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Sample records for methods include selective

  1. A Selection Method for COTS Systems

    DEFF Research Database (Denmark)

    Hedman, Jonas

    new skills and methods supporting the process of evaluating and selecting information systems. This paper presents a method for selecting COTS systems. The method includes the following phases: problem framing, requirements and appraisal, and selection of systems. The idea and distinguishing feature...... behind the method is that improved understanding of organizational' ends' or goals should govern the selection of a COTS system. This can also be expressed as a match or fit between ‘ends' (e.g. improved organizational effectiveness) and ‘means' (e.g. implementing COTS systems). This way of approaching...

  2. Mining method selection by integrated AHP and PROMETHEE method.

    Science.gov (United States)

    Bogdanovic, Dejan; Nikolic, Djordje; Ilic, Ivana

    2012-03-01

    Selecting the best mining method among many alternatives is a multicriteria decision making problem. The aim of this paper is to demonstrate the implementation of an integrated approach that employs AHP and PROMETHEE together for selecting the most suitable mining method for the "Coka Marin" underground mine in Serbia. The related problem includes five possible mining methods and eleven criteria to evaluate them. Criteria are accurately chosen in order to cover the most important parameters that impact on the mining method selection, such as geological and geotechnical properties, economic parameters and geographical factors. The AHP is used to analyze the structure of the mining method selection problem and to determine weights of the criteria, and PROMETHEE method is used to obtain the final ranking and to make a sensitivity analysis by changing the weights. The results have shown that the proposed integrated method can be successfully used in solving mining engineering problems.

  3. Methods for model selection in applied science and engineering.

    Energy Technology Data Exchange (ETDEWEB)

    Field, Richard V., Jr.

    2004-10-01

    Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be

  4. Inventory of LCIA selection methods for assessing toxic releases. Methods and typology report part B

    DEFF Research Database (Denmark)

    Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

    method(s) in Work package 8 (WP8) of the OMNIITOX project. The selection methods and the other CRS methods are described in detail, a set of evaluation criteria are developed and the methods are evaluated against these criteria. This report (Deliverable 11B (D11B)) gives the results from task 7.1d, 7.1e......This report describes an inventory of Life Cycle Impact Assessment (LCIA) selection methods for assessing toxic releases. It consists of an inventory of current selection methods and other Chemical Ranking and Scoring (CRS) methods assessed to be relevant for the development of (a) new selection...... and 7.1f of WP 7 for selection methods. The other part of D11 (D11A) is reported in another report and deals with characterisation methods. A selection method is a method for prioritising chemical emissions to be included in an LCIA characterisation of toxic releases, i.e. calculating indicator scores...

  5. Alternative microbial methods: An overview and selection criteria.

    Science.gov (United States)

    Jasson, Vicky; Jacxsens, Liesbeth; Luning, Pieternel; Rajkovic, Andreja; Uyttendaele, Mieke

    2010-09-01

    This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant bibliography. Perspectives on future development and the potential of the rapid method for routine application in food diagnostics are discussed. As various alternative "rapid" methods in different formats are available on the market, it can be very difficult for a food business operator or for a control authority to select the most appropriate method which fits its purpose. Validation of a method by a third party, according to international accepted protocol based upon ISO 16140, may increase the confidence in the performance of a method. A list of at the moment validated methods for enumeration of both utility indicators (aerobic plate count) and hygiene indicators (Enterobacteriaceae, Escherichia coli, coagulase positive Staphylococcus) as well as for detection of the four major pathogens (Salmonella spp., Listeria monocytogenes, E. coli O157 and Campylobacter spp.) is included with reference to relevant websites to check for updates. In a second part of this study, selection criteria are introduced to underpin the choice of the appropriate method(s) for a defined application. The selection criteria link the definition of the context in which the user of the method functions - and thus the prospective use of the microbial test results - with the technical information on the method and its operational requirements and sustainability. The selection criteria can help the end user of the method to obtain a systematic insight into all relevant factors to be taken into account for selection of a method for microbial analysis. Copyright 2010 Elsevier Ltd. All rights reserved.

  6. Evaluation of selection methods for toxicological impacts in LCA. Recommendations for OMNIITOX

    DEFF Research Database (Denmark)

    Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

    2004-01-01

    selection methods. Conclusion and Recommendations. For the development of SMs it is recommended that the general principles for CRS systems as applied to SMs are taken into account. Furthermore, special attention should be paid to some specific issues, i.e. the emitted amount should be included, data......Goal, Scope and Background. The aim of this study has been to come up with recommendations on how to develop a selection method (SM) within the method development research of the OMNIITOX project. An SM is a method for prioritization of chemical emissions to be included in a Life Cycle Impact...... categories, and when they do there are typically many gaps. This study covers the only existing methods explicitly designed as SMs (EDIP-selection, Priofactor and CPM-selection), the dominating Chemical Ranking and Scoring (CRS) method in Europe (EURAM) and in USA (WMPT) that can be adapted for this purpose...

  7. The experiments and analysis of several selective video encryption methods

    Science.gov (United States)

    Zhang, Yue; Yang, Cheng; Wang, Lei

    2013-07-01

    This paper presents four methods for selective video encryption based on the MPEG-2 video compression,including the slices, the I-frames, the motion vectors, and the DCT coefficients. We use the AES encryption method for simulation experiment for the four methods on VS2010 Platform, and compare the video effects and the processing speed of each frame after the video encrypted. The encryption depth can be arbitrarily selected, and design the encryption depth by using the double limit counting method, so the accuracy can be increased.

  8. Teaching Methods in Biology Education and Sustainability Education Including Outdoor Education for Promoting Sustainability—A Literature Review

    Directory of Open Access Journals (Sweden)

    Eila Jeronen

    2016-12-01

    Full Text Available There are very few studies concerning the importance of teaching methods in biology education and environmental education including outdoor education for promoting sustainability at the levels of primary and secondary schools and pre-service teacher education. The material was selected using special keywords from biology and sustainable education in several scientific databases. The article provides an overview of 24 selected articles published in peer-reviewed scientific journals from 2006–2016. The data was analyzed using qualitative content analysis. Altogether, 16 journals were selected and 24 articles were analyzed in detail. The foci of the analyses were teaching methods, learning environments, knowledge and thinking skills, psychomotor skills, emotions and attitudes, and evaluation methods. Additionally, features of good methods were investigated and their implications for teaching were emphasized. In total, 22 different teaching methods were found to improve sustainability education in different ways. The most emphasized teaching methods were those in which students worked in groups and participated actively in learning processes. Research points toward the value of teaching methods that provide a good introduction and supportive guidelines and include active participation and interactivity.

  9. Variable selection in near-infrared spectroscopy: Benchmarking of feature selection methods on biodiesel data

    International Nuclear Information System (INIS)

    Balabin, Roman M.; Smirnov, Sergey V.

    2011-01-01

    During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm -1 ) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic

  10. Determination of Selection Method in Genetic Algorithm for Land Suitability

    Directory of Open Access Journals (Sweden)

    Irfianti Asti Dwi

    2016-01-01

    Full Text Available Genetic Algoirthm is one alternative solution in the field of modeling optimization, automatic programming and machine learning. The purpose of the study was to compare some type of selection methods in Genetic Algorithm for land suitability. Contribution of this research applies the best method to develop region based horticultural commodities. This testing is done by comparing the three methods on the method of selection, the Roulette Wheel, Tournament Selection and Stochastic Universal Sampling. Parameters of the locations used in the test scenarios include Temperature = 27°C, Rainfall = 1200 mm, hummidity = 30%, Cluster fruit = 4, Crossover Probabiitiy (Pc = 0.6, Mutation Probabilty (Pm = 0.2 and Epoch = 10. The second test epoch incluides location parameters consist of Temperature = 30°C, Rainfall = 2000 mm, Humidity = 35%, Cluster fruit = 5, Crossover Probability (Pc = 0.7, Mutation Probability (Pm = 0.3 and Epoch 10. The conclusion of this study shows that the Roulette Wheel is the best method because it produces more stable and fitness value than the other two methods.

  11. Cleanup and treatment of radioactively contaminated land including areas near nuclear facilities. A selected bibliography

    International Nuclear Information System (INIS)

    Fore, C.S.; Faust, R.A.; Brewster, R.H.

    1982-09-01

    This annotated bibliography of 337 references summarizes the literature published on the cleanup and treatment of radioactively contaminated land. Specifically, this bibliography focuses on literature concerned with the methods of cleanup and treatment being applied - chemical, physical, or vegetative stabilization; the types of equipment being used; and the influence of climatic conditions on the method selected for use. The emphasis in such literature is placed on hazardous site cleanup efforts that have been completed as well as those that are in progress and are being planned. Appendix A includes 135 additional references to literature identified but not included in the bibliography because of time and funding constraints. Appendix B consists of a table that identifies the cleanup and treatment research conducted at specific sites. All of the information included in this bibliography is stored in a computerized form that is readily available upon request

  12. Electrode assemblies, plasma apparatuses and systems including electrode assemblies, and methods for generating plasma

    Science.gov (United States)

    Kong, Peter C; Grandy, Jon D; Detering, Brent A; Zuck, Larry D

    2013-09-17

    Electrode assemblies for plasma reactors include a structure or device for constraining an arc endpoint to a selected area or region on an electrode. In some embodiments, the structure or device may comprise one or more insulating members covering a portion of an electrode. In additional embodiments, the structure or device may provide a magnetic field configured to control a location of an arc endpoint on the electrode. Plasma generating modules, apparatus, and systems include such electrode assemblies. Methods for generating a plasma include covering at least a portion of a surface of an electrode with an electrically insulating member to constrain a location of an arc endpoint on the electrode. Additional methods for generating a plasma include generating a magnetic field to constrain a location of an arc endpoint on an electrode.

  13. Estimation of Genetic Variance Components Including Mutation and Epistasis using Bayesian Approach in a Selection Experiment on Body Weight in Mice

    DEFF Research Database (Denmark)

    Widyas, Nuzul; Jensen, Just; Nielsen, Vivi Hunnicke

    Selection experiment was performed for weight gain in 13 generations of outbred mice. A total of 18 lines were included in the experiment. Nine lines were allotted to each of the two treatment diets (19.3 and 5.1 % protein). Within each diet three lines were selected upwards, three lines were...... selected downwards and three lines were kept as controls. Bayesian statistical methods are used to estimate the genetic variance components. Mixed model analysis is modified including mutation effect following the methods by Wray (1990). DIC was used to compare the model. Models including mutation effect...... have better fit compared to the model with only additive effect. Mutation as direct effect contributes 3.18% of the total phenotypic variance. While in the model with interactions between additive and mutation, it contributes 1.43% as direct effect and 1.36% as interaction effect of the total variance...

  14. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data

    KAUST Repository

    Abusamra, Heba

    2013-05-01

    Microarray technology has enriched the study of gene expression in such a way that scientists are now able to measure the expression levels of thousands of genes in a single experiment. Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification, interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This thesis aims on a comparative study of state-of-the-art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k- nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t- statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used for this study. Different experiments have been applied to compare the performance of the classification methods with and without performing feature selection. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in

  15. IV international conference on computational methods in marine engineering : selected papers

    CERN Document Server

    Oñate, Eugenio; García-Espinosa, Julio; Kvamsdal, Trond; Bergan, Pål; MARINE 2011

    2013-01-01

    This book contains selected papers from the Fourth International Conference on Computational Methods in Marine Engineering, held at Instituto Superior Técnico, Technical University of Lisbon, Portugal in September 2011.  Nowadays, computational methods are an essential tool of engineering, which includes a major field of interest in marine applications, such as the maritime and offshore industries and engineering challenges related to the marine environment and renewable energies. The 2011 Conference included 8 invited plenary lectures and 86 presentations distributed through 10 thematic sessions that covered many of the most relevant topics of marine engineering today. This book contains 16 selected papers from the Conference that cover “CFD for Offshore Applications”, “Fluid-Structure Interaction”, “Isogeometric Methods for Marine Engineering”, “Marine/Offshore Renewable Energy”, “Maneuvering and Seakeeping”, “Propulsion and Cavitation” and “Ship Hydrodynamics”.  The papers we...

  16. METHOD FOR SELECTION OF PROJECT MANAGEMENT APPROACH BASED ON FUZZY CONCEPTS

    Directory of Open Access Journals (Sweden)

    Igor V. KONONENKO

    2017-03-01

    Full Text Available Literature analysis of works that devoted to research of the selection a project management approach and development of effective methods for this problem solution is given. Mathematical model and method for selection of project management approach with fuzzy concepts of applicability of existing approaches are proposed. The selection is made of such approaches as the PMBOK Guide, the ISO21500 standard, the PRINCE2 methodology, the SWEBOK Guide, agile methodologies Scrum, XP, and Kanban. The number of project parameters which have a great impact on the result of the selection and measure of their impact is determined. Project parameters relate to information about the project, team, communication, critical project risks. They include the number of people involved in the project, the customer's experience with this project team, the project team's experience in this field, the project team's understanding of requirements, adapting ability, initiative, and others. The suggested method is considered on the example of its application for selection a project management approach to software development project.

  17. Selection Component Analysis of Natural Polymorphisms using Population Samples Including Mother-Offspring Combinations, II

    DEFF Research Database (Denmark)

    Jarmer, Hanne Østergaard; Christiansen, Freddy Bugge

    1981-01-01

    Population samples including mother-offspring combinations provide information on the selection components: zygotic selection, sexual selection, gametic seletion and fecundity selection, on the mating pattern, and on the deviation from linkage equilibrium among the loci studied. The theory...

  18. Pyrochemical and Dry Processing Methods Program. A selected bibliography

    Energy Technology Data Exchange (ETDEWEB)

    McDuffie, H.F.; Smith, D.H.; Owen, P.T.

    1979-03-01

    This selected bibliography with abstracts was compiled to provide information support to the Pyrochemical and Dry Processing Methods (PDPM) Program sponsored by DOE and administered by the Argonne National Laboratory. Objectives of the PDPM Program are to evaluate nonaqueous methods of reprocessing spent fuel as a route to the development of proliferation-resistant and diversion-resistant methods for widespread use in the nuclear industry. Emphasis was placed on the literature indexed in the ERDA--DOE Energy Data Base (EDB). The bibliography includes indexes to authors, subject descriptors, EDB subject categories, and titles.

  19. Pyrochemical and Dry Processing Methods Program. A selected bibliography

    International Nuclear Information System (INIS)

    McDuffie, H.F.; Smith, D.H.; Owen, P.T.

    1979-03-01

    This selected bibliography with abstracts was compiled to provide information support to the Pyrochemical and Dry Processing Methods (PDPM) Program sponsored by DOE and administered by the Argonne National Laboratory. Objectives of the PDPM Program are to evaluate nonaqueous methods of reprocessing spent fuel as a route to the development of proliferation-resistant and diversion-resistant methods for widespread use in the nuclear industry. Emphasis was placed on the literature indexed in the ERDA--DOE Energy Data Base (EDB). The bibliography includes indexes to authors, subject descriptors, EDB subject categories, and titles

  20. EEG feature selection method based on decision tree.

    Science.gov (United States)

    Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

    2015-01-01

    This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

  1. Principal Feature Analysis: A Multivariate Feature Selection Method for fMRI Data

    Directory of Open Access Journals (Sweden)

    Lijun Wang

    2013-01-01

    Full Text Available Brain decoding with functional magnetic resonance imaging (fMRI requires analysis of complex, multivariate data. Multivoxel pattern analysis (MVPA has been widely used in recent years. MVPA treats the activation of multiple voxels from fMRI data as a pattern and decodes brain states using pattern classification methods. Feature selection is a critical procedure of MVPA because it decides which features will be included in the classification analysis of fMRI data, thereby improving the performance of the classifier. Features can be selected by limiting the analysis to specific anatomical regions or by computing univariate (voxel-wise or multivariate statistics. However, these methods either discard some informative features or select features with redundant information. This paper introduces the principal feature analysis as a novel multivariate feature selection method for fMRI data processing. This multivariate approach aims to remove features with redundant information, thereby selecting fewer features, while retaining the most information.

  2. A Study on Site Selecting for National Project including High Level Radioactive Waste Disposal

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kilyoo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    Many national projects are stopped since sites for the projects are not determined. The sites selections are hold by NIMBY for unpleasant facilities or by PYMFY for preferable facilities among local governments. The followings are the typical ones; NIMBY projects: high level radioactive waste disposal, THAAD, Nuclear power plant(NPP), etc. PIMFY projects: South-east new airport, KTX station, Research center for NPP decommission, etc. The site selection for high level radioactive waste disposal is more difficult problem, and thus government did not decide and postpone to a dead end street. Since it seems that there is no solution for site selection for high level radioactive waste disposal due to NIMBY among local governments, a solution method is proposed in this paper. To decide a high level radioactive waste disposal, the first step is to invite a bid by suggesting a package deal including PIMFY projects such as Research Center for NPP decommission. Maybe potential host local governments are asked to submit sealed bids indicating the minimum compensation sum that they would accept the high level radioactive waste disposal site. If there are more than one local government put in a bid, then decide an adequate site by considering both the accumulated PESS point and technical evaluation results. By considering how fairly preferable national projects and unpleasant national projects are distributed among local government, sites selection for NIMBY or PIMFY facilities is suggested. For NIMBY national projects, risk, cost benefit analysis is useful and required since it generates cost value to be used in the PESS. For many cases, the suggested method may be not adequate. However, similar one should be prepared, and be basis to decide sites for NIMBY or PIMFY national projects.

  3. AMES: Towards an Agile Method for ERP Selection

    OpenAIRE

    Juell-Skielse, Gustaf; Nilsson, Anders G.; Nordqvist, Andreas; Westergren, Mattias

    2012-01-01

    Conventional on-premise installations of ERP are now rapidly being replaced by ERP as service. Although ERP becomes more accessible and no longer requires local infrastructure, current selection methods do not take full advantage of the provided agility. In this paper we present AMES (Agile Method for ERP Selection), a novel method for ERP selection which better utilizes the strengths of service oriented ERP. AMES is designed to shorten lead time for selection, support identification of essen...

  4. LCIA selection methods for assessing toxic releases

    DEFF Research Database (Denmark)

    Larsen, Henrik Fred; Birkved, Morten; Hauschild, Michael Zwicky

    2002-01-01

    the inventory that contribute significantly to the impact categories on ecotoxicity and human toxicity to focus the characterisation work. The reason why the selection methods are more important for the chemical-related impact categories than for other impact categories is the extremely high number......Characterization of toxic emissions in life cycle impact assessment (LCIA) is in many cases severely limited by the lack of characterization factors for the emissions mapped in the inventory. The number of substances assigned characterization factors for (eco)toxicity included in the dominating LCA....... The methods are evaluated against a set of pre-defined criteria (comprising consistency with characterization and data requirement) and applied to case studies and a test set of chemicals. The reported work is part of the EU-project OMNIITOX....

  5. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

    KAUST Repository

    Abusamra, Heba

    2013-11-01

    Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  6. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data of Glioma

    KAUST Repository

    Abusamra, Heba

    2013-01-01

    Microarray gene expression data gained great importance in recent years due to its role in disease diagnoses and prognoses which help to choose the appropriate treatment plan for patients. This technology has shifted a new era in molecular classification. Interpreting gene expression data remains a difficult problem and an active research area due to their native nature of “high dimensional low sample size”. Such problems pose great challenges to existing classification methods. Thus, effective feature selection techniques are often needed in this case to aid to correctly classify different tumor types and consequently lead to a better understanding of genetic signatures as well as improve treatment strategies. This paper aims on a comparative study of state-of-the- art feature selection methods, classification methods, and the combination of them, based on gene expression data. We compared the efficiency of three different classification methods including: support vector machines, k-nearest neighbor and random forest, and eight different feature selection methods, including: information gain, twoing rule, sum minority, max minority, gini index, sum of variances, t-statistics, and one-dimension support vector machine. Five-fold cross validation was used to evaluate the classification performance. Two publicly available gene expression data sets of glioma were used in the experiments. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  7. Inspection methods and their selection

    International Nuclear Information System (INIS)

    Maier, H.J.

    1980-01-01

    First those nondestructive testing methods, which are used in quality assurance, are to be treated, e.g. - ultrasonics - radiography - magnetic particle testing - dye penetrant testing - eddy currents, and their capabilities and limitations are shown. Second the selection of optimal testing methods under the aspect of defect recognition in different materials and components are shown. (orig./RW)

  8. Quantitative sacroiliac scintigraphy. The effect of method of selection of region of interest

    International Nuclear Information System (INIS)

    Davis, M.C.; Turner, D.A.; Charters, J.R.; Golden, H.E.; Ali, A.; Fordham, E.W.

    1984-01-01

    Various authors have advocated quantitative methods of evaluating bone scintigrams to detect sacroiliitis, while others have not found them useful. Many explanations for this disagreement have been offered, including differences in the method of case selection, ethnicity, gender, and previous drug therapy. It would appear that one of the most important impediments to consistent results is the variability of selecting sacroiliac joint and reference regions of interest (ROIs). The effect of ROI selection would seem particularly important because of the normal variability of radioactivity within the reference regions that have been used (sacrum, spine, iliac wing) and the inhomogeneity of activity in the SI joints. We have investigated the effect of ROI selection, using five different methods representative of, though not necessarily identical to, those found in the literature. Each method produced unique mean indices that were different for patients with ankylosing spondylitis (AS) and controls. The method of Ayres (19) proved superior (largest mean difference, smallest variance), but none worked well as a diagnostic tool because of substantial overlap of the distributions of indices of patient and control groups. We conclude that ROI selection is important in determining results, and quantitative scintigraphic methods in general are not effective tools for diagnosing AS. Among the possible factors limiting success, difficulty in selecting a stable reference area seems of particular importance

  9. Systematic Methods in School Planning and Design. A Selected and Annotated Bibliography.

    Science.gov (United States)

    Murtha, D. Michael

    A selection of technical reports, journal articles and books on various aspects of systematic methods for school planning and design, are presented in this bibliography. The subject areas include the design process in terms of--(1) practice, (2) theory, (3) methods, (4) decision systems, and (5) computer applications. Criteria for design with…

  10. A Robust Service Selection Method Based on Uncertain QoS

    Directory of Open Access Journals (Sweden)

    Yanping Chen

    2016-01-01

    Full Text Available Nowadays, the number of Web services on the Internet is quickly increasing. Meanwhile, different service providers offer numerous services with the similar functions. Quality of Service (QoS has become an important factor used to select the most appropriate service for users. The most prominent QoS-based service selection models only take the certain attributes into account, which is an ideal assumption. In the real world, there are a large number of uncertain factors. In particular, at the runtime, QoS may become very poor or unacceptable. In order to solve the problem, a global service selection model based on uncertain QoS was proposed, including the corresponding normalization and aggregation functions, and then a robust optimization model adopted to transform the model. Experiment results show that the proposed method can effectively select services with high robustness and optimality.

  11. Using MACBETH method for supplier selection in manufacturing environment

    Directory of Open Access Journals (Sweden)

    Prasad Karande

    2013-04-01

    Full Text Available Supplier selection is always found to be a complex decision-making problem in manufacturing environment. The presence of several independent and conflicting evaluation criteria, either qualitative or quantitative, makes the supplier selection problem a candidate to be solved by multi-criteria decision-making (MCDM methods. Even several MCDM methods have already been proposed for solving the supplier selection problems, the need for an efficient method that can deal with qualitative judgments related to supplier selection still persists. In this paper, the applicability and usefulness of measuring attractiveness by a categorical-based evaluation technique (MACBETH is demonstrated to act as a decision support tool while solving two real time supplier selection problems having qualitative performance measures. The ability of MACBETH method to quantify the qualitative performance measures helps to provide a numerical judgment scale for ranking the alternative suppliers and selecting the best one. The results obtained from MACBETH method exactly corroborate with those derived by the past researchers employing different mathematical approaches.

  12. Teaching Methods in Biology Education and Sustainability Education Including Outdoor Education for Promoting Sustainability--A Literature Review

    Science.gov (United States)

    Jeronen, Eila; Palmberg, Irmeli; Yli-Panula, Eija

    2017-01-01

    There are very few studies concerning the importance of teaching methods in biology education and environmental education including outdoor education for promoting sustainability at the levels of primary and secondary schools and pre-service teacher education. The material was selected using special keywords from biology and sustainable education…

  13. Variable selection by lasso-type methods

    Directory of Open Access Journals (Sweden)

    Sohail Chand

    2011-09-01

    Full Text Available Variable selection is an important property of shrinkage methods. The adaptive lasso is an oracle procedure and can do consistent variable selection. In this paper, we provide an explanation that how use of adaptive weights make it possible for the adaptive lasso to satisfy the necessary and almost sufcient condition for consistent variable selection. We suggest a novel algorithm and give an important result that for the adaptive lasso if predictors are normalised after the introduction of adaptive weights, it makes the adaptive lasso performance identical to the lasso.

  14. Personnel Selection Based on Fuzzy Methods

    Directory of Open Access Journals (Sweden)

    Lourdes Cañós

    2011-03-01

    Full Text Available The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate. Our method is based on the Hamming distance and a Matching Level Index. The algorithms, implemented in the software StaffDesigner, allow us to rank the candidates, even when the competences of the ideal candidate have been evaluated only in part. Our approach is applied in a numerical example.

  15. A new and fast image feature selection method for developing an optimal mammographic mass detection scheme.

    Science.gov (United States)

    Tan, Maxine; Pu, Jiantao; Zheng, Bin

    2014-08-01

    Selecting optimal features from a large image feature pool remains a major challenge in developing computer-aided detection (CAD) schemes of medical images. The objective of this study is to investigate a new approach to significantly improve efficacy of image feature selection and classifier optimization in developing a CAD scheme of mammographic masses. An image dataset including 1600 regions of interest (ROIs) in which 800 are positive (depicting malignant masses) and 800 are negative (depicting CAD-generated false positive regions) was used in this study. After segmentation of each suspicious lesion by a multilayer topographic region growth algorithm, 271 features were computed in different feature categories including shape, texture, contrast, isodensity, spiculation, local topological features, as well as the features related to the presence and location of fat and calcifications. Besides computing features from the original images, the authors also computed new texture features from the dilated lesion segments. In order to select optimal features from this initial feature pool and build a highly performing classifier, the authors examined and compared four feature selection methods to optimize an artificial neural network (ANN) based classifier, namely: (1) Phased Searching with NEAT in a Time-Scaled Framework, (2) A sequential floating forward selection (SFFS) method, (3) A genetic algorithm (GA), and (4) A sequential forward selection (SFS) method. Performances of the four approaches were assessed using a tenfold cross validation method. Among these four methods, SFFS has highest efficacy, which takes 3%-5% of computational time as compared to GA approach, and yields the highest performance level with the area under a receiver operating characteristic curve (AUC) = 0.864 ± 0.034. The results also demonstrated that except using GA, including the new texture features computed from the dilated mass segments improved the AUC results of the ANNs optimized

  16. SELECTION OF NON-CONVENTIONAL MACHINING PROCESSES USING THE OCRA METHOD

    Directory of Open Access Journals (Sweden)

    Miloš Madić

    2015-04-01

    Full Text Available Selection of the most suitable nonconventional machining process (NCMP for a given machining application can be viewed as multi-criteria decision making (MCDM problem with many conflicting and diverse criteria. To aid these selection processes, different MCDM methods have been proposed. This paper introduces the use of an almost unexplored MCDM method, i.e. operational competitiveness ratings analysis (OCRA method for solving the NCMP selection problems. Applicability, suitability and computational procedure of OCRA method have been demonstrated while solving three case studies dealing with selection of the most suitable NCMP. In each case study the obtained rankings were compared with those derived by the past researchers using different MCDM methods. The results obtained using the OCRA method have good correlation with those derived by the past researchers which validate the usefulness of this method while solving complex NCMP selection problems.

  17. Selection of industrial robots using the Polygons area method

    Directory of Open Access Journals (Sweden)

    Mortaza Honarmande Azimi

    2014-08-01

    Full Text Available Selection of robots from the several proposed alternatives is a very important and tedious task. Decision makers are not limited to one method and several methods have been proposed for solving this problem. This study presents Polygons Area Method (PAM as a multi attribute decision making method for robot selection problem. In this method, the maximum polygons area obtained from the attributes of an alternative robot on the radar chart is introduced as a decision-making criterion. The results of this method are compared with other typical multiple attribute decision-making methods (SAW, WPM, TOPSIS, and VIKOR by giving two examples. To find similarity in ranking given by different methods, Spearman’s rank correlation coefficients are obtained for different pairs of MADM methods. It was observed that the introduced method is in good agreement with other well-known MADM methods in the robot selection problem.

  18. Equipment Selection by using Fuzzy TOPSIS Method

    Science.gov (United States)

    Yavuz, Mahmut

    2016-10-01

    In this study, Fuzzy TOPSIS method was performed for the selection of open pit truck and the optimal solution of the problem was investigated. Data from Turkish Coal Enterprises was used in the application of the method. This paper explains the Fuzzy TOPSIS approaches with group decision-making application in an open pit coal mine in Turkey. An algorithm of the multi-person multi-criteria decision making with fuzzy set approach was applied an equipment selection problem. It was found that Fuzzy TOPSIS with a group decision making is a method that may help decision-makers in solving different decision-making problems in mining.

  19. Optimization methods for activities selection problems

    Science.gov (United States)

    Mahad, Nor Faradilah; Alias, Suriana; Yaakop, Siti Zulaika; Arshad, Norul Amanina Mohd; Mazni, Elis Sofia

    2017-08-01

    Co-curriculum activities must be joined by every student in Malaysia and these activities bring a lot of benefits to the students. By joining these activities, the students can learn about the time management and they can developing many useful skills. This project focuses on the selection of co-curriculum activities in secondary school using the optimization methods which are the Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP). A secondary school in Negeri Sembilan, Malaysia was chosen as a case study. A set of questionnaires were distributed randomly to calculate the weighted for each activity based on the 3 chosen criteria which are soft skills, interesting activities and performances. The weighted was calculated by using AHP and the results showed that the most important criteria is soft skills. Then, the ZOGP model will be analyzed by using LINGO Software version 15.0. There are two priorities to be considered. The first priority which is to minimize the budget for the activities is achieved since the total budget can be reduced by RM233.00. Therefore, the total budget to implement the selected activities is RM11,195.00. The second priority which is to select the co-curriculum activities is also achieved. The results showed that 9 out of 15 activities were selected. Thus, it can concluded that AHP and ZOGP approach can be used as the optimization methods for activities selection problem.

  20. System and method for programmable bank selection for banked memory subsystems

    Energy Technology Data Exchange (ETDEWEB)

    Blumrich, Matthias A. (Ridgefield, CT); Chen, Dong (Croton on Hudson, NY); Gara, Alan G. (Mount Kisco, NY); Giampapa, Mark E. (Irvington, NY); Hoenicke, Dirk (Seebruck-Seeon, DE); Ohmacht, Martin (Yorktown Heights, NY); Salapura, Valentina (Chappaqua, NY); Sugavanam, Krishnan (Mahopac, NY)

    2010-09-07

    A programmable memory system and method for enabling one or more processor devices access to shared memory in a computing environment, the shared memory including one or more memory storage structures having addressable locations for storing data. The system comprises: one or more first logic devices associated with a respective one or more processor devices, each first logic device for receiving physical memory address signals and programmable for generating a respective memory storage structure select signal upon receipt of pre-determined address bit values at selected physical memory address bit locations; and, a second logic device responsive to each of the respective select signal for generating an address signal used for selecting a memory storage structure for processor access. The system thus enables each processor device of a computing environment memory storage access distributed across the one or more memory storage structures.

  1. Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

    Science.gov (United States)

    Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

    2017-11-01

    Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Relationship of Source Selection Methods to Contract Outcomes: an Analysis of Air Force Source Selection

    Science.gov (United States)

    2015-12-01

    some occasions, performance is terminated early; this can occur due to either mutual agreement or a breach of contract by one of the parties (Garrett...Relationship of Source Selection Methods to Contract Outcomes: an Analysis of Air Force Source Selection December 2015 Capt Jacques Lamoureux, USAF...on the contract management process, with special emphasis on the source selection methods of tradeoff and lowest price technically acceptable (LPTA

  3. Selective aerobic alcohol oxidation method for conversion of lignin into simple aromatic compounds

    Science.gov (United States)

    Stahl, Shannon S; Rahimi, Alireza

    2015-03-03

    Described is a method to oxidize lignin or lignin sub-units. The method includes oxidation of secondary benzylic alcohol in the lignin or lignin sub-unit to a corresponding ketone in the presence of unprotected primarily aliphatic alcohol in the lignin or lignin sub-unit. The optimal catalyst system consists of HNO.sub.3 in combination with another Bronsted acid, in the absence of a metal-containing catalyst, thereby yielding a selectively oxidized lignin or lignin sub-unit. The method may be carried out in the presence or absence of additional reagents including TEMPO and TEMPO derivatives.

  4. Selection Method for COTS Systems

    DEFF Research Database (Denmark)

    Hedman, Jonas; Andersson, Bo

    2014-01-01

    feature behind the method is that improved understanding of organizational ‘ends’ or goals should govern the selection of a COTS system. This can also be expressed as a match or fit between ‘ends’ (e.g. improved organizational effectiveness) and ‘means’ (e.g. implementing COTS systems). This way...

  5. An improved selective sampling method

    International Nuclear Information System (INIS)

    Miyahara, Hiroshi; Iida, Nobuyuki; Watanabe, Tamaki

    1986-01-01

    The coincidence methods which are currently used for the accurate activity standardisation of radio-nuclides, require dead time and resolving time corrections which tend to become increasingly uncertain as countrates exceed about 10 K. To reduce the dependence on such corrections, Muller, in 1981, proposed the selective sampling method using a fast multichannel analyser (50 ns ch -1 ) for measuring the countrates. It is, in many ways, more convenient and possibly potentially more reliable to replace the MCA with scalers and a circuit is described employing five scalers; two of them serving to measure the background correction. Results of comparisons using our new method and the coincidence method for measuring the activity of 60 Co sources yielded agree-ment within statistical uncertainties. (author)

  6. Using and reporting the Delphi method for selecting healthcare quality indicators: a systematic review.

    Science.gov (United States)

    Boulkedid, Rym; Abdoul, Hendy; Loustau, Marine; Sibony, Olivier; Alberti, Corinne

    2011-01-01

    Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1) to describe reporting of the Delphi method to develop quality indicators, 2) to discuss specific methodological skills for quality indicators selection 3) to give guidance about this practice. Three electronic data bases were searched over a 30 years period (1978-2009). All articles that used the Delphi method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results) were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used). Reporting of methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80) of studies reported response rates for all rounds, 60% (48/80) that feedback was given between rounds, 77% (62/80) the method used to achieve consensus and 57% (48/80) listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63%) with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31). In 40/70 (57%) studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40) of cases. Among 75 studies describing criteria to select quality indicators, 28 (37%) used validity and 17(23%) feasibility. The use and reporting of the Delphi method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the method in future surveys.

  7. Using and reporting the Delphi method for selecting healthcare quality indicators: a systematic review.

    Directory of Open Access Journals (Sweden)

    Rym Boulkedid

    Full Text Available OBJECTIVE: Delphi technique is a structured process commonly used to developed healthcare quality indicators, but there is a little recommendation for researchers who wish to use it. This study aimed 1 to describe reporting of the Delphi method to develop quality indicators, 2 to discuss specific methodological skills for quality indicators selection 3 to give guidance about this practice. METHODOLOGY AND MAIN FINDING: Three electronic data bases were searched over a 30 years period (1978-2009. All articles that used the Delphi method to select quality indicators were identified. A standardized data extraction form was developed. Four domains (questionnaire preparation, expert panel, progress of the survey and Delphi results were assessed. Of 80 included studies, quality of reporting varied significantly between items (9% for year's number of experience of the experts to 98% for the type of Delphi used. Reporting of methodological aspects needed to evaluate the reliability of the survey was insufficient: only 39% (31/80 of studies reported response rates for all rounds, 60% (48/80 that feedback was given between rounds, 77% (62/80 the method used to achieve consensus and 57% (48/80 listed quality indicators selected at the end of the survey. A modified Delphi procedure was used in 49/78 (63% with a physical meeting of the panel members, usually between Delphi rounds. Median number of panel members was 17(Q1:11; Q3:31. In 40/70 (57% studies, the panel included multiple stakeholders, who were healthcare professionals in 95% (38/40 of cases. Among 75 studies describing criteria to select quality indicators, 28 (37% used validity and 17(23% feasibility. CONCLUSION: The use and reporting of the Delphi method for quality indicators selection need to be improved. We provide some guidance to the investigators to improve the using and reporting of the method in future surveys.

  8. An Identification Key for Selecting Methods for Sustainability Assessments

    Directory of Open Access Journals (Sweden)

    Michiel C. Zijp

    2015-03-01

    Full Text Available Sustainability assessments can play an important role in decision making. This role starts with selecting appropriate methods for a given situation. We observed that scientists, consultants, and decision-makers often do not systematically perform a problem analyses that guides the choice of the method, partly related to a lack of systematic, though sufficiently versatile approaches to do so. Therefore, we developed and propose a new step towards method selection on the basis of question articulation: the Sustainability Assessment Identification Key. The identification key was designed to lead its user through all important choices needed for comprehensive question articulation. Subsequently, methods that fit the resulting specific questions are suggested by the key. The key consists of five domains, of which three determine method selection and two the design or use of the method. Each domain consists of four or more criteria that need specification. For example in the domain “system boundaries”, amongst others, the spatial and temporal scales are specified. The key was tested (retrospectively on a set of thirty case studies. Using the key appeared to contribute to improved: (i transparency in the link between the question and method selection; (ii consistency between questions asked and answers provided; and (iii internal consistency in methodological design. There is latitude to develop the current initial key further, not only for selecting methods pertinent to a problem definition, but also as a principle for associated opportunities such as stakeholder identification.

  9. A Selection Method That Succeeds!

    Science.gov (United States)

    Weitman, Catheryn J.

    Provided a structural selection method is carried out, it is possible to find quality early childhood personnel. The hiring process involves five definite steps, each of which establishes a base for the next. A needs assessment formulating basic minimal qualifications is the first step. The second step involves review of current job descriptions…

  10. Supplier selection based on multi-criterial AHP method

    Directory of Open Access Journals (Sweden)

    Jana Pócsová

    2010-03-01

    Full Text Available This paper describes a case-study of supplier selection based on multi-criterial Analytic Hierarchy Process (AHP method.It is demonstrated that using adequate mathematical method can bring us “unprejudiced” conclusion, even if the alternatives (suppliercompanies are very similar in given selection-criteria. The result is the best possible supplier company from the viewpoint of chosen criteriaand the price of the product.

  11. Methods for producing thin film charge selective transport layers

    Science.gov (United States)

    Hammond, Scott Ryan; Olson, Dana C.; van Hest, Marinus Franciscus Antonius Maria

    2018-01-02

    Methods for producing thin film charge selective transport layers are provided. In one embodiment, a method for forming a thin film charge selective transport layer comprises: providing a precursor solution comprising a metal containing reactive precursor material dissolved into a complexing solvent; depositing the precursor solution onto a surface of a substrate to form a film; and forming a charge selective transport layer on the substrate by annealing the film.

  12. Selection criteria for oxidation method in total organic carbon measurement.

    Science.gov (United States)

    Yoon, GeunSeok; Park, Sang-Min; Yang, Heuiwon; Tsang, Daniel C W; Alessi, Daniel S; Baek, Kitae

    2018-05-01

    During the measurement of total organic carbon (TOC), dissolved organic carbon is converted into CO 2 by using high temperature combustion (HTC) or wet chemical oxidation (WCO). However, the criteria for selecting the oxidation methods are not clear. In this study, the chemical structures of organic material were considered as a key factor to select the oxidation method used. Most non-degradable organic compounds showed a similar oxidation efficiency in both methods, including natural organic compounds, dyes, and pharmaceuticals, and thus both methods are appropriate to measure TOC in waters containing these compounds. However, only a fraction of the carbon in the halogenated compounds (perfluorooctanoic acid and trifluoroacetic acid) were oxidized using WCO, resulting in measured TOC values that are considerably lower than those determined by HTC. This result is likely due to the electronegativity of halogen elements which inhibits the approach of electron-rich sulfate radicals in the WCO, and the higher bond strength of carbon-halogen pairs as compared to carbon-hydrogen bonds, which results in a lower degree of oxidation of the compounds. Our results indicate that WCO could be used to oxidize most organic compounds, but may not be appropriate to quantify TOC in organic carbon pools that contain certain halogenated compounds. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. Reference satellite selection method for GNSS high-precision relative positioning

    Directory of Open Access Journals (Sweden)

    Xiao Gao

    2017-03-01

    Full Text Available Selecting the optimal reference satellite is an important component of high-precision relative positioning because the reference satellite directly influences the strength of the normal equation. The reference satellite selection methods based on elevation and positional dilution of precision (PDOP value were compared. Results show that all the above methods cannot select the optimal reference satellite. We introduce condition number of the design matrix in the reference satellite selection method to improve structure of the normal equation, because condition number can indicate the ill condition of the normal equation. The experimental results show that the new method can improve positioning accuracy and reliability in precise relative positioning.

  14. Methods of producing adsorption media including a metal oxide

    Science.gov (United States)

    Mann, Nicholas R; Tranter, Troy J

    2014-03-04

    Methods of producing a metal oxide are disclosed. The method comprises dissolving a metal salt in a reaction solvent to form a metal salt/reaction solvent solution. The metal salt is converted to a metal oxide and a caustic solution is added to the metal oxide/reaction solvent solution to adjust the pH of the metal oxide/reaction solvent solution to less than approximately 7.0. The metal oxide is precipitated and recovered. A method of producing adsorption media including the metal oxide is also disclosed, as is a precursor of an active component including particles of a metal oxide.

  15. Feature selection for splice site prediction: A new method using EDA-based feature ranking

    Directory of Open Access Journals (Sweden)

    Rouzé Pierre

    2004-05-01

    Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

  16. A novel peak-hopping stepwise feature selection method with application to Raman spectroscopy

    International Nuclear Information System (INIS)

    McShane, M.J.; Cameron, B.D.; Cote, G.L.; Motamedi, M.; Spiegelman, C.H.

    1999-01-01

    A new stepwise approach to variable selection for spectroscopy that includes chemical information and attempts to test several spectral regions producing high ranking coefficients has been developed to improve on currently available methods. Existing selection techniques can, in general, be placed into two groups: the first, time-consuming optimization approaches that ignore available information about sample chemistry and require considerable expertise to arrive at appropriate solutions (e.g. genetic algorithms), and the second, stepwise procedures that tend to select many variables in the same area containing redundant information. The algorithm described here is a fast stepwise procedure that uses multiple ranking chains to identify several spectral regions correlated with known sample properties. The multiple-chain approach allows the generation of a final ranking vector that moves quickly away from the initial selection point, testing several areas exhibiting correlation between spectra and composition early in the stepping procedure. Quantitative evidence of the success of this approach as applied to Raman spectroscopy is given in terms of processing speed, number of selected variables, and prediction error in comparison with other selection methods. In this respect, the procedure described here may be considered as a significant evolutionary step in variable selection algorithms. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

  17. Microfluidic devices and methods including porous polymer monoliths

    Science.gov (United States)

    Hatch, Anson V; Sommer, Gregory J; Singh, Anup K; Wang, Ying-Chih; Abhyankar, Vinay V

    2014-04-22

    Microfluidic devices and methods including porous polymer monoliths are described. Polymerization techniques may be used to generate porous polymer monoliths having pores defined by a liquid component of a fluid mixture. The fluid mixture may contain iniferters and the resulting porous polymer monolith may include surfaces terminated with iniferter species. Capture molecules may then be grafted to the monolith pores.

  18. Underground Mining Method Selection Using WPM and PROMETHEE

    Science.gov (United States)

    Balusa, Bhanu Chander; Singam, Jayanthu

    2018-04-01

    The aim of this paper is to represent the solution to the problem of selecting suitable underground mining method for the mining industry. It is achieved by using two multi-attribute decision making techniques. These two techniques are weighted product method (WPM) and preference ranking organization method for enrichment evaluation (PROMETHEE). In this paper, analytic hierarchy process is used for weight's calculation of the attributes (i.e. parameters which are used in this paper). Mining method selection depends on physical parameters, mechanical parameters, economical parameters and technical parameters. WPM and PROMETHEE techniques have the ability to consider the relationship between the parameters and mining methods. The proposed techniques give higher accuracy and faster computation capability when compared with other decision making techniques. The proposed techniques are presented to determine the effective mining method for bauxite mine. The results of these techniques are compared with methods used in the earlier research works. The results show, conventional cut and fill method is the most suitable mining method.

  19. Applicability of bioanalysis of multiple analytes in drug discovery and development: review of select case studies including assay development considerations.

    Science.gov (United States)

    Srinivas, Nuggehally R

    2006-05-01

    The development of sound bioanalytical method(s) is of paramount importance during the process of drug discovery and development culminating in a marketing approval. Although the bioanalytical procedure(s) originally developed during the discovery stage may not necessarily be fit to support the drug development scenario, they may be suitably modified and validated, as deemed necessary. Several reviews have appeared over the years describing analytical approaches including various techniques, detection systems, automation tools that are available for an effective separation, enhanced selectivity and sensitivity for quantitation of many analytes. The intention of this review is to cover various key areas where analytical method development becomes necessary during different stages of drug discovery research and development process. The key areas covered in this article with relevant case studies include: (a) simultaneous assay for parent compound and metabolites that are purported to display pharmacological activity; (b) bioanalytical procedures for determination of multiple drugs in combating a disease; (c) analytical measurement of chirality aspects in the pharmacokinetics, metabolism and biotransformation investigations; (d) drug monitoring for therapeutic benefits and/or occupational hazard; (e) analysis of drugs from complex and/or less frequently used matrices; (f) analytical determination during in vitro experiments (metabolism and permeability related) and in situ intestinal perfusion experiments; (g) determination of a major metabolite as a surrogate for the parent molecule; (h) analytical approaches for universal determination of CYP450 probe substrates and metabolites; (i) analytical applicability to prodrug evaluations-simultaneous determination of prodrug, parent and metabolites; (j) quantitative determination of parent compound and/or phase II metabolite(s) via direct or indirect approaches; (k) applicability in analysis of multiple compounds in select

  20. Development of modelling method selection tool for health services management: from problem structuring methods to modelling and simulation methods.

    Science.gov (United States)

    Jun, Gyuchan T; Morris, Zoe; Eldabi, Tillal; Harper, Paul; Naseer, Aisha; Patel, Brijesh; Clarkson, John P

    2011-05-19

    There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.

  1. Methods for the selective detection of alkyne-presenting molecules and related compositions and systems

    Science.gov (United States)

    Valdez, Carlos A.; Vu, Alexander K.

    2017-10-17

    Provided herein are methods for selectively detecting an alkyne-presenting molecule in a sample and related detection reagents, compositions, methods and systems. The methods include contacting a detection reagent with the sample for a time and under a condition to allow binding of the detection reagent to the one or more alkyne-presenting molecules possibly present in the matrix to the detection reagent. The detection reagent includes an organic label moiety presenting an azide group. The binding of the azide group to the alkyne-presenting molecules results in emission of a signal from the organic label moiety.

  2. Feature Selection Methods for Zero-Shot Learning of Neural Activity

    Directory of Open Access Journals (Sweden)

    Carlos A. Caceres

    2017-06-01

    Full Text Available Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

  3. A New Manufacturing Service Selection and Composition Method Using Improved Flower Pollination Algorithm

    Directory of Open Access Journals (Sweden)

    Wenyu Zhang

    2016-01-01

    Full Text Available With an increasing number of manufacturing services, the means by which to select and compose these manufacturing services have become a challenging problem. It can be regarded as a multiobjective optimization problem that involves a variety of conflicting quality of service (QoS attributes. In this study, a multiobjective optimization model of manufacturing service composition is presented that is based on QoS and an environmental index. Next, the skyline operator is applied to reduce the solution space. And then a new method called improved Flower Pollination Algorithm (FPA is proposed for solving the problem of manufacturing service selection and composition. The improved FPA enhances the performance of basic FPA by combining the latter with crossover and mutation operators of the Differential Evolution (DE algorithm. Finally, a case study is conducted to compare the proposed method with other evolutionary algorithms, including the Genetic Algorithm, DE, basic FPA, and extended FPA. The experimental results reveal that the proposed method performs best at solving the problem of manufacturing service selection and composition.

  4. FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

    Directory of Open Access Journals (Sweden)

    Ratri Enggar Pawening

    2016-06-01

    Full Text Available Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT is another way to handle heterogeneous features subset selection. The results of transformation from non-numerical into numerical features may produce redundancy to the original numerical features. In this paper, we propose a method to select feature subset based on mutual information (MI for classifying heterogeneous features. We use unsupervised feature transformation (UFT methods and joint mutual information maximation (JMIM methods. UFT methods is used to transform non-numerical features into numerical features. JMIM methods is used to select feature subset with a consideration of the class label. The transformed and the original features are combined entirely, then determine features subset by using JMIM methods, and classify them using support vector machine (SVM algorithm. The classification accuracy are measured for any number of selected feature subset and compared between UFT-JMIM methods and Dummy-JMIM methods. The average classification accuracy for all experiments in this study that can be achieved by UFT-JMIM methods is about 84.47% and Dummy-JMIM methods is about 84.24%. This result shows that UFT-JMIM methods can minimize information loss between transformed and original features, and select feature subset to avoid redundant and irrelevant features.

  5. Supplier Selection Using Weighted Utility Additive Method

    Science.gov (United States)

    Karande, Prasad; Chakraborty, Shankar

    2015-10-01

    Supplier selection is a multi-criteria decision-making (MCDM) problem which mainly involves evaluating a number of available suppliers according to a set of common criteria for choosing the best one to meet the organizational needs. For any manufacturing or service organization, selecting the right upstream suppliers is a key success factor that will significantly reduce purchasing cost, increase downstream customer satisfaction and improve competitive ability. The past researchers have attempted to solve the supplier selection problem employing different MCDM techniques which involve active participation of the decision makers in the decision-making process. This paper deals with the application of weighted utility additive (WUTA) method for solving supplier selection problems. The WUTA method, an extension of utility additive approach, is based on ordinal regression and consists of building a piece-wise linear additive decision model from a preference structure using linear programming (LP). It adopts preference disaggregation principle and addresses the decision-making activities through operational models which need implicit preferences in the form of a preorder of reference alternatives or a subset of these alternatives present in the process. The preferential preorder provided by the decision maker is used as a restriction of a LP problem, which has its own objective function, minimization of the sum of the errors associated with the ranking of each alternative. Based on a given reference ranking of alternatives, one or more additive utility functions are derived. Using these utility functions, the weighted utilities for individual criterion values are combined into an overall weighted utility for a given alternative. It is observed that WUTA method, having a sound mathematical background, can provide accurate ranking to the candidate suppliers and choose the best one to fulfill the organizational requirements. Two real time examples are illustrated to prove

  6. Alternative microbial methods: An overview and selection criteria.

    NARCIS (Netherlands)

    Jasson, V.; Jacxsens, L.; Luning, P.A.; Rajkovic, A.; Uyttendaele, M.

    2010-01-01

    This study provides an overview and criteria for the selection of a method, other than the reference method, for microbial analysis of foods. In a first part an overview of the general characteristics of rapid methods available, both for enumeration and detection, is given with reference to relevant

  7. Methods for selective functionalization and separation of carbon nanotubes

    Science.gov (United States)

    Strano, Michael S. (Inventor); Usrey, Monica (Inventor); Barone, Paul (Inventor); Dyke, Christopher A. (Inventor); Tour, James M. (Inventor); Kittrell, W. Carter (Inventor); Hauge, Robert H (Inventor); Smalley, Richard E. (Inventor); Marek, legal representative, Irene Marie (Inventor)

    2011-01-01

    The present invention is directed toward methods of selectively functionalizing carbon nanotubes of a specific type or range of types, based on their electronic properties, using diazonium chemistry. The present invention is also directed toward methods of separating carbon nanotubes into populations of specific types or range(s) of types via selective functionalization and electrophoresis, and also to the novel compositions generated by such separations.

  8. Advanced display object selection methods for enhancing user-computer productivity

    Science.gov (United States)

    Osga, Glenn A.

    1993-01-01

    The User-Interface Technology Branch at NCCOSC RDT&E Division has been conducting a series of studies to address the suitability of commercial off-the-shelf (COTS) graphic user-interface (GUI) methods for efficiency and performance in critical naval combat systems. This paper presents an advanced selection algorithm and method developed to increase user performance when making selections on tactical displays. The method has also been applied with considerable success to a variety of cursor and pointing tasks. Typical GUI's allow user selection by: (1) moving a cursor with a pointing device such as a mouse, trackball, joystick, touchscreen; and (2) placing the cursor on the object. Examples of GUI objects are the buttons, icons, folders, scroll bars, etc. used in many personal computer and workstation applications. This paper presents an improved method of selection and the theoretical basis for the significant performance gains achieved with various input devices tested. The method is applicable to all GUI styles and display sizes, and is particularly useful for selections on small screens such as notebook computers. Considering the amount of work-hours spent pointing and clicking across all styles of available graphic user-interfaces, the cost/benefit in applying this method to graphic user-interfaces is substantial, with the potential for increasing productivity across thousands of users and applications.

  9. A fuzzy logic based PROMETHEE method for material selection problems

    Directory of Open Access Journals (Sweden)

    Muhammet Gul

    2018-03-01

    Full Text Available Material selection is a complex problem in the design and development of products for diverse engineering applications. This paper presents a fuzzy PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation method based on trapezoidal fuzzy interval numbers that can be applied to the selection of materials for an automotive instrument panel. Also, it presents uniqueness in making a significant contribution to the literature in terms of the application of fuzzy decision-making approach to material selection problems. The method is illustrated, validated, and compared against three different fuzzy MCDM methods (fuzzy VIKOR, fuzzy TOPSIS, and fuzzy ELECTRE in terms of its ranking performance. Also, the relationships between the compared methods and the proposed scenarios for fuzzy PROMETHEE are evaluated via the Spearman’s correlation coefficient. Styrene Maleic Anhydride and Polypropylene are determined optionally as suitable materials for the automotive instrument panel case. We propose a generic fuzzy MCDM methodology that can be practically implemented to material selection problem. The main advantages of the methodology are consideration of the vagueness, uncertainty, and fuzziness to decision making environment.

  10. Factors of Selection of the Stock Allocation Method

    Directory of Open Access Journals (Sweden)

    Rohov Heorhii K.

    2014-03-01

    Full Text Available The article describes results of the author’s study of factors of making strategic decisions on selection of methods of stock allocation by public joint stock companies in Ukraine. The author used the Random forest mathematical apparatus of classification trees building and also informal methods. The article analyses the reasons that restrain public allocation of stock. It shows significant influence upon selection of a method of stock allocation of such factors as capital concentration, balance rate of corporate rights, sector of economy and significant participation of the institutes of common investment or the state in the authorised capital. The built hierarchical model of classification of factors of the issuing policy of joint stock companies finds logical justification in specific features of the institutional environment, however, it does not fit into the framework of the classical concept of the market economy. The model could be used both for formation of goals of corporate financial strategies and in the process of improvement of state regulation of activity of securities issuers. The prospect of further studies in this direction is identification of transformation of factors of selection of the stock allocation method under conditions of revival of the stock market.

  11. Proactive AP Selection Method Considering the Radio Interference Environment

    Science.gov (United States)

    Taenaka, Yuzo; Kashihara, Shigeru; Tsukamoto, Kazuya; Yamaguchi, Suguru; Oie, Yuji

    In the near future, wireless local area networks (WLANs) will overlap to provide continuous coverage over a wide area. In such ubiquitous WLANs, a mobile node (MN) moving freely between multiple access points (APs) requires not only permanent access to the Internet but also continuous communication quality during handover. In order to satisfy these requirements, an MN needs to (1) select an AP with better performance and (2) execute a handover seamlessly. To satisfy requirement (2), we proposed a seamless handover method in a previous study. Moreover, in order to achieve (1), the Received Signal Strength Indicator (RSSI) is usually employed to measure wireless link quality in a WLAN system. However, in a real environment, especially if APs are densely situated, it is difficult to always select an AP with better performance based on only the RSSI. This is because the RSSI alone cannot detect the degradation of communication quality due to radio interference. Moreover, it is important that AP selection is completed only on an MN, because we can assume that, in ubiquitous WLANs, various organizations or operators will manage APs. Hence, we cannot modify the APs for AP selection. To overcome these difficulties, in the present paper, we propose and implement a proactive AP selection method considering wireless link condition based on the number of frame retransmissions in addition to the RSSI. In the evaluation, we show that the proposed AP selection method can appropriately select an AP with good wireless link quality, i.e., high RSSI and low radio interference.

  12. Simulated selection responses for breeding programs including resistance and resilience to parasites in Creole goats.

    Science.gov (United States)

    Gunia, M; Phocas, F; Gourdine, J-L; Bijma, P; Mandonnet, N

    2013-02-01

    The Creole goat is a local breed used for meat production in Guadeloupe (French West Indies). As in other tropical countries, improvement of parasite resistance is needed. In this study, we compared predicted selection responses for alternative breeding programs with or without parasite resistance and resilience traits. The overall breeding goal included traits for production, reproduction, and parasite resilience and resistance to ensure a balanced selection outcome. The production traits were BW and dressing percentage (DP). The reproduction trait was fertility (FER), which was the number of doe kiddings per mating. The resistance trait was worm fecal egg count (FEC), which is a measurement of the number of gastro-intestinal parasite eggs found in the feces. The resilience trait was the packed cell volume (PCV), which is a measurement of the volume of red blood cells in the blood. Dressing percentage, BW, and FEC were measured at 11 mo of age, which is the mating or selling age. Fertility and PCV were measured on females at each kidding period. The breeding program accounting for the overall breeding goal and a selection index including all traits gave annual selection responses of 800 g for BW, 3.75% for FER, 0.08% for DP, -0.005 ln(eggs/g) for FEC, and 0.28% for PCV. The expected selection responses for BW and DP in this breeding program were reduced by 2% and 6%, respectively, compared with a breeding program not accounting for FEC and PCV. The overall breeding program, proposed for the Creole breed, offers the best breeding strategy in terms of expected selection responses, making it possible to improve all traits together. It offers a good balance between production and adaptation traits and may present some interest for the selection of other goat breeds in the tropics.

  13. Selection method of terrain matching area for TERCOM algorithm

    Science.gov (United States)

    Zhang, Qieqie; Zhao, Long

    2017-10-01

    The performance of terrain aided navigation is closely related to the selection of terrain matching area. The different matching algorithms have different adaptability to terrain. This paper mainly studies the adaptability to terrain of TERCOM algorithm, analyze the relation between terrain feature and terrain characteristic parameters by qualitative and quantitative methods, and then research the relation between matching probability and terrain characteristic parameters by the Monte Carlo method. After that, we propose a selection method of terrain matching area for TERCOM algorithm, and verify the method correctness with real terrain data by simulation experiment. Experimental results show that the matching area obtained by the method in this paper has the good navigation performance and the matching probability of TERCOM algorithm is great than 90%

  14. A probabilistic method for testing and estimating selection differences between populations.

    Science.gov (United States)

    He, Yungang; Wang, Minxian; Huang, Xin; Li, Ran; Xu, Hongyang; Xu, Shuhua; Jin, Li

    2015-12-01

    Human populations around the world encounter various environmental challenges and, consequently, develop genetic adaptations to different selection forces. Identifying the differences in natural selection between populations is critical for understanding the roles of specific genetic variants in evolutionary adaptation. Although numerous methods have been developed to detect genetic loci under recent directional selection, a probabilistic solution for testing and quantifying selection differences between populations is lacking. Here we report the development of a probabilistic method for testing and estimating selection differences between populations. By use of a probabilistic model of genetic drift and selection, we showed that logarithm odds ratios of allele frequencies provide estimates of the differences in selection coefficients between populations. The estimates approximate a normal distribution, and variance can be estimated using genome-wide variants. This allows us to quantify differences in selection coefficients and to determine the confidence intervals of the estimate. Our work also revealed the link between genetic association testing and hypothesis testing of selection differences. It therefore supplies a solution for hypothesis testing of selection differences. This method was applied to a genome-wide data analysis of Han and Tibetan populations. The results confirmed that both the EPAS1 and EGLN1 genes are under statistically different selection in Han and Tibetan populations. We further estimated differences in the selection coefficients for genetic variants involved in melanin formation and determined their confidence intervals between continental population groups. Application of the method to empirical data demonstrated the outstanding capability of this novel approach for testing and quantifying differences in natural selection. © 2015 He et al.; Published by Cold Spring Harbor Laboratory Press.

  15. Quantitative Methods for Software Selection and Evaluation

    National Research Council Canada - National Science Library

    Bandor, Michael S

    2006-01-01

    ... (the ability of the product to meet the need) and the cost. The method used for the analysis and selection activities can range from the use of basic intuition to counting the number of requirements fulfilled, or something...

  16. Proposed Project Selection Method for Human Support Research and Technology Development (HSR&TD)

    Science.gov (United States)

    Jones, Harry

    2005-01-01

    The purpose of HSR&TD is to deliver human support technologies to the Exploration Systems Mission Directorate (ESMD) that will be selected for future missions. This requires identifying promising candidate technologies and advancing them in technology readiness until they are acceptable. HSR&TD must select an may of technology development projects, guide them, and either terminate or continue them, so as to maximize the resulting number of usable advanced human support technologies. This paper proposes an effective project scoring methodology to support managing the HSR&TD project portfolio. Researchers strongly disagree as to what are the best technology project selection methods, or even if there are any proven ones. Technology development is risky and outstanding achievements are rare and unpredictable. There is no simple formula for success. Organizations that are satisfied with their project selection approach typically use a mix of financial, strategic, and scoring methods in an open, established, explicit, formal process. This approach helps to build consensus and develop management insight. It encourages better project proposals by clarifying the desired project attributes. We propose a project scoring technique based on a method previously used in a federal laboratory and supported by recent research. Projects are ranked by their perceived relevance, risk, and return - a new 3 R's. Relevance is the degree to which the project objective supports the HSR&TD goal of developing usable advanced human support technologies. Risk is the estimated probability that the project will achieve its specific objective. Return is the reduction in mission life cycle cost obtained if the project is successful. If the project objective technology performs a new function with no current cost, its return is the estimated cash value of performing the new function. The proposed project selection scoring method includes definitions of the criteria, a project evaluation

  17. [Study of near infrared spectral preprocessing and wavelength selection methods for endometrial cancer tissue].

    Science.gov (United States)

    Zhao, Li-Ting; Xiang, Yu-Hong; Dai, Yin-Mei; Zhang, Zhuo-Yong

    2010-04-01

    Near infrared spectroscopy was applied to measure the tissue slice of endometrial tissues for collecting the spectra. A total of 154 spectra were obtained from 154 samples. The number of normal, hyperplasia, and malignant samples was 36, 60, and 58, respectively. Original near infrared spectra are composed of many variables, for example, interference information including instrument errors and physical effects such as particle size and light scatter. In order to reduce these influences, original spectra data should be performed with different spectral preprocessing methods to compress variables and extract useful information. So the methods of spectral preprocessing and wavelength selection have played an important role in near infrared spectroscopy technique. In the present paper the raw spectra were processed using various preprocessing methods including first derivative, multiplication scatter correction, Savitzky-Golay first derivative algorithm, standard normal variate, smoothing, and moving-window median. Standard deviation was used to select the optimal spectral region of 4 000-6 000 cm(-1). Then principal component analysis was used for classification. Principal component analysis results showed that three types of samples could be discriminated completely and the accuracy almost achieved 100%. This study demonstrated that near infrared spectroscopy technology and chemometrics method could be a fast, efficient, and novel means to diagnose cancer. The proposed methods would be a promising and significant diagnosis technique of early stage cancer.

  18. Membrane for distillation including nanostructures, methods of making membranes, and methods of desalination and separation

    KAUST Repository

    Lai, Zhiping; Huang, Kuo-Wei; Chen, Wei

    2016-01-01

    In accordance with the purpose(s) of the present disclosure, as embodied and broadly described herein, embodiments of the present disclosure provide membranes, methods of making the membrane, systems including the membrane, methods of separation, methods of desalination, and the like.

  19. Membrane for distillation including nanostructures, methods of making membranes, and methods of desalination and separation

    KAUST Repository

    Lai, Zhiping

    2016-01-21

    In accordance with the purpose(s) of the present disclosure, as embodied and broadly described herein, embodiments of the present disclosure provide membranes, methods of making the membrane, systems including the membrane, methods of separation, methods of desalination, and the like.

  20. A Comparative Study of Feature Selection and Classification Methods for Gene Expression Data

    KAUST Repository

    Abusamra, Heba

    2013-01-01

    Different experiments have been applied to compare the performance of the classification methods with and without performing feature selection. Results revealed the important role of feature selection in classifying gene expression data. By performing feature selection, the classification accuracy can be significantly boosted by using a small number of genes. The relationship of features selected in different feature selection methods is investigated and the most frequent features selected in each fold among all methods for both datasets are evaluated.

  1. Will genomic selection be a practical method for plant breeding?

    Science.gov (United States)

    Nakaya, Akihiro; Isobe, Sachiko N

    2012-11-01

    Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use. In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed. Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.

  2. Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection.

    Science.gov (United States)

    Hanine, Mohamed; Boutkhoum, Omar; Tikniouine, Abdessadek; Agouti, Tarik

    2016-01-01

    Landfill location selection is a multi-criteria decision problem and has a strategic importance for many regions. The conventional methods for landfill location selection are insufficient in dealing with the vague or imprecise nature of linguistic assessment. To resolve this problem, fuzzy multi-criteria decision-making methods are proposed. The aim of this paper is to use fuzzy TODIM (the acronym for Interactive and Multi-criteria Decision Making in Portuguese) and the fuzzy analytic hierarchy process (AHP) methods for the selection of landfill location. The proposed methods have been applied to a landfill location selection problem in the region of Casablanca, Morocco. After determining the criteria affecting the landfill location decisions, fuzzy TODIM and fuzzy AHP methods are applied to the problem and results are presented. The comparisons of these two methods are also discussed.

  3. Research on filter’s parameter selection based on PROMETHEE method

    Science.gov (United States)

    Zhu, Hui-min; Wang, Hang-yu; Sun, Shi-yan

    2018-03-01

    The selection of filter’s parameters in target recognition was studied in this paper. The PROMETHEE method was applied to the optimization problem of Gabor filter parameters decision, the correspondence model of the elemental relation between two methods was established. The author took the identification of military target as an example, problem about the filter’s parameter decision was simulated and calculated by PROMETHEE. The result showed that using PROMETHEE method for the selection of filter’s parameters was more scientific. The human disturbance caused by the experts method and empirical method could be avoided by this way. The method can provide reference for the parameter configuration scheme decision of the filter.

  4. Combining AHP and DEA Methods for Selecting a Project Manager

    Directory of Open Access Journals (Sweden)

    Baruch Keren

    2014-07-01

    Full Text Available A project manager has a major influence on the success or failure of the project. A good project manager can match between the strategy and objectives of the organization and the goals of the project. Therefore, the selection of the appropriate project manager is a key factor for the success of the project. A potential project manager is judged by his or her proven performance and personal qualifications. This paper proposes a method to calculate the weighted scores and the full rank of candidates for managing a project, and to select the best of those candidates. The proposed method combines specific methodologies: the Data Envelopment Analysis (DEA and the Analytical Hierarchical Process (AHP and uses DEA Ranking Methods to enhance selection.

  5. Indicators for Monitoring Water, Sanitation, and Hygiene: A Systematic Review of Indicator Selection Methods

    Directory of Open Access Journals (Sweden)

    Stefanie Schwemlein

    2016-03-01

    Full Text Available Monitoring water, sanitation, and hygiene (WaSH is important to track progress, improve accountability, and demonstrate impacts of efforts to improve conditions and services, especially in low- and middle-income countries. Indicator selection methods enable robust monitoring of WaSH projects and conditions. However, selection methods are not always used and there are no commonly-used methods for selecting WaSH indicators. To address this gap, we conducted a systematic review of indicator selection methods used in WaSH-related fields. We present a summary of indicator selection methods for environment, international development, and water. We identified six methodological stages for selecting indicators for WaSH: define the purpose and scope; select a conceptual framework; search for candidate indicators; determine selection criteria; score indicators against criteria; and select a final suite of indicators. This summary of indicator selection methods provides a foundation for the critical assessment of existing methods. It can be used to inform future efforts to construct indicator sets in WaSH and related fields.

  6. Selective Integration in the Material-Point Method

    DEFF Research Database (Denmark)

    Andersen, Lars; Andersen, Søren; Damkilde, Lars

    2009-01-01

    The paper deals with stress integration in the material-point method. In order to avoid parasitic shear in bending, a formulation is proposed, based on selective integration in the background grid that is used to solve the governing equations. The suggested integration scheme is compared...... to a traditional material-point-method computation in which the stresses are evaluated at the material points. The deformation of a cantilever beam is analysed, assuming elastic or elastoplastic material behaviour....

  7. Maintenance of the selected infant feeding methods amongst ...

    African Journals Online (AJOL)

    The focus of this study was to explore and describe influences on decision making related to infant feeding methods in the context of HIV and AIDS. Study objectives were: (1) to explore and describe the influences on decision making related to infant feeding methods selected by the mother during the antenatal period and ...

  8. Supplier Portfolio Selection and Optimum Volume Allocation: A Knowledge Based Method

    NARCIS (Netherlands)

    Aziz, Romana; Aziz, R.; van Hillegersberg, Jos; Kersten, W.; Blecker, T.; Luthje, C.

    2010-01-01

    Selection of suppliers and allocation of optimum volumes to suppliers is a strategic business decision. This paper presents a decision support method for supplier selection and the optimal allocation of volumes in a supplier portfolio. The requirements for the method were gathered during a case

  9. A review of methods supporting supplier selection

    NARCIS (Netherlands)

    de Boer, L.; Labro, Eva; Morlacchi, Pierangela

    2001-01-01

    this paper we present a review of decision methods reported in the literature for supporting the supplier selection process. The review is based on an extensive search in the academic literature. We position the contributions in a framework that takes the diversity of procurement situations in terms

  10. Development of new methods in modern selective organic synthesis: preparation of functionalized molecules with atomic precision

    International Nuclear Information System (INIS)

    Ananikov, V P; Khemchyan, L L; Ivanova, Yu V; Dilman, A D; Levin, V V; Bukhtiyarov, V I; Sorokin, A M; Prosvirin, I P; Romanenko, A V; Simonov, P A; Vatsadze, S Z; Medved'ko, A V; Nuriev, V N; Nenajdenko, V G; Shmatova, O I; Muzalevskiy, V M; Koptyug, I V; Kovtunov, K V; Zhivonitko, V V; Likholobov, V A

    2014-01-01

    The challenges of the modern society and the growing demand of high-technology sectors of industrial production bring about a new phase in the development of organic synthesis. A cutting edge of modern synthetic methods is introduction of functional groups and more complex structural units into organic molecules with unprecedented control over the course of chemical transformation. Analysis of the state-of-the-art achievements in selective organic synthesis indicates the appearance of a new trend — the synthesis of organic molecules, biologically active compounds, pharmaceutical substances and smart materials with absolute selectivity. Most advanced approaches to organic synthesis anticipated in the near future can be defined as 'atomic precision' in chemical reactions. The present review considers selective methods of organic synthesis suitable for transformation of complex functionalized molecules under mild conditions. Selected key trends in the modern organic synthesis are considered including the preparation of organofluorine compounds, catalytic cross-coupling and oxidative cross-coupling reactions, atom-economic addition reactions, methathesis processes, oxidation and reduction reactions, synthesis of heterocyclic compounds, design of new homogeneous and heterogeneous catalytic systems, application of photocatalysis, scaling up synthetic procedures to industrial level and development of new approaches to investigation of mechanisms of catalytic reactions. The bibliography includes 840 references

  11. Selected Tools and Methods from Quality Management Field

    Directory of Open Access Journals (Sweden)

    Kateřina BRODECKÁ

    2009-06-01

    Full Text Available Following paper describes selected tools and methods from Quality management field and their practical applications on defined examples. Solved examples were elaborated in the form of electronic support. This in detail elaborated electronic support provides students opportunity to thoroughly practice specific issues, help them to prepare for exams and consequently will lead to education improvement. Especially students of combined study form will appreciate this support. The paper specifies project objectives, subjects that will be covered by mentioned support, target groups, structure and the way of elaboration of electronic exercise book in view. The emphasis is not only on manual solution of selected examples that may help students to understand the principles and relationships, but also on solving and results interpreting of selected examples using software support. Statistic software Statgraphics Plus v 5.0 is used while working support, because it is free to use for all students of the faculty. Exemplary example from the subject Basic Statistical Methods of Quality Management is also part of this paper.

  12. A survey of variable selection methods in two Chinese epidemiology journals

    Directory of Open Access Journals (Sweden)

    Lynn Henry S

    2010-09-01

    Full Text Available Abstract Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163 via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44% used stepwise procedures, 89 (41% tested individual regression coefficients, but 33 (15% did not mention how variables were selected. Sixty percent (58/97 of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals.

  13. The Preparation and Selection of Budget Methods for Promotion in Kosovo

    Directory of Open Access Journals (Sweden)

    MSc. Halit Karaxha

    2017-06-01

    Full Text Available Selecting the adequate method for promotion has a huge importance in increasing business’s performance. Selecting the method of the budget depends from a number of factors. The formulation of budget is known as the most critical period which requires special analysis from marketing’s managers. The expenses for promotion are usually high, and every investment made in the field of promotion directly influences in the business situation. Thus, the selection and adequate formulation of budget methods for promotion influences the growth of profit. The allocated amount for promotion depends from a number of factors, such as: the size of the firm, the sector in which it operates, competition etc. After planning the budget, we have to do the budget allocation to select the promotional form which is considered to be successful by the firms in promoting the products and services and that will help the company to connect with its clients. In this paper, I have elaborated the role and importance of the preparation and selection of budget methods for promotion in the theoretical aspect and the practical one as well.

  14. The Choice Method of Selected Material has influence single evaporation flash method

    International Nuclear Information System (INIS)

    Sunaryo, Geni Rina; Sumijanto; Nurul L, Siti

    2000-01-01

    The final objective of this research is to design the mini scale of desalination installation. It has been started from 1997/1998 and has been doing for this 3 years. Where the study on the assessment of various desalination system has been done in the first year and thermodynamic in the second year. In this third year, literatully study on material resistance from outside pressure has been done. The number of pressure for single evaporator flashing method is mainly depend on the temperature that applied in that system. In this paper, the configuration stage, the choice method of selecting material for main evaporator vessel, tube, tube plates, water boxes, pipework, and valves for multistage flash distillation will be described. The choice of selecting material for MSF is base on economical consideration, cheap, high resistance and easy to be maintained

  15. Personnel Selection Method Based on Personnel-Job Matching

    OpenAIRE

    Li Wang; Xilin Hou; Lili Zhang

    2013-01-01

    The existing personnel selection decisions in practice are based on the evaluation of job seeker's human capital, and it may be difficult to make personnel-job matching and make each party satisfy. Therefore, this paper puts forward a new personnel selection method by consideration of bilateral matching. Starting from the employment thoughts of ¡°satisfy¡±, the satisfaction evaluation indicator system of each party are constructed. The multi-objective optimization model is given according to ...

  16. Normalization method for metabolomics data using optimal selection of multiple internal standards

    Directory of Open Access Journals (Sweden)

    Yetukuri Laxman

    2007-03-01

    Full Text Available Abstract Background Success of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific sources of variability such as systematic error is therefore one of the foremost priorities in data preprocessing. However, chemical diversity of molecular species included in typical metabolic profiling experiments leads to different responses to variations in experimental conditions, making normalization a very demanding task. Results With the aim to remove unwanted systematic variation, we present an approach that utilizes variability information from multiple internal standard compounds to find optimal normalization factor for each individual molecular species detected by metabolomics approach (NOMIS. We demonstrate the method on mouse liver lipidomic profiles using Ultra Performance Liquid Chromatography coupled to high resolution mass spectrometry, and compare its performance to two commonly utilized normalization methods: normalization by l2 norm and by retention time region specific standard compound profiles. The NOMIS method proved superior in its ability to reduce the effect of systematic error across the full spectrum of metabolite peaks. We also demonstrate that the method can be used to select best combinations of standard compounds for normalization. Conclusion Depending on experiment design and biological matrix, the NOMIS method is applicable either as a one-step normalization method or as a two-step method where the normalization parameters, influenced by variabilities of internal standard compounds and their correlation to metabolites, are first calculated from a study conducted in repeatability conditions. The method can also be used in analytical development of metabolomics methods by helping to select best combinations of standard compounds for a particular biological matrix and analytical platform.

  17. SOURCES OF COPPER IONS AND SELECTED METHODS OF THEIR REMOVAL FROM WASTEWATER FROM THE PRINTED CIRCUITS BOARD PRODUCTION

    Directory of Open Access Journals (Sweden)

    Maciej Thomas

    2014-10-01

    Full Text Available This paper presents the issues related to the presence and removal of copper compounds from industrial effluents with including wastewater from plants involved in the production of printed circuit boards. Characterized the toxicological properties of selected copper compounds, described the applicable technological processes, sources of copper ions in the effluents and selected methods for their removal.

  18. Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes

    Directory of Open Access Journals (Sweden)

    Lotz Meredith J

    2008-01-01

    Full Text Available Abstract Background Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures × time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. Results We found that the optimal imputation algorithms (LSA, LLS, and BPCA are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Conclusion Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA

  19. Which missing value imputation method to use in expression profiles: a comparative study and two selection schemes.

    Science.gov (United States)

    Brock, Guy N; Shaffer, John R; Blakesley, Richard E; Lotz, Meredith J; Tseng, George C

    2008-01-10

    Gene expression data frequently contain missing values, however, most down-stream analyses for microarray experiments require complete data. In the literature many methods have been proposed to estimate missing values via information of the correlation patterns within the gene expression matrix. Each method has its own advantages, but the specific conditions for which each method is preferred remains largely unclear. In this report we describe an extensive evaluation of eight current imputation methods on multiple types of microarray experiments, including time series, multiple exposures, and multiple exposures x time series data. We then introduce two complementary selection schemes for determining the most appropriate imputation method for any given data set. We found that the optimal imputation algorithms (LSA, LLS, and BPCA) are all highly competitive with each other, and that no method is uniformly superior in all the data sets we examined. The success of each method can also depend on the underlying "complexity" of the expression data, where we take complexity to indicate the difficulty in mapping the gene expression matrix to a lower-dimensional subspace. We developed an entropy measure to quantify the complexity of expression matrixes and found that, by incorporating this information, the entropy-based selection (EBS) scheme is useful for selecting an appropriate imputation algorithm. We further propose a simulation-based self-training selection (STS) scheme. This technique has been used previously for microarray data imputation, but for different purposes. The scheme selects the optimal or near-optimal method with high accuracy but at an increased computational cost. Our findings provide insight into the problem of which imputation method is optimal for a given data set. Three top-performing methods (LSA, LLS and BPCA) are competitive with each other. Global-based imputation methods (PLS, SVD, BPCA) performed better on mcroarray data with lower complexity

  20. Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method

    Directory of Open Access Journals (Sweden)

    Mohammad Panahi Borujeni

    2017-01-01

    Full Text Available The increasing complexity surrounding decision-making situations has made it inevitable for practitioners to apply ideas from a group of experts or decision makers (DMs instead of individuals. In a large proportion of recent studies, not enough attention has been paid to considering uncertainty in practical ways. In this paper, a hesitant fuzzy preference selection index (HFPSI method is proposed based on a new soft computing approach with risk preferences of DMs to deal with imprecise multi-criteria decision-making problems. Meanwhile, qualitative assessing criteria are considered in the process of the proposed method to help the DMs by providing suitable expressions of membership degrees for an element under a set. Moreover, the best alternative is selected based on considering the concepts of preference relation and hesitant fuzzy sets, simultaneously. Therefore, DMs' weights are determined according to the proposed hesitant fuzzy compromise solution technique to prevent judgment errors. Moreover, the proposed method has been extended based on the last aggregation method by aggregating the DMs' opinions during the last stage to avoid data loss. In this respect, a real case study about the mining contractor selection problem is provided to represent the effectiveness and efficiency of the proposed HFPSI method in practice. Then, a comparative analysis is performed to show the feasibility of the presented approach. Finally, sensitivity analysis is carried out to show the effect of considering the DMs' weights and last aggregation approach in a dispersion of the alternatives’ ranking values.

  1. Selection of heat disposal methods for a Hanford Nuclear Energy Center

    International Nuclear Information System (INIS)

    Young, J.R.; Kannberg, L.D.; Ramsdell, J.V.; Rickard, W.H.; Watson, D.G.

    1976-06-01

    Selection of the best method for disposal of the waste heat from a large power generation center requires a comprehensive comparison of the costs and environmental effects. The objective is to identify the heat dissipation method with the minimum total economic and environmental cost. A 20 reactor HNEC will dissipate about 50,000 MWt of waste heat; a 40 reactor HNEC would release about 100,000 MWt. This is a much larger discharge of heat than has occurred from other concentrated industrial facilities and consequently a special analysis is required to determine the permissibility of such a large heat disposal and the best methods of disposal. It is possible that some methods of disposal will not be permissible because of excessive environmental effects or that the optimum disposal method may include a combination of several methods. A preliminary analysis is presented of the Hanford Nuclear Energy Center heat disposal problem to determine the best methods for disposal and any obvious limitations on the amount of heat that can be released. The analysis is based, in part, on information from an interim conceptual study, a heat sink management analysis, and a meteorological analysis

  2. GREY STATISTICS METHOD OF TECHNOLOGY SELECTION FOR ADVANCED PUBLIC TRANSPORTATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    Chien Hung WEI

    2003-01-01

    Full Text Available Taiwan is involved in intelligent transportation systems planning, and is now selecting its prior focus areas for investment and development. The high social and economic impact associated with which intelligent transportation systems technology are chosen explains the efforts of various electronics and transportation corporations for developing intelligent transportation systems technology to expand their business opportunities. However, there has been no detailed research conducted with regard to selecting technology for advanced public transportation systems in Taiwan. Thus, the present paper demonstrates a grey statistics method integrated with a scenario method for solving the problem of selecting advanced public transportation systems technology for Taiwan. A comprehensive questionnaire survey was conducted to demonstrate the effectiveness of the grey statistics method. The proposed approach indicated that contactless smart card technology is the appropriate technology for Taiwan to develop in the near future. The significance of our research results implies that the grey statistics method is an effective method for selecting advanced public transportation systems technologies. We feel our information will be beneficial to the private sector for developing an appropriate intelligent transportation systems technology strategy.

  3. Toward optimal feature selection using ranking methods and classification algorithms

    Directory of Open Access Journals (Sweden)

    Novaković Jasmina

    2011-01-01

    Full Text Available We presented a comparison between several feature ranking methods used on two real datasets. We considered six ranking methods that can be divided into two broad categories: statistical and entropy-based. Four supervised learning algorithms are adopted to build models, namely, IB1, Naive Bayes, C4.5 decision tree and the RBF network. We showed that the selection of ranking methods could be important for classification accuracy. In our experiments, ranking methods with different supervised learning algorithms give quite different results for balanced accuracy. Our cases confirm that, in order to be sure that a subset of features giving the highest accuracy has been selected, the use of many different indices is recommended.

  4. Unsteady panel method for complex configurations including wake modeling

    CSIR Research Space (South Africa)

    Van Zyl, Lourens H

    2008-01-01

    Full Text Available implementations of the DLM are however not very versatile in terms of geometries that can be modeled. The ZONA6 code offers a versatile surface panel body model including a separated wake model, but uses a pressure panel method for lifting surfaces. This paper...

  5. Traditional and robust vector selection methods for use with similarity based models

    International Nuclear Information System (INIS)

    Hines, J. W.; Garvey, D. R.

    2006-01-01

    Vector selection, or instance selection as it is often called in the data mining literature, performs a critical task in the development of nonparametric, similarity based models. Nonparametric, similarity based modeling (SBM) is a form of 'lazy learning' which constructs a local model 'on the fly' by comparing a query vector to historical, training vectors. For large training sets the creation of local models may become cumbersome, since each training vector must be compared to the query vector. To alleviate this computational burden, varying forms of training vector sampling may be employed with the goal of selecting a subset of the training data such that the samples are representative of the underlying process. This paper describes one such SBM, namely auto-associative kernel regression (AAKR), and presents five traditional vector selection methods and one robust vector selection method that may be used to select prototype vectors from a larger data set in model training. The five traditional vector selection methods considered are min-max, vector ordering, combination min-max and vector ordering, fuzzy c-means clustering, and Adeli-Hung clustering. Each method is described in detail and compared using artificially generated data and data collected from the steam system of an operating nuclear power plant. (authors)

  6. Selective saturation method for EPR dosimetry with tooth enamel

    International Nuclear Information System (INIS)

    Ignatiev, E.A.; Romanyukha, A.A.; Koshta, A.A.; Wieser, A.

    1996-01-01

    The method of selective saturation is based on the difference in the microwave (mw) power dependence of the background and radiation induced EPR components of the tooth enamel spectrum. The subtraction of the EPR spectrum recorded at low mw power from that recorded at higher mw power provides a considerable reduction of the background component in the spectrum. The resolution of the EPR spectrum could be improved 10-fold, however simultaneously the signal-to-noise ratio was found to be reduced twice. A detailed comparative study of reference samples with known absorbed doses was performed to demonstrate the advantage of the method. The application of the selective saturation method for EPR dosimetry with tooth enamel reduced the lower limit of EPR dosimetry to about 100 mGy. (author)

  7. A new DEA-GAHP method for supplier selection problem

    Directory of Open Access Journals (Sweden)

    Behrooz Ahadian

    2012-10-01

    Full Text Available Supplier selection is one of the most important decisions made in supply chain management. Supplier evaluation problem has been in the center of supply chain researcher’s attention in these years. Managers regard some of these studies and methods inappropriate due to simple, weight scoring methods that generally are based on subjective opinions and judgments of decision maker units involved in the supplier evaluation process yielding imprecise and even unreliable results. This paper seeks to propose a methodology to integrate data envelopment analysis (DEA and group analytical hierarchy process (GAHP for evaluating and selecting the most efficient supplier. We develop a methodology, which consists of 6 steps, one by one has been introduced in lecture and finally applicability of proposed method is indicated by assessing 12 suppliers in a numerical example.

  8. Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

    Directory of Open Access Journals (Sweden)

    Ueki Masao

    2012-05-01

    Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

  9. An iterative method for selecting degenerate multiplex PCR primers.

    Science.gov (United States)

    Souvenir, Richard; Buhler, Jeremy; Stormo, Gary; Zhang, Weixiong

    2007-01-01

    Single-nucleotide polymorphism (SNP) genotyping is an important molecular genetics process, which can produce results that will be useful in the medical field. Because of inherent complexities in DNA manipulation and analysis, many different methods have been proposed for a standard assay. One of the proposed techniques for performing SNP genotyping requires amplifying regions of DNA surrounding a large number of SNP loci. To automate a portion of this particular method, it is necessary to select a set of primers for the experiment. Selecting these primers can be formulated as the Multiple Degenerate Primer Design (MDPD) problem. The Multiple, Iterative Primer Selector (MIPS) is an iterative beam-search algorithm for MDPD. Theoretical and experimental analyses show that this algorithm performs well compared with the limits of degenerate primer design. Furthermore, MIPS outperforms an existing algorithm that was designed for a related degenerate primer selection problem.

  10. Wavelength selection method with standard deviation: application to pulse oximetry.

    Science.gov (United States)

    Vazquez-Jaccaud, Camille; Paez, Gonzalo; Strojnik, Marija

    2011-07-01

    Near-infrared spectroscopy provides useful biological information after the radiation has penetrated through the tissue, within the therapeutic window. One of the significant shortcomings of the current applications of spectroscopic techniques to a live subject is that the subject may be uncooperative and the sample undergoes significant temporal variations, due to his health status that, from radiometric point of view, introduce measurement noise. We describe a novel wavelength selection method for monitoring, based on a standard deviation map, that allows low-noise sensitivity. It may be used with spectral transillumination, transmission, or reflection signals, including those corrupted by noise and unavoidable temporal effects. We apply it to the selection of two wavelengths for the case of pulse oximetry. Using spectroscopic data, we generate a map of standard deviation that we propose as a figure-of-merit in the presence of the noise introduced by the living subject. Even in the presence of diverse sources of noise, we identify four wavelength domains with standard deviation, minimally sensitive to temporal noise, and two wavelengths domains with low sensitivity to temporal noise.

  11. A pragmatic pairwise group-decision method for selection of sites for nuclear power plants

    International Nuclear Information System (INIS)

    Kutbi, I.I.

    1987-01-01

    A pragmatic pairwise group-decision approach is applied to compare two regions in order to select the more suitable one for construction of nulcear power plants in the Kingdom of Saudi Arabia. The selection methodology is based on pairwise comparison by forced choice. The method facilitates rating of the regions or sites using simple calculations. Two regions, one close to Dhahran on the Arabian Gulf and another close to Jeddah on the Red Sea, are evaluated. No specific site in either region is considered at this stage. The comparison is based on a set of selection criteria which include (i) topography, (ii) geology, (iii) seismology, (iv) meteorology, (v) oceanography, (vi) hydrology and (vii) proximetry to oil and gas fields. The comparison shows that the Jeddah region is more suitable than the Dhahran region. (orig.)

  12. Selective adsorption-desorption method for the enrichment of krypton

    International Nuclear Information System (INIS)

    Yuasa, Y.; Ohta, M.; Watanabe, A.; Tani, A.; Takashima, N.

    1975-01-01

    Selective adsorption-desorption method has been developed as an effective means of enriching krypton and xenon gases. A seriesof laboratory-scale tests were performed to provide some basic data of the method when applied to off-gas streams of nuclear power plants. For the first step of the enrichment process of the experiments, krypton was adsorbed on solid adsorbents from dilute mixtures with air at temperatures ranging from -50 0 C to -170 0 C. After the complete breakthrough was obtained, the adsorption bed was evacuated at low temperature by a vacuum pump. By combining these two steps krypton was highly enriched on the adsorbents, and the enrichment factor for krypton was calculated as the product of individual enrichment factors of each step. Two types of adsorbents, coconut charcoal and molecular sieves 5A, were used. Experimental results showed that the present method gave the greater enrichment factor than the conventional method which used selective adsorption step only. (U.S.)

  13. Personnel selection using group fuzzy AHP and SAW methods

    Directory of Open Access Journals (Sweden)

    Ali Reza Afshari

    2017-01-01

    Full Text Available Personnel evaluation and selection is a very important activity for the enterprises. Different job needs different ability and the requirement of criteria which can measure ability is different. It needs a suitable and flexible method to evaluate the performance of each candidate according to different requirements of different jobs in relation to each criterion. Analytic Hierarchy Process (AHP is one of Multi Criteria decision making methods derived from paired comparisons. Simple Additive Weighting (SAW is most frequently used multi attribute decision technique. The method is based on the weighted average. It successfully models the ambiguity and imprecision associated with the pair wise comparison process and reduces the personal biasness. This study tries to analyze the Analytic Hierarchy Process in order to make the recruitment process more reasonable, based on the fuzzy multiple criteria decision making model to achieve the goal of personnel selection. Finally, an example is implemented to demonstrate the practicability of the proposed method.

  14. Out of the box selection and application of UX evaluation methods and practical cases

    DEFF Research Database (Denmark)

    Obrist, Marianna; Knoche, Hendrik; Basapur, Santosh

    2013-01-01

    The scope of user experience supersedes the concept of usability and other performance oriented measures by including for example users' emotions, motivations and a strong focus on the context of use. The purpose of this tutorial is to motivate researchers and practitioners to think about...... the challenging questions around how to select and apply UX evaluation methods for different usage contexts, in particular for the "home" and "mobile" context, relevant for TV-based services. Next to a general understanding of UX evaluation and available methods, we will provide concrete UX evaluation case...

  15. ALIS-FLP: Amplified ligation selected fragment-length polymorphism method for microbial genotyping

    DEFF Research Database (Denmark)

    Brillowska-Dabrowska, A.; Wianecka, M.; Dabrowski, Slawomir

    2008-01-01

    A DNA fingerprinting method known as ALIS-FLP (amplified ligation selected fragment-length polymorphism) has been developed for selective and specific amplification of restriction fragments from TspRI restriction endonuclease digested genomic DNA. The method is similar to AFLP, but differs...

  16. Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

    Directory of Open Access Journals (Sweden)

    Rasim M. Alguliyev

    2015-01-01

    Full Text Available Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method.

  17. Catalyst support structure, catalyst including the structure, reactor including a catalyst, and methods of forming same

    Science.gov (United States)

    Van Norman, Staci A.; Aston, Victoria J.; Weimer, Alan W.

    2017-05-09

    Structures, catalysts, and reactors suitable for use for a variety of applications, including gas-to-liquid and coal-to-liquid processes and methods of forming the structures, catalysts, and reactors are disclosed. The catalyst material can be deposited onto an inner wall of a microtubular reactor and/or onto porous tungsten support structures using atomic layer deposition techniques.

  18. Hot-spot selection and evaluation methods for whole slice images of meningiomas and oligodendrogliomas.

    Science.gov (United States)

    Swiderska, Zaneta; Markiewicz, Tomasz; Grala, Bartlomiej; Slodkowska, Janina

    2015-01-01

    The paper presents a combined method for an automatic hot-spot areas selection based on penalty factor in the whole slide images to support the pathomorphological diagnostic procedure. The studied slides represent the meningiomas and oligodendrogliomas tumor on the basis of the Ki-67/MIB-1 immunohistochemical reaction. It allows determining the tumor proliferation index as well as gives an indication to the medical treatment and prognosis. The combined method based on mathematical morphology, thresholding, texture analysis and classification is proposed and verified. The presented algorithm includes building a specimen map, elimination of hemorrhages from them, two methods for detection of hot-spot fields with respect to an introduced penalty factor. Furthermore, we propose localization concordance measure to evaluation localization of hot spot selection by the algorithms in respect to the expert's results. Thus, the results of the influence of the penalty factor are presented and discussed. It was found that the best results are obtained for 0.2 value of them. They confirm effectiveness of applied approach.

  19. A Fast Adaptive Receive Antenna Selection Method in MIMO System

    Directory of Open Access Journals (Sweden)

    Chaowei Wang

    2013-01-01

    Full Text Available Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory requirement and achieves considerable system capacity gain compared with the optimal selection technique in the same time.

  20. Method selection for mercury removal from hard coal

    Directory of Open Access Journals (Sweden)

    Dziok Tadeusz

    2017-01-01

    Full Text Available Mercury is commonly found in coal and the coal utilization processes constitute one of the main sources of mercury emission to the environment. This issue is particularly important for Poland, because the Polish energy production sector is based on brown and hard coal. The forecasts show that this trend in energy production will continue in the coming years. At the time of the emission limits introduction, methods of reducing the mercury emission will have to be implemented in Poland. Mercury emission can be reduced as a result of using coal with a relatively low mercury content. In the case of the absence of such coals, the methods of mercury removal from coal can be implemented. The currently used and developing methods include the coal cleaning process (both the coal washing and the dry deshaling as well as the thermal pretreatment of coal (mild pyrolysis. The effectiveness of these methods various for different coals, which is caused by the diversity of coal origin, various characteristics of coal and, especially, by the various modes of mercury occurrence in coal. It should be mentioned that the coal cleaning process allows for the removal of mercury occurring in mineral matter, mainly in pyrite. The thermal pretreatment of coal allows for the removal of mercury occurring in organic matter as well as in the inorganic constituents characterized by a low temperature of mercury release. In this paper, the guidelines for the selection of mercury removal method from hard coal were presented. The guidelines were developed taking into consideration: the effectiveness of mercury removal from coal in the process of coal cleaning and thermal pretreatment, the synergy effect resulting from the combination of these processes, the direction of coal utilization as well as the influence of these processes on coal properties.

  1. Some selected quantitative methods of thermal image analysis in Matlab.

    Science.gov (United States)

    Koprowski, Robert

    2016-05-01

    The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  2. [The assessment of biological maturation for talent selection - which method can be used?].

    Science.gov (United States)

    Müller, L; Müller, E; Hildebrandt, C; Kapelari, K; Raschner, C

    2015-03-01

    The biological maturity status plays an important role in sports, since it influences the performance level and the talent selection in various types of sport. More mature athletes are favorably selected for regional and national squads. Therefore, the biological maturity status should be considered during the talent selection process. In this context, the relative age effect (RAE), which exists when the relative age quarter distribution of selected sports groups shows a biased distribution with an over-representation of athletes born in the first months after the specific cut-off-date for the competition categories, represents another problem in the talent development. From an ethical point of view, discrimination of young talented kids does exist: the relatively younger athletes have little to no chance of reaching the elite level, despite their talents and efforts. The causal mechanisms behind the RAE are still unclear and have to be assessed. In this context, the biological maturation seems to be a possible influential factor for the existence of a RAE in sport, which has to be examined. Several methods for estimating the biological maturity status exist; however, they are often expensive and not practicable. Consequently, the aim of the present study was to assess the concordance of a simple, yet accurate method of estimating biological maturation (prediction equation of age at peak height velocity, APHV) of Mirwald and co-workers, and the gold standard method of estimating skeletal age (SA, the x-ray of the left wrist). In total, 75 Austrian students (40♂, 35♀) aged 10 - 13 years, were examined. Thirty of the participants (17♂, 13♀) were students of a well-known Austrian ski boarding school, and 45 (23♂, 22♀) of a non-sportive secondary modern school of the same region. The participants included in the study had not experienced a rupture of the carpal bones of the left wrist. Parents and participants were informed of the study aims

  3. A Simple Analytical Method Using HPLC with Fluorescence Detection to Determine Selected Polycyclic Aromatic Compounds in Filter Samples

    International Nuclear Information System (INIS)

    Garcia, S.; Perez, R. M.

    2014-01-01

    A study on the comparison and evaluation of a miniaturized extraction method for the determination of selected PACs in sample filters is presented. The main objective was the optimization and development of simple, rapid and low cost methods, minimizing the use of extracting solvent volume. The work also includes a study on the intermediate precision. (Author)

  4. Comparison of selected methods of prediction of wine exports and imports

    Directory of Open Access Journals (Sweden)

    Radka Šperková

    2008-01-01

    Full Text Available For prediction of future events, there exist a number of methods usable in managerial practice. Decision on which of them should be used in a particular situation depends not only on the amount and quality of input information, but also on a subjective managerial judgement. Paper performs a practical application and consequent comparison of results of two selected methods, which are statistical method and deductive method. Both methods were used for predicting wine exports and imports in (from the Czech Republic. Prediction was done in 2003 and it related to the economic years 2003/2004, 2004/2005, 2005/2006, and 2006/2007, within which it was compared with the real values of the given indicators.Within the deductive methods there were characterized the most important factors of external environment including the most important influence according to authors’ opinion, which was the integration of the Czech Republic into the EU from 1st May, 2004. On the contrary, the statistical method of time-series analysis did not regard the integration, which is comes out of its principle. Statistics only calculates based on data from the past, and cannot incorporate the influence of irregular future conditions, just as the EU integration. Because of this the prediction based on deductive method was more optimistic and more precise in terms of its difference from real development in the given field.

  5. Selecting device for processing method of radioactive gaseous wastes

    International Nuclear Information System (INIS)

    Sasaki, Ryoichi; Komoda, Norihisa.

    1976-01-01

    Object: To extend the period of replacement of a filter for adsorbing radioactive material by discharging waste gas containing radioactive material produced from an atomic power equipment after treating it by a method selected on the basis of the results of measurement of wind direction. Structure: Exhaust gas containing radioactive material produced from atomic power equipment is discharged after it is treated by a method selected on the basis of the results of wind direction measurement. For Instance, in case of sea wind the waste gas passes through a route selected for this case and is discharged through the waste gas outlet. When the sea wind disappears (that is, when a land wind or calm sets in), the exhaust gas is switched to a route for the case other than that of the sea wind, so that it passes through a filter consisting of active carbon where the radioactive material is removed through adsorption. The waste gas now free from the radioactive material is discharged through the waste gas outlet. (Moriyama, K.)

  6. Identification of solid state fermentation degree with FT-NIR spectroscopy: Comparison of wavelength variable selection methods of CARS and SCARS

    Science.gov (United States)

    Jiang, Hui; Zhang, Hang; Chen, Quansheng; Mei, Congli; Liu, Guohai

    2015-10-01

    The use of wavelength variable selection before partial least squares discriminant analysis (PLS-DA) for qualitative identification of solid state fermentation degree by FT-NIR spectroscopy technique was investigated in this study. Two wavelength variable selection methods including competitive adaptive reweighted sampling (CARS) and stability competitive adaptive reweighted sampling (SCARS) were employed to select the important wavelengths. PLS-DA was applied to calibrate identified model using selected wavelength variables by CARS and SCARS for identification of solid state fermentation degree. Experimental results showed that the number of selected wavelength variables by CARS and SCARS were 58 and 47, respectively, from the 1557 original wavelength variables. Compared with the results of full-spectrum PLS-DA, the two wavelength variable selection methods both could enhance the performance of identified models. Meanwhile, compared with CARS-PLS-DA model, the SCARS-PLS-DA model achieved better results with the identification rate of 91.43% in the validation process. The overall results sufficiently demonstrate the PLS-DA model constructed using selected wavelength variables by a proper wavelength variable method can be more accurate identification of solid state fermentation degree.

  7. Comparative study of SVM methods combined with voxel selection for object category classification on fMRI data.

    Science.gov (United States)

    Song, Sutao; Zhan, Zhichao; Long, Zhiying; Zhang, Jiacai; Yao, Li

    2011-02-16

    Support vector machine (SVM) has been widely used as accurate and reliable method to decipher brain patterns from functional MRI (fMRI) data. Previous studies have not found a clear benefit for non-linear (polynomial kernel) SVM versus linear one. Here, a more effective non-linear SVM using radial basis function (RBF) kernel is compared with linear SVM. Different from traditional studies which focused either merely on the evaluation of different types of SVM or the voxel selection methods, we aimed to investigate the overall performance of linear and RBF SVM for fMRI classification together with voxel selection schemes on classification accuracy and time-consuming. Six different voxel selection methods were employed to decide which voxels of fMRI data would be included in SVM classifiers with linear and RBF kernels in classifying 4-category objects. Then the overall performances of voxel selection and classification methods were compared. Results showed that: (1) Voxel selection had an important impact on the classification accuracy of the classifiers: in a relative low dimensional feature space, RBF SVM outperformed linear SVM significantly; in a relative high dimensional space, linear SVM performed better than its counterpart; (2) Considering the classification accuracy and time-consuming holistically, linear SVM with relative more voxels as features and RBF SVM with small set of voxels (after PCA) could achieve the better accuracy and cost shorter time. The present work provides the first empirical result of linear and RBF SVM in classification of fMRI data, combined with voxel selection methods. Based on the findings, if only classification accuracy was concerned, RBF SVM with appropriate small voxels and linear SVM with relative more voxels were two suggested solutions; if users concerned more about the computational time, RBF SVM with relative small set of voxels when part of the principal components were kept as features was a better choice.

  8. Color selective photodetector and methods of making

    Science.gov (United States)

    Walker, Brian J.; Dorn, August; Bulovic, Vladimir; Bawendi, Moungi G.

    2013-03-19

    A photoelectric device, such as a photodetector, can include a semiconductor nanowire electrostatically associated with a J-aggregate. The J-aggregate can facilitate absorption of a desired wavelength of light, and the semiconductor nanowire can facilitate charge transport. The color of light detected by the device can be chosen by selecting a J-aggregate with a corresponding peak absorption wavelength.

  9. Method for Selection of Solvents for Promotion of Organic Reactions

    DEFF Research Database (Denmark)

    Gani, Rafiqul; Jiménez-González, Concepción; Constable, David J.C.

    2005-01-01

    is to produce, for a given reaction, a short list of chemicals that could be considered as potential solvents, to evaluate their performance in the reacting system, and, based on this, to rank them according to a scoring system. Several examples of application are given to illustrate the main features and steps......A method to select appropriate green solvents for the promotion of a class of organic reactions has been developed. The method combines knowledge from industrial practice and physical insights with computer-aided property estimation tools for selection/design of solvents. In particular, it employs...... estimates of thermodynamic properties to generate a knowledge base of reaction, solvent and environment related properties that directly or indirectly influence the rate and/or conversion of a given reaction. Solvents are selected using a rules-based procedure where the estimated reaction-solvent properties...

  10. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Method for hydrometallurgical recovery of selected metals

    International Nuclear Information System (INIS)

    Lorenz, G.; Schaefer, B.; Balzat, W.

    1988-01-01

    The method for hydrometallurgical recovery of selected metals refers to ore dressing by means of milling and alkaline leaching of metals, preferably uranium. By adding CaO during wet milling, Na + or K + ions of clayey ores are replaced by Ca 2+ ions. Due to the ion exchange processes, the uranium bonded with clays becomes more accessible to the leaching solution. The uranium yield increases and the consumption of reagents decreases

  12. The predictive validity of a situational judgement test, a clinical problem solving test and the core medical training selection methods for performance in specialty training .

    Science.gov (United States)

    Patterson, Fiona; Lopes, Safiatu; Harding, Stephen; Vaux, Emma; Berkin, Liz; Black, David

    2017-02-01

    The aim of this study was to follow up a sample of physicians who began core medical training (CMT) in 2009. This paper examines the long-term validity of CMT and GP selection methods in predicting performance in the Membership of Royal College of Physicians (MRCP(UK)) examinations. We performed a longitudinal study, examining the extent to which the GP and CMT selection methods (T1) predict performance in the MRCP(UK) examinations (T2). A total of 2,569 applicants from 2008-09 who completed CMT and GP selection methods were included in the study. Looking at MRCP(UK) part 1, part 2 written and PACES scores, both CMT and GP selection methods show evidence of predictive validity for the outcome variables, and hierarchical regressions show the GP methods add significant value to the CMT selection process. CMT selection methods predict performance in important outcomes and have good evidence of validity; the GP methods may have an additional role alongside the CMT selection methods. © Royal College of Physicians 2017. All rights reserved.

  13. International meeting 'Selected topics on nuclear methods for non-nuclear applications'. Proceedings

    International Nuclear Information System (INIS)

    Stoyanov, Ch.

    2007-01-01

    The volume includes the presentations given on the International Meeting 'Selected Topics on Nuclear Methods for Non-nuclear Applications'. The meeting was organized by the Project CECOA. The Project 'CEnter for COoerative Activities' (CECOA) of the Institute for Nuclear Research and Nuclear Energy (INRNE) of Bulgarian Academy of Sciences is part of the Program 'Creating of Infrastructure' of Bulgarian Ministry of Science and Education. The CECOA-project unifies the groups of INRNE doing research in the field of nuclear methods. Four Laboratories of INRNE are members of CECOA-project: Moessbauer Spectroscopy and Low Radioactivity Measurements, High-Resolution Gamma-Spectroscopy, Neutron Methods in Condensed Matter, Neutron Optics and Structure Analysis. Taking into account the leading role of education on nuclear physics the Project includes program devoted to the training on nuclear physics. The presented volume contains 23 contributed papers. The contributions are separated in 6 sections. The section 'Nano technology' includes 5 papers. The activity in this field within the Project reveals the collaboration with other Institutes of Bulgarian Academy of Sciences as well as large international contacts. The section 'Radioecology and Radioactive Waste' is two fold. Part of the contributions of the section manifests the connection of the CECOA with small enterprises. The contacts are on the level of common projects concerning the investigations, remediation and release of radioactively contaminated terrain, soils, water, buildings and materials around the former uranium processing industry. Another part of the section is devoted to the application of nuclear methods to the treatment of radioactive waste produced by nuclear power stations. The section 'Neutron Physics' reveals the activity within the Project connected with the study of new materials using polarized neutrons and neutron diffraction methods. The section 'Nuclear Physics' is an introduction to some

  14. Preparation of Iron Nanoparticles by Selective Leaching Method

    Czech Academy of Sciences Publication Activity Database

    Michalcová, A.; Vojtěch, D.; Kubatík, Tomáš František; Stehlíková, K.; Brabec, F.; Marek, I.

    2015-01-01

    Roč. 128, č. 4 (2015), s. 640-642 ISSN 0587-4246. [International Symposium on Physics of Materials (ISPMA) /13./. Prague, 31.08.2014-04.09.2014] Institutional support: RVO:61389021 Keywords : Iron nanoparticles * selective leaching method Subject RIV: JK - Corrosion ; Surface Treatment of Materials Impact factor: 0.525, year: 2015

  15. Selecting and Using Mathematics Methods Texts: Nontrivial Tasks

    Science.gov (United States)

    Harkness, Shelly Sheats; Brass, Amy

    2017-01-01

    Mathematics methods textbooks/texts are important components of many courses for preservice teachers. Researchers should explore how these texts are selected and used. Within this paper we report the findings of a survey administered electronically to 132 members of the Association of Mathematics Teacher Educators (AMTE) in order to answer the…

  16. Enhanced individual selection for selecting fast growing fish: the "PROSPER" method, with application on brown trout (Salmo trutta fario

    Directory of Open Access Journals (Sweden)

    Vandeputte Marc

    2004-11-01

    Full Text Available Abstract Growth rate is the main breeding goal of fish breeders, but individual selection has often shown poor responses in fish species. The PROSPER method was developed to overcome possible factors that may contribute to this low success, using (1 a variable base population and high number of breeders (Ne > 100, (2 selection within groups with low non-genetic effects and (3 repeated growth challenges. Using calculations, we show that individual selection within groups, with appropriate management of maternal effects, can be superior to mass selection as soon as the maternal effect ratio exceeds 0.15, when heritability is 0.25. Practically, brown trout were selected on length at the age of one year with the PROSPER method. The genetic gain was evaluated against an unselected control line. After four generations, the mean response per generation in length at one year was 6.2% of the control mean, while the mean correlated response in weight was 21.5% of the control mean per generation. At the 4th generation, selected fish also appeared to be leaner than control fish when compared at the same size, and the response on weight was maximal (≈130% of the control mean between 386 and 470 days post fertilisation. This high response is promising, however, the key points of the method have to be investigated in more detail.

  17. A comparison of statistical methods for genomic selection in a mice population

    Directory of Open Access Journals (Sweden)

    Neves Haroldo HR

    2012-11-01

    Full Text Available Abstract Background The availability of high-density panels of SNP markers has opened new perspectives for marker-assisted selection strategies, such that genotypes for these markers are used to predict the genetic merit of selection candidates. Because the number of markers is often much larger than the number of phenotypes, marker effect estimation is not a trivial task. The objective of this research was to compare the predictive performance of ten different statistical methods employed in genomic selection, by analyzing data from a heterogeneous stock mice population. Results For the five traits analyzed (W6W: weight at six weeks, WGS: growth slope, BL: body length, %CD8+: percentage of CD8+ cells, CD4+/ CD8+: ratio between CD4+ and CD8+ cells, within-family predictions were more accurate than across-family predictions, although this superiority in accuracy varied markedly across traits. For within-family prediction, two kernel methods, Reproducing Kernel Hilbert Spaces Regression (RKHS and Support Vector Regression (SVR, were the most accurate for W6W, while a polygenic model also had comparable performance. A form of ridge regression assuming that all markers contribute to the additive variance (RR_GBLUP figured among the most accurate for WGS and BL, while two variable selection methods ( LASSO and Random Forest, RF had the greatest predictive abilities for %CD8+ and CD4+/ CD8+. RF, RKHS, SVR and RR_GBLUP outperformed the remainder methods in terms of bias and inflation of predictions. Conclusions Methods with large conceptual differences reached very similar predictive abilities and a clear re-ranking of methods was observed in function of the trait analyzed. Variable selection methods were more accurate than the remainder in the case of %CD8+ and CD4+/CD8+ and these traits are likely to be influenced by a smaller number of QTL than the remainder. Judged by their overall performance across traits and computational requirements, RR

  18. A Comparison of Multidimensional Item Selection Methods in Simple and Complex Test Designs

    Directory of Open Access Journals (Sweden)

    Eren Halil ÖZBERK

    2017-03-01

    Full Text Available In contrast with the previous studies, this study employed various test designs (simple and complex which allow the evaluation of the overall ability score estimations across multiple real test conditions. In this study, four factors were manipulated, namely the test design, number of items per dimension, correlation between dimensions and item selection methods. Using the generated item and ability parameters, dichotomous item responses were generated in by using M3PL compensatory multidimensional IRT model with specified correlations. MCAT composite ability score accuracy was evaluated using absolute bias (ABSBIAS, correlation and the root mean square error (RMSE between true and estimated ability scores. The results suggest that the multidimensional test structure, number of item per dimension and correlation between dimensions had significant effect on item selection methods for the overall score estimations. For simple structure test design it was found that V1 item selection has the lowest absolute bias estimations for both long and short tests while estimating overall scores. As the model gets complex KL item selection method performed better than other two item selection method.

  19. Why Include Impacts on Biodiversity from Land Use in LCIA and How to Select Useful Indicators?

    Directory of Open Access Journals (Sweden)

    Ottar Michelsen

    2015-05-01

    Full Text Available Loss of biodiversity is one of the most severe threats to sustainability, and land use and land use changes are still the single most important factor. Still, there is no sign of any consensus on how to include impacts on biodiversity from land use and land use changes in LCIA. In this paper, different characteristics of biodiversity are discussed and related to proposals on how to include land use and land use changes in LCIA. We identify the question of why we should care about biodiversity as a key question, since different motivations will result in different choices for the indicators, and we call for more openness in the motivation for indicator selection. We find a promising trend in combining pressure indicators with geographic weighting and regard this as a promising way ahead. More knowledge on the consequences of different choices, such as the selection of a reference state, is still needed.

  20. A new screening method for selection of desired recombinant ...

    African Journals Online (AJOL)

    A new screening method for selection of desired recombinant plasmids in molecular cloning. ... African Journal of Biotechnology ... Regarding the facts of this study, after digestion process, the products directly were subjected to ligation. Due to ...

  1. The Hull Method for Selecting the Number of Common Factors

    Science.gov (United States)

    Lorenzo-Seva, Urbano; Timmerman, Marieke E.; Kiers, Henk A. L.

    2011-01-01

    A common problem in exploratory factor analysis is how many factors need to be extracted from a particular data set. We propose a new method for selecting the number of major common factors: the Hull method, which aims to find a model with an optimal balance between model fit and number of parameters. We examine the performance of the method in an…

  2. Orthogonal feature selection method. [For preprocessing of man spectral data

    Energy Technology Data Exchange (ETDEWEB)

    Kowalski, B R [Univ. of Washington, Seattle; Bender, C F

    1976-01-01

    A new method of preprocessing spectral data for extraction of molecular structural information is desired. This SELECT method generates orthogonal features that are important for classification purposes and that also retain their identity to the original measurements. A brief introduction to chemical pattern recognition is presented. A brief description of the method and an application to mass spectral data analysis follow. (BLM)

  3. TEHRAN AIR POLLUTANTS PREDICTION BASED ON RANDOM FOREST FEATURE SELECTION METHOD

    Directory of Open Access Journals (Sweden)

    A. Shamsoddini

    2017-09-01

    Full Text Available Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

  4. Tehran Air Pollutants Prediction Based on Random Forest Feature Selection Method

    Science.gov (United States)

    Shamsoddini, A.; Aboodi, M. R.; Karami, J.

    2017-09-01

    Air pollution as one of the most serious forms of environmental pollutions poses huge threat to human life. Air pollution leads to environmental instability, and has harmful and undesirable effects on the environment. Modern prediction methods of the pollutant concentration are able to improve decision making and provide appropriate solutions. This study examines the performance of the Random Forest feature selection in combination with multiple-linear regression and Multilayer Perceptron Artificial Neural Networks methods, in order to achieve an efficient model to estimate carbon monoxide and nitrogen dioxide, sulfur dioxide and PM2.5 contents in the air. The results indicated that Artificial Neural Networks fed by the attributes selected by Random Forest feature selection method performed more accurate than other models for the modeling of all pollutants. The estimation accuracy of sulfur dioxide emissions was lower than the other air contaminants whereas the nitrogen dioxide was predicted more accurate than the other pollutants.

  5. Force measuring valve assemblies, systems including such valve assemblies and related methods

    Science.gov (United States)

    DeWall, Kevin George [Pocatello, ID; Garcia, Humberto Enrique [Idaho Falls, ID; McKellar, Michael George [Idaho Falls, ID

    2012-04-17

    Methods of evaluating a fluid condition may include stroking a valve member and measuring a force acting on the valve member during the stroke. Methods of evaluating a fluid condition may include measuring a force acting on a valve member in the presence of fluid flow over a period of time and evaluating at least one of the frequency of changes in the measured force over the period of time and the magnitude of the changes in the measured force over the period of time to identify the presence of an anomaly in a fluid flow and, optionally, its estimated location. Methods of evaluating a valve condition may include directing a fluid flow through a valve while stroking a valve member, measuring a force acting on the valve member during the stroke, and comparing the measured force to a reference force. Valve assemblies and related systems are also disclosed.

  6. Systems and strippable coatings for decontaminating structures that include porous material

    Science.gov (United States)

    Fox, Robert V [Idaho Falls, ID; Avci, Recep [Bozeman, MT; Groenewold, Gary S [Idaho Falls, ID

    2011-12-06

    Methods of removing contaminant matter from porous materials include applying a polymer material to a contaminated surface, irradiating the contaminated surface to cause redistribution of contaminant matter, and removing at least a portion of the polymer material from the surface. Systems for decontaminating a contaminated structure comprising porous material include a radiation device configured to emit electromagnetic radiation toward a surface of a structure, and at least one spray device configured to apply a capture material onto the surface of the structure. Polymer materials that can be used in such methods and systems include polyphosphazine-based polymer materials having polyphosphazine backbone segments and side chain groups that include selected functional groups. The selected functional groups may include iminos, oximes, carboxylates, sulfonates, .beta.-diketones, phosphine sulfides, phosphates, phosphites, phosphonates, phosphinates, phosphine oxides, monothio phosphinic acids, and dithio phosphinic acids.

  7. New Hybrid Features Selection Method: A Case Study on Websites Phishing

    Directory of Open Access Journals (Sweden)

    Khairan D. Rajab

    2017-01-01

    Full Text Available Phishing is one of the serious web threats that involves mimicking authenticated websites to deceive users in order to obtain their financial information. Phishing has caused financial damage to the different online stakeholders. It is massive in the magnitude of hundreds of millions; hence it is essential to minimize this risk. Classifying websites into “phishy” and legitimate types is a primary task in data mining that security experts and decision makers are hoping to improve particularly with respect to the detection rate and reliability of the results. One way to ensure the reliability of the results and to enhance performance is to identify a set of related features early on so the data dimensionality reduces and irrelevant features are discarded. To increase reliability of preprocessing, this article proposes a new feature selection method that combines the scores of multiple known methods to minimize discrepancies in feature selection results. The proposed method has been applied to the problem of website phishing classification to show its pros and cons in identifying relevant features. Results against a security dataset reveal that the proposed preprocessing method was able to derive new features datasets which when mined generate high competitive classifiers with reference to detection rate when compared to results obtained from other features selection methods.

  8. An efficient heuristic method for dynamic portfolio selection problem under transaction costs and uncertain conditions

    Science.gov (United States)

    Najafi, Amir Abbas; Pourahmadi, Zahra

    2016-04-01

    Selecting the optimal combination of assets in a portfolio is one of the most important decisions in investment management. As investment is a long term concept, looking into a portfolio optimization problem just in a single period may cause loss of some opportunities that could be exploited in a long term view. Hence, it is tried to extend the problem from single to multi-period model. We include trading costs and uncertain conditions to this model which made it more realistic and complex. Hence, we propose an efficient heuristic method to tackle this problem. The efficiency of the method is examined and compared with the results of the rolling single-period optimization and the buy and hold method which shows the superiority of the proposed method.

  9. The effects of predictor method factors on selection outcomes: A modular approach to personnel selection procedures.

    Science.gov (United States)

    Lievens, Filip; Sackett, Paul R

    2017-01-01

    Past reviews and meta-analyses typically conceptualized and examined selection procedures as holistic entities. We draw on the product design literature to propose a modular approach as a complementary perspective to conceptualizing selection procedures. A modular approach means that a product is broken down into its key underlying components. Therefore, we start by presenting a modular framework that identifies the important measurement components of selection procedures. Next, we adopt this modular lens for reviewing the available evidence regarding each of these components in terms of affecting validity, subgroup differences, and applicant perceptions, as well as for identifying new research directions. As a complement to the historical focus on holistic selection procedures, we posit that the theoretical contributions of a modular approach include improved insight into the isolated workings of the different components underlying selection procedures and greater theoretical connectivity among different selection procedures and their literatures. We also outline how organizations can put a modular approach into operation to increase the variety in selection procedures and to enhance the flexibility in designing them. Overall, we believe that a modular perspective on selection procedures will provide the impetus for programmatic and theory-driven research on the different measurement components of selection procedures. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  10. A Feature Subset Selection Method Based On High-Dimensional Mutual Information

    Directory of Open Access Journals (Sweden)

    Chee Keong Kwoh

    2011-04-01

    Full Text Available Feature selection is an important step in building accurate classifiers and provides better understanding of the data sets. In this paper, we propose a feature subset selection method based on high-dimensional mutual information. We also propose to use the entropy of the class attribute as a criterion to determine the appropriate subset of features when building classifiers. We prove that if the mutual information between a feature set X and the class attribute Y equals to the entropy of Y , then X is a Markov Blanket of Y . We show that in some cases, it is infeasible to approximate the high-dimensional mutual information with algebraic combinations of pairwise mutual information in any forms. In addition, the exhaustive searches of all combinations of features are prerequisite for finding the optimal feature subsets for classifying these kinds of data sets. We show that our approach outperforms existing filter feature subset selection methods for most of the 24 selected benchmark data sets.

  11. A fractured rock geophysical toolbox method selection tool

    Science.gov (United States)

    Day-Lewis, F. D.; Johnson, C.D.; Slater, L.D.; Robinson, J.L.; Williams, J.H.; Boyden, C.L.; Werkema, D.D.; Lane, J.W.

    2016-01-01

    Geophysical technologies have the potential to improve site characterization and monitoring in fractured rock, but the appropriate and effective application of geophysics at a particular site strongly depends on project goals (e.g., identifying discrete fractures) and site characteristics (e.g., lithology). No method works at every site or for every goal. New approaches are needed to identify a set of geophysical methods appropriate to specific project goals and site conditions while considering budget constraints. To this end, we present the Excel-based Fractured-Rock Geophysical Toolbox Method Selection Tool (FRGT-MST). We envision the FRGT-MST (1) equipping remediation professionals with a tool to understand what is likely to be realistic and cost-effective when contracting geophysical services, and (2) reducing applications of geophysics with unrealistic objectives or where methods are likely to fail.

  12. Investigation of the paired-gear method in selectivity studies

    DEFF Research Database (Denmark)

    Sistiaga, Manu; Herrmann, Bent; Larsen, R.B.

    2009-01-01

    was repeated throughout the eight cases in this investigation. When using the paired-gear method, the distribution of the estimated L50 and SR is wider; the distribution of the estimated split parameter has a higher variability than the true split; the estimated mean L50 and SR can be biased; the estimated...... recommend that the methodology used to obtain selectivity estimates using the paired-gear method be reviewed....

  13. Methods of selection and training of personnel for the Rajasthan atomic power station

    International Nuclear Information System (INIS)

    Sarma, M.S.R.; Wagadarikar, V.K.

    1975-01-01

    Personnel selected to work in a nuclear electric generating station rarely have the necessary knowledge and experience in all the related fields. A station can be operated and maintained and at the same time radiation doses absorbed by station personnel can be kept to a minimum only if the operating personnel are familiar with, and can be used for, all phases of station operation and the maintainers have more than one skill or trade. More technical knowledge and more diversified skills, in addition to those required in other industries, are needed because of the nature of the nuclear reactor and the associated radiation environment and high automation. A training programme has been developed at the Nuclear Training Centre (NTC) near the Rajasthan Atomic Power Station (RAPS), Kota, India, to cater to the needs of the operation and maintenance personnel for nuclear power stations including the Madras Atomic Power Station. This programme has been in operation for the last five years. The paper describes the method of recruitment/selection of various categories of personnel and the method of training them to meet the job requirements. (author)

  14. Method selection for sustainability assessments: The case of recovery of resources from waste water.

    Science.gov (United States)

    Zijp, M C; Waaijers-van der Loop, S L; Heijungs, R; Broeren, M L M; Peeters, R; Van Nieuwenhuijzen, A; Shen, L; Heugens, E H W; Posthuma, L

    2017-07-15

    Sustainability assessments provide scientific support in decision procedures towards sustainable solutions. However, in order to contribute in identifying and choosing sustainable solutions, the sustainability assessment has to fit the decision context. Two complicating factors exist. First, different stakeholders tend to have different views on what a sustainability assessment should encompass. Second, a plethora of sustainability assessment methods exist, due to the multi-dimensional characteristic of the concept. Different methods provide other representations of sustainability. Based on a literature review, we present a protocol to facilitate method selection together with stakeholders. The protocol guides the exploration of i) the decision context, ii) the different views of stakeholders and iii) the selection of pertinent assessment methods. In addition, we present an online tool for method selection. This tool identifies assessment methods that meet the specifications obtained with the protocol, and currently contains characteristics of 30 sustainability assessment methods. The utility of the protocol and the tool are tested in a case study on the recovery of resources from domestic waste water. In several iterations, a combination of methods was selected, followed by execution of the selected sustainability assessment methods. The assessment results can be used in the first phase of the decision procedure that leads to a strategic choice for sustainable resource recovery from waste water in the Netherlands. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. A Feature Selection Method for Large-Scale Network Traffic Classification Based on Spark

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2016-02-01

    Full Text Available Currently, with the rapid increasing of data scales in network traffic classifications, how to select traffic features efficiently is becoming a big challenge. Although a number of traditional feature selection methods using the Hadoop-MapReduce framework have been proposed, the execution time was still unsatisfactory with numeral iterative computations during the processing. To address this issue, an efficient feature selection method for network traffic based on a new parallel computing framework called Spark is proposed in this paper. In our approach, the complete feature set is firstly preprocessed based on Fisher score, and a sequential forward search strategy is employed for subsets. The optimal feature subset is then selected using the continuous iterations of the Spark computing framework. The implementation demonstrates that, on the precondition of keeping the classification accuracy, our method reduces the time cost of modeling and classification, and improves the execution efficiency of feature selection significantly.

  16. Material selection for the tool holder working under hard milling conditions using different multi criteria decision making methods

    International Nuclear Information System (INIS)

    Çalışkan, Halil; Kurşuncu, Bilal; Kurbanoğlu, Cahit; Güven, Şevki Yılmaz

    2013-01-01

    Highlights: ► The material selection problem for tool holders used in hard milling was solved. ► EXPROM2, TOPSIS and VIKOR methods were used for ranking the alternative materials. ► The weighting of criteria was performed by compromised weighting method. ► The best material for the tool holder was selected as Fe–5Cr–Mo–V aircraft steel. -- Abstract: Nowadays machining of materials in their hardened state, also called hard machining, is a challenge in production of tools and molds. It has some advantages such as lower process time and lower manufacturing cost when compared to conventional machining. In machining of hard workpiece materials, however, very high stresses act on the tool holder through the cutting tool. These stresses necessitate the tool holder to have some specific properties. Especially in hard milling, the tool holder should have high stiffness and should be able to dissipate the energy generated during interrupted cutting. Material cost of the tool holder is also important since lower costs provide a competitive advantage for manufacturers. The material selection for the tool holder should be conducted considering aforementioned requirements. To tackle the difficulty of the material selection with specific properties from a large number of alternatives, multi-criteria decision-making (MCDM) methods have been used. In this paper a decision model including extended PROMETHEE II (EXPROM2) (preference ranking organization method for enrichment evaluation), TOPSIS (technique for order performance by similarity to ideal solution) and VIKOR (VIšekriterijumsko KOmpromisno Rangiranje) methods were used for the selection of the best material for the tool holder used in hard milling. The criteria weighting was performed by compromised weighting method composed of AHP (analytic hierarchy process) and Entropy methods. The candidate materials were ranked by using these methods and the results obtained by each method were compared. It was confirmed

  17. AN APPLICATION OF FUZZY PROMETHEE METHOD FOR SELECTING OPTIMAL CAR PROBLEM

    Directory of Open Access Journals (Sweden)

    SERKAN BALLI

    2013-06-01

    Full Text Available Most of the economical, industrial, financial or political decision problems are multi-criteria. In these multi criteria problems, optimal selection of alternatives is hard and complex process. Recently, some kinds of methods are improved to solve these problems. Promethee is one of most efficient and easiest method and solves problems that consist quantitative criteria.  However, in daily life, there are criteria which are explained as linguistic and cannot modeled numerical. Hence, Promethee method is incomplete for linguistic criteria which are imprecise. To satisfy this deficiency, fuzzy set approximation can be used. Promethee method, which is extended with using fuzzy inputs, is applied to car selection for seven different cars in same class by using criteria: price, fuel, performance and security. The obtained results are appropriate and consistent.

  18. Sensor Selection method for IoT systems – focusing on embedded system requirements

    Directory of Open Access Journals (Sweden)

    Hirayama Masayuki

    2016-01-01

    Full Text Available Recently, various types of sensors have been developed. Using these sensors, IoT systems have become hot topics in embedded system domain. However, sensor selections for embedded systems are not well discussed up to now. This paper focuses on embedded system’s features and architecture, and proposes a sensor selection method which is composed seven steps. In addition, we applied the proposed method to a simple example – a sensor selection for computer scored answer sheet reader unit. From this case study, an idea to use FTA in sensor selection is also discussed.

  19. Composite materials and bodies including silicon carbide and titanium diboride and methods of forming same

    Science.gov (United States)

    Lillo, Thomas M.; Chu, Henry S.; Harrison, William M.; Bailey, Derek

    2013-01-22

    Methods of forming composite materials include coating particles of titanium dioxide with a substance including boron (e.g., boron carbide) and a substance including carbon, and reacting the titanium dioxide with the substance including boron and the substance including carbon to form titanium diboride. The methods may be used to form ceramic composite bodies and materials, such as, for example, a ceramic composite body or material including silicon carbide and titanium diboride. Such bodies and materials may be used as armor bodies and armor materials. Such methods may include forming a green body and sintering the green body to a desirable final density. Green bodies formed in accordance with such methods may include particles comprising titanium dioxide and a coating at least partially covering exterior surfaces thereof, the coating comprising a substance including boron (e.g., boron carbide) and a substance including carbon.

  20. A Fourier transform method for the selection of a smoothing interval

    International Nuclear Information System (INIS)

    Kekre, H.B.; Madan, V.K.; Bairi, B.R.

    1989-01-01

    A novel method for the selection of a smoothing interval for the widely used Savitzky and Golay's smoothing filter is proposed. Complementary bandwidths for the nuclear spectral data and the smoothing filter are defined. The criterion for the selection of smoothing interval is based on matching the bandwidths of the spectral data to the filter. Using the above method five real observed spectral peaks of different full width at half maximum, viz. 23.5, 19.5, 17, 8.5 and 6.5 channels, were smoothed and the results are presented. (orig.)

  1. Initiation devices, initiation systems including initiation devices and related methods

    Energy Technology Data Exchange (ETDEWEB)

    Daniels, Michael A.; Condit, Reston A.; Rasmussen, Nikki; Wallace, Ronald S.

    2018-04-10

    Initiation devices may include at least one substrate, an initiation element positioned on a first side of the at least one substrate, and a spark gap electrically coupled to the initiation element and positioned on a second side of the at least one substrate. Initiation devices may include a plurality of substrates where at least one substrate of the plurality of substrates is electrically connected to at least one adjacent substrate of the plurality of substrates with at least one via extending through the at least one substrate. Initiation systems may include such initiation devices. Methods of igniting energetic materials include passing a current through a spark gap formed on at least one substrate of the initiation device, passing the current through at least one via formed through the at least one substrate, and passing the current through an explosive bridge wire of the initiation device.

  2. Is preimplantation genetic diagnosis the ideal embryo selection method in aneuploidy screening?

    Directory of Open Access Journals (Sweden)

    Levent Sahin

    2014-10-01

    Full Text Available To select cytogenetically normal embryos, preimplantation genetic diagnosis (PGD aneuploidy screening (AS is used in numerous centers around the world. Chromosomal abnormalities lead to developmental problems, implantation failure, and early abortion of embryos. The usefulness of PGD in identifying single-gene diseases, human leukocyte antigen typing, X-linked diseases, and specific genetic diseases is well-known. In this review, preimplantation embryo genetics, PGD research studies, and the European Society of Human Reproduction and Embryology PGD Consortium studies and reports are examined. In addition, criteria for embryo selection, technical aspects of PGD-AS, and potential noninvasive embryo selection methods are described. Indications for PGD and possible causes of discordant PGD results between the centers are discussed. The limitations of fluorescence in situ hybridization, and the advantages of the array comparative genomic hybridization are included in this review. Although PGD-AS for patients of advanced maternal age has been shown to improve in vitro fertilization outcomes in some studies, to our knowledge, there is not sufficient evidence to use advanced maternal age as the sole indication for PGD-AS. PGD-AS might be harmful and may not increase the success rates of in vitro fertilization. At the same time PGD, is not recommended for recurrent implantation failure and unexplained recurrent pregnancy loss.

  3. Effect of cooking methods on the micronutrient profile of selected ...

    African Journals Online (AJOL)

    Effect of cooking methods on the micronutrient profile of selected vegetables: okra fruit ( Abelmoshcus esculentus ), fluted pumpkin ( Telfairia occidentalis ), African spinach ( Amarantus viridis ), and scent leaf ( Ocumum gratissimum.

  4. On a selection method of imaging condition in scintigraphy

    International Nuclear Information System (INIS)

    Ikeda, Hozumi; Kishimoto, Kenji; Shimonishi, Yoshihiro; Ohmura, Masahiro; Kosakai, Kazuhisa; Ochi, Hironobu

    1992-01-01

    Selection of imaging condition in scintigraphy was evaluated using analytic hierarchy process. First, a method of the selection was led by determining at the points of image quantity and imaging time. Influence of image quality was thought to depend on changes of system resolution, count density, image size, and image density. Also influence of imaging time was thought to depend on changes of system sensitivity and data acquisition time. Phantom study was done for paired comparison of these selection factors, and relations of sample data and the factors, that is Rollo phantom images were taken by changing count density, image size, and image density. Image quality was shown by calculating the score of visual evaluation that done by comparing of a pair of images in clearer cold lesion on the scintigrams. Imaging time was shown by relative values for changes of count density. However, system resolution and system sensitivity were constant in this study. Next, using these values analytic hierarchy process was adapted for this selection of imaging conditions. We conclude that this selection of imaging conditions can be analyzed quantitatively using analytic hierarchy process and this analysis develops theoretical consideration of imaging technique. (author)

  5. Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration

    Directory of Open Access Journals (Sweden)

    Haitao Chang

    2016-06-01

    Full Text Available One of the essential factors influencing the prediction accuracy of multivariate calibration models is the quality of the calibration data. A local regression strategy, together with a wavelength selection approach, is proposed to build the multivariate calibration models based on partial least squares regression. The local algorithm is applied to create a calibration set of spectra similar to the spectrum of an unknown sample; the synthetic degree of grey relation coefficient is used to evaluate the similarity. A wavelength selection method based on simple-to-use interactive self-modeling mixture analysis minimizes the influence of noisy variables, and the most informative variables of the most similar samples are selected to build the multivariate calibration model based on partial least squares regression. To validate the performance of the proposed method, ultraviolet-visible absorbance spectra of mixed solutions of food coloring analytes in a concentration range of 20–200 µg/mL is measured. Experimental results show that the proposed method can not only enhance the prediction accuracy of the calibration model, but also greatly reduce its complexity.

  6. Evolutionary dynamics on graphs: Efficient method for weak selection

    Science.gov (United States)

    Fu, Feng; Wang, Long; Nowak, Martin A.; Hauert, Christoph

    2009-04-01

    Investigating the evolutionary dynamics of game theoretical interactions in populations where individuals are arranged on a graph can be challenging in terms of computation time. Here, we propose an efficient method to study any type of game on arbitrary graph structures for weak selection. In this limit, evolutionary game dynamics represents a first-order correction to neutral evolution. Spatial correlations can be empirically determined under neutral evolution and provide the basis for formulating the game dynamics as a discrete Markov process by incorporating a detailed description of the microscopic dynamics based on the neutral correlations. This framework is then applied to one of the most intriguing questions in evolutionary biology: the evolution of cooperation. We demonstrate that the degree heterogeneity of a graph impedes cooperation and that the success of tit for tat depends not only on the number of rounds but also on the degree of the graph. Moreover, considering the mutation-selection equilibrium shows that the symmetry of the stationary distribution of states under weak selection is skewed in favor of defectors for larger selection strengths. In particular, degree heterogeneity—a prominent feature of scale-free networks—generally results in a more pronounced increase in the critical benefit-to-cost ratio required for evolution to favor cooperation as compared to regular graphs. This conclusion is corroborated by an analysis of the effects of population structures on the fixation probabilities of strategies in general 2×2 games for different types of graphs. Computer simulations confirm the predictive power of our method and illustrate the improved accuracy as compared to previous studies.

  7. Selective, electrochemical etching of a semiconductor

    Science.gov (United States)

    Dahal, Rajendra P.; Bhat, Ishwara B.; Chow, Tat-Sing

    2018-03-20

    Methods for facilitating fabricating semiconductor structures are provided which include: providing a multilayer structure including a semiconductor layer, the semiconductor layer including a dopant and having an increased conductivity; selectively increasing, using electrochemical processing, porosity of the semiconductor layer, at least in part, the selectively increasing porosity utilizing the increased conductivity of the semiconductor layer; and removing, at least in part, the semiconductor layer with the selectively increased porosity from the multilayer structure. By way of example, the selectively increasing porosity may include selectively, anodically oxidizing, at least in part, the semiconductor layer of the multilayer structure.

  8. A novel relational regularization feature selection method for joint regression and classification in AD diagnosis.

    Science.gov (United States)

    Zhu, Xiaofeng; Suk, Heung-Il; Wang, Li; Lee, Seong-Whan; Shen, Dinggang

    2017-05-01

    In this paper, we focus on joint regression and classification for Alzheimer's disease diagnosis and propose a new feature selection method by embedding the relational information inherent in the observations into a sparse multi-task learning framework. Specifically, the relational information includes three kinds of relationships (such as feature-feature relation, response-response relation, and sample-sample relation), for preserving three kinds of the similarity, such as for the features, the response variables, and the samples, respectively. To conduct feature selection, we first formulate the objective function by imposing these three relational characteristics along with an ℓ 2,1 -norm regularization term, and further propose a computationally efficient algorithm to optimize the proposed objective function. With the dimension-reduced data, we train two support vector regression models to predict the clinical scores of ADAS-Cog and MMSE, respectively, and also a support vector classification model to determine the clinical label. We conducted extensive experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to validate the effectiveness of the proposed method. Our experimental results showed the efficacy of the proposed method in enhancing the performances of both clinical scores prediction and disease status identification, compared to the state-of-the-art methods. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Multi criteria decision making methods for location selection of distribution centers

    Directory of Open Access Journals (Sweden)

    Romita Chakraborty

    2013-10-01

    Full Text Available In recent years, major challenges such as, increase in inflexible consumer demands and to improve the competitive advantage, it has become necessary for various industrial organizations all over the world to focus on strategies that will help them achieve cost reduction, continual quality improvement, increased customer satisfaction and on time delivery performance. As a result, selection of the most suitable and optimal facility location for a new organization or expansion of an existing location is one of the most important strategic issues, required to fulfill all of these above mentioned objectives. In order to sustain in the global competitive market of 21st century, many industrial organizations have begun to concentrate on the proper selection of the plant site or best facility location. The best location is that which results in higher economic benefits through increased productivity and good distribution network. When a choice is to be made from among several alternative facility locations, it is necessary to compare their performance characteristics in a decisive way. As the facility location selection problem involves multiple conflicting criteria and a finite set of potential candidate alternatives, different multi-criteria decision-making (MCDM methods can be effectively applied to solve such type of problem. In this paper, four well known MCDM methods have been applied on a facility location selection problem and their relative ranking performances are compared. Because of disagreement in the ranks obtained by the four different MCDM methods a final ranking method based on REGIME has been proposed by the authors to facilitate the decision making process.

  10. Assessment of different quit smoking methods selected by patients in tobacco cessation centers in Iran

    Directory of Open Access Journals (Sweden)

    Gholamreza Heydari

    2015-01-01

    Full Text Available Background: Health systems play key roles in identifying tobacco users and providing evidence-based care to help them quit. This treatment includes different methods such as simple medical consultation, medication, and telephone counseling. To assess different quit smoking methods selected by patients in tobacco cessation centers in Iran in order to identify those that are most appropriate for the country health system. Methods: In this cross-sectional and descriptive study, a random sample of all quit centers at the country level was used to obtain a representative sample. Patients completed the self-administered questionnaire which contained 10 questions regarding the quality, cost, effect, side effects and the results of quitting methods using a 5-point Likert-type scale. Percentages, frequencies, mean, T-test, and variance analyses were computed for all study variables. Results: A total of 1063 smokers returned completed survey questionnaires. The most frequently used methods were Nicotine Replacement Therapy (NRT and combination therapy (NRT and Counseling with 228 and 163 individuals reporting these respectively. The least used methods were hypnotism (n = 8 and the quit and win (n = 17. The methods which gained the maximum scores were respectively the combined method, personal and Champix with means of 21.4, 20.4 and 18.4. The minimum scores were for e-cigarettes, hypnotism and education with means of 12.8, 11 and 10.8, respectively. There were significant differences in mean scores based on different cities and different methods. Conclusions: According to smokers′ selection the combined therapy, personal methods and Champix are the most effective methods for quit smoking and these methods could be much more considered in the country health system.

  11. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang

    2017-02-16

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  12. Efficient nonparametric and asymptotic Bayesian model selection methods for attributed graph clustering

    KAUST Repository

    Xu, Zhiqiang; Cheng, James; Xiao, Xiaokui; Fujimaki, Ryohei; Muraoka, Yusuke

    2017-01-01

    Attributed graph clustering, also known as community detection on attributed graphs, attracts much interests recently due to the ubiquity of attributed graphs in real life. Many existing algorithms have been proposed for this problem, which are either distance based or model based. However, model selection in attributed graph clustering has not been well addressed, that is, most existing algorithms assume the cluster number to be known a priori. In this paper, we propose two efficient approaches for attributed graph clustering with automatic model selection. The first approach is a popular Bayesian nonparametric method, while the second approach is an asymptotic method based on a recently proposed model selection criterion, factorized information criterion. Experimental results on both synthetic and real datasets demonstrate that our approaches for attributed graph clustering with automatic model selection significantly outperform the state-of-the-art algorithm.

  13. Fuzzy decision-making: a new method in model selection via various validity criteria

    International Nuclear Information System (INIS)

    Shakouri Ganjavi, H.; Nikravesh, K.

    2001-01-01

    Modeling is considered as the first step in scientific investigations. Several alternative models may be candida ted to express a phenomenon. Scientists use various criteria to select one model between the competing models. Based on the solution of a Fuzzy Decision-Making problem, this paper proposes a new method in model selection. The method enables the scientist to apply all desired validity criteria, systematically by defining a proper Possibility Distribution Function due to each criterion. Finally, minimization of a utility function composed of the Possibility Distribution Functions will determine the best selection. The method is illustrated through a modeling example for the A verage Daily Time Duration of Electrical Energy Consumption in Iran

  14. Sustainable Supplier Performance Evaluation and Selection with Neofuzzy TOPSIS Method.

    Science.gov (United States)

    Chaharsooghi, S K; Ashrafi, Mehdi

    2014-01-01

    Supplier selection plays an important role in the supply chain management and traditional criteria such as price, quality, and flexibility are considered for supplier performance evaluation in researches. In recent years sustainability has received more attention in the supply chain management literature with triple bottom line (TBL) describing the sustainability in supply chain management with social, environmental, and economic initiatives. This paper explores sustainability in supply chain management and examines the problem of identifying a new model for supplier selection based on extended model of TBL approach in supply chain by presenting fuzzy multicriteria method. Linguistic values of experts' subjective preferences are expressed with fuzzy numbers and Neofuzzy TOPSIS is proposed for finding the best solution of supplier selection problem. Numerical results show that the proposed model is efficient for integrating sustainability in supplier selection problem. The importance of using complimentary aspects of sustainability and Neofuzzy TOPSIS concept in sustainable supplier selection process is shown with sensitivity analysis.

  15. Logging costs and production rates for the group selection cutting method

    Science.gov (United States)

    Philip M. McDonald

    1965-01-01

    Young-growth, mixed-conifer stands were logged by a group-selection method designed to create openings 30, 60, and 90 feet in diameter. Total costs for felling, limbing, bucking, and skidding on these openings ranged from $7.04 to $7.99 per thousand board feet. Cost differences between openings were not statistically significant. Logging costs for group selection...

  16. An active learning representative subset selection method using net analyte signal

    Science.gov (United States)

    He, Zhonghai; Ma, Zhenhe; Luan, Jingmin; Cai, Xi

    2018-05-01

    To guarantee accurate predictions, representative samples are needed when building a calibration model for spectroscopic measurements. However, in general, it is not known whether a sample is representative prior to measuring its concentration, which is both time-consuming and expensive. In this paper, a method to determine whether a sample should be selected into a calibration set is presented. The selection is based on the difference of Euclidean norm of net analyte signal (NAS) vector between the candidate and existing samples. First, the concentrations and spectra of a group of samples are used to compute the projection matrix, NAS vector, and scalar values. Next, the NAS vectors of candidate samples are computed by multiplying projection matrix with spectra of samples. Scalar value of NAS is obtained by norm computation. The distance between the candidate set and the selected set is computed, and samples with the largest distance are added to selected set sequentially. Last, the concentration of the analyte is measured such that the sample can be used as a calibration sample. Using a validation test, it is shown that the presented method is more efficient than random selection. As a result, the amount of time and money spent on reference measurements is greatly reduced.

  17. A novel technique for including surface tension in PLIC-VOF methods

    Energy Technology Data Exchange (ETDEWEB)

    Meier, M.; Yadigaroglu, G. [Swiss Federal Institute of Technology, Nuclear Engineering Lab. ETH-Zentrum, CLT, Zurich (Switzerland); Smith, B. [Paul Scherrer Inst. (PSI), Villigen (Switzerland). Lab. for Thermal-Hydraulics

    2002-02-01

    Various versions of Volume-of-Fluid (VOF) methods have been used successfully for the numerical simulation of gas-liquid flows with an explicit tracking of the phase interface. Of these, Piecewise-Linear Interface Construction (PLIC-VOF) appears as a fairly accurate, although somewhat more involved variant. Including effects due to surface tension remains a problem, however. The most prominent methods, Continuum Surface Force (CSF) of Brackbill et al. and the method of Zaleski and co-workers (both referenced later), both induce spurious or 'parasitic' currents, and only moderate accuracy in regards to determining the curvature. We present here a new method to determine curvature accurately using an estimator function, which is tuned with a least-squares-fit against reference data. Furthermore, we show how spurious currents may be drastically reduced using the reconstructed interfaces from the PLIC-VOF method. (authors)

  18. Optical wavelength selection for portable hemoglobin determination by near-infrared spectroscopy method

    Science.gov (United States)

    Tian, Han; Li, Ming; Wang, Yue; Sheng, Dinggao; Liu, Jun; Zhang, Linna

    2017-11-01

    Hemoglobin concentration is commonly used in clinical medicine to diagnose anemia, identify bleeding, and manage red blood cell transfusions. The golden standard method for determining hemoglobin concentration in blood requires reagent. Spectral methods were advantageous at fast and non-reagent measurement. However, model calibration with full spectrum is time-consuming. Moreover, it is necessary to use a few variables considering size and cost of instrumentation, especially for a portable biomedical instrument. This study presents different wavelength selection methods for optical wavelengths for total hemoglobin concentration determination in whole blood. The results showed that modelling using only two wavelengths combination (1143 nm, 1298 nm) can keep on the fine predictability with full spectrum. It appears that the proper selection of optical wavelengths can be more effective than using the whole spectra for determination hemoglobin in whole blood. We also discussed the influence of water absorptivity on the wavelength selection. This research provides valuable references for designing portable NIR instruments determining hemoglobin concentration, and may provide some experience for noninvasive hemoglobin measurement by NIR methods.

  19. Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

    International Nuclear Information System (INIS)

    Wang Xiaojia; Mao Qirong; Zhan Yongzhao

    2008-01-01

    There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions. The experiments show that this method can improve the recognition rate and the time of feature extraction

  20. A Selective Review of Multimodal Fusion Methods in Schizophrenia

    Directory of Open Access Journals (Sweden)

    Jing eSui

    2012-02-01

    Full Text Available Schizophrenia (SZ is one of the most cryptic and costly mental disorders in terms of human suffering and societal expenditure (van Os and Kapur, 2009. Though strong evidences for functional, structural and genetic abnormalities associated with this disease exist, there is yet no replicable finding which has proven accurate enough to be useful in clinical decision making (Fornito et al., 2009, and its diagnosis relies primarily upon symptom assessment (Williams et al., 2010a. It is likely in part that the lack of consistent neuroimaging findings is because most models favor only one data type or do not combine data from different imaging modalities effectively, thus missing potentially important differences which are only partially detected by each modality (Calhoun et al., 2006a. It is becoming increasingly clear that multi-modal fusion, a technique which takes advantage of the fact that each modality provides a limited view of the brain/gene and may uncover hidden relationships, is an important tool to help unravel the black box of schizophrenia. In this review paper, we survey a number of multimodal fusion applications which enable us to study the schizophrenia macro-connectome, including brain functional, structural and genetic aspects and may help us understand the disorder in a more comprehensive and integrated manner. We also provide a table that characterizes these applications by the methods used and compare these methods in detail, especially for multivariate models, which may serve as a valuable reference that helps readers select an appropriate method based on a given research.

  1. Objective Versus Subjective Military Pilot Selection Methods in the United States of America

    Science.gov (United States)

    2015-12-14

    a computerized test designed to assess pilot skills by measuring spatial orientation and psychomotor skills and multitasking . The second is the...AFRL-SA-WP-SR-2015-0028 Objective Versus Subjective Military Pilot Selection Methods in the United States of America Joe...September 2014 4. TITLE AND SUBTITLE Objective Versus Subjective Military Pilot Selection Methods in the United States of America 5a. CONTRACT

  2. An Integrated DEMATEL-VIKOR Method-Based Approach for Cotton Fibre Selection and Evaluation

    Science.gov (United States)

    Chakraborty, Shankar; Chatterjee, Prasenjit; Prasad, Kanika

    2018-01-01

    Selection of the most appropriate cotton fibre type for yarn manufacturing is often treated as a multi-criteria decision-making (MCDM) problem as the optimal selection decision needs to be taken in presence of several conflicting fibre properties. In this paper, two popular MCDM methods in the form of decision making trial and evaluation laboratory (DEMATEL) and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR) are integrated to aid the cotton fibre selection decision. DEMATEL method addresses the interrelationships between various physical properties of cotton fibres while segregating them into cause and effect groups, whereas, VIKOR method helps in ranking all the considered 17 cotton fibres from the best to the worst. The derived ranking of cotton fibre alternatives closely matches with that obtained by the past researchers. This model can assist the spinning industry personnel in the blending process while making accurate fibre selection decision when cotton fibre properties are numerous and interrelated.

  3. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System.

    Science.gov (United States)

    Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

    2015-01-01

    The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

  4. [Analysis on the accuracy of simple selection method of Fengshi (GB 31)].

    Science.gov (United States)

    Li, Zhixing; Zhang, Haihua; Li, Suhe

    2015-12-01

    To explore the accuracy of simple selection method of Fengshi (GB 31). Through the study of the ancient and modern data,the analysis and integration of the acupuncture books,the comparison of the locations of Fengshi (GB 31) by doctors from all dynasties and the integration of modern anatomia, the modern simple selection method of Fengshi (GB 31) is definite, which is the same as the traditional way. It is believed that the simple selec tion method is in accord with the human-oriented thought of TCM. Treatment by acupoints should be based on the emerging nature and the individual difference of patients. Also, it is proposed that Fengshi (GB 31) should be located through the integration between the simple method and body surface anatomical mark.

  5. Validity of a structured method of selecting abstracts for a plastic surgical scientific meeting

    NARCIS (Netherlands)

    van der Steen, LPE; Hage, JJ; Kon, M; Monstrey, SJ

    In 1999, the European Association of Plastic Surgeons accepted a structured method to assess and select the abstracts that are submitted for its yearly scientific meeting. The two criteria used to evaluate whether such a selection method is accurate were reliability and validity. The authors

  6. A frequency domain linearized Navier-Stokes method including acoustic damping by eddy viscosity using RANS

    Science.gov (United States)

    Holmberg, Andreas; Kierkegaard, Axel; Weng, Chenyang

    2015-06-01

    In this paper, a method for including damping of acoustic energy in regions of strong turbulence is derived for a linearized Navier-Stokes method in the frequency domain. The proposed method is validated and analyzed in 2D only, although the formulation is fully presented in 3D. The result is applied in a study of the linear interaction between the acoustic and the hydrodynamic field in a 2D T-junction, subject to grazing flow at Mach 0.1. Part of the acoustic energy at the upstream edge of the junction is shed as harmonically oscillating disturbances, which are conveyed across the shear layer over the junction, where they interact with the acoustic field. As the acoustic waves travel in regions of strong shear, there is a need to include the interaction between the background turbulence and the acoustic field. For this purpose, the oscillation of the background turbulence Reynold's stress, due to the acoustic field, is modeled using an eddy Newtonian model assumption. The time averaged flow is first solved for using RANS along with a k-ε turbulence model. The spatially varying turbulent eddy viscosity is then added to the spatially invariant kinematic viscosity in the acoustic set of equations. The response of the 2D T-junction to an incident acoustic field is analyzed via a plane wave scattering matrix model, and the result is compared to experimental data for a T-junction of rectangular ducts. A strong improvement in the agreement between calculation and experimental data is found when the modification proposed in this paper is implemented. Discrepancies remaining are likely due to inaccuracies in the selected turbulence model, which is known to produce large errors e.g. for flows with significant rotation, which the grazing flow across the T-junction certainly is. A natural next step is therefore to test the proposed methodology together with more sophisticated turbulence models.

  7. A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy

    Directory of Open Access Journals (Sweden)

    Ge Jianjun

    2017-12-01

    Full Text Available Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.

  8. A sensitive multi-residue method for the determination of 35 micropollutants including pharmaceuticals, iodinated contrast media and pesticides in water.

    Science.gov (United States)

    Valls-Cantenys, Carme; Scheurer, Marco; Iglesias, Mònica; Sacher, Frank; Brauch, Heinz-Jürgen; Salvadó, Victoria

    2016-09-01

    A sensitive, multi-residue method using solid-phase extraction followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed to determine a representative group of 35 analytes, including corrosion inhibitors, pesticides and pharmaceuticals such as analgesic and anti-inflammatory drugs, five iodinated contrast media, β-blockers and some of their metabolites and transformation products in water samples. Few other methods are capable of determining such a broad range of contrast media together with other analytes. We studied the parameters affecting the extraction of the target analytes, including sorbent selection and extraction conditions, their chromatographic separation (mobile phase composition and column) and detection conditions using two ionisation sources: electrospray ionisation (ESI) and atmospheric pressure chemical ionisation (APCI). In order to correct matrix effects, a total of 20 surrogate/internal standards were used. ESI was found to have better sensitivity than APCI. Recoveries ranging from 79 to 134 % for tap water and 66 to 144 % for surface water were obtained. Intra-day precision, calculated as relative standard deviation, was below 34 % for tap water and below 21 % for surface water, groundwater and effluent wastewater. Method quantification limits (MQL) were in the low ng L(-1) range, except for the contrast agents iomeprol, amidotrizoic acid and iohexol (22, 25.5 and 17.9 ng L(-1), respectively). Finally, the method was applied to the analysis of 56 real water samples as part of the validation procedure. All of the compounds were detected in at least some of the water samples analysed. Graphical Abstract Multi-residue method for the determination of micropollutants including pharmaceuticals, iodinated contrast media and pesticides in waters by LC-MS/MS.

  9. Selection method and characterization of neutron monochromator natural crystals

    International Nuclear Information System (INIS)

    Stasiulevicius, R.; Kastner, G.F.

    2000-01-01

    Thermal neutrons are important analytical tools for microscopic material probe. These neutrons can be selected by diffraction technique using monocrystal, usually artificial. A crystal selection process was implemented and the characteristics of natural specimens were studied by activation analysis-k 0 method. The representative 120 samples, of which 21 best types, were irradiated in IPR-R1 and measured with a neutron diffractometer at IEA-R1m Brazilian reactors. These results are useful for database build up and ease the choice of appropriate natural crystal, with some advantage options: highest intensity diffracted, enlarging the energy operational interval and optimal performance in special applications. (author)

  10. Effects of the control method (Goč variety in selection forest management in Western Serbia

    Directory of Open Access Journals (Sweden)

    Medarević M.

    2010-01-01

    Full Text Available The control method, one of the most reliable methods of selection forest management, has been applied in selection forests of western Serbia in a somewhat modified form (Goč variety for fifty years. This paper analyzes the effects of the control method, i.e. its Goč variety, in the period from 1960/70 - 2000. It is based on the data of five successive complete inventories of the Forest Management Unit (FMU 'Tara', whose high selection forest of spruce, fir and beech (Piceo-Abieti-Fagetum subass. typicum trees on diluvium, brown and illimerised soil on limestone, and on limestone in formation with hornfels, are the best quality and the most spacious forests in the Management Class MC 491/1. The effects were monitored through the changes in the distribution of the number of trees and volume per diameter classes, separately for fir as the protagonist of the selection structure, and collectively at the level of a compartment, a typical representative of MC 491/1. Also, the analysis included the changes in the number of trees, volume, current volume increment, yield, and number of recruited trees per unit area (1 ha by tree species in MC 491/1, occupying an area of 2,648.78 ha. The study results show that in the study period the average volume in MC 491/1 increased by 18.8%, the percentage of conifers increased from 66.0% to 78.5%, and the bearer of the changes was fir. The volume of the mean fir tree increased by 35.9% and it attained 1.086 m3. The volume increment increased by 15.7%. The selection structure of conifers was satisfactory, but there were problems with beech regeneration, in its stable presence and in its achievement of the targeted structure. The number of trees per unit area (1 ha decreased, which in the long run could have detrimental consequences, but the sustainability in general was satisfactory. The levels of regeneration and recruitment were satisfactory. The health of the trees was improved; the stands were healthy, vital

  11. Recurrence predictive models for patients with hepatocellular carcinoma after radiofrequency ablation using support vector machines with feature selection methods.

    Science.gov (United States)

    Liang, Ja-Der; Ping, Xiao-Ou; Tseng, Yi-Ju; Huang, Guan-Tarn; Lai, Feipei; Yang, Pei-Ming

    2014-12-01

    Recurrence of hepatocellular carcinoma (HCC) is an important issue despite effective treatments with tumor eradication. Identification of patients who are at high risk for recurrence may provide more efficacious screening and detection of tumor recurrence. The aim of this study was to develop recurrence predictive models for HCC patients who received radiofrequency ablation (RFA) treatment. From January 2007 to December 2009, 83 newly diagnosed HCC patients receiving RFA as their first treatment were enrolled. Five feature selection methods including genetic algorithm (GA), simulated annealing (SA) algorithm, random forests (RF) and hybrid methods (GA+RF and SA+RF) were utilized for selecting an important subset of features from a total of 16 clinical features. These feature selection methods were combined with support vector machine (SVM) for developing predictive models with better performance. Five-fold cross-validation was used to train and test SVM models. The developed SVM-based predictive models with hybrid feature selection methods and 5-fold cross-validation had averages of the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the ROC curve as 67%, 86%, 82%, 69%, 90%, and 0.69, respectively. The SVM derived predictive model can provide suggestive high-risk recurrent patients, who should be closely followed up after complete RFA treatment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  12. Cross-border shipment route selection utilizing analytic hierarchy process (AHP method

    Directory of Open Access Journals (Sweden)

    Veeris Ammarapala

    2018-02-01

    Full Text Available Becoming a member of ASEAN Economic Community (AEC, Thailand expects a growth of cross-border trade with neighboring countries, especially the agricultural products shipment. To facilitate this, a number of strategies are set, such as the utilization of single check point, the Asian Highway (AH route development, and the truck lane initiation. However, majority of agricultural products traded through the borders are transported using the rural roads, from growing area to the factory, before continuing to the borders using different highways. It is, therefore, necessary for the Department of Rural Roads (DRR to plan for rural road improvement to accommodate the growth of the cross-border trades in the near future. This research, thus, aims to select potential rural roads to support cross-border shipment utilizing the analytic hierarchy process (AHP method. Seven key factors affecting rural roads selection, with references from transport and other related literatures, are extracted. They include:1 cross-border trade value, 2 distance from border to rural road, 3 agriculture and processed agriculture goods transported across the border, 4 compatibility with national strategies, 5 area characteristics around the rural road, 6 truck volume, and 7 number of rural roads in the radius of 50 kilometers from the border. Interviews are conducted with the experts based on seven key factors to collect data for the AHP analysis. The results identify the weight of each factor with an acceptable consistency ratio. It shows that the cross-border trade value is the most important factor as it achieves the highest weight. The distance from border to rural road and the compatibility with national strategies are also found crucial when making rural road selection decision. The Department of Rural Roads could use the results to select suitable roads, and plan for road improvement to support the crossborder shipment when the AEC is fully implemented.

  13. Contextual control over selective attention: evidence from a two-target method.

    Science.gov (United States)

    MacLellan, Ellen; Shore, David I; Milliken, Bruce

    2015-07-01

    Selective attention is generally studied with conflict tasks, using response time as the dependent measure. Here, we study the impact of selective attention to a first target, T1, presented simultaneously with a distractor, on the accuracy of subsequent encoding of a second target item, T2. This procedure produces an "attentional blink" (AB) effect much like that reported in other studies, and allowed us to study the influence of context on cognitive control with a novel method. In particular, we examined whether preparation to attend selectively to T1 had an impact on the selective encoding of T1 that would translate to report of T2. Preparation to attend selectively was manipulated by varying whether difficult selective attention T1 trials were presented in the context of other difficult selective attention T1 trials. The results revealed strong context effects of this nature, with smaller AB effects when difficult selective attention T1 trials were embedded in a context with many, rather than few, other difficult selective attention T1 trials. Further, the results suggest that both the trial-to-trial local context and the block-wide global context modulate performance in this task.

  14. Manual of selected physico-chemical analytical methods. IV

    International Nuclear Information System (INIS)

    Beran, M.; Klosova, E.; Krtil, J.; Sus, F.; Kuvik, V.; Vrbova, L.; Hamplova, M.; Lengyel, J.; Kelnar, L.; Zakouril, K.

    1990-11-01

    The Central Testing Laboratory of the Nuclear Research Institute at Rez has for a decade been participating in the development of analytical procedures and has been providing analyses of samples of different types and origin. The analytical procedures developed have been published in special journals and a number of them in the Manuals of analytical methods, in three parts. The 4th part of the Manual contains selected physico-chemical methods developed or modified by the Laboratory in the years 1986-1990 within the project ''Development of physico-chemical analytical methods''. In most cases, techniques are involved for non-nuclear applications. Some can find wider applications, especially in analyses of environmental samples. Others have been developed for specific cases of sample analyses or require special instrumentation (mass spectrometer), which partly restricts their applicability by other institutions. (author)

  15. Selection of the treatment method for the West Valley alkaline supernatant

    International Nuclear Information System (INIS)

    Carl, D.E.; Leonard, I.M.

    1987-02-01

    As part of the West Valley Demonstration Project (WVDP), th PUREX supernatant stored in Tank 8d-2 will be partially decontaminated before encapsulation in the final glass form. This report discusses selection of a method for removing Cs-137, the major radioactive ion in the supernatant. Methods considered were: (1) electrodialysis; (2) hyperfiltration; (3) precipitation with ferrocyanide, NaTPB, or PTA; (4) organic ion exchange using Cs-100 or a biologically derived media; (5) chelation using DeVoe/Holbein compostions; and (6) inorganic ion exchange using Durasil, natural zeolities, IE-95 or IE-96 media. Several different methods of using inorganic ion exchange media were also reviewed including (1) four columns with elution, and (2) two, three, or four columns without elution. After the careful evaluation of experimental data with all process constraints taken into account, the inorganic exchange media IE-96 (Linde Ionsiv IE-96 synthetic zeolite) was chosen for WVDP cesium recovery. IE-96 was chosen for the following reasons: high sorption rate, a decontamination factor (DF) over 1000, excellent exchange capacity at WVDP conditions, compatability with the glass formers used for borosilicate glass in direct melter feed applications, and a history of successful application in radio chemical seperation for waste streams. 34 refs., 29 figs., 27 tabs

  16. The MCDM Model for Personnel Selection Based on SWARA and ARAS Methods

    Directory of Open Access Journals (Sweden)

    Darjan Karabasevic

    2015-05-01

    Full Text Available Competent employees are the key resource in an organization for achieving success and, therefore, competitiveness on the market. The aim of the recruitment and selection process is to acquire personnel with certain competencies required for a particular position, i.e.,a position within the company. Bearing in mind the fact that in the process of decision making decision-makers have underused the methods of making decisions, this paper aims to establish an MCDM model for the evaluation and selection of candidates in the process of the recruitment and selection of personnel based on the SWARA and the ARAS methods. Apart from providing an MCDM model, the paper will additionally provide a set of evaluation criteria for the position of a sales manager (the middle management in the telecommunication industry which will also be used in the numerical example. On the basis of a numerical example, in the process of employment, theproposed MCDMmodel can be successfully usedin selecting candidates.

  17. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

    Directory of Open Access Journals (Sweden)

    Pavol Partila

    2015-01-01

    Full Text Available The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.

  18. Including Children with Selective Mutism in Mainstream Schools and Kindergartens: Problems and Possibilities

    Science.gov (United States)

    Omdal, Heidi

    2008-01-01

    There is little research on inclusion of children with selective mutism in school/kindergarten. Moreover, few studies have tried to understand selectively mute children's interactions in the natural surroundings of their home and school/kindergarten. Five children meeting the DSM-IV criteria for selective mutism were video-observed in social…

  19. Selection of boron based tribological hard coatings using multi-criteria decision making methods

    International Nuclear Information System (INIS)

    Çalışkan, Halil

    2013-01-01

    Highlights: • Boron based coating selection problem for cutting tools was solved. • EXPROM2, TOPSIS and VIKOR methods were used for ranking the alternative materials. • The best coatings for cutting tool were selected as TiBN and TiSiBN. • The ranking results are in good agreement with cutting test results in literature. - Abstract: Mechanical and tribological properties of hard coatings can be enhanced using boron as alloying element. Therefore, multicomponent nanostructured boron based hard coatings are deposited on cutting tools by different methods at different parameters. Different mechanical and tribological properties are obtained after deposition, and it is a difficult task to select the best coating material. In this paper, therefore, a systematic evaluation model was proposed to tackle the difficulty of the material selection with specific properties among a set of available alternatives. The alternatives consist of multicomponent nanostructured TiBN, TiCrBN, TiSiBN and TiAlSiBN coatings deposited by magnetron sputtering and ion implantation assisted magnetron sputtering at different parameters. The alternative coating materials were ranked by using three multi-criteria decision-making (MCDM) methods, i.e. EXPROM2 (preference ranking organization method for enrichment evaluation), TOPSIS (technique for order performance by similarity to ideal solution) and VIKOR (VIšekriterijumsko KOmpromisno Rangiranje), in order to determine the best coating material for cutting tools. Hardness (H), Young’s modulus (E), elastic recovery, friction coefficient, critical load, H/E and H 3 /E 2 ratios were considered as material selection criteria. In order to determine the importance weights of the evaluation criteria, a compromised weighting method, which composes of the analytic hierarchy process and Entropy methods, were used. The ranking results showed that TiBN and TiSiBN coatings deposited at given parameters are the best coatings for cutting tools

  20. A Method to Select Human–System Interfaces for Nuclear Power Plants

    Directory of Open Access Journals (Sweden)

    Jacques V. Hugo

    2016-02-01

    Full Text Available The new generation of nuclear power plants (NPPs will likely make use of state-of-the-art technologies in many areas of the plant. The analysis, design, and selection of advanced human–system interfaces (HSIs constitute an important part of power plant engineering. Designers need to consider the new capabilities afforded by these technologies in the context of current regulations and new operational concepts, which is why they need a more rigorous method by which to plan the introduction of advanced HSIs in NPP work areas. Much of current human factors research stops at the user interface and fails to provide a definitive process for integration of end user devices with instrumentation and control and operational concepts. The current lack of a clear definition of HSI technology, including the process for integration, makes characterization and implementation of new and advanced HSIs difficult. This paper describes how new design concepts in the nuclear industry can be analyzed and how HSI technologies associated with new industrial processes might be considered. It also describes a basis for an understanding of human as well as technology characteristics that could be incorporated into a prioritization scheme for technology selection and deployment plans.

  1. A multi-fidelity analysis selection method using a constrained discrete optimization formulation

    Science.gov (United States)

    Stults, Ian C.

    The purpose of this research is to develop a method for selecting the fidelity of contributing analyses in computer simulations. Model uncertainty is a significant component of result validity, yet it is neglected in most conceptual design studies. When it is considered, it is done so in only a limited fashion, and therefore brings the validity of selections made based on these results into question. Neglecting model uncertainty can potentially cause costly redesigns of concepts later in the design process or can even cause program cancellation. Rather than neglecting it, if one were to instead not only realize the model uncertainty in tools being used but also use this information to select the tools for a contributing analysis, studies could be conducted more efficiently and trust in results could be quantified. Methods for performing this are generally not rigorous or traceable, and in many cases the improvement and additional time spent performing enhanced calculations are washed out by less accurate calculations performed downstream. The intent of this research is to resolve this issue by providing a method which will minimize the amount of time spent conducting computer simulations while meeting accuracy and concept resolution requirements for results. In many conceptual design programs, only limited data is available for quantifying model uncertainty. Because of this data sparsity, traditional probabilistic means for quantifying uncertainty should be reconsidered. This research proposes to instead quantify model uncertainty using an evidence theory formulation (also referred to as Dempster-Shafer theory) in lieu of the traditional probabilistic approach. Specific weaknesses in using evidence theory for quantifying model uncertainty are identified and addressed for the purposes of the Fidelity Selection Problem. A series of experiments was conducted to address these weaknesses using n-dimensional optimization test functions. These experiments found that model

  2. APPLICATION OF THE PERFORMANCE SELECTION INDEX METHOD FOR SOLVING MACHINING MCDM PROBLEMS

    Directory of Open Access Journals (Sweden)

    Dušan Petković

    2017-04-01

    Full Text Available Complex nature of machining processes requires the use of different methods and techniques for process optimization. Over the past few years a number of different optimization methods have been proposed for solving continuous machining optimization problems. In manufacturing environment, engineers are also facing a number of discrete machining optimization problems. In order to help decision makers in solving this type of optimization problems a number of multi criteria decision making (MCDM methods have been proposed. This paper introduces the use of an almost unexplored MCDM method, i.e. performance selection index (PSI method for solving machining MCDM problems. The main motivation for using the PSI method is that it is not necessary to determine criteria weights as in other MCDM methods. Applicability and effectiveness of the PSI method have been demonstrated while solving two case studies dealing with machinability of materials and selection of the most suitable cutting fluid for the given machining application. The obtained rankings have good correlation with those derived by the past researchers using other MCDM methods which validate the usefulness of this method for solving machining MCDM problems.

  3. Method for selective immobilization of macromolecules on self assembled monolayer surfaces

    Science.gov (United States)

    Laskin, Julia [Richland, WA; Wang, Peng [Billerica, MA

    2011-11-29

    Disclosed is a method for selective chemical binding and immobilization of macromolecules on solid supports in conjunction with self-assembled monolayer (SAM) surfaces. Immobilization involves selective binding of peptides and other macromolecules to SAM surfaces using reactive landing (RL) of mass-selected, gas phase ions. SAM surfaces provide a simple and convenient platform for tailoring chemical properties of a variety of substrates. The invention finds applications in biochemistry ranging from characterization of molecular recognition events at the amino acid level and identification of biologically active motifs in proteins, to development of novel biosensors and substrates for stimulated protein and cell adhesion.

  4. Selection and evaluation of gamma decay standards for detector calibration using coincidence method

    International Nuclear Information System (INIS)

    Hlavac, S.

    2000-01-01

    Coincidence method for calibration of gamma detectors using suitable calibration standards with two cascading gamma rays is analyzed. From the list of recommended gamma ray standards currently under reevaluation by the CRP, 14 radionuclides were selected as the potential source candidates for the coincidence method. The following sources were selected 24 Na, 46 Sc, 60 Co, 66 Ga, 75 Se, 88 Y, Nb 94 , 111 In, 123m Te, 133 Ba, 134 Cs, 152 Eu, 154 Eu and 207 Bi. Reaction 11 B (p,γ) 12 C* was also selected as a source of high energy gamma rays. Experimental data on angular correlation coefficients for selected sources were collected from the literature and evaluated according to the recommended procedure. Theoretical angular correlation coefficients were calculated and compared to the evaluated data. (author)

  5. Primitive polynomials selection method for pseudo-random number generator

    Science.gov (United States)

    Anikin, I. V.; Alnajjar, Kh

    2018-01-01

    In this paper we suggested the method for primitive polynomials selection of special type. This kind of polynomials can be efficiently used as a characteristic polynomials for linear feedback shift registers in pseudo-random number generators. The proposed method consists of two basic steps: finding minimum-cost irreducible polynomials of the desired degree and applying primitivity tests to get the primitive ones. Finally two primitive polynomials, which was found by the proposed method, used in pseudorandom number generator based on fuzzy logic (FRNG) which had been suggested before by the authors. The sequences generated by new version of FRNG have low correlation magnitude, high linear complexity, less power consumption, is more balanced and have better statistical properties.

  6. Supplier selection for a tire company with AHP and PROMETHEE methods

    Directory of Open Access Journals (Sweden)

    Atakan ALKAN

    2017-04-01

    Full Text Available Supplier selection is very important for a company to be successful in a globalized competitive environment. The aims at choosing the optimal supplier; to increase customer satisfaction, improve the competitive ability and continue to exist at minimal cost. This study was intended to choose the most suitable raw material supplier in a company engaged in the production of agricultural tires. In the study Analytical Hierarchy Process (AHP and Promethee I-II methods were applied in order to select the most optimal supplier to a company. In conclusion, AHP and Promethee I-II methods used by the company to determine the suppliers with the optimal supplier and brought several recommendations.

  7. Application of mathematical methods of analysis in selection of competing information technologies

    Science.gov (United States)

    Semenov, V. L.; Kadyshev, E. N.; Zakharova, A. N.; Patianova, A. O.; Dulina, G. S.

    2018-05-01

    The article discusses the use of qualimetry methods using the apparatus of mathematical analysis in the formation of the integral index that allows one to select the best option among competing information technology. The authors propose the use of affine space in the evaluation and selection of competing information technologies.

  8. An input feature selection method applied to fuzzy neural networks for signal esitmation

    International Nuclear Information System (INIS)

    Na, Man Gyun; Sim, Young Rok

    2001-01-01

    It is well known that the performance of a fuzzy neural networks strongly depends on the input features selected for its training. In its applications to sensor signal estimation, there are a large number of input variables related with an output. As the number of input variables increases, the training time of fuzzy neural networks required increases exponentially. Thus, it is essential to reduce the number of inputs to a fuzzy neural networks and to select the optimum number of mutually independent inputs that are able to clearly define the input-output mapping. In this work, principal component analysis (PAC), genetic algorithms (GA) and probability theory are combined to select new important input features. A proposed feature selection method is applied to the signal estimation of the steam generator water level, the hot-leg flowrate, the pressurizer water level and the pressurizer pressure sensors in pressurized water reactors and compared with other input feature selection methods

  9. YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features

    KAUST Repository

    Kleftogiannis, Dimitrios A.; Theofilatos, Konstantinos; Likothanassis, Spiros; Mavroudi, Seferina

    2015-01-01

    MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of Support Vector Machines (SVM) with Genetic Algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

  10. YamiPred: A novel evolutionary method for predicting pre-miRNAs and selecting relevant features

    KAUST Repository

    Kleftogiannis, Dimitrios A.

    2015-01-23

    MicroRNAs (miRNAs) are small non-coding RNAs, which play a significant role in gene regulation. Predicting miRNA genes is a challenging bioinformatics problem and existing experimental and computational methods fail to deal with it effectively. We developed YamiPred, an embedded classification method that combines the efficiency and robustness of Support Vector Machines (SVM) with Genetic Algorithms (GA) for feature selection and parameters optimization. YamiPred was tested in a new and realistic human dataset and was compared with state-of-the-art computational intelligence approaches and the prevalent SVM-based tools for miRNA prediction. Experimental results indicate that YamiPred outperforms existing approaches in terms of accuracy and of geometric mean of sensitivity and specificity. The embedded feature selection component selects a compact feature subset that contributes to the performance optimization. Further experimentation with this minimal feature subset has achieved very high classification performance and revealed the minimum number of samples required for developing a robust predictor. YamiPred also confirmed the important role of commonly used features such as entropy and enthalpy, and uncovered the significance of newly introduced features, such as %A-U aggregate nucleotide frequency and positional entropy. The best model trained on human data has successfully predicted pre-miRNAs to other organisms including the category of viruses.

  11. Automatic variable selection method and a comparison for quantitative analysis in laser-induced breakdown spectroscopy

    Science.gov (United States)

    Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong

    2018-05-01

    In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.

  12. Evaluation of Maryland abutment scour equation through selected threshold velocity methods

    Science.gov (United States)

    Benedict, S.T.

    2010-01-01

    The U.S. Geological Survey, in cooperation with the Maryland State Highway Administration, used field measurements of scour to evaluate the sensitivity of the Maryland abutment scour equation to the critical (or threshold) velocity variable. Four selected methods for estimating threshold velocity were applied to the Maryland abutment scour equation, and the predicted scour to the field measurements were compared. Results indicated that performance of the Maryland abutment scour equation was sensitive to the threshold velocity with some threshold velocity methods producing better estimates of predicted scour than did others. In addition, results indicated that regional stream characteristics can affect the performance of the Maryland abutment scour equation with moderate-gradient streams performing differently from low-gradient streams. On the basis of the findings of the investigation, guidance for selecting threshold velocity methods for application to the Maryland abutment scour equation are provided, and limitations are noted.

  13. Evaluation and selection of decision-making methods to assess landfill mining projects.

    Science.gov (United States)

    Hermann, Robert; Baumgartner, Rupert J; Vorbach, Stefan; Ragossnig, Arne; Pomberger, Roland

    2015-09-01

    For the first time in Austria, fundamental technological and economic studies on recovering secondary raw materials from large landfills have been carried out, based on the 'LAMIS - Landfill Mining Austria' pilot project. A main focus of the research - and the subject of this article - was to develop an assessment or decision-making procedure that allows landfill owners to thoroughly examine the feasibility of a landfill mining project in advance. Currently there are no standard procedures that would sufficiently cover all the multiple-criteria requirements. The basic structure of the multiple attribute decision making process was used to narrow down on selection, conceptual design and assessment of suitable procedures. Along with a breakdown into preliminary and main assessment, the entire foundation required was created, such as definitions of requirements to an assessment method, selection and accurate description of the various assessment criteria and classification of the target system for the present 'landfill mining' vs. 'retaining the landfill in after-care' decision-making problem. Based on these studies, cost-utility analysis and the analytical-hierarchy process were selected from the range of multiple attribute decision-making procedures and examined in detail. Overall, both methods have their pros and cons with regard to their use for assessing landfill mining projects. Merging these methods or connecting them with single-criteria decision-making methods (like the net present value method) may turn out to be reasonable and constitute an appropriate assessment method. © The Author(s) 2015.

  14. Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

    Directory of Open Access Journals (Sweden)

    Abdel Samee Nagwan M

    2012-08-01

    Full Text Available Abstract Background Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC. The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. Results In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy. A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer in the top ten genes of the list of intersected genes. Conclusions To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when

  15. Comparison of different methods to include recycling in LCAs of aluminium cans and disposable polystyrene cups.

    Science.gov (United States)

    van der Harst, Eugenie; Potting, José; Kroeze, Carolien

    2016-02-01

    Many methods have been reported and used to include recycling in life cycle assessments (LCAs). This paper evaluates six widely used methods: three substitution methods (i.e. substitution based on equal quality, a correction factor, and alternative material), allocation based on the number of recycling loops, the recycled-content method, and the equal-share method. These six methods were first compared, with an assumed hypothetical 100% recycling rate, for an aluminium can and a disposable polystyrene (PS) cup. The substitution and recycled-content method were next applied with actual rates for recycling, incineration and landfilling for both product systems in selected countries. The six methods differ in their approaches to credit recycling. The three substitution methods stimulate the recyclability of the product and assign credits for the obtained recycled material. The choice to either apply a correction factor, or to account for alternative substituted material has a considerable influence on the LCA results, and is debatable. Nevertheless, we prefer incorporating quality reduction of the recycled material by either a correction factor or an alternative substituted material over simply ignoring quality loss. The allocation-on-number-of-recycling-loops method focusses on the life expectancy of material itself, rather than on a specific separate product. The recycled-content method stimulates the use of recycled material, i.e. credits the use of recycled material in products and ignores the recyclability of the products. The equal-share method is a compromise between the substitution methods and the recycled-content method. The results for the aluminium can follow the underlying philosophies of the methods. The results for the PS cup are additionally influenced by the correction factor or credits for the alternative material accounting for the drop in PS quality, the waste treatment management (recycling rate, incineration rate, landfilling rate), and the

  16. A Parameter Selection Method for Wind Turbine Health Management through SCADA Data

    Directory of Open Access Journals (Sweden)

    Mian Du

    2017-02-01

    Full Text Available Wind turbine anomaly or failure detection using machine learning techniques through supervisory control and data acquisition (SCADA system is drawing wide attention from academic and industry While parameter selection is important for modelling a wind turbine’s condition, only a few papers have been published focusing on this issue and in those papers interconnections among sub-components in a wind turbine are used to address this problem. However, merely the interconnections for decision making sometimes is too general to provide a parameter list considering the differences of each SCADA dataset. In this paper, a method is proposed to provide more detailed suggestions on parameter selection based on mutual information. First, the copula is proven to be capable of simplifying the estimation of mutual information. Then an empirical copulabased mutual information estimation method (ECMI is introduced for application. After that, a real SCADA dataset is adopted to test the method, and the results show the effectiveness of the ECMI in providing parameter selection suggestions when physical knowledge is not accurate enough.

  17. Application of PROMETHEE-GAIA method for non-traditional machining processes selection

    Directory of Open Access Journals (Sweden)

    Prasad Karande

    2012-10-01

    Full Text Available With ever increasing demand for manufactured products of hard alloys and metals with high surface finish and complex shape geometry, more interest is now being paid to non-traditional machining (NTM processes, where energy in its direct form is used to remove material from workpiece surface. Compared to conventional machining processes, NTM processes possess almost unlimited capabilities and there is a strong believe that use of NTM processes would go on increasing in diverse range of applications. Presence of a large number of NTM processes along with complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Past researchers have already attempted to solve NTM process selection problems using various complex mathematical approaches which often require a profound knowledge in mathematics/artificial intelligence from the part of process engineers. In this paper, four NTM process selection problems are solved using an integrated PROMETHEE (preference ranking organization method for enrichment evaluation and GAIA (geometrical analysis for interactive aid method which would act as a visual decision aid to the process engineers. The observed results are quite satisfactory and exactly match with the expected solutions.

  18. Analysis of Criteria Influencing Contractor Selection Using TOPSIS Method

    Science.gov (United States)

    Alptekin, Orkun; Alptekin, Nesrin

    2017-10-01

    Selection of the most suitable contractor is an important process in public construction projects. This process is a major decision which may influence the progress and success of a construction project. Improper selection of contractors may lead to problems such as bad quality of work and delay in project duration. Especially in the construction projects of public buildings, the proper choice of contractor is beneficial to the public institution. Public procurement processes have different characteristics in respect to dissimilarities in political, social and economic features of every country. In Turkey, Turkish Public Procurement Law PPL 4734 is the main regulatory law for the procurement of the public buildings. According to the PPL 4734, public construction administrators have to contract with the lowest bidder who has the minimum requirements according to the criteria in prequalification process. Public administrators are not sufficient for selection of the proper contractor because of the restrictive provisions of the PPL 4734. The lowest bid method does not enable public construction administrators to select the most qualified contractor and they have realised the fact that the selection of a contractor based on lowest bid alone is inadequate and may lead to the failure of the project in terms of time delay Eand poor quality standards. In order to evaluate the overall efficiency of a project, it is necessary to identify selection criteria. This study aims to focus on identify importance of other criteria besides lowest bid criterion in contractor selection process of PPL 4734. In this study, a survey was conducted to staff of Department of Construction Works of Eskisehir Osmangazi University. According to TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) for analysis results, termination of construction work in previous tenders is the most important criterion of 12 determined criteria. The lowest bid criterion is ranked in rank 5.

  19. ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition.

    Science.gov (United States)

    Zhang, Jianhai; Chen, Ming; Zhao, Shaokai; Hu, Sanqing; Shi, Zhiguo; Cao, Yu

    2016-09-22

    Electroencephalogram (EEG) signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI) environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP). Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation). Furthermore, support vector machine (SVM) was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels' weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels). In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a contribution to the

  20. ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition

    Directory of Open Access Journals (Sweden)

    Jianhai Zhang

    2016-09-01

    Full Text Available Electroencephalogram (EEG signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP. Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation. Furthermore, support vector machine (SVM was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels’ weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels. In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a

  1. Fringe-period selection for a multifrequency fringe-projection phase unwrapping method

    International Nuclear Information System (INIS)

    Zhang, Chunwei; Zhao, Hong; Jiang, Kejian

    2016-01-01

    The multi-frequency fringe-projection phase unwrapping method (MFPPUM) is a typical phase unwrapping algorithm for fringe projection profilometry. It has the advantage of being capable of correctly accomplishing phase unwrapping even in the presence of surface discontinuities. If the fringe frequency ratio of the MFPPUM is too large, fringe order error (FOE) may be triggered. FOE will result in phase unwrapping error. It is preferable for the phase unwrapping to be kept correct while the fewest sets of lower frequency fringe patterns are used. To achieve this goal, in this paper a parameter called fringe order inaccuracy (FOI) is defined, dominant factors which may induce FOE are theoretically analyzed, a method to optimally select the fringe periods for the MFPPUM is proposed with the aid of FOI, and experiments are conducted to research the impact of the dominant factors in phase unwrapping and demonstrate the validity of the proposed method. Some novel phenomena are revealed by these experiments. The proposed method helps to optimally select the fringe periods and detect the phase unwrapping error for the MFPPUM. (paper)

  2. Improved time series prediction with a new method for selection of model parameters

    International Nuclear Information System (INIS)

    Jade, A M; Jayaraman, V K; Kulkarni, B D

    2006-01-01

    A new method for model selection in prediction of time series is proposed. Apart from the conventional criterion of minimizing RMS error, the method also minimizes the error on the distribution of singularities, evaluated through the local Hoelder estimates and its probability density spectrum. Predictions of two simulated and one real time series have been done using kernel principal component regression (KPCR) and model parameters of KPCR have been selected employing the proposed as well as the conventional method. Results obtained demonstrate that the proposed method takes into account the sharp changes in a time series and improves the generalization capability of the KPCR model for better prediction of the unseen test data. (letter to the editor)

  3. A novel selection method of seismic attributes based on gray relational degree and support vector machine.

    Directory of Open Access Journals (Sweden)

    Yaping Huang

    Full Text Available The selection of seismic attributes is a key process in reservoir prediction because the prediction accuracy relies on the reliability and credibility of the seismic attributes. However, effective selection method for useful seismic attributes is still a challenge. This paper presents a novel selection method of seismic attributes for reservoir prediction based on the gray relational degree (GRD and support vector machine (SVM. The proposed method has a two-hierarchical structure. In the first hierarchy, the primary selection of seismic attributes is achieved by calculating the GRD between seismic attributes and reservoir parameters, and the GRD between the seismic attributes. The principle of the primary selection is that these seismic attributes with higher GRD to the reservoir parameters will have smaller GRD between themselves as compared to those with lower GRD to the reservoir parameters. Then the SVM is employed in the second hierarchy to perform an interactive error verification using training samples for the purpose of determining the final seismic attributes. A real-world case study was conducted to evaluate the proposed GRD-SVM method. Reliable seismic attributes were selected to predict the coalbed methane (CBM content in southern Qinshui basin, China. In the analysis, the instantaneous amplitude, instantaneous bandwidth, instantaneous frequency, and minimum negative curvature were selected, and the predicted CBM content was fundamentally consistent with the measured CBM content. This real-world case study demonstrates that the proposed method is able to effectively select seismic attributes, and improve the prediction accuracy. Thus, the proposed GRD-SVM method can be used for the selection of seismic attributes in practice.

  4. A novel heterogeneous training sample selection method on space-time adaptive processing

    Science.gov (United States)

    Wang, Qiang; Zhang, Yongshun; Guo, Yiduo

    2018-04-01

    The performance of ground target detection about space-time adaptive processing (STAP) decreases when non-homogeneity of clutter power is caused because of training samples contaminated by target-like signals. In order to solve this problem, a novel nonhomogeneous training sample selection method based on sample similarity is proposed, which converts the training sample selection into a convex optimization problem. Firstly, the existing deficiencies on the sample selection using generalized inner product (GIP) are analyzed. Secondly, the similarities of different training samples are obtained by calculating mean-hausdorff distance so as to reject the contaminated training samples. Thirdly, cell under test (CUT) and the residual training samples are projected into the orthogonal subspace of the target in the CUT, and mean-hausdorff distances between the projected CUT and training samples are calculated. Fourthly, the distances are sorted in order of value and the training samples which have the bigger value are selective preference to realize the reduced-dimension. Finally, simulation results with Mountain-Top data verify the effectiveness of the proposed method.

  5. The selective dynamical downscaling method for extreme-wind atlases

    DEFF Research Database (Denmark)

    Larsén, Xiaoli Guo; Badger, Jake; Hahmann, Andrea N.

    2012-01-01

    A selective dynamical downscaling method is developed to obtain extreme-wind atlases for large areas. The method is general, efficient and flexible. The method consists of three steps: (i) identifying storm episodes for a particular area, (ii) downscaling of the storms using mesoscale modelling...... and (iii) post-processing. The post-processing generalizes the winds from the mesoscale modelling to standard conditions, i.e. 10-m height over a homogeneous surface with roughness length of 5 cm. The generalized winds are then used to calculate the 50-year wind using the annual maximum method for each...... mesoscale grid point. The generalization of the mesoscale winds through the post-processing provides a framework for data validation and for applying further the mesoscale extreme winds at specific places using microscale modelling. The results are compared with measurements from two areas with different...

  6. A Ranking Method for Neutral Pion and Eta Selection in Hadronic Events

    International Nuclear Information System (INIS)

    Bingoel, A.

    2004-01-01

    The selection of neutral pions and etas with a high purity while maintaining also a high efficiency can be important in the formation of statistically significant mass spectra in the reconstruction of short-lived particles such as the omega meson (ω→π + + π - + π 0 ). In this study a Ranking method has been optimized for data from the ALEPH Experiment, CERN. The results show that the Ranking method, when applied to high multiplicity events, yields significant improvements in the purity of selected pion candidates and facilitates the relaxation of standard cuts thereby avoiding some systematic uncertainties

  7. 20 CFR 617.23 - Selection of training methods and programs.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Selection of training methods and programs. 617.23 Section 617.23 Employees' Benefits EMPLOYMENT AND TRAINING ADMINISTRATION, DEPARTMENT OF LABOR... for which training is undertaken shall not preclude the development of an individual retraining...

  8. Standard methods for rearing and selection of Apis mellifera queens

    DEFF Research Database (Denmark)

    Büchler, Ralph; Andonov, Sreten; Bienefeld, Kaspar

    2013-01-01

    Here we cover a wide range of methods currently in use and recommended in modern queen rearing, selection and breeding. The recommendations are meant to equally serve as standards for both scientific and practical beekeeping purposes. The basic conditions and different management techniques for q...

  9. Sampling point selection for energy estimation in the quasicontinuum method

    NARCIS (Netherlands)

    Beex, L.A.A.; Peerlings, R.H.J.; Geers, M.G.D.

    2010-01-01

    The quasicontinuum (QC) method reduces computational costs of atomistic calculations by using interpolation between a small number of so-called repatoms to represent the displacements of the complete lattice and by selecting a small number of sampling atoms to estimate the total potential energy of

  10. Selection of candidate plus phenotypes of Jatropha curcas L. using method of paired comparisons

    Energy Technology Data Exchange (ETDEWEB)

    Mishra, D.K. [Silviculture Division, Arid Forest Research Institute, P.O. Krishi Mandi, New Pali Road, Jodhpur 342005, Rajasthan (India)

    2009-03-15

    Jatropha curcas L. (Euphorbiaceae) is an oil bearing species with multiple uses and considerable potential as a biodiesel crop. The present communication deals with the method of selecting plus phenotypes of J. curcas for exploiting genetic variability for further improvement. Candidate plus tree selection is the first and most important stage in any tree improvement programme. The selection of candidate plus plants (CPPs) is based upon various important attributes associated with the species and their relative ranking. Relative preference between various traits and scoring for each trait has been worked out by using the method of paired comparisons for the selection of CPP in J. curcas L. The most important ones are seed and oil yields. (author)

  11. Research on the Selection Strategy of Green Building Parts Supplier Based on the Catastrophe Theory and Kent Index Method

    Directory of Open Access Journals (Sweden)

    Zhenhua Luo

    2016-01-01

    Full Text Available At present, the green building and housing industrialization are two mainstream directions in the real estate industry. The production of green building parts which combines green building and housing industrialization, two concepts, is to be vigorously developed. The key of quality assurance in the assembly project is choosing reliable and proper green building parts suppliers. This paper analyzes the inherent requirements of the green building, combined with the characteristics of the housing industrialization, and puts forward an evaluation index system of supplier selection for green building parts, which includes product index, enterprise index, green development index, and cooperation ability index. To reduce the influence of subjective factors, the improved method which merges Kent index method and catastrophe theory is applied to the green building parts supplier selection and evaluation. This paper takes the selection of the unit bathroom suppliers as an example, uses the improved model to calculate and analyze the data of each supplier, and finally selects the optimal supplier. With combination of the Kent index and the catastrophe theory, the result shows that it can effectively reduce the subjectivity of the evaluation and provide a basis for the selection of the green building parts suppliers.

  12. New evaluation methods for conceptual design selection using computational intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai [University of Electronic Science and Technology of China, Chengdu (China); Xue, Lihua [Higher Education Press, Beijing (China)

    2013-03-15

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  13. New evaluation methods for conceptual design selection using computational intelligence techniques

    International Nuclear Information System (INIS)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai; Xue, Lihua

    2013-01-01

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  14. The research progress of genomic selection in livestock.

    Science.gov (United States)

    Li, Hong-wei; Wang, Rui-jun; Wang, Zhi-ying; Li, Xue-wu; Wang, Zhen-yu; Yanjun, Zhang; Rui, Su; Zhihong, Liu; Jinquan, Li

    2017-05-20

    With the development of gene chip and breeding technology, genomic selection in plants and animals has become research hotspots in recent years. Genomic selection has been extensively applied to all kinds of economic livestock, due to its high accuracy, short generation intervals and low breeding costs. In this review, we summarize genotyping technology and the methods for genomic breeding value estimation, the latter including the least square method, RR-BLUP, GBLUP, ssGBLUP, BayesA and BayesB. We also cover basic principles of genomic selection and compare their genetic marker ranges, genomic selection accuracy and operational speed. In addition, we list common indicators, methods and influencing factors that are related to genomic selection accuracy. Lastly, we discuss latest applications and the current problems of genomic selection at home and abroad. Importantly, we envision future status of genomic selection research, including multi-trait and multi-population genomic selection, as well as impact of whole genome sequencing and dominant effects on genomic selection. This review will provide some venues for other breeders to further understand genome selection.

  15. Variable Selection via Partial Correlation.

    Science.gov (United States)

    Li, Runze; Liu, Jingyuan; Lou, Lejia

    2017-07-01

    Partial correlation based variable selection method was proposed for normal linear regression models by Bühlmann, Kalisch and Maathuis (2010) as a comparable alternative method to regularization methods for variable selection. This paper addresses two important issues related to partial correlation based variable selection method: (a) whether this method is sensitive to normality assumption, and (b) whether this method is valid when the dimension of predictor increases in an exponential rate of the sample size. To address issue (a), we systematically study this method for elliptical linear regression models. Our finding indicates that the original proposal may lead to inferior performance when the marginal kurtosis of predictor is not close to that of normal distribution. Our simulation results further confirm this finding. To ensure the superior performance of partial correlation based variable selection procedure, we propose a thresholded partial correlation (TPC) approach to select significant variables in linear regression models. We establish the selection consistency of the TPC in the presence of ultrahigh dimensional predictors. Since the TPC procedure includes the original proposal as a special case, our theoretical results address the issue (b) directly. As a by-product, the sure screening property of the first step of TPC was obtained. The numerical examples also illustrate that the TPC is competitively comparable to the commonly-used regularization methods for variable selection.

  16. A QSAR Study of Environmental Estrogens Based on a Novel Variable Selection Method

    Directory of Open Access Journals (Sweden)

    Aiqian Zhang

    2012-05-01

    Full Text Available A large number of descriptors were employed to characterize the molecular structure of 53 natural, synthetic, and environmental chemicals which are suspected of disrupting endocrine functions by mimicking or antagonizing natural hormones and may thus pose a serious threat to the health of humans and wildlife. In this work, a robust quantitative structure-activity relationship (QSAR model with a novel variable selection method has been proposed for the effective estrogens. The variable selection method is based on variable interaction (VSMVI with leave-multiple-out cross validation (LMOCV to select the best subset. During variable selection, model construction and assessment, the Organization for Economic Co-operation and Development (OECD principles for regulation of QSAR acceptability were fully considered, such as using an unambiguous multiple-linear regression (MLR algorithm to build the model, using several validation methods to assessment the performance of the model, giving the define of applicability domain and analyzing the outliers with the results of molecular docking. The performance of the QSAR model indicates that the VSMVI is an effective, feasible and practical tool for rapid screening of the best subset from large molecular descriptors.

  17. Genomic selection in plant breeding.

    Science.gov (United States)

    Newell, Mark A; Jannink, Jean-Luc

    2014-01-01

    Genomic selection (GS) is a method to predict the genetic value of selection candidates based on the genomic estimated breeding value (GEBV) predicted from high-density markers positioned throughout the genome. Unlike marker-assisted selection, the GEBV is based on all markers including both minor and major marker effects. Thus, the GEBV may capture more of the genetic variation for the particular trait under selection.

  18. Genetic gain and economic values of selection strategies including semen traits in three- and four-way crossbreeding systems for swine production.

    Science.gov (United States)

    González-Peña, D; Knox, R V; MacNeil, M D; Rodriguez-Zas, S L

    2015-03-01

    Four semen traits: volume (VOL), concentration (CON), progressive motility of spermatozoa (MOT), and abnormal spermatozoa (ABN) provide complementary information on boar fertility. Assessment of the impact of selection for semen traits is hindered by limited information on economic parameters. Objectives of this study were to estimate economic values for semen traits and to evaluate the genetic gain when these traits are incorporated into traditional selection strategies in a 3-tier system of swine production. Three-way (maternal nucleus lines A and B and paternal nucleus line C) and 4-way (additional paternal nucleus line D) crossbreeding schemes were compared. A novel population structure that accommodated selection for semen traits was developed. Three selection strategies were simulated. Selection Strategy I (baseline) encompassed selection for maternal traits: number of pigs born alive (NBA), litter birth weight (LBW), adjusted 21-d litter weight (A21), and number of pigs at 21 d (N21); and paternal traits: number of days to 113.5 kg (D113), backfat (BF), ADG, feed efficiency (FE), and carcass lean % (LEAN). Selection Strategy II included Strategy I and the number of usable semen doses per collection (DOSES), a function of the 4 semen traits. Selection Strategy III included Strategy I and the 4 semen traits individually. The estimated economic values of VOL, CON, MOT, ABN, and DOSES for 7 to 1 collections/wk ranged from $0.21 to $1.44/mL, $0.12 to $0.83/10 spermatozoa/mm, $0.61 to $12.66/%, -$0.53 to -$10.88/%, and $2.01 to $41.43/%, respectively. The decrease in the relative economic values of semen traits and DOSES with higher number of collections per wk was sharper between 1 and 2.33 collections/wk than between 2.33 and 7 collections/wk. The higher economic value of MOT and ABN relative to VOL and CON could be linked to the genetic variances and covariances of these traits. Average genetic gains for the maternal traits were comparable across strategies

  19. Comparison of multimedia system and conventional method in patients’ selecting prosthetic treatment

    Directory of Open Access Journals (Sweden)

    Baghai R

    2010-12-01

    Full Text Available "nBackground and Aims: Selecting an appropriate treatment plan is one of the most critical aspects of dental treatments. The purpose of this study was to compare multimedia system and conventional method in patients' selecting prosthetic treatment and the time consumed."nMaterials and Methods: Ninety patients were randomly divided into three groups. Patients in group A, once were instructed using the conventional method of dental office and once multimedia system and time was measured in seconds from the beginning of the instruction till the patient had came to decision. The patients were asked about the satisfaction of the method used for them. In group B, patients were only instructed using the conventional method, whereas they were only exposed to soft ware in group C. The data were analyzed with Paired-T-test"n(in group A and T-test and Mann-Whitney test (in groups B and C."nResult: There was a significant difference between multimedia system and conventional method in group A and also between groups B and C (P<0.001. In group A and between groups B and C, patient's satisfaction about multimedia system was better. However, in comparison between groups B and C, multimedia system did not have a significant effect in treatment selection score (P=0.08."nConclusion: Using multimedia system is recommended due to its high ability in giving answers to a large number of patient's questions as well as in terms of marketing.

  20. A method for selection of spent nuclear fuel (SNF) transportation route considering socioeconomic cost based on contingent valuation method (CVM)

    International Nuclear Information System (INIS)

    Kim, Young Sik

    2008-02-01

    A transportation of SNF may cause an additional radiation exposure to human beings. It means that the radiological risk should be estimated and managed quantitatively for the public who live near the shipments route. Before the SNF transportation is performed, the route selection is concluded based on the radiological risk estimated with RADTRAN code in existing method generally. It means the existing method for route selection is based only on the radiological health risk but there are not only the impacts related to the radiological health risk but also the socioeconomic impacts related to the cost. In this study, a new method and its numerical formula for route selection on transporting SNF is proposed based on cost estimation because there are several costs in transporting SNF. The total cost consists of radiological health cost, transportation cost, and socioeconomic cost. Each cost is defined properly to the characteristics of SNF transportation and many coefficients and variables describing the meaning of each cost are obtained or estimated through many surveys. Especially to get the socioeconomic cost, contingent valuation method (CVM) is used with a questionnaire. The socioeconomic cost estimation is the most important part of the total cost originated from transporting SNF because it is a very dominant cost in the total cost. The route selection regarding SNF transportation can be supported with the proposed method reasonably and unnecessary or exhausting controversies about the shipments could be avoided

  1. Location of airports - selected quantitative methods

    Directory of Open Access Journals (Sweden)

    Agnieszka Merkisz-Guranowska

    2016-09-01

    Full Text Available Background: The role of air transport in  the economic development of a country and its regions cannot be overestimated. The decision concerning an airport's location must be in line with the expectations of all the stakeholders involved. This article deals with the issues related to the choice of  sites where airports should be located. Methods: Two main quantitative approaches related to the issue of airport location are presented in this article, i.e. the question of optimizing such a choice and the issue of selecting the location from a predefined set. The former involves mathematical programming and formulating the problem as an optimization task, the latter, however, involves ranking the possible variations. Due to various methodological backgrounds, the authors present the advantages and disadvantages of both approaches and point to the one which currently has its own practical application. Results: Based on real-life examples, the authors present a multi-stage procedure, which renders it possible to solve the problem of airport location. Conclusions: Based on the overview of literature of the subject, the authors point to three types of approach to the issue of airport location which could enable further development of currently applied methods.

  2. Systematic differences in the response of genetic variation to pedigree and genome-based selection methods.

    Science.gov (United States)

    Heidaritabar, M; Vereijken, A; Muir, W M; Meuwissen, T; Cheng, H; Megens, H-J; Groenen, M A M; Bastiaansen, J W M

    2014-12-01

    Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60 K SNP chip with markers spaced throughout the entire chicken genome, we compared the impact of GS and traditional BLUP (best linear unbiased prediction) selection methods applied side-by-side in three different lines of egg-laying chickens. Differences were demonstrated between methods, both at the level and genomic distribution of allele frequency changes. In all three lines, the average allele frequency changes were larger with GS, 0.056 0.064 and 0.066, compared with BLUP, 0.044, 0.045 and 0.036 for lines B1, B2 and W1, respectively. With BLUP, 35 selected regions (empirical P selected regions were identified. Empirical thresholds for local allele frequency changes were determined from gene dropping, and differed considerably between GS (0.167-0.198) and BLUP (0.105-0.126). Between lines, the genomic regions with large changes in allele frequencies showed limited overlap. Our results show that GS applies selection pressure much more locally than BLUP, resulting in larger allele frequency changes. With these results, novel insights into the nature of selection on quantitative traits have been gained and important questions regarding the long-term impact of GS are raised. The rapid changes to a part of the genetic architecture, while another part may not be selected, at least in the short term, require careful consideration, especially when selection occurs before phenotypes are observed.

  3. extrap: Software to assist the selection of extrapolation methods for moving-boat ADCP streamflow measurements

    Science.gov (United States)

    Mueller, David S.

    2013-04-01

    Selection of the appropriate extrapolation methods for computing the discharge in the unmeasured top and bottom parts of a moving-boat acoustic Doppler current profiler (ADCP) streamflow measurement is critical to the total discharge computation. The software tool, extrap, combines normalized velocity profiles from the entire cross section and multiple transects to determine a mean profile for the measurement. The use of an exponent derived from normalized data from the entire cross section is shown to be valid for application of the power velocity distribution law in the computation of the unmeasured discharge in a cross section. Selected statistics are combined with empirically derived criteria to automatically select the appropriate extrapolation methods. A graphical user interface (GUI) provides the user tools to visually evaluate the automatically selected extrapolation methods and manually change them, as necessary. The sensitivity of the total discharge to available extrapolation methods is presented in the GUI. Use of extrap by field hydrographers has demonstrated that extrap is a more accurate and efficient method of determining the appropriate extrapolation methods compared with tools currently (2012) provided in the ADCP manufacturers' software.

  4. Stock selection using a hybrid MCDM approach

    Directory of Open Access Journals (Sweden)

    Tea Poklepović

    2014-12-01

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

  5. Computational Experiment Study on Selection Mechanism of Project Delivery Method Based on Complex Factors

    Directory of Open Access Journals (Sweden)

    Xiang Ding

    2014-01-01

    Full Text Available Project delivery planning is a key stage used by the project owner (or project investor for organizing design, construction, and other operations in a construction project. The main task in this stage is to select an appropriate project delivery method. In order to analyze different factors affecting the PDM selection, this paper establishes a multiagent model mainly to show how project complexity, governance strength, and market environment affect the project owner’s decision on PDM. Experiment results show that project owner usually choose Design-Build method when the project is very complex within a certain range. Besides, this paper points out that Design-Build method will be the prior choice when the potential contractors develop quickly. This paper provides the owners with methods and suggestions in terms of showing how the factors affect PDM selection, and it may improve the project performance.

  6. Systematic differences in the response of genetic variation to pedigree and genome-based selection methods

    NARCIS (Netherlands)

    Heidaritabar, M.; Vereijken, A.; Muir, W.M.; Meuwissen, T.H.E.; Cheng, H.; Megens, H.J.W.C.; Groenen, M.; Bastiaansen, J.W.M.

    2014-01-01

    Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60¿K SNP chip with markers spaced throughout the

  7. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

    Science.gov (United States)

    Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

    2017-01-01

    Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  8. A kernel-based multivariate feature selection method for microarray data classification.

    Directory of Open Access Journals (Sweden)

    Shiquan Sun

    Full Text Available High dimensionality and small sample sizes, and their inherent risk of overfitting, pose great challenges for constructing efficient classifiers in microarray data classification. Therefore a feature selection technique should be conducted prior to data classification to enhance prediction performance. In general, filter methods can be considered as principal or auxiliary selection mechanism because of their simplicity, scalability, and low computational complexity. However, a series of trivial examples show that filter methods result in less accurate performance because they ignore the dependencies of features. Although few publications have devoted their attention to reveal the relationship of features by multivariate-based methods, these methods describe relationships among features only by linear methods. While simple linear combination relationship restrict the improvement in performance. In this paper, we used kernel method to discover inherent nonlinear correlations among features as well as between feature and target. Moreover, the number of orthogonal components was determined by kernel Fishers linear discriminant analysis (FLDA in a self-adaptive manner rather than by manual parameter settings. In order to reveal the effectiveness of our method we performed several experiments and compared the results between our method and other competitive multivariate-based features selectors. In our comparison, we used two classifiers (support vector machine, [Formula: see text]-nearest neighbor on two group datasets, namely two-class and multi-class datasets. Experimental results demonstrate that the performance of our method is better than others, especially on three hard-classify datasets, namely Wang's Breast Cancer, Gordon's Lung Adenocarcinoma and Pomeroy's Medulloblastoma.

  9. Optimization of the Analytical Method Using HPLC with Fluorescence Detection to Determine Selected Polycyclic Aromatic Compounds in Clean Water Samples

    International Nuclear Information System (INIS)

    Garcia Alonso, S.; Perez Pastor, R. M.

    2013-01-01

    A study on the comparison and evaluation of 3 miniaturized extraction methods for the determination of selected PACs in clear waters is presented. Three types of liquid-liquid extraction were used for chromatographic analysis by HPLC with fluorescence detection. The main objective was the optimization and development of simple, rapid and low cost methods, minimizing the use of extracting solvent volume. The work also includes a study on the scope of the methods developed at low and high levels of concentration and intermediate precision. (Author)

  10. Variable selection methods in PLS regression - a comparison study on metabolomics data

    DEFF Research Database (Denmark)

    Karaman, İbrahim; Hedemann, Mette Skou; Knudsen, Knud Erik Bach

    . The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using LC-MS based metabolomic approach. References 1. Lê Cao KA, Rossouw D, Robert-Granié C, Besse P: A Sparse PLS for Variable Selection when...... integrated approach. Due to the high number of variables in data sets (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need to be related. Variable selection (or removal of irrelevant...... different strategies for variable selection on PLSR method were considered and compared with respect to selected subset of variables and the possibility for biological validation. Sparse PLSR [1] as well as PLSR with Jack-knifing [2] was applied to data in order to achieve variable selection prior...

  11. Evaluation of an Improved Branch-Site Likelihood Method for Detecting Positive Selection at the Molecular Level

    DEFF Research Database (Denmark)

    Zhang, Jianzhi; Nielsen, Rasmus; Yang, Ziheng

    2005-01-01

    of interest, while test 2 had acceptable false-positive rates and appeared robust against violations of model assumptions. As test 2 is a direct test of positive selection on the lineages of interest, it is referred to as the branch-site test of positive selection and is recommended for use in real data......Detecting positive Darwinian selection at the DNA sequence level has been a subject of considerable interest. However, positive selection is difficult to detect because it often operates episodically on a few amino acid sites, and the signal may be masked by negative selection. Several methods have...... been developed to test positive selection that acts on given branches (branch methods) or on a subset of sites (site methods). Recently, Yang, Z., and R. Nielsen (2002. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol. Biol. Evol. 19...

  12. A target recognition method for maritime surveillance radars based on hybrid ensemble selection

    Science.gov (United States)

    Fan, Xueman; Hu, Shengliang; He, Jingbo

    2017-11-01

    In order to improve the generalisation ability of the maritime surveillance radar, a novel ensemble selection technique, termed Optimisation and Dynamic Selection (ODS), is proposed. During the optimisation phase, the non-dominated sorting genetic algorithm II for multi-objective optimisation is used to find the Pareto front, i.e. a set of ensembles of classifiers representing different tradeoffs between the classification error and diversity. During the dynamic selection phase, the meta-learning method is used to predict whether a candidate ensemble is competent enough to classify a query instance based on three different aspects, namely, feature space, decision space and the extent of consensus. The classification performance and time complexity of ODS are compared against nine other ensemble methods using a self-built full polarimetric high resolution range profile data-set. The experimental results clearly show the effectiveness of ODS. In addition, the influence of the selection of diversity measures is studied concurrently.

  13. Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space.

    Science.gov (United States)

    Wickman, Jonas; Diehl, Sebastian; Blasius, Bernd; Klausmeier, Christopher A; Ryabov, Alexey B; Brännström, Åke

    2017-04-01

    Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

  14. Locating disease genes using Bayesian variable selection with the Haseman-Elston method

    Directory of Open Access Journals (Sweden)

    He Qimei

    2003-12-01

    Full Text Available Abstract Background We applied stochastic search variable selection (SSVS, a Bayesian model selection method, to the simulated data of Genetic Analysis Workshop 13. We used SSVS with the revisited Haseman-Elston method to find the markers linked to the loci determining change in cholesterol over time. To study gene-gene interaction (epistasis and gene-environment interaction, we adopted prior structures, which incorporate the relationship among the predictors. This allows SSVS to search in the model space more efficiently and avoid the less likely models. Results In applying SSVS, instead of looking at the posterior distribution of each of the candidate models, which is sensitive to the setting of the prior, we ranked the candidate variables (markers according to their marginal posterior probability, which was shown to be more robust to the prior. Compared with traditional methods that consider one marker at a time, our method considers all markers simultaneously and obtains more favorable results. Conclusions We showed that SSVS is a powerful method for identifying linked markers using the Haseman-Elston method, even for weak effects. SSVS is very effective because it does a smart search over the entire model space.

  15. Selective hydrogenation of phenol to cyclohexanone over Pd@CN (N-doped porous carbon): Role of catalyst reduction method

    Science.gov (United States)

    Hu, Shuo; Yang, Guangxin; Jiang, Hong; Liu, Yefei; Chen, Rizhi

    2018-03-01

    Selective phenol hydrogenation is a green and sustainable technology to produce cyclohexanone. The work focused on investigating the role of catalyst reduction method in the liquid-phase phenol hydrogenation to cyclohexanone over Pd@CN (N-doped porous carbon). A series of reduction methods including flowing hydrogen reduction, in-situ reaction reduction and liquid-phase reduction were designed and performed. The results highlighted that the reduction method significantly affected the catalytic performance of Pd@CN in the liquid-phase hydrogenation of phenol to cyclohexanone, and the liquid-phase reduction with the addition of appropriate amount of phenol was highly efficient to improve the catalytic activity of Pd@CN. The influence mechanism was explored by a series of characterizations. The results of TEM, XPS and CO chemisorption confirmed that the reduction method mainly affected the size, surface composition and dispersion of Pd in the CN material. The addition of phenol during the liquid-phase reduction could inhibit the aggregation of Pd NPs and promote the reduction of Pd (2+), and then improved the catalytic activity of Pd@CN. The work would aid the development of high-performance Pd@CN catalysts for selective phenol hydrogenation.

  16. A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

    Science.gov (United States)

    Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

    2017-07-01

    Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant

  17. Systems and Methods for Fabricating Structures Including Metallic Glass-Based Materials Using Low Pressure Casting

    Science.gov (United States)

    Hofmann, Douglas C. (Inventor); Kennett, Andrew (Inventor)

    2018-01-01

    Systems and methods to fabricate objects including metallic glass-based materials using low-pressure casting techniques are described. In one embodiment, a method of fabricating an object that includes a metallic glass-based material includes: introducing molten alloy into a mold cavity defined by a mold using a low enough pressure such that the molten alloy does not conform to features of the mold cavity that are smaller than 100 microns; and cooling the molten alloy such that it solidifies, the solid including a metallic glass-based material.

  18. Robust gene selection methods using weighting schemes for microarray data analysis.

    Science.gov (United States)

    Kang, Suyeon; Song, Jongwoo

    2017-09-02

    A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

  19. A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection

    Science.gov (United States)

    Sabourin, Jeremy A; Valdar, William; Nobel, Andrew B

    2015-01-01

    Summary We describe a simple, computationally effcient, permutation-based procedure for selecting the penalty parameter in LASSO penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study and an analysis of real biomedical data sets in which permutation selection is compared with selection based on the following: cross-validation (CV), the Bayesian information criterion (BIC), Scaled Sparse Linear Regression, and a selection method based on recently developed testing procedures for the LASSO. PMID:26243050

  20. NON-CONVENTIONAL MACHINING PROCESSES SELECTION USING MULTI-OBJECTIVE OPTIMIZATION ON THE BASIS OF RATIO ANALYSIS METHOD

    Directory of Open Access Journals (Sweden)

    MILOŠ MADIĆ

    2015-11-01

    Full Text Available The role of non-conventional machining processes (NCMPs in today’s manufacturing environment has been well acknowledged. For effective utilization of the capabilities and advantages of different NCMPs, selection of the most appropriate NCMP for a given machining application requires consideration of different conflicting criteria. The right choice of the NCMP is critical to the success and competitiveness of the company. As the NCMP selection problem involves consideration of different conflicting criteria, of different relative importance, the multi-criteria decision making (MCDM methods are very useful in systematical selection of the most appropriate NCMP. This paper presents the application of a recent MCDM method, i.e., the multi-objective optimization on the basis of ratio analysis (MOORA method to solve NCMP selection which has been defined considering different performance criteria of four most widely used NCMPs. In order to determine the relative significance of considered quality criteria a pair-wise comparison matrix of the analytic hierarchy process was used. The results obtained using the MOORA method showed perfect correlation with those obtained by the technique for order preference by similarity to ideal solution (TOPSIS method which proves the applicability and potentiality of this MCDM method for solving complex NCMP selection problems.

  1. Solar cells, structures including organometallic halide perovskite monocrystalline films, and methods of preparation thereof

    KAUST Repository

    Bakr, Osman; Peng, Wei; Wang, Lingfei

    2017-01-01

    Embodiments of the present disclosure provide for solar cells including an organometallic halide perovskite monocrystalline film (see fig. 1.1B), other devices including the organometallic halide perovskite monocrystalline film, methods of making

  2. Study on the partner selecting method of strategic alliance in high and new technology enterprises

    Institute of Scientific and Technical Information of China (English)

    王宏起; 唐宇; 迟运领

    2004-01-01

    A successful and effective strategic alliance involves many factors, of which selecting a proper partner is the most important factor to achieve the success of the alliance. In view of the characteristics of strategic alliance in high and new technology enterprises and according to the analysis on the standards of partner selecting and the factors of the success of alliance, this paper does some deeper research on the partner selecting and the alliance evaluation process from the perspective of different strategic levels by using a fuzzy comprehensive evaluating method, thus providing a method to select the alliance partner for high and new technology enterprises in China.

  3. Method of generating intense nuclear polarized beams by selective photodetachment of negative ions

    International Nuclear Information System (INIS)

    Hershcovitch, A.

    1986-01-01

    A novel method for production of nuclear polarized negative hydrogen ions by selective neutralization with a laser of negative hydrogen ions in a magnetic field is described. This selectivity is possible since a final state of the neutralized atom, and hence the neutralization energy, depends on its nuclear polarization. The main advantages of this scheme are the availability of multi-ampere negative ion sources and the possibility of neutralizing negative ions with very high efficiency. An assessment of the required laser power indicates that this method is in principle feasible with today's technology

  4. Selected nutrient contents, fatty acid composition, including conjugated linoleic acid, and retention values in separable lean from lamb rib loins as affected by external fat and cooking method.

    Science.gov (United States)

    Badiani, Anna; Montellato, Lara; Bochicchio, Davide; Anfossi, Paola; Zanardi, Emanuela; Maranesi, Magda

    2004-08-11

    Proximate composition and fatty acid profile, conjugated linoleic acid (CLA) isomers included, were determined in separable lean of raw and cooked lamb rib loins. The cooking methods compared, which were also investigated for cooking yields and true nutrient retention values, were dry heating of fat-on cuts and moist heating of fat-off cuts; the latter method was tested as a sort of dietetic approach against the more traditional former type. With significantly (P cooking losses, dry heating of fat-on rib-loins produced slightly (although only rarely significantly) higher retention values for all of the nutrients considered, including CLA isomers. On the basis of the retention values obtained, both techniques led to a minimum migration of lipids into the separable lean, which was higher (P cooking of the class of CLA isomers (including that of the nutritionally most important isomer cis-9,trans-11) was more similar to that of the monounsaturated than the polyunsaturated fatty acids.

  5. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    Directory of Open Access Journals (Sweden)

    Jun-He Yang

    2017-01-01

    Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  6. The multi-objective decision making methods based on MULTIMOORA and MOOSRA for the laptop selection problem

    Science.gov (United States)

    Aytaç Adalı, Esra; Tuş Işık, Ayşegül

    2017-06-01

    A decision making process requires the values of conflicting objectives for alternatives and the selection of the best alternative according to the needs of decision makers. Multi-objective optimization methods may provide solution for this selection. In this paper it is aimed to present the laptop selection problem based on MOORA plus full multiplicative form (MULTIMOORA) and multi-objective optimization on the basis of simple ratio analysis (MOOSRA) which are relatively new multi-objective optimization methods. The novelty of this paper is solving this problem with the MULTIMOORA and MOOSRA methods for the first time.

  7. Methods for measurement of durability parameters

    DEFF Research Database (Denmark)

    Hansen, Ernst Jan De Place

    1996-01-01

    Present selected methods for measurement of durabilty parameters relating to chlorides, corrosion, moisture and freeze-thaw, primarly on concrete. Advantages and drawbacks of the different methods are included.......Present selected methods for measurement of durabilty parameters relating to chlorides, corrosion, moisture and freeze-thaw, primarly on concrete. Advantages and drawbacks of the different methods are included....

  8. Research on Big Data Attribute Selection Method in Submarine Optical Fiber Network Fault Diagnosis Database

    Directory of Open Access Journals (Sweden)

    Chen Ganlang

    2017-11-01

    Full Text Available At present, in the fault diagnosis database of submarine optical fiber network, the attribute selection of large data is completed by detecting the attributes of the data, the accuracy of large data attribute selection cannot be guaranteed. In this paper, a large data attribute selection method based on support vector machines (SVM for fault diagnosis database of submarine optical fiber network is proposed. Mining large data in the database of optical fiber network fault diagnosis, and calculate its attribute weight, attribute classification is completed according to attribute weight, so as to complete attribute selection of large data. Experimental results prove that ,the proposed method can improve the accuracy of large data attribute selection in fault diagnosis database of submarine optical fiber network, and has high use value.

  9. Simulation-based investigation of the paired-gear method in cod-end selectivity studies

    DEFF Research Database (Denmark)

    Herrmann, Bent; Frandsen, Rikke; Holst, René

    2007-01-01

    In this paper, the paired-gear and covered cod-end methods for estimating the selectivity of trawl cod-ends are compared. A modified version of the cod-end selectivity simulator PRESEMO is used to simulate the data that would be collected from a paired-gear experiment where the test cod-end also ...

  10. Novel Selective Detection Method of Tumor Angiogenesis Factors Using Living Nano-Robots.

    Science.gov (United States)

    Al-Fandi, Mohamed; Alshraiedeh, Nida; Owies, Rami; Alshdaifat, Hala; Al-Mahaseneh, Omamah; Al-Tall, Khadijah; Alawneh, Rawan

    2017-07-14

    This paper reports a novel self-detection method for tumor cells using living nano-robots. These living robots are a nonpathogenic strain of E. coli bacteria equipped with naturally synthesized bio-nano-sensory systems that have an affinity to VEGF, an angiogenic factor overly-expressed by cancer cells. The VEGF-affinity/chemotaxis was assessed using several assays including the capillary chemotaxis assay, chemotaxis assay on soft agar, and chemotaxis assay on solid agar. In addition, a microfluidic device was developed to possibly discover tumor cells through the overexpressed vascular endothelial growth factor (VEGF). Various experiments to study the sensing characteristic of the nano-robots presented a strong response toward the VEGF. Thus, a new paradigm of selective targeting therapies for cancer can be advanced using swimming E. coli as self-navigator miniaturized robots as well as drug-delivery vehicles.

  11. A Method to Select Software Test Cases in Consideration of Past Input Sequence

    International Nuclear Information System (INIS)

    Kim, Hee Eun; Kim, Bo Gyung; Kang, Hyun Gook

    2015-01-01

    In the Korea Nuclear I and C Systems (KNICS) project, the software for the fully-digitalized reactor protection system (RPS) was developed under a strict procedure. Even though the behavior of the software is deterministic, the randomness of input sequence produces probabilistic behavior of software. A software failure occurs when some inputs to the software occur and interact with the internal state of the digital system to trigger a fault that was introduced into the software during the software lifecycle. In this paper, the method to select test set for software failure probability estimation is suggested. This test set reflects past input sequence of software, which covers all possible cases. In this study, the method to select test cases for software failure probability quantification was suggested. To obtain profile of paired state variables, relationships of the variables need to be considered. The effect of input from human operator also have to be considered. As an example, test set of PZR-PR-Lo-Trip logic was examined. This method provides framework for selecting test cases of safety-critical software

  12. Method for selecting FBR development strategies in the presence of uncertainty

    International Nuclear Information System (INIS)

    Fraley, D.W.; Burnham, J.B.

    1981-12-01

    This report describes the methods used to probabilistically analyze data related to the uranium supply the FBR's competitive dates, development strategies' time and costs, and economic benefits. It also describes the econometric methods used to calculate the economic risks of mistiming the development. Seven strategies for developing the FBR are analyzed. The various measures of a strategy's performance - timing, costs, benefits, and risks - are combined into several criteria which are used to evaluate the seven strategies. Methods are described for selecting a strategy based on a number of alternative criteria

  13. Selective laser etching or ablation for fabrication of devices

    KAUST Repository

    Buttner, Ulrich; Salama, Khaled N.; Sapsanis, Christos

    2017-01-01

    Methods of fabricating devices vial selective laser etching are provided. The methods can include selective laser etching of a portion of a metal layer, e.g. using a laser light source having a wavelength of 1,000 nm to 1,500 nm. The methods can

  14. Ion-selective electrode reviews

    CERN Document Server

    Thomas, J D R

    1982-01-01

    Ion-Selective Electrode Reviews, Volume 3, provides a review of articles on ion-selective electrodes (ISEs). The volume begins with an article on methods based on titration procedures for surfactant analysis, which have been developed for discrete batch operation and for continuous AutoAnalyser use. Separate chapters deal with detection limits of ion-selective electrodes; the possibility of using inorganic ion-exchange materials as ion-sensors; and the effect of solvent on potentials of cells with ion-selective electrodes. Also included is a chapter on advances in calibration procedures, the d

  15. A novel knot selection method for the error-bounded B-spline curve fitting of sampling points in the measuring process

    International Nuclear Information System (INIS)

    Liang, Fusheng; Zhao, Ji; Ji, Shijun; Zhang, Bing; Fan, Cheng

    2017-01-01

    The B-spline curve has been widely used in the reconstruction of measurement data. The error-bounded sampling points reconstruction can be achieved by the knot addition method (KAM) based B-spline curve fitting. In KAM, the selection pattern of initial knot vector has been associated with the ultimate necessary number of knots. This paper provides a novel initial knots selection method to condense the knot vector required for the error-bounded B-spline curve fitting. The initial knots are determined by the distribution of features which include the chord length (arc length) and bending degree (curvature) contained in the discrete sampling points. Firstly, the sampling points are fitted into an approximate B-spline curve Gs with intensively uniform knot vector to substitute the description of the feature of the sampling points. The feature integral of Gs is built as a monotone increasing function in an analytic form. Then, the initial knots are selected according to the constant increment of the feature integral. After that, an iterative knot insertion (IKI) process starting from the initial knots is introduced to improve the fitting precision, and the ultimate knot vector for the error-bounded B-spline curve fitting is achieved. Lastly, two simulations and the measurement experiment are provided, and the results indicate that the proposed knot selection method can reduce the number of ultimate knots available. (paper)

  16. Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading.

    Science.gov (United States)

    Sahran, Shahnorbanun; Albashish, Dheeb; Abdullah, Azizi; Shukor, Nordashima Abd; Hayati Md Pauzi, Suria

    2018-04-18

    Feature selection (FS) methods are widely used in grading and diagnosing prostate histopathological images. In this context, FS is based on the texture features obtained from the lumen, nuclei, cytoplasm and stroma, all of which are important tissue components. However, it is difficult to represent the high-dimensional textures of these tissue components. To solve this problem, we propose a new FS method that enables the selection of features with minimal redundancy in the tissue components. We categorise tissue images based on the texture of individual tissue components via the construction of a single classifier and also construct an ensemble learning model by merging the values obtained by each classifier. Another issue that arises is overfitting due to the high-dimensional texture of individual tissue components. We propose a new FS method, SVM-RFE(AC), that integrates a Support Vector Machine-Recursive Feature Elimination (SVM-RFE) embedded procedure with an absolute cosine (AC) filter method to prevent redundancy in the selected features of the SV-RFE and an unoptimised classifier in the AC. We conducted experiments on H&E histopathological prostate and colon cancer images with respect to three prostate classifications, namely benign vs. grade 3, benign vs. grade 4 and grade 3 vs. grade 4. The colon benchmark dataset requires a distinction between grades 1 and 2, which are the most difficult cases to distinguish in the colon domain. The results obtained by both the single and ensemble classification models (which uses the product rule as its merging method) confirm that the proposed SVM-RFE(AC) is superior to the other SVM and SVM-RFE-based methods. We developed an FS method based on SVM-RFE and AC and successfully showed that its use enabled the identification of the most crucial texture feature of each tissue component. Thus, it makes possible the distinction between multiple Gleason grades (e.g. grade 3 vs. grade 4) and its performance is far superior to

  17. METHODS OF SELECTING THE EFFECTIVE MODELS OF BUILDINGS REPROFILING PROJECTS

    Directory of Open Access Journals (Sweden)

    Александр Иванович МЕНЕЙЛЮК

    2016-02-01

    Full Text Available The article highlights the important task of project management in reprofiling of buildings. It is expedient to pay attention to selecting effective engineering solutions to reduce the duration and cost reduction at the project management in the construction industry. This article presents a methodology for the selection of efficient organizational and technical solutions for the reconstruction of buildings reprofiling. The method is based on a compilation of project variants in the program Microsoft Project and experimental statistical analysis using the program COMPEX. The introduction of this technique in the realigning of buildings allows choosing efficient models of projects, depending on the given constraints. Also, this technique can be used for various construction projects.

  18. Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures.

    Science.gov (United States)

    Bastiaansen, John W M; Coster, Albart; Calus, Mario P L; van Arendonk, Johan A M; Bovenhuis, Henk

    2012-01-24

    Genomic selection has become an important tool in the genetic improvement of animals and plants. The objective of this study was to investigate the impacts of breeding value estimation method, reference population structure, and trait genetic architecture, on long-term response to genomic selection without updating marker effects. Three methods were used to estimate genomic breeding values: a BLUP method with relationships estimated from genome-wide markers (GBLUP), a Bayesian method, and a partial least squares regression method (PLSR). A shallow (individuals from one generation) or deep reference population (individuals from five generations) was used with each method. The effects of the different selection approaches were compared under four different genetic architectures for the trait under selection. Selection was based on one of the three genomic breeding values, on pedigree BLUP breeding values, or performed at random. Selection continued for ten generations. Differences in long-term selection response were small. For a genetic architecture with a very small number of three to four quantitative trait loci (QTL), the Bayesian method achieved a response that was 0.05 to 0.1 genetic standard deviation higher than other methods in generation 10. For genetic architectures with approximately 30 to 300 QTL, PLSR (shallow reference) or GBLUP (deep reference) had an average advantage of 0.2 genetic standard deviation over the Bayesian method in generation 10. GBLUP resulted in 0.6% and 0.9% less inbreeding than PLSR and BM and on average a one third smaller reduction of genetic variance. Responses in early generations were greater with the shallow reference population while long-term response was not affected by reference population structure. The ranking of estimation methods was different with than without selection. Under selection, applying GBLUP led to lower inbreeding and a smaller reduction of genetic variance while a similar response to selection was

  19. Experimental Evaluation of Suitability of Selected Multi-Criteria Decision-Making Methods for Large-Scale Agent-Based Simulations.

    Science.gov (United States)

    Tučník, Petr; Bureš, Vladimír

    2016-01-01

    Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.

  20. Entropy Based Test Point Evaluation and Selection Method for Analog Circuit Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2014-01-01

    Full Text Available By simplifying tolerance problem and treating faulty voltages on different test points as independent variables, integer-coded table technique is proposed to simplify the test point selection process. Usually, simplifying tolerance problem may induce a wrong solution while the independence assumption will result in over conservative result. To address these problems, the tolerance problem is thoroughly considered in this paper, and dependency relationship between different test points is considered at the same time. A heuristic graph search method is proposed to facilitate the test point selection process. First, the information theoretic concept of entropy is used to evaluate the optimality of test point. The entropy is calculated by using the ambiguous sets and faulty voltage distribution, determined by component tolerance. Second, the selected optimal test point is used to expand current graph node by using dependence relationship between the test point and graph node. Simulated results indicate that the proposed method more accurately finds the optimal set of test points than other methods; therefore, it is a good solution to minimize the size of the test point set. To simplify and clarify the proposed method, only catastrophic and some specific parametric faults are discussed in this paper.

  1. Solar cells, structures including organometallic halide perovskite monocrystalline films, and methods of preparation thereof

    KAUST Repository

    Bakr, Osman M.

    2017-03-02

    Embodiments of the present disclosure provide for solar cells including an organometallic halide perovskite monocrystalline film (see fig. 1.1B), other devices including the organometallic halide perovskite monocrystalline film, methods of making organometallic halide perovskite monocrystalline film, and the like.

  2. Analysis of a wavelength selectable cascaded DFB laser based on the transfer matrix method

    International Nuclear Information System (INIS)

    Xie Hongyun; Chen Liang; Shen Pei; Sun Botao; Wang Renqing; Xiao Ying; You Yunxia; Zhang Wanrong

    2010-01-01

    A novel cascaded DFB laser, which consists of two serial gratings to provide selectable wavelengths, is presented and analyzed by the transfer matrix method. In this method, efficient facet reflectivity is derived from the transfer matrix built for each serial section and is then used to simulate the performance of the novel cascaded DFB laser through self-consistently solving the gain equation, the coupled wave equation and the current continuity equations. The simulations prove the feasibility of this kind of wavelength selectable laser and a corresponding designed device with two selectable wavelengths of 1.51 μm and 1.53 μm is realized by experiments on InP-based multiple quantum well structure. (semiconductor devices)

  3. Classical mechanics including an introduction to the theory of elasticity

    CERN Document Server

    Hentschke, Reinhard

    2017-01-01

    This textbook teaches classical mechanics as one of the foundations of physics. It describes the mechanical stability and motion in physical systems ranging from the molecular to the galactic scale. Aside from the standard topics of mechanics in the physics curriculum, this book includes an introduction to the theory of elasticity and its use in selected modern engineering applications, e.g. dynamic mechanical analysis of viscoelastic materials. The text also covers many aspects of numerical mechanics, ranging from the solution of ordinary differential equations, including molecular dynamics simulation of many particle systems, to the finite element method. Attendant Mathematica programs or parts thereof are provided in conjunction with selected examples. Numerous links allow the reader to connect to related subjects and research topics. Among others this includes statistical mechanics (separate chapter), quantum mechanics, space flight, galactic dynamics, friction, and vibration spectroscopy. An introductory...

  4. Methods of selecting factors in the analysis of the real estates market

    OpenAIRE

    Jasińska, Elżbieta; Preweda, Edward

    2006-01-01

    In the paper the problem of selecting the method of choosing factors in factorial analysis is presented. For the database of 61 real estates the process of singling out the factors was carried out with the use of all the methods proposed in the STATISTICA 6.0 pack. A particular attention was paid on the number of differentiated factors and the efficiency of subsequent methods for the analysis of the real estates market. Edward Preweda

  5. SORIOS – A method for evaluating and selecting environmental certificates and labels

    DEFF Research Database (Denmark)

    Kikkenborg Pedersen, Dennis; Dukovska-Popovska, Iskra; Ola Strandhagen, Jan

    2012-01-01

    This paper presents a general method for evaluating and selecting environmental certificates and labels for companies to use on products and services. The method is developed based on a case study using a Grounded Theory approach. The result is a generalized six-step method that features an initial...... searching strategy and an evaluation model that weighs the prerequisites, rewards and the organization of certificate or label against the strategic needs of a company....

  6. Aplication of AHP method in partner's selection process for supply chain development

    Directory of Open Access Journals (Sweden)

    Barac Nada

    2012-06-01

    Full Text Available The process of developing a supply chain is long and complex. with many restrictions and obstacles that accompany it. In this paper the authors focus on the first stage in developing the supply chain and the selection process and selection of partners. This phase of the development significantly affect the competitive position of the supply chain and create value for the consumer. Selected partners or 'links' of the supply chain influence the future performance of the chain which points to the necessity of full commitment to this process. The process of selection and choice of partner is conditioned by the key criteria that are used on that occasion. The use of inadequate criteria may endanger the whole process of building a supply chain partner selection through inadequate future supply chain needs. This paper is an analysis of partner selection based on key criteria used by managers in Serbia. For this purpose we used the AHP method. the results show that these are the top ranked criteria in terms of managers.

  7. A NEW METHOD HIGHLIGHTING PSYCHOMOTOR SKILLS AND COGNITIVE ATTRIBUTES IN ATHLETE SELECTIONS

    Directory of Open Access Journals (Sweden)

    Engin Sagdilek

    2015-05-01

    the athletes improved their points around 20%, while no improvement was observed for the non-athletes. Non-athletes scored the worst points for the pink balls and during the second trial a minor decrease in their points was observed. Table tennis athletes demonstrated the highest improvement in points in the second trial for the pink balls. The findings of the selective action array developed for this study showed that in the first phase, and especially in sports played using rackets, the development of the sustenance of attention and visual perception could be attained rapidly. Thus, by making changes in the number and color of the balls as well as differences in actions to be taken, this method could be a new approach to be used for other sports to include the cognitive attributes in selection process of the athletes.

  8. A DYNAMIC FEATURE SELECTION METHOD FOR DOCUMENT RANKING WITH RELEVANCE FEEDBACK APPROACH

    Directory of Open Access Journals (Sweden)

    K. Latha

    2010-07-01

    Full Text Available Ranking search results is essential for information retrieval and Web search. Search engines need to not only return highly relevant results, but also be fast to satisfy users. As a result, not all available features can be used for ranking, and in fact only a small percentage of these features can be used. Thus, it is crucial to have a feature selection mechanism that can find a subset of features that both meets latency requirements and achieves high relevance. In this paper we describe a 0/1 knapsack procedure for automatically selecting features to use within Generalization model for Document Ranking. We propose an approach for Relevance Feedback using Expectation Maximization method and evaluate the algorithm on the TREC Collection for describing classes of feedback textual information retrieval features. Experimental results, evaluated on standard TREC-9 part of the OHSUMED collections, show that our feature selection algorithm produces models that are either significantly more effective than, or equally effective as, models such as Markov Random Field model, Correlation Co-efficient and Count Difference method

  9. Closed-form solutions for linear regulator-design of mechanical systems including optimal weighting matrix selection

    Science.gov (United States)

    Hanks, Brantley R.; Skelton, Robert E.

    1991-01-01

    This paper addresses the restriction of Linear Quadratic Regulator (LQR) solutions to the algebraic Riccati Equation to design spaces which can be implemented as passive structural members and/or dampers. A general closed-form solution to the optimal free-decay control problem is presented which is tailored for structural-mechanical systems. The solution includes, as subsets, special cases such as the Rayleigh Dissipation Function and total energy. Weighting matrix selection is a constrained choice among several parameters to obtain desired physical relationships. The closed-form solution is also applicable to active control design for systems where perfect, collocated actuator-sensor pairs exist. Some examples of simple spring mass systems are shown to illustrate key points.

  10. A general method for selection of riboflavin-overproducing food grade micro-organisms

    Directory of Open Access Journals (Sweden)

    Rutten Ger

    2006-07-01

    Full Text Available Abstract Background This study describes a strategy to select and isolate spontaneous riboflavin-overproducing strains of Lactobacillus (Lb. plantarum, Leuconostoc (Lc. mesenteroides and Propionibacterium (P. freudenreichii. Results The toxic riboflavin analogue roseoflavin was used to isolate natural riboflavin-overproducing variants of the food grade micro-organisms Lb. plantarum, Lc. mesenteroides and P. freudenreichii strains. The method was successfully employed for strains of all three species. The mutation(s responsible for the observed overproduction of riboflavin were identified for isolates of two species. Conclusion Selection for spontaneous roseoflavin-resistant mutants was found to be a reliable method to obtain natural riboflavin-overproducing strains of a number of species commonly used in the food industry. This study presents a convenient method for deriving riboflavin-overproducing strains of bacterial starter cultures, which are currently used in the food industry, by a non-recombinant methodology. Use of such starter strains can be exploited to increase the vitamin content in certain food products.

  11. Method for selection of optimal road safety composite index with examples from DEA and TOPSIS method.

    Science.gov (United States)

    Rosić, Miroslav; Pešić, Dalibor; Kukić, Dragoslav; Antić, Boris; Božović, Milan

    2017-01-01

    Concept of composite road safety index is a popular and relatively new concept among road safety experts around the world. As there is a constant need for comparison among different units (countries, municipalities, roads, etc.) there is need to choose an adequate method which will make comparison fair to all compared units. Usually comparisons using one specific indicator (parameter which describes safety or unsafety) can end up with totally different ranking of compared units which is quite complicated for decision maker to determine "real best performers". Need for composite road safety index is becoming dominant since road safety presents a complex system where more and more indicators are constantly being developed to describe it. Among wide variety of models and developed composite indexes, a decision maker can come to even bigger dilemma than choosing one adequate risk measure. As DEA and TOPSIS are well-known mathematical models and have recently been increasingly used for risk evaluation in road safety, we used efficiencies (composite indexes) obtained by different models, based on DEA and TOPSIS, to present PROMETHEE-RS model for selection of optimal method for composite index. Method for selection of optimal composite index is based on three parameters (average correlation, average rank variation and average cluster variation) inserted into a PROMETHEE MCDM method in order to choose the optimal one. The model is tested by comparing 27 police departments in Serbia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Including climate change in energy investment decisions

    International Nuclear Information System (INIS)

    Ybema, J.R.; Boonekamp, P.G.M.; Smit, J.T.J.

    1995-08-01

    To properly take climate change into account in the analysis of energy investment decisions, it is required to apply decision analysis methods that are capable of considering the specific characteristics of climate change (large uncertainties, long term horizon). Such decision analysis methods do exist. They can explicitly include evolving uncertainties, multi-stage decisions, cumulative effects and risk averse attitudes. Various methods are considered in this report and two of these methods have been selected: hedging calculations and sensitivity analysis. These methods are applied to illustrative examples, and its limitations are discussed. The examples are (1a) space heating and hot water for new houses from a private investor perspective and (1b) as example (1a) but from a government perspective, (2) electricity production with an integrated coal gasification combined cycle (ICGCC) with or without CO 2 removal, and (3) national energy strategy to hedge for climate change. 9 figs., 21 tabs., 42 refs., 1 appendix

  13. Studies on the matched potential method for determining the selectivity coefficients of ion-selective electrodes based on neutral ionophores: experimental and theoretical verification.

    Science.gov (United States)

    Tohda, K; Dragoe, D; Shibata, M; Umezawa, Y

    2001-06-01

    A theory is presented that describes the matched potential method (MPM) for the determination of the potentiometric selectivity coefficients (KA,Bpot) of ion-selective electrodes for two ions with any charge. This MPM theory is based on electrical diffuse layers on both the membrane and the aqueous side of the interface, and is therefore independent of the Nicolsky-Eisenman equation. Instead, the Poisson equation is used and a Boltzmann distribution is assumed with respect to all charged species, including primary, interfering and background electrolyte ions located at the diffuse double layers. In this model, the MPM-selectivity coefficients of ions with equal charge (ZA = ZB) are expressed as the ratio of the concentrations of the primary and interfering ions in aqueous solutions at which the same amounts of the primary and interfering ions permselectively extracted into the membrane surface. For ions with unequal charge (ZA not equal to ZB), the selectivity coefficients are expressed as a function not only of the amounts of the primary and interfering ions permeated into the membrane surface, but also of the primary ion concentration in the initial reference solution and the delta EMF value. Using the measured complexation stability constants and single ion distribution coefficients for the relevant systems, the corresponding MPM selectivity coefficients can be calculated from the developed MPM theory. It was found that this MPM theory is capable of accurately and precisely predicting the MPM selectivity coefficients for a series of ion-selective electrodes (ISEs) with representative ionophore systems, which are generally in complete agreement with independently determined MPM selectivity values from the potentiometric measurements. These results also conclude that the assumption for the Boltzmann distribution was in fact valid in the theory. The recent critical papers on MPM have pointed out that because the MPM selectivity coefficients are highly concentration

  14. Earthquake analysis of structures including structure-soil interaction by a substructure method

    International Nuclear Information System (INIS)

    Chopra, A.K.; Guttierrez, J.A.

    1977-01-01

    A general substructure method for analysis of response of nuclear power plant structures to earthquake ground motion, including the effects of structure-soil interaction, is summarized. The method is applicable to complex structures idealized as finite element systems and the soil region treated as either a continuum, for example as a viscoelastic halfspace, or idealized as a finite element system. The halfspace idealization permits reliable analysis for sites where essentially similar soils extend to large depths and there is no rigid boundary such as soil-rock interface. For sites where layers of soft soil are underlain by rock at shallow depth, finite element idealization of the soil region is appropriate; in this case, the direct and substructure methods would lead to equivalent results but the latter provides the better alternative. Treating the free field motion directly as the earthquake input in the substructure eliminates the deconvolution calculations and the related assumption-regarding type and direction of earthquake waves-required in the direct method. (Auth.)

  15. Selection of the Bank Investment Strategy on the Basis of the Hierarchy Analysis Method

    Directory of Open Access Journals (Sweden)

    Zhytar Maksym O.

    2014-02-01

    Full Text Available The goal of the article lies in identification of a methodical approach to selection of the investment strategy of banks on the basis of factors of its formation with the use of the hierarchy analysis method. Factors of formation of the bank’s investment strategy were identified in the result of the study. The article demonstrates that selection of the investment strategy of the bank could be efficiently realised on the basis of the hierarchy analysis method, which is the most popular under conditions of a multi-criteria assessment of the search for optimal solution of the set task. The article offers a hierarchical structure of decision making, which could be a basis of selection of the bank’s investment strategy with consideration of the institutional flexibility. The prospect of further study in this direction is development of an optimisation model of the bank’s investment portfolio with consideration of not only institutional, but also market flexibility of decision making.

  16. A systematic and practical method for selecting systems engineering tools

    DEFF Research Database (Denmark)

    Munck, Allan; Madsen, Jan

    2017-01-01

    analyses of the actual needs and the available tools. Grouping needs into categories, allow us to obtain a comprehensive set of requirements for the tools. The entire model-based systems engineering discipline was categorized for a modeling tool case to enable development of a tool specification...... in successful operation since 2013 at GN Hearing. We further utilized the method to select a set of tools that we used on pilot cases at GN Hearing for modeling, simulating and formally verifying embedded systems.......The complexity of many types of systems has grown considerably over the last decades. Using appropriate systems engineering tools therefore becomes increasingly important. Starting the tool selection process can be intimidating because organizations often only have a vague idea about what they need...

  17. Application of Bayesian methods to habitat selection modeling of the northern spotted owl in California: new statistical methods for wildlife research

    Science.gov (United States)

    Howard B. Stauffer; Cynthia J. Zabel; Jeffrey R. Dunk

    2005-01-01

    We compared a set of competing logistic regression habitat selection models for Northern Spotted Owls (Strix occidentalis caurina) in California. The habitat selection models were estimated, compared, evaluated, and tested using multiple sample datasets collected on federal forestlands in northern California. We used Bayesian methods in interpreting...

  18. Research on Methods for Discovering and Selecting Cloud Infrastructure Services Based on Feature Modeling

    Directory of Open Access Journals (Sweden)

    Huamin Zhu

    2016-01-01

    Full Text Available Nowadays more and more cloud infrastructure service providers are providing large numbers of service instances which are a combination of diversified resources, such as computing, storage, and network. However, for cloud infrastructure services, the lack of a description standard and the inadequate research of systematic discovery and selection methods have exposed difficulties in discovering and choosing services for users. First, considering the highly configurable properties of a cloud infrastructure service, the feature model method is used to describe such a service. Second, based on the description of the cloud infrastructure service, a systematic discovery and selection method for cloud infrastructure services are proposed. The automatic analysis techniques of the feature model are introduced to verify the model’s validity and to perform the matching of the service and demand models. Finally, we determine the critical decision metrics and their corresponding measurement methods for cloud infrastructure services, where the subjective and objective weighting results are combined to determine the weights of the decision metrics. The best matching instances from various providers are then ranked by their comprehensive evaluations. Experimental results show that the proposed methods can effectively improve the accuracy and efficiency of cloud infrastructure service discovery and selection.

  19. Using the AHP Method to Select an ERP System for an SME Manufacturing Company

    Directory of Open Access Journals (Sweden)

    Kłos Sławomir

    2014-09-01

    Full Text Available This paper proposes the application of the Analytic Hierarchy Process method to support decision making regarding the selection of an Enterprise Resource Planning system in a manufacturing company. The main assumption of the work is that the management of the selection of an ERP system should consider that the most important selection criteria are concerned with the functionality of the ERP system. Besides this, the aspects of total cost of ownership, technical support and implementation time or vendor experience are taken into consideration to guarantee a successful ERP implementation. The proposed procedure of an ERP system selection is dedicated for small and medium manufacturing enterprises. A structure of attributes for the AHP method is proposed on the basis of an analysis and identification of critical success factors. Different kinds of production (make-to-stock, make-to-order and engineer-to-order are taken into consideration. Illustrative examples are also given.

  20. The measurement of acetanilide in plasma by spectrophotometric and selected ion monitoring methods.

    Science.gov (United States)

    Baty, J D; Playfer, J; Evans, D A; Lamb, J

    1977-08-01

    Plasma samples from volunteers who had received an oral dose of acetanilide have been analysed by gas chromatography mass spectrometry and ultraviolet absorption techniques. The gas chromatography mass spectrometry method involved extraction of the plasma and analysis of the acetanilide using selected ion monitoring with a deuterated internal standard. In the ultraviolet method the plasma was hydrolysed with acid to convert the acetanilide to aniline, and this compound was diazotized and coupled with N-1-naphthylethylene-diamine. The absorbance of the resulting complex was read at 550 nm. Acetanilide levels in plasma determined by the selected ion monitoring method were significantly lower than those measured by spectrophotometry. Pharmacokinetic data calculated from the results obtained using these two assays are very different and illustrate the need for an accurate and specific method of analysis. The major metabolites of acetanilide are shown not to interfere with these assays and the results suggest the possible presence of a new metabolite of acetanilide.

  1. A comparison of two methods for prediction of response and rates of inbreeding in selected populations with the results obtained in two selection experiments

    Directory of Open Access Journals (Sweden)

    Verrier Etienne

    2005-05-01

    Full Text Available Abstract Selection programmes are mainly concerned with increasing genetic gain. However, short-term progress should not be obtained at the expense of the within-population genetic variability. Different prediction models for the evolution within a small population of the genetic mean of a selected trait, its genetic variance and its inbreeding have been developed but have mainly been validated through Monte Carlo simulation studies. The purpose of this study was to compare theoretical predictions to experimental results. Two deterministic methods were considered, both grounded on a polygenic additive model. Differences between theoretical predictions and experimental results arise from differences between the true and the assumed genetic model, and from mathematical simplifications applied in the prediction methods. Two sets of experimental lines of chickens were used in this study: the Dutch lines undergoing true truncation mass selection, the other lines (French undergoing mass selection with a restriction on the representation of the different families. This study confirmed, on an experimental basis, that modelling is an efficient approach to make useful predictions of the evolution of selected populations although the basic assumptions considered in the models (polygenic additive model, normality of the distribution, base population at the equilibrium, etc. are not met in reality. The two deterministic methods compared yielded results that were close to those observed in real data, especially when the selection scheme followed the rules of strict mass selection: for instance, both predictions overestimated the genetic gain in the French experiment, whereas both predictions were close to the observed values in the Dutch experiment.

  2. Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

    Science.gov (United States)

    Stephan, Wolfgang

    2016-01-01

    In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

  3. Selection of variables for neural network analysis. Comparisons of several methods with high energy physics data

    International Nuclear Information System (INIS)

    Proriol, J.

    1994-01-01

    Five different methods are compared for selecting the most important variables with a view to classifying high energy physics events with neural networks. The different methods are: the F-test, Principal Component Analysis (PCA), a decision tree method: CART, weight evaluation, and Optimal Cell Damage (OCD). The neural networks use the variables selected with the different methods. We compare the percentages of events properly classified by each neural network. The learning set and the test set are the same for all the neural networks. (author)

  4. Selection of polychlorinated plastics in plastic waste by X-ray fluorescence method

    International Nuclear Information System (INIS)

    Kumasaki, H.; Shinozaki, Y.

    1979-01-01

    The X-ray fluorescence method using a small source of 55 Fe was examined and found to be applicable for the selection of polychlorinated plastics from plastic waste in model areas in Tokyo designated for investigating their content in the waste. The weight ratios of soft and hard polychlorinated plastics to the total plastic waste estimated by this method were found to be 15.6% and 0.29% respectively. These values agree well with the results obtained with the Beilstein method. (author)

  5. An Ensemble Method with Integration of Feature Selection and Classifier Selection to Detect the Landslides

    Science.gov (United States)

    Zhongqin, G.; Chen, Y.

    2017-12-01

    Abstract Quickly identify the spatial distribution of landslides automatically is essential for the prevention, mitigation and assessment of the landslide hazard. It's still a challenging job owing to the complicated characteristics and vague boundary of the landslide areas on the image. The high resolution remote sensing image has multi-scales, complex spatial distribution and abundant features, the object-oriented image classification methods can make full use of the above information and thus effectively detect the landslides after the hazard happened. In this research we present a new semi-supervised workflow, taking advantages of recent object-oriented image analysis and machine learning algorithms to quick locate the different origins of landslides of some areas on the southwest part of China. Besides a sequence of image segmentation, feature selection, object classification and error test, this workflow ensemble the feature selection and classifier selection. The feature this study utilized were normalized difference vegetation index (NDVI) change, textural feature derived from the gray level co-occurrence matrices (GLCM), spectral feature and etc. The improvement of this study shows this algorithm significantly removes some redundant feature and the classifiers get fully used. All these improvements lead to a higher accuracy on the determination of the shape of landslides on the high resolution remote sensing image, in particular the flexibility aimed at different kinds of landslides.

  6. A method for the deliberate and deliberative selection of policy instrument mixes for climate change adaptation

    Directory of Open Access Journals (Sweden)

    Heleen L. P. Mees

    2014-06-01

    Full Text Available Policy instruments can help put climate adaptation plans into action. Here, we propose a method for the systematic assessment and selection of policy instruments for stimulating adaptation action. The multi-disciplinary set of six assessment criteria is derived from economics, policy, and legal studies. These criteria are specified for the purpose of climate adaptation by taking into account four challenges to the governance of climate adaptation: uncertainty, spatial diversity, controversy, and social complexity. The six criteria and four challenges are integrated into a step-wise method that enables the selection of instruments starting from a generic assessment and ending with a specific assessment of policy instrument mixes for the stimulation of a specific adaptation measure. We then apply the method to three examples of adaptation measures. The method's merits lie in enabling deliberate choices through a holistic and comprehensive set of adaptation specific criteria, as well as deliberative choices by offering a stepwise method that structures an informed dialog on instrument selection. Although the method was created and applied by scientific experts, policy-makers can also use the method.

  7. Stochastic weather inputs for improved urban water demand forecasting: application of nonlinear input variable selection and machine learning methods

    Science.gov (United States)

    Quilty, J.; Adamowski, J. F.

    2015-12-01

    Urban water supply systems are often stressed during seasonal outdoor water use as water demands related to the climate are variable in nature making it difficult to optimize the operation of the water supply system. Urban water demand forecasts (UWD) failing to include meteorological conditions as inputs to the forecast model may produce poor forecasts as they cannot account for the increase/decrease in demand related to meteorological conditions. Meteorological records stochastically simulated into the future can be used as inputs to data-driven UWD forecasts generally resulting in improved forecast accuracy. This study aims to produce data-driven UWD forecasts for two different Canadian water utilities (Montreal and Victoria) using machine learning methods by first selecting historical UWD and meteorological records derived from a stochastic weather generator using nonlinear input variable selection. The nonlinear input variable selection methods considered in this work are derived from the concept of conditional mutual information, a nonlinear dependency measure based on (multivariate) probability density functions and accounts for relevancy, conditional relevancy, and redundancy from a potential set of input variables. The results of our study indicate that stochastic weather inputs can improve UWD forecast accuracy for the two sites considered in this work. Nonlinear input variable selection is suggested as a means to identify which meteorological conditions should be utilized in the forecast.

  8. Sighting optics including an optical element having a first focal length and a second focal length and methods for sighting

    Science.gov (United States)

    Crandall, David Lynn

    2011-08-16

    Sighting optics include a front sight and a rear sight positioned in a spaced-apart relation. The rear sight includes an optical element having a first focal length and a second focal length. The first focal length is selected so that it is about equal to a distance separating the optical element and the front sight and the second focal length is selected so that it is about equal to a target distance. The optical element thus brings into simultaneous focus for a user images of the front sight and the target.

  9. Quality Control Of Selected Pesticides With GC

    Energy Technology Data Exchange (ETDEWEB)

    Karasali, H. [Benaki Phytopathological Institute Laboratory of Physical and Chemical Analysis of Pesticides, Ekalis (Greece)

    2009-07-15

    The practical quality control of selected pesticides with GC is treated. Detailed descriptions are given on materials and methods used, including sample preparation and GC operating conditions. The systematic validation of multi methods is described, comprising performance characteristics in routine analysis, like selectivity, specificity etc. This is illustrated by chromatograms, calibration curves and tables derived from real laboratory data. (author)

  10. Evaluation and selection of energy technologies using an integrated graph theory and analytic hierarchy process methods

    Directory of Open Access Journals (Sweden)

    P. B. Lanjewar

    2016-06-01

    Full Text Available The evaluation and selection of energy technologies involve a large number of attributes whose selection and weighting is decided in accordance with the social, environmental, technical and economic framework. In the present work an integrated multiple attribute decision making methodology is developed by combining graph theory and analytic hierarchy process methods to deal with the evaluation and selection of energy technologies. The energy technology selection attributes digraph enables a quick visual appraisal of the energy technology selection attributes and their interrelationships. The preference index provides a total objective score for comparison of energy technologies alternatives. Application of matrix permanent offers a better appreciation of the considered attributes and helps to analyze the different alternatives from combinatorial viewpoint. The AHP is used to assign relative weights to the attributes. Four examples of evaluation and selection of energy technologies are considered in order to demonstrate and validate the proposed method.

  11. Phenomenology and treatment of selective mutism.

    Science.gov (United States)

    Kumpulainen, Kirsti

    2002-01-01

    Selective mutism is a multidimensional childhood disorder in which, according to the most recent studies, biologically mediated temperament and anxiety components seem to play a major role. Several psychotherapy methods have been reported in case studies to be useful, but the disorder is commonly seen to be resistant to change, particularly in cases of long duration. Currently, behaviour modification and other cognitive methods, together with cooperation with the family and the school personnel, are recommended in the treatment of selective mutism. Selective serotonin reuptake inhibitors and selective monoamine oxidase inhibitors have also been reported to be helpful when treating children with selective mutism. At the moment, pharmacotherapy cannot be recommended as the treatment of first choice but if other methods of treatment are not helpful, medication can be included in the treatment scheme. Comprehensive evaluation and treatment of possible primary and comorbid problems that require treatment are also essential.

  12. Evaluation of Stress Loaded Steel Samples Using Selected Electromagnetic Methods

    International Nuclear Information System (INIS)

    Chady, T.

    2004-01-01

    In this paper the magnetic leakage flux and eddy current method were used to evaluate changes of materials' properties caused by stress. Seven samples made of ferromagnetic material with different level of applied stress were prepared. First, the leakage magnetic fields were measured by scanning the surface of the specimens with GMR gradiometer. Next, the same samples were evaluated using an eddy current sensor. A comparison between results obtained from both methods was carried out. Finally, selected parameters of the measured signal were calculated and utilized to evaluate level of the applied stress. A strong coincidence between amount of the applied stress and the maximum amplitude of the derivative was confirmed

  13. Conditional maximum-entropy method for selecting prior distributions in Bayesian statistics

    Science.gov (United States)

    Abe, Sumiyoshi

    2014-11-01

    The conditional maximum-entropy method (abbreviated here as C-MaxEnt) is formulated for selecting prior probability distributions in Bayesian statistics for parameter estimation. This method is inspired by a statistical-mechanical approach to systems governed by dynamics with largely separated time scales and is based on three key concepts: conjugate pairs of variables, dimensionless integration measures with coarse-graining factors and partial maximization of the joint entropy. The method enables one to calculate a prior purely from a likelihood in a simple way. It is shown, in particular, how it not only yields Jeffreys's rules but also reveals new structures hidden behind them.

  14. Equipment related methods and means for professional selection of operators in the Kozloduy NPP

    International Nuclear Information System (INIS)

    Pandov, E.; Popandreeva, A.

    1993-01-01

    The principal methods of psychological tests for the selection of nuclear power plant operators are presented. The mobility of the psychic processes, the stability and the shift of attention, the short-term memory and the speed of the sensory-motor reactions are evaluated by adopted testing procedures to assess the functional status of the applicants. A set of 11 tests, divided into 4 groups according to the qualities under evaluation is described. The tests include various reactions to light and sound stimulus and a repetitive numerical test in limited time. The differentiating bimodal response is considered as the most conclusive for the assessment of the sensory-motor response of importance in the nuclear reactor operators work. 4 refs. (R.Ts.)

  15. Prediction of bioavailability of selected bisphosphonates using in silico methods towards categorization into a biopharmaceutical classification system.

    Science.gov (United States)

    Biernacka, Joanna; Betlejewska-Kielak, Katarzyna; Kłosińska-Szmurło, Ewa; Pluciński, Franciszek A; Mazurek, Aleksander P

    2013-01-01

    The physicochemical properties relevant to biological activity of selected bisphosphonates such as clodronate disodium salt, etidronate disodium salt, pamidronate disodium salt, alendronate sodium salt, ibandronate sodium salt, risedronate sodium salt and zoledronate disodium salt were determined using in silico methods. The main aim of our research was to investigate and propose molecular determinants thataffect bioavailability of above mentioned compounds. These determinants are: stabilization energy (deltaE), free energy of solvation (deltaG(solv)), electrostatic potential, dipole moment, as well as partition and distribution coefficients estimated by the log P and log D values. Presented values indicate that selected bisphosphonates a recharacterized by high solubility and low permeability. The calculated parameters describing both solubility and permeability through biological membranes seem to be a good bioavailability indicators of bisphosphonates examined and can be a useful tool to include into Biopharmaceutical Classification System (BCS) development.

  16. Exploring selection and recruitment processes for newly qualified nurses: a sequential-explanatory mixed-method study.

    Science.gov (United States)

    Newton, Paul; Chandler, Val; Morris-Thomson, Trish; Sayer, Jane; Burke, Linda

    2015-01-01

    To map current selection and recruitment processes for newly qualified nurses and to explore the advantages and limitations of current selection and recruitment processes. The need to improve current selection and recruitment practices for newly qualified nurses is highlighted in health policy internationally. A cross-sectional, sequential-explanatory mixed-method design with 4 components: (1) Literature review of selection and recruitment of newly qualified nurses; and (2) Literature review of a public sector professions' selection and recruitment processes; (3) Survey mapping existing selection and recruitment processes for newly qualified nurses; and (4) Qualitative study about recruiters' selection and recruitment processes. Literature searches on the selection and recruitment of newly qualified candidates in teaching and nursing (2005-2013) were conducted. Cross-sectional, mixed-method data were collected from thirty-one (n = 31) individuals in health providers in London who had responsibility for the selection and recruitment of newly qualified nurses using a survey instrument. Of these providers who took part, six (n = 6) purposively selected to be interviewed qualitatively. Issues of supply and demand in the workforce, rather than selection and recruitment tools, predominated in the literature reviews. Examples of tools to measure values, attitudes and skills were found in the nursing literature. The mapping exercise found that providers used many selection and recruitment tools, some providers combined tools to streamline process and assure quality of candidates. Most providers had processes which addressed the issue of quality in the selection and recruitment of newly qualified nurses. The 'assessment centre model', which providers were adopting, allowed for multiple levels of assessment and streamlined recruitment. There is a need to validate the efficacy of the selection tools. © 2014 John Wiley & Sons Ltd.

  17. r2VIM: A new variable selection method for random forests in genome-wide association studies.

    Science.gov (United States)

    Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E

    2016-01-01

    Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.

  18. Method for routine determination of fluoride in urine by selective ion- electrode

    International Nuclear Information System (INIS)

    Pires, M.A.F.; Bellintani, S.A.

    1985-01-01

    A simple, fast and sensitive method is outlined for determining fluoride in urine of workers who handle fluoride compounds. The determination is based on the measurement of fluoride by ion selective electrode. Cationic interferents like Ca ++ , Mg ++ , Fe +++ and Al +++ are complexed by EDTA and citric acid. Common anions present in urine, such as Cl - , PO --- 4 and SO -- 4 do not interfere in the method. (Author) [pt

  19. Comparison of selection methods to deduce natural background levels for groundwater units

    NARCIS (Netherlands)

    Griffioen, J.; Passier, H.F.; Klein, J.

    2008-01-01

    Establishment of natural background levels (NBL) for groundwater is commonly performed to serve as reference when assessing the contamination status of groundwater units. We compare various selection methods to establish NBLs using groundwater quality data forfour hydrogeologically different areas

  20. A simple and rapid method for calixarene-based selective extraction of bioactive molecules from natural products.

    Science.gov (United States)

    Segneanu, Adina-Elena; Damian, Daniel; Hulka, Iosif; Grozescu, Ioan; Salifoglou, Athanasios

    2016-03-01

    Natural products derived from medicinal plants have gained an important role in drug discovery due to their complex and abundant composition of secondary metabolites, with their structurally unique molecular components bearing a significant number of stereo-centers exhibiting high specificity linked to biological activity. Usually, the extraction process of natural products involves various techniques targeting separation of a specific class of compounds from a highly complex matrix. Aiding the process entails the use of well-defined and selective molecular extractants with distinctly configured structural attributes. Calixarenes conceivably belong to that class of molecules. They have been studied intensely over the years in an effort to develop new and highly selective receptors for biomolecules. These macrocycles, which display remarkable structural architectures and properties, could help usher a new approach in the efficient separation of specific classes of compounds from complex matrices in natural products. A simple and rapid such extraction method is presented herein, based on host-guest interaction(s) between a calixarene synthetic receptor, 4-tert-butyl-calix[6]arene, and natural biomolecular targets (amino acids and peptides) from Helleborus purpurascens and Viscum album. Advanced physicochemical methods (including GC-MS and chip-based nanoESI-MS analysis) suggest that the molecular structure and specifically the calixarene cavity size are closely linked to the nature of compounds separated. Incorporation of biomolecules and modification of the macrocyclic architecture during separation were probed and confirmed by scanning electronic microscopy and atomic force microscopy. The collective results project calixarene as a promising molecular extractant candidate, facilitating the selective separation of amino acids and peptides from natural products.

  1. Standard Guide for Selection and Use of Mathematical Methods for Calculating Absorbed Dose in Radiation Processing Applications

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    2010-01-01

    1.1 This guide describes different mathematical methods that may be used to calculate absorbed dose and criteria for their selection. Absorbed-dose calculations can determine the effectiveness of the radiation process, estimate the absorbed-dose distribution in product, or supplement or complement, or both, the measurement of absorbed dose. 1.2 Radiation processing is an evolving field and annotated examples are provided in Annex A6 to illustrate the applications where mathematical methods have been successfully applied. While not limited by the applications cited in these examples, applications specific to neutron transport, radiation therapy and shielding design are not addressed in this document. 1.3 This guide covers the calculation of radiation transport of electrons and photons with energies up to 25 MeV. 1.4 The mathematical methods described include Monte Carlo, point kernel, discrete ordinate, semi-empirical and empirical methods. 1.5 General purpose software packages are available for the calcul...

  2. A quick method based on SIMPLISMA-KPLS for simultaneously selecting outlier samples and informative samples for model standardization in near infrared spectroscopy

    Science.gov (United States)

    Li, Li-Na; Ma, Chang-Ming; Chang, Ming; Zhang, Ren-Cheng

    2017-12-01

    A novel method based on SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) and Kernel Partial Least Square (KPLS), named as SIMPLISMA-KPLS, is proposed in this paper for selection of outlier samples and informative samples simultaneously. It is a quick algorithm used to model standardization (or named as model transfer) in near infrared (NIR) spectroscopy. The NIR experiment data of the corn for analysis of the protein content is introduced to evaluate the proposed method. Piecewise direct standardization (PDS) is employed in model transfer. And the comparison of SIMPLISMA-PDS-KPLS and KS-PDS-KPLS is given in this research by discussion of the prediction accuracy of protein content and calculation speed of each algorithm. The conclusions include that SIMPLISMA-KPLS can be utilized as an alternative sample selection method for model transfer. Although it has similar accuracy to Kennard-Stone (KS), it is different from KS as it employs concentration information in selection program. This means that it ensures analyte information is involved in analysis, and the spectra (X) of the selected samples is interrelated with concentration (y). And it can be used for outlier sample elimination simultaneously by validation of calibration. According to the statistical data results of running time, it is clear that the sample selection process is more rapid when using KPLS. The quick algorithm of SIMPLISMA-KPLS is beneficial to improve the speed of online measurement using NIR spectroscopy.

  3. Hybrid Multicriteria Group Decision Making Method for Information System Project Selection Based on Intuitionistic Fuzzy Theory

    Directory of Open Access Journals (Sweden)

    Jian Guo

    2013-01-01

    Full Text Available Information system (IS project selection is of critical importance to every organization in dynamic competing environment. The aim of this paper is to develop a hybrid multicriteria group decision making approach based on intuitionistic fuzzy theory for IS project selection. The decision makers’ assessment information can be expressed in the form of real numbers, interval-valued numbers, linguistic variables, and intuitionistic fuzzy numbers (IFNs. All these evaluation pieces of information can be transformed to the form of IFNs. Intuitionistic fuzzy weighted averaging (IFWA operator is utilized to aggregate individual opinions of decision makers into a group opinion. Intuitionistic fuzzy entropy is used to obtain the entropy weights of the criteria. TOPSIS method combined with intuitionistic fuzzy set is proposed to select appropriate IS project in group decision making environment. Finally, a numerical example for information system projects selection is given to illustrate application of hybrid multi-criteria group decision making (MCGDM method based on intuitionistic fuzzy theory and TOPSIS method.

  4. A simple negative selection method to identify adenovirus recombinants using colony PCR

    Directory of Open Access Journals (Sweden)

    Yongliang Zhao

    2014-01-01

    Conclusions: The negative selection method to identify AdEasy adenovirus recombinants by colony PCR can identify the recombined colony within a short time-period, and maximally avoid damage to the recombinant plasmid by limiting recombination time, resulting in improved adenovirus packaging.

  5. Highly selective coulometric method and equipment for the automated determination of plutonium

    International Nuclear Information System (INIS)

    Jackson, D.D.; Hollen, R.M.; Roensch, F.R.; Rein, J.E.

    1977-01-01

    A highly selective, controlled-potential coulometric method has been developed for the determination of plutonium. An automated instrument, consisting of commercial electronic components under control of a programmable calculator, is being constructed. Half-cell potentials and interfering anions are listed

  6. A Feature Selection Method Based on Fisher's Discriminant Ratio for Text Sentiment Classification

    Science.gov (United States)

    Wang, Suge; Li, Deyu; Wei, Yingjie; Li, Hongxia

    With the rapid growth of e-commerce, product reviews on the Web have become an important information source for customers' decision making when they intend to buy some product. As the reviews are often too many for customers to go through, how to automatically classify them into different sentiment orientation categories (i.e. positive/negative) has become a research problem. In this paper, based on Fisher's discriminant ratio, an effective feature selection method is proposed for product review text sentiment classification. In order to validate the validity of the proposed method, we compared it with other methods respectively based on information gain and mutual information while support vector machine is adopted as the classifier. In this paper, 6 subexperiments are conducted by combining different feature selection methods with 2 kinds of candidate feature sets. Under 1006 review documents of cars, the experimental results indicate that the Fisher's discriminant ratio based on word frequency estimation has the best performance with F value 83.3% while the candidate features are the words which appear in both positive and negative texts.

  7. Essay on Methods in Futures Studies and a Selective Bibliography

    DEFF Research Database (Denmark)

    Poulsen, Claus

    2005-01-01

    Futures studies is often conflated with science fiction or pop-futurism. Consequently there is a need for demarcation of what is futures studies and what is not. From the same reason the essay stresses the need for quality control to focus on futures research and its methods: Publications in futu...... programme are (only) partly reduced by applying Causal Layered Analysis as an internal quality control. The following selective bibliography is focussed on these methodological issues...

  8. Tree regeneration response to the group selection method in southern Indiana

    Science.gov (United States)

    Dale R. Weigel; George R. Parker

    1997-01-01

    Tree regeneration response following the use of the group selection method was studied within 36 group openings on the Naval Surface Warfare Center, Crane Division in south central Indiana. Two different aspects and three time periods since cutting were examined. The objectives were to determine whether aspect, age, species group, location within the opening, or their...

  9. The stock selection problem: Is the stock selection approach more important than the optimization method? Evidence from the Danish stock market

    OpenAIRE

    Grobys, Klaus

    2011-01-01

    Passive investment strategies basically aim to replicate an underlying benchmark. Thereby, the management usually selects a subset of stocks being employed in the optimization procedure. Apart from the optimization procedure, the stock selection approach determines the stock portfolios' out-of-sample performance. The empirical study here takes into account the Danish stock market from 2000-2010 and gives evidence that stock portfolios including small companies' stocks being estimated via coin...

  10. Earthquake analysis of structures including structure-soil interaction by a substructure method

    International Nuclear Information System (INIS)

    Chopra, A.K.; Guttierrez, J.A.

    1977-01-01

    A general substructure method for analysis of response of nuclear power plant structures to earthquake ground motion, including the effects of structure-soil interaction, is summarized. The method is applicable to complex structures idealized as finite element systems and the soil region treated as either a continuum, for example as a viscoelastic halfspace, or idealized as a finite element system. The halfspace idealization permits reliable analysis for sites where essentially similar soils extend to large depths and there is no rigid boundary such as soil-rock interface. For sites where layers of soft soil are underlain by rock at shallow depth, finite element idealization of the soil region is appropriate; in this case, the direct and substructure methods would lead to equivalent results but the latter provides the better alternative. Treating the free field motion directly as the earthquake input in the substructure method eliminates the deconvolution calculations and the related assumption -regarding type and direction of earthquake waves- required in the direct method. The substructure method is computationally efficient because the two substructures-the structure and the soil region- are analyzed separately; and, more important, it permits taking advantage of the important feature that response to earthquake ground motion is essentially contained in the lower few natural modes of vibration of the structure on fixed base. For sites where essentially similar soils extend to large depths and there is no obvious rigid boundary such as a soil-rock interface, numerical results for earthquake response of a nuclear reactor structure are presented to demonstrate that the commonly used finite element method may lead to unacceptable errors; but the substructure method leads to reliable results

  11. Using the Delphi Method for Selecting Effective Rehabilitation Practices for Case Study Research: Methods, Challenges, and Solutions and Implications for Future Research

    Science.gov (United States)

    Fleming, Allison R.; Boeltzig-Brown, Heike; Foley, Susan M.

    2015-01-01

    Purpose: We describe a modified Delphi method used to select effective state vocational rehabilitation agency practices to prioritize rehabilitation services for individuals with most significant disabilities within the context of Order of Selection, an area where there is little known and published. Specifically, we describe how we applied the…

  12. Automatic method for selective enhancement of different tissue densities at digital chest radiography

    International Nuclear Information System (INIS)

    McNitt-Gray, M.F.; Taira, R.K.; Eldredge, S.L.; Razavi, M.

    1991-01-01

    This paper reports that digital chest radiographs often are too bright and/or lack contrast when viewed on a video display. The authors have developed a method that can automatically provide a series of look-up tables that selectively enhance the radiographically soft or dense tissues on a digital chest radiograph. This reduces viewer interaction and improves displayed image quality. On the basis of a histogram analysis, gray-level ranges are approximated for the patient background, radiographically soft tissues, and radiographically dense tissues. A series of look-up tables is automatically created by varying the contrast in each range to achieve a level of enhancement for a selected tissue range. This is repeated for differing amounts of enhancement and for each tissue range. This allows the viewer to interactively select a tissue density range and degree of enhancement at the time of display via precalculated look-up tables. Preclinical trials in pediatric radiology using computed radiography images show that this method reduces viewer interaction and improves or maintains the displayed image quality

  13. TU-AB-202-10: How Effective Are Current Atlas Selection Methods for Atlas-Based Auto-Contouring in Radiotherapy Planning?

    Energy Technology Data Exchange (ETDEWEB)

    Peressutti, D; Schipaanboord, B; Kadir, T; Gooding, M [Mirada Medical Limited, Science and Medical Technology, Oxford (United Kingdom); Soest, J van; Lustberg, T; Elmpt, W van; Dekker, A [Maastricht University Medical Centre, Department of Radiation Oncology MAASTRO - GROW School for Oncology Developmental Biology, Maastricht (Netherlands)

    2016-06-15

    Purpose: To investigate the effectiveness of atlas selection methods for improving atlas-based auto-contouring in radiotherapy planning. Methods: 275 H&N clinically delineated cases were employed as an atlas database from which atlases would be selected. A further 40 previously contoured cases were used as test patients against which atlas selection could be performed and evaluated. 26 variations of selection methods proposed in the literature and used in commercial systems were investigated. Atlas selection methods comprised either global or local image similarity measures, computed after rigid or deformable registration, combined with direct atlas search or with an intermediate template image. Workflow Box (Mirada-Medical, Oxford, UK) was used for all auto-contouring. Results on brain, brainstem, parotids and spinal cord were compared to random selection, a fixed set of 10 “good” atlases, and optimal selection by an “oracle” with knowledge of the ground truth. The Dice score and the average ranking with respect to the “oracle” were employed to assess the performance of the top 10 atlases selected by each method. Results: The fixed set of “good” atlases outperformed all of the atlas-patient image similarity-based selection methods (mean Dice 0.715 c.f. 0.603 to 0.677). In general, methods based on exhaustive comparison of local similarity measures showed better average Dice scores (0.658 to 0.677) compared to the use of either template image (0.655 to 0.672) or global similarity measures (0.603 to 0.666). The performance of image-based selection methods was found to be only slightly better than a random (0.645). Dice scores given relate to the left parotid, but similar results patterns were observed for all organs. Conclusion: Intuitively, atlas selection based on the patient CT is expected to improve auto-contouring performance. However, it was found that published approaches performed marginally better than random and use of a fixed set of

  14. A technique of including the effect of aging of passive components in probabilistic risk assessments

    International Nuclear Information System (INIS)

    Phillips, J.H.; Weidenhamer, G.H.

    1992-01-01

    The probabilistic risk assessments (PRAS) being developed at most nuclear power plants to calculate the risk of core damage generally focus on the possible failure of active components. The possible failure of passive components is given little consideration. We are developing methods for selecting risk-significant passive components and including them in PRAS. These methods provide effective ways to prioritize passive components for inspection, and where inspection reveals aging damage, mitigation or repair can be employed to reduce the likelihood of component failure. We demonstrated a method by selecting a weld in the auxiliary feedwater (AFW) system, basing our selection on expert judgement of the likelihood of failure and on an estimate of the consequence of component failure to plant safety. We then modified and used the Piping Reliability Analysis Including Seismic Events (PRAISE) computer code to perform a probabilistic structural analysis to calculate the probability that crack growth due to aging would cause the weld to fail. The PRAISE code was modified to include the effects of changing design material properties with age and changing stress cycles. The calculation included the effects of mechanical loads and thermal transients typical of the service loads for this piping design and the effects of thermal cycling caused by a leaking check valve. However, this particular calculation showed little change in low component failure probability and plant risk for 48 years of service. However, sensitivity studies showed that if the probability of component failure is high, the effect on plant risk is significant. The success of this demonstration shows that this method could be applied to nuclear power plants. The demonstration showed the method is too involved (PRAISE takes a long time to perform the calculation and the input information is extensive) for handling a large number of passive components and therefore simpler methods are needed

  15. SELECTING A MANAGEMENT SYSTEM HOSPITAL BY A METHOD MULTICRITERIA

    Directory of Open Access Journals (Sweden)

    Vitorino, Sidney L.

    2016-12-01

    Full Text Available The objective of this report is to assess how the multi-criteria method Analytic Hierarchy Process [HP] can help a hospital complex to choose a more suitable management system, known as Enterprise Resource Planning (ERP. The choice coated is very complex due to the novelty of the process of choosing and conflicts generated between areas that did not have a single view of organizational needs, generating a lot of pressure in the department responsible for implementing systems. To assist in this process, he was hired an expert consultant in decision-making and AHP, which in its role of facilitator, contributed to the criteria for system selection were defined, and the choice to occur within a consensual process. We used the study of a single case, based on two indepth interviews with the consultant and the project manager, and documents generated by the advisory and the tool that supported the method. The results of this analysis showed that the method could effectively collaborate in the system acquisition process, but knowledge of the problems of employees and senior management support, it was not used in new decisions of the organization. We conclude that this method contributed to the consensus in the procurement process, team commitment and engagement of those involved.

  16. Roka Listeria detection method using transcription mediated amplification to detect Listeria species in select foods and surfaces. Performance Tested Method(SM) 011201.

    Science.gov (United States)

    Hua, Yang; Kaplan, Shannon; Reshatoff, Michael; Hu, Ernie; Zukowski, Alexis; Schweis, Franz; Gin, Cristal; Maroni, Brett; Becker, Michael; Wisniewski, Michele

    2012-01-01

    The Roka Listeria Detection Assay was compared to the reference culture methods for nine select foods and three select surfaces. The Roka method used Half-Fraser Broth for enrichment at 35 +/- 2 degrees C for 24-28 h. Comparison of Roka's method to reference methods requires an unpaired approach. Each method had a total of 545 samples inoculated with a Listeria strain. Each food and surface was inoculated with a different strain of Listeria at two different levels per method. For the dairy products (Brie cheese, whole milk, and ice cream), our method was compared to AOAC Official Method(SM) 993.12. For the ready-to-eat meats (deli chicken, cured ham, chicken salad, and hot dogs) and environmental surfaces (sealed concrete, stainless steel, and plastic), these samples were compared to the U.S. Department of Agriculture/Food Safety and Inspection Service-Microbiology Laboratory Guidebook (USDA/FSIS-MLG) method MLG 8.07. Cold-smoked salmon and romaine lettuce were compared to the U.S. Food and Drug Administration/Bacteriological Analytical Manual, Chapter 10 (FDA/BAM) method. Roka's method had 358 positives out of 545 total inoculated samples compared to 332 positive for the reference methods. Overall the probability of detection analysis of the results showed better or equivalent performance compared to the reference methods.

  17. Analysis of Multi-Criteria Evaluation Method of Landfill Site Selection for Municipal Solid Waste Management

    Science.gov (United States)

    Mohammed, Habiba Ibrahim; Majid, Zulkepli; Yusof, Norhakim Bin; Bello Yamusa, Yamusa

    2018-03-01

    Landfilling remains the most common systematic technique of solid waste disposal in most of the developed and developing countries. Finding a suitable site for landfill is a very challenging task. Landfill site selection process aims to provide suitable areas that will protect the environment and public health from pollution and hazards. Therefore, various factors such as environmental, physical, socio-economic, and geological criteria must be considered before siting any landfill. This makes the site selection process vigorous and tedious because it involves the processing of large amount of spatial data, rules and regulations from different agencies and also policy from decision makers. This allows the incorporation of conflicting objectives and decision maker preferences into spatial decision models. This paper particularly analyzes the multi-criteria evaluation (MCE) method of landfill site selection for solid waste management by means of literature reviews and surveys. The study will help the decision makers and waste management authorities to choose the most effective method when considering landfill site selection.

  18. Analysis of Multi-Criteria Evaluation Method of Landfill Site Selection for Municipal Solid Waste Management

    Directory of Open Access Journals (Sweden)

    Ibrahim Mohammed Habiba

    2018-01-01

    Full Text Available Landfilling remains the most common systematic technique of solid waste disposal in most of the developed and developing countries. Finding a suitable site for landfill is a very challenging task. Landfill site selection process aims to provide suitable areas that will protect the environment and public health from pollution and hazards. Therefore, various factors such as environmental, physical, socio-economic, and geological criteria must be considered before siting any landfill. This makes the site selection process vigorous and tedious because it involves the processing of large amount of spatial data, rules and regulations from different agencies and also policy from decision makers. This allows the incorporation of conflicting objectives and decision maker preferences into spatial decision models. This paper particularly analyzes the multi-criteria evaluation (MCE method of landfill site selection for solid waste management by means of literature reviews and surveys. The study will help the decision makers and waste management authorities to choose the most effective method when considering landfill site selection.

  19. Genomic Selection Using Extreme Phenotypes and Pre-Selection of SNPs in Large Yellow Croaker (Larimichthys crocea).

    Science.gov (United States)

    Dong, Linsong; Xiao, Shijun; Chen, Junwei; Wan, Liang; Wang, Zhiyong

    2016-10-01

    Genomic selection (GS) is an effective method to improve predictive accuracies of genetic values. However, high cost in genotyping will limit the application of this technology in some species. Therefore, it is necessary to find some methods to reduce the genotyping costs in genomic selection. Large yellow croaker is one of the most commercially important marine fish species in southeast China and Eastern Asia. In this study, genotyping-by-sequencing was used to construct the libraries for the NGS sequencing and find 29,748 SNPs in the genome. Two traits, eviscerated weight (EW) and the ratio between eviscerated weight and whole body weight (REW), were chosen to study. Two strategies to reduce the costs were proposed as follows: selecting extreme phenotypes (EP) for genotyping in reference population or pre-selecting SNPs to construct low-density marker panels in candidates. Three methods of pre-selection of SNPs, i.e., pre-selecting SNPs by absolute effects (SE), by single marker analysis (SMA), and by fixed intervals of sequence number (EL), were studied. The results showed that using EP was a feasible method to save the genotyping costs in reference population. Heritability did not seem to have obvious influences on the predictive abilities estimated by EP. Using SMA was the most feasible method to save the genotyping costs in candidates. In addition, the combination of EP and SMA in genomic selection also showed good results, especially for trait of REW. We also described how to apply the new methods in genomic selection and compared the genotyping costs before and after using the new methods. Our study may not only offer a reference for aquatic genomic breeding but also offer a reference for genomic prediction in other species including livestock and plants, etc.

  20. Systematic wavelength selection for improved multivariate spectral analysis

    Science.gov (United States)

    Thomas, Edward V.; Robinson, Mark R.; Haaland, David M.

    1995-01-01

    Methods and apparatus for determining in a biological material one or more unknown values of at least one known characteristic (e.g. the concentration of an analyte such as glucose in blood or the concentration of one or more blood gas parameters) with a model based on a set of samples with known values of the known characteristics and a multivariate algorithm using several wavelength subsets. The method includes selecting multiple wavelength subsets, from the electromagnetic spectral region appropriate for determining the known characteristic, for use by an algorithm wherein the selection of wavelength subsets improves the model's fitness of the determination for the unknown values of the known characteristic. The selection process utilizes multivariate search methods that select both predictive and synergistic wavelengths within the range of wavelengths utilized. The fitness of the wavelength subsets is determined by the fitness function F=.function.(cost, performance). The method includes the steps of: (1) using one or more applications of a genetic algorithm to produce one or more count spectra, with multiple count spectra then combined to produce a combined count spectrum; (2) smoothing the count spectrum; (3) selecting a threshold count from a count spectrum to select these wavelength subsets which optimize the fitness function; and (4) eliminating a portion of the selected wavelength subsets. The determination of the unknown values can be made: (1) noninvasively and in vivo; (2) invasively and in vivo; or (3) in vitro.

  1. Comparison of different methods to include recycling in LCAs of aluminium cans and disposable polystyrene cups

    NARCIS (Netherlands)

    Harst-Wintraecken, van der Eugenie; Potting, José; Kroeze, Carolien

    2016-01-01

    Many methods have been reported and used to include recycling in life cycle assessments (LCAs). This paper evaluates six widely used methods: three substitution methods (i.e. substitution based on equal quality, a correction factor, and alternative material), allocation based on the number of

  2. Clustering based gene expression feature selection method: A computational approach to enrich the classifier efficiency of differentially expressed genes

    KAUST Repository

    Abusamra, Heba

    2016-07-20

    The native nature of high dimension low sample size of gene expression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia gene expression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressed genes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

  3. A method for selecting cis-acting regulatory sequences that respond to small molecule effectors

    Directory of Open Access Journals (Sweden)

    Allas Ülar

    2010-08-01

    Full Text Available Abstract Background Several cis-acting regulatory sequences functioning at the level of mRNA or nascent peptide and specifically influencing transcription or translation have been described. These regulatory elements often respond to specific chemicals. Results We have developed a method that allows us to select cis-acting regulatory sequences that respond to diverse chemicals. The method is based on the β-lactamase gene containing a random sequence inserted into the beginning of the ORF. Several rounds of selection are used to isolate sequences that suppress β-lactamase expression in response to the compound under study. We have isolated sequences that respond to erythromycin, troleandomycin, chloramphenicol, meta-toluate and homoserine lactone. By introducing synonymous and non-synonymous mutations we have shown that at least in the case of erythromycin the sequences act at the peptide level. We have also tested the cross-activities of the constructs and found that in most cases the sequences respond most strongly to the compound on which they were isolated. Conclusions Several selected peptides showed ligand-specific changes in amino acid frequencies, but no consensus motif could be identified. This is consistent with previous observations on natural cis-acting peptides, showing that it is often impossible to demonstrate a consensus. Applying the currently developed method on a larger scale, by selecting and comparing an extended set of sequences, might allow the sequence rules underlying the activity of cis-acting regulatory peptides to be identified.

  4. Eco-Material Selection for Auto Bodies

    Energy Technology Data Exchange (ETDEWEB)

    Mayyas, Ahmad T [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Omar, Mohammed [Masdar Institute of Science & Technology; Hayajneh, Mohammed T. [Jordan University of Science and Technology

    2017-09-25

    In the last decades, majority of automakers started to include lightweight materials in their vehicles to meet hard environmental regulations and to improve fuel efficiency of their vehicles. As a result, eco-material selection for vehicles emerged as a new discipline under design for environment. This chapter will summarize methods of eco-material selections for automotive applications with more emphasis into auto-bodies. A set of metrics for eco-material selection that takes into account all economic, environmental and social factors will be developed using numerical and qualitative methods. These metrics cover products' environmental impact, functionality and manufacturability, in addition to the economic and societal factors.

  5. Development of an optimal velocity selection method with velocity obstacle

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Min Geuk; Oh, Jun Ho [KAIST, Daejeon (Korea, Republic of)

    2015-08-15

    The Velocity obstacle (VO) method is one of the most well-known methods for local path planning, allowing consideration of dynamic obstacles and unexpected obstacles. Typical VO methods separate a velocity map into a collision area and a collision-free area. A robot can avoid collisions by selecting its velocity from within the collision-free area. However, if there are numerous obstacles near a robot, the robot will have very few velocity candidates. In this paper, a method for choosing optimal velocity components using the concept of pass-time and vertical clearance is proposed for the efficient movement of a robot. The pass-time is the time required for a robot to pass by an obstacle. By generating a latticized available velocity map for a robot, each velocity component can be evaluated using a cost function that considers the pass-time and other aspects. From the output of the cost function, even a velocity component that will cause a collision in the future can be chosen as a final velocity if the pass-time is sufficiently long enough.

  6. a Method for the Seamlines Network Automatic Selection Based on Building Vector

    Science.gov (United States)

    Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.

    2018-04-01

    In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.

  7. Selection of a method to produce activated charcoal using four forest species

    International Nuclear Information System (INIS)

    Herrera Builes, Jhon Fredy; Morales Yepes, Wilmar Alexander; Perez Schile, Juan David

    2004-01-01

    This investigation was conducted in the coal and of forest products laboratory of the Universidad Nacional de Colombia, sede Medellin. It was oriented towards the selection of a method to obtain activated carbon form the following forest species; pino patula (Pinus patula), chingale Jacaranda copaia) pino tecunumani (pinus tecunumani) and roble (Quercus humboldti). The wood of each was characterized determining their physical properties of density and contraction. Seven different methods were tested; chemical activation chemical-physical activation with CO 2 chemical-physical activation with CO 2 and water vapor; chemical-physical activation with water vapor; physical activation with CO 2 ; physical activation with water vapor and physical activation with CO 2 and water vapor. The variables studied were residence time and temperature. Taking as a parameter the Iodine index, the chemical-physical activation with water vapor was selected, obtaining an Iodine index of over 800 for all the species studied with the exception of roble that only attained 764 which is still acceptable for water treatment

  8. A New Decision-Making Method for Stock Portfolio Selection Based on Computing with Linguistic Assessment

    Directory of Open Access Journals (Sweden)

    Chen-Tung Chen

    2009-01-01

    Full Text Available The purpose of stock portfolio selection is how to allocate the capital to a large number of stocks in order to bring a most profitable return for investors. In most of past literatures, experts considered the portfolio of selection problem only based on past crisp or quantitative data. However, many qualitative and quantitative factors will influence the stock portfolio selection in real investment situation. It is very important for experts or decision-makers to use their experience or knowledge to predict the performance of each stock and make a stock portfolio. Because of the knowledge, experience, and background of each expert are different and vague, different types of 2-tuple linguistic variable are suitable used to express experts' opinions for the performance evaluation of each stock with respect to criteria. According to the linguistic evaluations of experts, the linguistic TOPSIS and linguistic ELECTRE methods are combined to present a new decision-making method for dealing with stock selection problems in this paper. Once the investment set has been determined, the risk preferences of investor are considered to calculate the investment ratio of each stock in the investment set. Finally, an example is implemented to demonstrate the practicability of the proposed method.

  9. A Novel Fault Line Selection Method Based on Improved Oscillator System of Power Distribution Network

    Directory of Open Access Journals (Sweden)

    Xiaowei Wang

    2014-01-01

    Full Text Available A novel method of fault line selection based on IOS is presented. Firstly, the IOS is established by using math model, which adopted TZSC signal to replace built-in signal of duffing chaotic oscillator by selecting appropriate parameters. Then, each line’s TZSC decomposed by db10 wavelet packet to get CFB with the maximum energy principle, and CFB was solved by IOS. Finally, maximum chaotic distance and average chaotic distance on the phase trajectory are used to judge fault line. Simulation results show that the proposed method can accurately judge fault line and healthy line in strong noisy background. Besides, the nondetection zones of proposed method are elaborated.

  10. A method for selecting potential geosites. The case of glacial geosites in the Chablais area (French and Swiss Prealps)

    Science.gov (United States)

    Perret, Amandine; Reynard, Emmanuel

    2014-05-01

    stages of the glacial retreat since the Last Glacial Maximum. From a spatial point of view, the objective was to show the different types of glacial remnants, but also some landforms related to deglaciation processes. Finally, 32 glacial and associated geosites were selected. Each geosite was submitted to a full evaluation process, including basis information, description, explanation of morphogenesis and an evaluation of values assigned to geosites. This assessment, first qualitative, provided valuable information concerning their intrinsic interest and their management. A numerical evaluation was also assessed to classify geosites and define an order of priority for their touristic promotion. It is worth to be noted that each selected points of interest can in fact be qualified as a geosite, using a clear method of selection. In this study, the numerical evaluation is not a mean to select geosites but a way to rank one geosite to another. Some geosites can be abandoned if intrinsic values are too low. Despite a well-defined protocol, the subjectivity and authors' choices are part of the selection process and inventory. This fact is certainly not a weakness. It must be considered whenever such inventory is made. Reference Martin, S. (2012). Valoriser le géopatrimoine par la médiation indirecte et la visualisation des objets géomorphologiques (Thèse de doctorat). Université de Lausanne, Lausanne. Reynard E., Fontana G., Kozlik L., Scapozza C. (2007). A method for assessing the scientific and additional values of geomorphosites, Geographica Helvetica, 62(3), 148-158. Reynard, E., Perret, A., Grangier, L., & Kozlik, L. (2012). Methodological approach for the assessment, protection, promotion and management of geoheritage. EGU General Assembly, Vienna.

  11. Method selection and evaluation of midtrimester and long-term therapeutic efficiency of achalasia with three methods of interventional procedure

    International Nuclear Information System (INIS)

    Cheng Yingsheng; Yang Renjie; Li Minghua; Chen Weixiong; Shang Kezhong; Zhuang Qixin; Xu Jianrong; Chen Niwei; Zhu Yude

    2000-01-01

    Objective: To study method selection and evaluation of midtrimester and long-term therapeutic efficiency of achalasia with three methods of interventional procedure. Method: 50 cases achalasia with 30 cases performing with balloon dilation (group A) and 5 cases with permanent metallic internal stent dilation (group B) and 15 cases with temporary metallic internal stent dilation (group C) under fluoroscopy. Results: 30 cases of group A had 56 times of dilations (mean 1.9 times). The mean diameter of cardia was (2.4 +- 1.2) mm before dilation and (9.7 +- 3.0) mm after dilation. The mean dysphagia scores were 2.4 +- 1.2 grades before dilation and 1.0 +- 0.3 grades after dilation. Complications in 30 cases included chest pain (n = 9), reflux (n = 8) and bleeding (n = 3). 18(60%) of 30 cases showed dysphagia relapse during follow-up over 6 months, 18(90%) of 20 cases showed dysphagia relapse during follow-up over 12 months. 5 uncovered expandable metal stents were permanently placed in 5 cases of group B. The mean diameter of cardia was (3.2 +- 2.0) mm before dilation and (18.4 +- 1.7) mm after dilation. The mean dysphagia scores were (2.4 +- 1.1) grade before dilation and (0.4 +- 0.2) grade after dilation. Complications in 5 cases included chest pain (n = 3), reflux (n = 4), bleeding (n = 1) and hyperplasia of granulation tissue (n 2). 3(60%) in 5 cases showed dysphagia relapse during follow-up over 6 months, 1(50%) in 2 cases were dysphagia relapse during follow-up over 12 months. 15 covered expandable metal stents were temporarily placed in 15 cases of group C and drawn out at the 3-7 days via gastroscopy. The mean diameter of cardia was (3.4 +- 2.9) mm before dilation and (14.7 +- 2.9) mm after dilation. The mean dysphagia scores were (2.5 +- 1.1) grades before dilation and (0.6 +- 0.3) grades after dilation. Complications in 15 cases included chest pain (n = 3), reflux (n = 3) and bleeding (n = 2). 3(20%) in 15 cases showed dysphagia relapse during follow-up over 6

  12. Selection of nursing teaching strategies in mainland China: A questionnaire survey.

    Science.gov (United States)

    Zhou, HouXiu; Liu, MengJie; Zeng, Jing; Zhu, JingCi

    2016-04-01

    In nursing education, the traditional lecture and direct demonstration teaching method cannot cultivate the various skills that nursing students need. How to choose a more scientific and rational teaching method is a common concern for nursing educators worldwide. To investigate the basis for selecting teaching methods among nursing teachers in mainland China, the factors affecting the selection of different teaching methods, and the application of different teaching methods in theoretical and skill-based nursing courses. Questionnaire survey. Seventy one nursing colleges from 28 provincial-level administrative regions in mainland China. Following the principle of voluntary informed consent, 262 nursing teachers were randomly selected through a nursing education network platform and a conference platform. The questionnaire contents included the basis for and the factors influencing the selection of nursing teaching methods, the participants' common teaching methods, and the teaching experience of the surveyed nursing teachers. The questionnaires were distributed through the network or conference platform, and the data were analyzed by SPSS 17.0 software. The surveyed nursing teachers selected teaching methods mainly based on the characteristics of the teaching content, the characteristics of the students, and their previous teaching experiences. The factors affecting the selection of teaching methods mainly included large class sizes, limited class time, and limited examination formats. The surveyed nursing teachers primarily used lectures to teach theory courses and the direct demonstration method to teach skills courses, and the application frequencies of these two teaching methods were significantly higher than those of other teaching methods (P=0.000). More attention should be paid to the selection of nursing teaching methods. Every teacher should strategically choose teaching methods before each lesson, and nursing education training focused on selecting

  13. An Entropy-based gene selection method for cancer classification using microarray data

    Directory of Open Access Journals (Sweden)

    Krishnan Arun

    2005-03-01

    Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

  14. Membranes, methods of making membranes, and methods of separating gases using membranes

    Science.gov (United States)

    Ho, W. S. Winston

    2012-10-02

    Membranes, methods of making membranes, and methods of separating gases using membranes are provided. The membranes can include at least one hydrophilic polymer, at least one cross-linking agent, at least one base, and at least one amino compound. The methods of separating gases using membranes can include contacting a gas stream containing at least one of CO.sub.2, H.sub.2S, and HCl with one side of a nonporous and at least one of CO.sub.2, H.sub.2S, and HCl selectively permeable membrane such that at least one of CO.sub.2, H.sub.2S, and HCl is selectively transported through the membrane.

  15. Linear feature selection in texture analysis - A PLS based method

    DEFF Research Database (Denmark)

    Marques, Joselene; Igel, Christian; Lillholm, Martin

    2013-01-01

    We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... and considering all CV groups, the methods selected 36 % of the original features available. The diagnosis evaluation reached a generalization area-under-the-ROC curve of 0.92, which was higher than established cartilage-based markers known to relate to OA diagnosis....

  16. Proteomics in pulmonary research: selected methodical aspects

    Directory of Open Access Journals (Sweden)

    Martin Petrek

    2007-10-01

    Full Text Available Recent years witness rapid expansion of applications of proteomics to clinical research including non-malignant lung disorders. These developments bring along the need for standardisation of proteomic experiments. This paper briefly reviews basic methodical aspects of appliedproteomic studies using SELDI-TOF mass spectrometry platform as example but also emphasizes general aspects of quality assurance in proteomics. Key-words: lung proteome, quality assurance, SELDI-TOF MS

  17. Band selection method based on spectrum difference in targets of interest in hyperspectral imagery

    Science.gov (United States)

    Zhang, Xiaohan; Yang, Guang; Yang, Yongbo; Huang, Junhua

    2016-10-01

    While hyperspectral data shares rich spectrum information, it has numbers of bands with high correlation coefficients, causing great data redundancy. A reasonable band selection is important for subsequent processing. Bands with large amount of information and low correlation should be selected. On this basis, according to the needs of target detection applications, the spectral characteristics of the objects of interest are taken into consideration in this paper, and a new method based on spectrum difference is proposed. Firstly, according to the spectrum differences of targets of interest, a difference matrix which represents the different spectral reflectance of different targets in different bands is structured. By setting a threshold, the bands satisfying the conditions would be left, constituting a subset of bands. Then, the correlation coefficients between bands are calculated and correlation matrix is given. According to the size of the correlation coefficient, the bands can be set into several groups. At last, the conception of normalized variance is used on behalf of the information content of each band. The bands are sorted by the value of its normalized variance. Set needing number of bands, and the optimum band combination solution can be get by these three steps. This method retains the greatest degree of difference between the target of interest and is easy to achieve by computer automatically. Besides, false color image synthesis experiment is carried out using the bands selected by this method as well as other 3 methods to show the performance of method in this paper.

  18. ELV Recycling Service Provider Selection Using the Hybrid MCDM Method: A Case Application in China

    Directory of Open Access Journals (Sweden)

    Fuli Zhou

    2016-05-01

    Full Text Available With the rapid depletion of natural resources and undesired environmental changes globally, more interest has been shown in the research of green supply chain practices, including end-of-life vehicle (ELV recycling. The ELV recycling is mandatory for auto-manufacturers by legislation for the purpose of minimizing potential environmental damages. The purpose of the present research is to determine the best choice of ELV recycling service provider by employing an integrating hybrid multi-criteria decision making (MCDM method. In this research, economic, environmental and social factors are taken into consideration. The linguistic variables and trapezoidal fuzzy numbers (TFNs are applied into this evaluation to deal with the vague and qualitative information. With the combined weight calculation of criteria based on fuzzy aggregation and Shannon Entropy techniques, the normative multi-criteria optimization technique (FVIKOR method is applied to explore the best solution. An application was performed based on the proposed hybrid MCDM method, and sensitivity analysis was conducted on different decision making scenarios. The present study provides a decision-making approach on ELV recycling business selection under sustainability and green philosophy with high robustness and easy implementation.

  19. Assessment selection in human-automation interaction studies: The Failure-GAM2E and review of assessment methods for highly automated driving.

    Science.gov (United States)

    Grane, Camilla

    2018-01-01

    Highly automated driving will change driver's behavioural patterns. Traditional methods used for assessing manual driving will only be applicable for the parts of human-automation interaction where the driver intervenes such as in hand-over and take-over situations. Therefore, driver behaviour assessment will need to adapt to the new driving scenarios. This paper aims at simplifying the process of selecting appropriate assessment methods. Thirty-five papers were reviewed to examine potential and relevant methods. The review showed that many studies still relies on traditional driving assessment methods. A new method, the Failure-GAM 2 E model, with purpose to aid assessment selection when planning a study, is proposed and exemplified in the paper. Failure-GAM 2 E includes a systematic step-by-step procedure defining the situation, failures (Failure), goals (G), actions (A), subjective methods (M), objective methods (M) and equipment (E). The use of Failure-GAM 2 E in a study example resulted in a well-reasoned assessment plan, a new way of measuring trust through feet movements and a proposed Optimal Risk Management Model. Failure-GAM 2 E and the Optimal Risk Management Model are believed to support the planning process for research studies in the field of human-automation interaction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Optimal Site Selection of Electric Vehicle Charging Stations Based on a Cloud Model and the PROMETHEE Method

    Directory of Open Access Journals (Sweden)

    Yunna Wu

    2016-03-01

    Full Text Available The task of site selection for electric vehicle charging stations (EVCS is hugely important from the perspective of harmonious and sustainable development. However, flaws and inadequacies in the currently used multi-criteria decision making methods could result in inaccurate and irrational decision results. First of all, the uncertainty of the information cannot be described integrally in the evaluation of the EVCS site selection. Secondly, rigorous consideration of the mutual influence between the various criteria is lacking, which is mainly evidenced in two aspects: one is ignoring the correlation, and the other is the unconscionable measurements. Last but not least, the ranking method adopted in previous studies is not very appropriate for evaluating the EVCS site selection problem. As a result of the above analysis, a Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE method-based decision system combined with the cloud model is proposed in this paper for EVCS site selection. Firstly, the use of the PROMETHEE method can bolster the confidence and visibility for decision makers. Secondly, the cloud model is recommended to describe the fuzziness and randomness of linguistic terms integrally and accurately. Finally, the Analytical Network Process (ANP method is adopted to measure the correlation of the indicators with a greatly simplified calculation of the parameters and the steps required.

  1. A comparison of U.S. and European methods for accident scenario, identificaton, selection and quantification

    International Nuclear Information System (INIS)

    Cadwallader, L.C.; Djerassi, H.; Lampin, I.

    1989-10-01

    This paper presents a comparison of the varying methods used to identify and select accident-initiating events for safety analysis and probabilistic risk assessment (PRA). Initiating events are important in that they define the extent of a given safety analysis or PRA. Comprehensiveness in identification and selection of initiating events is necessary to ensure that a thorough analysis is being performed. While total completeness cannot ever be realized, inclusion of all safety significant events can be attained. The European approach to initiating event identification and selection arises from within a newly developed Safety Analysis methodology framework. This is a functional approach, with accident initiators based on events that will cause a system or facility loss of function. The US method divides accident initiators into two groups, internal accident initiators into two groups, internal and external events. Since traditional US PRA techniques are applied to fusion facilities, the recommended PRA-based approach is a review of historical safety documents coupled with a facility-level Master Logic Diagram. The US and European methods are described, and both are applied to a proposed International Thermonuclear Experiment Reactor (ITER) Magnet System in a sample problem. Contrasts in the US and European methods are discussed. Within their respective frameworks, each method can provide the comprehensiveness of safety-significant events needed for a thorough analysis. 4 refs., 8 figs., 11 tabs

  2. Dichotomous versus semi-quantitative scoring of ultrasound joint inflammation in rheumatoid arthritis using novel individualized joint selection methods.

    Science.gov (United States)

    Tan, York Kiat; Allen, John C; Lye, Weng Kit; Conaghan, Philip G; Chew, Li-Ching; Thumboo, Julian

    2017-05-01

    The aim of the study is to compare the responsiveness of two joint inflammation scoring systems (dichotomous scoring (DS) versus semi-quantitative scoring (SQS)) using novel individualized ultrasound joint selection methods and existing ultrasound joint selection methods. Responsiveness measured by the standardized response means (SRMs) using the DS and the SQS system (for both the novel and existing ultrasound joint selection methods) was derived using the baseline and the 3-month total inflammatory scores from 20 rheumatoid arthritis patients. The relative SRM gain ratios (SRM-Gains) for both scoring system (DS and SQS) comparing the novel to the existing methods were computed. Both scoring systems (DS and SQS) demonstrated substantial SRM-Gains (ranged from 3.31 to 5.67 for the DS system and ranged from 1.82 to 3.26 for the SQS system). The SRMs using the novel methods ranged from 0.94 to 1.36 for the DS system and ranged from 0.89 to 1.11 for the SQS system. The SRMs using the existing methods ranged from 0.24 to 0.32 for the DS system and ranged from 0.34 to 0.49 for the SQS system. The DS system appears to achieve high responsiveness comparable to SQS for the novel individualized ultrasound joint selection methods.

  3. Selection of analytical methods for mixed waste analysis at the Hanford Site

    International Nuclear Information System (INIS)

    Morant, P.M.

    1994-09-01

    This document describes the process that the US Department of Energy (DOE), Richland Operations Office (RL) and contractor laboratories use to select appropriate or develop new or modified analytical methods. These methods are needed to provide reliable mixed waste characterization data that meet project-specific quality assurance (QA) requirements while also meeting health and safety standards for handling radioactive materials. This process will provide the technical basis for DOE's analysis of mixed waste and support requests for regulatory approval of these new methods when they are used to satisfy the regulatory requirements of the Hanford Federal Facility Agreement and Consent Order (Tri-party Agreement) (Ecology et al. 1992)

  4. Selection of Investment Projects by Monte Carlo Method in Risk Condition

    Directory of Open Access Journals (Sweden)

    M. E.

    2017-12-01

    Full Text Available The Monte Carlo method (also known as the Monte Carlo simulation was proposed by Nicholas Metropolis, S. Ulam and Jhon Von Neiman in 50-th years of the past century. The method can be widely applied to analysis of investment projects due to the advantages recognized both by practitioners and the academic community. The balance model of a project with discounted financial flows has been implemented for Microsoft Excel and Google Docs spread-sheet solutions. The Monte Carlo method for project with low and high correlated net present value (NPV parameters in the environment of the electronic tables of MS Excel/Google Docs. A distinct graduation of risk was identified. A necessity of account of correlation effects and the use of multivariate imitation during the project selection has been demonstrated.

  5. A Novel Extension Decision-Making Method for Selecting Solar Power Systems

    Directory of Open Access Journals (Sweden)

    Meng-Hui Wang

    2013-01-01

    Full Text Available Due to the complex parameters of a solar power system, the designer not only must think about the load demand but also needs to consider the price, weight, and annual power generating capacity (APGC and maximum power of the solar system. It is an important task to find the optimal solar power system with many parameters. Therefore, this paper presents a novel decision-making method based on the extension theory; we call it extension decision-making method (EDMM. Using the EDMM can make it quick to select the optimal solar power system. The paper proposed this method not only to provide a useful estimated tool for the solar system engineers but also to supply the important reference with the installation of solar systems to the consumer.

  6. A method for the computation of turbulent polymeric liquids including hydrodynamic interactions and chain entanglements

    Energy Technology Data Exchange (ETDEWEB)

    Kivotides, Demosthenes, E-mail: demosthenes.kivotides@strath.ac.uk

    2017-02-12

    An asymptotically exact method for the direct computation of turbulent polymeric liquids that includes (a) fully resolved, creeping microflow fields due to hydrodynamic interactions between chains, (b) exact account of (subfilter) residual stresses, (c) polymer Brownian motion, and (d) direct calculation of chain entanglements, is formulated. Although developed in the context of polymeric fluids, the method is equally applicable to turbulent colloidal dispersions and aerosols. - Highlights: • An asymptotically exact method for the computation of polymer and colloidal fluids is developed. • The method is valid for all flow inertia and all polymer volume fractions. • The method models entanglements and hydrodynamic interactions between polymer chains.

  7. Development of calculation method for one-dimensional kinetic analysis in fission reactors, including feedback effects

    International Nuclear Information System (INIS)

    Paixao, S.B.; Marzo, M.A.S.; Alvim, A.C.M.

    1986-01-01

    The calculation method used in WIGLE code is studied. Because of the non availability of such a praiseworthy solution, expounding the method minutely has been tried. This developed method has been applied for the solution of the one-dimensional, two-group, diffusion equations in slab, axial analysis, including non-boiling heat transfer, accountig for feedback. A steady-state program (CITER-1D), written in FORTRAN 4, has been implemented, providing excellent results, ratifying the developed work quality. (Author) [pt

  8. Selecting minimum dataset soil variables using PLSR as a regressive multivariate method

    Science.gov (United States)

    Stellacci, Anna Maria; Armenise, Elena; Castellini, Mirko; Rossi, Roberta; Vitti, Carolina; Leogrande, Rita; De Benedetto, Daniela; Ferrara, Rossana M.; Vivaldi, Gaetano A.

    2017-04-01

    Long-term field experiments and science-based tools that characterize soil status (namely the soil quality indices, SQIs) assume a strategic role in assessing the effect of agronomic techniques and thus in improving soil management especially in marginal environments. Selecting key soil variables able to best represent soil status is a critical step for the calculation of SQIs. Current studies show the effectiveness of statistical methods for variable selection to extract relevant information deriving from multivariate datasets. Principal component analysis (PCA) has been mainly used, however supervised multivariate methods and regressive techniques are progressively being evaluated (Armenise et al., 2013; de Paul Obade et al., 2016; Pulido Moncada et al., 2014). The present study explores the effectiveness of partial least square regression (PLSR) in selecting critical soil variables, using a dataset comparing conventional tillage and sod-seeding on durum wheat. The results were compared to those obtained using PCA and stepwise discriminant analysis (SDA). The soil data derived from a long-term field experiment in Southern Italy. On samples collected in April 2015, the following set of variables was quantified: (i) chemical: total organic carbon and nitrogen (TOC and TN), alkali-extractable C (TEC and humic substances - HA-FA), water extractable N and organic C (WEN and WEOC), Olsen extractable P, exchangeable cations, pH and EC; (ii) physical: texture, dry bulk density (BD), macroporosity (Pmac), air capacity (AC), and relative field capacity (RFC); (iii) biological: carbon of the microbial biomass quantified with the fumigation-extraction method. PCA and SDA were previously applied to the multivariate dataset (Stellacci et al., 2016). PLSR was carried out on mean centered and variance scaled data of predictors (soil variables) and response (wheat yield) variables using the PLS procedure of SAS/STAT. In addition, variable importance for projection (VIP

  9. The Analysis Of Accuracy Of Selected Methods Of Measuring The Thermal Resistance Of IGBTs

    Directory of Open Access Journals (Sweden)

    Górecki Krzysztof

    2015-09-01

    Full Text Available In the paper selected methods of measuring the thermal resistance of an IGBT (Insulated Gate Bipolar Transistor are presented and the accuracy of these methods is analysed. The analysis of the measurement error is performed and operating conditions of the considered device, at which each measurement method assures the least measuring error, are pointed out. Theoretical considerations are illustrated with some results of measurements and calculations.

  10. New visible and selective DNA staining method in gels with tetrazolium salts.

    Science.gov (United States)

    Paredes, Aaron J; Naranjo-Palma, Tatiana; Alfaro-Valdés, Hilda M; Barriga, Andrés; Babul, Jorge; Wilson, Christian A M

    2017-01-15

    DNA staining in gels has historically been carried out using silver staining and fluorescent dyes like ethidium bromide and SYBR Green I (SGI). Using fluorescent dyes allows recovery of the analyte, but requires instruments such as a transilluminator or fluorimeter to visualize the DNA. Here we described a new and simple method that allows DNA visualization to the naked eye by generating a colored precipitate. It works by soaking the acrylamide or agarose DNA gel in SGI and nitro blue tetrazolium (NBT) solution that, when exposed to sunlight, produces a purple insoluble formazan precipitate that remains in the gel after exposure to light. A calibration curve made with a DNA standard established a detection limit of approximately 180 pg/band at 500 bp. Selectivity of this assay was determined using different biomolecules, demonstrating a high selectivity for DNA. Integrity and functionality of the DNA recovered from gels was determined by enzymatic cutting with a restriction enzyme and by transforming competent cells after the different staining methods, respectively. Our method showed the best performance among the dyes employed. Based on its specificity, low cost and its adequacy for field work, this new methodology has enormous potential benefits to research and industry. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

    Science.gov (United States)

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...

  12. Analysis of Various Frequency Selective Shielding Glass by FDTD method

    OpenAIRE

    笠嶋, 善憲; Kasashima, Yoshinori

    2012-01-01

    A frequency Selective shielding (FSS) glass is a print of many same size antennas on a sheet of glass, and it has high shielding properties for one specific frequency. This time, the author analyzed characteristics of various FSSs whose antenna types are different by FDTD method. The antenna types are cross dipole, circular loop, square loop, circular patch, and square patch. As the result, the FSSs can be composed of the various types of the antennas, and the FSSs have broad-band shielding c...

  13. The CHOICE study: effect of counselling on the selection of combined hormonal contraceptive methods in 11 countries.

    Science.gov (United States)

    Bitzer, Johannes; Gemzell-Danielsson, Kristina; Roumen, Frans; Marintcheva-Petrova, Maya; van Bakel, Bas; Oddens, Björn J

    2012-02-01

    To encourage healthcare professionals to counsel women seeking combined hormonal contraceptives (CHCs) about alternative CHCs and to study the influence of counselling on women's selection of CHCs. Women (15-40 years old) in 11 countries who consulted HCPs about CHCs were counselled about the pill, transdermal patch, and vaginal ring. Both the HCPs and the women completed questionnaires. Of women who were counselled (n = 18,787), 47% selected another CHC method than originally planned. One in four who intended to use the pill chose another method (16% chose the patch; 65% chose the ring). In total, patch use increased from 5% -8% (difference = 3.7% [97.5% CI: 3.3-4.2]; p use nearly quadrupled from 8% -30% (difference = 21.7% [97.5% CI: 21.0-22.5]; p women who were undecided prior to counselling selected a method after counselling. Selection of the pill increased most in Russia (+ 11%) and Sweden (+ 5%); patch selection was greatest in Russia (+ 7%) and Israel (+ 6%); ring use increased most in Ukraine and in the Czech Republic and Slovakia (+ 36%). Counselling increases use of alternative CHCs, such as the patch and the ring. Considerable differences between countries were noted.

  14. A simple method for finding explicit analytic transition densities of diffusion processes with general diploid selection.

    Science.gov (United States)

    Song, Yun S; Steinrücken, Matthias

    2012-03-01

    The transition density function of the Wright-Fisher diffusion describes the evolution of population-wide allele frequencies over time. This function has important practical applications in population genetics, but finding an explicit formula under a general diploid selection model has remained a difficult open problem. In this article, we develop a new computational method to tackle this classic problem. Specifically, our method explicitly finds the eigenvalues and eigenfunctions of the diffusion generator associated with the Wright-Fisher diffusion with recurrent mutation and arbitrary diploid selection, thus allowing one to obtain an accurate spectral representation of the transition density function. Simplicity is one of the appealing features of our approach. Although our derivation involves somewhat advanced mathematical concepts, the resulting algorithm is quite simple and efficient, only involving standard linear algebra. Furthermore, unlike previous approaches based on perturbation, which is applicable only when the population-scaled selection coefficient is small, our method is nonperturbative and is valid for a broad range of parameter values. As a by-product of our work, we obtain the rate of convergence to the stationary distribution under mutation-selection balance.

  15. Improvement of prediction ability for genomic selection of dairy cattle by including dominance effects.

    Directory of Open Access Journals (Sweden)

    Chuanyu Sun

    Full Text Available Dominance may be an important source of non-additive genetic variance for many traits of dairy cattle. However, nearly all prediction models for dairy cattle have included only additive effects because of the limited number of cows with both genotypes and phenotypes. The role of dominance in the Holstein and Jersey breeds was investigated for eight traits: milk, fat, and protein yields; productive life; daughter pregnancy rate; somatic cell score; fat percent and protein percent. Additive and dominance variance components were estimated and then used to estimate additive and dominance effects of single nucleotide polymorphisms (SNPs. The predictive abilities of three models with both additive and dominance effects and a model with additive effects only were assessed using ten-fold cross-validation. One procedure estimated dominance values, and another estimated dominance deviations; calculation of the dominance relationship matrix was different for the two methods. The third approach enlarged the dataset by including cows with genotype probabilities derived using genotyped ancestors. For yield traits, dominance variance accounted for 5 and 7% of total variance for Holsteins and Jerseys, respectively; using dominance deviations resulted in smaller dominance and larger additive variance estimates. For non-yield traits, dominance variances were very small for both breeds. For yield traits, including additive and dominance effects fit the data better than including only additive effects; average correlations between estimated genetic effects and phenotypes showed that prediction accuracy increased when both effects rather than just additive effects were included. No corresponding gains in prediction ability were found for non-yield traits. Including cows with derived genotype probabilities from genotyped ancestors did not improve prediction accuracy. The largest additive effects were located on chromosome 14 near DGAT1 for yield traits for both

  16. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

    Science.gov (United States)

    Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

    2017-07-01

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

  17. Factor analysis improves the selection of prescribing indicators

    DEFF Research Database (Denmark)

    Rasmussen, Hanne Marie Skyggedal; Søndergaard, Jens; Sokolowski, Ineta

    2006-01-01

    OBJECTIVE: To test a method for improving the selection of indicators of general practitioners' prescribing. METHODS: We conducted a prescription database study including all 180 general practices in the County of Funen, Denmark, approximately 472,000 inhabitants. Principal factor analysis was us...... appropriate and inappropriate prescribing, as revealed by the correlation of the indicators in the first factor. CONCLUSION: Correlation and factor analysis is a feasible method that assists the selection of indicators and gives better insight into prescribing patterns....

  18. A Simple and Sensitive Plant-Based Western Corn Rootworm Bioassay Method for Resistance Determination and Event Selection.

    Science.gov (United States)

    Wen, Zhimou; Chen, Jeng Shong

    2018-05-26

    We report here a simple and sensitive plant-based western corn rootworm, Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae), bioassay method that allows for examination of multiple parameters for both plants and insects in a single experimental setup within a short duration. For plants, injury to roots can be visually examined, fresh root weight can be measured, and expression of trait protein in plant roots can be analyzed. For insects, in addition to survival, larval growth and development can be evaluated in several aspects including body weight gain, body length, and head capsule width. We demonstrated using the method that eCry3.1Ab-expressing 5307 corn was very effective against western corn rootworm by eliciting high mortality and significantly inhibiting larval growth and development. We also validated that the method allowed determination of resistance in an eCry3.1Ab-resistant western corn rootworm strain. While data presented in this paper demonstrate the usefulness of the method for selection of events of protein traits and for determination of resistance in laboratory populations, we envision that the method can be applied in much broader applications.

  19. The Selected Method and Tools for Performance Measurement in the Green Supply Chain—Survey Analysis in Poland

    Directory of Open Access Journals (Sweden)

    Blanka Tundys

    2018-02-01

    Full Text Available The methods and tools for the performance measurement and evaluation of the green supply chain management are very important elements for the construction and function of this type of supply chain. The result is a presentation of the considerations underlying a very general model, which presents some selected tools, but no breakdown of individual industries. The considerations undertaken are important and have scientific added value as usually in practice, a very large number of tools are used to assess the supply chain, which are not always correlated or adapted to the specificity of the chain. It is worth pointing out which of the already used or completely new tools and methods will be most useful for assessing the green supply chain. The structure of the paper covers the theoretical and empirical. It includes an introduction, our goals and hypotheses, state of the art, methodology, empirical findings, and discussion. We present the definitional differences between green and sustainable supply chains and focus on the selection and identification of methods for the framework model for evaluating the green supply chain. In the next step, the theoretical and selected method and tools were compared to a survey of Poland. On the basis of the survey, we present the findings and discussions found in this area. The main methodology used includes a literature review, a survey analysis using a questionnaire and statistical tools. The survey was carried out in 2015 in sample organizations in Poland. The research results showed that organizations were aware of the environmental elements of measuring and assessing the supply chain from an environmental point of view, but their use depended on many factors: the area, size of the organization, or the industry. If certain boundary conditions are met and the organizations are aware of the essence of environmental aspects in the chain, then they are applying green measures to the supply chain. These findings

  20. Ion-selective electrodes

    Energy Technology Data Exchange (ETDEWEB)

    Mikhelson, Konstantin N. [St. Petersburg State Univ. (Russian Federation). Ion-Selective Electrode Laboratory

    2013-06-01

    Ion-selective electrodes (ISEs) have a wide range of applications in clinical, environmental, food and pharmaceutical analysis as well as further uses in chemistry and life sciences. Based on his profound experience as a researcher in ISEs and a course instructor, the author summarizes current knowledge for advanced teaching and training purposes with a particular focus on ionophore-based ISEs. Coverage includes the basics of measuring with ISEs, essential membrane potential theory and a comprehensive overview of the various classes of ion-selective electrodes. The principles of constructing ISEs are outlined, and the transfer of methods into routine analysis is considered.

  1. Analysis of multicriteria models application for selection of an optimal artificial lift method in oil production

    Directory of Open Access Journals (Sweden)

    Crnogorac Miroslav P.

    2016-01-01

    Full Text Available In the world today for the exploitation of oil reservoirs by artificial lift methods are applied different types of deep pumps (piston, centrifugal, screw, hydraulic, water jet pumps and gas lift (continuous, intermittent and plunger. Maximum values of oil production achieved by these exploitation methods are significantly different. In order to select the optimal exploitation method of oil well, the multicriteria analysis models are used. In this paper is presented an analysis of the multicriteria model's application known as VIKOR, TOPSIS, ELECTRE, AHP and PROMETHEE for selection of optimal exploitation method for typical oil well at Serbian exploration area. Ranking results of applicability of the deep piston pumps, hydraulic pumps, screw pumps, gas lift method and electric submersible centrifugal pumps, indicated that in the all above multicriteria models except in PROMETHEE, the optimal method of exploitation are deep piston pumps and gas lift.

  2. Complete Tangent Stiffness for eXtended Finite Element Method by including crack growth parameters

    DEFF Research Database (Denmark)

    Mougaard, J.F.; Poulsen, P.N.; Nielsen, L.O.

    2013-01-01

    the crack geometry parameters, such as the crack length and the crack direction directly in the virtual work formulation. For efficiency, it is essential to obtain a complete tangent stiffness. A new method in this work is presented to include an incremental form the crack growth parameters on equal terms......The eXtended Finite Element Method (XFEM) is a useful tool for modeling the growth of discrete cracks in structures made of concrete and other quasi‐brittle and brittle materials. However, in a standard application of XFEM, the tangent stiffness is not complete. This is a result of not including...... with the degrees of freedom in the FEM‐equations. The complete tangential stiffness matrix is based on the virtual work together with the constitutive conditions at the crack tip. Introducing the crack growth parameters as direct unknowns, both equilibrium equations and the crack tip criterion can be handled...

  3. Selection of materials using multi-criteria decision-making methods with minimum data

    Directory of Open Access Journals (Sweden)

    Shankar Chakraborty

    2013-07-01

    Full Text Available Selection of material for a specific engineering component, which plays a significant role in its design and proper functioning, is often treated as a multi-criteria decision-making (MCDM problem where the most suitable material is to be chosen based on a given set of conflicting criteria. For solving these MCDM problems, the designers do not generally know what should be the optimal number of criteria required for arriving at the best decisive action. Those criteria should be independent to each other and their number should usually limit to seven plus or minus two. In this paper, five material selection problems are solved using three common MCDM techniques to demonstrate the effect of number of criteria on the final rankings of the material alternatives. It is interesting to observe that the choices of the best suited materials solely depend on the criterion having the maximum priority value. It is also found that among the three MCDM methods, the ranking performance of VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje method is the best.

  4. Statistical approach for selection of regression model during validation of bioanalytical method

    Directory of Open Access Journals (Sweden)

    Natalija Nakov

    2014-06-01

    Full Text Available The selection of an adequate regression model is the basis for obtaining accurate and reproducible results during the bionalytical method validation. Given the wide concentration range, frequently present in bioanalytical assays, heteroscedasticity of the data may be expected. Several weighted linear and quadratic regression models were evaluated during the selection of the adequate curve fit using nonparametric statistical tests: One sample rank test and Wilcoxon signed rank test for two independent groups of samples. The results obtained with One sample rank test could not give statistical justification for the selection of linear vs. quadratic regression models because slight differences between the error (presented through the relative residuals were obtained. Estimation of the significance of the differences in the RR was achieved using Wilcoxon signed rank test, where linear and quadratic regression models were treated as two independent groups. The application of this simple non-parametric statistical test provides statistical confirmation of the choice of an adequate regression model.

  5. An objective method for High Dynamic Range source content selection

    DEFF Research Database (Denmark)

    Narwaria, Manish; Mantel, Claire; Da Silva, Matthieu Perreira

    2014-01-01

    With the aim of improving the immersive experience of the end user, High Dynamic Range (HDR) imaging has been gaining popularity. Therefore, proper validation and performance benchmarking of HDR processing algorithms is a key step towards standardization and commercial deployment. A crucial...... component of such validation studies is the selection of a challenging and balanced set of source (reference) HDR content. In order to facilitate this, we present an objective method based on the premise that a more challenging HDR scene encapsulates higher contrast, and as a result will show up more...

  6. An Efficient Adaptive Window Size Selection Method for Improving Spectrogram Visualization

    Directory of Open Access Journals (Sweden)

    Shibli Nisar

    2016-01-01

    Full Text Available Short Time Fourier Transform (STFT is an important technique for the time-frequency analysis of a time varying signal. The basic approach behind it involves the application of a Fast Fourier Transform (FFT to a signal multiplied with an appropriate window function with fixed resolution. The selection of an appropriate window size is difficult when no background information about the input signal is known. In this paper, a novel empirical model is proposed that adaptively adjusts the window size for a narrow band-signal using spectrum sensing technique. For wide-band signals, where a fixed time-frequency resolution is undesirable, the approach adapts the constant Q transform (CQT. Unlike the STFT, the CQT provides a varying time-frequency resolution. This results in a high spectral resolution at low frequencies and high temporal resolution at high frequencies. In this paper, a simple but effective switching framework is provided between both STFT and CQT. The proposed method also allows for the dynamic construction of a filter bank according to user-defined parameters. This helps in reducing redundant entries in the filter bank. Results obtained from the proposed method not only improve the spectrogram visualization but also reduce the computation cost and achieves 87.71% of the appropriate window length selection.

  7. A comparison of methods to separate treatment from self-selection effects in an online banking setting

    NARCIS (Netherlands)

    Gensler, S.; Leeflang, P.S.H.; Skiera, B.

    The literature discusses several methods to control for self-selection effects but provides little guidance on which method to use in a setting with a limited number of variables. The authors theoretically compare and empirically assess the performance of different matching methods and instrumental

  8. [Targeted pharmacist-led medication order review in hospital: Assessment of a selection method for drug prescriptions].

    Science.gov (United States)

    Jarre, C; Bouchet, J; Hellot-Guersing, M; Leromain, A-S; Derharoutunian, C; Gadot, A; Roubille, R

    2017-11-01

    The aim of this study was to assess a selection method for drug prescriptions developed at the hospital level that allows to target pharmacist-led medication order review for at-risk patients and drugs. A one-month study has been conducted on all targeted medication orders in 19 care units. Selection criteria have been identified: biological criteria, alert medications and drug interactions. Pharmacists' interventions proposed during medication order review were listed and the possible links to the selection criteria were determined. A total of 1612 prescriptions were analysed and 236 pharmacists' interventions were performed (14.6 interventions per 100 prescriptions). Physicians' acceptance rate was 60.6%. The percentage of pharmacists' interventions linked to the selection criteria was 35.6%. The relevance of the biological criteria was identified, particularly the one identifying patients with creatinine clearance below 30ml/min. Six alert medications were also relevant selection criteria: dabigatran, morphine, gentamicin, methotrexate, potassium chloride and trimethoprim sulfamethoxazole. Drug interactions criteria was irrelevant. This study allowed a first assessment of the selection criteria used. A largest study seems necessary to continue the analysis of this selection method for prescriptions, especially the assessment of the alert medications list, in order to refine the prescriptions targeting. Copyright © 2017 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

  9. Method for assessment of stormwater treatment facilities - Synthetic road runoff addition including micro-pollutants and tracer.

    Science.gov (United States)

    Cederkvist, Karin; Jensen, Marina B; Holm, Peter E

    2017-08-01

    Stormwater treatment facilities (STFs) are becoming increasingly widespread but knowledge on their performance is limited. This is due to difficulties in obtaining representative samples during storm events and documenting removal of the broad range of contaminants found in stormwater runoff. This paper presents a method to evaluate STFs by addition of synthetic runoff with representative concentrations of contaminant species, including the use of tracer for correction of removal rates for losses not caused by the STF. A list of organic and inorganic contaminant species, including trace elements representative of runoff from roads is suggested, as well as relevant concentration ranges. The method was used for adding contaminants to three different STFs including a curbstone extension with filter soil, a dual porosity filter, and six different permeable pavements. Evaluation of the method showed that it is possible to add a well-defined mixture of contaminants despite different field conditions by having a flexibly system, mixing different stock-solutions on site, and use bromide tracer for correction of outlet concentrations. Bromide recovery ranged from only 12% in one of the permeable pavements to 97% in the dual porosity filter, stressing the importance of including a conservative tracer for correction of contaminant retention values. The method is considered useful in future treatment performance testing of STFs. The observed performance of the STFs is presented in coming papers. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. New Method of Selecting Efficient Project Portfolios in the Presence of Hybrid Uncertainty

    Directory of Open Access Journals (Sweden)

    Bogdan Rębiasz

    2016-01-01

    Full Text Available A new methods of selecting efficient project portfolios in the presence of hybrid uncertainty has been presented. Pareto optimal solutions have been defined by an algorithm for generating project portfolios. The method presented allows us to select efficient project portfolios taking into account statistical and economic dependencies between projects when some of the parameters used in the calculation of effectiveness can be expressed in the form of an interactive possibility distribution and some in the form of a probability distribution. The procedure for processing such hybrid data combines stochastic simulation with nonlinear programming. The interaction between data are modeled by correlation matrices and the interval regression. Economic dependences are taken into account by the equations balancing the production capacity of the company. The practical example presented indicates that an interaction between projects has a significant impact on the results of calculations. (original abstract

  11. Directional Darwinian Selection in proteins.

    Science.gov (United States)

    McClellan, David A

    2013-01-01

    Molecular evolution is a very active field of research, with several complementary approaches, including dN/dS, HON90, MM01, and others. Each has documented strengths and weaknesses, and no one approach provides a clear picture of how natural selection works at the molecular level. The purpose of this work is to present a simple new method that uses quantitative amino acid properties to identify and characterize directional selection in proteins. Inferred amino acid replacements are viewed through the prism of a single physicochemical property to determine the amount and direction of change caused by each replacement. This allows the calculation of the probability that the mean change in the single property associated with the amino acid replacements is equal to zero (H0: μ = 0; i.e., no net change) using a simple two-tailed t-test. Example data from calanoid and cyclopoid copepod cytochrome oxidase subunit I sequence pairs are presented to demonstrate how directional selection may be linked to major shifts in adaptive zones, and that convergent evolution at the whole organism level may be the result of convergent protein adaptations. Rather than replace previous methods, this new method further complements existing methods to provide a holistic glimpse of how natural selection shapes protein structure and function over evolutionary time.

  12. An improved culture method for selective isolation of Campylobacter jejuni from wastewater

    Directory of Open Access Journals (Sweden)

    Jinyong Kim

    2016-08-01

    Full Text Available Campylobacter jejuni is one of the leading foodborne pathogens worldwide. C. jejuni is isolated from a wide range of foods, domestic animals, wildlife, and environmental sources. The currently-available culture-based isolation methods are not highly effective for wastewater samples due to the low number of C. jejuni in the midst of competing bacteria. To detect and isolate C. jejuni from wastewater samples, in this study, we evaluated a few different enrichment conditions using five different antibiotics (i.e., cefoperazone, vancomycin, trimethoprim, polymyxin B, and rifampicin, to which C. jejuni is intrinsically resistant. The selectivity of each enrichment condition was measured with Ct value using quantitative real-time PCR (qRT-PCR, and multiplex PCR to determine Campylobacter species. In addition, the efficacy of Campylobacter isolation on different culture media after selective enrichment was examined by growing on Bolton and Preston agar plates. The addition of polymyxin B, rifampicin, or both to the Bolton selective supplements enhanced the selective isolation of C. jejuni. In particular, rifampicin supplementation and an increased culture temperature (i.e., 42°C had a decisive effect on the selective enrichment of C. jejuni from wastewater. The results of 16S rDNA sequencing also revealed that Enterococcus spp. and Pseudomonas aeruginosa are major competing bacteria in the enrichment conditions. Although it is known to be difficult to isolate Campylobacter from samples with heavy contamination, this study well exhibited that the manipulation of antibiotic selective pressure improves the isolation efficiency of fastidious Campylobacter from wastewater.

  13. A stereo remote sensing feature selection method based on artificial bee colony algorithm

    Science.gov (United States)

    Yan, Yiming; Liu, Pigang; Zhang, Ye; Su, Nan; Tian, Shu; Gao, Fengjiao; Shen, Yi

    2014-05-01

    To improve the efficiency of stereo information for remote sensing classification, a stereo remote sensing feature selection method is proposed in this paper presents, which is based on artificial bee colony algorithm. Remote sensing stereo information could be described by digital surface model (DSM) and optical image, which contain information of the three-dimensional structure and optical characteristics, respectively. Firstly, three-dimensional structure characteristic could be analyzed by 3D-Zernike descriptors (3DZD). However, different parameters of 3DZD could descript different complexity of three-dimensional structure, and it needs to be better optimized selected for various objects on the ground. Secondly, features for representing optical characteristic also need to be optimized. If not properly handled, when a stereo feature vector composed of 3DZD and image features, that would be a lot of redundant information, and the redundant information may not improve the classification accuracy, even cause adverse effects. To reduce information redundancy while maintaining or improving the classification accuracy, an optimized frame for this stereo feature selection problem is created, and artificial bee colony algorithm is introduced for solving this optimization problem. Experimental results show that the proposed method can effectively improve the computational efficiency, improve the classification accuracy.

  14. Method and apparatus for controlling a powertrain system including a multi-mode transmission

    Science.gov (United States)

    Hessell, Steven M.; Morris, Robert L.; McGrogan, Sean W.; Heap, Anthony H.; Mendoza, Gil J.

    2015-09-08

    A powertrain including an engine and torque machines is configured to transfer torque through a multi-mode transmission to an output member. A method for controlling the powertrain includes employing a closed-loop speed control system to control torque commands for the torque machines in response to a desired input speed. Upon approaching a power limit of a power storage device transferring power to the torque machines, power limited torque commands are determined for the torque machines in response to the power limit and the closed-loop speed control system is employed to determine an engine torque command in response to the desired input speed and the power limited torque commands for the torque machines.

  15. Designing monitoring programs for chemicals of emerging concern in potable reuse--what to include and what not to include?

    Science.gov (United States)

    Drewes, J E; Anderson, P; Denslow, N; Olivieri, A; Schlenk, D; Snyder, S A; Maruya, K A

    2013-01-01

    This study discussed a proposed process to prioritize chemicals for reclaimed water monitoring programs, selection of analytical methods required for their quantification, toxicological relevance of chemicals of emerging concern regarding human health, and related issues. Given that thousands of chemicals are potentially present in reclaimed water and that information about those chemicals is rapidly evolving, a transparent, science-based framework was developed to guide prioritization of which compounds of emerging concern (CECs) should be included in reclaimed water monitoring programs. The recommended framework includes four steps: (1) compile environmental concentrations (e.g., measured environmental concentration or MEC) of CECs in the source water for reuse projects; (2) develop a monitoring trigger level (MTL) for each of these compounds (or groups thereof) based on toxicological relevance; (3) compare the environmental concentration (e.g., MEC) to the MTL; CECs with a MEC/MTL ratio greater than 1 should be prioritized for monitoring, compounds with a ratio less than '1' should only be considered if they represent viable treatment process performance indicators; and (4) screen the priority list to ensure that a commercially available robust analytical method is available for that compound.

  16. Selective methods for polyphenols and sulphur dioxide determination in wines.

    Science.gov (United States)

    García-Guzmán, Juan J; Hernández-Artiga, María P; Palacios-Ponce de León, Lourdes; Bellido-Milla, Dolores

    2015-09-01

    A critical review to the methods recommended by international bodies and widely used in the winery industry and research studies was performed. A Laccase biosensor was applied to the selective determination of polyphenols in wines. The biosensor response was characterised and it responds mainly to o-diphenols which are the principal polyphenols responsible for the stability and sensory qualities of wines. The spectrophotometric method to determine free and total sulphur dioxide recommended for beers was applied directly to wines. A sampling of 14 red and white wines was performed and they were analysed for biosensor polyphenol index (IBP) and sulphur dioxide concentration (SO2). The antioxidant capacity by the ABTS(+) spectrophotometric method was also determined. A correlation study was performed to elucidate the influence of the polyphenols and SO2 on the wines stability. High correlations were found between IBP and antioxidant capacity and low correlation between SO2 and antioxidant capacity. To evaluate the benefits of wine drinking a new parameter (IBP/SO2) is proposed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Selective laser etching or ablation for fabrication of devices

    KAUST Repository

    Buttner, Ulrich

    2017-01-12

    Methods of fabricating devices vial selective laser etching are provided. The methods can include selective laser etching of a portion of a metal layer, e.g. using a laser light source having a wavelength of 1,000 nm to 1,500 nm. The methods can be used to fabricate a variety of features, including an electrode, an interconnect, a channel, a reservoir, a contact hole, a trench, a pad, or a combination thereof. A variety of devices fabricated according to the methods are also provided. In some aspects, capacitive humidity sensors are provided that can be fabricated according to the provided methods. The capacitive humidity sensors can be fabricated with intricate electrodes, e.g. having a fractal pattern such as a Peano curve, a Hilbert curve, a Moore curve, or a combination thereof.

  18. Reliability and limitation of various diagnostic methods including nuclear medicine in myocardial disease

    International Nuclear Information System (INIS)

    Tokuyasu, Yoshiki; Kusakabe, Kiyoko; Yamazaki, Toshio

    1981-01-01

    Electrocardiography (ECG), echocardiography, nuclear method, cardiac catheterization, left ventriculography and endomyocardial biopsy (biopsy) were performed in 40 cases of cardiomyopathy (CM), 9 of endocardial fibroelastosis and 19 of specific heart muscle disease, and the usefulness and limitation of each method was comparatively estimated. In CM, various methods including biopsy were performed. The 40 patients were classified into 3 groups, i.e., hypertrophic (17), dilated (20) and non-hypertrophic.non-dilated (3) on the basis of left ventricular ejection fraction and hypertrophy of the ventricular wall. The hypertrophic group was divided into 4 subgroups: 9 septal, 4 apical, 2 posterior and 2 anterior. The nuclear study is useful in assessing the site of the abnormal ventricular thickening, perfusion defect and ventricular function. Echocardiography is most useful in detecting asymmetric septal hypertrophy. The biopsy gives the sole diagnostic clue, especially in non-hypertrophic.non-dilated cardiomyopathy. ECG is useful in all cases but correlation with the site of disproportional hypertrophy was not obtained. (J.P.N.)

  19. FCNN-MR: A Parallel Instance Selection Method Based on Fast Condensed Nearest Neighbor Rule

    OpenAIRE

    Lu Si; Jie Yu; Shasha Li; Jun Ma; Lei Luo; Qingbo Wu; Yongqi Ma; Zhengji Liu

    2017-01-01

    Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rul...

  20. Developing TOPSIS method using statistical normalization for selecting knowledge management strategies

    Directory of Open Access Journals (Sweden)

    Amin Zadeh Sarraf

    2013-09-01

    Full Text Available Purpose: Numerous companies are expecting their knowledge management (KM to be performed effectively in order to leverage and transform the knowledge into competitive advantages. However, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy prior to a successful KM implementation. Design/methodology/approach: An extension of TOPSIS, a multi-attribute decision making (MADM technique, to a group decision environment is investigated. TOPSIS is a practical and useful technique for ranking and selection of a number of externally determined alternatives through distance measures. The entropy method is often used for assessing weights in the TOPSIS method. Entropy in information theory is a criterion uses for measuring the amount of disorder represented by a discrete probability distribution. According to decrease resistance degree of employees opposite of implementing a new strategy, it seems necessary to spot all managers’ opinion. The normal distribution considered the most prominent probability distribution in statistics is used to normalize gathered data. Findings: The results of this study show that by considering 6 criteria for alternatives Evaluation, the most appropriate KM strategy to implement  in our company was ‘‘Personalization’’. Research limitations/implications: In this research, there are some assumptions that might affect the accuracy of the approach such as normal distribution of sample and community. These assumptions can be changed in future work. Originality/value: This paper proposes an effective solution based on combined entropy and TOPSIS approach to help companies that need to evaluate and select KM strategies. In represented solution, opinions of all managers is gathered and normalized by using standard normal distribution and central limit theorem. Keywords: Knowledge management; strategy; TOPSIS; Normal distribution; entropy

  1. Duration and speed of speech events: A selection of methods

    Directory of Open Access Journals (Sweden)

    Gibbon Dafydd

    2015-07-01

    Full Text Available The study of speech timing, i.e. the duration and speed or tempo of speech events, has increased in importance over the past twenty years, in particular in connection with increased demands for accuracy, intelligibility and naturalness in speech technology, with applications in language teaching and testing, and with the study of speech timing patterns in language typology. H owever, the methods used in such studies are very diverse, and so far there is no accessible overview of these methods. Since the field is too broad for us to provide an exhaustive account, we have made two choices: first, to provide a framework of paradigmatic (classificatory, syntagmatic (compositional and functional (discourse-oriented dimensions for duration analysis; and second, to provide worked examples of a selection of methods associated primarily with these three dimensions. Some of the methods which are covered are established state-of-the-art approaches (e.g. the paradigmatic Classification and Regression Trees, CART , analysis, others are discussed in a critical light (e.g. so-called ‘rhythm metrics’. A set of syntagmatic approaches applies to the tokenisation and tree parsing of duration hierarchies, based on speech annotations, and a functional approach describes duration distributions with sociolinguistic variables. Several of the methods are supported by a new web-based software tool for analysing annotated speech data, the Time Group Analyser.

  2. Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection

    Directory of Open Access Journals (Sweden)

    Jaesung Lee

    2016-11-01

    Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

  3. Rapid one-step selection method for generating nucleic acid aptamers: development of a DNA aptamer against α-bungarotoxin.

    Directory of Open Access Journals (Sweden)

    Lasse H Lauridsen

    Full Text Available BACKGROUND: Nucleic acids based therapeutic approaches have gained significant interest in recent years towards the development of therapeutics against many diseases. Recently, research on aptamers led to the marketing of Macugen®, an inhibitor of vascular endothelial growth factor (VEGF for the treatment of age related macular degeneration (AMD. Aptamer technology may prove useful as a therapeutic alternative against an array of human maladies. Considering the increased interest in aptamer technology globally that rival antibody mediated therapeutic approaches, a simplified selection, possibly in one-step, technique is required for developing aptamers in limited time period. PRINCIPAL FINDINGS: Herein, we present a simple one-step selection of DNA aptamers against α-bungarotoxin. A toxin immobilized glass coverslip was subjected to nucleic acid pool binding and extensive washing followed by PCR enrichment of the selected aptamers. One round of selection successfully identified a DNA aptamer sequence with a binding affinity of 7.58 µM. CONCLUSION: We have demonstrated a one-step method for rapid production of nucleic acid aptamers. Although the reported binding affinity is in the low micromolar range, we believe that this could be further improved by using larger targets, increasing the stringency of selection and also by combining a capillary electrophoresis separation prior to the one-step selection. Furthermore, the method presented here is a user-friendly, cheap and an easy way of deriving an aptamer unlike the time consuming conventional SELEX-based approach. The most important application of this method is that chemically-modified nucleic acid libraries can also be used for aptamer selection as it requires only one enzymatic step. This method could equally be suitable for developing RNA aptamers.

  4. Optimal Selection Method of Process Patents for Technology Transfer Using Fuzzy Linguistic Computing

    Directory of Open Access Journals (Sweden)

    Gangfeng Wang

    2014-01-01

    Full Text Available Under the open innovation paradigm, technology transfer of process patents is one of the most important mechanisms for manufacturing companies to implement process innovation and enhance the competitive edge. To achieve promising technology transfers, we need to evaluate the feasibility of process patents and optimally select the most appropriate patent according to the actual manufacturing situation. Hence, this paper proposes an optimal selection method of process patents using multiple criteria decision-making and 2-tuple fuzzy linguistic computing to avoid information loss during the processes of evaluation integration. An evaluation index system for technology transfer feasibility of process patents is designed initially. Then, fuzzy linguistic computing approach is applied to aggregate the evaluations of criteria weights for each criterion and corresponding subcriteria. Furthermore, performance ratings for subcriteria and fuzzy aggregated ratings of criteria are calculated. Thus, we obtain the overall technology transfer feasibility of patent alternatives. Finally, a case study of aeroengine turbine manufacturing is presented to demonstrate the applicability of the proposed method.

  5. Selection strategy for the most Suitable CEC method for clay barrier characterisation

    International Nuclear Information System (INIS)

    Dohrmann, R.; Kaufhold, S.

    2010-01-01

    competition to barium ions in smectite interlayers. The present study aims at proposing a selection strategy for CEC methods including exchangeable cation determination of different clay materials typically used in radioactive waste disposal studies. 1) If the clay/bentonite contains calcium carbonates but no gypsum several methods are available, all of them are based on a saturation of the exchange solution with calcite before the exchange experiment starts: AgTU-calcite, CoHex-calcite, and Cu-trien5xcalcite. If dolomite is present the initial calcite saturation minimizes dolomite dissolution as well (proved for AgTU-calcite). 2) If a bentonite contains carbonates and gypsum the only known successful method for determination of all exchangeable cations (including calcium) and the CEC is a combination of two separate results: i) calcite saturation of exchange solution (e.g. Cu-trien5xcalcite) and ii) quantification of gypsum with suitable mineralogical methods. Result i) is free of error caused by calcite dissolution; however it is still wrong because it contains significant amounts of Ca 2+ from gypsum dissolution. After proving that gypsum was completely dissolved during the exchange experiment result ii) was used to subtract the theoretical Ca 2+ portion of gypsum from result i). Gypsum saturation of exchange solutions was tested as not suitable owing to the high solubility of gypsum which results in high initial Ca 2+ concentrations. 3) If no such soluble minerals are present and if the pore water contains no excess electrolyte then usually any accepted CEC method can be used, however, the results should always be checked for plausibility (e.g. using mineralogical composition of the sample). Any accepted method means that methods with known systematic errors (hydrophobic interaction, dependency on layer charge density) are excluded. (authors)

  6. Using multi-criteria decision methods for selecting a language school

    Directory of Open Access Journals (Sweden)

    Mileine Henriques Elias Velasco

    2014-11-01

    Full Text Available Nowadays, the interest of organizations by professionals who have deep knowledge concerning more than one language has been increasing. In this scenario, the choice of a language school has been one of the most common decision problems, which has been often made on the basis of word-of-mouth, marketing activities of schools and trials without criteria. In order to contribute to this problem, this paper presents a study in which two multi-criteria decision aid methods (AHP and Weighted Average were used to select a language school. Thus, the degree of importance of criteria relating to the problem and the degree of satisfaction of undergraduate and postgraduate students in relation to language schools they study were taken into account. The best ranked language school was the same for both MCDA methods, although some schools have obtained different positions. It was found that the analysis with AHP is richer and more elaborate than with the Weighted Average method. However, the large number of pairwise comparisons which were required to the study demanded significant attention and cognitive effort from the decision maker, and more time to perform the analysis - aspects that may contribute to the preference for the Weighted Average method in similar studies.

  7. Practical Approaches for Detecting Selection in Microbial Genomes.

    Science.gov (United States)

    Hedge, Jessica; Wilson, Daniel J

    2016-02-01

    Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.

  8. Rapid determination method of radiocesium in sea water by cesium-selective resin

    International Nuclear Information System (INIS)

    Nakaoka, A.; Yokoyama, H.; Fukushima, M.; Takagi, S.

    1980-01-01

    A rapid and precise method of determining radiocesium corresponding to 5 mrem/y (the Japan AEC's guideline) was proposed. The development and practical performance of cesium-selective resin and the determination method are described in this paper. The resin was prepared by the formation of ammonium molybdophosphate in the structure of Amberlite XAD-7 resin. It took only 3 hours to carry out all the procedures the authors proposed. This value represents 1/10 to 1/2 of the time of the conventional method. The concentration of 137 Cs and 134 Cs in sea water was determined to be 0.13 to 0.16 pCi/l and less than 7.1x10 -2 pCi/l, respectively. (author)

  9. THIRD PARTY LOGISTIC SERVICE PROVIDER SELECTION USING FUZZY AHP AND TOPSIS METHOD

    Directory of Open Access Journals (Sweden)

    Golam Kabir

    2012-03-01

    Full Text Available The use of third party logistic(3PL services providers is increasing globally to accomplish the strategic objectives. In the increasingly competitive environment, logistics strategic management requires systematic and structured approach to have cutting edge over the rival. Logistics service provider selection is a complex multi-criteria decision making process; in which, decision makers have to deals with the optimization of conflicting objectives such as quality, cost, and delivery time. In this paper, fuzzy analytic hierarchy process (FAHP approach based on technique for order preference by similarity to ideal solution (TOPSIS method has been proposed for evaluating and selecting an appropriate logistics service provider, where the ratings of each alternative and importance weight of each criterion are expressed in triangular fuzzy numbers.

  10. Success/Failure Prediction of Noninvasive Mechanical Ventilation in Intensive Care Units. Using Multiclassifiers and Feature Selection Methods.

    Science.gov (United States)

    Martín-González, Félix; González-Robledo, Javier; Sánchez-Hernández, Fernando; Moreno-García, María N

    2016-05-17

    This paper addresses the problem of decision-making in relation to the administration of noninvasive mechanical ventilation (NIMV) in intensive care units. Data mining methods were employed to find out the factors influencing the success/failure of NIMV and to predict its results in future patients. These artificial intelligence-based methods have not been applied in this field in spite of the good results obtained in other medical areas. Feature selection methods provided the most influential variables in the success/failure of NIMV, such as NIMV hours, PaCO2 at the start, PaO2 / FiO2 ratio at the start, hematocrit at the start or PaO2 / FiO2 ratio after two hours. These methods were also used in the preprocessing step with the aim of improving the results of the classifiers. The algorithms provided the best results when the dataset used as input was the one containing the attributes selected with the CFS method. Data mining methods can be successfully applied to determine the most influential factors in the success/failure of NIMV and also to predict NIMV results in future patients. The results provided by classifiers can be improved by preprocessing the data with feature selection techniques.

  11. Comparison of selected methods for the enumeration of fecal coliforms and Escherichia coli in shellfish.

    Science.gov (United States)

    Grabow, W O; De Villiers, J C; Schildhauer, C I

    1992-09-01

    In a comparison of five selected methods for the enumeration of fecal coliforms and Escherichia coli in naturally contaminated and sewage-seeded mussels (Choromytilus spp.) and oysters (Ostrea spp.), a spread-plate procedure with mFC agar without rosolic acid and preincubation proved the method of choice for routine quality assessment.

  12. Methods of forming aluminum oxynitride-comprising bodies, including methods of forming a sheet of transparent armor

    Science.gov (United States)

    Chu, Henry Shiu-Hung [Idaho Falls, ID; Lillo, Thomas Martin [Idaho Falls, ID

    2008-12-02

    The invention includes methods of forming an aluminum oxynitride-comprising body. For example, a mixture is formed which comprises A:B:C in a respective molar ratio in the range of 9:3.6-6.2:0.1-1.1, where "A" is Al.sub.2O.sub.3, "B" is AlN, and "C" is a total of one or more of B.sub.2O.sub.3, SiO.sub.2, Si--Al--O--N, and TiO.sub.2. The mixture is sintered at a temperature of at least 1,600.degree. C. at a pressure of no greater than 500 psia effective to form an aluminum oxynitride-comprising body which is at least internally transparent and has at least 99% maximum theoretical density.

  13. Improving the time efficiency of the Fourier synthesis method for slice selection in magnetic resonance imaging.

    Science.gov (United States)

    Tahayori, B; Khaneja, N; Johnston, L A; Farrell, P M; Mareels, I M Y

    2016-01-01

    The design of slice selective pulses for magnetic resonance imaging can be cast as an optimal control problem. The Fourier synthesis method is an existing approach to solve these optimal control problems. In this method the gradient field as well as the excitation field are switched rapidly and their amplitudes are calculated based on a Fourier series expansion. Here, we provide a novel insight into the Fourier synthesis method via representing the Bloch equation in spherical coordinates. Based on the spherical Bloch equation, we propose an alternative sequence of pulses that can be used for slice selection which is more time efficient compared to the original method. Simulation results demonstrate that while the performance of both methods is approximately the same, the required time for the proposed sequence of pulses is half of the original sequence of pulses. Furthermore, the slice selectivity of both sequences of pulses changes with radio frequency field inhomogeneities in a similar way. We also introduce a measure, referred to as gradient complexity, to compare the performance of both sequences of pulses. This measure indicates that for a desired level of uniformity in the excited slice, the gradient complexity for the proposed sequence of pulses is less than the original sequence. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  14. Analytical Comparison of Miniaturized Methods for Selected PAH Determination in Clean Waters; Comparacion Analitica de 4 Metodos Miniaturizados de Determinacion de PAHs mediante HPLC en Aguas

    Energy Technology Data Exchange (ETDEWEB)

    Garcia, S.; Perez, R. M.; Fernandez, O.

    2012-04-11

    A study on the comparison and evaluation of 4 miniaturized extraction methods for the determination of selected PAHs in clear waters is presented. Four types of liquid-liquid extraction were used for chromatographic analysis by HPLC/ FD. The main objective was the optimization and development of simple, rapid and low cost methods, minimizing the use of extracting solvent volume. The work also includes a study on the scope of the methods developed at low and high levels of concentration. (Author) 13 refs.

  15. Hierarchical Robot Control System and Method for Controlling Select Degrees of Freedom of an Object Using Multiple Manipulators

    Science.gov (United States)

    Abdallah, Muhammad E. (Inventor); Platt, Robert (Inventor); Wampler, II, Charles W. (Inventor)

    2013-01-01

    A robotic system includes a robot having manipulators for grasping an object using one of a plurality of grasp types during a primary task, and a controller. The controller controls the manipulators during the primary task using a multiple-task control hierarchy, and automatically parameterizes the internal forces of the system for each grasp type in response to an input signal. The primary task is defined at an object-level of control, e.g., using a closed-chain transformation, such that only select degrees of freedom are commanded for the object. A control system for the robotic system has a host machine and algorithm for controlling the manipulators using the above hierarchy. A method for controlling the system includes receiving and processing the input signal using the host machine, including defining the primary task at the object-level of control, e.g., using a closed-chain definition, and parameterizing the internal forces for each of grasp type.

  16. Breast cancer tumor classification using LASSO method selection approach

    International Nuclear Information System (INIS)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M.

    2016-10-01

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  17. Breast cancer tumor classification using LASSO method selection approach

    Energy Technology Data Exchange (ETDEWEB)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  18. Engine including hydraulically actuated valvetrain and method of valve overlap control

    Science.gov (United States)

    Cowgill, Joel [White Lake, MI

    2012-05-08

    An exhaust valve control method may include displacing an exhaust valve in communication with the combustion chamber of an engine to an open position using a hydraulic exhaust valve actuation system and returning the exhaust valve to a closed position using the hydraulic exhaust valve actuation assembly. During closing, the exhaust valve may be displaced for a first duration from the open position to an intermediate closing position at a first velocity by operating the hydraulic exhaust valve actuation assembly in a first mode. The exhaust valve may be displaced for a second duration greater than the first duration from the intermediate closing position to a fully closed position at a second velocity at least eighty percent less than the first velocity by operating the hydraulic exhaust valve actuation assembly in a second mode.

  19. Laccase-catalyzed oxidation and intramolecular cyclization of dopamine: A new method for selective determination of dopamine with laccase/carbon nanotube-based electrochemical biosensors

    International Nuclear Information System (INIS)

    Xiang, Ling; Lin, Yuqing; Yu, Ping; Su, Lei; Mao, Lanqun

    2007-01-01

    This study demonstrates a new electrochemical method for the selective determination of dopamine (DA) with the coexistence of ascorbic acid (AA) and 3,4-dihydroxyphenylacetic acid (DOPAC) with laccase/multi-walled carbon nanotube (MWNT)-based biosensors prepared by cross-linking laccase into MWNT layer confined onto glassy carbon electrodes. The method described here is essentially based on the chemical reaction properties of DA including oxidation, intramolecular cyclization and disproportionation reactions to finally give 5,6-dihydroxyindoline quinone and on the uses of the two-electron and two-proton reduction of the formed 5,6-dihydroxyindoline quinone to constitute a method for the selective determination of DA at a negative potential that is totally separated from those for the redox processes of AA and DOPAC. Instead of the ECE reactions of DA with the first oxidation of DA being driven electrochemically, laccase is used here as the biocatalyst to drive the first oxidation of DA into its quinone form and thus initialize the sequential reactions of DA finally into 5,6-dihydroxyindoline quinone. In addition, laccase also catalyzes the oxidation of AA and DOPAC into electroinactive species with the concomitant reduction of O 2 . As a consequence, a combinational exploitation of the chemical properties inherent in DA and the multifunctional catalytic properties of laccase as well as the excellent electrochemical properties of carbon nanotubes substantially enables the prepared laccase/MWNT-based biosensors to be well competent for the selective determination of DA with the coexistence of physiological levels of AA and DOPAC. This demonstration offers a new method for the selective determination of DA, which could be potentially employed for the determination of DA in biological systems

  20. The healthy building intervention study: Objectives, methods and results of selected environmental measurements

    Energy Technology Data Exchange (ETDEWEB)

    Fisk, W.J.; Faulkner, D.; Sullivan, D. [and others

    1998-02-17

    To test proposed methods for reducing SBS symptoms and to learn about the causes of these symptoms, a double-blind controlled intervention study was designed and implemented. This study utilized two different interventions designed to reduce occupants` exposures to airborne particles: (1) high efficiency filters in the building`s HVAC systems; and (2) thorough cleaning of carpeted floors and fabric-covered chairs with an unusually powerful vacuum cleaner. The study population was the workers on the second and fourth floors of a large office building with mechanical ventilation, air conditioning, and sealed windows. Interventions were implemented on one floor while the occupants on the other floor served as a control group. For the enhanced-filtration intervention, a multiple crossover design was used (a crossover is a repeat of the experiment with the former experimental group as the control group and vice versa). Demographic and health symptom data were collected via an initial questionnaire on the first study week and health symptom data were obtained each week, for eight additional weeks, via weekly questionnaires. A large number of indoor environmental parameters were measured during the study including air temperatures and humidities, carbon dioxide concentrations, particle concentrations, concentrations of several airborne bioaerosols, and concentrations of several microbiologic compounds within the dust sampled from floors and chairs. This report describes the study methods and summarizes the results of selected environmental measurements.

  1. [Selective mutism].

    Science.gov (United States)

    Ytzhak, A; Doron, Y; Lahat, E; Livne, A

    2012-10-01

    Selective mutism is an uncommon disorder in young children, in which they selectively don't speak in certain social situations, while being capable of speaking easily in other social situations. Many etiologies were proposed for selective mutism including psychodynamic, behavioral and familial etc. A developmental etiology that includes insights from all the above is gaining support. Accordingly, mild language impairment in a child with an anxiety trait may be at the root of developing selective mutism. The behavior will be reinforced by an avoidant pattern in the family. Early treatment and followup for children with selective mutism is important. The treatment includes non-pharmacological therapy (psychodynamic, behavioral and familial) and pharmacologic therapy--mainly selective serotonin reuptake inhibitors (SSRI).

  2. Closed-form solutions for linear regulator design of mechanical systems including optimal weighting matrix selection

    Science.gov (United States)

    Hanks, Brantley R.; Skelton, Robert E.

    1991-01-01

    Vibration in modern structural and mechanical systems can be reduced in amplitude by increasing stiffness, redistributing stiffness and mass, and/or adding damping if design techniques are available to do so. Linear Quadratic Regulator (LQR) theory in modern multivariable control design, attacks the general dissipative elastic system design problem in a global formulation. The optimal design, however, allows electronic connections and phase relations which are not physically practical or possible in passive structural-mechanical devices. The restriction of LQR solutions (to the Algebraic Riccati Equation) to design spaces which can be implemented as passive structural members and/or dampers is addressed. A general closed-form solution to the optimal free-decay control problem is presented which is tailored for structural-mechanical system. The solution includes, as subsets, special cases such as the Rayleigh Dissipation Function and total energy. Weighting matrix selection is a constrained choice among several parameters to obtain desired physical relationships. The closed-form solution is also applicable to active control design for systems where perfect, collocated actuator-sensor pairs exist.

  3. Automatic Peak Selection by a Benjamini-Hochberg-Based Algorithm

    KAUST Repository

    Abbas, Ahmed; Kong, Xin-Bing; Liu, Zhi; Jing, Bing-Yi; Gao, Xin

    2013-01-01

    A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into p-values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak [1] and PICKY [2]. Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx. © 2013

  4. Automatic Peak Selection by a Benjamini-Hochberg-Based Algorithm

    KAUST Repository

    Abbas, Ahmed

    2013-01-07

    A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into p-values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak [1] and PICKY [2]. Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx. © 2013

  5. A Methodology for the Selection of Multi-Criteria Decision Analysis Methods in Real Estate and Land Management Processes

    Directory of Open Access Journals (Sweden)

    Maria Rosaria Guarini

    2018-02-01

    Full Text Available Real estate and land management are characterised by a complex, elaborate combination of technical, regulatory and governmental factors. In Europe, Public Administrators must address the complex decision-making problems that need to be resolved, while also acting in consideration of the expectations of the different stakeholders involved in settlement transformation. In complex situations (e.g., with different aspects to be considered and multilevel actors involved, decision-making processes are often used to solve multidisciplinary and multidimensional analyses, which support the choices of those who are making the decision. Multi-Criteria Decision Analysis (MCDA methods are included among the examination and evaluation techniques considered useful by the European Community. Such analyses and techniques are performed using methods, which aim to reach a synthesis of the various forms of input data needed to define decision-making problems of a similar complexity. Thus, one or more of the conclusions reached allow for informed, well thought-out, strategic decisions. According to the technical literature on MCDA, numerous methods are applicable in different decision-making situations, however, advice for selecting the most appropriate for the specific field of application and problem have not been thoroughly investigated. In land and real estate management, numerous queries regarding evaluations often arise. In brief, the objective of this paper is to outline a procedure with which to select the method best suited to the specific queries of evaluation, which commonly arise while addressing decision-making problems. In particular issues of land and real estate management, representing the so-called “settlement sector”. The procedure will follow a theoretical-methodological approach by formulating a taxonomy of the endogenous and exogenous variables of the multi-criteria analysis methods.

  6. A Developed Meta-model for Selection of Cotton Fabrics Using Design of Experiments and TOPSIS Method

    Science.gov (United States)

    Chakraborty, Shankar; Chatterjee, Prasenjit

    2017-12-01

    Selection of cotton fabrics for providing optimal clothing comfort is often considered as a multi-criteria decision making problem consisting of an array of candidate alternatives to be evaluated based of several conflicting properties. In this paper, design of experiments and technique for order preference by similarity to ideal solution (TOPSIS) are integrated so as to develop regression meta-models for identifying the most suitable cotton fabrics with respect to the computed TOPSIS scores. The applicability of the adopted method is demonstrated using two real time examples. These developed models can also identify the statistically significant fabric properties and their interactions affecting the measured TOPSIS scores and final selection decisions. There exists good degree of congruence between the ranking patterns as derived using these meta-models and the existing methods for cotton fabric ranking and subsequent selection.

  7. A general method for selection of riboflavin-overproducing food grade micro-organisms

    OpenAIRE

    Burgess, Catherine M; Smid, Eddy J; Rutten, Ger; van Sinderen, Douwe

    2006-01-01

    Abstract Background This study describes a strategy to select and isolate spontaneous riboflavin-overproducing strains of Lactobacillus (Lb.) plantarum, Leuconostoc (Lc.) mesenteroides and Propionibacterium (P.) freudenreichii. Results The toxic riboflavin analogue roseoflavin was used to isolate natural riboflavin-overproducing variants of the food grade micro-organisms Lb. plantarum, Lc. mesenteroides and P. freudenreichii strains. The method was successfully employed for strains of all thr...

  8. Designing monitoring programs for chemicals of emerging concern in potable reuse ⋯ What to include and what not to include?

    KAUST Repository

    Drewes, Jorg; Anderson, Paul D.; Denslow, Nancy D.; Olivieri, Adam W.; Schlenk, Daniel K.; Snyder, Shane A.; Maruya, Keith

    2012-01-01

    This study discussed a proposed process to prioritize chemicals for reclaimed water monitoring programs, selection of analytical methods required for their quantification, toxicological relevance of chemicals of emerging concern regarding human health, and related issues. Given that thousands of chemicals are potentially present in reclaimed water and that information about those chemicals is rapidly evolving, a transparent, science-based framework was developed to guide prioritization of which compounds of emerging concern (CECs) should be included in reclaimed water monitoring programs. The recommended framework includes four steps: (1) compile environmental concentrations (e.g., measured environmental concentration or MEC) of CECs in the source water for reuse projects; (2) develop a monitoring trigger level (MTL) for each of these compounds (or groups thereof) based on toxicological relevance; (3) compare the environmental concentration (e.g., MEC) to the MTL; CECs with a MEC/MTL ratio greater than 1 should be prioritized for monitoring, compounds with a ratio less than '1' should only be considered if they represent viable treatment process performance indicators; and (4) screen the priority list to ensure that a commercially available robust analytical method is available for that compound. © IWA Publishing 2013.

  9. Designing monitoring programs for chemicals of emerging concern in potable reuse ⋯ What to include and what not to include?

    KAUST Repository

    Drewes, Jorg

    2012-11-01

    This study discussed a proposed process to prioritize chemicals for reclaimed water monitoring programs, selection of analytical methods required for their quantification, toxicological relevance of chemicals of emerging concern regarding human health, and related issues. Given that thousands of chemicals are potentially present in reclaimed water and that information about those chemicals is rapidly evolving, a transparent, science-based framework was developed to guide prioritization of which compounds of emerging concern (CECs) should be included in reclaimed water monitoring programs. The recommended framework includes four steps: (1) compile environmental concentrations (e.g., measured environmental concentration or MEC) of CECs in the source water for reuse projects; (2) develop a monitoring trigger level (MTL) for each of these compounds (or groups thereof) based on toxicological relevance; (3) compare the environmental concentration (e.g., MEC) to the MTL; CECs with a MEC/MTL ratio greater than 1 should be prioritized for monitoring, compounds with a ratio less than \\'1\\' should only be considered if they represent viable treatment process performance indicators; and (4) screen the priority list to ensure that a commercially available robust analytical method is available for that compound. © IWA Publishing 2013.

  10. IT Project Selection

    DEFF Research Database (Denmark)

    Pedersen, Keld

    2016-01-01

    for initiation. Most of the research on project selection is normative, suggesting new methods, but available empirical studies indicate that many methods are seldom used in practice. This paper addresses the issue by providing increased understanding of IT project selection practice, thereby facilitating...... the development of methods that better fit current practice. The study is based on naturalistic decision-making theory and interviews with experienced project portfolio managers who, when selecting projects, primarily rely on political skills, experience and personal networks rather than on formal IT project......-selection methods, and these findings point to new areas for developing new methodological support for IT project selection....

  11. Method of Menu Selection by Gaze Movement Using AC EOG Signals

    Science.gov (United States)

    Kanoh, Shin'ichiro; Futami, Ryoko; Yoshinobu, Tatsuo; Hoshimiya, Nozomu

    A method to detect the direction and the distance of voluntary eye gaze movement from EOG (electrooculogram) signals was proposed and tested. In this method, AC-amplified vertical and horizontal transient EOG signals were classified into 8-class directions and 2-class distances of voluntary eye gaze movements. A horizontal and a vertical EOGs during eye gaze movement at each sampling time were treated as a two-dimensional vector, and the center of gravity of the sample vectors whose norms were more than 80% of the maximum norm was used as a feature vector to be classified. By the classification using the k-nearest neighbor algorithm, it was shown that the averaged correct detection rates on each subject were 98.9%, 98.7%, 94.4%, respectively. This method can avoid strict EOG-based eye tracking which requires DC amplification of very small signal. It would be useful to develop robust human interfacing systems based on menu selection for severely paralyzed patients.

  12. Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

    International Nuclear Information System (INIS)

    Anderson, Ryan B.; Bell, James F.; Wiens, Roger C.; Morris, Richard V.; Clegg, Samuel M.

    2012-01-01

    We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO 2 at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by ∼ 3 wt.%. The statistical significance of these improvements was ∼ 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and specifically

  13. Investigation of selection methods im mutation breeding of barley for protein quantity and quality

    International Nuclear Information System (INIS)

    Ulonska, E.; Gaul, H.; Baumer, M.; Gesellschaft fuer Strahlen- und Umweltforschung m.b.H., Gruenbach

    1975-01-01

    This mutation breeding programme is investigating the qualification of micro-mutations for the selection of improved protein quality and quantity. Normally, improvement of protein content in micro-mutations is rather small. Therefore, it is important to develop methods and conditions of selection being (a) capable of measuring these small deviations in protein content and quality, and (b) simple to use. In two experiments carried out in 1971 and 1972 nitrogen fertilization was found to be the most important factor in the improvement of selection conditions. There is a highly significant negative correlation between crude protein content and the standard deviation; i.e. the higher the content of crude protein, the lower the variation coefficient. This in turn leads to an increase of genetic variation necessary for better selection progress. Nitrogen fertilization, especially during ear emergence, covers environmental influences - e.g., planting space, sowing rate, growing in different plots (6, 3, 2, 1 rows or in half-ear hills) - to a great extent. Thus, by applying high doses of nitrogen dressings comparable results can be achieved. In an overall selection experiment (testing the entire crossing and mutation material available at Weihenstephan in a stepwise selection from 1971 to 1973) and two selection experiments conducted in 1971 to 1973 with micro-mutants - variety Nota, 4 times X-rayed and the naked barley strain 1606 treated once with EMS - significant selection results were found. (author)

  14. DOE methods compendium

    International Nuclear Information System (INIS)

    Leasure, C.S.

    1992-01-01

    The Department of Energy (DOE) has established an analytical methods compendium development program to integrate its environmental analytical methods. This program is administered through DOE's Laboratory Management Division (EM-563). The primary objective of this program is to assemble a compendium of analytical chemistry methods of known performance for use by all DOE Environmental Restoration and Waste Management program. This compendium will include methods for sampling, field screening, fixed analytical laboratory and mobile analytical laboratory analyses. It will also include specific guidance on the proper selection of appropriate sampling and analytical methods in using specific analytical requirements

  15. Effects of advanced selection methods on sperm quality and ART outcome : a systematic review

    NARCIS (Netherlands)

    Said, Tamer M.; Land, Jolande A.

    2011-01-01

    BACKGROUND: Current routine semen preparation techniques do not inclusively target all intrinsic sperm characteristics that may impact the fertilization potential. In order to address these characteristics, several methods have been recently developed and applied to sperm selection. The objective of

  16. Selection of disposal contractor by multi criteria decision making methods

    Directory of Open Access Journals (Sweden)

    Cenker Korkmazer

    2016-08-01

    Full Text Available Hazardous waste is substance that threaten people and environment in case of improper storage, disposal and transport due to its concentration, physical and chemical properties. Companies producing hazardous waste as a result of several activities mostly do not have any own disposal facilities. In addition, they do not pay attention enough to determine the right contractor as a disposal facility. On the other hand, there are various qualitative and quantitative criteria affecting the selection of the contractor and conflicting with each other. The aim of the performed study is to assist one of these companies producing hazardous waste in the selection of the best contractor that eliminates hazardous waste economic and harmless way. In the study, contractor weights in percentage is calculated by using Analytic Network Process (ANP as one of the multi-criteria decision making (MCDM methods and widely used in the literature which considers both qualitative and quantitative criteria. In the next step, by the help of the mathematical model, contractors that will be given which type of hazardous waste are identified. This integrated approach can be used as a guide for similar firms.

  17. The optimum support design selection by using AHP method for the main haulage road in WLC Tuncbilek colliery

    Energy Technology Data Exchange (ETDEWEB)

    Yavuz, M.; Iphar, M.; Once, G.

    2008-03-15

    The engineers can frequently encounter with the situation to select the optimum option among the alternatives related with mining operations. The optimum choice can be selected by the experienced engineers taking into consideration their judgement and intuition. However, decision-making methods can offer to the engineers to support their optimum selection for a particular application in the scientific way. The Analytical Hierarchy Process (AHP) is one of the multi attribute decision-making (MADM) methods utilizing structured pair-wise comparisons. This paper presents an application of the AHP method to the selection of the optimum support design for the main transport road, which has been planned for deep coal seam panels of Western Lignite Corporation (WLC) Tuncbilek in Turkeiy. The methodology considers eight main objectives, namely: four different displacement values for determined history locations, factor of safety (FOS), cost, labour and applicability factor for the selection of support design. The displacements and stress values were obtained by using the finite difference program FLAC(3D) as the numerical studies have been widely used by the engineers examining the response of any opening in underground, in advance. After carrying out several numerical models for different support design, the AHP method was incorporated to evaluate these support designs according to the pre-determined criteria. The result of this study shows that such AHP application can assist the engineers to effectively evaluate the support system alternatives for an underground mine.

  18. Selected asymptotic methods with applications to electromagnetics and antennas

    CERN Document Server

    Fikioris, George; Bakas, Odysseas N

    2013-01-01

    This book describes and illustrates the application of several asymptotic methods that have proved useful in the authors' research in electromagnetics and antennas. We first define asymptotic approximations and expansions and explain these concepts in detail. We then develop certain prerequisites from complex analysis such as power series, multivalued functions (including the concepts of branch points and branch cuts), and the all-important gamma function. Of particular importance is the idea of analytic continuation (of functions of a single complex variable); our discussions here include som

  19. Selection of non-destructive assay methods: Neutron counting or calorimetric assay?

    International Nuclear Information System (INIS)

    Cremers, T.L.; Wachter, J.R.

    1994-01-01

    The transition of DOE facilities from production to D ampersand D has lead to more measurements of product, waste, scrap, and other less attractive materials. Some of these materials are difficult to analyze by either neutron counting or calorimetric assay. To determine the most efficacious analysis method, variety of materials, impure salts and hydrofluorination residues have been assayed by both calorimetric assay and neutron counting. New data will be presented together with a review of published data. The precision and accuracy of these measurements are compared to chemistry values and are reported. The contribution of the gamma ray isotopic determination measurement to the overall error of the calorimetric assay or neutron assay is examined and discussed. Other factors affecting selection of the most appropriate non-destructive assay method are listed and considered

  20. Analysis of Broad-band Frequency Selective Shielding Glass by FDTD method

    OpenAIRE

    笠嶋, 善憲; Kasashima, Yoshinori

    2010-01-01

    A frequency Selective shielding (FSS) glass is a print of many same size antennas on a sheet of glass, and it has high shielding properties for one specific frequency. In the past, the author analyzed theoretically the characteristics of the FSS, as a large scale array antenna. The FSS has narrow-band shielding characteristics. This time, the author analyzed accurately the characteristics of a FSS glass being a print of many same size dipole antennas on a sheet of glass by FDTD method. As the...

  1. Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method.

    Science.gov (United States)

    Guo, Xinyu; Dominick, Kelli C; Minai, Ali A; Li, Hailong; Erickson, Craig A; Lu, Long J

    2017-01-01

    The whole-brain functional connectivity (FC) pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD) by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN) with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS) is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD) controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS) is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes). Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150). Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t -test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross different pre

  2. Diagnosing Autism Spectrum Disorder from Brain Resting-State Functional Connectivity Patterns Using a Deep Neural Network with a Novel Feature Selection Method

    Directory of Open Access Journals (Sweden)

    Xinyu Guo

    2017-08-01

    Full Text Available The whole-brain functional connectivity (FC pattern obtained from resting-state functional magnetic resonance imaging data are commonly applied to study neuropsychiatric conditions such as autism spectrum disorder (ASD by using different machine learning models. Recent studies indicate that both hyper- and hypo- aberrant ASD-associated FCs were widely distributed throughout the entire brain rather than only in some specific brain regions. Deep neural networks (DNN with multiple hidden layers have shown the ability to systematically extract lower-to-higher level information from high dimensional data across a series of neural hidden layers, significantly improving classification accuracy for such data. In this study, a DNN with a novel feature selection method (DNN-FS is developed for the high dimensional whole-brain resting-state FC pattern classification of ASD patients vs. typical development (TD controls. The feature selection method is able to help the DNN generate low dimensional high-quality representations of the whole-brain FC patterns by selecting features with high discriminating power from multiple trained sparse auto-encoders. For the comparison, a DNN without the feature selection method (DNN-woFS is developed, and both of them are tested with different architectures (i.e., with different numbers of hidden layers/nodes. Results show that the best classification accuracy of 86.36% is generated by the DNN-FS approach with 3 hidden layers and 150 hidden nodes (3/150. Remarkably, DNN-FS outperforms DNN-woFS for all architectures studied. The most significant accuracy improvement was 9.09% with the 3/150 architecture. The method also outperforms other feature selection methods, e.g., two sample t-test and elastic net. In addition to improving the classification accuracy, a Fisher's score-based biomarker identification method based on the DNN is also developed, and used to identify 32 FCs related to ASD. These FCs come from or cross

  3. Applying the partitioned multiobjective risk method (PMRM) to portfolio selection.

    Science.gov (United States)

    Reyes Santos, Joost; Haimes, Yacov Y

    2004-06-01

    The analysis of risk-return tradeoffs and their practical applications to portfolio analysis paved the way for Modern Portfolio Theory (MPT), which won Harry Markowitz a 1992 Nobel Prize in Economics. A typical approach in measuring a portfolio's expected return is based on the historical returns of the assets included in a portfolio. On the other hand, portfolio risk is usually measured using volatility, which is derived from the historical variance-covariance relationships among the portfolio assets. This article focuses on assessing portfolio risk, with emphasis on extreme risks. To date, volatility is a major measure of risk owing to its simplicity and validity for relatively small asset price fluctuations. Volatility is a justified measure for stable market performance, but it is weak in addressing portfolio risk under aberrant market fluctuations. Extreme market crashes such as that on October 19, 1987 ("Black Monday") and catastrophic events such as the terrorist attack of September 11, 2001 that led to a four-day suspension of trading on the New York Stock Exchange (NYSE) are a few examples where measuring risk via volatility can lead to inaccurate predictions. Thus, there is a need for a more robust metric of risk. By invoking the principles of the extreme-risk-analysis method through the partitioned multiobjective risk method (PMRM), this article contributes to the modeling of extreme risks in portfolio performance. A measure of an extreme portfolio risk, denoted by f(4), is defined as the conditional expectation for a lower-tail region of the distribution of the possible portfolio returns. This article presents a multiobjective problem formulation consisting of optimizing expected return and f(4), whose solution is determined using Evolver-a software that implements a genetic algorithm. Under business-as-usual market scenarios, the results of the proposed PMRM portfolio selection model are found to be compatible with those of the volatility-based model

  4. THE DEVELOPMENT OF A NOVEL MODEL FOR MINING METHOD SELECTION IN A FUZZY ENVIRONMENT; CASE STUDY: TAZAREH COAL MINE, SEMNAN PROVINCE, IRAN

    Directory of Open Access Journals (Sweden)

    Fatemeh Asadi Ooriad

    2018-01-01

    Full Text Available Mining method selection (MMS for mineral resources is one of the most significant steps in mining production management. Due to high costs involved and environmental problems, it is usually not possible to change the coal mining method after planning and starting the operation. In most cases, MMS can be considered as an irreversible process. Selecting a method for mining mainly depends on geological, geometrical properties of the resource, environmental impacts of exploration, impacts of hazardous activities and land use management. This paper seeks to develop a novel model for mining method selection in order to achieve a stable production rate and to reduce environmental problems. This novel model is illustrated by implementing for Tazareh coal mine. Given the disadvantages of the previous models for selecting coal mining method, the purpose of this research is modifying the previous models and offering a comprehensive model. In this respect, TOPSIS method is used as a powerful multi attribute decision-making procedure in Fuzzy environment. After implementation of the presented model in Tazareh coal mine, long wall mining method has been selected as the most appropriate mining method.

  5. Practical Approaches for Detecting Selection in Microbial Genomes.

    Directory of Open Access Journals (Sweden)

    Jessica Hedge

    2016-02-01

    Full Text Available Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.

  6. Wavelength Selection Method Based on Differential Evolution for Precise Quantitative Analysis Using Terahertz Time-Domain Spectroscopy.

    Science.gov (United States)

    Li, Zhi; Chen, Weidong; Lian, Feiyu; Ge, Hongyi; Guan, Aihong

    2017-12-01

    Quantitative analysis of component mixtures is an important application of terahertz time-domain spectroscopy (THz-TDS) and has attracted broad interest in recent research. Although the accuracy of quantitative analysis using THz-TDS is affected by a host of factors, wavelength selection from the sample's THz absorption spectrum is the most crucial component. The raw spectrum consists of signals from the sample and scattering and other random disturbances that can critically influence the quantitative accuracy. For precise quantitative analysis using THz-TDS, the signal from the sample needs to be retained while the scattering and other noise sources are eliminated. In this paper, a novel wavelength selection method based on differential evolution (DE) is investigated. By performing quantitative experiments on a series of binary amino acid mixtures using THz-TDS, we demonstrate the efficacy of the DE-based wavelength selection method, which yields an error rate below 5%.

  7. Replacement method and enhanced replacement method versus the genetic algorithm approach for the selection of molecular descriptors in QSPR/QSAR theories.

    Science.gov (United States)

    Mercader, Andrew G; Duchowicz, Pablo R; Fernández, Francisco M; Castro, Eduardo A

    2010-09-27

    We compare three methods for the selection of optimal subsets of molecular descriptors from a much greater pool of such regression variables. On the one hand is our enhanced replacement method (ERM) and on the other is the simpler replacement method (RM) and the genetic algorithm (GA). These methods avoid the impracticable full search for optimal variables in large sets of molecular descriptors. Present results for 10 different experimental databases suggest that the ERM is clearly preferable to the GA that is slightly better than the RM. However, the latter approach requires the smallest amount of linear regressions and, consequently, the lowest computation time.

  8. The Criteria for the Selection of Wells for Hydraulic Fracturing

    Directory of Open Access Journals (Sweden)

    O.V. Salimov

    2017-12-01

    Full Text Available Various methods of selection of wells for hydraulic fracturing are analyzed. It is established that all methods can be divided into three large groups: criteria in the table form of boundary values of parameters, statistical methods of pattern recognition, methods of engineering calculation. The complication or use of additional parameters only leads to a reduction in the number of wells at which hydraulic fracturing is possible. It is shown that the use of reservoir properties of rocks, which are already used by hydraulic fracturing simulators, is not practicable as selection criteria. It is required to include in the selection criteria only those additional factors on which the effectiveness of hydraulic fracturing depends directly.

  9. Least absolute shrinkage and selection operator type methods for the identification of serum biomarkers of overweight and obesity: simulation and application

    Directory of Open Access Journals (Sweden)

    Monica M. Vasquez

    2016-11-01

    Full Text Available Abstract Background The study of circulating biomarkers and their association with disease outcomes has become progressively complex due to advances in the measurement of these biomarkers through multiplex technologies. The Least Absolute Shrinkage and Selection Operator (LASSO is a data analysis method that may be utilized for biomarker selection in these high dimensional data. However, it is unclear which LASSO-type method is preferable when considering data scenarios that may be present in serum biomarker research, such as high correlation between biomarkers, weak associations with the outcome, and sparse number of true signals. The goal of this study was to compare the LASSO to five LASSO-type methods given these scenarios. Methods A simulation study was performed to compare the LASSO, Adaptive LASSO, Elastic Net, Iterated LASSO, Bootstrap-Enhanced LASSO, and Weighted Fusion for the binary logistic regression model. The simulation study was designed to reflect the data structure of the population-based Tucson Epidemiological Study of Airway Obstructive Disease (TESAOD, specifically the sample size (N = 1000 for total population, 500 for sub-analyses, correlation of biomarkers (0.20, 0.50, 0.80, prevalence of overweight (40% and obese (12% outcomes, and the association of outcomes with standardized serum biomarker concentrations (log-odds ratio = 0.05–1.75. Each LASSO-type method was then applied to the TESAOD data of 306 overweight, 66 obese, and 463 normal-weight subjects with a panel of 86 serum biomarkers. Results Based on the simulation study, no method had an overall superior performance. The Weighted Fusion correctly identified more true signals, but incorrectly included more noise variables. The LASSO and Elastic Net correctly identified many true signals and excluded more noise variables. In the application study, biomarkers of overweight and obesity selected by all methods were Adiponectin, Apolipoprotein H, Calcitonin, CD

  10. Assessment of the possibility of using data mining methods to predict sorption isotherms of selected organic compounds on activated carbon

    Directory of Open Access Journals (Sweden)

    Dąbek Lidia

    2017-01-01

    Full Text Available The paper analyses the use of four data mining methods (Support Vector Machines. Cascade Neural Networks. Random Forests and Boosted Trees to predict sorption on activated carbons. The input data for statistical models included the activated carbon parameters, organic substances and equilibrium concentrations in the solution. The assessment of the predictive abilities of the developed models was made with the use of mean absolute error (MAE, mean absolute percentage error (MAPE, and root mean squared error (RMSE. The computations proved that methods of data mining considered in the study can be applied to predict sorption of selected organic compounds 011 activated carbon. The lowest values of sorption prediction errors were obtained with the Cascade Neural Networks method (MAE = 1.23 g/g; MAPE = 7.90% and RMSE = 1.81 g/g, while the highest error values were produced by the Boosted Trees method (MAE=14.31 g/g; MAPE = 39.43% and RMSE = 27.76 g/g.

  11. Decision method for optimal selection of warehouse material handling strategies by production companies

    Science.gov (United States)

    Dobos, P.; Tamás, P.; Illés, B.

    2016-11-01

    Adequate establishment and operation of warehouse logistics determines the companies’ competitiveness significantly because it effects greatly the quality and the selling price of the goods that the production companies produce. In order to implement and manage an adequate warehouse system, adequate warehouse position, stock management model, warehouse technology, motivated work force committed to process improvement and material handling strategy are necessary. In practical life, companies have paid small attantion to select the warehouse strategy properly. Although it has a major influence on the production in the case of material warehouse and on smooth costumer service in the case of finished goods warehouse because this can happen with a huge loss in material handling. Due to the dynamically changing production structure, frequent reorganization of warehouse activities is needed, on what the majority of the companies react basically with no reactions. This work presents a simulation test system frames for eligible warehouse material handling strategy selection and also the decision method for selection.

  12. Method of a fast selection of inelastic nucleus-nucleus collisions for the CMS experiment

    International Nuclear Information System (INIS)

    Krasnov, V.A.; Malakhov, A.I.; Savina, M.V.; Shmatov, S.V.; Zarubin, P.I.

    1998-01-01

    On the basis of the HIJING generator simulation of heavy ion collisions at ultrarelativistic energy scale, a method of a fast selection of inelastic nucleus-nucleus interactions is proposed for the CMS experiment at LHC. The basic idea is to use the time coincidence of signals with resolution better than 1 ns from the two very forward calorimeter arms covering the acceptance 3<|η|<5. The method efficiency is investigated by variation of energy thresholds in the calorimeters for different colliding ion species, namely, PbPb, NbNb, CaCa, OO, pPb, pCa, pp. It is shown that a stable efficiency of event selection (∼98%) is provided in an energy threshold range up to 100 GeV for nuclear collisions at 5 TeV/nucleon in the centre of mass system. In the pp collision case the relevant efficiency drops from 93% down to 80%

  13. HEURISTIC METHOD OF SHIPS SELECTION FOR THE COORDINATED WORK OF WATER TRANSPORT

    Directory of Open Access Journals (Sweden)

    O. V. Shcherbina

    2018-02-01

    Full Text Available Purpose. The study aims to develop a formulation methodology for ship selection in the coordinated work of sea and river transport using a heuristic approach. Methodology. To realize the purpose set in the study, the authors carried out an analysis of domestic and foreign literature sources on the current topic, studied specifics and conditions for the effective operation of marine mono-hulled ships and composite tug/barge towing ones. Findings. The analysis results allowed formulating the heuristics methods that ensure the selection of the type sizes of tug/barge towing ships for the mixed «river-sea» navigation from the priority range of ships of the existing fleet. The proposed method makes it possible to select ships in a more appropriate manner according to the established scheme of work. Rational combinations of technical and operational characteristics of such pairs as «barges and tows», «tug/barge towing ship and sea-going ship», «tug/barge towing ship and restrictive characteristics of the area of navigation» are a prerequisite for the shipping company profit growth by increasing the capacity of ships. Originality. For the first time, the authors applied a heuristic approach to the selection of tug/barge towing ships and sea-going ones for coordinated work with the performance of cargo operations on the raid of the estuary port when transporting bulk goods. The basis of the approach is the selection of a rational mix of technical and operational characteristics of barges and tugs. The proposed approach allows determining the best combination of ship type sizes in the organization of coordinated work of sea and river transport. At the same time, the continuity of the goods transportation process from the sea ports to the river ones located in the depth of the country (and in the opposite direction is ensured. Practical value. The presented methodology is a logical continuation of the cycle of studies performed by the authors. The

  14. Online feature selection with streaming features.

    Science.gov (United States)

    Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

    2013-05-01

    We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

  15. Operator psychological selection system for nuclear power plant

    International Nuclear Information System (INIS)

    He Xuhong; Huang Xiangrui

    2004-01-01

    Based on a detailed job analysis of nuclear power plant operator including operation procedures analysis, interview with personnel familiar with operator job, and 9 events happened in the past in the plant involved operator error analysis, several operator work characteristics and performance influence factors are obtained. According to these specific characteristics and factors, referring to the psychological selection research results in the other related critical occupational fields, a full psychological selection system of nuclear power plant operator is forwarded in this paper, including 21 dimensions in 3 facets as general psychological ability, personality and psychological healthy. Practical measurement methods for the proposed selection dimensions are discussed in the end

  16. A new method of hybrid frequency hopping signals selection and blind parameter estimation

    Science.gov (United States)

    Zeng, Xiaoyu; Jiao, Wencheng; Sun, Huixian

    2018-04-01

    Frequency hopping communication is widely used in military communications at home and abroad. In the case of single-channel reception, it is scarce to process multiple frequency hopping signals both effectively and simultaneously. A method of hybrid FH signals selection and blind parameter estimation is proposed. The method makes use of spectral transformation, spectral entropy calculation and PRI transformation basic theory to realize the sorting and parameter estimation of the components in the hybrid frequency hopping signal. The simulation results show that this method can correctly classify the frequency hopping component signal, and the estimated error of the frequency hopping period is about 5% and the estimated error of the frequency hopping frequency is less than 1% when the SNR is 10dB. However, the performance of this method deteriorates seriously at low SNR.

  17. Selection of the Chrome Reduction Bacteria in the Waste of Tanning Leather Industries by Ozonization Method

    International Nuclear Information System (INIS)

    Yazid, M.; Aris Bastianudin; Widdi Usada

    2007-01-01

    Selection of the chrome reduction bacteria in the waste of tanning leather industries by ozonization method has been done. The objectives of this research was to obtain isolate bacteria from the waste with chrome contain, so that expected can be used for chrome bioremediation agent for arrange to improved the waste treatment for tanning leather industries. Selection of bacteria in the waste was carried out by ozonization method with time variation 0 to 210 minutes by time interval 15 minutes. Isolation bacteria was carried out was grown on the BHI media for 24 hours at 37°C temperature. So be inoculated by streak plate method on the TBX, MC, EA, CTM and BP media. Characterization of bacteria was done by saw the colonies morphology, sel morphology and biochemical characterization. So, identification of isolate bacteria by matching profile method. The result of this research can be obtained 5 isolate bacteria BCR1, BCR2, BCR3, BCR4 and BCR5 with the different phenotypic character. From the five isolate can be selected resistance ozon isolate until 180 minutes time ozonization were BCR 2, were identified belong to the genus of Bacillus. The examination results showed that the isolate bacteria be able to reduction of the chrome concentration in the waste of tanning leather industries by 71.03 %. Efficiency. (author)

  18. Statistical model selection with “Big Data”

    Directory of Open Access Journals (Sweden)

    Jurgen A. Doornik

    2015-12-01

    Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.

  19. Selective amygdalohippocampectomy via trans-superior temporal gyrus keyhole approach

    OpenAIRE

    Mathon , Bertrand; Clemenceau , Stéphane

    2016-01-01

    International audience; BackgroundHippocampal sclerosis is the most common cause of drug-resistant epilepsy amenable for surgical treatment and seizure control. The rationale of the selective amygdalohippocampectomy is to spare cerebral tissue not included in the seizure generator.MethodDescribe the selective amygdalohippocampectomy through the trans-superior temporal gyrus keyhole approach.ConclusionSelective amygdalohippocampectomy for temporal lobe epilepsy is performed when the data (semi...

  20. A ROC-based feature selection method for computer-aided detection and diagnosis

    Science.gov (United States)

    Wang, Songyuan; Zhang, Guopeng; Liao, Qimei; Zhang, Junying; Jiao, Chun; Lu, Hongbing

    2014-03-01

    Image-based computer-aided detection and diagnosis (CAD) has been a very active research topic aiming to assist physicians to detect lesions and distinguish them from benign to malignant. However, the datasets fed into a classifier usually suffer from small number of samples, as well as significantly less samples available in one class (have a disease) than the other, resulting in the classifier's suboptimal performance. How to identifying the most characterizing features of the observed data for lesion detection is critical to improve the sensitivity and minimize false positives of a CAD system. In this study, we propose a novel feature selection method mR-FAST that combines the minimal-redundancymaximal relevance (mRMR) framework with a selection metric FAST (feature assessment by sliding thresholds) based on the area under a ROC curve (AUC) generated on optimal simple linear discriminants. With three feature datasets extracted from CAD systems for colon polyps and bladder cancer, we show that the space of candidate features selected by mR-FAST is more characterizing for lesion detection with higher AUC, enabling to find a compact subset of superior features at low cost.

  1. A holistic method for selecting tidal stream energy hotspots under technical, economic and functional constraints

    International Nuclear Information System (INIS)

    Vazquez, A.; Iglesias, G.

    2016-01-01

    Highlights: • A method for selecting the most suitable sites for tidal stream farms was presented. • The selection was based on relevant technical, economic and functional aspects. • As a case study, a model of the Bristol Channel was implemented and validated. - Abstract: Although a number of prospective locations for tidal stream farms have been identified, the development of a unified approach for selecting the optimum site in a region remains a current research topic. The objective of this work is to develop and apply a methodology for determining the most suitable sites for tidal stream farms, i.e. sites whose characteristics maximise power performance, minimise cost and avoid conflicts with competing uses of the marine space. Illustrated through a case study in the Bristol Channel, the method uses a validated hydrodynamics model to identify highly energetic areas and a geospatial Matlab-based program (designed ad hoc) to estimate the energy output that a tidal farm at the site with a given technology would have. This output is then used to obtain the spatial distribution of the levelised cost of energy and, on this basis, to preselect certain areas. Subsequently, potential conflicts with other functions of the marine space (e.g. fishing, shipping) are considered. The result is a selection of areas for tidal stream energy development based on a holistic approach, encompassing the relevant technical, economic and functional aspects. This methodology can lead to a significant improvement in the selection of tidal sites, thereby increasing the possibilities of project acceptance and development.

  2. Technique for Increasing the Selectivity of the Method of Laser Fragmentation/Laser-Induced Fluorescence

    Science.gov (United States)

    Bobrovnikov, S. M.; Gorlov, E. V.; Zharkov, V. I.

    2018-05-01

    A technique for increasing the selectivity of the method of detecting high-energy materials (HEMs) based on laser fragmentation of HEM molecules with subsequent laser excitation of fluorescence of the characteristic NO fragments from the first vibrational level of the ground state is suggested.

  3. Methods of using structures including catalytic materials disposed within porous zeolite materials to synthesize hydrocarbons

    Science.gov (United States)

    Rollins, Harry W [Idaho Falls, ID; Petkovic, Lucia M [Idaho Falls, ID; Ginosar, Daniel M [Idaho Falls, ID

    2011-02-01

    Catalytic structures include a catalytic material disposed within a zeolite material. The catalytic material may be capable of catalyzing a formation of methanol from carbon monoxide and/or carbon dioxide, and the zeolite material may be capable of catalyzing a formation of hydrocarbon molecules from methanol. The catalytic material may include copper and zinc oxide. The zeolite material may include a first plurality of pores substantially defined by a crystal structure of the zeolite material and a second plurality of pores dispersed throughout the zeolite material. Systems for synthesizing hydrocarbon molecules also include catalytic structures. Methods for synthesizing hydrocarbon molecules include contacting hydrogen and at least one of carbon monoxide and carbon dioxide with such catalytic structures. Catalytic structures are fabricated by forming a zeolite material at least partially around a template structure, removing the template structure, and introducing a catalytic material into the zeolite material.

  4. Spine surgeon's kinematics during discectomy, part II: operating table height and visualization methods, including microscope.

    Science.gov (United States)

    Park, Jeong Yoon; Kim, Kyung Hyun; Kuh, Sung Uk; Chin, Dong Kyu; Kim, Keun Su; Cho, Yong Eun

    2014-05-01

    Surgeon spine angle during surgery was studied ergonomically and the kinematics of the surgeon's spine was related with musculoskeletal fatigue and pain. Spine angles varied depending on operation table height and visualization method, and in a previous paper we showed that the use of a loupe and a table height at the midpoint between the umbilicus and the sternum are optimal for reducing musculoskeletal loading. However, no studies have previously included a microscope as a possible visualization method. The objective of this study is to assess differences in surgeon spine angles depending on operating table height and visualization method, including microscope. We enrolled 18 experienced spine surgeons for this study, who each performed a discectomy using a spine surgery simulator. Three different methods were used to visualize the surgical field (naked eye, loupe, microscope) and three different operating table heights (anterior superior iliac spine, umbilicus, the midpoint between the umbilicus and the sternum) were studied. Whole spine angles were compared for three different views during the discectomy simulation: midline, ipsilateral, and contralateral. A 16-camera optoelectronic motion analysis system was used, and 16 markers were placed from the head to the pelvis. Lumbar lordosis, thoracic kyphosis, cervical lordosis, and occipital angle were compared between the different operating table heights and visualization methods as well as a natural standing position. Whole spine angles differed significantly depending on visualization method. All parameters were closer to natural standing values when discectomy was performed with a microscope, and there were no differences between the naked eye and the loupe. Whole spine angles were also found to differ from the natural standing position depending on operating table height, and became closer to natural standing position values as the operating table height increased, independent of the visualization method

  5. Natural Selection in Large Populations

    Science.gov (United States)

    Desai, Michael

    2011-03-01

    I will discuss theoretical and experimental approaches to the evolutionary dynamics and population genetics of natural selection in large populations. In these populations, many mutations are often present simultaneously, and because recombination is limited, selection cannot act on them all independently. Rather, it can only affect whole combinations of mutations linked together on the same chromosome. Methods common in theoretical population genetics have been of limited utility in analyzing this coupling between the fates of different mutations. In the past few years it has become increasingly clear that this is a crucial gap in our understanding, as sequence data has begun to show that selection appears to act pervasively on many linked sites in a wide range of populations, including viruses, microbes, Drosophila, and humans. I will describe approaches that combine analytical tools drawn from statistical physics and dynamical systems with traditional methods in theoretical population genetics to address this problem, and describe how experiments in budding yeast can help us directly observe these evolutionary dynamics.

  6. Clustering and training set selection methods for improving the accuracy of quantitative laser induced breakdown spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, Ryan B., E-mail: randerson@astro.cornell.edu [Cornell University Department of Astronomy, 406 Space Sciences Building, Ithaca, NY 14853 (United States); Bell, James F., E-mail: Jim.Bell@asu.edu [Arizona State University School of Earth and Space Exploration, Bldg.: INTDS-A, Room: 115B, Box 871404, Tempe, AZ 85287 (United States); Wiens, Roger C., E-mail: rwiens@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States); Morris, Richard V., E-mail: richard.v.morris@nasa.gov [NASA Johnson Space Center, 2101 NASA Parkway, Houston, TX 77058 (United States); Clegg, Samuel M., E-mail: sclegg@lanl.gov [Los Alamos National Laboratory, P.O. Box 1663 MS J565, Los Alamos, NM 87545 (United States)

    2012-04-15

    We investigated five clustering and training set selection methods to improve the accuracy of quantitative chemical analysis of geologic samples by laser induced breakdown spectroscopy (LIBS) using partial least squares (PLS) regression. The LIBS spectra were previously acquired for 195 rock slabs and 31 pressed powder geostandards under 7 Torr CO{sub 2} at a stand-off distance of 7 m at 17 mJ per pulse to simulate the operational conditions of the ChemCam LIBS instrument on the Mars Science Laboratory Curiosity rover. The clustering and training set selection methods, which do not require prior knowledge of the chemical composition of the test-set samples, are based on grouping similar spectra and selecting appropriate training spectra for the partial least squares (PLS2) model. These methods were: (1) hierarchical clustering of the full set of training spectra and selection of a subset for use in training; (2) k-means clustering of all spectra and generation of PLS2 models based on the training samples within each cluster; (3) iterative use of PLS2 to predict sample composition and k-means clustering of the predicted compositions to subdivide the groups of spectra; (4) soft independent modeling of class analogy (SIMCA) classification of spectra, and generation of PLS2 models based on the training samples within each class; (5) use of Bayesian information criteria (BIC) to determine an optimal number of clusters and generation of PLS2 models based on the training samples within each cluster. The iterative method and the k-means method using 5 clusters showed the best performance, improving the absolute quadrature root mean squared error (RMSE) by {approx} 3 wt.%. The statistical significance of these improvements was {approx} 85%. Our results show that although clustering methods can modestly improve results, a large and diverse training set is the most reliable way to improve the accuracy of quantitative LIBS. In particular, additional sulfate standards and

  7. Method of selecting optimum cross arm lengths for a 750 kV transmission line

    Energy Technology Data Exchange (ETDEWEB)

    Aleksandrov, G N; Olorokov, V P

    1965-01-01

    A method is presented, based on both technical and economic considerations, for selecting cross arm lengths for intermediate poles of power transmission lines according to the effects of internal overvoltage, methods from probability theory and mathematical statistics employed. The problem of optimum pole size is considered in terms of the effect of internal overvoltages for a prescribed maximum level of 2.1 PU currently used in the USSR for the design of 750 kV lines.

  8. Learning to Select Supplier Portfolios for Service Supply Chain.

    Science.gov (United States)

    Zhang, Rui; Li, Jingfei; Wu, Shaoyu; Meng, Dabin

    2016-01-01

    The research on service supply chain has attracted more and more focus from both academia and industrial community. In a service supply chain, the selection of supplier portfolio is an important and difficult problem due to the fact that a supplier portfolio may include multiple suppliers from a variety of fields. To address this problem, we propose a novel supplier portfolio selection method based on a well known machine learning approach, i.e., Ranking Neural Network (RankNet). In the proposed method, we regard the problem of supplier portfolio selection as a ranking problem, which integrates a large scale of decision making features into a ranking neural network. Extensive simulation experiments are conducted, which demonstrate the feasibility and effectiveness of the proposed method. The proposed supplier portfolio selection model can be applied in a real corporation easily in the future.

  9. Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

    Directory of Open Access Journals (Sweden)

    Hailun Wang

    2017-01-01

    Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

  10. [Selecting methods and awaiting growth: the teaching experience of fundamental nursing practicum instructors].

    Science.gov (United States)

    Lin, Hui-Chen; Lin, Chi-Yi; Chien, Tsui-Wei; Liu, Kuei-Fen; Chen, Miao-Yen; Lin, Wen-Chuan

    2013-02-01

    A constellation of factors accounts for teaching efficacy in the fundamental nursing practicum. Teachers play a critical role in terms of designing and executing an appropriate teaching plan, choosing effective methods, and holding appropriate teaching attitudes. It is thus extremely important that clinical teachers master the core characteristics of basic nursing practice. This study aimed to illuminate the core characteristics of basic nursing practice for students for reference by clinical practicum teachers. Qualitative research was used to identify the fundamentals of nursing practice by clinical teacher. Five focus group meetings were convened during the practice period. The researchers presided over group discussions held during the normal weekly teaching schedule and lasting approximately 2-4 hours each. The content analysis was adopted to analyze the data. Three major themes were proposed, including (1) student status: "novices were stymied by problems and thus improved slowly"; (2) teacher awareness: "teachers need to be aware of student capabilities, mood, and discomfort"; and (3) teaching style: "a good choice of methods should support and encourage students. To cultivate professional nursing knowledge and self-confidence for future professional commitment, clinical teachers must first understand the characteristics and motivations of learning of their students and then select the, skills, and attitudes appropriate to provide step-by-step guidance. Communication with staffs and the preparation of atmosphere prior to nursing practice are also essential for students. Results provide insights into the technical college environment with regard to basic-level clinical nursing practice.

  11. Least absolute shrinkage and selection operator type methods for the identification of serum biomarkers of overweight and obesity: simulation and application.

    Science.gov (United States)

    Vasquez, Monica M; Hu, Chengcheng; Roe, Denise J; Chen, Zhao; Halonen, Marilyn; Guerra, Stefano

    2016-11-14

    The study of circulating biomarkers and their association with disease outcomes has become progressively complex due to advances in the measurement of these biomarkers through multiplex technologies. The Least Absolute Shrinkage and Selection Operator (LASSO) is a data analysis method that may be utilized for biomarker selection in these high dimensional data. However, it is unclear which LASSO-type method is preferable when considering data scenarios that may be present in serum biomarker research, such as high correlation between biomarkers, weak associations with the outcome, and sparse number of true signals. The goal of this study was to compare the LASSO to five LASSO-type methods given these scenarios. A simulation study was performed to compare the LASSO, Adaptive LASSO, Elastic Net, Iterated LASSO, Bootstrap-Enhanced LASSO, and Weighted Fusion for the binary logistic regression model. The simulation study was designed to reflect the data structure of the population-based Tucson Epidemiological Study of Airway Obstructive Disease (TESAOD), specifically the sample size (N = 1000 for total population, 500 for sub-analyses), correlation of biomarkers (0.20, 0.50, 0.80), prevalence of overweight (40%) and obese (12%) outcomes, and the association of outcomes with standardized serum biomarker concentrations (log-odds ratio = 0.05-1.75). Each LASSO-type method was then applied to the TESAOD data of 306 overweight, 66 obese, and 463 normal-weight subjects with a panel of 86 serum biomarkers. Based on the simulation study, no method had an overall superior performance. The Weighted Fusion correctly identified more true signals, but incorrectly included more noise variables. The LASSO and Elastic Net correctly identified many true signals and excluded more noise variables. In the application study, biomarkers of overweight and obesity selected by all methods were Adiponectin, Apolipoprotein H, Calcitonin, CD14, Complement 3, C-reactive protein, Ferritin

  12. Laser-induced Breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

    International Nuclear Information System (INIS)

    Yang, Jianhong; Yi, Cancan; Xu, Jinwu; Ma, Xianghong

    2015-01-01

    A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine. - Highlights: • Both training and testing samples are considered for analytical lines selection. • The analytical lines are auto-selected based on the built-in characteristics of spectral lines. • The new method can achieve better prediction accuracy and modeling robustness. • Model predictions are given with confidence interval of probabilistic distribution

  13. [Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

    Science.gov (United States)

    Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

    2013-12-01

    To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

  14. Implementation of preference ranking organization method for enrichment evaluation (Promethee) on selection system of student’s achievement

    Science.gov (United States)

    Karlitasari, L.; Suhartini, D.; Nurrosikawati, L.

    2018-03-01

    Selection of Student Achievement is conducted every year, starting from the level of Study Program, Faculty, to University, which then rank one will be sent to Kopertis level. The criteria made for the selection are Academic and Rich Scientific, Organizational, Personality, and English. In order for the selection of Student Achievement is Objective, then in addition to the presence of the jury is expected to use methods that support the decision to be more optimal in determining the Student Achievement. One method used is the Promethee Method. Preference Ranking Organization Method for Enrichment Evaluation (Promethee) is a method of ranking in Multi Criteria Decision Making (MCDM). PROMETHEE has the advantage that there is a preference type against the criteria that can take into account alternatives with other alternatives on the same criteria. The conjecture of alternate dominance over a criterion used in PROMETHEE is the use of values in the relationships between alternative ranking values. Based on the calculation result, from 7 applicants between Manual and Promethee Matrices, rank 1, 2, and 3, did not change, only 4 to 7 positions were changed. However, after the sensitivity test, almost all criteria experience a high level of sensitivity. Although it does not affect the students who will be sent to the next level, but can bring psychological impact on prospective student’s achievement

  15. A New Hybrid Method for Improving the Performance of Myocardial Infarction Prediction

    Directory of Open Access Journals (Sweden)

    Hojatollah Hamidi

    2016-06-01

    Full Text Available Abstract Introduction: Myocardial Infarction, also known as heart attack, normally occurs due to such causes as smoking, family history, diabetes, and so on. It is recognized as one of the leading causes of death in the world. Therefore, the present study aimed to evaluate the performance of classification models in order to predict Myocardial Infarction, using a feature selection method that includes Forward Selection and Genetic Algorithm. Materials & Methods: The Myocardial Infarction data set used in this study contains the information related to 519 visitors to Shahid Madani Specialized Hospital of Khorramabad, Iran. This data set includes 33 features. The proposed method includes a hybrid feature selection method in order to enhance the performance of classification algorithms. The first step of this method selects the features using Forward Selection. At the second step, the selected features were given to a genetic algorithm, in order to select the best features. Classification algorithms entail Ada Boost, Naïve Bayes, J48 decision tree and simpleCART are applied to the data set with selected features, for predicting Myocardial Infarction. Results: The best results have been achieved after applying the proposed feature selection method, which were obtained via simpleCART and J48 algorithms with the accuracies of 96.53% and 96.34%, respectively. Conclusion: Based on the results, the performances of classification algorithms are improved. So, applying the proposed feature selection method, along with classification algorithms seem to be considered as a confident method with respect to predicting the Myocardial Infarction.

  16. Positron emission tomography probe to monitor selected sugar metabolism in vivo

    Science.gov (United States)

    Witte, Owen; Clark, Peter M.; Castillo, Blanca Graciela Flores; Jung, Michael E.; Evdokimov, Nikolai M.

    2017-03-14

    The invention disclosed herein discloses selected ribose isomers that are useful as PET probes (e.g. [18F]-2-fluoro-2-deoxy-arabinose). These PET probes are useful, for example, in methods designed to monitor physiological processes including ribose metabolism and/or to selectively observe certain tissue/organs in vivo. The invention disclosed herein further provides methods for making and using such probes.

  17. Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

    Science.gov (United States)

    Noma, Hisashi; Matsui, Shigeyuki

    2013-05-20

    The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression. Copyright © 2012 John Wiley & Sons, Ltd.

  18. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  19. 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.

  20. Selection, competency development and assessment of nuclear power plant managers

    International Nuclear Information System (INIS)

    1998-06-01

    This publication provides information on proven methods and good practices with respect to the selection, development and assessment of nuclear power plant (NPP) managers. The report is organized into four sections, a glossary, two appendices, and several annexes. The Introduction (Section 1) provides the framework for the report. Section 2 describes how appropriate management competencies can be used for the selection, development and assessment of NPP managers, including: -Selection which includes recruitment, promotion and succession management. -Management development programmes including formal training, job rotation, on the job training, mentoring, and outside assignments. -Assessment of individual performance. Section 3 describes a systematic process for identifying the competencies needed by NPP managers. This section culminates in a set of suggested core competencies for NPP managers which are further expanded in Appendix A. The annexes included provide specific examples of competency-based management selection, development, and assessment programmes in several Member States. -Annex A is one method to organize and display competencies. -Annex B is an example of using competencies for selection of first line managers. -Annex C is an example of using management competencies for succession management. -Annexes -H are examples of management development programmes. -Annexes I and J are examples of management assessment programmes. A glossary of terms is provided at the end of the report to explain the use of some key terms explain the use of some key terms

  1. Machine Selection in A Dairy Product Company with Entropy and SAW Method Integration

    Directory of Open Access Journals (Sweden)

    Aşkın Özdağoğlu

    2017-07-01

    Full Text Available Machine selection is an important and difficult process for the firms, and its results may generate more problems than anticipated. In order to find the best alternative, managers should define the requirements of the factory and determine the necessary criteria. On the other hand, the decision making criteria in order to choose the right equipment may vary according to the type of the manufacturing facility, market requirements, and consumer assigned criteria. This study aims to find the best machine alternative  among  the three machine offerings according to twelve evaluation criteria by integrating entropy method with SAW method.

  2. A Combined Fuzzy-AHP and Fuzzy-GRA Methodology for Hydrogen Energy Storage Method Selection in Turkey

    Directory of Open Access Journals (Sweden)

    Aytac Yildiz

    2013-06-01

    Full Text Available In this paper, we aim to select the most appropriate Hydrogen Energy Storage (HES method for Turkey from among the alternatives of tank, metal hydride and chemical storage, which are determined based on expert opinions and literature review. Thus, we propose a Buckley extension based fuzzy Analytical Hierarchical Process (Fuzzy-AHP and linear normalization based fuzzy Grey Relational Analysis (Fuzzy-GRA combined Multi Criteria Decision Making (MCDM methodology. This combined approach can be applied to a complex decision process, which often makes sense with subjective data or vague information; and used to solve to solve HES selection problem with different defuzzification methods. The proposed approach is unique both in the HES literature and the MCDM literature.

  3. Plasma spraying method for forming diamond and diamond-like coatings

    Science.gov (United States)

    Holcombe, Cressie E.; Seals, Roland D.; Price, R. Eugene

    1997-01-01

    A method and composition for the deposition of a thick layer (10) of diamond or diamond-like material. The method includes high temperature processing wherein a selected composition (12) including at least glassy carbon is heated in a direct current plasma arc device to a selected temperature above the softening point, in an inert atmosphere, and is propelled to quickly quenched on a selected substrate (20). The softened or molten composition (18) crystallizes on the substrate (20) to form a thick deposition layer (10) comprising at least a diamond or diamond-like material. The selected composition (12) includes at least glassy carbon as a primary constituent (14) and may include at least one secondary constituent (16). Preferably, the secondary constituents (16) are selected from the group consisting of at least diamond powder, boron carbide (B.sub.4 C) powder and mixtures thereof.

  4. The optical method of the straw selection for the MPD end-cap tracker

    International Nuclear Information System (INIS)

    Grigalashvili, N.; Kekelidze, G.D.; Myalkovskij, V.V.; Peshekhonov, V.D.

    2015-01-01

    The paper describes the optical method for measurement of the straightness deviation in the straws with a diameter of 4 mm and a length of 60 cm mounted in the ring frames of the detector and for defining the parameters for the straw selection. With this method, the maximal acceptable deviation from straightness in a straw does not exceed 400 microns and the changes of the amplitudes of signals from a 55 Fe source along the straw do not exceed 9%. The results of the optical straightness control are in good agreement with the data obtained with a more accurate method of determining the offset of the anode from the straw axis by measuring amplitude characteristics with the use of the 55 Fe source.

  5. Evaluation of pump pulsation in respirable size-selective sampling: Part III. Investigation of European standard methods.

    Science.gov (United States)

    Soo, Jhy-Charm; Lee, Eun Gyung; Lee, Larry A; Kashon, Michael L; Harper, Martin

    2014-10-01

    Lee et al. (Evaluation of pump pulsation in respirable size-selective sampling: part I. Pulsation measurements. Ann Occup Hyg 2014a;58:60-73) introduced an approach to measure pump pulsation (PP) using a real-world sampling train, while the European Standards (EN) (EN 1232-1997 and EN 12919-1999) suggest measuring PP using a resistor in place of the sampler. The goal of this study is to characterize PP according to both EN methods and to determine the relationship of PP between the published method (Lee et al., 2014a) and the EN methods. Additional test parameters were investigated to determine whether the test conditions suggested by the EN methods were appropriate for measuring pulsations. Experiments were conducted using a factorial combination of personal sampling pumps (six medium- and two high-volumetric flow rate pumps), back pressures (six medium- and seven high-flow rate pumps), resistors (two types), tubing lengths between a pump and resistor (60 and 90 cm), and different flow rates (2 and 2.5 l min(-1) for the medium- and 4.4, 10, and 11.2 l min(-1) for the high-flow rate pumps). The selection of sampling pumps and the ranges of back pressure were based on measurements obtained in the previous study (Lee et al., 2014a). Among six medium-flow rate pumps, only the Gilian5000 and the Apex IS conformed to the 10% criterion specified in EN 1232-1997. Although the AirChek XR5000 exceeded the 10% limit, the average PP (10.9%) was close to the criterion. One high-flow rate pump, the Legacy (PP=8.1%), conformed to the 10% criterion in EN 12919-1999, while the Elite12 did not (PP=18.3%). Conducting supplemental tests with additional test parameters beyond those used in the two subject EN standards did not strengthen the characterization of PPs. For the selected test conditions, a linear regression model [PPEN=0.014+0.375×PPNIOSH (adjusted R2=0.871)] was developed to determine the PP relationship between the published method (Lee et al., 2014a) and the EN methods

  6. Comparison of Sparse and Jack-knife partial least squares regression methods for variable selection

    DEFF Research Database (Denmark)

    Karaman, Ibrahim; Qannari, El Mostafa; Martens, Harald

    2013-01-01

    The objective of this study was to compare two different techniques of variable selection, Sparse PLSR and Jack-knife PLSR, with respect to their predictive ability and their ability to identify relevant variables. Sparse PLSR is a method that is frequently used in genomics, whereas Jack-knife PL...

  7. Dropouts in Swiss Vocational Education and the Effect of Training Companies' Trainee Selection Methods

    Science.gov (United States)

    Forsblom, Lara; Negrini, Lucio; Gurtner, Jean-Luc; Schumann, Stephan

    2016-01-01

    In the Swiss vocational education system, which is often called a "Dual System", trainees enter into an apprenticeship contract with a training company. On average, 25% of those contracts are terminated prematurely (PCT). This article examines the relationship between training companies' selection methods and PCTs. The investigation is…

  8. A consistency-based feature selection method allied with linear SVMs for HIV-1 protease cleavage site prediction.

    Directory of Open Access Journals (Sweden)

    Orkun Oztürk

    Full Text Available BACKGROUND: Predicting type-1 Human Immunodeficiency Virus (HIV-1 protease cleavage site in protein molecules and determining its specificity is an important task which has attracted considerable attention in the research community. Achievements in this area are expected to result in effective drug design (especially for HIV-1 protease inhibitors against this life-threatening virus. However, some drawbacks (like the shortage of the available training data and the high dimensionality of the feature space turn this task into a difficult classification problem. Thus, various machine learning techniques, and specifically several classification methods have been proposed in order to increase the accuracy of the classification model. In addition, for several classification problems, which are characterized by having few samples and many features, selecting the most relevant features is a major factor for increasing classification accuracy. RESULTS: We propose for HIV-1 data a consistency-based feature selection approach in conjunction with recursive feature elimination of support vector machines (SVMs. We used various classifiers for evaluating the results obtained from the feature selection process. We further demonstrated the effectiveness of our proposed method by comparing it with a state-of-the-art feature selection method applied on HIV-1 data, and we evaluated the reported results based on attributes which have been selected from different combinations. CONCLUSION: Applying feature selection on training data before realizing the classification task seems to be a reasonable data-mining process when working with types of data similar to HIV-1. On HIV-1 data, some feature selection or extraction operations in conjunction with different classifiers have been tested and noteworthy outcomes have been reported. These facts motivate for the work presented in this paper. SOFTWARE AVAILABILITY: The software is available at http

  9. Investigating the Effect of Normalization Norms in Flexible Manufacturing Sytem Selection Using Multi-Criteria Decision-Making Methods

    Directory of Open Access Journals (Sweden)

    Prasenjit Chatterjee

    2014-07-01

    Full Text Available The main objective of this paper is to assess the effect of different normalization norms within multi-criteria decisionmaking (MADM models. Three well accepted MCDM tools, namely, preference ranking organization method for enrichment evaluation (PROMETHEE, grey relation analysis (GRA and technique for order preference by similarity to ideal solution (TOPSIS methods are applied for solving a flexible manufacturing system (FMS selection problem in a discrete manufacturing environment. Finally, by the introduction of different normalization norms to the decision algorithms, its effct on the FMS selection problem using these MCDM models are also studied.

  10. Auralization of airborne sound insulation including the influence of source room

    DEFF Research Database (Denmark)

    Rindel, Jens Holger

    2006-01-01

    The paper describes a simple and acoustically accurate method for the auralization of airborne sound insulation between two rooms by means of a room acoustic simulation software (ODEON). The method makes use of a frequency independent transparency of the transmitting surface combined...... with a frequency dependent power setting of the source in the source room. The acoustic properties in terms of volume and reverberation time as well as the area of the transmitting surface are all included in the simulation. The user only has to select the position of the source in the source room and the receiver...... of the transmitting surface is used for the simulation of sound transmission. Also the reduced clarity of the auralization due to the reverberance of the source room is inherent in the method. Currently the method is restricted to transmission loss data in octave bands....

  11. Comparison of differents methods of sperm selection of llama raw semen.

    Science.gov (United States)

    Santa Cruz, R; Giuliano, S M; Gambarotta, M C; Morrell, J M; Abraham, M C; Miragaya, M H; Carretero, M I

    2016-10-01

    The objective of this study was to compare the efficiency of different sperm selection methods applied to the same llama ejaculate. Four treatments were compared: two variants of the swim up technique (with and without seminal plasma), and two different colloids, Androcoll-E-Large and Percoll(®). Using electroejaculation, 21 semen samples were obtained from 7 llama males (n=7, r=3). The ejaculates were incubated in a solution of 0.1% collagenase, to decrease thread formation, and then split into 4 aliquots: one aliquot was layered over a column of Androcoll-E-Large (SLC) and the second over a column of Percoll (45%). The third aliquot was deposited in a tube with culture medium and was incubated at a 45° angle for 30min at 37°C (SU1). The last aliquot was centrifuged to separate the spermatozoa and seminal plasma. The sperm pellet obtained was resuspended, and transferred to a tube with culture medium which was incubated at an angle of 45° for 30min at 37°C (SU2). Both aliquots SLC and P showed higher proportions of progressive motility and plasma membrane functionality (p≤0.05) than raw semen. There were no significant differences (p>0.05) in sperm viability and in normal spermatozoa between raw semen and treatments. Nevertheless, only SLC did not have a significant increase of bent tails. In conclusion SLC centrifugation would be the method of choice for selecting llama spermatozoa. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Influence of Feature Selection Methods on Classification Sensitivity Based on the Example of A Study of Polish Voivodship Tourist Attractiveness

    Directory of Open Access Journals (Sweden)

    Bąk Iwona

    2014-07-01

    Full Text Available The purpose of this article is to determine the influence of various methods of selection of diagnostic features on the sensitivity of classification. Three options of feature selection are presented: a parametric feature selection method with a sum (option I, a median of the correlation coefficients matrix column elements (option II and the method of a reversed matrix (option III. Efficiency of the groupings was verified by the indicators of homogeneity, heterogeneity and the correctness of grouping. In the assessment of group efficiency the approach with the Weber median was used. The undertaken problem was illustrated with a research into the tourist attractiveness of voivodships in Poland in 2011.

  13. Method of App Selection for Healthcare Providers Based on Consumer Needs.

    Science.gov (United States)

    Lee, Jisan; Kim, Jeongeun

    2018-01-01

    Mobile device applications can be used to manage health. However, healthcare providers hesitate to use them because selection methods that consider the needs of health consumers and identify the most appropriate application are rare. This study aimed to create an effective method of identifying applications that address user needs. Women experiencing dysmenorrhea and premenstrual syndrome were the targeted users. First, we searched for related applications from two major sources of mobile applications. Brainstorming, mind mapping, and persona and scenario techniques were used to create a checklist of relevant criteria, which was used to rate the applications. Of the 2784 applications found, 369 were analyzed quantitatively. Of those, five of the top candidates were evaluated by three groups: application experts, clinical experts, and potential users. All three groups ranked one application the highest; however, the remaining rankings differed. The results of this study suggest that the method created is useful because it considers not only the needs of various users but also the knowledge of application and clinical experts. This study proposes a method for finding and using the best among existing applications and highlights the need for nurses who can understand and combine opinions of users and application and clinical experts.

  14. PLS-based and regularization-based methods for the selection of relevant variables in non-targeted metabolomics data

    Directory of Open Access Journals (Sweden)

    Renata Bujak

    2016-07-01

    Full Text Available Non-targeted metabolomics constitutes a part of systems biology and aims to determine many metabolites in complex biological samples. Datasets obtained in non-targeted metabolomics studies are multivariate and high-dimensional due to the sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA without and with multiple testing correction as well as least absolute shrinkage and selection operator (LASSO were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction, selected 46 and 218 variables based on VIP criteria using Pareto and UV scaling, respectively. In the case of the PH study, 217 and 320 variables were selected based on VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built with multiple testing correction, selected 4 and 19 variables as statistically significant in terms of Pareto and UV scaling, respectively. For PH study, 14 and 18 variables were selected based on VIP criteria in terms of Pareto and UV scaling, respectively. Additionally, the concept and fundaments of the least absolute shrinkage and selection operator (LASSO with bootstrap procedure evaluating reproducibility of results, was demonstrated. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3% and 100%. However, apart from the popularity of PLS-DA and OPLS-DA methods in metabolomics, it should be highlighted that they do not control type I or type II error, but only arbitrarily establish a cut-off value for PLS-DA loadings

  15. Determination of Selected Volatiles in Cigarette Mainstream Smoke. The CORESTA 2009 Collaborative Study and Recommended Method

    Directory of Open Access Journals (Sweden)

    Intorp M

    2014-12-01

    Full Text Available A recommended method has been developed and published by CORESTA, applicable to the quantification of selected volatiles (1,3-butadiene, isoprene, acrylonitrile, benzene, and toluene in the gas phase of cigarette mainstream smoke. The method involved smoke collection in impinger traps and detection and measurement using gas chromatography/mass spectrometry techniques.

  16. An innovative method for offshore wind farm site selection based on the interval number with probability distribution

    Science.gov (United States)

    Wu, Yunna; Chen, Kaifeng; Xu, Hu; Xu, Chuanbo; Zhang, Haobo; Yang, Meng

    2017-12-01

    There is insufficient research relating to offshore wind farm site selection in China. The current methods for site selection have some defects. First, information loss is caused by two aspects: the implicit assumption that the probability distribution on the interval number is uniform; and ignoring the value of decision makers' (DMs') common opinion on the criteria information evaluation. Secondly, the difference in DMs' utility function has failed to receive attention. An innovative method is proposed in this article to solve these drawbacks. First, a new form of interval number and its weighted operator are proposed to reflect the uncertainty and reduce information loss. Secondly, a new stochastic dominance degree is proposed to quantify the interval number with a probability distribution. Thirdly, a two-stage method integrating the weighted operator with stochastic dominance degree is proposed to evaluate the alternatives. Finally, a case from China proves the effectiveness of this method.

  17. UNLABELED SELECTED SAMPLES IN FEATURE EXTRACTION FOR CLASSIFICATION OF HYPERSPECTRAL IMAGES WITH LIMITED TRAINING SAMPLES

    Directory of Open Access Journals (Sweden)

    A. Kianisarkaleh

    2015-12-01

    Full Text Available Feature extraction plays a key role in hyperspectral images classification. Using unlabeled samples, often unlimitedly available, unsupervised and semisupervised feature extraction methods show better performance when limited number of training samples exists. This paper illustrates the importance of selecting appropriate unlabeled samples that used in feature extraction methods. Also proposes a new method for unlabeled samples selection using spectral and spatial information. The proposed method has four parts including: PCA, prior classification, posterior classification and sample selection. As hyperspectral image passes these parts, selected unlabeled samples can be used in arbitrary feature extraction methods. The effectiveness of the proposed unlabeled selected samples in unsupervised and semisupervised feature extraction is demonstrated using two real hyperspectral datasets. Results show that through selecting appropriate unlabeled samples, the proposed method can improve the performance of feature extraction methods and increase classification accuracy.

  18. Method for fluoride routine determination in urine of personnel exposed, by ion selective electrode

    International Nuclear Information System (INIS)

    Pires, M.A.F.; Bellintani, S.A.

    1986-01-01

    A simple, fast and sensible method is outlined for the determination of fluoride in urine of workers that handle fluorine compounds. The determination is based on the measurement of fluoride by ion selective electrode. Cationic interference like Ca ++ , Mg ++ , Fe +++ and Al +++ are complexed by EDTA and citric acid. (Author) [pt

  19. Determination of laser cutting process conditions using the preference selection index method

    Science.gov (United States)

    Madić, Miloš; Antucheviciene, Jurgita; Radovanović, Miroslav; Petković, Dušan

    2017-03-01

    Determination of adequate parameter settings for improvement of multiple quality and productivity characteristics at the same time is of great practical importance in laser cutting. This paper discusses the application of the preference selection index (PSI) method for discrete optimization of the CO2 laser cutting of stainless steel. The main motivation for application of the PSI method is that it represents an almost unexplored multi-criteria decision making (MCDM) method, and moreover, this method does not require assessment of the considered criteria relative significances. After reviewing and comparing the existing approaches for determination of laser cutting parameter settings, the application of the PSI method was explained in detail. Experiment realization was conducted by using Taguchi's L27 orthogonal array. Roughness of the cut surface, heat affected zone (HAZ), kerf width and material removal rate (MRR) were considered as optimization criteria. The proposed methodology is found to be very useful in real manufacturing environment since it involves simple calculations which are easy to understand and implement. However, while applying the PSI method it was observed that it can not be useful in situations where there exist a large number of alternatives which have attribute values (performances) very close to those which are preferred.

  20. A novel EMD selecting thresholding method based on multiple iteration for denoising LIDAR signal

    Science.gov (United States)

    Li, Meng; Jiang, Li-hui; Xiong, Xing-long

    2015-06-01

    Empirical mode decomposition (EMD) approach has been believed to be potentially useful for processing the nonlinear and non-stationary LIDAR signals. To shed further light on its performance, we proposed the EMD selecting thresholding method based on multiple iteration, which essentially acts as a development of EMD interval thresholding (EMD-IT), and randomly alters the samples of noisy parts of all the corrupted intrinsic mode functions to generate a better effect of iteration. Simulations on both synthetic signals and LIDAR signals from real world support this method.