion paper by Leka & Barnes, with the goal of identifying those properties that are important for the production of energetic events such as solar flares. The photospheric vector magnetic field data from the University of Hawai'i Imaging Vector Magnetograph are well sampled both temporally and spatially, and we include here data covering 24 flare-event and flare-quiet epochs taken from seven active regions. The mean value and rate of change of each magnetic parameter are treated as separate variables, thus evaluating both the parameter's state and its evolution, to determine which properties are associated with flaring. Considering single variables first, Hotelling's T2-tests show small statistical differences between flare-producing and flare-quiet epochs. Even pairs of variables considered simultaneously, which do show a statistical difference for a number of properties, have high error rates, implying a large degree of overlap of the samples. To better distinguish between flare-producing and flare-quiet populations, larger numbers of variables are simultaneously considered; lower error rates result, but no unique combination of variables is clearly the best discriminator. The sample size is too small to directly compare the predictive power of large numbers of variables simultaneously. Instead, we rank all possible four-variable permutations based on Hotelling's T2-test and look for the most frequently appearing variables in the best permutations, with the interpretation that they are most likely to be associated with flaring. These variables include an increasing kurtosis of the twist parameter and a larger standard deviation of the twist parameter, but a smaller standard deviation of the distribution of the horizontal shear angle and a horizontal field that has a smaller standard deviation but a larger kurtosis. To support the

  13. Overall energy, exergy and carbon credit analysis by different type of hybrid photovoltaic thermal air collectors

    International Nuclear Information System (INIS)

    Agrawal, Sanjay; Tiwari, G.N.

    2013-01-01

    Highlights: ► Comparative study of PVT air collectors. ► CO 2 analysis of all type of PVT air collectors. ► Study of thermal energy, exergy gain and exergy efficiency. ► Exergy efficiency of unglazed hybrid PVT tiles air collector is most efficient. - Abstract: In this paper, comparative analysis of different type of photovoltaic thermal (PVT) air collector namely: (i) unglazed hybrid PVT tiles, (ii) glazed hybrid PVT tiles and (iii) conventional hybrid PVT air collectors have been carried out for the composite climate of Srinagar (India). The comparative study has been carried out in terms of overall thermal energy and exergy gain, exergy efficiency and carbon credit earned by different type of hybrid PVT air collectors. It has been observed that overall annual thermal energy and exergy gain of unglazed hybrid PVT tiles air collector is higher by 27% and 29.3% respectively as compared to glazed hybrid PVT tiles air collector and by 61% and 59.8% respectively as compared to conventional hybrid PVT air collector. It has also been observed that overall annual exergy efficiency of unglazed and glazed hybrid PVT tiles air collector is higher by 9.6% and 53.8% respectively as compared to conventional hybrid PVT air collector. On the basis of comparative study, it has been concluded that CO 2 emission reduction per annum on the basis of overall thermal energy gain of unglazed and glazed hybrid PVT tiles air collector is higher by 62.3% and 27.7% respectively as compared to conventional hybrid PVT air collector and on the basis of overall exergy gain it is 59.7% and 22.7%.

  14. A longitudinal analysis of Hispanic youth acculturation and cigarette smoking: the roles of gender, culture, family, and discrimination.

    Science.gov (United States)

    Lorenzo-Blanco, Elma I; Unger, Jennifer B; Ritt-Olson, Anamara; Soto, Daniel; Baezconde-Garbanati, Lourdes

    2013-05-01

    Risk for smoking initiation increases as Hispanic youth acculturate to U.S. society, and this association seems to be stronger for Hispanic girls than boys. To better understand the influence of culture, family, and everyday discrimination on cigarette smoking, we tested a process-oriented model of acculturation and cigarette smoking. Data came from Project RED (Reteniendo y Entendiendo Diversidad para Salud), which included 1,436 Hispanic students (54% girls) from Southern California. We used data from 9th to 11th grade (85% were 14 years old, and 86% were U.S. born) to test the influence of acculturation-related experiences on smoking over time. Multigroup structural equation analysis suggested that acculturation was associated with increased familismo and lower traditional gender roles, and enculturation was linked more with familismo and respeto. Familismo, respeto, and traditional gender roles were linked with lower family conflict and increased family cohesion, and these links were stronger for girls. Familismo and respeto were further associated with lower discrimination. Conversely, fatalismo was linked with worse family functioning (especially for boys) and increased discrimination in both the groups. Discrimination was the only predictor of smoking for boys and girls. In all, the results of the current study indicate that reducing discrimination and helping youth cope with discrimination may prevent or reduce smoking in Hispanic boys and girls. This may be achieved by promoting familismo and respeto and by discouraging fatalistic beliefs.

  15. A Longitudinal Analysis of Hispanic Youth Acculturation and Cigarette Smoking: The Roles of Gender, Culture, Family, and Discrimination

    Science.gov (United States)

    2013-01-01

    Introduction: Risk for smoking initiation increases as Hispanic youth acculturate to U.S. society, and this association seems to be stronger for Hispanic girls than boys. To better understand the influence of culture, family, and everyday discrimination on cigarette smoking, we tested a process-oriented model of acculturation and cigarette smoking. Methods: Data came from Project RED (Reteniendo y Entendiendo Diversidad para Salud), which included 1,436 Hispanic students (54% girls) from Southern California. We used data from 9th to 11th grade (85% were 14 years old, and 86% were U.S. born) to test the influence of acculturation-related experiences on smoking over time. Results: Multigroup structural equation analysis suggested that acculturation was associated with increased familismo and lower traditional gender roles, and enculturation was linked more with familismo and respeto. Familismo, respeto, and traditional gender roles were linked with lower family conflict and increased family cohesion, and these links were stronger for girls. Familismo and respeto were further associated with lower discrimination. Conversely, fatalismo was linked with worse family functioning (especially for boys) and increased discrimination in both the groups. Discrimination was the only predictor of smoking for boys and girls. Conclusions: In all, the results of the current study indicate that reducing discrimination and helping youth cope with discrimination may prevent or reduce smoking in Hispanic boys and girls. This may be achieved by promoting familismo and respeto and by discouraging fatalistic beliefs. PMID:23109671

  16. Performance analysis of switching based hybrid FSO/RF transmission

    KAUST Repository

    Usman, Muneer

    2014-09-01

    Hybrid free space optical (FSO)/ radio frequency (RF) systems have emerged as a promising solution for high data rate wireless back haul.We present and analyze a switching based transmission scheme for hybrid FSO/RF system. Specifically, either FSO or RF link will be active at a certain time instance, with FSO link enjoying a higher priority. Analytical expressions have been obtained for the outage probability, average bit error rate and ergodic capacity for the resulting system. Numerical examples are presented to compare the performance of the hybrid scheme with FSO only scenario.

  17. Performance analysis of switching based hybrid FSO/RF transmission

    KAUST Repository

    Usman, Muneer; Yang, Hongchuan; Alouini, Mohamed-Slim

    2014-01-01

    Hybrid free space optical (FSO)/ radio frequency (RF) systems have emerged as a promising solution for high data rate wireless back haul.We present and analyze a switching based transmission scheme for hybrid FSO/RF system. Specifically, either FSO or RF link will be active at a certain time instance, with FSO link enjoying a higher priority. Analytical expressions have been obtained for the outage probability, average bit error rate and ergodic capacity for the resulting system. Numerical examples are presented to compare the performance of the hybrid scheme with FSO only scenario.

  18. The Analysis of the Ethnical Discrimination on the Manpower’s Market under the Economical Crisis

    Directory of Open Access Journals (Sweden)

    Mihaela Hrisanta DOBRE

    2012-06-01

    Full Text Available Discrimination means any difference, exclusion, restriction, preference or different treatment that brings forth disadvantages for a person or a group as compared to other ones that are in similar situations. The reasons on which discrimination is based can be various, such as race, nationality, ethnics, religion, gender, sexual orientation, language, age, disabilities etc. and in this case we talk about multiple discrimination. In Romania the main forms of discrimination are linked to ethnics and to sexual appurtenance. Within this column we analysed the discrimination amongst the Romany ethnics people, according to a statistical investigation (Access onto the Labour Market – A Chance for You, the research goal being to identify the answer to the following questions: Is there any discrimination inside the Romany ethnic group? What is the correlation between their level of education and their income? What is the correlation between the level of education of the parents and the respondent’s?

  19. Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options

    Science.gov (United States)

    Quanbao, Jiang; Marcus W., Feldman

    2013-01-01

    The large number of missing females in China, a consequence of gender discrimination, is having and will continue to have a profound effect on the country's population development. In this paper, we analyze the causes of this gender discrimination in terms of institutions, culture and, economy, and suggest public policies that might help eliminate gender discrimination. Using a population simulation model, we study the effect of public policies on the sex ratio at birth and excess female child mortality, and the effect of gender discrimination on China's population development. We find that gender discrimination will decrease China's population size, number of births, and working age population, accelerate population aging and exacerbate the male marriage squeeze. These results provide theoretical support for suggesting that the government enact and implement public policies aimed at eliminating gender discrimination. PMID:24363477

  20. Phonological experience modulates voice discrimination: Evidence from functional brain networks analysis.

    Science.gov (United States)

    Hu, Xueping; Wang, Xiangpeng; Gu, Yan; Luo, Pei; Yin, Shouhang; Wang, Lijun; Fu, Chao; Qiao, Lei; Du, Yi; Chen, Antao

    2017-10-01

    Numerous behavioral studies have found a modulation effect of phonological experience on voice discrimination. However, the neural substrates underpinning this phenomenon are poorly understood. Here we manipulated language familiarity to test the hypothesis that phonological experience affects voice discrimination via mediating the engagement of multiple perceptual and cognitive resources. The results showed that during voice discrimination, the activation of several prefrontal regions was modulated by language familiarity. More importantly, the same effect was observed concerning the functional connectivity from the fronto-parietal network to the voice-identity network (VIN), and from the default mode network to the VIN. Our findings indicate that phonological experience could bias the recruitment of cognitive control and information retrieval/comparison processes during voice discrimination. Therefore, the study unravels the neural substrates subserving the modulation effect of phonological experience on voice discrimination, and provides new insights into studying voice discrimination from the perspective of network interactions. Copyright © 2017. Published by Elsevier Inc.

  1. Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options.

    Science.gov (United States)

    Quanbao, Jiang; Shuzhuo, Li; Marcus W, Feldman

    2011-08-01

    The large number of missing females in China, a consequence of gender discrimination, is having and will continue to have a profound effect on the country's population development. In this paper, we analyze the causes of this gender discrimination in terms of institutions, culture and, economy, and suggest public policies that might help eliminate gender discrimination. Using a population simulation model, we study the effect of public policies on the sex ratio at birth and excess female child mortality, and the effect of gender discrimination on China's population development. We find that gender discrimination will decrease China's population size, number of births, and working age population, accelerate population aging and exacerbate the male marriage squeeze. These results provide theoretical support for suggesting that the government enact and implement public policies aimed at eliminating gender discrimination.

  2. Hybrid scintillators for neutron discrimination

    Science.gov (United States)

    Feng, Patrick L; Cordaro, Joseph G; Anstey, Mitchell R; Morales, Alfredo M

    2015-05-12

    A composition capable of producing a unique scintillation response to neutrons and gamma rays, comprising (i) at least one surfactant; (ii) a polar hydrogen-bonding solvent; and (iii) at least one luminophore. A method including combining at least one surfactant, a polar hydrogen-bonding solvent and at least one luminophore in a scintillation cell under vacuum or an inert atmosphere.

  3. Discrimination in relation to parenthood reported by community psychiatric service users in the UK: a framework analysis.

    Science.gov (United States)

    Jeffery, Debra; Clement, Sarah; Corker, Elizabeth; Howard, Louise M; Murray, Joanna; Thornicroft, Graham

    2013-04-20

    Experienced discrimination refers to an individual's perception that they have been treated unfairly due to an attribute and is an important recent focus within stigma research. A significant proportion of mental health service users report experiencing mental illness-based discrimination in relation to parenthood. Existing studies in this area have not gone beyond prevalence, therefore little is known about the nature of experienced discrimination in relation to parenthood, and how is it constituted. This study aims to generate a typology of community psychiatric service users' reports of mental illness-based discrimination in relation to becoming or being a parent. A secondary aim is to assess the prevalence of these types of experienced discrimination. In a telephone survey 2026 community psychiatric service users in ten UK Mental Health service provider organisations (Trusts) were asked about discrimination experienced in the previous 12 months using the Discrimination and Stigma Scale (DISC). The sample were asked if, due to their mental health problem, they had been treated unfairly in starting a family, or in their role as a parent, and gave examples of this. Prevalence is reported and the examples of experienced discrimination in relation to parenthood were analysed using the framework method of qualitative analysis. Three hundred and four participants (73% female) reported experienced discrimination, with prevalences of 22.5% and 28.3% for starting a family and for the parenting role respectively. Participants gave 89 examples of discrimination about starting a family and 228 about parenting, and these occurred in social and professional contexts. Ten themes were identified. These related to being seen as an unfit parent; people not being understanding; being stopped from having children; not being allowed to see their children; not getting the support needed; children being affected; children avoiding their parents; children's difficulties being blamed

  4. Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

    Science.gov (United States)

    Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

    1984-01-01

    An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.

  5. Statistical analysis for discrimination of prompt gamma ray peak induced by high energy neutron: Monte Carlo simulation study

    International Nuclear Information System (INIS)

    Do-Kun Yoon; Joo-Young Jung; Tae Suk Suh; Seong-Min Han

    2015-01-01

    The purpose of this research is a statistical analysis for discrimination of prompt gamma ray peak induced by the 14.1 MeV neutron particles from spectra using Monte Carlo simulation. For the simulation, the information of 18 detector materials was used to simulate spectra by the neutron capture reaction. The discrimination of nine prompt gamma ray peaks from the simulation of each detector material was performed. We presented the several comparison indexes of energy resolution performance depending on the detector material using the simulation and statistics for the prompt gamma activation analysis. (author)

  6. Computational analysis on plug-in hybrid electric motorcycle chassis

    Science.gov (United States)

    Teoh, S. J.; Bakar, R. A.; Gan, L. M.

    2013-12-01

    Plug-in hybrid electric motorcycle (PHEM) is an alternative to promote sustainability lower emissions. However, the PHEM overall system packaging is constrained by limited space in a motorcycle chassis. In this paper, a chassis applying the concept of a Chopper is analysed to apply in PHEM. The chassis 3dimensional (3D) modelling is built with CAD software. The PHEM power-train components and drive-train mechanisms are intergraded into the 3D modelling to ensure the chassis provides sufficient space. Besides that, a human dummy model is built into the 3D modelling to ensure the rider?s ergonomics and comfort. The chassis 3D model then undergoes stress-strain simulation. The simulation predicts the stress distribution, displacement and factor of safety (FOS). The data are used to identify the critical point, thus suggesting the chassis design is applicable or need to redesign/ modify to meet the require strength. Critical points mean highest stress which might cause the chassis to fail. This point occurs at the joints at triple tree and bracket rear absorber for a motorcycle chassis. As a conclusion, computational analysis predicts the stress distribution and guideline to develop a safe prototype chassis.

  7. Analysis and optimization of hybrid electric vehicle thermal management systems

    Science.gov (United States)

    Hamut, H. S.; Dincer, I.; Naterer, G. F.

    2014-02-01

    In this study, the thermal management system of a hybrid electric vehicle is optimized using single and multi-objective evolutionary algorithms in order to maximize the exergy efficiency and minimize the cost and environmental impact of the system. The objective functions are defined and decision variables, along with their respective system constraints, are selected for the analysis. In the multi-objective optimization, a Pareto frontier is obtained and a single desirable optimal solution is selected based on LINMAP decision-making process. The corresponding solutions are compared against the exergetic, exergoeconomic and exergoenvironmental single objective optimization results. The results show that the exergy efficiency, total cost rate and environmental impact rate for the baseline system are determined to be 0.29, ¢28 h-1 and 77.3 mPts h-1 respectively. Moreover, based on the exergoeconomic optimization, 14% higher exergy efficiency and 5% lower cost can be achieved, compared to baseline parameters at an expense of a 14% increase in the environmental impact. Based on the exergoenvironmental optimization, a 13% higher exergy efficiency and 5% lower environmental impact can be achieved at the expense of a 27% increase in the total cost.

  8. Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options

    OpenAIRE

    Quanbao, Jiang; Shuzhuo, Li; Marcus W., Feldman

    2011-01-01

    The large number of missing females in China, a consequence of gender discrimination, is having and will continue to have a profound effect on the country's population development. In this paper, we analyze the causes of this gender discrimination in terms of institutions, culture and, economy, and suggest public policies that might help eliminate gender discrimination. Using a population simulation model, we study the effect of public policies on the sex ratio at birth and excess female chil...

  9. Genetic analysis of agro-morphological traits in promising hybrids of sunflower (Helianthus annuus L.

    Directory of Open Access Journals (Sweden)

    Maryam GOLABADI

    2015-11-01

    Full Text Available The main objective underlying sunflower breeding programs is to develop high-yielding productive F1 hybrid cultivars. This study was conducted to investigate the genetic control of some agro-morphological traits of new sunflower F1 hybrids. For this purpose, fourteen inbred lines of sunflower were crossed with three male sterile inbred lines. Their hybrids (14 hybrids were then evaluated against three control cultivars. The data thus obtained were analyzed using the nested model (North Carolina Design І as a completely randomized block design (CRBD with four replications. Analysis of variance showed that the hybrids were significantly different in all the traits studied, except for head and stem diameters. From among the hybrids evaluated, Cms19 × Rn1-81 was found to have the highest seed yield and oil content. Cluster analysis classified the hybrids into four different groups. Genetic analysis showed that days to maturity, seed weight, and oil content (% were under the additive gene action. Breeding strategies based on selection could be suggested for the improvement of these traits. Head angle, head diameter, seed yield, and oil yield were under the dominance gene action; breeding based on hybridization methods is, therefore, proposed for these traits. Finally, both additive and dominance gene actions were observed to play important roles in the genetic control of plant height and stem diameter.

  10. Laws' masks descriptors applied to bone texture analysis: an innovative and discriminant tool in osteoporosis

    International Nuclear Information System (INIS)

    Rachidi, M.; Marchadier, A.; Gadois, C.; Lespessailles, E.; Chappard, C.; Benhamou, C.L.

    2008-01-01

    The objective of this study was to explore Laws' masks analysis to describe structural variations of trabecular bone due to osteoporosis on high-resolution digital radiographs and to check its dependence on the spatial resolution. Laws' masks are well established as one of the best methods for texture analysis in image processing and are used in various applications, but not in bone tissue characterisation. This method is based on masks that aim to filter the images. From each mask, five classical statistical parameters can be calculated. The study was performed on 182 healthy postmenopausal women with no fractures and 114 age-matched women with fractures [26 hip fractures (HFs), 29 vertebrae fractures (VFs), 29 wrist fractures (WFs) and 30 other fractures (OFs)]. For all subjects radiographs were obtained of the calcaneus with a new high-resolution X-ray device with direct digitisation (BMA, D3A, France). The lumbar spine, femoral neck, and total hip bone mineral density (BMD) were assessed by dual-energy X-ray absorptiometry. In terms of reproducibility, the best results were obtained with the TR E5E5 mask, especially for three parameters: ''mean'', ''standard deviation'' and ''entropy'' with, respectively, in vivo mid-term root mean square average coefficient of variation (RMSCV)%=1.79, 4.24 and 2.05. The ''mean'' and ''entropy'' parameters had a better reproducibility but ''standard deviation'' showed a better discriminant power. Thus, for univariate analysis, the difference between subjects with fractures and controls was significant (P -3 ) and significant for each fracture group independently (P -4 for HF, P=0.025 for VF and P -3 for OF). After multivariate analysis with adjustment for age and total hip BMD, the difference concerning the ''standard deviation'' parameter remained statistically significant between the control group and the HF and VF groups (P -5 , and P=0.04, respectively). No significant correlation between these Laws' masks parameters and

  11. The LOFA analysis of fusion-fission hybrid reactor

    International Nuclear Information System (INIS)

    Yu, Z.-C.; Xie, H.

    2014-01-01

    The fusion-fission hybrid energy reactor can produce energy, breed nuclear fuel, and handle the nuclear waste, etc, with the fusion neutron source striking the subcritical blanket. The passive safety system, consisting of passive residual heat removal system, passive safety injection system and automatic depressurization system, was adopted into the fusion-fission hybrid energy reactor in this paper. Modeling and nodalization of primary loop, passive core cooling system and partial secondary loop of the fusion-fission hybrid energy reactor using RELAP5 were conducted and LOFA (Loss of Flow Accident) was analyzed. The results of key transient parameters indicated that the PRHRs could mitigate the accidental consequence of LOFA effectively. It is also concluded that it is feasible to apply the passive safety system concept to fusion-fission hybrid energy reactor. (author)

  12. Genetic diversity in intraspecific hybrid populations of Eucommia ulmoides Oliver evaluated from ISSR and SRAP molecular marker analysis.

    Science.gov (United States)

    Yu, J; Wang, Y; Ru, M; Peng, L; Liang, Z S

    2015-07-03

    Eucommia ulmoides Oliver, the only extant species of Eucommiaceae, is a second-category state-protected endangered plant in China. Evaluation of genetic diversity among some intraspecific hybrid populations of E. ulmoides Oliver is vital for breeding programs and further conservation of this rare species. We studied the genetic diversity of 130 accessions from 13 E. ulmoides intraspecific hybrid populations using inter-simple sequence related (ISSR) and sequence-related amplified polymorphism (SRAP) markers. Of the 100 ISSR primers and 100 SRAP primer combinations screened, eight ISSRs and eight SRAPs were used to evaluate the level of polymorphism and discriminating capacity. A total number of 65 bands were amplified using eight ISSR primers, in which 50 bands (76.9%) were polymorphic, with an average of 8.1 polymorphic fragments per primer. Alternatively, another 244 bands were observed using eight SRAP primer combinations, and 163 (66.8%) of them were polymorphic, with an average of 30.5 polymorphic fragments per primer. The unweighted pair-group method (UPGMA) analysis showed that these 13 populations could be classified into three groups by the ISSR marker and two groups by the SRAP marker. Principal coordinate analysis using SRAP was completely identical to the UPGMA-based clustering, although this was partly confirmed by the results of UPGMA cluster analysis using the ISSR marker. This study provides insights into the genetic background of E. ulmoides intraspecific hybrids. The progenies of the variations "Huazhong-3", "big fruit", "Yanci", and "smooth bark" present high genetic diversity and offer great potential for E. ulmoides breeding and conservation.

  13. Design and Analysis of the AlNiCo Hybrid Magnet in EMS Maglev Vehicles

    Directory of Open Access Journals (Sweden)

    Lv Chao

    2017-01-01

    Full Text Available In order to solve the problem of hybrid electromagnet lock orbit, we design a new type of AlNiCo-NdFeB hybrid levitation electromagnet. The theoretical analysis has be carried on and mathematical model is established for AlNiCo-NdFeB hybrid levitation electromagnet. Through two dimensional simulation, the electromagnetic characteristics of the suspended electromagnet are analyzed in the 3 typical operating conditions , which are in heavy load at gap 8mm, in full load at gap 16mm and in no-load at gap 3mm. And it’s compared with the traditional electromagnetic magnet and NdFeB hybrid electromagnet. Calculation and analysis show that the new hybrid levitation electromagnet can effectively solve the problems of the electromagnet lock orbit, at the same time, have a good dynamic performance and suspension regulation performance.

  14. A Comparative Study of Feature Selection Methods for the Discriminative Analysis of Temporal Lobe Epilepsy

    Directory of Open Access Journals (Sweden)

    Chunren Lai

    2017-12-01

    Full Text Available It is crucial to differentiate patients with temporal lobe epilepsy (TLE from the healthy population and determine abnormal brain regions in TLE. The cortical features and changes can reveal the unique anatomical patterns of brain regions from structural magnetic resonance (MR images. In this study, structural MR images from 41 patients with left TLE, 34 patients with right TLE, and 58 normal controls (NC were acquired, and four kinds of cortical measures, namely cortical thickness, cortical surface area, gray matter volume (GMV, and mean curvature, were explored for discriminative analysis. Three feature selection methods including the independent sample t-test filtering, the sparse-constrained dimensionality reduction model (SCDRM, and the support vector machine-recursive feature elimination (SVM-RFE were investigated to extract dominant features among the compared groups for classification using the support vector machine (SVM classifier. The results showed that the SVM-RFE achieved the highest performance (most classifications with more than 84% accuracy, followed by the SCDRM, and the t-test. Especially, the surface area and GMV exhibited prominent discriminative ability, and the performance of the SVM was improved significantly when the four cortical measures were combined. Additionally, the dominant regions with higher classification weights were mainly located in the temporal and the frontal lobe, including the entorhinal cortex, rostral middle frontal, parahippocampal cortex, superior frontal, insula, and cuneus. This study concluded that the cortical features provided effective information for the recognition of abnormal anatomical patterns and the proposed methods had the potential to improve the clinical diagnosis of TLE.

  15. The use of principal component, discriminate and rough sets analysis methods of radiological data

    International Nuclear Information System (INIS)

    Seddeek, M.K.; Kozae, A.M.; Sharshar, T.; Badran, H.M.

    2006-01-01

    In this work, computational methods of finding clusters of multivariate data points were explored using principal component analysis (PCA), discriminate analysis (DA) and rough set analysis (RSA) methods. The variables were the concentrations of four natural isotopes and the texture characteristics of 100 sand samples from the coast of North Sinai, Egypt. Beach and dune sands are the two types of samples included. These methods were used to reduce the dimensionality of multivariate data and as classification and clustering methods. The results showed that the classification of sands in the environment of North Sinai is dependent upon the radioactivity contents of the naturally occurring radioactive materials and not upon the characteristics of the sand. The application of DA enables the creation of a classification rule for sand type and it revealed that samples with high negatively values of the first score have the highest contamination of black sand. PCA revealed that radioactivity concentrations alone can be considered to predict the classification of other samples. The results of RSA showed that only one of the concentrations of 238 U, 226 Ra and 232 Th with 40 K content, can characterize the clusters together with characteristics of the sand. Both PCA and RSA result in the following conclusion: 238 U, 226 Ra and 232 Th behave similarly. RSA revealed that one/two of them may not be considered without affecting the body of knowledge

  16. Classification of Surface and Deep Soil Samples Using Linear Discriminant Analysis

    International Nuclear Information System (INIS)

    Wasim, M.; Ali, M.; Daud, M.

    2015-01-01

    A statistical analysis was made of the activity concentrations measured in surface and deep soil samples for natural and anthropogenic gamma-emitting radionuclides. Soil samples were obtained from 48 different locations in Gilgit, Pakistan covering about 50 km/sup 2/ areas at an average altitude of 1550 m above sea level. From each location two samples were collected: one from the top soil (2-6 cm) and another from a depth of 6-10 cm. Four radionuclides including /sup 226/Ra, /sup 232/Th, /sup 40/K and /sup 137/Cs were quantified. The data was analyzed using t-test to find out activity concentration difference between the surface and depth samples. At the surface, the median activity concentrations were 23.7, 29.1, 4.6 and 115 Bq kg/sup -1/ for 226Ra, 232Th, 137Cs and 40K respectively. For the same radionuclides, the activity concentrations were respectively 25.5, 26.2, 2.9 and 191 Bq kg/sup -1/ for the depth samples. Principal component analysis (PCA) was applied to explore patterns within the data. A positive significant correlation was observed between the radionuclides /sup 226/Ra and /sup 232/Th. The data from PCA was further utilized in linear discriminant analysis (LDA) for the classification of surface and depth samples. LDA classified surface and depth samples with good predictability. (author)

  17. Classification of root canal microorganisms using electronic-nose and discriminant analysis

    Directory of Open Access Journals (Sweden)

    Özbilge Hatice

    2010-11-01

    Full Text Available Abstract Background Root canal treatment is a debridement process which disrupts and removes entire microorganisms from the root canal system. Identification of microorganisms may help clinicians decide on treatment alternatives such as using different irrigants, intracanal medicaments and antibiotics. However, the difficulty in cultivation and the complexity in isolation of predominant anaerobic microorganisms make clinicians resort to empirical medical treatments. For this reason, identification of microorganisms is not a routinely used procedure in root canal treatment. In this study, we aimed at classifying 7 different standard microorganism strains which are frequently seen in root canal infections, using odor data collected using an electronic nose instrument. Method Our microorganism odor data set consisted of 5 repeated samples from 7 different classes at 4 concentration levels. For each concentration, 35 samples were classified using 3 different discriminant analysis methods. In order to determine an optimal setting for using electronic-nose in such an application, we have tried 3 different approaches in evaluating sensor responses. Moreover, we have used 3 different sensor baseline values in normalizing sensor responses. Since the number of sensors is relatively large compared to sample size, we have also investigated the influence of two different dimension reduction methods on classification performance. Results We have found that quadratic type dicriminant analysis outperforms other varieties of this method. We have also observed that classification performance decreases as the concentration decreases. Among different baseline values used for pre-processing the sensor responses, the model where the minimum values of sensor readings in the sample were accepted as the baseline yields better classification performance. Corresponding to this optimal choice of baseline value, we have noted that among different sensor response model and

  18. Structural Discrimination

    DEFF Research Database (Denmark)

    Thorsen, Mira Skadegård

    discrimination as two ways of articulating particular, opaque forms of racial discrimination that occur in everyday Danish (and other) contexts, and have therefore become normalized. I present and discuss discrimination as it surfaces in data from my empirical studies of discrimination in Danish contexts...

  19. Restriction endonuclease analysis of chloroplast DNA in interspecies somatic Hybrids of Petunia.

    Science.gov (United States)

    Kumar, A; Cocking, E C; Bovenberg, W A; Kool, A J

    1982-12-01

    Restriction endonuclease cleavage pattern analysis of chloroplast DNA (cpDNA) of three different interspecific somatic hybrid plants revealed that the cytoplasms of the hybrids contained only cpDNA of P. parodii. The somatic hybrid plants analysed were those between P. parodii (wild type) + P. hybrida (wild type); P. parodii (wild type)+P. inflata (cytoplasmic albino mutant); P. parodii (wild type) + P. parviflora (nuclear albino mutant). The presence of only P. parodii chloroplasts in the somatic hybrid of P. parodii + P. inflata is possibly due to the stringent selection used for somatic hybrid production. However, in the case of the two other somatic hybrids P. parodii + P. hybrida and P. parodii + P. parviflora it was not possible to determine whether the presence of only P. parodii chloroplasts in these somatic hybrid plants was due to the nature of the selection schemes used or simply occurred by chance. The relevance of such somatic hybrid material for the study of genomic-cytoplasmic interaction is discussed, as well as the use of restriction endonuclease fragment patterns for the analysis of taxonomic and evolutionary inter-relationships in the genus Petunia.

  20. Race, Sex, and Discrimination in School Settings: A Multilevel Analysis of Associations with Delinquency

    Science.gov (United States)

    Chambers, Brittany D.; Erausquin, Jennifer Toller

    2018-01-01

    Background: Adolescence is a critical phase of development and experimentation with delinquent behaviors. There is a growing body of literature exploring individual and structural impacts of discrimination on health outcomes and delinquent behaviors. However, there is limited research assessing how school diversity and discrimination impact…

  1. Perceived Discrimination among African American Adolescents and Allostatic Load: A Longitudinal Analysis with Buffering Effects

    Science.gov (United States)

    Brody, Gene H.; Lei, Man-Kit; Chae, David H.; Yu, Tianyi; Kogan, Steven M.; Beach, Steven R. H.

    2014-01-01

    This study was designed to examine the prospective relations of perceived racial discrimination with allostatic load (AL), along with a possible buffer of the association. A sample of 331 African Americans in the rural South provided assessments of perceived discrimination from ages 16 to 18 years. When youth were 18 years, caregivers reported…

  2. A nutritional risk screening model for patients with liver cirrhosis established using discriminant analysis

    Directory of Open Access Journals (Sweden)

    ZHU Binghua

    2017-06-01

    Full Text Available ObjectiveTo establish a nutritional risk screening model for patients with liver cirrhosis using discriminant analysis. MethodsThe clinical data of 273 patients with liver cirrhosis who were admitted to Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from August 2015 to March 2016 were collected. Body height, body weight, upper arm circumference, triceps skinfold thickness, subscapular skinfold thickness, and hand grip strength were measured and recorded, and then body mass index (BMI and upper arm muscle circumference were calculated. Laboratory markers including liver function parameters, renal function parameters, and vitamins were measured. The patients were asked to complete Nutritional Risk Screening 2002 and Malnutrition Universal Screening Tool (MUST, and a self-developed nutritional risk screening pathway was used for nutritional risk classification. Observation scales of the four diagnostic methods in traditional Chinese medicine were used to collect patients′ symptoms and signs. Continuous data were expressed as mean±SD (x±s; an analysis of variance was used for comparison between multiple groups, and the least significant difference t-test was used for further comparison between two groups. Discriminant analysis was used for model establishment, and cross validation was used for model verification. ResultsThe nutritional risk screening pathway for patients with liver cirrhosis was used for the screening of respondents, and there were 49 patients (17.95% in non-risk group, 49 (17.95% in possible-risk group, and 175 (64.10% in risk group. The distance criterion function was used to establish the nutritional risk screening model for patients with liver cirrhosis: D1=-11.885+0.310×BMI+0150×MAC+0.005×P-Alb-0.001×Vit B12+0.103×Vit D-0.89×ascites-0.404×weakness-0.560×hypochondriac pain+0035×dysphoria with feverish sensation (note: if a patient has ascites, weakness, hypochondriac pain

  3. Benefit Analysis of Hybrid CNT/CFRP Composites in Future Aircraft Structures, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — During Phase I, Aurora Flight Sciences and N12 Technologies propose to conduct a comprehensive analysis of the benefits of hybrid composites in future aircraft...

  4. Unified performance analysis of hybrid-ARQ with incremental redundancy over free-space optical channels

    KAUST Repository

    Zedini, Emna; Chelli, Ali; Alouini, Mohamed-Slim

    2014-01-01

    In this paper, we carry out a unified performance analysis of hybrid automatic repeat request (HARQ) with incremental redundancy (IR) from an information theoretic perspective over a point-to-point free-space optical (FSO) system. First, we

  5. Combining pharmacophore fingerprints and PLS-discriminant analysis for virtual screening and SAR elucidation

    DEFF Research Database (Denmark)

    Askjær, Sune; Langgård, Morten

    2008-01-01

    The criterion of success for the initial stages of a ligand-based drug-discovery project is dual. First, a set of suitable lead compounds has to be identified. Second, a level of a preliminary structure-activity relationship (SAR) of the identified ligands has to be established in order to guide ...... by the protein-binding site known from X-ray complexes. The result of this analysis assists in explaining the efficiency of 2D pharmacophore fingerprints as descriptors in virtual screening....... the lead optimization toward a final drug candidate. This paper presents a combined approach to solving these two problems of ligand-based virtual screening and elucidation of SAR based on interplay between pharmacophore fingerprints and interpretation of PLS-discriminant analysis (PLS-DA) models....... The virtual screening capability of the PLS-DA method is compared to group fusion maximum similarity searching in a test using four graph-based pharmacophore fingerprints over a range of 10 diverse targets. The PLS-DA method was generally found to do better than the Smax method. The GpiDAPH3 and PCH...

  6. Molecular discrimination of lactobacilli used as starter and probiotic cultures by amplified ribosomal DNA restriction analysis.

    Science.gov (United States)

    Roy, D; Sirois, S; Vincent, D

    2001-04-01

    Lactic acid bacteria such as Lactobacillus helveticus, L. delbrueckii subsp. delbrueckii, L. delbrueckii subsp. lactis, L. delbrueckii subsp. bulgaricus, L. acidophilus, and L. casei related taxa which are widely used as starter or probiotic cultures can be identified by amplified ribosomal DNA restriction analysis (ARDRA). The genetic discrimination of the related species belonging to these groups was first obtained by PCR amplifications by using group-specific or species-specific 16S rDNA primers. The numerical analysis of the ARDRA patterns obtained by using CfoI, HinfI, Tru9I, and ScrFI was an efficient typing tool for identification of species of the L. acidophilus and L. casei complex. ARDRA by using CfoI was a reliable method for differentiation of L. delbrueckii subsp. bulgaricus and L. delbrueckii subsp. lactis. Finally, strains ATCC 393 and ATCC 15820 exhibited unique ARDRA patterns with CfoI and Tru9I restriction enzymes as compared with the other strains of L. casei, L. paracasei, and L. rhamnosus.

  7. Two-dimensional statistical linear discriminant analysis for real-time robust vehicle-type recognition

    Science.gov (United States)

    Zafar, I.; Edirisinghe, E. A.; Acar, S.; Bez, H. E.

    2007-02-01

    Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic License Plate Recognition (ALPR) systems. Several car MMR systems have been proposed in literature. However these approaches are based on feature detection algorithms that can perform sub-optimally under adverse lighting and/or occlusion conditions. In this paper we propose a real time, appearance based, car MMR approach using Two Dimensional Linear Discriminant Analysis that is capable of addressing this limitation. We provide experimental results to analyse the proposed algorithm's robustness under varying illumination and occlusions conditions. We have shown that the best performance with the proposed 2D-LDA based car MMR approach is obtained when the eigenvectors of lower significance are ignored. For the given database of 200 car images of 25 different make-model classifications, a best accuracy of 91% was obtained with the 2D-LDA approach. We use a direct Principle Component Analysis (PCA) based approach as a benchmark to compare and contrast the performance of the proposed 2D-LDA approach to car MMR. We conclude that in general the 2D-LDA based algorithm supersedes the performance of the PCA based approach.

  8. Using stable isotope analysis to discriminate gasoline on the basis of its origin.

    Science.gov (United States)

    Heo, Su-Young; Shin, Woo-Jin; Lee, Sin-Woo; Bong, Yeon-Sik; Lee, Kwang-Sik

    2012-03-15

    Leakage of gasoline and diesel from underground tanks has led to a severe environmental problem in many countries. Tracing the production origin of gasoline and diesel is required to enable the development of dispute resolution and appropriate remediation strategies for the oil-contaminated sites. We investigated the bulk and compound-specific isotopic compositions of gasoline produced by four oil companies in South Korea: S-Oil, SK, GS and Hyundai. The relative abundance of several compounds in gasoline was determined by the peak height of the major ion (m/z 44). The δ(13)C(Bulk) and δD(Bulk) values of gasoline produced by S-Oil were significantly different from those of SK, GS and Hyundai. In particular, the compound-specific isotopic value (δ(13)C(CSIA)) of methyl tert-butyl ether (MTBE) in S-Oil gasoline was significantly lower than that of gasoline produced by other oil companies. The abundance of several compounds in gasoline, such as n-pentane, MTBE, n-hexane, toluene, ethylbenzene and o-xylene, differed widely among gasoline from different oil companies. This study shows that gasoline can be forensically discriminated according to the oil company responsible for its manufacture using stable isotope analysis combined with multivariate statistical analysis. Copyright © 2012 John Wiley & Sons, Ltd.

  9. Ultrasonic analysis to discriminate bread dough of different types of flour

    Science.gov (United States)

    García-Álvarez, J.; Rosell, C. M.; García-Hernández, M. J.; Chávez, J. A.; Turó, A.; Salazar, J.

    2012-12-01

    Many varieties of bread are prepared using flour coming from wheat. However, there are other types of flours milled from rice, legumes and some fruits and vegetables that are also suitable for baking purposes, used alone or in combination with wheat flour. The type of flour employed strongly influences the dough consistency, which is a relevant property for determining the dough potential for breadmaking purposes. Traditional methods for dough testing are relatively expensive, time-consuming, off-line and often require skilled operators. In this work, ultrasonic analysis are performed in order to obtain acoustic properties of bread dough samples prepared using two different types of flour, wheat flour and rice flour. The dough acoustic properties can be related to its viscoelastic characteristics, which in turn determine the dough feasibility for baking. The main advantages of the ultrasonic dough testing can be, among others, its low cost, fast, hygienic and on-line performance. The obtained results point out the potential of the ultrasonic analysis to discriminate doughs of different types of flour.

  10. Ultrasonic analysis to discriminate bread dough of different types of flour

    International Nuclear Information System (INIS)

    García-Álvarez, J; García-Hernández, M J; Chávez, J A; Turó, A; Salazar, J; Rosell, C M

    2012-01-01

    Many varieties of bread are prepared using flour coming from wheat. However, there are other types of flours milled from rice, legumes and some fruits and vegetables that are also suitable for baking purposes, used alone or in combination with wheat flour. The type of flour employed strongly influences the dough consistency, which is a relevant property for determining the dough potential for breadmaking purposes. Traditional methods for dough testing are relatively expensive, time-consuming, off-line and often require skilled operators. In this work, ultrasonic analysis are performed in order to obtain acoustic properties of bread dough samples prepared using two different types of flour, wheat flour and rice flour. The dough acoustic properties can be related to its viscoelastic characteristics, which in turn determine the dough feasibility for baking. The main advantages of the ultrasonic dough testing can be, among others, its low cost, fast, hygienic and on-line performance. The obtained results point out the potential of the ultrasonic analysis to discriminate doughs of different types of flour.

  11. Parallel Hybrid Gas-Electric Geared Turbofan Engine Conceptual Design and Benefits Analysis

    Science.gov (United States)

    Lents, Charles; Hardin, Larry; Rheaume, Jonathan; Kohlman, Lee

    2016-01-01

    The conceptual design of a parallel gas-electric hybrid propulsion system for a conventional single aisle twin engine tube and wing vehicle has been developed. The study baseline vehicle and engine technology are discussed, followed by results of the hybrid propulsion system sizing and performance analysis. The weights analysis for the electric energy storage & conversion system and thermal management system is described. Finally, the potential system benefits are assessed.

  12. Further studies of crania from ancient northern Africa: an analysis of crania from first dynasty Egyptian tombs, using discriminant functions.

    Science.gov (United States)

    Keita, S O

    1992-03-01

    An analysis of First Dynasty crania from Abydos was undertaken using multiple discriminant functions. The results demonstrate greater affinity with Upper Nile Valley patterns, but also suggest change from earlier craniometric trends. Gene flow and movement of northern officials to the important southern city may explain the findings.

  13. Signal Detection Methods and Discriminant Analysis Applied to Categorization of Newspaper and Government Documents: A Preliminary Study.

    Science.gov (United States)

    Ng, Kwong Bor; Rieh, Soo Young; Kantor, Paul

    2000-01-01

    Discussion of natural language processing focuses on experiments using linear discriminant analysis to distinguish "Wall Street Journal" texts from "Federal Register" tests using information about the frequency of occurrence of word boundaries, sentence boundaries, and punctuation marks. Displays and interprets results in terms…

  14. Analysis on a hybrid desiccant air-conditioning system

    International Nuclear Information System (INIS)

    Jia, C.X.; Dai, Y.J.; Wu, J.Y.; Wang, R.Z.

    2006-01-01

    Hybrid desiccant-assisted preconditioner and split cooling coil system, which combines the merits of moisture removal by desiccant and cooling coil for sensible heat removal, is a potential alternative to conventional vapor compression cooling systems. In this paper, experiments on a hybrid desiccant air-conditioning system, which is actually an integration of a rotary solid desiccant dehumidification and a vapor compression air-conditioning unit, had been carried out. It is found that, compared with the conventional VC (vapor compression) system, the hybrid desiccant cooling system economizes 37.5% electricity powers when the process air temperature and relative humidity are maintained at 30 o C, and 55% respectively. The reason why the hybrid desiccant cooling system features better performance relative to the VC system lies in the improvement brought about in the performance of the evaporator in VC unit due to desiccant dehumidification. A thermodynamic model of the hybrid desiccant system with R-22 as the refrigerant has been developed and the impact of operating parameters on the sensible heat ratio of the evaporator and the electric power saving rate has been analyzed. It is found that a majority of evaporators can operate in the dry condition even if the regeneration temperature is lower (i.e. 80 o C)

  15. Energy metrics analysis of hybrid - photovoltaic (PV) modules

    Energy Technology Data Exchange (ETDEWEB)

    Tiwari, Arvind [Department of Electronics and Communication, Krishna Institute of Engineering and Technology, 13 k.m. stone, Ghaziabad - Meerut Road, Ghaziabad 201 206, UP (India); Barnwal, P.; Sandhu, G.S.; Sodha, M.S. [Centre for Energy Studies, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016 (India)

    2009-12-15

    In this paper, energy metrics (energy pay back time, electricity production factor and life cycle conversion efficiency) of hybrid photovoltaic (PV) modules have been analyzed and presented for the composite climate of New Delhi, India. For this purpose, it is necessary to calculate (1) the energy consumption in making different components of the PV modules and (2) the annual energy (electrical and thermal) available from the hybrid-PV modules. A set of mathematical relations have been reformulated for computation of the energy metrics. The manufacturing energy, material production energy, energy use and distribution energy of the system have been taken into account, to determine the embodied energy for the hybrid-PV modules. The embodied energy and annual energy outputs have been used for evaluation of the energy metrics. For hybrid PV module, it has been observed that the EPBT gets significantly reduced by taking into account the increase in annual energy availability of the thermal energy in addition to the electrical energy. The values of EPF and LCCE of hybrid PV module become higher as expected. (author)

  16. Search for the standard model Higgs boson in $e^{+}e^{-}$ four- jet topology using neural networks and discriminant analysis

    CERN Document Server

    Mjahed, M

    2003-01-01

    We present an attempt to separate between Higgs boson events (e/sup + /e/sup -/ to ZH to qqbb) and other physics processes in the 4-jet channel (e/sup +/e/sup -/ to Z/ gamma , W/sup +/W, ZZ to 4jets), using the discriminant analysis and neural networks methods. Events were produced at LEP2 energies, using the Lund Monte Carlo generator and the Aleph package. The most discriminant variables as the reconstructed jet mass, the jet properties (b-tag, rapidity weighted moments) and other variables are used. (8 refs).

  17. Discrimination of Geographical Origin of Asian Garlic Using Isotopic and Chemical Datasets under Stepwise Principal Component Analysis.

    Science.gov (United States)

    Liu, Tsang-Sen; Lin, Jhen-Nan; Peng, Tsung-Ren

    2018-01-16

    Isotopic compositions of δ 2 H, δ 18 O, δ 13 C, and δ 15 N and concentrations of 22 trace elements from garlic samples were analyzed and processed with stepwise principal component analysis (PCA) to discriminate garlic's country of origin among Asian regions including South Korea, Vietnam, Taiwan, and China. Results indicate that there is no single trace-element concentration or isotopic composition that can accomplish the study's purpose and the stepwise PCA approach proposed does allow for discrimination between countries on a regional basis. Sequentially, Step-1 PCA distinguishes garlic's country of origin among Taiwanese, South Korean, and Vietnamese samples; Step-2 PCA discriminates Chinese garlic from South Korean garlic; and Step-3 and Step-4 PCA, Chinese garlic from Vietnamese garlic. In model tests, countries of origin of all audit samples were correctly discriminated by stepwise PCA. Consequently, this study demonstrates that stepwise PCA as applied is a simple and effective approach to discriminating country of origin among Asian garlics. © 2018 American Academy of Forensic Sciences.

  18. GeoNeoLogical novel and other hybrimedia experiments: or how to use hybrid methods such as Hybrid Discourse Analysis (HDA within a knowledge base

    Directory of Open Access Journals (Sweden)

    Andrade, Pedro

    2016-07-01

    Full Text Available In this essay I will present some results of the project Public Communication of Art, which developed a seminal theory and methodology intended to cope with hybridity and new media literacy in our globalized and inter/transcultural world. Some of the methods used blend vision with touch and are called ‘hybrid methods’ or ‘hybrimethods’. Examples of these are, for instance, a Multitouch Interactive Table, a Multitouch Questionnaire, Trichotomies Game and GeoNeoLogic Novel, this last one being a hybrid novel activated by fusion of vision, touch and GPS coordinates. Another hybrimethod is a sort of discursive analysis, named Hybrid Discourse Analysis (HDA, which uses ‘semantic-logical networks’ organized by concepts and ‘relation-concepts’. HDA is here articulated with Critical Sociology and applied to the analysis of a text on Magic Realism, which is also a hybrid genre within the social field of literature.

  19. Identifying Plant Part Composition of Forest Logging Residue Using Infrared Spectral Data and Linear Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Gifty E. Acquah

    2016-08-01

    Full Text Available As new markets, technologies and economies evolve in the low carbon bioeconomy, forest logging residue, a largely untapped renewable resource will play a vital role. The feedstock can however be variable depending on plant species and plant part component. This heterogeneity can influence the physical, chemical and thermochemical properties of the material, and thus the final yield and quality of products. Although it is challenging to control compositional variability of a batch of feedstock, it is feasible to monitor this heterogeneity and make the necessary changes in process parameters. Such a system will be a first step towards optimization, quality assurance and cost-effectiveness of processes in the emerging biofuel/chemical industry. The objective of this study was therefore to qualitatively classify forest logging residue made up of different plant parts using both near infrared spectroscopy (NIRS and Fourier transform infrared spectroscopy (FTIRS together with linear discriminant analysis (LDA. Forest logging residue harvested from several Pinus taeda (loblolly pine plantations in Alabama, USA, were classified into three plant part components: clean wood, wood and bark and slash (i.e., limbs and foliage. Five-fold cross-validated linear discriminant functions had classification accuracies of over 96% for both NIRS and FTIRS based models. An extra factor/principal component (PC was however needed to achieve this in FTIRS modeling. Analysis of factor loadings of both NIR and FTIR spectra showed that, the statistically different amount of cellulose in the three plant part components of logging residue contributed to their initial separation. This study demonstrated that NIR or FTIR spectroscopy coupled with PCA and LDA has the potential to be used as a high throughput tool in classifying the plant part makeup of a batch of forest logging residue feedstock. Thus, NIR/FTIR could be employed as a tool to rapidly probe/monitor the variability

  20. Diagnosing basal cell carcinoma in vivo by near-infrared Raman spectroscopy: a Principal Components Analysis discrimination algorithm

    Science.gov (United States)

    Silveira, Landulfo, Jr.; Silveira, Fabrício L.; Bodanese, Benito; Pacheco, Marcos Tadeu T.; Zângaro, Renato A.

    2012-02-01

    This work demonstrated the discrimination among basal cell carcinoma (BCC) and normal human skin in vivo using near-infrared Raman spectroscopy. Spectra were obtained in the suspected lesion prior resectional surgery. After tissue withdrawn, biopsy fragments were submitted to histopathology. Spectra were also obtained in the adjacent, clinically normal skin. Raman spectra were measured using a Raman spectrometer (830 nm) with a fiber Raman probe. By comparing the mean spectra of BCC with the normal skin, it has been found important differences in the 800-1000 cm-1 and 1250-1350 cm-1 (vibrations of C-C and amide III, respectively, from lipids and proteins). A discrimination algorithm based on Principal Components Analysis and Mahalanobis distance (PCA/MD) could discriminate the spectra of both tissues with high sensitivity and specificity.

  1. Phenotypic and Genotypic Analysis of Newly Obtained Interspecific Hybrids in the Campanula Genus.

    Directory of Open Access Journals (Sweden)

    Anna-Catharina Röper

    Full Text Available Interspecific hybridisation creates new phenotypes within several ornamental plant species including the Campanula genus. We have employed phenotypic and genotypic methods to analyse and evaluate interspecific hybridisation among cultivars of four Campanula species, i.e. C. cochleariifolia, C. isophylla, C. medium and C. formanekiana. Hybrids were analysed using amplified fragment length polymorphism (AFLP, flow cytometry and biometrical measurements. Results of correlation matrices demonstrated heterogeneous phenotypes for the parental species, which confirmed our basic premise for new phenotypes of interspecific hybrids. AFLP assays confirmed the hybridity and identified self-pollinated plants. Limitation of flow cytometry analysis detection was observed while detecting the hybridity status of two closely related parents, e.g. C. cochleariiafolia × C. isophylla. Phenotypic characteristics such as shoot habitus and flower colour were strongly influenced by one of the parental species in most crosses. Rooting analysis revealed that inferior rooting quality occurred more often in interspecific hybrids than in the parental species. Only interspecific hybrid lines of C. formanekiana 'White' × C. medium 'Pink' showed a high rooting level. Phenotype analyses demonstrated a separation from the interspecific hybrid lines of C. formanekiana 'White' × C. medium 'Pink' to the other clustered hybrids of C. formanekiana and C. medium. In our study we demonstrated that the use of correlation matrices is a suitable tool for identifying suitable cross material. This study presents a comprehensive overview for analysing newly obtained interspecific hybrids. The chosen methods can be used as guidance for analyses for further interspecific hybrids in Campanula, as well as in other ornamental species.

  2. Sensorless Suitability Analysis of Hybrid PM Machines for Electric Vehicles

    DEFF Research Database (Denmark)

    Matzen, Torben Nørregaard; Rasmussen, Peter Omand

    2009-01-01

    Electrical machines for traction in electric vehicles are an essential component which attract attention with respect to machine design and control as a part of the emerging renewable industry. For the hybrid electric machine to replace the familiar behaviour of the combustion engine torque......, control seems necessary to implement. For hybrid permanent magnet (PM) machines torque control in an indirect fashion using dq-current control is frequently done. This approach requires knowledge about the machine shaft position which may be obtained sensorless. In this article a method based on accurate...

  3. Analysis of the discriminative methods for diagnosis of benign and malignant solitary pulmonary nodules based on serum markers.

    Science.gov (United States)

    Wang, Wanping; Liu, Mingyue; Wang, Jing; Tian, Rui; Dong, Junqiang; Liu, Qi; Zhao, Xianping; Wang, Yuanfang

    2014-01-01

    Screening indexes of tumor serum markers for benign and malignant solitary pulmonary nodules (SPNs) were analyzed to find the optimum method for diagnosis. Enzyme-linked immunosorbent assays, an automatic immune analyzer and radioimmunoassay methods were used to examine the levels of 8 serum markers in 164 SPN patients, and the sensitivity for differential diagnosis of malignant or benign SPN was compared for detection using a single plasma marker or a combination of markers. The results for serological indicators that closely relate to benign and malignant SPNs were screened using the Fisher discriminant analysis and a non-conditional logistic regression analysis method, respectively. The results were then verified by the k-means clustering analysis method. The sensitivity when using a combination of serum markers to detect SPN was higher than that using a single marker. By Fisher discriminant analysis, cytokeratin 19 fragments (CYFRA21-1), carbohydrate antigen 125 (CA125), squamous cell carcinoma antigen (SCC) and breast cancer antigen (CA153), which relate to the benign and malignant SPNs, were screened. Through non-conditional logistic regression analysis, CYFRA21-1, SCC and CA153 were obtained. Using the k-means clustering analysis, the cophenetic correlation coefficient (0.940) obtained by the Fisher discriminant analysis was higher than that obtained with logistic regression analysis (0.875). This study indicated that the Fisher discriminant analysis functioned better in screening out serum markers to recognize the benign and malignant SPN. The combined detection of CYFRA21-1, CA125, SCC and CA153 is an effective way to distinguish benign and malignant SPN, and will find an important clinical application in the early diagnosis of SPN. © 2014 S. Karger GmbH, Freiburg.

  4. Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

    Science.gov (United States)

    Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

    2017-09-01

    In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis.

    Science.gov (United States)

    Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X

    2016-09-01

    The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.

  6. Partial Least Square Discriminant Analysis Discovered a Dietary Pattern Inversely Associated with Nasopharyngeal Carcinoma Risk.

    Science.gov (United States)

    Lo, Yen-Li; Pan, Wen-Harn; Hsu, Wan-Lun; Chien, Yin-Chu; Chen, Jen-Yang; Hsu, Mow-Ming; Lou, Pei-Jen; Chen, I-How; Hildesheim, Allan; Chen, Chien-Jen

    2016-01-01

    Evidence on the association between dietary component, dietary pattern and nasopharyngeal carcinoma (NPC) is scarce. A major challenge is the high degree of correlation among dietary constituents. We aimed to identify dietary pattern associated with NPC and to illustrate the dose-response relationship between the identified dietary pattern scores and the risk of NPC. Taking advantage of a matched NPC case-control study, data from a total of 319 incident cases and 319 matched controls were analyzed. Dietary pattern was derived employing partial least square discriminant analysis (PLS-DA) performed on energy-adjusted food frequencies derived from a 66-item food-frequency questionnaire. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated with multiple conditional logistic regression models, linking pattern scores and NPC risk. A high score of the PLS-DA derived pattern was characterized by high intakes of fruits, milk, fresh fish, vegetables, tea, and eggs ordered by loading values. We observed that one unit increase in the scores was associated with a significantly lower risk of NPC (ORadj = 0.73, 95% CI = 0.60-0.88) after controlling for potential confounders. Similar results were observed among Epstein-Barr virus seropositive subjects. An NPC protective diet is indicated with more phytonutrient-rich plant foods (fruits, vegetables), milk, other protein-rich foods (in particular fresh fish and eggs), and tea. This information may be used to design potential dietary regimen for NPC prevention.

  7. Why Does Rebalancing Class-Unbalanced Data Improve AUC for Linear Discriminant Analysis?

    Science.gov (United States)

    Xue, Jing-Hao; Hall, Peter

    2015-05-01

    Many established classifiers fail to identify the minority class when it is much smaller than the majority class. To tackle this problem, researchers often first rebalance the class sizes in the training dataset, through oversampling the minority class or undersampling the majority class, and then use the rebalanced data to train the classifiers. This leads to interesting empirical patterns. In particular, using the rebalanced training data can often improve the area under the receiver operating characteristic curve (AUC) for the original, unbalanced test data. The AUC is a widely-used quantitative measure of classification performance, but the property that it increases with rebalancing has, as yet, no theoretical explanation. In this note, using Gaussian-based linear discriminant analysis (LDA) as the classifier, we demonstrate that, at least for LDA, there is an intrinsic, positive relationship between the rebalancing of class sizes and the improvement of AUC. We show that the largest improvement of AUC is achieved, asymptotically, when the two classes are fully rebalanced to be of equal sizes.

  8. Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection.

    Science.gov (United States)

    Wang, Shunfang; Nie, Bing; Yue, Kun; Fei, Yu; Li, Wenjia; Xu, Dongshu

    2017-12-15

    Kernel discriminant analysis (KDA) is a dimension reduction and classification algorithm based on nonlinear kernel trick, which can be novelly used to treat high-dimensional and complex biological data before undergoing classification processes such as protein subcellular localization. Kernel parameters make a great impact on the performance of the KDA model. Specifically, for KDA with the popular Gaussian kernel, to select the scale parameter is still a challenging problem. Thus, this paper introduces the KDA method and proposes a new method for Gaussian kernel parameter selection depending on the fact that the differences between reconstruction errors of edge normal samples and those of interior normal samples should be maximized for certain suitable kernel parameters. Experiments with various standard data sets of protein subcellular localization show that the overall accuracy of protein classification prediction with KDA is much higher than that without KDA. Meanwhile, the kernel parameter of KDA has a great impact on the efficiency, and the proposed method can produce an optimum parameter, which makes the new algorithm not only perform as effectively as the traditional ones, but also reduce the computational time and thus improve efficiency.

  9. Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

    Directory of Open Access Journals (Sweden)

    Shengwen Guo

    2017-05-01

    Full Text Available Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI. Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI, the converted MCI (cMCI, and the normal control (NC groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM. An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and

  10. Athermal design and analysis of glass-plastic hybrid lens

    Science.gov (United States)

    Yang, Jian; Cen, Zhaofeng; Li, Xiaotong

    2018-01-01

    With the rapid development of security market, the glass-plastic hybrid lens has gradually become a choice for the special requirements like high imaging quality in a wide temperature range and low cost. The reduction of spherical aberration is achieved by using aspherical surface instead of increasing the number of lenses. Obviously, plastic aspherical lens plays a great role in the cost reduction. However, the hybrid lens has a priority issue, which is the large thermal coefficient of expansion of plastic, causing focus shift and seriously affecting the imaging quality, so the hybrid lens is highly sensitive to the change of temperature. To ensure the system operates normally in a wide temperature range, it is necessary to eliminate the influence of temperature on the hybrid lens system. A practical design method named the Athermal Material Map is summarized and verified by an athermal design example according to the design index. It includes the distribution of optical power and selection of glass or plastic. The design result shows that the optical system has excellent imaging quality at a wide temperature range from -20 ° to 70 °. The method of athermal design in this paper has generality which could apply to optical system with plastic aspherical surface.

  11. Influence of DNA treatments on Southern blot hybridization analysis ...

    African Journals Online (AJOL)

    STORAGESEVER

    2008-06-03

    Jun 3, 2008 ... DNA samples obtained by a non-phenol/chloroform isolation method, from three races of Fusarium oxysporum f. sp. lycopersici ... Key words: Fusarium oxysporum, DIG-IGS Probe, Southern hybridization. INTRODUCTION .... Detection of Fusarium spp in plants with monoclonal antibody. Ann. Phytopathol.

  12. Comparative analysis of the aquaculture potential of hybrid Tilapia ...

    African Journals Online (AJOL)

    , on the growth rate, feeding efficiency and mortality rates of hybrid tilapia — Tilapia zillii (male) x T. guineensis (female) — was evaluated for 233 days. Fish of average weight 12.59g were stocked at a density of 20 fish m–³ and were fed a 30% ...

  13. Hybridization within a Pilosella population: a morphometric analysis

    Czech Academy of Sciences Publication Activity Database

    Urfus, Tomáš; Krahulec, František; Krahulcová, Anna

    2014-01-01

    Roč. 49, č. 2 (2014), s. 223-238 ISSN 1211-9520 R&D Projects: GA ČR GA206/08/0890 Institutional research plan: CEZ:AV0Z60050516 Institutional support: RVO:67985939 Keywords : hybridization * introgression * multivariate morphometrics Subject RIV: EF - Botanics Impact factor: 1.778, year: 2014

  14. Mechanical analysis of CFRP-steel hybrid composites considering the interfacial adhesion

    Science.gov (United States)

    Jang, Jinhyeok; Sung, Minchang; Han, Sungjin; Shim, Wonbo; Yu, Woong-Ryeol

    2017-10-01

    Recently, hybrid composites of carbon fiber reinforced plastics (CFRP) and steel have attracted great attention from automotive engineers due to their high potential for lightweight and multi-materials structures. Interestingly, such hybrid composites have demonstrated increased breaking strain, i.e., the breaking strain of CFRP in the hybrid was larger than that of single CFRP. As such the mechanical properties of hybrid composites could not be calculated using the rule of mixture. In addition, such increase is strongly dependent on the adhesion between CFRP and steel. In this study, a numerical analysis model was built to investigate the mechanism behind increased breaking strain of CFRP in the hybrid structure. Using cohesive zone model, the adhesion between CFRP and steel was effectively considered. The numerical results showed that the simulated mechanical behavior of the hybrid composites did not change as much as observed in experimental as the interfacial adhesion varied. We will investigate this discrepancy in detail and will report new analysis method suitable for CFRP and steel hybrid composites.

  15. Digital discrimination of neutrons and γ-rays in liquid scintillators using pulse gradient analysis

    International Nuclear Information System (INIS)

    D'Mellow, B.; Aspinall, M.D.; Mackin, R.O.; Joyce, M.J.; Peyton, A.J.

    2007-01-01

    A method for the digital discrimination of neutrons and γ-rays in mixed radiation fields is described. Pulses in the time domain, arising from the interaction of photons and neutrons in a liquid scintillator, have been produced using an accepted empirical model and from experimental measurements with an americium-beryllium source. Neutrons and γ-rays have been successfully discriminated in both of these data sets in the digital domain. The digital discrimination method described in this paper is simple and exploits samples early in the life of the pulse. It is thus compatible with current embedded system technologies, offers a degree of immunity to pulse pile-up and heralds a real-time means for neutron/γ discrimination that is fundamental to many potential industrial applications

  16. Discrimination of Clover and Citrus Honeys from Egypt According to Floral Type Using Easily Assessable Physicochemical Parameters and Discriminant Analysis: An External Validation of the Chemometric Approach

    Directory of Open Access Journals (Sweden)

    Ioannis K. Karabagias

    2018-05-01

    Full Text Available Twenty-two honey samples, namely clover and citrus honeys, were collected from the greater Cairo area during the harvesting year 2014–2015. The main purpose of the present study was to characterize the aforementioned honey types and to investigate whether the use of easily assessable physicochemical parameters, including color attributes in combination with chemometrics, could differentiate honey floral origin. Parameters taken into account were: pH, electrical conductivity, ash, free acidity, lactonic acidity, total acidity, moisture content, total sugars (degrees Brix-°Bx, total dissolved solids and their ratio to total acidity, salinity, CIELAB color parameters, along with browning index values. Results showed that all honey samples analyzed met the European quality standards set for honey and had variations in the aforementioned physicochemical parameters depending on floral origin. Application of linear discriminant analysis showed that eight physicochemical parameters, including color, could classify Egyptian honeys according to floral origin (p < 0.05. Correct classification rate was 95.5% using the original method and 90.9% using the cross validation method. The discriminatory ability of the developed model was further validated using unknown honey samples. The overall correct classification rate was not affected. Specific physicochemical parameter analysis in combination with chemometrics has the potential to enhance the differences in floral honeys produced in a given geographical zone.

  17. Discrimination of irradiated MOX fuel from UOX fuel by multivariate statistical analysis of simulated activities of gamma-emitting isotopes

    Science.gov (United States)

    Åberg Lindell, M.; Andersson, P.; Grape, S.; Hellesen, C.; Håkansson, A.; Thulin, M.

    2018-03-01

    This paper investigates how concentrations of certain fission products and their related gamma-ray emissions can be used to discriminate between uranium oxide (UOX) and mixed oxide (MOX) type fuel. Discrimination of irradiated MOX fuel from irradiated UOX fuel is important in nuclear facilities and for transport of nuclear fuel, for purposes of both criticality safety and nuclear safeguards. Although facility operators keep records on the identity and properties of each fuel, tools for nuclear safeguards inspectors that enable independent verification of the fuel are critical in the recovery of continuity of knowledge, should it be lost. A discrimination methodology for classification of UOX and MOX fuel, based on passive gamma-ray spectroscopy data and multivariate analysis methods, is presented. Nuclear fuels and their gamma-ray emissions were simulated in the Monte Carlo code Serpent, and the resulting data was used as input to train seven different multivariate classification techniques. The trained classifiers were subsequently implemented and evaluated with respect to their capabilities to correctly predict the classes of unknown fuel items. The best results concerning successful discrimination of UOX and MOX-fuel were acquired when using non-linear classification techniques, such as the k nearest neighbors method and the Gaussian kernel support vector machine. For fuel with cooling times up to 20 years, when it is considered that gamma-rays from the isotope 134Cs can still be efficiently measured, success rates of 100% were obtained. A sensitivity analysis indicated that these methods were also robust.

  18. Sex determination using discriminant function analysis in Indigenous (Kurubas children and adolescents of Coorg, Karnataka, India: A lateral cephalometric study

    Directory of Open Access Journals (Sweden)

    Darshan Devang Divakar

    2016-11-01

    Full Text Available Aim: To test the validity of sex discrimination using lateral cephalometric radiograph and discriminant function analysis in Indigenous (Kuruba children and adolescents of Coorg, Karnataka, India. Methods and materials: Six hundred and sixteen lateral cephalograms of 380 male and 236 females of age ranging from 6.5 to 18 years of Indigenous population of Coorg, Karnataka, India called Kurubas having a normal occlusion were included in the study. Lateral cephalograms were obtained in a standard position with teeth in centric occlusion and lips relaxed. Each radiograph was traced and cephalometric landmarks were measured using digital calliper. Calculations of 24 cephalometric measurements were performed. Results: Males exhibited significantly greater mean angular and linear cephalometric measurements as compared to females (p < 0.05 (Table 5. Also, significant differences (p < 0.05 were observed in all the variables according to age (Table 6. Out of 24 variables, only ULTc predicts the gender. The reliability of the derived discriminant function was assessed among study subjects; 100% of males and females were recognized correctly. Conclusion: The final outcome of this study validates the existence of sexual dimorphism in the skeleton as early as 6.5 years of age. There is a need for further research to determine other landmarks that can help in sex determination and norms for Indigenous (Kuruba population and also other Indigenous population of Coorg, Karnataka, India. Keywords: Discriminant function analysis, Forensic investigation, Indigenous, Lateral cephalograms, Sex determination

  19. Discrimination and chemical phylogenetic study of seven species of Dendrobium using infrared spectroscopy combined with cluster analysis

    Science.gov (United States)

    Luo, Congpei; He, Tao; Chun, Ze

    2013-04-01

    Dendrobium is a commonly used and precious herb in Traditional Chinese Medicine. The high biodiversity of Dendrobium and the therapeutic needs require tools for the correct and fast discrimination of different Dendrobium species. This study investigates Fourier transform infrared spectroscopy followed by cluster analysis for discrimination and chemical phylogenetic study of seven Dendrobium species. Despite the general pattern of the IR spectra, different intensities, shapes, peak positions were found in the IR spectra of these samples, especially in the range of 1800-800 cm-1. The second derivative transformation and alcoholic extracting procedure obviously enlarged the tiny spectral differences among these samples. The results indicated each Dendrobium species had a characteristic IR spectra profile, which could be used to discriminate them. The similarity coefficients among the samples were analyzed based on their second derivative IR spectra, which ranged from 0.7632 to 0.9700, among the seven Dendrobium species, and from 0.5163 to 0.9615, among the ethanol extracts. A dendrogram was constructed based on cluster analysis the IR spectra for studying the chemical phylogenetic relationships among the samples. The results indicated that D. denneanum and D. crepidatum could be the alternative resources to substitute D. chrysotoxum, D. officinale and D. nobile which were officially recorded in Chinese Pharmacopoeia. In conclusion, with the advantages of high resolution, speediness and convenience, the experimental approach can successfully discriminate and construct the chemical phylogenetic relationships of the seven Dendrobium species.

  20. Site-specific analysis of hybrid geothermal/fossil power plants

    Energy Technology Data Exchange (ETDEWEB)

    1977-06-01

    A preliminary economic analysis of a hybrid geothermal/coal power plant was completed for four geothermal resource areas: Roosevelt Hot Springs, Coso Hot Springs, East Mesa, and Long Valley. A hybrid plant would be economically viable at Roosevelt Hot Springs and somewhat less so at Coso Hot Springs. East Mesa and Long Valley show no economic promise. A well-designed hybrid plant could use geothermal energy for boiler feedwater heating, auxiliary power, auxiliary heating, and cooling water. Construction and operation of a hybrid plant at either Roosevelt Hot Springs or Coso Hot Springs is recommended. A modified version of the Lawrence Berkeley Livermore GEOTHM Program is the major analytical tool used in the analysis. The Intermountain Power Project is the reference all coal-fired plant.

  1. Evaluation of genotype x environment interactions in maize hybrids using GGE biplot analysis

    Directory of Open Access Journals (Sweden)

    Fatma Aykut Tonk

    2011-01-01

    Full Text Available Seventeen hybrid maize genotypes were evaluated at four different locations in 2005 and 2006 cropping seasonsunder irrigated conditions in Turkey. The analysis of variance showed that mean squares of environments (E, genotypes (G andGE interactions (GEI were highly significant and accounted for 74, 7 and 19 % of treatment combination sum squares, respectively.To determine the effects of GEI on grain yield, the data were subjected to the GGE biplot analysis. Maize hybrid G16 can be proposedas reliably growing in test locations for high grain yield. Also, only the Yenisehir location could be best representative of overalllocations for deciding about which experimental hybrids can be recommended for grain yield in this study. Consequently, using ofgrain yield per plant instead of grain yield per plot in hybrid maize breeding programs could be preferred by private companies dueto some advantages.

  2. Evaluation of sensory panels of consumers of specialty coffee beverages using the boosting method in discriminant analysis

    Directory of Open Access Journals (Sweden)

    Gilberto Rodrigues Liska

    2015-12-01

    Full Text Available Automatic classification methods have been widely used in numerous situations and the boosting method has become known for use of a classification algorithm, which considers a set of training data and, from that set, constructs a classifier with reweighted versions of the training set. Given this characteristic, the aim of this study is to assess a sensory experiment related to acceptance tests with specialty coffees, with reference to both trained and untrained consumer groups. For the consumer group, four sensory characteristics were evaluated, such as aroma, body, sweetness, and final score, attributed to four types of specialty coffees. In order to obtain a classification rule that discriminates trained and untrained tasters, we used the conventional Fisher’s Linear Discriminant Analysis (LDA and discriminant analysis via boosting algorithm (AdaBoost. The criteria used in the comparison of the two approaches were sensitivity, specificity, false positive rate, false negative rate, and accuracy of classification methods. Additionally, to evaluate the performance of the classifiers, the success rates and error rates were obtained by Monte Carlo simulation, considering 100 replicas of a random partition of 70% for the training set, and the remaining for the test set. It was concluded that the boosting method applied to discriminant analysis yielded a higher sensitivity rate in regard to the trained panel, at a value of 80.63% and, hence, reduction in the rate of false negatives, at 19.37%. Thus, the boosting method may be used as a means of improving the LDA classifier for discrimination of trained tasters.

  3. Probabilistic modelling and analysis of stand-alone hybrid power systems

    International Nuclear Information System (INIS)

    Lujano-Rojas, Juan M.; Dufo-López, Rodolfo; Bernal-Agustín, José L.

    2013-01-01

    As a part of the Hybrid Intelligent Algorithm, a model based on an ANN (artificial neural network) has been proposed in this paper to represent hybrid system behaviour considering the uncertainty related to wind speed and solar radiation, battery bank lifetime, and fuel prices. The Hybrid Intelligent Algorithm suggests a combination of probabilistic analysis based on a Monte Carlo simulation approach and artificial neural network training embedded in a genetic algorithm optimisation model. The installation of a typical hybrid system was analysed. Probabilistic analysis was used to generate an input–output dataset of 519 samples that was later used to train the ANNs to reduce the computational effort required. The generalisation ability of the ANNs was measured in terms of RMSE (Root Mean Square Error), MBE (Mean Bias Error), MAE (Mean Absolute Error), and R-squared estimators using another data group of 200 samples. The results obtained from the estimation of the expected energy not supplied, the probability of a determined reliability level, and the estimation of expected value of net present cost show that the presented model is able to represent the main characteristics of a typical hybrid power system under uncertain operating conditions. - Highlights: • This paper presents a probabilistic model for stand-alone hybrid power system. • The model considers the main sources of uncertainty related to renewable resources. • The Hybrid Intelligent Algorithm has been applied to represent hybrid system behaviour. • The installation of a typical hybrid system was analysed. • The results obtained from the study case validate the presented model

  4. An analysis of hybrid power generation systems for a residential load

    Directory of Open Access Journals (Sweden)

    Ceran Bartosz

    2017-01-01

    Full Text Available This paper presents the results of an energetic and economical analysis of a hybrid power generation system (HPGS which utilises photovoltaic modules, wind turbines, fuel cells and an electrolyzer with hydrogen tank working as the energy storage. The analysis was carried out for three different residential loads, local solar radiation and local wind speed, based on the real measurement values. The analysis shows the optimal solution and the limits of the investment costs required for the system construction. The presented results confirm the effectiveness of the proposed approach, which could be assumed as a very useful tool in the design and analysis of a hybrid power generation system.

  5. Analysis of the Fuel Efficiency of a Hybrid Electric Drive with an Electric Power Splitter

    OpenAIRE

    D. Čundev

    2008-01-01

    This paper presents the results of an analysis of the fuel efficiency of a hybrid electric car drive, with an electric power splitter based on a double rotor synchronous permanent magnet generator. The results have been obtained through a precisely determined mathematical model and by simulating the characteristics of all essential values for the entire drive. This work is related to the experimental working stand for electric and hybrid car drive research, which has been developed at the Fac...

  6. Analysis of fixed tilt and sun tracking photovoltaic–micro wind based hybrid power systems

    International Nuclear Information System (INIS)

    Sinha, Sunanda; Chandel, S.S.

    2016-01-01

    Graphical abstract: 6 kW_p photovoltaic–micro wind based hybrid power system analysis in a Indian Western Himalayan location. - Highlights: • Power generation by a roof mounted photovoltaic–micro wind hybrid system is explored. • Optimum hybrid configurations using fixed and sun tracking photovoltaic systems are determined. • Analysis of hybrid systems with optimally tilted and different sun tracking systems is presented. • Two axis sun tracking systems are found to generate 4.88–26.29% more energy than fixed tilt system. • Hybrid system installed at optimum tilt angle is found to be cost effective than a sun tracking system. - Abstract: In this study fixed tilt and sun tracking photovoltaic based micro wind hybrid power systems are analyzed along with determining the optimum configurations for a 6 kW_p roof mounted micro wind based hybrid system using fixed and tracking photovoltaic systems to enhance the power generation potential in a low windy Indian hilly terrain with good solar resource. The main objective of the study is to enhance power generation by focusing on photovoltaic component of the hybrid system. A comparative power generation analysis of different configurations of hybrid systems with fixed tilt, monthly optimum tilt, yearly optimum tilt and 6 different sun tracking photovoltaic systems is carried out using Hybrid Optimization Model for Electric Renewables. Monthly and seasonal optimum tilt angles determined for the location vary between 0° and 60° with annual optimum tilt angle as 29.25°. The optimum configurations for all sun tracking systems except for the two axis tracking system is found to be 7 kW_p photovoltaic system, one 5 kW_p wind turbine, 10 batteries and a 2 kW_p inverter. The optimum configuration for two axis tracking system and two types of fixed tilt systems, is found to be a 8 kW_p photovoltaic system, one 5 kW_p wind turbine, 10 batteries and a 2 kW_p inverter. The results show that horizontal axis with

  7. [External therapy of plasma cell mastitis by jiuyi powder using partial least-squares discriminant analysis: a safety analysis].

    Science.gov (United States)

    Ye, Mei-na; Yang, Ming; Cheng, Yi-qin; Wang, Bing; Zhu, Ying; Xia, Ya-ru; Meng, Tian; Chen, Hao; Chen, Li-ying; Cheng, Hong-feng

    2015-04-01

    To evaluate the safety and the clinical value of external use of jiuyi Powder (JP) in treating plasma cell mastitis using partial least-squares discriminant analysis (PLSDA). Totally 50 patients with plasma cell mastitis treated by external use of JP were observed and biochemical examinations of blood and urine detected before application, at day 4 after application, at day 1 and 14 after discontinuation. Blood mercury and urinary mercury were detected before application, at day 1, 4, and 7 after application, at day 1 and 14 after discontinuation. Urinary mercury was also detected at 28 after discontinuation and 3 months after discontinuation. The information of wound, days of external application and the total dosage of external application were recorded before application, at day 1, 4, and 7 after application, as well as at day 1 after discontinuation. Then a discriminant model covering potential safety factors was set up by PLSDA after screening safety indices with important effects. The applicability of the model was assessed using area under ROC curve. Potential safety factors were assessed using variable importance in the projection (VIP). Urinary β2-microglobulin (β2-MG), urinary N-acetyl-β-D-glucosaminidase (NAG), 24 h urinary protein, and urinary α1-microglobulin (α1-MG) were greatly affected by external use of JP in treating plasma cell mastitis. The accuracy rate of PLSDA discriminate model was 74. 00%. The sensitivity, specificity, and the area under ROC curve was 0. 7826, 0. 7037, and 0. 8084, respectively. Three factors with greater effect on the potential safety were screened as follows: pre-application volume of the sore cavity, days of external application, and the total dosage of external application. PLSDA method could be used in analyzing bioinformation of clinical Chinese medicine. Urinary β2-MG and urinary NAG were two main safety monitoring indices. Days of external application and the total dosage of external application were main

  8. Thermoeconomic analysis of a fuel cell hybrid power system from the fuel cell experimental data

    Energy Technology Data Exchange (ETDEWEB)

    Alvarez, Tomas [Endesa Generacion, Ribera del Loira, 60, 28042 Madrid (Spain)]. E-mail: talvarez@endesa.es; Valero, Antonio [Fundacion CIRCE, Centro Politecnico Superior, Maria de Luna, 3, 50018 Zaragoza (Spain); Montes, Jose M. [ETSIMM-Universidad Politecnica de.Madrid, Rios Rosas, 21, 28003 Madrid (Spain)

    2006-08-15

    An innovative configuration of fuel cell technology is proposed based on a hybrid fuel cell system that integrates a turbogenerator to overcome the intrinsic limitations of fuel cells in conventional operation. An analysis is done of the application of molten carbonate fuel cell technology at the Guadalix Fuel Cell Test Facility, for the assessment of the performance of the fuel cell prototype to be integrated in the Hybrid Fuel Cell System. This is completed with a thermoeconomic analysis of the 100 kW cogeneration fuel cell power plant which was subsequently built. The operational results and design limitations are evaluated, together with the operational limits and thermodynamic inefficiencies (exergy destruction and losses) of the 100 kW fuel cell. This leads to the design of a hybrid system in order to demonstrate the possibilities and benefits of the new hybrid configuration. The results are quantified through a thermoeconomic analysis in order to get the most cost-effective plant configuration. One promising configuration is the MCFC topper where the fuel cell in the power plant behaves as a combustor for the turbogenerator. The latter behaves as the balance of plant for the fuel cell. The combined efficiency increased to 57% and NOx emissions are essentially eliminated. The synergy of the fuel cell/turbine hybrids lies mainly in the use of the rejected thermal energy and residual fuel from the fuel cell to drive the turbogenerator in a 500 kW hybrid system.

  9. Analysis and evaluation of hybrid scooter transmission systems

    Energy Technology Data Exchange (ETDEWEB)

    Sheu, Kuen-Bao [Department of Vehicle Engineering, National Formosa University, 64 Wunhua Road, Huwei, Yuenlin 63208 (China)

    2007-12-15

    This paper presents a new design concept of transmissions for the hybrid scooters. These transmissions consist of a one-degree-of-freedom planetary gear train and a two-degree-of-freedom planetary gear train to from a split power system and to combine the power of two power sources, a gasoline engine and an electric motor. In order to maximize the performance and reduce emissions, the transmissions can provide a hybrid scooter to run five operating modes: electric motor mode; engine mode; engine/charging mode; power mode, and regenerative braking mode. The main advantages of the transmissions proposed in this paper include the use of only one electric motor/generator, need not use clutch/brake for the shift of the operating modes, and high efficiency. The kinematics, power flow, and mechanical efficiency analyzes are performed; and according to these results, the evaluation of transmission power performances are accomplished. (author)

  10. Fabrication and performance analysis of concentrated hybrid photovoltaic system

    Directory of Open Access Journals (Sweden)

    Murthy Krishna

    2018-01-01

    Full Text Available Sun is the most important source of renewable source of energy. During the past few decades there has been an ever-increasing interest in Photovoltaic (PV cells as it directly converts solar radiation into electricity. This paper involves the performance study of photovoltaic system under concentrated solar radiation. The main problem with the concentration solar energy is the drastic increase in temperature of the photovoltaic module resulting in a decrease in performance efficiency of the system. This problem of overheating of the system can be overcome by providing cooling which would ensure operation of the module in the optimal temperature range. Hence, the setup would function as a hybrid model serving the dual purpose of power generation while also utilizing the waste heat for water heating applications. The experimental set up consist of a novel arrangement of concentrator and reflector and the cooling system. The Hybrid Photovoltaic System was repeatedly tested under real time conditions on several days. A comparison was drawn between the results obtained from direct exposure of a standard photovoltaic module to that obtained from the hybrid system in order to better understand the improvement in performance parameters. The study shown a significant improvement of output of standard photovoltaic module under the concentrated solar radiation.

  11. Analysis of alternative flow sheets for the hybrid chlorine cycle

    Energy Technology Data Exchange (ETDEWEB)

    Gooding, Charles H. [Department of Chemical and Biomolecular Engineering, 209 Earle Hall, Clemson University, Clemson, SC 29634-0909 (United States)

    2009-05-15

    This paper reports the results of the most complete conceptual study conducted to date on hydrogen production using the hybrid chlorine cycle. Three alternative process flow sheets were developed, each capable of producing hydrogen at 35 C (308 K) and 21 bar. The alternative approaches differ primarily in the way HCl is isolated and converted to hydrogen and chlorine gases. Aspen Plus trademark simulation software was used to model the unit processes, supplemented where necessary by custom Excel spreadsheets. Major equipment was sized for a 200-million kg/yr plant; feasible materials of construction were identified; fixed capital investments and variable costs were estimated. Estimated net thermal efficiencies of the flow sheets range from 30% to 36%, based on the lower heating value of the hydrogen produced. With electrical power valued at $0.05/kWh, the cost of hydrogen produced by the hybrid chlorine cycle would be at least $3/kg. These results indicate that direct electrolysis of water is a more attractive way to produce hydrogen than any presently conceived version of the hybrid chlorine cycle. (author)

  12. Hybrid Psychology: The marriage of discourse analysis with neuroscience

    Directory of Open Access Journals (Sweden)

    Rom Harré

    2010-07-01

    Full Text Available As the 21st Century opened the controversial and unstable discipline of `academic psychology’ seemed to separating into two radically distinct and perhaps irreconcilable domains. Discursive psychology focused on the management of meaning in a world of norms while Neuropsychology focused on the investigation of brain and cognitive processes. These two domains can be reconciled in a hybrid science that brings them together into a synthesis more powerful than anything psychologists have achieved before. In this paper means Hybrid psychology depends on the intuition that while brains can be assimilated into the world of persons, people cannot be assimilated into the world of cell structures and molecular processes. The project of setting up a hybrid science, in which the symbol using capacities of human beings are brought into a unified scheme with the organic aspects of members of the species homo sapiens, demands the dissolution of the mind-body problem, somehow setting it aside as an illusion, based on a mistaken presupposition.

  13. Genotype differences in 13C discrimination between atmosphere and leaf matter match differences in transpiration efficiency at leaf and whole-plant levels in hybrid Populus deltoides x nigra.

    Science.gov (United States)

    Rasheed, Fahad; Dreyer, Erwin; Richard, Béatrice; Brignolas, Franck; Montpied, Pierre; Le Thiec, Didier

    2013-01-01

    (13) C discrimination between atmosphere and bulk leaf matter (Δ(13) C(lb) ) is frequently used as a proxy for transpiration efficiency (TE). Nevertheless, its relevance is challenged due to: (1) potential deviations from the theoretical discrimination model, and (2) complex time integration and upscaling from leaf to whole plant. Six hybrid genotypes of Populus deltoides×nigra genotypes were grown in climate chambers and tested for whole-plant TE (i.e. accumulated biomass/water transpired). Net CO(2) assimilation rates (A) and stomatal conductance (g(s) ) were recorded in parallel to: (1) (13) C in leaf bulk material (δ(13) C(lb) ) and in soluble sugars (δ(13) C(ss) ) and (2) (18) O in leaf water and bulk leaf material. Genotypic means of δ(13) C(lb) and δ(13) C(ss) were tightly correlated. Discrimination between atmosphere and soluble sugars was correlated with daily intrinsic TE at leaf level (daily mean A/g(s) ), and with whole-plant TE. Finally, g(s) was positively correlated to (18) O enrichment of bulk matter or water of leaves at individual level, but not at genotype level. We conclude that Δ(13) C(lb) captures efficiently the genetic variability of whole-plant TE in poplar. Nevertheless, scaling from leaf level to whole-plant TE requires to take into account water losses and respiration independent of photosynthesis, which remain poorly documented. © 2012 Blackwell Publishing Ltd.

  14. The role of critical ethnic awareness and social support in the discrimination-depression relationship among Asian Americans: path analysis.

    Science.gov (United States)

    Kim, Isok

    2014-01-01

    This study used a path analytic technique to examine associations among critical ethnic awareness, racial discrimination, social support, and depressive symptoms. Using a convenience sample from online survey of Asian American adults (N = 405), the study tested 2 main hypotheses: First, based on the empowerment theory, critical ethnic awareness would be positively associated with racial discrimination experience; and second, based on the social support deterioration model, social support would partially mediate the relationship between racial discrimination and depressive symptoms. The result of the path analysis model showed that the proposed path model was a good fit based on global fit indices, χ²(2) = 4.70, p = .10; root mean square error of approximation = 0.06; comparative fit index = 0.97; Tucker-Lewis index = 0.92; and standardized root mean square residual = 0.03. The examinations of study hypotheses demonstrated that critical ethnic awareness was directly associated (b = .11, p Asian Americans. This study highlights the usefulness of the critical ethnic awareness concept as a way to better understand how Asian Americans might perceive and recognize racial discrimination experiences in relation to its mental health consequences.

  15. Subclassification and Detection of New Markers for the Discrimination of Primary Liver Tumors by Gene Expression Analysis Using Oligonucleotide Arrays.

    Science.gov (United States)

    Hass, Holger G; Vogel, Ulrich; Scheurlen, Michael; Jobst, Jürgen

    2017-12-26

    The failure to correctly differentiate between intrahepatic cholangiocarcinoma [CC] and hepatocellular carcinoma [HCC] is a significant clinical problem, particularly in terms of the different treatment goals for both cancers. In this study a specific gene expression profile to discriminate these two subgroups of liver cancer was established and potential diagnostic markers for clinical use were analyzed. To evaluate the gene expression profiles of HCC and intrahepatic CC, Oligonucleotide arrays ( Affymetrix U133A) were used. Overexpressed genes were checked for their potential use as new markers for discrimination and their expression values were validated by reverse transcription polymerase chain reaction and immunohistochemistry analyses. 695 genes/expressed sequence tags (ESTs) in HCC (245 up-/450 down-regulated) and 552 genes/ESTs in CC (221 up-/331 down-regulated) were significantly dysregulated (p〈0.05, fold change >2, ≥70%). Using a supervised learning method, and one-way analysis of variance a specific 270-gene expression profile that enabled rapid, reproducible differentiation between both tumors and non-malignant liver tissues was established. A panel of 12 genes (e.g. HSP90β, ERG1, GPC3, TKT, ACLY, and NME1 for HCC; SPT2, T4S3, CNX43, TTD1, HBD01 for CC) were detected and partly described for the first time as potential discrimination markers. A specific gene expression profile for discrimination of primary liver cancer was identified and potential marker genes with feasible clinical impact were described.

  16. The use of kernel local Fisher discriminant analysis for the channelization of the Hotelling model observer

    Science.gov (United States)

    Wen, Gezheng; Markey, Mia K.

    2015-03-01

    It is resource-intensive to conduct human studies for task-based assessment of medical image quality and system optimization. Thus, numerical model observers have been developed as a surrogate for human observers. The Hotelling observer (HO) is the optimal linear observer for signal-detection tasks, but the high dimensionality of imaging data results in a heavy computational burden. Channelization is often used to approximate the HO through a dimensionality reduction step, but how to produce channelized images without losing significant image information remains a key challenge. Kernel local Fisher discriminant analysis (KLFDA) uses kernel techniques to perform supervised dimensionality reduction, which finds an embedding transformation that maximizes betweenclass separability and preserves within-class local structure in the low-dimensional manifold. It is powerful for classification tasks, especially when the distribution of a class is multimodal. Such multimodality could be observed in many practical clinical tasks. For example, primary and metastatic lesions may both appear in medical imaging studies, but the distributions of their typical characteristics (e.g., size) may be very different. In this study, we propose to use KLFDA as a novel channelization method. The dimension of the embedded manifold (i.e., the result of KLFDA) is a counterpart to the number of channels in the state-of-art linear channelization. We present a simulation study to demonstrate the potential usefulness of KLFDA for building the channelized HOs (CHOs) and generating reliable decision statistics for clinical tasks. We show that the performance of the CHO with KLFDA channels is comparable to that of the benchmark CHOs.

  17. Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

    Directory of Open Access Journals (Sweden)

    Guan Yu

    Full Text Available Accurately identifying mild cognitive impairment (MCI individuals who will progress to Alzheimer's disease (AD is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI and fluorodeoxyglucose positron emission tomography (FDG-PET. However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI subjects and 226 stable MCI (sMCI subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images and also the single-task classification method (using only MRI or only subjects with both MRI and

  18. Identifikasi Huruf Kapital Tulisan Tangan Menggunakan Linear Discriminant Analysis dan Euclidean Distance

    Directory of Open Access Journals (Sweden)

    Septa Cahyani

    2018-04-01

    Full Text Available The human ability to recognize a variety of objects, however complex the object, is the special ability that humans possess. Any normal human will have no difficulty in recognizing handwriting objects between an author and another author. With the rapid development of digital technology, the human ability to recognize handwriting objects has been applied in a program known as Computer Vision. This study aims to create identification system different types of handwriting capital letters that have different sizes, thickness, shape, and tilt (distinctive features in handwriting using Linear Discriminant Analysis (LDA and Euclidean Distance methods. LDA is used to obtain characteristic characteristics of the image and provide the distance between the classes becomes larger, while the distance between training data in one class becomes smaller, so that the introduction time of digital image of handwritten capital letter using Euclidean Distance becomes faster computation time (by searching closest distance between training data and data testing. The results of testing the sample data showed that the image resolution of 50x50 pixels is the exact image resolution used for data as much as 1560 handwritten capital letter data compared to image resolution 25x25 pixels and 40x40 pixels. While the test data and training data testing using the method of 10-fold cross validation where 1404 for training data and 156 for data testing showed identification of digital image handwriting capital letter has an average effectiveness of the accuracy rate of 75.39% with the average time computing of 0.4199 seconds.

  19. Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

    Science.gov (United States)

    Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

    2014-01-01

    Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images

  20. Differential discriminator

    International Nuclear Information System (INIS)

    Dukhanov, V.I.; Mazurov, I.B.

    1981-01-01

    A principal flowsheet of a differential discriminator intended for operation in a spectrometric circuit with statistical time distribution of pulses is described. The differential discriminator includes four integrated discriminators and a channel of piled-up signal rejection. The presence of the rejection channel enables the discriminator to operate effectively at loads of 14x10 3 pulse/s. The temperature instability of the discrimination thresholds equals 250 μV/ 0 C. The discrimination level changes within 0.1-5 V, the level shift constitutes 0.5% for the filling ratio of 1:10. The rejection coefficient is not less than 90%. Alpha spectrum of the 228 Th source is presented to evaluate the discriminator operation with the rejector. The rejector provides 50 ns time resolution

  1. Automated discrimination of lower and higher grade gliomas based on histopathological image analysis

    Directory of Open Access Journals (Sweden)

    Hojjat Seyed Mousavi

    2015-01-01

    Full Text Available Introduction: Histopathological images have rich structural information, are multi-channel in nature and contain meaningful pathological information at various scales. Sophisticated image analysis tools that can automatically extract discriminative information from the histopathology image slides for diagnosis remain an area of significant research activity. In this work, we focus on automated brain cancer grading, specifically glioma grading. Grading of a glioma is a highly important problem in pathology and is largely done manually by medical experts based on an examination of pathology slides (images. To complement the efforts of clinicians engaged in brain cancer diagnosis, we develop novel image processing algorithms and systems to automatically grade glioma tumor into two categories: Low-grade glioma (LGG and high-grade glioma (HGG which represent a more advanced stage of the disease. Results: We propose novel image processing algorithms based on spatial domain analysis for glioma tumor grading that will complement the clinical interpretation of the tissue. The image processing techniques are developed in close collaboration with medical experts to mimic the visual cues that a clinician looks for in judging of the grade of the disease. Specifically, two algorithmic techniques are developed: (1 A cell segmentation and cell-count profile creation for identification of Pseudopalisading Necrosis, and (2 a customized operation of spatial and morphological filters to accurately identify microvascular proliferation (MVP. In both techniques, a hierarchical decision is made via a decision tree mechanism. If either Pseudopalisading Necrosis or MVP is found present in any part of the histopathology slide, the whole slide is identified as HGG, which is consistent with World Health Organization guidelines. Experimental results on the Cancer Genome Atlas database are presented in the form of: (1 Successful detection rates of pseudopalisading necrosis

  2. Predicting The Type Of Pregnancy Using Flexible Discriminate Analysis And Artificial Neural Networks: A Comparison Study

    International Nuclear Information System (INIS)

    Hooman, A.; Mohammadzadeh, M.

    2008-01-01

    Some medical and epidemiological surveys have been designed to predict a nominal response variable with several levels. With regard to the type of pregnancy there are four possible states: wanted, unwanted by wife, unwanted by husband and unwanted by couple. In this paper, we have predicted the type of pregnancy, as well as the factors influencing it using three different models and comparing them. Regarding the type of pregnancy with several levels, we developed a multinomial logistic regression, a neural network and a flexible discrimination based on the data and compared their results using tow statistical indices: Surface under curve (ROC) and kappa coefficient. Based on these tow indices, flexible discrimination proved to be a better fit for prediction on data in comparison to other methods. When the relations among variables are complex, one can use flexible discrimination instead of multinomial logistic regression and neural network to predict the nominal response variables with several levels in order to gain more accurate predictions

  3. EVALUATION OF HYBRIDIZATION BETWEEN PANGASIUS DJAMBAL BLEEKER 1846 AND PANGASIANODON HYPOPHTHALMUS (SAUVAGE 1878: BIOMETRIC CHARACTERIZATION AND GROWTH ANALYSIS

    Directory of Open Access Journals (Sweden)

    Rudhy Gustiano

    2007-06-01

    Full Text Available Possible use of pangasiid hybrids in aquaculture might generate potential impacts on wild populations. Therefore, rapid identification tools in the field such as growth rate are urgently needed. This study examines morphological characters and growth performance of P. djambal and P. hypophthalmus and their reciprocal hybrids. A detailed morphological study analysed 32 morphometric measurements and 5 meristic counts on hybrids of Pangasius djambal and P. hypophthalmus. Morphometric analysis and meristic counts showed that the reciprocal hybrids have intermediate characters except for gill rakers number which were lower than that of parental species. In general, the hybrids have tendency to be like P. hypophthalmus rather than P. djambal. The only typical character P. djambal appearing in hybrids is teeth shape, both vomerine and palatine. It was shown that the true hybrids have seven pelvic fin rays. Eight months of growth comparison in earthen ponds showed that the hybrids have a better performance for specific growth rate than the parental stock.

  4. Early discrimination of nasopharyngeal carcinoma based on tissue deoxyribose nucleic acid surface-enhanced Raman spectroscopy analysis

    Science.gov (United States)

    Qiu, Sufang; Li, Chao; Lin, Jinyong; Xu, Yuanji; Lu, Jun; Huang, Qingting; Zou, Changyan; Chen, Chao; Xiao, Nanyang; Lin, Duo; Chen, Rong; Pan, Jianji; Feng, Shangyuan

    2016-12-01

    Surface-enhanced Raman spectroscopy (SERS) was employed to detect deoxyribose nucleic acid (DNA) variations associated with the development of nasopharyngeal carcinoma (NPC). Significant SERS spectral differences between the DNA extracted from early NPC, advanced NPC, and normal nasopharyngeal tissue specimens were observed at 678, 729, 788, 1337, 1421, 1506, and 1573 cm-1, which reflects the genetic variations in NPC. Principal component analysis combined with discriminant function analysis for early NPC discrimination yielded a diagnostic accuracy of 86.8%, 92.3%, and 87.9% for early NPC, advanced NPC, and normal nasopharyngeal tissue DNA, respectively. In this exploratory study, we demonstrated the potential of SERS for early detection of NPC based on the DNA molecular study of biopsy tissues.

  5. EVOLUTION OF NEUROENDOCRINE CELL POPULATION AND PEPTIDERGIC INNERVATION, ASSESSED BY DISCRIMINANT ANALYSIS, DURING POSTNATAL DEVELOPMENT OF THE RAT PROSTATE

    Directory of Open Access Journals (Sweden)

    Rosario Rodríguez

    2011-05-01

    Full Text Available Serotonin immunoreactive neuroendocrine cells and peptidergic nerves (NPY and VIP could have a role in prostate growth and function. In the present study, rats grouped by stages of postnatal development (prepubertal, pubertal, young and aged adults were employed in order to ascertain whether age causes changes in the number of serotoninergic neuroendocrine cells and the length of NPY and VIP fibres. Discriminant analysis was performed in order to ascertain the classificatory power of stereologic variables (absolute and relative measurements of cell number and fibre length on age groups. The following conclusions were drawn: a discriminant analysis confirms the androgen-dependence of both neuroendocrine cells and NPYVIP innervation during the postnatal development of the rat prostate; b periglandular innervation has more relevance than interglandular innervation in classifying the rats in age groups; and c peptidergic nerves from ventral, ampullar and periductal regions were more age-dependent than nerves from the dorso-lateral region.

  6. An automated land-use mapping comparison of the Bayesian maximum likelihood and linear discriminant analysis algorithms

    Science.gov (United States)

    Tom, C. H.; Miller, L. D.

    1984-01-01

    The Bayesian maximum likelihood parametric classifier has been tested against the data-based formulation designated 'linear discrimination analysis', using the 'GLIKE' decision and "CLASSIFY' classification algorithms in the Landsat Mapping System. Identical supervised training sets, USGS land use/land cover classes, and various combinations of Landsat image and ancilliary geodata variables, were used to compare the algorithms' thematic mapping accuracy on a single-date summer subscene, with a cellularized USGS land use map of the same time frame furnishing the ground truth reference. CLASSIFY, which accepts a priori class probabilities, is found to be more accurate than GLIKE, which assumes equal class occurrences, for all three mapping variable sets and both levels of detail. These results may be generalized to direct accuracy, time, cost, and flexibility advantages of linear discriminant analysis over Bayesian methods.

  7. HYBRID SULFUR PROCESS REFERENCE DESIGN AND COST ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Gorensek, M.; Summers, W.; Boltrunis, C.; Lahoda, E.; Allen, D.; Greyvenstein, R.

    2009-05-12

    This report documents a detailed study to determine the expected efficiency and product costs for producing hydrogen via water-splitting using energy from an advanced nuclear reactor. It was determined that the overall efficiency from nuclear heat to hydrogen is high, and the cost of hydrogen is competitive under a high energy cost scenario. It would require over 40% more nuclear energy to generate an equivalent amount of hydrogen using conventional water-cooled nuclear reactors combined with water electrolysis compared to the proposed plant design described herein. There is a great deal of interest worldwide in reducing dependence on fossil fuels, while also minimizing the impact of the energy sector on global climate change. One potential opportunity to contribute to this effort is to replace the use of fossil fuels for hydrogen production by the use of water-splitting powered by nuclear energy. Hydrogen production is required for fertilizer (e.g. ammonia) production, oil refining, synfuels production, and other important industrial applications. It is typically produced by reacting natural gas, naphtha or coal with steam, which consumes significant amounts of energy and produces carbon dioxide as a byproduct. In the future, hydrogen could also be used as a transportation fuel, replacing petroleum. New processes are being developed that would permit hydrogen to be produced from water using only heat or a combination of heat and electricity produced by advanced, high temperature nuclear reactors. The U.S. Department of Energy (DOE) is developing these processes under a program known as the Nuclear Hydrogen Initiative (NHI). The Republic of South Africa (RSA) also is interested in developing advanced high temperature nuclear reactors and related chemical processes that could produce hydrogen fuel via water-splitting. This report focuses on the analysis of a nuclear hydrogen production system that combines the Pebble Bed Modular Reactor (PBMR), under development by

  8. Rotation and Noise Invariant Near-Infrared Face Recognition by means of Zernike Moments and Spectral Regression Discriminant Analysis

    Czech Academy of Sciences Publication Activity Database

    Farokhi, S.; Shamsuddin, S. M.; Flusser, Jan; Sheikh, U. U.; Khansari, M.; Jafari-Khouzani, K.

    2013-01-01

    Roč. 22, č. 1 (2013), s. 1-11 ISSN 1017-9909 R&D Projects: GA ČR GAP103/11/1552 Keywords : face recognition * infrared imaging * image moments Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.850, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/flusser-rotation and noise invariant near-infrared face recognition by means of zernike moments and spectral regression discriminant analysis.pdf

  9. A qualitative analysis of hate speech reported to the Romanian National Council for Combating Discrimination (2003‑2015)

    OpenAIRE

    Adriana Iordache

    2015-01-01

    The article analyzes the specificities of Romanian hate speech over a period of twelve years through a qualitative analysis of 384 Decisions of the National Council for Combating Discrimination. The study employs a coding methodology which allows one to separate decisions according to the group that was the victim of hate speech. The article finds that stereotypes employed are similar to those encountered in the international literature. The main target of hate speech is the Roma, who are ...

  10. Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

    Science.gov (United States)

    Liu, Yan; Salvendy, Gavriel

    2009-05-01

    This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

  11. Ultimate refrigerating conditions, behavior turning and a thermodynamic analysis for absorption–compression hybrid refrigeration cycle

    International Nuclear Information System (INIS)

    Zheng Danxing; Meng Xuelin

    2012-01-01

    Highlights: ► Two novel fundamental concepts of the absorption refrigeration cycle were proposed. ► The interaction mechanism of compressor pressure increasing with other key-parameters was investigated. ► A set of optimal operating condition of hybrid refrigeration cycle was found. ► A simulation and investigation for R134a-DMF hybrid refrigeration cycle was performed. - Abstract: The absorption–compression hybrid refrigeration cycle has been considered as an effective approach to reduce the mechanical work consumption by using low-grade heat, such as solar energy. This work aims at studying the thermodynamic mechanism of the hybrid refrigeration cycle. Two fundamental concepts have been proposed, which are the ultimate refrigerating temperature (or the ultimate temperature lift) and the behavior turning. On the basis of that, the interaction mechanism of compressor pressure increasing with other key-parameters and the impact of compressor pressure increasing on the cycle performance have been investigated. The key-parameters include the concentration difference, the circulation ratio of working fluid, etc. The work points out that the hybrid refrigeration cycle performance varies with the change of compressor outlet pressure and depends on which one achieves dominance in the hybrid refrigeration cycle, the absorption sub-system or the compression sub-system. The behavior turning point during parameters changing corresponds to a maximum value of the heat powered coefficient of performance. In this case, the hybrid refrigeration cycle performance is optimal because the low-grade heat utilization is the most effective. In addition, to validate the theoretical analysis, a solar hybrid refrigeration cycle with R134a–DMF as working pair was simulated. The Peng–Robinson equation of state was adopted to calculate thermophysical properties when the reliability assessment of the prediction models on the available literature data of R134a–DMF system had been

  12. An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300

    Directory of Open Access Journals (Sweden)

    Jinyi Long

    2017-01-01

    Full Text Available The hybrid brain computer interface (BCI based on motor imagery (MI and P300 has been a preferred strategy aiming to improve the detection performance through combining the features of each. However, current methods used for combining these two modalities optimize them separately, which does not result in optimal performance. Here, we present an efficient framework to optimize them together by concatenating the features of MI and P300 in a block diagonal form. Then a linear classifier under a dual spectral norm regularizer is applied to the combined features. Under this framework, the hybrid features of MI and P300 can be learned, selected, and combined together directly. Experimental results on the data set of hybrid BCI based on MI and P300 are provided to illustrate competitive performance of the proposed method against other conventional methods. This provides an evidence that the method used here contributes to the discrimination performance of the brain state in hybrid BCI.

  13. A rapid method to screen for cell-wall mutants using discriminant analysis of Fourier transform infrared spectra

    International Nuclear Information System (INIS)

    Chen LiMei; Carpita, N.C.; Reiter, W.D.; Wilson, R.H.; Jeffries, C.; McCann, M.C.

    1998-01-01

    We have developed a rapid method to screen large numbers of mutant plants for a broad range of cell wall phenotypes using Fourier transform infrared (FTIR) microspectroscopy of leaves. We established and validated a model that can discriminate between the leaves of wild-type and a previously defined set of cell-wall mutants of Arabidopsis. Exploratory principal component analysis indicated that mutants deficient in different cell-wall sugars can be distinguished from each other. Discrimination of cell-wall mutants from wild-type was independent of variability in starch content or additional unrelated mutations that might be present in a heavily mutagenised population. We then developed an analysis of FTIR spectra of leaves obtained from over 1000 mutagenised flax plants, and selected 59 plants whose spectral variation from wild-type was significantly out of the range of a wild-type population, determined by Mahalanobis distance. Cell wall sugars from the leaves of selected putative mutants were assayed by gas chromatography-mass spectrometry and 42 showed significant differences in neutral sugar composition. The FTIR spectra indicated that six of the remaining 17 plants have altered ester or protein content. We conclude that linear discriminant analysis of FTIR spectra is a robust method to identify a broad range of structural and architectural alterations in cell walls, appearing as a consequence of developmental regulation, environmental adaptation or genetic modification. (author)

  14. Principal Component and Cluster Analysis as a Tool in the Assessment of Tomato Hybrids and Cultivars

    Directory of Open Access Journals (Sweden)

    G. Evgenidis

    2011-01-01

    Full Text Available Determination of germplasm diversity and genetic relationships among breeding materials is an invaluable aid in crop improvement strategies. This study assessed the breeding value of tomato source material. Two commercial hybrids along with an experimental hybrid and four cultivars were assessed with cluster and principal component analyses based on morphophysiological data, yield and quality, stability of performance, heterosis, and combining abilities. The assessment of commercial hybrids revealed a related origin and subsequently does not support the identification of promising offspring in their crossing. The assessment of the cultivars discriminated them according to origin and evolutionary and selection effects. On the Principal Component 1, the largest group with positive loading included, yield components, heterosis, general and specific combining ability, whereas the largest negative loading was obtained by qualitative and descriptive traits. The Principal Component 2 revealed two smaller groups, a positive one with phenotypic traits and a negative one with tolerance to inbreeding. Stability of performance was loaded positively and/or negatively. In conclusion, combing ability, yield components, and heterosis provided a mechanism for ensuring continued improvement in plant selection programs.

  15. EEG Classification for Hybrid Brain-Computer Interface Using a Tensor Based Multiclass Multimodal Analysis Scheme.

    Science.gov (United States)

    Ji, Hongfei; Li, Jie; Lu, Rongrong; Gu, Rong; Cao, Lei; Gong, Xiaoliang

    2016-01-01

    Electroencephalogram- (EEG-) based brain-computer interface (BCI) systems usually utilize one type of changes in the dynamics of brain oscillations for control, such as event-related desynchronization/synchronization (ERD/ERS), steady state visual evoked potential (SSVEP), and P300 evoked potentials. There is a recent trend to detect more than one of these signals in one system to create a hybrid BCI. However, in this case, EEG data were always divided into groups and analyzed by the separate processing procedures. As a result, the interactive effects were ignored when different types of BCI tasks were executed simultaneously. In this work, we propose an improved tensor based multiclass multimodal scheme especially for hybrid BCI, in which EEG signals are denoted as multiway tensors, a nonredundant rank-one tensor decomposition model is proposed to obtain nonredundant tensor components, a weighted fisher criterion is designed to select multimodal discriminative patterns without ignoring the interactive effects, and support vector machine (SVM) is extended to multiclass classification. Experiment results suggest that the proposed scheme can not only identify the different changes in the dynamics of brain oscillations induced by different types of tasks but also capture the interactive effects of simultaneous tasks properly. Therefore, it has great potential use for hybrid BCI.

  16. Performance analysis of a hybrid photovoltaic thermal solar air heater

    International Nuclear Information System (INIS)

    Othman, Mohd Yusof; Yatim, Baharudin; Abu Bakar, Mohd Nazari; Sopian, Kamaruzzaman

    2006-01-01

    A photovoltaic (PV/T) air heater is a collector that combines thermal and photovoltaic systems in one single hybrid generating unit. It generators both thermal and electrical energies simultaneously. A new design of a double-pass photovoltaic-thermal solar air collector with CPC and fins was successfully developed and fabricated at Universiti Kebangsaam Malaysia. This collector tested under actual environmental conditions to study its performance over a range of operating conditions. The test set-up, instrumentation and measurement are described further. It was found that the performance of the collector was in agreement with the theoretical prediction. Results of the outdoors test are presented and discussed(Author)

  17. Hybrid Vortex Method for the Aerodynamic Analysis of Wind Turbine

    Directory of Open Access Journals (Sweden)

    Hao Hu

    2015-01-01

    Full Text Available The hybrid vortex method, in which vortex panel method is combined with the viscous-vortex particle method (HPVP, was established to model the wind turbine aerodynamic and relevant numerical procedure program was developed to solve flow equations. The panel method was used to calculate the blade surface vortex sheets and the vortex particle method was employed to simulate the blade wake vortices. As a result of numerical calculations on the flow over a wind turbine, the HPVP method shows significant advantages in accuracy and less computation resource consuming. The validation of the aerodynamic parameters against Phase VI wind turbine experimental data is performed, which shows reasonable agreement.

  18. Describing three-class task performance: three-class linear discriminant analysis and three-class ROC analysis

    Science.gov (United States)

    He, Xin; Frey, Eric C.

    2007-03-01

    Binary ROC analysis has solid decision-theoretic foundations and a close relationship to linear discriminant analysis (LDA). In particular, for the case of Gaussian equal covariance input data, the area under the ROC curve (AUC) value has a direct relationship to the Hotelling trace. Many attempts have been made to extend binary classification methods to multi-class. For example, Fukunaga extended binary LDA to obtain multi-class LDA, which uses the multi-class Hotelling trace as a figure-of-merit, and we have previously developed a three-class ROC analysis method. This work explores the relationship between conventional multi-class LDA and three-class ROC analysis. First, we developed a linear observer, the three-class Hotelling observer (3-HO). For Gaussian equal covariance data, the 3- HO provides equivalent performance to the three-class ideal observer and, under less strict conditions, maximizes the signal to noise ratio for classification of all pairs of the three classes simultaneously. The 3-HO templates are not the eigenvectors obtained from multi-class LDA. Second, we show that the three-class Hotelling trace, which is the figureof- merit in the conventional three-class extension of LDA, has significant limitations. Third, we demonstrate that, under certain conditions, there is a linear relationship between the eigenvectors obtained from multi-class LDA and 3-HO templates. We conclude that the 3-HO based on decision theory has advantages both in its decision theoretic background and in the usefulness of its figure-of-merit. Additionally, there exists the possibility of interpreting the two linear features extracted by the conventional extension of LDA from a decision theoretic point of view.

  19. Computer code MLCOSP for multiple-correlation and spectrum analysis with a hybrid computer

    International Nuclear Information System (INIS)

    Oguma, Ritsuo; Fujii, Yoshio; Usui, Hozumi; Watanabe, Koichi

    1975-10-01

    Usage of the computer code MLCOSP(Multiple Correlation and Spectrum) developed is described for a hybrid computer installed in JAERI Functions of the hybrid computer and its terminal devices are utilized ingeniously in the code to reduce complexity of the data handling which occurrs in analysis of the multivariable experimental data and to perform the analysis in perspective. Features of the code are as follows; Experimental data can be fed to the digital computer through the analog part of the hybrid computer by connecting with a data recorder. The computed results are displayed in figures, and hardcopies are taken when necessary. Series-messages to the code are shown on the terminal, so man-machine communication is possible. And further the data can be put in through a keyboard, so case study according to the results of analysis is possible. (auth.)

  20. Multiple endmember spectral-angle-mapper (SAM) analysis improves discrimination of Savanna tree species

    CSIR Research Space (South Africa)

    Cho, Moses A

    2009-08-01

    Full Text Available of this paper was to evaluate the classification performance of a multiple-endmember spectral angle mapper (SAM) classification approach in discriminating seven common African savanna tree species and to compare the results with the traditional SAM classifier...

  1. An Information Analysis of 2-, 3-, and 4-Word Verbal Discrimination Learning.

    Science.gov (United States)

    Arima, James K.; Gray, Francis D.

    Information theory was used to qualify the difficulty of verbal discrimination (VD) learning tasks and to measure VD performance. Words for VD items were selected with high background frequency and equal a priori probabilities of being selected as a first response. Three VD lists containing only 2-, 3-, or 4-word items were created and equated for…

  2. A Qualitative Analysis of Multiracial Students' Experiences with Prejudice and Discrimination in College

    Science.gov (United States)

    Museus, Samuel D.; Lambe Sariñana, Susan A.; Yee, April L.; Robinson, Thomas E.

    2016-01-01

    Mixed-race persons constitute a substantial and growing population in the United States. We examined multiracial college students' experiences with prejudice and discrimination in college with conducted focus group interviews with 12 mixed-race participants and individual interviews with 22 mixed-race undergraduates to understand how they…

  3. Using a Hybrid Cost-FMEA Analysis for Wind Turbine Reliability Analysis

    Directory of Open Access Journals (Sweden)

    Nacef Tazi

    2017-02-01

    Full Text Available Failure mode and effects analysis (FMEA has been proven to be an effective methodology to improve system design reliability. However, the standard approach reveals some weaknesses when applied to wind turbine systems. The conventional criticality assessment method has been criticized as having many limitations such as the weighting of severity and detection factors. In this paper, we aim to overcome these drawbacks and develop a hybrid cost-FMEA by integrating cost factors to assess the criticality, these costs vary from replacement costs to expected failure costs. Then, a quantitative comparative study is carried out to point out average failure rate, main cause of failure, expected failure costs and failure detection techniques. A special reliability analysis of gearbox and rotor-blades are presented.

  4. Power quality analysis of hybrid renewable energy system

    Directory of Open Access Journals (Sweden)

    Rinchin W. Mosobi

    2015-12-01

    Full Text Available An hybrid renewable energy sources consisting of solar photovoltaic, wind energy system, and a microhydro system is proposed in this paper. This system is suitable for supplying electricity to isolated locations or remote villages far from the grid supply. The solar photovoltaic system is modeled with two power converters, the first one being a DC-DC converter along with an maximum power point tracking to achieve a regulated DC output voltage and the second one being a DC-AC converter to obtain AC output. The wind energy system is modeled with a wind-turbine prime mover with varying wind speed and fixed pitch angle to drive an self excited induction generator (SEIG. Owing to inherent drooping characteristics of the SEIG, a closed loop turbine input system is incorporated. The microhydro system is modeled with a constant input power to drive an SEIG. The three different sources are integrated through an AC bus and the proposed hybrid system is supplied to R, R-L, and induction motor loads. A static compensator is proposed to improve the load voltage and current profiles; it also mitigates the harmonic contents of the voltage and current. The static synchronous compensator is realized by means of a three-phase IGBT-based current-controlled voltage source inverter with a self-supporting DC bus. The complete system is modeled and simulated using Matlab/Simulink. The simulation results obtained illustrate the feasibility of the proposed system and are found to be satisfactory.

  5. Analysis of a Hybrid Solar-Assisted Trigeneration System

    Directory of Open Access Journals (Sweden)

    Elisa Marrasso

    2016-09-01

    Full Text Available A hybrid solar-assisted trigeneration system is analyzed in this paper. The system is composed of a 20 m2 solar field of evacuated tube collectors, a natural gas fired micro combined heat and power system delivering 12.5 kW of thermal power, an absorption heat pump (AHP with a nominal cooling power of 17.6 kW, two storage tanks (hot and cold and an electric auxiliary heater (AH. The plant satisfies the energy demand of an office building located in Naples (Southern Italy. The electric energy of the cogenerator is used to meet the load and auxiliaries electric demand; the interactions with the grid are considered in cases of excess or over requests. This hybrid solution is interesting for buildings located in cities or historical centers with limited usable roof surface to install a conventional solar heating and cooling (SHC system able to achieve high solar fraction (SF. The results of dynamic simulation show that a tilt angle of 30° maximizes the SF of the system on annual basis achieving about 53.5%. The influence on the performance of proposed system of the hot water storage tank (HST characteristics (volume, insulation is also studied. It is highlighted that the SF improves when better insulated and bigger HSTs are considered. A maximum SF of about 58.2% is obtained with a 2000 L storage, whereas the lower thermal losses take place with a better insulated 1000 L tank.

  6. Comparative genomic hybridization of cancer of the gastroesophageal junction: deletion of 14Q31-32.1 discriminates between esophageal (Barrett's) and gastric cardia adenocarcinomas.

    Science.gov (United States)

    van Dekken, H; Geelen, E; Dinjens, W N; Wijnhoven, B P; Tilanus, H W; Tanke, H J; Rosenberg, C

    1999-02-01

    Incidence rates have risen rapidly for esophageal and gastric cardia adenocarcinomas. These cancers, arising at and around the gastroesophageal junction (GEJ), share a poor prognosis. In contrast, there is no consensus with respect to clinical staging resulting in possible adverse effects on treatment and survival. The goal of this study was to provide more insight into the genetic changes underlying esophageal and gastric cardia adenocarcinomas. We have used comparative genomic hybridization for a genetic analysis of 28 adenocarcinomas of the GEJ. Eleven tumors were localized in the distal esophagus and related to Barrett's esophagus, and 10 tumors were situated in the gastric cardia. The remaining seven tumors were located at the junction and could not be classified as either Barrett-related, or gastric cardia. We found alterations in all 28 neoplasms. Gains and losses were distinguished in comparable numbers. Frequent loss (> or = 25% of all tumors) was detected, in decreasing order of frequency, on 4pq (54%), 14q (46%), 18q (43%), 5q (36%), 16q (36%), 9p (29%), 17p (29%), and 21q (29%). Frequent gain (> or = 25% of all tumors) was observed, in decreasing order of frequency, on 20pq (86%), 8q (79%), 7p (61%), 13q (46%), 12q (39%), 15q (39%), 1q (36%), 3q (32%), 5p (32%), 6p (32%), 19q (32%), Xpq (32%), 17q (29%), and 18p (25%). Nearly all patients were male, and loss of chromosome Y was frequently noted (64%). Recurrent high-level amplifications (> 10% of all tumors) were seen at 8q23-24.1, 15q25, 17q12-21, and 19q13.1. Minimal overlapping regions could be determined at multiple locations (candidate genes are in parentheses): minimal regions of overlap for deletions were assigned to 3p14 (FHIT, RCA1), 5q14-21 (APC, MCC), 9p21 (MTS1/CDKN2), 14q31-32.1 (TSHR), 16q23, 18q21 (DCC, P15) and 21q21. Minimal overlapping amplified sites could be seen at 5p14 (MLVI2), 6p12-21.1 (NRASL3), 7p12 (EGFR), 8q23-24.1 (MYC), 12q21.1, 15q25 (IGF1R), 17q12-21 (ERBB2/HER2-neu), 19q

  7. Gender-based discrimination in South Africa: A quantitative analysis of fairness of remuneration

    Directory of Open Access Journals (Sweden)

    Renier Steyn

    2015-05-01

    Full Text Available Equity is important to most individuals and its perceived absence  may impact negatively on individual and organisational performance. The concept of equity presupposes fair treatment, while discrimination implies unfair treatment. The perceptions of discrimination, or being treated unfairly, may result from psycho-social processes, or from data that justifies discrimination and is quantifiable. Objectives: To assess whether differences in post grading and remuneration for males and females are based on gender, rather than on quantifiable variables that could justify these differences. Method: Biographical information was gathered from 1740 employees representing 29 organisations. The data collected included self-reported post grading (dependent variable and 14 independent variables, which may predict the employees’ post gradings. The independent variables related primarily to education, tenure and family responsibility. Results: Males reported higher post gradings and higher salaries than those of females, but the difference was not statistically significant and the practical significance of this difference was slight. Qualification types, job specific training, and membership of professional bodies did not affect post grading along gender lines. The ways in which work experience was measured had no influence on post grading or salary for either males or females. Furthermore, family responsibility, union membership and the type of work the employees performed did not influence the employees’ post grading. The only difference found concerned the unfair treatment of males, particularly those who were well-qualified.   Conclusions: Objective evidence of unfair gender-based discrimination affecting post grading and salary is scarce, and the few differences that do occur have little statistical and practical significance. Perceptions of being discriminated against may therefore more often be seen as the result of psycho-social processes and

  8. Hybrid Real-time Zero-day Malware Analysis and Reporting System

    OpenAIRE

    Ratinder Kaur; Maninder Singh

    2016-01-01

    To understand completely the malicious intents of a zero-day malware there is really no automated way. There is no single best approach for malware analysis so it demands to combine existing static, dynamic and manual malware analysis techniques in a single unit. In this paper a hybrid real-time analysis and reporting system is presented. The proposed system integrates various malware analysis tools and utilities in a component-based architecture. The system automatica...

  9. Studies in genetic discrimination. Final progress report

    Energy Technology Data Exchange (ETDEWEB)

    1994-06-01

    We have screened 1006 respondents in a study of genetic discrimination. Analysis of these responses has produced evidence of the range of institutions engaged in genetic discrimination and demonstrates the impact of this discrimination on the respondents to the study. We have found that both ignorance and policy underlie genetic discrimination and that anti-discrimination laws are being violated.

  10. Yield stability and adaptability of maize hybrids based on GGE biplot analysis characteristics

    Directory of Open Access Journals (Sweden)

    Marcio Balestre

    2009-01-01

    Full Text Available The objective of this study was to evaluate stability and adaptability of the grain yield of commercial intervarietalmaize hybrids by the GGE (Genotype and Genotype by Environment Interaction biplot and AMMI (Additive Main Effects andMultiplicative Interaction analyses. Two intervarietal hybrids (BIO 2 and BIO4 were evaluated together with single, doubleand three-way cross hybrids. The performance of the intervarietal hybrid BIO 4 was superior to all double and three-waycross hybrids and outmatched the single-cross hybrids by 43%. In terms of stability, BIO 2 was more stable than BIO4, whichis desirable, but biological stability, which is not necessarily desirable, was also observed, since the yield was below theenvironmental mean. The graphical GGE biplot analysis was superior to the AMMI1 since a greater portion of the sum ofsquares of GE and G+GE was captured and the predictive accuracy was higher. On the other hand, the AMMI2 graphoutperformed the GGE biplot in predictive accuracy and explanation of G + GE and GE, although the difference in accuracywas smaller than between GGE2 and AMMI1.

  11. Probing the transition state for nucleic acid hybridization using phi-value analysis.

    Science.gov (United States)

    Kim, Jandi; Shin, Jong-Shik

    2010-04-27

    Genetic regulation by noncoding RNA elements such as microRNA and small interfering RNA (siRNA) involves hybridization of a short single-stranded RNA with a complementary segment in a target mRNA. The physical basis of the hybridization process between the structured nucleic acids is not well understood primarily because of the lack of information about the transition-state structure. Here we use transition-state theory, inspired by phi-value analysis in protein folding studies, to provide quantitative analysis of the relationship between changes in the secondary structure stability and the activation free energy. Time course monitoring of the hybridization reaction was performed under pseudo-steady-state conditions using a single fluorophore. The phi-value analysis indicates that the native secondary structure remains intact in the transition state. The nativelike transition state was confirmed via examination of the salt dependence of the hybridization kinetics, indicating that the number of sodium ions associated with the transition state was not substantially affected by changes in the native secondary structure. These results propose that hybridization between structured nucleic acids undergoes a transition state leading to formation of a nucleation complex and then is followed by sequential displacement of preexisting base pairings involving successive small energy barriers. The proposed mechanism might provide new insight into physical processes during small RNA-mediated gene silencing, which is essential to selection of a target mRNA segment for siRNA design.

  12. Otolith shape analysis for stock discrimination of two Collichthys genus croaker (Pieces: Sciaenidae,) from the northern Chinese coast

    Science.gov (United States)

    Zhao, Bo; Liu, Jinhu; Song, Junjie; Cao, Liang; Dou, Shuozeng

    2017-08-01

    The otolith morphology of two croaker species (Collichthys lucidus and Collichthys niveatus) from three areas (Liaodong Bay, LD; Huanghe (Yellow) River estuary, HRE; Jiaozhou Bay, JZ) along the northern Chinese coast were investigated for species identification and stock discrimination. The otolith contour shape described by elliptic Fourier coefficients (EFC) were analysed using principal components analysis (PCA) and stepwise canonical discriminant analysis (CDA) to identify species and stocks. The two species were well differentiated, with an overall classification success rate of 97.8%. And variations in the otolith shapes were significant enough to discriminate among the three geographical samples of C. lucidus (67.7%) or C. niveatus (65.2%). Relatively high mis-assignment occurred between the geographically adjacent LD and HRE samples, which implied that individual mixing may exist between the two samples. This study yielded information complementary to that derived from genetic studies and provided information for assessing the stock structure of C. lucidus and C. niveatus in the Bohai Sea and the Yellow Sea.

  13. Modeling, analysis and control of fuel cell hybrid power systems

    Science.gov (United States)

    Suh, Kyung Won

    Transient performance is a key characteristic of fuel cells, that is sometimes more critical than efficiency, due to the importance of accepting unpredictable electric loads. To fulfill the transient requirement in vehicle propulsion and portable fuel cell applications, a fuel cell stack is typically coupled with a battery through a DC/DC converter to form a hybrid power system. Although many power management strategies already exist, they all rely on low level controllers that realize the power split. In this dissertation we design controllers that realize various power split strategies by directly manipulating physical actuators (low level commands). We maintain the causality of the electric dynamics (voltage and current) and investigate how the electric architecture affects the hybridization level and the power management. We first establish the performance limitations associated with a stand-alone and power-autonomous fuel cell system that is not supplemented by an additional energy storage and powers all its auxiliary components by itself. Specifically, we examine the transient performance in fuel cell power delivery as it is limited by the air supplied by a compressor driven by the fuel cell itself. The performance limitations arise from the intrinsic coupling in the fluid and electrical domain between the compressor and the fuel cell stack. Feedforward and feedback control strategies are used to demonstrate these limitations analytically and with simulations. Experimental tests on a small commercial fuel cell auxiliary power unit (APU) confirm the dynamics and the identified limitations. The dynamics associated with the integration of a fuel cell system and a DC/DC converter is then investigated. Decentralized and fully centralized (using linear quadratic techniques) controllers are designed to regulate the power system voltage and to prevent fuel cell oxygen starvation. Regulating these two performance variables is a difficult task and requires a compromise

  14. Optimal Threshold Determination for Discriminating Driving Anger Intensity Based on EEG Wavelet Features and ROC Curve Analysis

    Directory of Open Access Journals (Sweden)

    Ping Wan

    2016-08-01

    Full Text Available Driving anger, called “road rage”, has become increasingly common nowadays, affecting road safety. A few researches focused on how to identify driving anger, however, there is still a gap in driving anger grading, especially in real traffic environment, which is beneficial to take corresponding intervening measures according to different anger intensity. This study proposes a method for discriminating driving anger states with different intensity based on Electroencephalogram (EEG spectral features. First, thirty drivers were recruited to conduct on-road experiments on a busy route in Wuhan, China where anger could be inducted by various road events, e.g., vehicles weaving/cutting in line, jaywalking/cyclist crossing, traffic congestion and waiting red light if they want to complete the experiments ahead of basic time for extra paid. Subsequently, significance analysis was used to select relative energy spectrum of β band (β% and relative energy spectrum of θ band (θ% for discriminating the different driving anger states. Finally, according to receiver operating characteristic (ROC curve analysis, the optimal thresholds (best cut-off points of β% and θ% for identifying none anger state (i.e., neutral were determined to be 0.2183 ≤ θ% < 1, 0 < β% < 0.2586; low anger state is 0.1539 ≤ θ% < 0.2183, 0.2586 ≤ β% < 0.3269; moderate anger state is 0.1216 ≤ θ% < 0.1539, 0.3269 ≤ β% < 0.3674; high anger state is 0 < θ% < 0.1216, 0.3674 ≤ β% < 1. Moreover, the discrimination performances of verification indicate that, the overall accuracy (Acc of the optimal thresholds of β% for discriminating the four driving anger states is 80.21%, while 75.20% for that of θ%. The results can provide theoretical foundation for developing driving anger detection or warning devices based on the relevant optimal thresholds.

  15. 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....

  16. An Initial Analysis of LANDSAT-4 Thematic Mapper Data for the Discrimination of Agricultural, Forested Wetland, and Urban Land Covers

    Science.gov (United States)

    Quattrochi, D. A.

    1984-01-01

    An initial analysis of LANDSAT 4 Thematic Mapper (TM) data for the discrimination of agricultural, forested wetland, and urban land covers is conducted using a scene of data collected over Arkansas and Tennessee. A classification of agricultural lands derived from multitemporal LANDSAT Multispectral Scanner (MSS) data is compared with a classification of TM data for the same area. Results from this comparative analysis show that the multitemporal MSS classification produced an overall accuracy of 80.91% while the TM classification yields an overall classification accuracy of 97.06% correct.

  17. Neutron analysis of a hybrid system fusion-fission

    International Nuclear Information System (INIS)

    Dorantes C, J. J.; Francois L, J. L.

    2011-11-01

    The use of energy at world level implies the decrease of natural resources, reduction of fossil fuels, in particular, and a high environmental impact. In view of this problem, an alternative is the energy production for nuclear means, because up to now is one of the less polluting energy; however, the nuclear fuel wastes continue being even a problem without being solved. For the above mentioned this work intends the creation of a device that incorporates the combined technologies of fission and nuclear fusion, called Nuclear Hybrid Reactor Fusion-Fission (HRFF). The HRFF has been designed theoretically with base in experimental fusion reactors in different parts of the world like: United States, Russia, Japan, China and United Kingdom, mainly. The hybrid reactor model here studied corresponds at the Compact Nuclear Facility Source (CNFS). The importance of the CNFS resides in its feasibility, simple design, minor size and low cost; uses deuterium-tritium like main source of neutrons, and as fuel can use the spent fuel of conventional nuclear reactors, such as the current light water reactors. Due to the high costs of experimental research, this work consists on simulating in computer a proposed model of CNFS under normal conditions of operation, to modify the arrangement of the used fuel: MOX and IMF, to analyze the obtained results and to give final conclusions. In conclusion, the HRFF can be a versatile system for the management of spent fuel of light water reactors, so much for the possibility of actinides destruction, like for the breeding of fissile material. (Author)

  18. Morphometric analysis to discriminate between species: The case of the Megalobulimus leucostoma complex

    Directory of Open Access Journals (Sweden)

    Victor Borda

    2014-10-01

    Full Text Available Plasticity of conchological characters had led to erroneous descriptions and the accumulation of synonyms making difficult the discrimination among species. The land snail genus Megalobulimus is an example of this problem. Megalobulimus leucostoma (Sowerby, 1835 has three subspecies which are difficult to differentiate by using the original descriptions. The aim of this paper is to discriminate among the subspecies of M. leucostoma by using morphometric and distribution analyses. Both provide substantial differences between M. l. leucostoma and M. l lacunosus that would not support the subspecies status of the former. Megalobulimus leucostoma weyrauchi fits into the great conchological variability of M. l .leucostoma; also the sympatric status between these two subspecies would not support the subspecies status of the former, and M. l. weyrauchi should be considered as part of M. l. leucostoma.

  19. Micro-PIXE analysis of fish otoliths. Methodology and evaluation of first results for stock discrimination

    International Nuclear Information System (INIS)

    Sie, S.H.; Thresher, R.E.

    1992-01-01

    Micro-PIXE has been used to measure the trace element distribution in otoliths from several species of ocean fish, in order to investigate its possible use in stock discrimination. Trace elements detected include Sr, Fe, Mn, Ni, Zn, Cu, Se, Cd, Br, Hg and Pb. Trace elements Na, K, Cl, S and Cl were detected with the electron microprobe. The high sensitivity of PIXE demands a meticulous sample preparation procedure to avoid contamination problems. Practical problems associated with the application of the technique were investigated in detail. Preliminary results indicate that most trace elements except Sr, are present at close to the limits of detection at few ppm, but biologically significant data can be obtained for stock discrimination applications. (author)

  20. Analysis of Child Gender Discrimination Based on Adults' Consumption Patterns: Microdata Evidence from China

    OpenAIRE

    Feridoon Koohi-Kamali; R. Liu; Y. Liu

    2015-01-01

    The applications of the Rothbarth model of inferring child gender discrimination from the variations in parental living standard have consistently failed to uncover evidence for bias from surveys in countries with some of the world's worst welfare outcomes for girls. This paper demonstrates the importance of the remedies required for an effective implementation of that model with an application to a survey from urban China. The paper obtains econometric evidence for the presence of child gend...

  1. Post-Apartheid Trends in Gender Discrimination in South Africa: Analysis through Decomposition Techniques

    OpenAIRE

    Debra Shepherd

    2008-01-01

    Using appropriate econometric methods and 11 representative household surveys, this paper empirically assesses the extent and evolution of gender discrimination in the South African labour market over the post-apartheid period. Attention is also paid to the role that anti-discriminatory legislation has had to play in effecting change in the South African labour market. Much of the paper’s focus is placed on African women who would have benefited most from the new legislative environment. Afri...

  2. Prion strain discrimination based on rapid in vivo amplification and analysis by the cell panel assay.

    Directory of Open Access Journals (Sweden)

    Yervand Eduard Karapetyan

    Full Text Available Prion strain identification has been hitherto achieved using time-consuming incubation time determinations in one or more mouse lines and elaborate neuropathological assessment. In the present work, we make a detailed study of the properties of PrP-overproducing Tga20 mice. We show that in these mice the four prion strains examined are rapidly and faithfully amplified and can subsequently be discriminated by a cell-based procedure, the Cell Panel Assay.

  3. Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems

    International Nuclear Information System (INIS)

    Chen, Jun; Rabiti, Cristian

    2017-01-01

    Hybrid energy systems consisting of multiple energy inputs and multiple energy outputs have been proposed to be an effective element to enable ever increasing penetration of clean energy. In order to better understand the dynamic and probabilistic behavior of hybrid energy systems, this paper proposes a model combining Fourier series and autoregressive moving average (ARMA) to characterize historical weather measurements and to generate synthetic weather (e.g., wind speed) data. In particular, Fourier series is used to characterize the seasonal trend in historical data, while ARMA is applied to capture the autocorrelation in residue time series (e.g., measurements with seasonal trends subtracted). The generated synthetic wind speed data is then utilized to perform probabilistic analysis of a particular hybrid energy system configuration, which consists of nuclear power plant, wind farm, battery storage, natural gas boiler, and chemical plant. Requirements on component ramping rate, economic and environmental impacts of hybrid energy systems, and the effects of deploying different sizes of batteries in smoothing renewable variability, are all investigated. - Highlights: • Computational model to synthesize artificial wind speed data with consistent characteristics with database. • Fourier series to capture seasonal trends in the database. • Monte Carlo simulation and probabilistic analysis of hybrid energy systems. • Investigation of the effect of battery in smoothing variability of wind power generation.

  4. Pinpointing the classifiers of English language writing ability: A discriminant function analysis approach

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Shams

    2013-02-01

    Full Text Available     The major aim of this paper was to investigate the validity of language and intelligence factors for classifying Iranian English learners` writing performance. Iranian participants of the study took three tests for grammar, breadth, and depth of vocabulary, and two tests for verbal and narrative intelligence. They also produced a corpus of argumentative writings in answer to IELTS specimen. Several runs of discriminant function analyses were used to examine the classifying power of the five variables for discriminating between low and high ability L2 writers. The results revealed that among language factors, depth of vocabulary (collocational knowledge produces the best discriminant function. In general, narrative intelligence was found to be the most reliable predictor for membership in low or high groups. It was also found that, among the five sub-abilities of narrative intelligence, emplotment carries the highest classifying value. Finally, the applications and implications of the results for second language researchers, cognitive scientists, and applied linguists were discussed.Â

  5. Design, Synthesis, and Analysis of Minor Groove Binder Pyrrolepolyamide-2′-Deoxyguanosine Hybrids

    Directory of Open Access Journals (Sweden)

    Etsuko Kawashima

    2010-01-01

    Full Text Available Pyrrolepolyamide-2′-deoxyguanosine hybrids (Hybrid 2 and Hybrid 3 incorporating the 3-aminopropionyl or 3-aminopropyl linker were designed and synthesized on the basis of previously reported results of a pyrrolepolyamide-adenosine hybrid (Hybrid 1. Evaluation of the DNA binding sequence selectivity of pyrrolepolyamide-2′-deoxyguanosine hybrids was performed by CD spectral and Tm analyses. It was shown that Hybrid 3 possessed greater binding specificity than distamycin A, Hybrid 1 and Hybrid 2.

  6. Sex determination using discriminant function analysis in Indigenous (Kurubas) children and adolescents of Coorg, Karnataka, India: A lateral cephalometric study.

    Science.gov (United States)

    Devang Divakar, Darshan; John, Jacob; Al Kheraif, Abdulaziz Abdullah; Mavinapalla, Seema; Ramakrishnaiah, Ravikumar; Vellappally, Sajith; Hashem, Mohamed Ibrahim; Dalati, M H N; Durgesh, B H; Safadi, Rima A; Anil, Sukumaran

    2016-11-01

    Aim: To test the validity of sex discrimination using lateral cephalometric radiograph and discriminant function analysis in Indigenous (Kuruba) children and adolescents of Coorg, Karnataka, India. Methods and materials: Six hundred and sixteen lateral cephalograms of 380 male and 236 females of age ranging from 6.5 to 18 years of Indigenous population of Coorg, Karnataka, India called Kurubas having a normal occlusion were included in the study. Lateral cephalograms were obtained in a standard position with teeth in centric occlusion and lips relaxed. Each radiograph was traced and cephalometric landmarks were measured using digital calliper. Calculations of 24 cephalometric measurements were performed. Results: Males exhibited significantly greater mean angular and linear cephalometric measurements as compared to females ( p  gender. The reliability of the derived discriminant function was assessed among study subjects; 100% of males and females were recognized correctly. Conclusion: The final outcome of this study validates the existence of sexual dimorphism in the skeleton as early as 6.5 years of age. There is a need for further research to determine other landmarks that can help in sex determination and norms for Indigenous (Kuruba) population and also other Indigenous population of Coorg, Karnataka, India.

  7. Genotypic and Phenotypic Analysis of Dairy Lactococcus lactis Biodiversity in Milk: Volatile Organic Compounds as Discriminating Markers

    Science.gov (United States)

    Dhaisne, Amandine; Guellerin, Maeva; Laroute, Valérie; Laguerre, Sandrine; Le Bourgeois, Pascal; Loubiere, Pascal

    2013-01-01

    The diversity of nine dairy strains of Lactococcus lactis subsp. lactis in fermented milk was investigated by both genotypic and phenotypic analyses. Pulsed-field gel electrophoresis and multilocus sequence typing were used to establish an integrated genotypic classification. This classification was coherent with discrimination of the L. lactis subsp. lactis bv. diacetylactis lineage and reflected clonal complex phylogeny and the uniqueness of the genomes of these strains. To assess phenotypic diversity, 82 variables were selected as important dairy features; they included physiological descriptors and the production of metabolites and volatile organic compounds (VOCs). Principal-component analysis (PCA) demonstrated the phenotypic uniqueness of each of these genetically closely related strains, allowing strain discrimination. A method of variable selection was developed to reduce the time-consuming experimentation. We therefore identified 20 variables, all associated with VOCs, as phenotypic markers allowing discrimination between strain groups. These markers are representative of the three metabolic pathways involved in flavor: lipolysis, proteolysis, and glycolysis. Despite great phenotypic diversity, the strains could be divided into four robust phenotypic clusters based on their metabolic orientations. Inclusion of genotypic diversity in addition to phenotypic characters in the classification led to five clusters rather than four being defined. However, genotypic characters make a smaller contribution than phenotypic variables (no genetic distances selected among the most contributory variables). This work proposes an original method for the phenotypic differentiation of closely related strains in milk and may be the first step toward a predictive classification for the manufacture of starters. PMID:23709512

  8. An RNA-seq transcriptome analysis of floral buds of an interspecific Brassica hybrid between B. carinata and B. napus.

    Science.gov (United States)

    Chu, Pu; Liu, Huijuan; Yang, Qing; Wang, Yankun; Yan, Guixia; Guan, Rongzhan

    2014-12-01

    Interspecific hybridizations promote gene transfer between species and play an important role in plant speciation and crop improvement. However, hybrid sterility that commonly found in the first generation of hybrids hinders the utilization of interspecific hybridization. The combination of divergent parental genomes can create extensive transcriptome variations, and to determine these gene expression alterations and their effects on hybrids, an interspecific Brassica hybrid of B. carinata × B. napus was generated. Scanning electron microscopy analysis indicated that some of the hybrid pollen grains were irregular in shape and exhibited abnormal exine patterns compared with those from the parents. Using the Illumina HiSeq 2000 platform, 39,598, 32,403 and 42,208 genes were identified in flower buds of B. carinata cv. W29, B. napus cv. Zhongshuang 11 and their hybrids, respectively. The differentially expressed genes were significantly enriched in pollen wall assembly, pollen exine formation, pollen development, pollen tube growth, pollination, gene transcription, macromolecule methylation and translation, which might be associated with impaired fertility in the F1 hybrid. These results will shed light on the mechanisms underlying the low fertility of the interspecific hybrids and expand our knowledge of interspecific hybridization.

  9. Verification of hybrid analysis concept of soil-foundation interaction by field vibration tests. Pt. 2

    International Nuclear Information System (INIS)

    Katayama, I.; Niwa, A.; Kubo, Y.; Penzien, J.

    1987-01-01

    The paper describes the outline of the hybrid analysis code for soil-structure interaction (HASSI) and the results of numerical simulation of the responses obtained at the model 2C in both cases of the forced vibration test and the natural earthquake excitation. (orig./HP)

  10. Energy performance analysis for a photovoltaic, diesel, battery hybrid power supply system

    CSIR Research Space (South Africa)

    Tazvinga, Henerica

    2010-03-01

    Full Text Available This paper looks at an energy performance analysis for a photovoltaic, diesel, and battery hybrid power supply system. The procedure starts by the identification of the hourly load requirements for a typical target consumer and the concept of load...

  11. Analysis of Adoption Spell of Hybrid Maize in the Central Rift Valley ...

    African Journals Online (AJOL)

    This paper estimates farm household level determinants of the speed of adoption of hybrid maize in the central rift valley of Ethiopia in the framework of the dynamic time on cross-sectional data. Descriptive statistics and duration model were used to study the objectives of the study. The results from descriptive analysis ...

  12. Study and Analysis of Congestion Management in Hybrid Electric Market

    Directory of Open Access Journals (Sweden)

    Moayed Mohseni

    2013-01-01

    Full Text Available The congestion management system is a systematic approach, collaboratively developed and implemented throughout a metropolitan region that provides for the safe and effective management and operation of new and existing transportation facilities through the use of demand reduction and operational management strat­e­gies. In this paper we try to present some points which should be investigated in congestion management problems. We calculate different kinds of congestion problems which may be occurred in our network. Here, the hybrid model is used to solve problems in the electricity market to solve the congestion problem in the network and Benders techniques is used together with an optimal power flow (OPF. In fact, by using of Benders algorithm the problem is divided into two major and minor problems. Therefore, the major problem related to the economy sector and no network is included and the minor problem is to solve the network and examine the accuracy of the network. Benders algorithm has been tested on a standard network IEEE 24 bus and Matlab software is used to implement the algorithm.

  13. Analysis of a gas turbine driven hybrid drive system for heavy vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Malmquist, Anders

    1999-07-01

    The goal of this thesis has been to analyze the performance and behavior of a gas turbine driven hybrid drive train. The thesis covers both computer simulations and experimental tests. In two case studies, a number of measurements have been made on gas turbine driven hybrid vehicles that are developed by Volvo and ABB. In the recent years, much effort is currently put into the design and analysis of hybrid drive trains. Many studies involve computer simulations, but they are often made on a general level. This thesis concentrate on gas turbine driven hybrids for heavy vehicles, a field that has previously not been covered to a large extent in academic studies. A major contribution to the field of hybrid drive train design is the development of detailed simulation models that have a close connection to hybrids that are actually built and tested. The access to detailed gas turbine data has further enhanced the possibility to design a dynamic model of the gas turbine driven and the electric circuits. The combination of simulations and extensive field experience gains new knowledge on the properties of gas turbines in hybrid drive trains. Two simulation models have been developed in Matlab and Simulink. One is a quasi-steady state model that can be used for drive cycle simulations, e.g. a complete bus line. The other is a transient model that combines the thermodynamic properties of the gas turbine, the mechanical properties of the combined turbine-generator shaft, the electric power circuit and the control system. The transient model has been used to simulate the power response during accelerations and retardation. An analysis of the internal energy flows and the system efficiency of a hybrid drive train contributes to the understanding of the properties of series hybrid drive trains. An important part of the topology is that the system is based on a DC/DC-converter that is connected between the battery and the DC-bus. It controls the DC-bus voltage and by this

  14. Application of the exploratory analysis of data in the geographical discrimination of okra of Rio Grande do Norte and Pernambuco

    Directory of Open Access Journals (Sweden)

    Francisco Santos Panero

    2009-11-01

    Full Text Available The contents of Cu, Zn, Na, Fe, K, Ca, Mn, Mg, PO43-, Cl- and SO42- were determined in samples of okra of the municipal districts of Caruaru and Vitória de Santo Antão, in Pernambuco, as well as in the municipal districts of Ceará-Mirim, Macaíba and Extremoz in the state of Rio Grande do Norte. The objective of this work is the application of two methods of  exploratory analysis of data: Principal Component Analysis - PCA and Hierarquical Cluster Analysis - HCA in the geographical discrimination of okra originating in the states of Rio Grande do Norte and Pernambuco. The results showed that Cl- and Na were the main elements for the differentiation of the samples of Rio Grande do Norte and, the samples of Pernambuco presented the largest amount of Fe, Cu, Mn, Mg, Ca, Zn, K, PO43-, and SO42-. Boths the methods of exploratory analysis of data investigated are efficient for geographical discrimination of okra originating in Rio Grande do Norte and Pernambuco.

  15. Chemical discrimination of lubricant marketing types using direct analysis in real time time-of-flight mass spectrometry.

    Science.gov (United States)

    Maric, Mark; Harvey, Lauren; Tomcsak, Maren; Solano, Angelique; Bridge, Candice

    2017-06-30

    In comparison to other violent crimes, sexual assaults suffer from very low prosecution and conviction rates especially in the absence of DNA evidence. As a result, the forensic community needs to utilize other forms of trace contact evidence, like lubricant evidence, in order to provide a link between the victim and the assailant. In this study, 90 personal bottled and condom lubricants from the three main marketing types, silicone-based, water-based and condoms, were characterized by direct analysis in real time time of flight mass spectrometry (DART-TOFMS). The instrumental data was analyzed by multivariate statistics including hierarchal cluster analysis, principal component analysis, and linear discriminant analysis. By interpreting the mass spectral data with multivariate statistics, 12 discrete groupings were identified, indicating inherent chemical diversity not only between but within the three main marketing groups. A number of unique chemical markers, both major and minor, were identified, other than the three main chemical components (i.e. PEG, PDMS and nonoxynol-9) currently used for lubricant classification. The data was validated by a stratified 20% withheld cross-validation which demonstrated that there was minimal overlap between the groupings. Based on the groupings identified and unique features of each group, a highly discriminating statistical model was then developed that aims to provide the foundation for the development of a forensic lubricant database that may eventually be applied to casework. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  16. Analysis the parameters of seed quality in ns sunflower hybrid after processing in gravity separator

    Directory of Open Access Journals (Sweden)

    Jokić Goran

    2016-01-01

    Full Text Available This paper analyzed the processed seed of five sunflower hybrid seed developed at the Institute of Field and Vegetable Crops in Novi Sad before and after processing in gravity separator. The cultivars were Pegaz, Duško, NS Fantazija, Sumo 1 PR and NS Oskar. The analysis was conducted on seed lots processed in 2015 and involved the following parameters: seed purity percentage, 1.000-seed weight, germination energy, germination, seed moisture, number of sclerotinia per 1.000. The results showed that all the parameters of seed quality of sunflower hybrids were better after processing seeds in the gravity separator.

  17. Analysis of the Fuel Efficiency of a Hybrid Electric Drive with an Electric Power Splitter

    Directory of Open Access Journals (Sweden)

    D. Čundev

    2008-01-01

    Full Text Available This paper presents the results of an analysis of the fuel efficiency of a hybrid electric car drive, with an electric power splitter based on a double rotor synchronous permanent magnet generator. The results have been obtained through a precisely determined mathematical model and by simulating the characteristics of all essential values for the entire drive. This work is related to the experimental working stand for electric and hybrid car drive research, which has been developed at the Faculty of Electrical Engineering (FEE at CTU in Prague. 

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

    Directory of Open Access Journals (Sweden)

    Florian Heberle

    2014-07-01

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

  19. Techno-economical analysis of off-grid hybrid systems at Kutubdia Island, Bangladesh

    International Nuclear Information System (INIS)

    Kumar Nandi, Sanjoy; Ranjan Ghosh, Himangshu

    2010-01-01

    Kutubdia is an island in the southern coast of Bangladesh where mainland grid electricity is not present or would not feasible in near future. Presently, electricity is generated using a diesel generator by Bangladesh Power Development Board (BPDB) for a limited time and location. Due to its remote location, the fuel cost in Kutubdia is very expensive. In the present study one-year recorded wind by Bangladesh Centre of Advanced Studies (BCAS) location and other three potential locations for hybrid system analysis is discussed. The system configuration of the hybrid is achieved based on a theoretical domestic load at the island. The sizing of the hybrid power systems is discussed with 0% and 5% annual capacity of shortage. This feasibility study indicates that wind-PV-diesel system is feasible with 0% capacity of shortage and wind-diesel system is feasible with 5% annual capacity of shortage at all locations. As 5% annual capacity of shortage can be considered, the wind-diesel hybrid system will reduce net present cost as well as cost of energy to about 20% and the diesel consumption on the island can be reduced to about 50% of its present annual consumption. Such a hybrid system will reduce about 44% green house gases (GHG) from the local atmosphere.

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

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  1. Analysis of the Hybrid Power System for High-Altitude Unmanned Aircraft

    Directory of Open Access Journals (Sweden)

    Kangwen Sun

    2015-01-01

    Full Text Available The application of single solar array on high-altitude unmanned aircraft will waste energy because of its low conversion efficiency. Furthermore, since its energy utilization is limited, the surface temperature of solar array will rise to 70°C due to the waste solar energy, thus reducing the electrical performance of the solar array. In order to reuse the energy converted into heat by solar array, a hybrid power system is presented in this paper. In the hybrid power system, a new electricity-generating method is adopted to spread the photovoltaic cell on the wing surface and arrange photothermal power in the wing box section. Because the temperature on the back of photovoltaic cell is high, it can be used as the high-temperature heat source. The lower wing surface can be a low-temperature cold source. A high-altitude unmanned aircraft was used to analyze the performances of pure solar-powered aircraft and hybrid powered aircraft. The analysis result showed that the hybrid system could reduce the area of wing by 19% and that high-altitude unmanned aircraft with a 35 m or less wingspan could raise the utilization rate of solar energy per unit area after adopting the hybrid power system.

  2. Groundwater flow analysis using mixed hybrid finite element method for radioactive waste disposal facilities

    International Nuclear Information System (INIS)

    Aoki, Hiroomi; Shimomura, Masanori; Kawakami, Hiroto; Suzuki, Shunichi

    2011-01-01

    In safety assessments of radioactive waste disposal facilities, ground water flow analysis are used for calculating the radionuclide transport pathway and the infiltration flow rate of groundwater into the disposal facilities. For this type of calculations, the mixed hybrid finite element method has been used and discussed about the accuracy of ones in Europe. This paper puts great emphasis on the infiltration flow rate of groundwater into the disposal facilities, and describes the accuracy of results obtained from mixed hybrid finite element method by comparing of local water mass conservation and the reliability of the element breakdown numbers among the mixed hybrid finite element method, finite volume method and nondegenerated finite element method. (author)

  3. Clinical utility of an array comparative genomic hybridization analysis for Williams syndrome.

    Science.gov (United States)

    Yagihashi, Tatsuhiko; Torii, Chiharu; Takahashi, Reiko; Omori, Mikimasa; Kosaki, Rika; Yoshihashi, Hiroshi; Ihara, Masahiro; Minagawa-Kawai, Yasuyo; Yamamoto, Junichi; Takahashi, Takao; Kosaki, Kenjiro

    2014-11-01

    To reveal the relation between intellectual disability and the deleted intervals in Williams syndrome, we performed an array comparative genomic hybridization analysis and standardized developmental testing for 11 patients diagnosed as having Williams syndrome based on fluorescent in situ hybridization testing. One patient had a large 4.2-Mb deletion spanning distally beyond the common 1.5-Mb intervals observed in 10/11 patients. We formulated a linear equation describing the developmental age of the 10 patients with the common deletion; the developmental age of the patient with the 4.2-Mb deletion was significantly below the expectation (developmental age = 0.51 × chronological age). The large deletion may account for the severe intellectual disability; therefore, the use of array comparative genomic hybridization may provide practical information regarding individuals with Williams syndrome. © 2014 Japanese Teratology Society.

  4. A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

    Science.gov (United States)

    Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

    2016-11-23

    A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

  5. Discrimination of Wild Paris Based on Near Infrared Spectroscopy and High Performance Liquid Chromatography Combined with Multivariate Analysis

    Science.gov (United States)

    Zhao, Yanli; Zhang, Ji; Yuan, Tianjun; Shen, Tao; Li, Wei; Yang, Shihua; Hou, Ying; Wang, Yuanzhong; Jin, Hang

    2014-01-01

    Different geographical origins and species of Paris obtained from southwestern China were discriminated by near infrared (NIR) spectroscopy and high performance liquid chromatography (HPLC) combined with multivariate analysis. The NIR parameter settings were scanning (64 times), resolution (4 cm−1), scanning range (10000 cm−1∼4000 cm−1) and parallel collection (3 times). NIR spectrum was optimized by TQ 8.6 software, and the ranges 7455∼6852 cm−1 and 5973∼4007 cm−1 were selected according to the spectrum standard deviation. The contents of polyphyllin I, polyphyllin II, polyphyllin VI, and polyphyllin VII and total steroid saponins were detected by HPLC. The contents of chemical components data matrix and spectrum data matrix were integrated and analyzed by partial least squares discriminant analysis (PLS-DA). From the PLS-DA model of NIR spectrum, Paris samples were separated into three groups according to the different geographical origins. The R2X and Q2Y described accumulative contribution rates were 99.50% and 94.03% of the total variance, respectively. The PLS-DA model according to 12 species of Paris described 99.62% of the variation in X and predicted 95.23% in Y. The results of the contents of chemical components described differences among collections quantitatively. A multivariate statistical model of PLS-DA showed geographical origins of Paris had a much greater influence on Paris compared with species. NIR and HPLC combined with multivariate analysis could discriminate different geographical origins and different species. The quality of Paris showed regional dependence. PMID:24558477

  6. Spatial discrimination and visual discrimination

    DEFF Research Database (Denmark)

    Haagensen, Annika M. J.; Grand, Nanna; Klastrup, Signe

    2013-01-01

    Two methods investigating learning and memory in juvenile Gottingen minipigs were evaluated for potential use in preclinical toxicity testing. Twelve minipigs were tested using a spatial hole-board discrimination test including a learning phase and two memory phases. Five minipigs were tested...... in a visual discrimination test. The juvenile minipigs were able to learn the spatial hole-board discrimination test and showed improved working and reference memory during the learning phase. Performance in the memory phases was affected by the retention intervals, but the minipigs were able to remember...... the concept of the test in both memory phases. Working memory and reference memory were significantly improved in the last trials of the memory phases. In the visual discrimination test, the minipigs learned to discriminate between the three figures presented to them within 9-14 sessions. For the memory test...

  7. Sensitivity analysis of hybrid power systems using Power Pinch Analysis considering Feed-in Tariff

    International Nuclear Information System (INIS)

    Mohammad Rozali, Nor Erniza; Wan Alwi, Sharifah Rafidah; Manan, Zainuddin Abdul; Klemeš, Jiří Jaromír

    2016-01-01

    Feed-in Tariff (FiT) has been one of the most effective policies in accelerating the development of renewable energy (RE) projects. The amount of RE electricity in the FiT purchase agreement is an important decision that has to be made by the RE project developers. They have to consider various crucial factors associated with RE system operation as well as its stochastic nature. The presented work aims to assess the sensitivity and profitability of a hybrid power system (HPS) in cases of RE system failure or shutdown. The amount of RE electricity for the FiT purchase agreement in various scenarios was determined using a novel tool called On-Grid Problem Table based on the Power Pinch Analysis (PoPA). A sensitivity table has also been introduced to assist planners to evaluate the effects of the RE system's failure on the profitability of the HPS. This table offers insights on the variance of the RE electricity. The sensitivity analysis of various possible scenarios shows that the RE projects can still provide financial benefits via the FiT, despite the losses incurred from the penalty levied. - Highlights: • A Power Pinch Analysis (PoPA) tool to assess the economics of an HPS with FiT. • The new On-Grid Problem Table for targeting the available RE electricity for FiT sale. • A sensitivity table showing the effect of RE electricity changes on the HPS profitability.

  8. A battery-fuel cell hybrid auxiliary power unit for trucks: Analysis of direct and indirect hybrid configurations

    International Nuclear Information System (INIS)

    Samsun, Remzi Can; Krupp, Carsten; Baltzer, Sidney; Gnörich, Bruno; Peters, Ralf; Stolten, Detlef

    2016-01-01

    Highlights: • A battery-fuel cell hybrid auxiliary power unit for heavy duty vehicles is reported. • Comparison of direct and indirect hybrids using representative load profiles. • Evaluation based on validated fuel cell system and battery models. • Indirect hybrid with constant fuel cell load yields 29.3% hybrid system efficiency. • Fuel cell should be pre-heated using waste heat from the diesel engine during drive. - Abstract: The idling operation of engines in heavy duty vehicles to cover electricity demand during layovers entails significant fuel consumption and corresponding emissions. Indeed, this mode of operation is highly inefficient and a noteworthy contributor to the transportation sector’s aggregate carbon dioxide emissions. Here, a potential solution to this wasteful practice is outlined in the form of a hybrid battery-fuel cell system for application as an auxiliary power unit for trucks. Drawing on experimentally-validated fuel cell and battery models, several possible hybrid concepts are evaluated and direct and indirect hybrid configurations analyzed using a representative load profile. The results indicate that a direct hybrid configuration is only applicable if the load demand profile does not deviate strongly from the assumed profile. Operation of an indirect hybrid with a constant fuel cell load yields the greatest hybrid system efficiency, at 29.3%, while battery size could be reduced by 87% if the fuel cell is operated at the highest dynamics. Maximum efficiency in truck applications can be achieved by pre-heating the system prior to operation using exhaust heat from the motor, which increased system efficiency from 25.3% to 28.1%, including start-up. These findings confirm that hybrid systems could offer enormous fuel savings and constitute a sizeable step on the path toward energy-efficient and environmentally-friendly heavy duty vehicles that does not necessitate a fuel switch.

  9. Study on non-linear bistable dynamics model based EEG signal discrimination analysis method.

    Science.gov (United States)

    Ying, Xiaoguo; Lin, Han; Hui, Guohua

    2015-01-01

    Electroencephalogram (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations generating from ionic current flows within the neurons of the brain. EEG signal is looked as one of the most important factors that will be focused in the next 20 years. In this paper, EEG signal discrimination based on non-linear bistable dynamical model was proposed. EEG signals were processed by non-linear bistable dynamical model, and features of EEG signals were characterized by coherence index. Experimental results showed that the proposed method could properly extract the features of different EEG signals.

  10. Numerical experiment on different validation cases of water coolant flow in supercritical pressure test sections assisted by discriminated dimensional analysis part I: the dimensional analysis

    International Nuclear Information System (INIS)

    Kiss, A.; Aszodi, A.

    2011-01-01

    As recent studies prove in contrast to 'classical' dimensional analysis, whose application is widely described in heat transfer textbooks despite its poor results, the less well known and used discriminated dimensional analysis approach can provide a deeper insight into the physical problems involved and much better results in all cases where it is applied. As a first step of this ongoing research discriminated dimensional analysis has been performed on supercritical pressure water pipe flow heated through the pipe solid wall to identify the independent dimensionless groups (which play an independent role in the above mentioned thermal hydraulic phenomena) in order to serve a theoretical base to comparison between well known supercritical pressure water pipe heat transfer experiments and results of their validated CFD simulations. (author)

  11. Characterization and Discrimination of Gram-Positive Bacteria Using Raman Spectroscopy with the Aid of Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Alia Colniță

    2017-09-01

    Full Text Available Raman scattering and its particular effect, surface-enhanced Raman scattering (SERS, are whole-organism fingerprinting spectroscopic techniques that gain more and more popularity in bacterial detection. In this work, two relevant Gram-positive bacteria species, Lactobacillus casei (L. casei and Listeria monocytogenes (L. monocytogenes were characterized based on their Raman and SERS spectral fingerprints. The SERS spectra were used to identify the biochemical structures of the bacterial cell wall. Two synthesis methods of the SERS-active nanomaterials were used and the recorded spectra were analyzed. L. casei and L. monocytogenes were successfully discriminated by applying Principal Component Analysis (PCA to their specific spectral data.

  12. Thermal resistance analysis and optimization of photovoltaic-thermoelectric hybrid system

    International Nuclear Information System (INIS)

    Yin, Ershuai; Li, Qiang; Xuan, Yimin

    2017-01-01

    Highlights: • A detailed thermal resistance analysis of the PV-TE hybrid system is proposed. • c-Si PV and p-Si PV cells are proved to be inapplicable for the PV-TE hybrid system. • Some criteria for selecting coupling devices and optimal design are obtained. • A detailed process of designing the practical PV-TE hybrid system is provided. - Abstract: The thermal resistance theory is introduced into the theoretical model of the photovoltaic-thermoelectric (PV-TE) hybrid system. A detailed thermal resistance analysis is proposed to optimize the design of the coupled system in terms of optimal total conversion efficiency. Systems using four types of photovoltaic cells are investigated, including monocrystalline silicon photovoltaic cell, polycrystalline silicon photovoltaic cell, amorphous silicon photovoltaic cell and polymer photovoltaic cell. Three cooling methods, including natural cooling, forced air cooling and water cooling, are compared, which demonstrates a significant superiority of water cooling for the concentrating photovoltaic-thermoelectric hybrid system. Influences of the optical concentrating ratio and velocity of water are studied together and the optimal values are revealed. The impacts of the thermal resistances of the contact surface, TE generator and the upper heat loss thermal resistance on the property of the coupled system are investigated, respectively. The results indicate that amorphous silicon PV cell and polymer PV cell are more appropriate for the concentrating hybrid system. Enlarging the thermal resistance of the thermoelectric generator can significantly increase the performance of the coupled system using amorphous silicon PV cell or polymer PV cell.

  13. Contributions to sensitivity analysis and generalized discriminant analysis; Contributions a l'analyse de sensibilite et a l'analyse discriminante generalisee

    Energy Technology Data Exchange (ETDEWEB)

    Jacques, J

    2005-12-15

    Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)

  14. Contributions to sensitivity analysis and generalized discriminant analysis; Contributions a l'analyse de sensibilite et a l'analyse discriminante generalisee

    Energy Technology Data Exchange (ETDEWEB)

    Jacques, J

    2005-12-15

    Two topics are studied in this thesis: sensitivity analysis and generalized discriminant analysis. Global sensitivity analysis of a mathematical model studies how the output variables of this last react to variations of its inputs. The methods based on the study of the variance quantify the part of variance of the response of the model due to each input variable and each subset of input variables. The first subject of this thesis is the impact of a model uncertainty on results of a sensitivity analysis. Two particular forms of uncertainty are studied: that due to a change of the model of reference, and that due to the use of a simplified model with the place of the model of reference. A second problem was studied during this thesis, that of models with correlated inputs. Indeed, classical sensitivity indices not having significance (from an interpretation point of view) in the presence of correlation of the inputs, we propose a multidimensional approach consisting in expressing the sensitivity of the output of the model to groups of correlated variables. Applications in the field of nuclear engineering illustrate this work. Generalized discriminant analysis consists in classifying the individuals of a test sample in groups, by using information contained in a training sample, when these two samples do not come from the same population. This work extends existing methods in a Gaussian context to the case of binary data. An application in public health illustrates the utility of generalized discrimination models thus defined. (author)

  15. Discriminative analysis of Parkinson's disease based on whole-brain functional connectivity.

    Directory of Open Access Journals (Sweden)

    Yongbin Chen

    Full Text Available Recently, there has been an increasing emphasis on applications of pattern recognition and neuroimaging techniques in the effective and accurate diagnosis of psychiatric or neurological disorders. In the present study, we investigated the whole-brain resting-state functional connectivity patterns of Parkinson's disease (PD, which are expected to provide additional information for the clinical diagnosis and treatment of this disease. First, we computed the functional connectivity between each pair of 116 regions of interest derived from a prior atlas. The most discriminative features based on Kendall tau correlation coefficient were then selected. A support vector machine classifier was employed to classify 21 PD patients with 26 demographically matched healthy controls. This method achieved a classification accuracy of 93.62% using leave-one-out cross-validation, with a sensitivity of 90.47% and a specificity of 96.15%. The majority of the most discriminative functional connections were located within or across the default mode, cingulo-opercular and frontal-parietal networks and the cerebellum. These disease-related resting-state network alterations might play important roles in the pathophysiology of this disease. Our results suggest that analyses of whole-brain resting-state functional connectivity patterns have the potential to improve the clinical diagnosis and treatment evaluation of PD.

  16. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    OpenAIRE

    Daniel-Petru GHENCEA; Miron ZAPCIU; Claudiu-Florinel BISU; Elena-Iuliana BOTEANU; Elena-Luminiţa OLTEANU

    2017-01-01

    The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic). The paper presents a prediction mode obtaining valid range of values f...

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

    OpenAIRE

    Sathyanarayana, Y; Munjal, ML

    2000-01-01

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

  18. Morphological evaluation of common bean diversity in Bosnia and Herzegovina using the discriminant analysis of principal components (DAPC multivariate method

    Directory of Open Access Journals (Sweden)

    Grahić Jasmin

    2013-01-01

    Full Text Available In order to analyze morphological characteristics of locally cultivated common bean landraces from Bosnia and Herzegovina (B&H, thirteen quantitative and qualitative traits of 40 P. vulgaris accessions, collected from four geographical regions (Northwest B&H, Northeast B&H, Central B&H and Sarajevo and maintained at the Gene bank of the Faculty of Agriculture and Food Sciences in Sarajevo, were examined. Principal component analysis (PCA showed that the proportion of variance retained in the first two principal components was 54.35%. The first principal component had high contributing factor loadings from seed width, seed height and seed weight, whilst the second principal component had high contributing factor loadings from the analyzed traits seed per pod and pod length. PCA plot, based on the first two principal components, displayed a high level of variability among the analyzed material. The discriminant analysis of principal components (DAPC created 3 discriminant functions (DF, whereby the first two discriminant functions accounted for 90.4% of the variance retained. Based on the retained DFs, DAPC provided group membership probabilities which showed that 70% of the accessions examined were correctly classified between the geographically defined groups. Based on the taxonomic distance, 40 common bean accessions analyzed in this study formed two major clusters, whereas two accessions Acc304 and Acc307 didn’t group in any of those. Acc360 and Acc362, as well as Acc324 and Acc371 displayed a high level of similarity and are probably the same landrace. The present diversity of Bosnia and Herzegovina’s common been landraces could be useful in future breeding programs.

  19. Mass discrimination

    Energy Technology Data Exchange (ETDEWEB)

    Broeckman, A. [Rijksuniversiteit Utrecht (Netherlands)

    1978-12-15

    In thermal ionization mass spectrometry the phenomenon of mass discrimination has led to the use of a correction factor for isotope ratio-measurements. The correction factor is defined as the measured ratio divided by the true or accepted value of this ratio. In fact this factor corrects for systematic errors of the whole procedure; however mass discrimination is often associated just with the mass spectrometer.

  20. How discriminating are discriminative instruments?

    Science.gov (United States)

    Hankins, Matthew

    2008-05-27

    The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL). The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness), but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta) is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

  1. How discriminating are discriminative instruments?

    Directory of Open Access Journals (Sweden)

    Hankins Matthew

    2008-05-01

    Full Text Available Abstract The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL. The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness, but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

  2. Application of linear discriminant analysis and Attenuated Total Reflectance Fourier Transform Infrared microspectroscopy for diagnosis of colon cancer.

    Science.gov (United States)

    Khanmohammadi, Mohammadreza; Bagheri Garmarudi, Amir; Samani, Simin; Ghasemi, Keyvan; Ashuri, Ahmad

    2011-06-01

    Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) microspectroscopy was applied for detection of colon cancer according to the spectral features of colon tissues. Supervised classification models can be trained to identify the tissue type based on the spectroscopic fingerprint. A total of 78 colon tissues were used in spectroscopy studies. Major spectral differences were observed in 1,740-900 cm(-1) spectral region. Several chemometric methods such as analysis of variance (ANOVA), cluster analysis (CA) and linear discriminate analysis (LDA) were applied for classification of IR spectra. Utilizing the chemometric techniques, clear and reproducible differences were observed between the spectra of normal and cancer cases, suggesting that infrared microspectroscopy in conjunction with spectral data processing would be useful for diagnostic classification. Using LDA technique, the spectra were classified into cancer and normal tissue classes with an accuracy of 95.8%. The sensitivity and specificity was 100 and 93.1%, respectively.

  3. Quantitative analysis of the clinical data on leukemia, 5. Specificity of clinical features in acute myelocytic leukemia with 8; 21 translocation by multiple logistic discriminant analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ueoka, Hiroshi; Kamada, Nanao; Yamamoto, Hisashi; Ohtaki, Megu; Takimoto, Yasuo; Kuramoto, Atsushi; Munaka, Masaki

    1984-11-01

    In order to determine the necessity of chromosome analysis required for the evaluation of 8;21 translocation, multiple logistic discriminant analysis was made on 124 patients with acute non-lymphocytic leukemia experienced in the authors' institution. Variables which showed positive correlation with the presence of 8;21 translocation were the presence of Auer body and granular abnormality of the cells, numbers of peripheral promyelocytes, myelocytes and metamyelocytes, and bone marrow promyelocytes, myelocytes, and the sum of rods and segments. Those which showed negative correlation with 8;21 translocation were peripheral platelet count, neutrocytealkaline phosphatase (N-AP) score, numbers of eosinocytes, monocytes and erythroblasts, and erythroblasts on myelogram. Auer body, four peripheral hematological features (platelet count, N-AP score, metamyelocytes and monocytes), and three myelogram features (myelocytes, reticular cells and granulocytes/eosionocytes) were used for the multiple logistic discriminant analysis. By the analysis, 2 of the 22 patients (9.1%) with translocation were judged not to have 8;21 translocation and 3 of the 102 patients (2.9%) without translocation were judged to have it. Therefore, this multiple logistic discriminant method has proved to be simple and useful in clinically evaluating acute non-lymphocytic leukemia. (Namekawa, K.).

  4. Historical perspective of in situ hybridization for the analysis of ...

    African Journals Online (AJOL)

    Yomi

    2010-12-29

    Dec 29, 2010 ... analysis of genomic constitution of plants. Fida M Abbasi*, M. Tariq .... may be genus specific or even unique to a particular species. The physical ... cation of translocated chromosome, localization of break point and estimation ...

  5. Yield stability analysis of pearl millet hybrids in Nigeria

    African Journals Online (AJOL)

    hope&shola

    2006-02-02

    .] was ... Genotype x environment interaction was observed, a large component of which was accounted ... The importance of evaluating many potential genotypes .... Pooled analysis of variance for stability of grain yield (t/ha).

  6. Thermal modeling of a hydraulic hybrid vehicle transmission based on thermodynamic analysis

    International Nuclear Information System (INIS)

    Kwon, Hyukjoon; Sprengel, Michael; Ivantysynova, Monika

    2016-01-01

    Hybrid vehicles have become a popular alternative to conventional powertrain architectures by offering improved fuel efficiency along with a range of environmental benefits. Hydraulic Hybrid Vehicles (HHV) offer one approach to hybridization with many benefits over competing technologies. Among these benefits are lower component costs, more environmentally friendly construction materials, and the ability to recover a greater quantity of energy during regenerative braking which make HHVs partially well suited to urban environments. In order to further the knowledge base regarding HHVs, this paper explores the thermodynamic characteristics of such a system. A system model is detailed for both the hydraulic and thermal components of a closed circuit hydraulic hybrid transmission following the FTP-72 driving cycle. Among the new techniques proposed in this paper is a novel method for capturing rapid thermal transients. This paper concludes by comparing the results of this model with experimental data gathered on a Hardware-in-the-Loop (HIL) transmission dynamometer possessing the same architecture, components, and driving cycle used within the simulation model. This approach can be used for several applications such as thermal stability analysis of HHVs, optimal thermal management, and analysis of the system's thermodynamic efficiency. - Highlights: • Thermal modeling for HHVs is introduced. • A model for the hydraulic and thermal system is developed for HHVs. • A novel method for capturing rapid thermal transients is proposed. • The thermodynamic system diagram of a series HHV is predicted.

  7. Like/dislike analysis using EEG: determination of most discriminative channels and frequencies.

    Science.gov (United States)

    Yılmaz, Bülent; Korkmaz, Sümeyye; Arslan, Dilek Betül; Güngör, Evrim; Asyalı, Musa H

    2014-02-01

    In this study, we have analyzed electroencephalography (EEG) signals to investigate the following issues, (i) which frequencies and EEG channels could be relatively better indicators of preference (like or dislike decisions) of consumer products, (ii) timing characteristic of "like" decisions during such mental processes. For this purpose, we have obtained multichannel EEG recordings from 15 subjects, during total of 16 epochs of 10 s long, while they were presented with some shoe photographs. When they liked a specific shoe, they pressed on a button and marked the time of this activity and the particular epoch was labeled as a LIKE case. No button press meant that the subject did not like the particular shoe that was displayed and corresponding epoch designated as a DISLIKE case. After preprocessing, power spectral density (PSD) of EEG data was estimated at different frequencies (4, 5, …, 40 Hz) using the Burg method, for each epoch corresponding to one shoe presentation. Each subject's data consisted of normalized PSD values (NPVs) from all LIKE and DISLIKE cases/epochs coming from all 19 EEG channels. In order to determine the most discriminative frequencies and channels, we have utilized logistic regression, where LIKE/DISLIKE status was used as a categorical (binary) response variable and corresponding NPVs were the continuously valued input variables or predictors. We observed that when all the NPVs (total of 37) are used as predictors, the regression problem was becoming ill-posed due to large number of predictors (compared to the number of samples) and high correlation among predictors. To circumvent this issue, we have divided the frequency band into low frequency (LF) 4-19 Hz and high frequency (HF) 20-40 Hz bands and analyzed the influence of the NPV in these bands separately. Then, using the p-values that indicate how significantly estimated predictor weights are different than zero, we have determined the NPVs and channels that are more influential

  8. Acromegaly determination using discriminant analysis of the three-dimensional facial classification in Taiwanese.

    Science.gov (United States)

    Wang, Ming-Hsu; Lin, Jen-Der; Chang, Chen-Nen; Chiou, Wen-Ko

    2017-08-01

    The aim of this study was to assess the size, angles and positional characteristics of facial anthropometry between "acromegalic" patients and control subjects. We also identify possible facial soft tissue measurements for generating discriminant functions toward acromegaly determination in males and females for acromegaly early self-awareness. This is a cross-sectional study. Subjects participating in this study included 70 patients diagnosed with acromegaly (35 females and 35 males) and 140 gender-matched control individuals. Three-dimensional facial images were collected via a camera system. Thirteen landmarks were selected. Eleven measurements from the three categories were selected and applied, including five frontal widths, three lateral depths and three lateral angular measurements. Descriptive analyses were conducted using means and standard deviations for each measurement. Univariate and multivariate discriminant function analyses were applied in order to calculate the accuracy of acromegaly detection. Patients with acromegaly exhibit soft-tissue facial enlargement and hypertrophy. Frontal widths as well as lateral depth and angle of facial changes were evident. The average accuracies of all functions for female patient detection ranged from 80.0-91.40%. The average accuracies of all functions for male patient detection were from 81.0-94.30%. The greatest anomaly observed was evidenced in the lateral angles, with greater enlargement of "nasofrontal" angles for females and greater "mentolabial" angles for males. Additionally, shapes of the lateral angles showed changes. The majority of the facial measurements proved dynamic for acromegaly patients; however, it is problematic to detect the disease with progressive body anthropometric changes. The discriminant functions of detection developed in this study could help patients, their families, medical practitioners and others to identify and track progressive facial change patterns before the possible patients

  9. Sensitivity of cognitive tests in four cognitive domains in discriminating MDD patients from healthy controls: a meta-analysis.

    Science.gov (United States)

    Lim, JaeHyoung; Oh, In Kyung; Han, Changsu; Huh, Yu Jeong; Jung, In-Kwa; Patkar, Ashwin A; Steffens, David C; Jang, Bo-Hyoung

    2013-09-01

    We performed a meta-analysis in order to determine which neuropsychological domains and tasks would be most sensitive for discriminating between patients with major depressive disorder (MDD) and healthy controls. Relevant articles were identified through a literature search of the PubMed and Cochrane Library databases for the period between January 1997 and May 2011. A meta-analysis was conducted using the standardized means of individual cognitive tests in each domain. The heterogeneity was assessed, and subgroup analyses according to age and medication status were performed to explore the sources of heterogeneity. A total of 22 trials involving 955 MDD patients and 7,664 healthy participants were selected for our meta-analysis. MDD patients showed significantly impaired results compared with healthy participants on the Digit Span and Continuous Performance Test in the attention domain; the Trail Making Test A (TMT-A) and the Digit Symbol Test in the processing speed domain; the Stroop Test, the Wisconsin Card Sorting Test, and Verbal Fluency in the executive function domain; and immediate verbal memory in the memory domain. The Finger Tapping Task, TMT-B, delayed verbal memory, and immediate and delayed visual memory failed to separate MDD patients from healthy controls. The results of subgroup analysis showed that performance of Verbal Fluency was significantly impaired in younger depressed patients (memory was significantly reduced in depressed patients using antidepressants. Our findings have inevitable limitations arising from methodological issues inherent in the meta-analysis and we could not explain high heterogeneity between studies. Despite such limitations, current study has the strength of being the first meta-analysis which tried to specify cognitive function of depressed patients compared with healthy participants. And our findings may provide clinicians with further evidences that some cognitive tests in specific cognitive domains have sensitivity

  10. Feasibility study and energy conversion analysis of stand-alone hybrid renewable energy system

    International Nuclear Information System (INIS)

    Baghdadi, Fazia; Mohammedi, Kamal; Diaf, Said; Behar, Omar

    2015-01-01

    Highlights: • Hybrid stand-alone wind–solar–fossil power system is analyzed. • Measurement data are used to evaluate system performance. • The proposed system can generate about 70% from renewables. • Such a hybrid plant is very promising for remote regions in Algeria. - Abstract: There is a great interest in the development of renewable power technologies in Algeria, and more particularly hybrid concept. The present paper has investigated the performance of hybrid PV–Wind–Diesel–Battery configuration based on hourly measurements of Adrar climate (southern Algeria). Data of global solar radiation, ambient temperature and wind speed for a period of one year have been used. Firstly, the proposed hybrid system has been optimized by means of HOMER software. The optimization process has been carried out taking into account renewable resources potential and energy demand; while maximizing renewable electricity use and fuel saving are the purpose. In the second step, a mathematical model has been developed to ensure efficient energy management on the basis of various operation strategies. The analysis has shown that renewable energy system (PV–Wind) is able to supply about 70% of the demand. Wind power has ranked first with 43% of the annual total electricity production followed by diesel generator (with 31%) while the remaining fraction is being to PV panels. In this context, 69% of the fossil fuel can be saved when using the proposed hybrid configuration instead of the diesel generators that are currently installed in most remote regions in Algeria. Such a concept is very promising to meet the focus of renewable energy program announced in 2011.

  11. Sensitivity analysis for the energy performance assessment of hybrid compressed air energy storage systems

    International Nuclear Information System (INIS)

    Briola, Stefano; Di Marco, Paolo; Gabbrielli, Roberto; Riccardi, Juri

    2017-01-01

    Highlights: •A sensitivity analysis and DOE of the complete hybrid CAES are carried out. •The influence of the storage site volume on performance indicators is negligible. •The performances increase with the decrease of the compressor outlet pressure. •The performances are correlated for each temperature increase in combustion chamber. •Hybridization of Huntorf implies a significant increase of its first law efficiency. -- Abstract: A detailed mathematical model was developed for the complete Hybrid Compressed Air Energy Storage (H-CAES) configuration with underground storage site and liquid thermal energy storage, operating with a sequence of processes (charging, holding and discharging with respective duration) in arbitrary order. A sensitivity analysis was carried out in order to calculate several performance indicators of the complete H-CAES configuration, in relation to the simultaneous change of several process parameters. The methodology “Design of Experiments” was applied to the results of the sensitivity analysis in order to calculate the main effects of each process parameter on each performance indicator. The influence of the storage site volume on each performance indicator is negligible. The reduction of the compressor group outlet pressure and of the turbine group power allows a more effective thermodynamic utilization both of the energy stored by the compressors and of the overall energy supplied to the plant. Furthermore, the former utilization is more effective by an increase of the gas temperature in the combustion chambers, whereas the latter utilization is worsened. Moreover, as case study, the existing diabatic CAES plant of Huntorf was modified by introducing a diathermic oil thermal storage. This plant is suitable to operate according to a partial hybrid configuration by the deactivation of the heat exchanger located upstream of the low pressure turbine. The thermodynamic utilization of the overall energy supplied to the plant

  12. Proteome comparison for discrimination between honeydew and floral honeys from botanical species Mimosa scabrella Bentham by principal component analysis.

    Science.gov (United States)

    Azevedo, Mônia Stremel; Valentim-Neto, Pedro Alexandre; Seraglio, Siluana Katia Tischer; da Luz, Cynthia Fernandes Pinto; Arisi, Ana Carolina Maisonnave; Costa, Ana Carolina Oliveira

    2017-10-01

    Due to the increasing valuation and appreciation of honeydew honey in many European countries and also to existing contamination among different types of honeys, authentication is an important aspect of quality control with regard to guaranteeing the origin in terms of source (honeydew or floral) and needs to be determined. Furthermore, proteins are minor components of the honey, despite the importance of their physiological effects, and can differ according to the source of the honey. In this context, the aims of this study were to carry out protein extraction from honeydew and floral honeys and to discriminate these honeys from the same botanical species, Mimosa scabrella Bentham, through proteome comparison using two-dimensional gel electrophoresis and principal component analysis. The results showed that the proteome profile and principal component analysis can be a useful tool for discrimination between these types of honey using matched proteins (45 matched spots). Also, the proteome profile showed 160 protein spots in honeydew honey and 84 spots in the floral honey. The protein profile can be a differential characteristic of this type of honey, in view of the importance of proteins as bioactive compounds in honey. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

  13. HDclassif : An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data

    Directory of Open Access Journals (Sweden)

    Laurent Berge

    2012-01-01

    Full Text Available This paper presents the R package HDclassif which is devoted to the clustering and the discriminant analysis of high-dimensional data. The classification methods proposed in the package result from a new parametrization of the Gaussian mixture model which combines the idea of dimension reduction and model constraints on the covariance matrices. The supervised classification method using this parametrization is called high dimensional discriminant analysis (HDDA. In a similar manner, the associated clustering method iscalled high dimensional data clustering (HDDC and uses the expectation-maximization algorithm for inference. In order to correctly t the data, both methods estimate the specific subspace and the intrinsic dimension of the groups. Due to the constraints on the covariance matrices, the number of parameters to estimate is significantly lower than other model-based methods and this allows the methods to be stable and efficient in high dimensions. Two introductory examples illustrated with R codes allow the user to discover the hdda and hddc functions. Experiments on simulated and real datasets also compare HDDC and HDDA with existing classification methods on high-dimensional datasets. HDclassif is a free software and distributed under the general public license, as part of the R software project.

  14. Nonlinear Analysis and Preliminary Testing Results of a Hybrid Wing Body Center Section Test Article

    Science.gov (United States)

    Przekop, Adam; Jegley, Dawn C.; Rouse, Marshall; Lovejoy, Andrew E.; Wu, Hsi-Yung T.

    2015-01-01

    A large test article was recently designed, analyzed, fabricated, and successfully tested up to the representative design ultimate loads to demonstrate that stiffened composite panels with through-the-thickness reinforcement are a viable option for the next generation large transport category aircraft, including non-conventional configurations such as the hybrid wing body. This paper focuses on finite element analysis and test data correlation of the hybrid wing body center section test article under mechanical, pressure and combined load conditions. Good agreement between predictive nonlinear finite element analysis and test data is found. Results indicate that a geometrically nonlinear analysis is needed to accurately capture the behavior of the non-circular pressurized and highly-stressed structure when the design approach permits local buckling.

  15. Discriminant analysis of characteristics determining acceptance or rejection of nuclear power

    International Nuclear Information System (INIS)

    Holsapple, C.W.; Whinston, A.B.

    1977-01-01

    This study utilizes the linear discriminant model to analyze demographic and attitudinal data concerning the construction of a nuclear power facility at the Bailly site in northern Indiana. The objective is to ascertain the extent to which various respondent characteristics are useful in distinguishing among respondent attitudes (opposed, in favor, unsure) toward the Bailly project. Examination of reduced space characteristics leads the authors to postulate an interpretation of its two dimensions as respondent uncertainty and respondent resistance. The largest contributor (positive) to uncertainty was found to be a divorced or separated marital status; the greatest contributer (negative) to resistance was found to be home ownership. Both of these respondent characteristics were significant in the univariate sense. A particularly striking trend was the reliance of the opposed group upon electronic media as the source of most local news, whereas the other two groups tended to rely most heavily on newspapers

  16. Combining generative and discriminative representation learning for lung CT analysis with convolutional restricted Boltzmann machines

    DEFF Research Database (Denmark)

    van Tulder, Gijs; de Bruijne, Marleen

    2016-01-01

    The choice of features greatly influences the performance of a tissue classification system. Despite this, many systems are built with standard, predefined filter banks that are not optimized for that particular application. Representation learning methods such as restricted Boltzmann machines may...... outperform these standard filter banks because they learn a feature description directly from the training data. Like many other representation learning methods, restricted Boltzmann machines are unsupervised and are trained with a generative learning objective; this allows them to learn representations from...... unlabeled data, but does not necessarily produce features that are optimal for classification. In this paper we propose the convolutional classification restricted Boltzmann machine, which combines a generative and a discriminative learning objective. This allows it to learn filters that are good both...

  17. Male-female discrimination: an analysis of gender gap and its determinants

    Directory of Open Access Journals (Sweden)

    Claudio Quintano

    2013-05-01

    Full Text Available In recent years, the occupational dynamics have brought in significant innovations in Italy, as the increased participation of women in the labour market, that have stimulated studies about the gender wage gap, concerning the different remuneration reserved to male and female workers. In this work the Authors, following Oaxaca and Blinder approach, estimate the gap for Italian employers and proceed to its decomposition, one part due to differences in individual characteristics (endowment effect and another part due to the different returns on the same characteristics (coefficient effect, related to discrimination. Then, the gender wage gap and its decomposition is analyzed with reference to Italian macro-areas considered separately with the aim to highlight the different fundamental dynamics. The model has also been modified using the Heckmann correction to eliminate the bias due to self-selection; i.e. the different propensity to work for men and women.

  18. Discriminating poststroke depression from stroke by nuclear magnetic resonance spectroscopy-based metabonomic analysis

    Directory of Open Access Journals (Sweden)

    Xiao J

    2016-08-01

    Full Text Available Jianqi Xiao,1,* Jie Zhang,2,* Dan Sun,3,* Lin Wang,4,* Lijun Yu,5 Hongjing Wu,5 Dan Wang,5 Xuerong Qiu5 1Department of Neurosurgery, The First Hospital of Qiqihar City, Qiqihar, 2Department of Internal Medicine, Central Hospital of Jiamusi City, Jiamusi, 3Department of Geriatrics, General Hospital of Daqing Oil Field, Daqing, 4Department of Nursing, 5Department of Neurology, The First Hospital of Qiqihar City, Qiqihar, Heilongjiang, People’s Republic of China *These authors contributed equally to this work Abstract: Poststroke depression (PSD, the most common psychiatric disease that stroke survivors face, is estimated to affect ~30% of poststroke patients. However, there are still no objective methods to diagnose PSD. In this study, to explore the differential metabolites in the urine of PSD subjects and to identify a potential biomarker panel for PSD diagnosis, the nuclear magnetic resonance-based metabonomic method was applied. Ten differential metabolites responsible for discriminating PSD subjects from healthy control (HC and stroke subjects were found, and five of these metabolites were identified as potential biomarkers (lactate, α-hydroxybutyrate, phenylalanine, formate, and arabinitol. The panel consisting of these five metabolites provided excellent performance in discriminating PSD subjects from HC and stroke subjects, achieving an area under the receiver operating characteristic curve of 0.946 in the training set (43 HC, 45 stroke, and 62 PSD subjects. Moreover, this panel could classify the blinded samples from the test set (31 HC, 33 stroke, and 32 PSD subjects with an area under the curve of 0.946. These results laid a foundation for the future development of urine-based objective methods for PSD diagnosis and investigation of PSD pathogenesis. Keywords: poststroke depression, PSD, stroke, nuclear magnetic resonance, NMR, metabonomic

  19. Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

    Directory of Open Access Journals (Sweden)

    Jouventin Pierre

    2010-05-01

    Full Text Available Abstract Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions.

  20. Development and application of dynamic hybrid multi-region inventory analysis for macro-level environmental policy analysis. A case study on climate policy in Taiwan

    NARCIS (Netherlands)

    Chao, C.-W.; Heijungs, R.

    2013-01-01

    We develop a novel inventory method called Dynamic Hybrid Multi-Region Inventory analysis (DHMRI), which integrates the EEMRIOA and Integrated Hybrid LCA and applies time-dependent environmental intervention information for inventory analysis. Consequently, DHMRI is able to quantify the change in