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Sample records for methods multivariate logistic

  1. Marshall-Olkin multivariate semi-logistic distribution and minification ...

    African Journals Online (AJOL)

    Olkin multivariate logistic distribution (MO-ML) are introduced and studied. Various characterizations properties of Marshall-Olkin multivariate semi-logistic distribution are investigated and studied. First order autoregressive minification processes ...

  2. Multivariate semi-logistic distribution and processes | Umar | Journal ...

    African Journals Online (AJOL)

    Multivariate semi-logistic distribution is introduced and studied. Some characterizations properties of multivariate semi-logistic distribution are presented. First order autoregressive minification processes and its generalization to kth order autoregressive minification processes with multivariate semi-logistic distribution as ...

  3. A comparison between univariate probabilistic and multivariate (logistic regression) methods for landslide susceptibility analysis: the example of the Febbraro valley (Northern Alps, Italy)

    Science.gov (United States)

    Rossi, M.; Apuani, T.; Felletti, F.

    2009-04-01

    The aim of this paper is to compare the results of two statistical methods for landslide susceptibility analysis: 1) univariate probabilistic method based on landslide susceptibility index, 2) multivariate method (logistic regression). The study area is the Febbraro valley, located in the central Italian Alps, where different types of metamorphic rocks croup out. On the eastern part of the studied basin a quaternary cover represented by colluvial and secondarily, by glacial deposits, is dominant. In this study 110 earth flows, mainly located toward NE portion of the catchment, were analyzed. They involve only the colluvial deposits and their extension mainly ranges from 36 to 3173 m2. Both statistical methods require to establish a spatial database, in which each landslide is described by several parameters that can be assigned using a main scarp central point of landslide. The spatial database is constructed using a Geographical Information System (GIS). Each landslide is described by several parameters corresponding to the value of main scarp central point of the landslide. Based on bibliographic review a total of 15 predisposing factors were utilized. The width of the intervals, in which the maps of the predisposing factors have to be reclassified, has been defined assuming constant intervals to: elevation (100 m), slope (5 °), solar radiation (0.1 MJ/cm2/year), profile curvature (1.2 1/m), tangential curvature (2.2 1/m), drainage density (0.5), lineament density (0.00126). For the other parameters have been used the results of the probability-probability plots analysis and the statistical indexes of landslides site. In particular slope length (0 ÷ 2, 2 ÷ 5, 5 ÷ 10, 10 ÷ 20, 20 ÷ 35, 35 ÷ 260), accumulation flow (0 ÷ 1, 1 ÷ 2, 2 ÷ 5, 5 ÷ 12, 12 ÷ 60, 60 ÷27265), Topographic Wetness Index 0 ÷ 0.74, 0.74 ÷ 1.94, 1.94 ÷ 2.62, 2.62 ÷ 3.48, 3.48 ÷ 6,00, 6.00 ÷ 9.44), Stream Power Index (0 ÷ 0.64, 0.64 ÷ 1.28, 1.28 ÷ 1.81, 1.81 ÷ 4.20, 4.20 ÷ 9

  4. Methods of Multivariate Analysis

    CERN Document Server

    Rencher, Alvin C

    2012-01-01

    Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere."-IIE Transactions Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life sit

  5. Multivariate statistical methods a primer

    CERN Document Server

    Manly, Bryan FJ

    2004-01-01

    THE MATERIAL OF MULTIVARIATE ANALYSISExamples of Multivariate DataPreview of Multivariate MethodsThe Multivariate Normal DistributionComputer ProgramsGraphical MethodsChapter SummaryReferencesMATRIX ALGEBRAThe Need for Matrix AlgebraMatrices and VectorsOperations on MatricesMatrix InversionQuadratic FormsEigenvalues and EigenvectorsVectors of Means and Covariance MatricesFurther Reading Chapter SummaryReferencesDISPLAYING MULTIVARIATE DATAThe Problem of Displaying Many Variables in Two DimensionsPlotting index VariablesThe Draftsman's PlotThe Representation of Individual Data P:ointsProfiles o

  6. Multivariate analysis: models and method

    International Nuclear Information System (INIS)

    Sanz Perucha, J.

    1990-01-01

    Data treatment techniques are increasingly used since computer methods result of wider access. Multivariate analysis consists of a group of statistic methods that are applied to study objects or samples characterized by multiple values. A final goal is decision making. The paper describes the models and methods of multivariate analysis

  7. Multivariate analysis methods in physics

    International Nuclear Information System (INIS)

    Wolter, M.

    2007-01-01

    A review of multivariate methods based on statistical training is given. Several multivariate methods useful in high-energy physics analysis are discussed. Selected examples from current research in particle physics are discussed, both from the on-line trigger selection and from the off-line analysis. Also statistical training methods are presented and some new application are suggested [ru

  8. Multivariate methods for particle identification

    CERN Document Server

    Visan, Cosmin

    2013-01-01

    The purpose of this project was to evaluate several MultiVariate methods in order to determine which one, if any, offers better results in Particle Identification (PID) than a simple n$\\sigma$ cut on the response of the ALICE PID detectors. The particles considered in the analysis were Pions, Kaons and Protons and the detectors used were TPC and TOF. When used with the same input n$\\sigma$ variables, the results show similar perfoance between the Rectangular Cuts Optimization method and the simple n$\\sigma$ cuts. The method MLP and BDT show poor results for certain ranges of momentum. The KNN method is the best performing, showing similar results for Pions and Protons as the Cuts method, and better results for Kaons. The extension of the methods to include additional input variables leads to poor results, related to instabilities still to be investigated.

  9. Non-proportional odds multivariate logistic regression of ordinal family data.

    Science.gov (United States)

    Zaloumis, Sophie G; Scurrah, Katrina J; Harrap, Stephen B; Ellis, Justine A; Gurrin, Lyle C

    2015-03-01

    Methods to examine whether genetic and/or environmental sources can account for the residual variation in ordinal family data usually assume proportional odds. However, standard software to fit the non-proportional odds model to ordinal family data is limited because the correlation structure of family data is more complex than for other types of clustered data. To perform these analyses we propose the non-proportional odds multivariate logistic regression model and take a simulation-based approach to model fitting using Markov chain Monte Carlo methods, such as partially collapsed Gibbs sampling and the Metropolis algorithm. We applied the proposed methodology to male pattern baldness data from the Victorian Family Heart Study. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Multivariate statistical methods a first course

    CERN Document Server

    Marcoulides, George A

    2014-01-01

    Multivariate statistics refer to an assortment of statistical methods that have been developed to handle situations in which multiple variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical analysis. An introductory text for students learning multivariate statistical methods for the first time, this book keeps mathematical details to a minimum while conveying the basic principles. One of the principal strategies used throughout the book--in addition to the presentation of actual data analyses--is poin

  11. Multivariate methods and forecasting with IBM SPSS statistics

    CERN Document Server

    Aljandali, Abdulkader

    2017-01-01

    This is the second of a two-part guide to quantitative analysis using the IBM SPSS Statistics software package; this volume focuses on multivariate statistical methods and advanced forecasting techniques. More often than not, regression models involve more than one independent variable. For example, forecasting methods are commonly applied to aggregates such as inflation rates, unemployment, exchange rates, etc., that have complex relationships with determining variables. This book introduces multivariate regression models and provides examples to help understand theory underpinning the model. The book presents the fundamentals of multivariate regression and then moves on to examine several related techniques that have application in business-orientated fields such as logistic and multinomial regression. Forecasting tools such as the Box-Jenkins approach to time series modeling are introduced, as well as exponential smoothing and naïve techniques. This part also covers hot topics such as Factor Analysis, Dis...

  12. Risk factors for pedicled flap necrosis in hand soft tissue reconstruction: a multivariate logistic regression analysis.

    Science.gov (United States)

    Gong, Xu; Cui, Jianli; Jiang, Ziping; Lu, Laijin; Li, Xiucun

    2018-03-01

    Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction. © 2017 Royal Australasian College of Surgeons.

  13. [Multivariate ordinal logistic regression analysis on the association between consumption of fried food and both esophageal cancer and precancerous lesions].

    Science.gov (United States)

    Guo, L W; Liu, S Z; Zhang, M; Chen, Q; Zhang, S K; Sun, X B

    2017-12-10

    Objective: To investigate the effect of fried food intake on the pathogenesis of esophageal cancer and precancerous lesions. Methods: From 2005 to 2013, all the residents aged 40-69 years from 11 counties (cities) where cancer screening of upper gastrointestinal cancer had been conducted in rural areas of Henan province, were recruited as the subjects of study. Information on demography and lifestyle was collected. The residents under study were screened with iodine staining endoscopic examination and biopsy samples were diagnosed pathologically, under standardized criteria. Subjects with high risk were divided into the groups based on their different pathological degrees. Multivariate ordinal logistic regression analysis was used to analyze the relationship between the frequency of fried food intake and esophageal cancer and precancerous lesions. Results: A total number of 8 792 cases with normal esophagus, 3 680 with mild hyperplasia, 972 with moderate hyperplasia, 413 with severe hyperplasia carcinoma in situ, and 336 cases of esophageal cancer were recruited. Results from multivariate logistic regression analysis showed that, when compared with those who did not eat fried food, the intake of fried food (food appeared a risk factor for both esophageal cancer and precancerous lesions.

  14. Model for Building a Distribution Network Based on the Multivariate Analysis of the Industrial and Logistical Potential of Regions

    Directory of Open Access Journals (Sweden)

    Alexander Vladimirovich Kirillov

    2015-12-01

    Full Text Available The international integration of the Russian economy is connected to the need of the realization of the competitive advantages of the geopolitical position of Russia, the industrial potential of regions, the logistic infrastructure of transport corridors. This article discusses the design model of the supply chain (distribution network based on the multivariate analysis and the methodology of the substantiation of its configuration based on the cost factors and the level of the logistics infrastructure development. For solving the problem of placing one or more logistics centers in the service area, a two-stage algorithm is used. At the first stage, the decisions on the reasonability of the choice of one or another version of the development are made with А. В. Кириллов, В. Е. Целин 345 ЭКОНОМИКА РЕГИОНА №4 (2015 the use of the “Make or Buy” standard model. The criterion of decision making is the guaranteed overcoming of the threshold of “indifference” taking into account the statistical characteristics of costs for options of “buy” and “make” depending on the volume of consumption of goods or services. At the second stage, the Ardalan’s heuristic method is used for the evaluation of the choice of placing one or more logistics centers in the service area. The model parameters are based on the assessment of the development prospects of the region and its investment potential (existence and composition of employment, production, natural resources, financial and consumer opportunities, institutional, innovation, infrastructure capacity. Furthermore, such criteria as a regional financial appeal, professionally trained specialists, the competitive advantages of the promoted company and others are analyzed. An additional criterion is the development of the priority matrix, which considers such factors as difficulties of customs registration and certification, a level of regional transport

  15. Reporting quality of multivariable logistic regression in selected Indian medical journals.

    Science.gov (United States)

    Kumar, R; Indrayan, A; Chhabra, P

    2012-01-01

    Use of multivariable logistic regression (MLR) modeling has steeply increased in the medical literature over the past few years. Testing of model assumptions and adequate reporting of MLR allow the reader to interpret results more accurately. To review the fulfillment of assumptions and reporting quality of MLR in selected Indian medical journals using established criteria. Analysis of published literature. Medknow.com publishes 68 Indian medical journals with open access. Eight of these journals had at least five articles using MLR between the years 1994 to 2008. Articles from each of these journals were evaluated according to the previously established 10-point quality criteria for reporting and to test the MLR model assumptions. SPSS 17 software and non-parametric test (Kruskal-Wallis H, Mann Whitney U, Spearman Correlation). One hundred and nine articles were finally found using MLR for analyzing the data in the selected eight journals. The number of such articles gradually increased after year 2003, but quality score remained almost similar over time. P value, odds ratio, and 95% confidence interval for coefficients in MLR was reported in 75.2% and sufficient cases (>10) per covariate of limiting sample size were reported in the 58.7% of the articles. No article reported the test for conformity of linear gradient for continuous covariates. Total score was not significantly different across the journals. However, involvement of statistician or epidemiologist as a co-author improved the average quality score significantly (P=0.014). Reporting of MLR in many Indian journals is incomplete. Only one article managed to score 8 out of 10 among 109 articles under review. All others scored less. Appropriate guidelines in instructions to authors, and pre-publication review of articles using MLR by a qualified statistician may improve quality of reporting.

  16. Modeling the potential risk factors of bovine viral diarrhea prevalence in Egypt using univariable and multivariable logistic regression analyses

    Directory of Open Access Journals (Sweden)

    Abdelfattah M. Selim

    2018-03-01

    Full Text Available Aim: The present cross-sectional study was conducted to determine the seroprevalence and potential risk factors associated with Bovine viral diarrhea virus (BVDV disease in cattle and buffaloes in Egypt, to model the potential risk factors associated with the disease using logistic regression (LR models, and to fit the best predictive model for the current data. Materials and Methods: A total of 740 blood samples were collected within November 2012-March 2013 from animals aged between 6 months and 3 years. The potential risk factors studied were species, age, sex, and herd location. All serum samples were examined with indirect ELIZA test for antibody detection. Data were analyzed with different statistical approaches such as Chi-square test, odds ratios (OR, univariable, and multivariable LR models. Results: Results revealed a non-significant association between being seropositive with BVDV and all risk factors, except for species of animal. Seroprevalence percentages were 40% and 23% for cattle and buffaloes, respectively. OR for all categories were close to one with the highest OR for cattle relative to buffaloes, which was 2.237. Likelihood ratio tests showed a significant drop of the -2LL from univariable LR to multivariable LR models. Conclusion: There was an evidence of high seroprevalence of BVDV among cattle as compared with buffaloes with the possibility of infection in different age groups of animals. In addition, multivariable LR model was proved to provide more information for association and prediction purposes relative to univariable LR models and Chi-square tests if we have more than one predictor.

  17. Methodical approach to financial stimulation of logistics managers

    Directory of Open Access Journals (Sweden)

    Melnykova Kateryna V.

    2014-01-01

    Full Text Available The article offers a methodical approach to financial stimulation of logistics managers, which allows calculation of the incentive amount with consideration of profit obtained from introduction of optimisation logistics solutions. The author generalises measures, which would allow increase of stimulation of labour of logistics managers by the enterprise top managers. The article marks out motivation factors, which exert influence upon relation of logistics managers to execution of optimisation logistical solutions, which minimise logistical costs. The author builds a scale of financial encouragement for introduction of optimisation logistical solutions proposed by logistics managers. This scale is basic for functioning of the encouragement system and influences the increase of efficiency of logistics managers operation and also optimisation of enterprise logistical solutions.

  18. On Multivariate Methods in Robust Econometrics

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2012-01-01

    Roč. 21, č. 1 (2012), s. 69-82 ISSN 1210-0455 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : least weighted squares * heteroscedasticity * multivariate statistics * model selection * diagnostics * computational aspects Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.561, year: 2012 http://www.vse.cz/pep/abstrakt.php?IDcl=411

  19. Methodical approach to financial stimulation of logistics managers

    OpenAIRE

    Melnykova Kateryna V.

    2014-01-01

    The article offers a methodical approach to financial stimulation of logistics managers, which allows calculation of the incentive amount with consideration of profit obtained from introduction of optimisation logistics solutions. The author generalises measures, which would allow increase of stimulation of labour of logistics managers by the enterprise top managers. The article marks out motivation factors, which exert influence upon relation of logistics managers to execution of optimisatio...

  20. Method for statistical data analysis of multivariate observations

    CERN Document Server

    Gnanadesikan, R

    1997-01-01

    A practical guide for multivariate statistical techniques-- now updated and revised In recent years, innovations in computer technology and statistical methodologies have dramatically altered the landscape of multivariate data analysis. This new edition of Methods for Statistical Data Analysis of Multivariate Observations explores current multivariate concepts and techniques while retaining the same practical focus of its predecessor. It integrates methods and data-based interpretations relevant to multivariate analysis in a way that addresses real-world problems arising in many areas of inte

  1. Multivariate methods in nuclear waste remediation: Needs and applications

    International Nuclear Information System (INIS)

    Pulsipher, B.A.

    1992-05-01

    The United States Department of Energy (DOE) has developed a strategy for nuclear waste remediation and environmental restoration at several major sites across the country. Nuclear and hazardous wastes are found in underground storage tanks, containment drums, soils, and facilities. Due to the many possible contaminants and complexities of sampling and analysis, multivariate methods are directly applicable. However, effective application of multivariate methods will require greater ability to communicate methods and results to a non-statistician community. Moreover, more flexible multivariate methods may be required to accommodate inherent sampling and analysis limitations. This paper outlines multivariate applications in the context of select DOE environmental restoration activities and identifies several perceived needs

  2. METHODS FOR DETERMINATION AND OPTIMIZATION OF LOGISTICS COSTS

    Directory of Open Access Journals (Sweden)

    Mihaela STET

    2016-12-01

    Full Text Available The paper is dealing with the problems of logistics costs, highlighting some methods for estimation and determination of specific costs for different transport modes in freight distribution. There are highlighted, besides costs of transports, the other costs in supply chain, as well as costing methods used in logistics activities. In this context, there are also revealed some optimization means of transport costs in logistics chain.

  3. METHODS FOR DETERMINATION AND OPTIMIZATION OF LOGISTICS COSTS

    OpenAIRE

    Mihaela STET

    2016-01-01

    The paper is dealing with the problems of logistics costs, highlighting some methods for estimation and determination of specific costs for different transport modes in freight distribution. There are highlighted, besides costs of transports, the other costs in supply chain, as well as costing methods used in logistics activities. In this context, there are also revealed some optimization means of transport costs in logistics chain.

  4. A retrospective study: Multivariate logistic regression analysis of the outcomes after pressure sores reconstruction with fasciocutaneous, myocutaneous, and perforator flaps.

    Science.gov (United States)

    Chiu, Yu-Jen; Liao, Wen-Chieh; Wang, Tien-Hsiang; Shih, Yu-Chung; Ma, Hsu; Lin, Chih-Hsun; Wu, Szu-Hsien; Perng, Cherng-Kang

    2017-08-01

    Despite significant advances in medical care and surgical techniques, pressure sore reconstruction is still prone to elevated rates of complication and recurrence. We conducted a retrospective study to investigate not only complication and recurrence rates following pressure sore reconstruction but also preoperative risk stratification. This study included 181 ulcers underwent flap operations between January 2002 and December 2013 were included in the study. We performed a multivariable logistic regression model, which offers a regression-based method accounting for the within-patient correlation of the success or failure of each flap. The overall complication and recurrence rates for all flaps were 46.4% and 16.0%, respectively, with a mean follow-up period of 55.4 ± 38.0 months. No statistically significant differences of complication and recurrence rates were observed among three different reconstruction methods. In subsequent analysis, albumin ≤3.0 g/dl and paraplegia were significantly associated with higher postoperative complication. The anatomic factor, ischial wound location, significantly trended toward the development of ulcer recurrence. In the fasciocutaneous group, paraplegia had significant correlation to higher complication and recurrence rates. In the musculocutaneous flap group, variables had no significant correlation to complication and recurrence rates. In the free-style perforator group, ischial wound location and malnourished status correlated with significantly higher complication rates; ischial wound location also correlated with significantly higher recurrence rate. Ultimately, our review of a noteworthy cohort with lengthy follow-up helped identify and confirm certain risk factors that can facilitate a more informed and thoughtful pre- and postoperative decision-making process for patients with pressure ulcers. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All

  5. Study of risk factors affecting both hypertension and obesity outcome by using multivariate multilevel logistic regression models

    Directory of Open Access Journals (Sweden)

    Sepedeh Gholizadeh

    2016-07-01

    Full Text Available Background:Obesity and hypertension are the most important non-communicable diseases thatin many studies, the prevalence and their risk factors have been performedin each geographic region univariately.Study of factors affecting both obesity and hypertension may have an important role which to be adrressed in this study. Materials &Methods:This cross-sectional study was conducted on 1000 men aged 20-70 living in Bushehr province. Blood pressure was measured three times and the average of them was considered as one of the response variables. Hypertension was defined as systolic blood pressure ≥140 (and-or diastolic blood pressure ≥90 and obesity was defined as body mass index ≥25. Data was analyzed by using multilevel, multivariate logistic regression model by MlwiNsoftware. Results:Intra class correlations in cluster level obtained 33% for high blood pressure and 37% for obesity, so two level model was fitted to data. The prevalence of obesity and hypertension obtained 43.6% (0.95%CI; 40.6-46.5, 29.4% (0.95%CI; 26.6-32.1 respectively. Age, gender, smoking, hyperlipidemia, diabetes, fruit and vegetable consumption and physical activity were the factors affecting blood pressure (p≤0.05. Age, gender, hyperlipidemia, diabetes, fruit and vegetable consumption, physical activity and place of residence are effective on obesity (p≤0.05. Conclusion: The multilevel models with considering levels distribution provide more precise estimates. As regards obesity and hypertension are the major risk factors for cardiovascular disease, by knowing the high-risk groups we can d careful planning to prevention of non-communicable diseases and promotion of society health.

  6. Differential diagnosis of degenerative dementias using basic neuropsychological tests: multivariable logistic regression analysis of 301 patients.

    Science.gov (United States)

    Jiménez-Huete, Adolfo; Riva, Elena; Toledano, Rafael; Campo, Pablo; Esteban, Jesús; Barrio, Antonio Del; Franch, Oriol

    2014-12-01

    The validity of neuropsychological tests for the differential diagnosis of degenerative dementias may depend on the clinical context. We constructed a series of logistic models taking into account this factor. We retrospectively analyzed the demographic and neuropsychological data of 301 patients with probable Alzheimer's disease (AD), frontotemporal degeneration (FTLD), or dementia with Lewy bodies (DLB). Nine models were constructed taking into account the diagnostic question (eg, AD vs DLB) and subpopulation (incident vs prevalent). The AD versus DLB model for all patients, including memory recovery and phonological fluency, was highly accurate (area under the curve = 0.919, sensitivity = 90%, and specificity = 80%). The results were comparable in incident and prevalent cases. The FTLD versus AD and DLB versus FTLD models were both inaccurate. The models constructed from basic neuropsychological variables allowed an accurate differential diagnosis of AD versus DLB but not of FTLD versus AD or DLB. © The Author(s) 2014.

  7. Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies

    Directory of Open Access Journals (Sweden)

    Qiong Yang

    2012-01-01

    Full Text Available Multivariate phenotypes are frequently encountered in genetic association studies. The purpose of analyzing multivariate phenotypes usually includes discovery of novel genetic variants of pleiotropy effects, that is, affecting multiple phenotypes, and the ultimate goal of uncovering the underlying genetic mechanism. In recent years, there have been new method development and application of existing statistical methods to such phenotypes. In this paper, we provide a review of the available methods for analyzing association between a single marker and a multivariate phenotype consisting of the same type of components (e.g., all continuous or all categorical or different types of components (e.g., some are continuous and others are categorical. We also reviewed causal inference methods designed to test whether the detected association with the multivariate phenotype is truly pleiotropy or the genetic marker exerts its effects on some phenotypes through affecting the others.

  8. Multivariate Methods Based Soft Measurement for Wine Quality Evaluation

    Directory of Open Access Journals (Sweden)

    Shen Yin

    2014-01-01

    a decision. However, since the physicochemical indexes of wine can to some extent reflect the quality of wine, the multivariate statistical methods based soft measure can help the oenologist in wine evaluation.

  9. A comparison of multivariate genome-wide association methods

    DEFF Research Database (Denmark)

    Galesloot, Tessel E; Van Steen, Kristel; Kiemeney, Lambertus A L M

    2014-01-01

    Joint association analysis of multiple traits in a genome-wide association study (GWAS), i.e. a multivariate GWAS, offers several advantages over analyzing each trait in a separate GWAS. In this study we directly compared a number of multivariate GWAS methods using simulated data. We focused on six...... methods that are implemented in the software packages PLINK, SNPTEST, MultiPhen, BIMBAM, PCHAT and TATES, and also compared them to standard univariate GWAS, analysis of the first principal component of the traits, and meta-analysis of univariate results. We simulated data (N = 1000) for three...... for scenarios with an opposite sign of genetic and residual correlation. All multivariate analyses resulted in a higher power than univariate analyses, even when only one of the traits was associated with the QTL. Hence, use of multivariate GWAS methods can be recommended, even when genetic correlations between...

  10. Multivariate Methods for Meta-Analysis of Genetic Association Studies.

    Science.gov (United States)

    Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

    2018-01-01

    Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

  11. Robust methods for multivariate data analysis A1

    DEFF Research Database (Denmark)

    Frosch, Stina; Von Frese, J.; Bro, Rasmus

    2005-01-01

    Outliers may hamper proper classical multivariate analysis, and lead to incorrect conclusions. To remedy the problem of outliers, robust methods are developed in statistics and chemometrics. Robust methods reduce or remove the effect of outlying data points and allow the ?good? data to primarily...... determine the result. This article reviews the most commonly used robust multivariate regression and exploratory methods that have appeared since 1996 in the field of chemometrics. Special emphasis is put on the robust versions of chemometric standard tools like PCA and PLS and the corresponding robust...

  12. Multivariable control in nuclear power stations -survey of design methods

    International Nuclear Information System (INIS)

    Mcmorran, P.D.

    1979-12-01

    The development of larger nuclear generating stations increases the importance of dynamic interaction between controllers, because each control action may affect several plant outputs. Multivariable control provides the techniques to design controllers which perform well under these conditions. This report is a foundation for further work on the application of multivariable control in AECL. It covers the requirements of control and the fundamental mathematics used, then reviews the most important linear methods, based on both state-space and frequency-response concepts. State-space methods are derived from analysis of the system differential equations, while frequency-response methods use the input-output transfer function. State-space methods covered include linear-quadratic optimal control, pole shifting, and the theory of state observers and estimators. Frequency-response methods include the inverse Nyquist array method, and classical non-interactive techniques. Transfer-function methods are particularly emphasized since they can incorporate ill-defined design criteria. The underlying concepts, and the application strengths and weaknesses of each design method are presented. A review of significant applications is also given. It is concluded that the inverse Nyquist array method, a frequency-response technique based on inverse transfer-function matrices, is preferred for the design of multivariable controllers for nuclear power plants. This method may be supplemented by information obtained from a modal analysis of the plant model. (auth)

  13. Evaluation of Logistic Regression and Multivariate Adaptive Regression Spline Models for Groundwater Potential Mapping Using R and GIS

    Directory of Open Access Journals (Sweden)

    Soyoung Park

    2017-07-01

    Full Text Available This study mapped and analyzed groundwater potential using two different models, logistic regression (LR and multivariate adaptive regression splines (MARS, and compared the results. A spatial database was constructed for groundwater well data and groundwater influence factors. Groundwater well data with a high potential yield of ≥70 m3/d were extracted, and 859 locations (70% were used for model training, whereas the other 365 locations (30% were used for model validation. We analyzed 16 groundwater influence factors including altitude, slope degree, slope aspect, plan curvature, profile curvature, topographic wetness index, stream power index, sediment transport index, distance from drainage, drainage density, lithology, distance from fault, fault density, distance from lineament, lineament density, and land cover. Groundwater potential maps (GPMs were constructed using LR and MARS models and tested using a receiver operating characteristics curve. Based on this analysis, the area under the curve (AUC for the success rate curve of GPMs created using the MARS and LR models was 0.867 and 0.838, and the AUC for the prediction rate curve was 0.836 and 0.801, respectively. This implies that the MARS model is useful and effective for groundwater potential analysis in the study area.

  14. An Alternative Flight Software Trigger Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions Using Inaccurate or Scarce Information

    Science.gov (United States)

    Smith, Kelly M.; Gay, Robert S.; Stachowiak, Susan J.

    2013-01-01

    In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles.

  15. An Alternative Flight Software Paradigm: Applying Multivariate Logistic Regression to Sense Trigger Conditions using Inaccurate or Scarce Information

    Science.gov (United States)

    Smith, Kelly; Gay, Robert; Stachowiak, Susan

    2013-01-01

    In late 2014, NASA will fly the Orion capsule on a Delta IV-Heavy rocket for the Exploration Flight Test-1 (EFT-1) mission. For EFT-1, the Orion capsule will be flying with a new GPS receiver and new navigation software. Given the experimental nature of the flight, the flight software must be robust to the loss of GPS measurements. Once the high-speed entry is complete, the drogue parachutes must be deployed within the proper conditions to stabilize the vehicle prior to deploying the main parachutes. When GPS is available in nominal operations, the vehicle will deploy the drogue parachutes based on an altitude trigger. However, when GPS is unavailable, the navigated altitude errors become excessively large, driving the need for a backup barometric altimeter to improve altitude knowledge. In order to increase overall robustness, the vehicle also has an alternate method of triggering the parachute deployment sequence based on planet-relative velocity if both the GPS and the barometric altimeter fail. However, this backup trigger results in large altitude errors relative to the targeted altitude. Motivated by this challenge, this paper demonstrates how logistic regression may be employed to semi-automatically generate robust triggers based on statistical analysis. Logistic regression is used as a ground processor pre-flight to develop a statistical classifier. The classifier would then be implemented in flight software and executed in real-time. This technique offers improved performance even in the face of highly inaccurate measurements. Although the logistic regression-based trigger approach will not be implemented within EFT-1 flight software, the methodology can be carried forward for future missions and vehicles

  16. Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

    Science.gov (United States)

    Pradhan, Biswajeet

    2010-05-01

    This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross

  17. A Multivariate Time Series Method for Monte Carlo Reactor Analysis

    International Nuclear Information System (INIS)

    Taro Ueki

    2008-01-01

    A robust multivariate time series method has been established for the Monte Carlo calculation of neutron multiplication problems. The method is termed Coarse Mesh Projection Method (CMPM) and can be implemented using the coarse statistical bins for acquisition of nuclear fission source data. A novel aspect of CMPM is the combination of the general technical principle of projection pursuit in the signal processing discipline and the neutron multiplication eigenvalue problem in the nuclear engineering discipline. CMPM enables reactor physicists to accurately evaluate major eigenvalue separations of nuclear reactors with continuous energy Monte Carlo calculation. CMPM was incorporated in the MCNP Monte Carlo particle transport code of Los Alamos National Laboratory. The great advantage of CMPM over the traditional Fission Matrix method is demonstrated for the three space-dimensional modeling of the initial core of a pressurized water reactor

  18. Classification of Specialized Farms Applying Multivariate Statistical Methods

    Directory of Open Access Journals (Sweden)

    Zuzana Hloušková

    2017-01-01

    Full Text Available Classification of specialized farms applying multivariate statistical methods The paper is aimed at application of advanced multivariate statistical methods when classifying cattle breeding farming enterprises by their economic size. Advantage of the model is its ability to use a few selected indicators compared to the complex methodology of current classification model that requires knowledge of detailed structure of the herd turnover and structure of cultivated crops. Output of the paper is intended to be applied within farm structure research focused on future development of Czech agriculture. As data source, the farming enterprises database for 2014 has been used, from the FADN CZ system. The predictive model proposed exploits knowledge of actual size classes of the farms tested. Outcomes of the linear discriminatory analysis multifactor classification method have supported the chance of filing farming enterprises in the group of Small farms (98 % filed correctly, and the Large and Very Large enterprises (100 % filed correctly. The Medium Size farms have been correctly filed at 58.11 % only. Partial shortages of the process presented have been found when discriminating Medium and Small farms.

  19. Estimating Contraceptive Prevalence Using Logistics Data for Short-Acting Methods: Analysis Across 30 Countries.

    Science.gov (United States)

    Cunningham, Marc; Bock, Ariella; Brown, Niquelle; Sacher, Suzy; Hatch, Benjamin; Inglis, Andrew; Aronovich, Dana

    2015-09-01

    Contraceptive prevalence rate (CPR) is a vital indicator used by country governments, international donors, and other stakeholders for measuring progress in family planning programs against country targets and global initiatives as well as for estimating health outcomes. Because of the need for more frequent CPR estimates than population-based surveys currently provide, alternative approaches for estimating CPRs are being explored, including using contraceptive logistics data. Using data from the Demographic and Health Surveys (DHS) in 30 countries, population data from the United States Census Bureau International Database, and logistics data from the Procurement Planning and Monitoring Report (PPMR) and the Pipeline Monitoring and Procurement Planning System (PipeLine), we developed and evaluated 3 models to generate country-level, public-sector contraceptive prevalence estimates for injectable contraceptives, oral contraceptives, and male condoms. Models included: direct estimation through existing couple-years of protection (CYP) conversion factors, bivariate linear regression, and multivariate linear regression. Model evaluation consisted of comparing the referent DHS prevalence rates for each short-acting method with the model-generated prevalence rate using multiple metrics, including mean absolute error and proportion of countries where the modeled prevalence rate for each method was within 1, 2, or 5 percentage points of the DHS referent value. For the methods studied, family planning use estimates from public-sector logistics data were correlated with those from the DHS, validating the quality and accuracy of current public-sector logistics data. Logistics data for oral and injectable contraceptives were significantly associated (Plogistics data are strongly correlated with public-sector prevalence rates for short-acting methods, demonstrating the quality of current logistics data and their ability to provide relatively accurate prevalence estimates. The

  20. Identification of mine waters by statistical multivariate methods

    Energy Technology Data Exchange (ETDEWEB)

    Mali, N [IGGG, Ljubljana (Slovenia)

    1992-01-01

    Three water-bearing aquifers are present in the Velenje lignite mine. The aquifer waters have differing chemical composition; a geochemical water analysis can therefore determine the source of mine water influx. Mine water samples from different locations in the mine were analyzed, the results of chemical content and of electric conductivity of mine water were statistically processed by means of MICROGAS, SPSS-X and IN STATPAC computer programs, which apply three multivariate statistical methods (discriminate, cluster and factor analysis). Reliability of calculated values was determined with the Kolmogorov and Smirnov tests. It is concluded that laboratory analysis of single water samples can produce measurement errors, but statistical processing of water sample data can identify origin and movement of mine water. 15 refs.

  1. Finding Similarities in Ancient Ceramics by EDXRF and Multivariate Methods

    International Nuclear Information System (INIS)

    Civici, N.; Stamati, F.

    1999-01-01

    We have studied 39 samples of fragments from ceramic roof tiles with different stamps(Diamalas and Heraion), dated between 330 to 170 BC and found at the archaeological site of Dimales, some 30 km from the Adriatic coast. The data from these samples were compared with those obtained from 7 samples of similar objects and period with the stamp H eraion , found at the archaeological site of APOLLONIA. The samples were analyzed by energy-dispersive X -ray fluorescence(EDXRF), using of the x-ray lines of the elements to the intensity of the Compton peak. The results have been treated with diverse multivariate methods. The application of hierarchical cluster analysis and factor analysis permitted the identification of two main clusters. The first cluster is composed from the ''Heraion'' samples discovered in Apollonia, while the second comprises all the samples discovered in Dimale independent of their stamp. (authors)

  2. PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

    Science.gov (United States)

    The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

  3. Kernel Multivariate Analysis Framework for Supervised Subspace Learning: A Tutorial on Linear and Kernel Multivariate Methods

    DEFF Research Database (Denmark)

    Arenas-Garcia, J.; Petersen, K.; Camps-Valls, G.

    2013-01-01

    correlation analysis (CCA), and orthonormalized PLS (OPLS), as well as their nonlinear extensions derived by means of the theory of reproducing kernel Hilbert spaces (RKHSs). We also review their connections to other methods for classification and statistical dependence estimation and introduce some recent...

  4. Assessment of susceptibility to earth-flow landslide using logistic regression and multivariate adaptive regression splines: A case of the Belice River basin (western Sicily, Italy)

    Science.gov (United States)

    Conoscenti, Christian; Ciaccio, Marilena; Caraballo-Arias, Nathalie Almaru; Gómez-Gutiérrez, Álvaro; Rotigliano, Edoardo; Agnesi, Valerio

    2015-08-01

    In this paper, terrain susceptibility to earth-flow occurrence was evaluated by using geographic information systems (GIS) and two statistical methods: Logistic regression (LR) and multivariate adaptive regression splines (MARS). LR has been already demonstrated to provide reliable predictions of earth-flow occurrence, whereas MARS, as far as we know, has never been used to generate earth-flow susceptibility models. The experiment was carried out in a basin of western Sicily (Italy), which extends for 51 km2 and is severely affected by earth-flows. In total, we mapped 1376 earth-flows, covering an area of 4.59 km2. To explore the effect of pre-failure topography on earth-flow spatial distribution, we performed a reconstruction of topography before the landslide occurrence. This was achieved by preparing a digital terrain model (DTM) where altitude of areas hosting landslides was interpolated from the adjacent undisturbed land surface by using the algorithm topo-to-raster. This DTM was exploited to extract 15 morphological and hydrological variables that, in addition to outcropping lithology, were employed as explanatory variables of earth-flow spatial distribution. The predictive skill of the earth-flow susceptibility models and the robustness of the procedure were tested by preparing five datasets, each including a different subset of landslides and stable areas. The accuracy of the predictive models was evaluated by drawing receiver operating characteristic (ROC) curves and by calculating the area under the ROC curve (AUC). The results demonstrate that the overall accuracy of LR and MARS earth-flow susceptibility models is from excellent to outstanding. However, AUC values of the validation datasets attest to a higher predictive power of MARS-models (AUC between 0.881 and 0.912) with respect to LR-models (AUC between 0.823 and 0.870). The adopted procedure proved to be resistant to overfitting and stable when changes of the learning and validation samples are

  5. Third-party Reverse logistics platform and method Based on Bilateral Resource Integration

    Directory of Open Access Journals (Sweden)

    Zheng Hong Zhen

    2016-01-01

    Full Text Available Dispersion of reverse logistics resources makes it difficult to create relationships between demanders and providers, thereby the personalized demand for the construction of enterprise reverse logistics cannot be satisfied and the service quality cannot be guaranteed. Aiming at these problems, this paper presents a platform and method of enterprise reverse logistics based on bilateral resource integration (RLBRI. The method creates a third-party reverse logistics platform to accumulate a mass of reverse logistics demanders and providers together. And the platform integrates bilateral resources and acts as an intermediary to establish relationships between two sides. Through the platform, a complete and high-quality business chain for enterprise reverse logistics will be built efficiently. Finally put forward an effective strategy of non-defective reverse logistics depends on the integrity checking service provided by third-party logistics. By using this strategy it can short the distance of non-defective reverse transportation. Computational tests validate the strategy.

  6. Personal, Social, and Game-Related Correlates of Active and Non-Active Gaming Among Dutch Gaming Adolescents: Survey-Based Multivariable, Multilevel Logistic Regression Analyses

    Science.gov (United States)

    de Vet, Emely; Chinapaw, Mai JM; de Boer, Michiel; Seidell, Jacob C; Brug, Johannes

    2014-01-01

    Background Playing video games contributes substantially to sedentary behavior in youth. A new generation of video games—active games—seems to be a promising alternative to sedentary games to promote physical activity and reduce sedentary behavior. At this time, little is known about correlates of active and non-active gaming among adolescents. Objective The objective of this study was to examine potential personal, social, and game-related correlates of both active and non-active gaming in adolescents. Methods A survey assessing game behavior and potential personal, social, and game-related correlates was conducted among adolescents (12-16 years, N=353) recruited via schools. Multivariable, multilevel logistic regression analyses, adjusted for demographics (age, sex and educational level of adolescents), were conducted to examine personal, social, and game-related correlates of active gaming ≥1 hour per week (h/wk) and non-active gaming >7 h/wk. Results Active gaming ≥1 h/wk was significantly associated with a more positive attitude toward active gaming (OR 5.3, CI 2.4-11.8; Pgames (OR 0.30, CI 0.1-0.6; P=.002), a higher score on habit strength regarding gaming (OR 1.9, CI 1.2-3.2; P=.008) and having brothers/sisters (OR 6.7, CI 2.6-17.1; Pgame engagement (OR 0.95, CI 0.91-0.997; P=.04). Non-active gaming >7 h/wk was significantly associated with a more positive attitude toward non-active gaming (OR 2.6, CI 1.1-6.3; P=.035), a stronger habit regarding gaming (OR 3.0, CI 1.7-5.3; P7 h/wk. Active gaming is most strongly (negatively) associated with attitude with respect to non-active games, followed by observed active game behavior of brothers and sisters and attitude with respect to active gaming (positive associations). On the other hand, non-active gaming is most strongly associated with observed non-active game behavior of friends, habit strength regarding gaming and attitude toward non-active gaming (positive associations). Habit strength was a

  7. Prediction of periodically correlated processes by wavelet transform and multivariate methods with applications to climatological data

    Science.gov (United States)

    Ghanbarzadeh, Mitra; Aminghafari, Mina

    2015-05-01

    This article studies the prediction of periodically correlated process using wavelet transform and multivariate methods with applications to climatological data. Periodically correlated processes can be reformulated as multivariate stationary processes. Considering this fact, two new prediction methods are proposed. In the first method, we use stepwise regression between the principal components of the multivariate stationary process and past wavelet coefficients of the process to get a prediction. In the second method, we propose its multivariate version without principal component analysis a priori. Also, we study a generalization of the prediction methods dealing with a deterministic trend using exponential smoothing. Finally, we illustrate the performance of the proposed methods on simulated and real climatological data (ozone amounts, flows of a river, solar radiation, and sea levels) compared with the multivariate autoregressive model. The proposed methods give good results as we expected.

  8. Multivariate analysis with LISREL

    CERN Document Server

    Jöreskog, Karl G; Y Wallentin, Fan

    2016-01-01

    This book traces the theory and methodology of multivariate statistical analysis and shows how it can be conducted in practice using the LISREL computer program. It presents not only the typical uses of LISREL, such as confirmatory factor analysis and structural equation models, but also several other multivariate analysis topics, including regression (univariate, multivariate, censored, logistic, and probit), generalized linear models, multilevel analysis, and principal component analysis. It provides numerous examples from several disciplines and discusses and interprets the results, illustrated with sections of output from the LISREL program, in the context of the example. The book is intended for masters and PhD students and researchers in the social, behavioral, economic and many other sciences who require a basic understanding of multivariate statistical theory and methods for their analysis of multivariate data. It can also be used as a textbook on various topics of multivariate statistical analysis.

  9. Simulation and optimization methods for logistics pooling in the outbound supply chain

    OpenAIRE

    Jesus Gonzalez-Feliu; Carlos Peris-Pla; Dina Rakotonarivo

    2010-01-01

    International audience; Logistics pooling and collaborative transportation systems are relatively new concepts in logistics research, but are very popular in practice. This communication proposes a conceptual framework for logistics and transportation pooling systems, as well as a simulation method for strategic planning optimization. This method is based on a twostep constructive heuristic in order to estimate for big instances the transportation and storage costs at a macroscopic level. Fou...

  10. Planning Approach to Organisational and Methodical Provision of Formation and Functioning of Logistic Systems of Enterprises

    OpenAIRE

    Kolodizyeva Tetyana O.; Panasyants Hanna S.

    2013-01-01

    The article analyses factors of external and internal environment of enterprises that influence the process of formation of logistic systems and justifies expediency of use of the planning approach to development of the organisational and methodical provision of functioning of logistic systems of enterprises. The article offers to conduct development of organisational and methodical provision of formation of functioning of logistic systems with the use of not one but several methodological ap...

  11. Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models

    NARCIS (Netherlands)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A.; van t Veld, Aart A.

    2012-01-01

    PURPOSE: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator

  12. Methods of the Development Strategy of Service Companies: Logistical Approach

    Science.gov (United States)

    Toymentseva, Irina A.; Karpova, Natalya P.; Toymentseva, Angelina A.; Chichkina, Vera D.; Efanov, Andrey V.

    2016-01-01

    The urgency of the analyzed issue is due to lack of attention of heads of service companies to the theory and methodology of strategic management, methods and models of management decision-making in times of economic instability. The purpose of the article is to develop theoretical positions and methodical recommendations on the formation of the…

  13. Understanding gendered aspects of migration aspiration and motives of university students by multivariate statistical methods

    Directory of Open Access Journals (Sweden)

    Đula Borozan

    2014-03-01

    Full Text Available The paper deals with the application of multivariate analysis of variance and logistic regression in measuring, explaining and evaluating (i gender differences in expressing migration aspirations, and (ii a gender effect on migration motivation of university students in Croatia. The results supported the thesis that migration is a complex gendering process that assumes subjective assessment of the whole set of interrelated motives. According to logistic regression, gender is a significant predictor of migration aspirations among the selected demographic and socio-economic variables. A multivariate analysis of variance showed that gender and migration aspirations in interaction matter when it comes to migration motives, particularly related to the perceived importance of social networks. Females, and especially those who aspire to migrate, assessed these motives as more important than males.

  14. Value Added Methods: Moving from Univariate to Multivariate Criteria

    Science.gov (United States)

    Newman, David; Newman, Isadore; Ridenour, Carolyn; Morales, Jennifer

    2014-01-01

    The authors describe five value-added methods (VAM) used in school assessment as the backdrop to their main thesis. Then they review the assumptions underlying measurement and evaluation, the foundation of all assessment systems, including value-added. They discuss the traditional criterion variable used in VAM: a standardized test score. Next,…

  15. Multi-block methods in multivariate process control

    DEFF Research Database (Denmark)

    Kohonen, J.; Reinikainen, S.P.; Aaljoki, K.

    2008-01-01

    methods the effect of a sub-process can be seen and an example with two blocks, near infra-red, NIR, and process data, is shown. The results show improvements in modelling task, when a MB-based approach is used. This way of working with data gives more information on the process than if all data...... are in one X-matrix. The procedure is demonstrated by an industrial continuous process, where knowledge about the sub-processes is available and X-matrix can be divided into blocks between process variables and NIR spectra.......In chemometric studies all predictor variables are usually collected in one data matrix X. This matrix is then analyzed by PLS regression or other methods. When data from several different sub-processes are collected in one matrix, there is a possibility that the effects of some sub-processes may...

  16. PROGRAMMING OF METHODS FOR THE NEEDS OF LOGISTICS DISTRIBUTION SOLVING PROBLEMS

    Directory of Open Access Journals (Sweden)

    Andrea Štangová

    2014-06-01

    Full Text Available Logistics has become one of the dominant factors which is affecting the successful management, competitiveness and mentality of the global economy. Distribution logistics materializes the connesciton of production and consumer marke. It uses different methodology and methods of multicriterial evaluation and allocation. This thesis adresses the problem of the costs of securing the distribution of product. It was therefore relevant to design a software product thet would be helpful in solvin the problems related to distribution logistics. Elodis – electronic distribution logistics program was designed on the basis of theoretical analysis of the issue of distribution logistics and on the analysis of the software products market. The program uses a multicriterial evaluation methods to deremine the appropriate type and mathematical and geometrical method to determine an appropriate allocation of the distribution center, warehouse and company.

  17. International manufacturing and logistics: application of a design method in five case studies

    NARCIS (Netherlands)

    Vos, G.C.J.M.

    1993-01-01

    International manufacturing and logistics has become an important topic for an increasing number of industrial firms. In this paper, a design method will be described which is aimed at supporting managers in decisions regarding the (re)design of international logistic structures. The heart of this

  18. Regionalization of Drought across South Korea Using Multivariate Methods

    Directory of Open Access Journals (Sweden)

    Muhammad Azam

    2017-12-01

    Full Text Available Topographic and hydro-climatic features of South Korea are highly heterogeneous and able to influence the drought phenomena in the region. The complex topographical and hydro-climatic features of South Korea need a statistically accurate method to find homogeneous regions. Regionalization of drought in a bivariate framework has scarcely been applied in South Korea before. Hierarchical Classification on Principal Components (HCPC algorithm together with Principal Component Analysis (PCA method and cluster validation indices were investigated and used for the regionalization of drought across the South Korean region. Statistical homogeneity and discordancy of the region was tested on univariate and bivariate frameworks. HCPC indicate that South Korea should be divided into four regions which are closer to being homogeneous. Univariate and bivariate homogeneity and discordancy tests showed the significant difference in their results due to the inability of univariate homogeneity and discordancy measures to consider the joint behavior of duration and severity. Regionalization of drought for SPI time scale of 1, 3, 6, 12, and 24 months showed significant variation in discordancy and homogeneity of the region with the change in SPI time scale. The results of this study can be used as basic data required to establish a drought mitigation plan on regional scales.

  19. Refining developmental coordination disorder subtyping with multivariate statistical methods

    Directory of Open Access Journals (Sweden)

    Lalanne Christophe

    2012-07-01

    Full Text Available Abstract Background With a large number of potentially relevant clinical indicators penalization and ensemble learning methods are thought to provide better predictive performance than usual linear predictors. However, little is known about how they perform in clinical studies where few cases are available. We used Random Forests and Partial Least Squares Discriminant Analysis to select the most salient impairments in Developmental Coordination Disorder (DCD and assess patients similarity. Methods We considered a wide-range testing battery for various neuropsychological and visuo-motor impairments which aimed at characterizing subtypes of DCD in a sample of 63 children. Classifiers were optimized on a training sample, and they were used subsequently to rank the 49 items according to a permuted measure of variable importance. In addition, subtyping consistency was assessed with cluster analysis on the training sample. Clustering fitness and predictive accuracy were evaluated on the validation sample. Results Both classifiers yielded a relevant subset of items impairments that altogether accounted for a sharp discrimination between three DCD subtypes: ideomotor, visual-spatial and constructional, and mixt dyspraxia. The main impairments that were found to characterize the three subtypes were: digital perception, imitations of gestures, digital praxia, lego blocks, visual spatial structuration, visual motor integration, coordination between upper and lower limbs. Classification accuracy was above 90% for all classifiers, and clustering fitness was found to be satisfactory. Conclusions Random Forests and Partial Least Squares Discriminant Analysis are useful tools to extract salient features from a large pool of correlated binary predictors, but also provide a way to assess individuals proximities in a reduced factor space. Less than 15 neuro-visual, neuro-psychomotor and neuro-psychological tests might be required to provide a sensitive and

  20. LOGISTICS RISK RESEARCH OF PREFABRICATED HOUSE CONSTRUCTION ENGINEERING BASED ON CREDIBILITY METHOD

    Directory of Open Access Journals (Sweden)

    Xiaoping Bai

    2017-07-01

    Full Text Available In recent years, the prefabricated house industry has rapid development,.Because of fewer suppliers, higher demand transport scheme and complex quality test, the risks of construction engineering logistics links are relatively high. Studying how to effectively evaluate the risks of construction engineering logistics links is significant. According to the characteristics of the prefabricated house construction engineering, we analyse the construction engineering logistics risks and use the combined weights method to determine the weight of indexes which contains both subjective and objective factors, to improve the scientific value and the validity of the assessment. Based on credibility measure method, a new logistics risk evaluation model in prefabricated housing is established to estimate the risk during making prefabricated house construction engineering. The presented model can avoid the subjectivity of selecting the membership function and solve the problem of how to comprehensively assess the construction engineering logistics risk in a certain extent.

  1. The application of outsourcing decision-making methods in a logistics context in South Africa

    Directory of Open Access Journals (Sweden)

    Naomi Bloem

    2015-07-01

    Full Text Available Background: Companies have often relinquished the control of important business functions to outside suppliers for the sake of short-term savings and because of the lack of use of proper decision-making methods within the business. Objectives: This article identified three methods of decision-making and applied it to a logistics outsourcing problem. The logistics outsourcing problem consisted of a make-or-buy decision as well as a supplier selection process. The purpose of the study was to determine the most suitable method in the case of logistics outsourcing. Method: The decision-making methods were applied to a South African case study within the fast moving consumer goods (FMCG industry. The logistics functions considered in the case study included secondary distribution and warehousing of finished goods. Each method considered the same evaluation criteria and the results were analysed and compared. Results: Each method produced different results to the logistics outsourcing problem. The method developed by Platts, Probert and Canez (2000 suggested that the logistics functions be insourced. The decision tree method suggested outsourcing both functions, with a unit rate cost model. The results from the linear programming (LP method indicated that the secondary distribution function should be insourced and the warehousing function outsourced, with a fixed and variable cost model pending further analysis of the demand trends. Conclusion: The study provides empirical evidence that proven outsourcing decision-making methods, such as the method developed by Platts et al. (2000, the LP method and the decision tree method traditionally applied to a manufacturing outsourcing decision problem, can be adapted and applied to a logistics outsourcing decision problem of a South African FMCG company.

  2. The application of outsourcing decision-making methods in a logistics context in South Africa

    OpenAIRE

    Naomi Bloem; Wilna L. Bean

    2015-01-01

    Background: Companies have often relinquished the control of important business functions to outside suppliers for the sake of short-term savings and because of the lack of use of proper decision-making methods within the business. Objectives: This article identified three methods of decision-making and applied it to a logistics outsourcing problem. The logistics outsourcing problem consisted of a make-or-buy decision as well as a supplier selection process. The purpose of the study was t...

  3. 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.

  4. Planning Approach to Organisational and Methodical Provision of Formation and Functioning of Logistic Systems of Enterprises

    Directory of Open Access Journals (Sweden)

    Kolodizyeva Tetyana O.

    2013-12-01

    Full Text Available The article analyses factors of external and internal environment of enterprises that influence the process of formation of logistic systems and justifies expediency of use of the planning approach to development of the organisational and methodical provision of functioning of logistic systems of enterprises. The article offers to conduct development of organisational and methodical provision of formation of functioning of logistic systems with the use of not one but several methodological approaches: situational, process, functional and planning. The conducted analysis allowed composing a basic project, which could be laid in the foundation of formation of a logistic system by any enterprise for meeting requirements of the planning triangle: content / borders, time, cost, taking into consideration the forth limitation – quality.

  5. Personal, social, and game-related correlates of active and non-active gaming among dutch gaming adolescents: survey-based multivariable, multilevel logistic regression analyses.

    Science.gov (United States)

    Simons, Monique; de Vet, Emely; Chinapaw, Mai Jm; de Boer, Michiel; Seidell, Jacob C; Brug, Johannes

    2014-04-04

    Playing video games contributes substantially to sedentary behavior in youth. A new generation of video games-active games-seems to be a promising alternative to sedentary games to promote physical activity and reduce sedentary behavior. At this time, little is known about correlates of active and non-active gaming among adolescents. The objective of this study was to examine potential personal, social, and game-related correlates of both active and non-active gaming in adolescents. A survey assessing game behavior and potential personal, social, and game-related correlates was conducted among adolescents (12-16 years, N=353) recruited via schools. Multivariable, multilevel logistic regression analyses, adjusted for demographics (age, sex and educational level of adolescents), were conducted to examine personal, social, and game-related correlates of active gaming ≥1 hour per week (h/wk) and non-active gaming >7 h/wk. Active gaming ≥1 h/wk was significantly associated with a more positive attitude toward active gaming (OR 5.3, CI 2.4-11.8; Pgames (OR 0.30, CI 0.1-0.6; P=.002), a higher score on habit strength regarding gaming (OR 1.9, CI 1.2-3.2; P=.008) and having brothers/sisters (OR 6.7, CI 2.6-17.1; Pgame engagement (OR 0.95, CI 0.91-0.997; P=.04). Non-active gaming >7 h/wk was significantly associated with a more positive attitude toward non-active gaming (OR 2.6, CI 1.1-6.3; P=.035), a stronger habit regarding gaming (OR 3.0, CI 1.7-5.3; P7 h/wk. Active gaming is most strongly (negatively) associated with attitude with respect to non-active games, followed by observed active game behavior of brothers and sisters and attitude with respect to active gaming (positive associations). On the other hand, non-active gaming is most strongly associated with observed non-active game behavior of friends, habit strength regarding gaming and attitude toward non-active gaming (positive associations). Habit strength was a correlate of both active and non-active gaming

  6. 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.

  7. Comparing treatment effects after adjustment with multivariable Cox proportional hazards regression and propensity score methods

    NARCIS (Netherlands)

    Martens, Edwin P; de Boer, Anthonius; Pestman, Wiebe R; Belitser, Svetlana V; Stricker, Bruno H Ch; Klungel, Olaf H

    PURPOSE: To compare adjusted effects of drug treatment for hypertension on the risk of stroke from propensity score (PS) methods with a multivariable Cox proportional hazards (Cox PH) regression in an observational study with censored data. METHODS: From two prospective population-based cohort

  8. A Novel Optimization Method on Logistics Operation for Warehouse & Port Enterprises Based on Game Theory

    Directory of Open Access Journals (Sweden)

    Junyang Li

    2013-09-01

    Full Text Available Purpose: The following investigation aims to deal with the competitive relationship among different warehouses & ports in the same company. Design/methodology/approach: In this paper, Game Theory is used in carrying out the optimization model. Genetic Algorithm is used to solve the model. Findings: Unnecessary competition will rise up if there is little internal communication among different warehouses & ports in one company. This paper carries out a novel optimization method on warehouse & port logistics operation model. Originality/value: Warehouse logistics business is a combination of warehousing services and terminal services which is provided by port logistics through the existing port infrastructure on the basis of a port. The newly proposed method can help to optimize logistics operation model for warehouse & port enterprises effectively. We set Sinotrans Guangdong Company as an example to illustrate the newly proposed method. Finally, according to the case study, this paper gives some responses and suggestions on logistics operation in Sinotrans Guangdong warehouse & port for its future development.

  9. A multivariate nonlinear mixed effects method for analyzing energy partitioning in growing pigs

    DEFF Research Database (Denmark)

    Strathe, Anders Bjerring; Danfær, Allan Christian; Chwalibog, André

    2010-01-01

    to the multivariate nonlinear regression model because the MNLME method accounted for correlated errors associated with PD and LD measurements and could also include the random effect of animal. It is recommended that multivariate models used to quantify energy metabolism in growing pigs should account for animal......Simultaneous equations have become increasingly popular for describing the effects of nutrition on the utilization of ME for protein (PD) and lipid deposition (LD) in animals. The study developed a multivariate nonlinear mixed effects (MNLME) framework and compared it with an alternative method...... for estimating parameters in simultaneous equations that described energy metabolism in growing pigs, and then proposed new PD and LD equations. The general statistical framework was implemented in the NLMIXED procedure in SAS. Alternative PD and LD equations were also developed, which assumed...

  10. Multivariate Statistical Methods as a Tool of Financial Analysis of Farm Business

    Czech Academy of Sciences Publication Activity Database

    Novák, J.; Sůvová, H.; Vondráček, Jiří

    2002-01-01

    Roč. 48, č. 1 (2002), s. 9-12 ISSN 0139-570X Institutional research plan: AV0Z1030915 Keywords : financial analysis * financial ratios * multivariate statistical methods * correlation analysis * discriminant analysis * cluster analysis Subject RIV: BB - Applied Statistics, Operational Research

  11. Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method

    Science.gov (United States)

    Denis Valle; Benjamin Baiser; Christopher W. Woodall; Robin Chazdon; Jerome. Chave

    2014-01-01

    We propose a novel multivariate method to analyse biodiversity data based on the Latent Dirichlet Allocation (LDA) model. LDA, a probabilistic model, reduces assemblages to sets of distinct component communities. It produces easily interpretable results, can represent abrupt and gradual changes in composition, accommodates missing data and allows for coherent estimates...

  12. The intervals method: a new approach to analyse finite element outputs using multivariate statistics

    Directory of Open Access Journals (Sweden)

    Jordi Marcé-Nogué

    2017-10-01

    Full Text Available Background In this paper, we propose a new method, named the intervals’ method, to analyse data from finite element models in a comparative multivariate framework. As a case study, several armadillo mandibles are analysed, showing that the proposed method is useful to distinguish and characterise biomechanical differences related to diet/ecomorphology. Methods The intervals’ method consists of generating a set of variables, each one defined by an interval of stress values. Each variable is expressed as a percentage of the area of the mandible occupied by those stress values. Afterwards these newly generated variables can be analysed using multivariate methods. Results Applying this novel method to the biological case study of whether armadillo mandibles differ according to dietary groups, we show that the intervals’ method is a powerful tool to characterize biomechanical performance and how this relates to different diets. This allows us to positively discriminate between specialist and generalist species. Discussion We show that the proposed approach is a useful methodology not affected by the characteristics of the finite element mesh. Additionally, the positive discriminating results obtained when analysing a difficult case study suggest that the proposed method could be a very useful tool for comparative studies in finite element analysis using multivariate statistical approaches.

  13. The intervals method: a new approach to analyse finite element outputs using multivariate statistics

    Science.gov (United States)

    De Esteban-Trivigno, Soledad; Püschel, Thomas A.; Fortuny, Josep

    2017-01-01

    Background In this paper, we propose a new method, named the intervals’ method, to analyse data from finite element models in a comparative multivariate framework. As a case study, several armadillo mandibles are analysed, showing that the proposed method is useful to distinguish and characterise biomechanical differences related to diet/ecomorphology. Methods The intervals’ method consists of generating a set of variables, each one defined by an interval of stress values. Each variable is expressed as a percentage of the area of the mandible occupied by those stress values. Afterwards these newly generated variables can be analysed using multivariate methods. Results Applying this novel method to the biological case study of whether armadillo mandibles differ according to dietary groups, we show that the intervals’ method is a powerful tool to characterize biomechanical performance and how this relates to different diets. This allows us to positively discriminate between specialist and generalist species. Discussion We show that the proposed approach is a useful methodology not affected by the characteristics of the finite element mesh. Additionally, the positive discriminating results obtained when analysing a difficult case study suggest that the proposed method could be a very useful tool for comparative studies in finite element analysis using multivariate statistical approaches. PMID:29043107

  14. Índice de risco de mortalidade por endocardite infecciosa: um modelo logístico multivariado Risk index for death by infective endocarditis: a multivariate logistic model

    Directory of Open Access Journals (Sweden)

    Mário Augusto Cray da Costa

    2007-06-01

    Full Text Available OBJETIVO: Os objetivos do presente trabalho foram identificar variáveis preditivas de mortalidade hospitalar em endocardite infecciosa e criar fórmula matemática para cálculo do risco de óbito e um escore de risco, comparando os dois métodos com a curva ROC. MÉTODO: Foram estudados, retrospectivamente, 186 casos consecutivos de endocardite infecciosa (EI confirmados, divididos em dois grupos: alta (137 e óbito hospitalar (49. A partir das razões das chances obtidas em análise multivariada, foram criados: uma fórmula para cálculo do risco de óbito e um escore de risco. RESULTADOS: Fatores preditivos de maior mortalidade (análise multivariada e o escore de risco com seus respectivos pesos foram: idade > 40 anos (RC = 4.16-95%I.C. [1.63,10.80] - 4 pontos, insuficiência cardíaca classe IV ou choque cardiovascular (RC = 4.93 - 95%I.C. [1.86,13.05] - 5 pontos, sepsis não-controlada (RC =5.97 - 95%I.C. [1.95,18.35] - 6 pontos, distúrbio de condução (RC = 5.07-95%I.C. [1.67,15.35] - 5 pontos, arritmia (RC = 8.17 - 95%I.C. [2.60,25.71] - 8 pontos, valva com grande destruição ou abscesso ou prótese (RC = 4.77-95%I.C. [1.44,15.76] - 5 pontos, e vegetação grande e móvel (RC = 4.36-95%I.C. [1.55,12.90] - 4 pontos. Pacientes com escore entre 0 e 10 tiveram 5,26% de MT e maior que 20: 78,9%. CONCLUSÕES: Quanto maior o escore, maior é a mortalidade, complemente-se, ainda, que a estimativa de mortalidade obtida por cálculo ou pelo escore é semelhante. É possível utilizar software para facilitar a aplicação do escore e calcular risco de mortalidade por endocardite infecciosa.OBJECTIVE: This study aimed at identifying predictive variables for in-hospital mortality, calculating the probability of death and creating a risk index for death by infective endocarditis by comparing two methods using a Receiver Operating Characteristic (ROC curve. METHODS: A retrospective study was conducted of 186 consecutive cases of confirmed infective

  15. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    Energy Technology Data Exchange (ETDEWEB)

    Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van' t [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands)

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  16. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    International Nuclear Information System (INIS)

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van’t

    2012-01-01

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  17. Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models.

    Science.gov (United States)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A

    2012-03-15

    To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright © 2012 Elsevier Inc. All rights reserved.

  18. Analysis Of The Logistics Intermediaries Choice Methods In The Supply Chains

    Directory of Open Access Journals (Sweden)

    Lukinskiy Valery

    2015-12-01

    Full Text Available The increase of the supply chains efficiency requires optimization of all types of logistic operations and functions. One of such functions is the choice of intermediaries (carriers, freight forwarders, suppliers, service enterprises etc. and, according to some specialists, it is a major strategic decision in management supply chains. The methods of choosing the logistic intermediaries are considered in many works, however, some questions remain debatable. The article discusses the analytical and expert approaches which serve as a basis to choose the intermediaries; along with it, in the article a comparative evaluation of choice expert methods is done: point-rating assessment, analytic hierarchy process and the general algorithm for selecting; the conclusions have been drawn about the applicability of each method.

  19. Multivariate statistical methods and data mining in particle physics (4/4)

    CERN Multimedia

    CERN. Geneva

    2008-01-01

    The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.

  20. Multivariate statistical methods and data mining in particle physics (2/4)

    CERN Multimedia

    CERN. Geneva

    2008-01-01

    The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.

  1. Multivariate statistical methods and data mining in particle physics (1/4)

    CERN Multimedia

    CERN. Geneva

    2008-01-01

    The lectures will cover multivariate statistical methods and their applications in High Energy Physics. The methods will be viewed in the framework of a statistical test, as used e.g. to discriminate between signal and background events. Topics will include an introduction to the relevant statistical formalism, linear test variables, neural networks, probability density estimation (PDE) methods, kernel-based PDE, decision trees and support vector machines. The methods will be evaluated with respect to criteria relevant to HEP analyses such as statistical power, ease of computation and sensitivity to systematic effects. Simple computer examples that can be extended to more complex analyses will be presented.

  2. Validated univariate and multivariate spectrophotometric methods for the determination of pharmaceuticals mixture in complex wastewater

    Science.gov (United States)

    Riad, Safaa M.; Salem, Hesham; Elbalkiny, Heba T.; Khattab, Fatma I.

    2015-04-01

    Five, accurate, precise, and sensitive univariate and multivariate spectrophotometric methods were developed for the simultaneous determination of a ternary mixture containing Trimethoprim (TMP), Sulphamethoxazole (SMZ) and Oxytetracycline (OTC) in waste water samples collected from different cites either production wastewater or livestock wastewater after their solid phase extraction using OASIS HLB cartridges. In univariate methods OTC was determined at its λmax 355.7 nm (0D), while (TMP) and (SMZ) were determined by three different univariate methods. Method (A) is based on successive spectrophotometric resolution technique (SSRT). The technique starts with the ratio subtraction method followed by ratio difference method for determination of TMP and SMZ. Method (B) is successive derivative ratio technique (SDR). Method (C) is mean centering of the ratio spectra (MCR). The developed multivariate methods are principle component regression (PCR) and partial least squares (PLS). The specificity of the developed methods is investigated by analyzing laboratory prepared mixtures containing different ratios of the three drugs. The obtained results are statistically compared with those obtained by the official methods, showing no significant difference with respect to accuracy and precision at p = 0.05.

  3. Assessing the performance of variational methods for mixed logistic regression models

    Czech Academy of Sciences Publication Activity Database

    Rijmen, F.; Vomlel, Jiří

    2008-01-01

    Roč. 78, č. 8 (2008), s. 765-779 ISSN 0094-9655 R&D Projects: GA MŠk 1M0572 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Mixed models * Logistic regression * Variational methods * Lower bound approximation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.353, year: 2008

  4. 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.

  5. Modern nonparametric, robust and multivariate methods festschrift in honour of Hannu Oja

    CERN Document Server

    Taskinen, Sara

    2015-01-01

    Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volume is dedicated to Hannu Oja on the occasion of his 65th birthday and is intended for researchers as well as PhD students with a good knowledge of statistics.

  6. Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

    Science.gov (United States)

    Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

    2013-08-01

    Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

  7. Simulation of multivariate stationary stochastic processes using dimension-reduction representation methods

    Science.gov (United States)

    Liu, Zhangjun; Liu, Zenghui; Peng, Yongbo

    2018-03-01

    In view of the Fourier-Stieltjes integral formula of multivariate stationary stochastic processes, a unified formulation accommodating spectral representation method (SRM) and proper orthogonal decomposition (POD) is deduced. By introducing random functions as constraints correlating the orthogonal random variables involved in the unified formulation, the dimension-reduction spectral representation method (DR-SRM) and the dimension-reduction proper orthogonal decomposition (DR-POD) are addressed. The proposed schemes are capable of representing the multivariate stationary stochastic process with a few elementary random variables, bypassing the challenges of high-dimensional random variables inherent in the conventional Monte Carlo methods. In order to accelerate the numerical simulation, the technique of Fast Fourier Transform (FFT) is integrated with the proposed schemes. For illustrative purposes, the simulation of horizontal wind velocity field along the deck of a large-span bridge is proceeded using the proposed methods containing 2 and 3 elementary random variables. Numerical simulation reveals the usefulness of the dimension-reduction representation methods.

  8. A Novel and Effective Multivariate Method for Compositional Analysis using Laser Induced Breakdown Spectroscopy

    International Nuclear Information System (INIS)

    Wang, W; Qi, H; Ayhan, B; Kwan, C; Vance, S

    2014-01-01

    Compositional analysis is important to interrogate spectral samples for direct analysis of materials in agriculture, environment and archaeology, etc. In this paper, multi-variate analysis (MVA) techniques are coupled with laser induced breakdown spectroscopy (LIBS) to estimate quantitative elemental compositions and determine the type of the sample. In particular, we present a new multivariate analysis method for composition analysis, referred to as s pectral unmixing . The LIBS spectrum of a testing sample is considered as a linear mixture with more than one constituent signatures that correspond to various chemical elements. The signature library is derived from regression analysis using training samples or is manually set up with the information from an elemental LIBS spectral database. A calibration step is used to make all the signatures in library to be homogeneous with the testing sample so as to avoid inhomogeneous signatures that might be caused by different sampling conditions. To demonstrate the feasibility of the proposed method, we compare it with the traditional partial least squares (PLS) method and the univariate method using a standard soil data set with elemental concentration measured a priori. The experimental results show that the proposed method holds great potential for reliable and effective elemental concentration estimation

  9. Landslide susceptibility mapping on a global scale using the method of logistic regression

    Directory of Open Access Journals (Sweden)

    L. Lin

    2017-08-01

    Full Text Available This paper proposes a statistical model for mapping global landslide susceptibility based on logistic regression. After investigating explanatory factors for landslides in the existing literature, five factors were selected for model landslide susceptibility: relative relief, extreme precipitation, lithology, ground motion and soil moisture. When building the model, 70 % of landslide and nonlandslide points were randomly selected for logistic regression, and the others were used for model validation. To evaluate the accuracy of predictive models, this paper adopts several criteria including a receiver operating characteristic (ROC curve method. Logistic regression experiments found all five factors to be significant in explaining landslide occurrence on a global scale. During the modeling process, percentage correct in confusion matrix of landslide classification was approximately 80 % and the area under the curve (AUC was nearly 0.87. During the validation process, the above statistics were about 81 % and 0.88, respectively. Such a result indicates that the model has strong robustness and stable performance. This model found that at a global scale, soil moisture can be dominant in the occurrence of landslides and topographic factor may be secondary.

  10. Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

    Science.gov (United States)

    Kim, Yoonsang; Emery, Sherry

    2013-01-01

    Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

  11. 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.

  12. Application of instrumental neutron activation analysis and multivariate statistical methods to archaeological Syrian ceramics

    International Nuclear Information System (INIS)

    Bakraji, E. H.; Othman, I.; Sarhil, A.; Al-Somel, N.

    2002-01-01

    Instrumental neutron activation analysis (INAA) has been utilized in the analysis of thirty-seven archaeological ceramics fragment samples collected from Tal AI-Wardiate site, Missiaf town, Hamma city, Syria. 36 chemical elements were determined. These elemental concentrations have been processed using two multivariate statistical methods, cluster and factor analysis in order to determine similarities and correlation between the various samples. Factor analysis confirms that samples were correctly classified by cluster analysis. The results showed that samples can be considered to be manufactured using three different sources of raw material. (author)

  13. A Timed Colored Petri Net Simulation-Based Self-Adaptive Collaboration Method for Production-Logistics Systems

    Directory of Open Access Journals (Sweden)

    Zhengang Guo

    2017-03-01

    Full Text Available Complex and customized manufacturing requires a high level of collaboration between production and logistics in a flexible production system. With the widespread use of Internet of Things technology in manufacturing, a great amount of real-time and multi-source manufacturing data and logistics data is created, that can be used to perform production-logistics collaboration. To solve the aforementioned problems, this paper proposes a timed colored Petri net simulation-based self-adaptive collaboration method for Internet of Things-enabled production-logistics systems. The method combines the schedule of token sequences in the timed colored Petri net with real-time status of key production and logistics equipment. The key equipment is made ‘smart’ to actively publish or request logistics tasks. An integrated framework based on a cloud service platform is introduced to provide the basis for self-adaptive collaboration of production-logistics systems. A simulation experiment is conducted by using colored Petri nets (CPN Tools to validate the performance and applicability of the proposed method. Computational experiments demonstrate that the proposed method outperforms the event-driven method in terms of reductions of waiting time, makespan, and electricity consumption. This proposed method is also applicable to other manufacturing systems to implement production-logistics collaboration.

  14. Application of L1/2 regularization logistic method in heart disease diagnosis.

    Science.gov (United States)

    Zhang, Bowen; Chai, Hua; Yang, Ziyi; Liang, Yong; Chu, Gejin; Liu, Xiaoying

    2014-01-01

    Heart disease has become the number one killer of human health, and its diagnosis depends on many features, such as age, blood pressure, heart rate and other dozens of physiological indicators. Although there are so many risk factors, doctors usually diagnose the disease depending on their intuition and experience, which requires a lot of knowledge and experience for correct determination. To find the hidden medical information in the existing clinical data is a noticeable and powerful approach in the study of heart disease diagnosis. In this paper, sparse logistic regression method is introduced to detect the key risk factors using L(1/2) regularization on the real heart disease data. Experimental results show that the sparse logistic L(1/2) regularization method achieves fewer but informative key features than Lasso, SCAD, MCP and Elastic net regularization approaches. Simultaneously, the proposed method can cut down the computational complexity, save cost and time to undergo medical tests and checkups, reduce the number of attributes needed to be taken from patients.

  15. Logistical Worlds

    Directory of Open Access Journals (Sweden)

    Ned Rossiter

    2014-03-01

    Full Text Available As the managerial art and science of coordinating the movement of people, finance and things, logistical operations are central to contemporary capital. Despite its materiality in the form of communications and transport infrastructure, logistics remains an abstract machine for many. This is largely due to the compartmental structure of global supply chains and the invisibility of code. In registering the mediating force of logistics, the essay considers parametric politics as an architecture of intervention for both game design and software development. There are implications here not only for gameplay, but also the invention of method and governance of labour. How, for instance, might game design facilitate the production of a political knowledge of logistics? This becomes a matter to address for labour power vis-à-vis collective research on infrastructure, software and global supply chains.

  16. Modified generalized method of moments for a robust estimation of polytomous logistic model

    Directory of Open Access Journals (Sweden)

    Xiaoshan Wang

    2014-07-01

    Full Text Available The maximum likelihood estimation (MLE method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM approach is developed for dealing with contaminated polytomous response data. In this approach, distances are calculated based on individual sample moments. And Huber weights are applied to those observations with large distances. Mellow-type weights are also used to downplay leverage points. We describe theoretical properties of the proposed approach. Simulations suggest that the GMWM performs very well in correcting contamination-caused biases. An empirical application of the GMWM estimator on data from a survey demonstrates its usefulness.

  17. Multivariate analysis methods to tag b quark events at LEP/SLC

    International Nuclear Information System (INIS)

    Brandl, B.; Falvard, A.; Guicheney, C.; Henrard, P.; Jousset, J.; Proriol, J.

    1992-01-01

    Multivariate analyses are applied to tag Z → bb-bar events at LEP/SLC. They are based on the specific b-event shape caused by the large b-quark mass. Discriminant analyses, classification trees and neural networks are presented and their performances are compared. It is shown that the neural network approach, due to its non-linearity, copes best with the complexity of the problem. As an example for an application of the developed methods the measurement of Γ(Z → bb-bar) is discussed. The usefulness of methods based on the global event shape is limited by the uncertainties introduced by the necessity of event simulation. As solution a double tag method is presented which can be applied to many tasks of LEP/SLC heavy flavour physics. (author) 29 refs.; 6 figs.; 1 tab

  18. Study of a multivariable nonlinear process by the phase space method

    International Nuclear Information System (INIS)

    Tomei, Alain

    1969-02-01

    This paper concerns the study of the properties of a multivariate nonlinear process using the phase space method. Based on the example of the Rapsodie reactor, a fast sodium reactor, the authors have established the simplified differential equations with the analogical study of partial differential equations (in order to replace them with ordinary differential equations), a mathematical study of dynamic properties and stability of the simplified model by the phase space method, and the verification of the model properties using an analog calculator. The reactor, with all its thermal circuits, has been considered as a nonlinear system with two inputs and one output (reactor power). The great stability of a fast reactor such as Rapsodie, in the normal operating conditions, has been verified. The same method could be applied to any other type of reactor

  19. Identification and adoptive multivariable control method. Application to fast breeder nuclear reactors

    International Nuclear Information System (INIS)

    Dang Van Mien, H.; Irving, E.; Rousseau, I.

    1982-01-01

    Motivated by the limitations inherent in the standard approach, a new model reference multivariable adaptive control method is described. This latter control method utilizes as a design tool a simple vector difference equation of the controlled system. The adaptive control method is of the series-parallel direct reference model type and the adjustment algorithm is the standard least squares estimation technics with hyperstability conditions, controlled convergence speed forgetting, regularization and threshold operations. Numerical results are presented which illustrate the interest of the latter approach. The precise problem which has been tackled is the control of the steam generator of the second fast breeder French nuclear reactor called Super-Phenix. After a short description of the plant and its responses at different loads, the principles and the performances of the standard technique control scheme which has been adopted are discussed [fr

  20. Multivariate methods for analysis of environmental reference materials using laser-induced breakdown spectroscopy

    Directory of Open Access Journals (Sweden)

    Shikha Awasthi

    2017-06-01

    Full Text Available Analysis of emission from laser-induced plasma has a unique capability for quantifying the major and minor elements present in any type of samples under optimal analysis conditions. Chemometric techniques are very effective and reliable tools for quantification of multiple components in complex matrices. The feasibility of laser-induced breakdown spectroscopy (LIBS in combination with multivariate analysis was investigated for the analysis of environmental reference materials (RMs. In the present work, different (Certified/Standard Reference Materials of soil and plant origin were analyzed using LIBS and the presence of Al, Ca, Mg, Fe, K, Mn and Si were identified in the LIBS spectra of these materials. Multivariate statistical methods (Partial Least Square Regression and Partial Least Square Discriminant Analysis were employed for quantitative analysis of the constituent elements using the LIBS spectral data. Calibration models were used to predict the concentrations of the different elements of test samples and subsequently, the concentrations were compared with certified concentrations to check the authenticity of models. The non-destructive analytical method namely Instrumental Neutron Activation Analysis (INAA using high flux reactor neutrons and high resolution gamma-ray spectrometry was also used for intercomparison of results of two RMs by LIBS.

  1. A new solution method of ant colony-based logistic center area ...

    Indian Academy of Sciences (India)

    Fulya Zarali

    2018-05-21

    May 21, 2018 ... additional attention and interest. Examination of the related .... activity in the main area where the logistic center to be established. Area dimensions of ... The main areas of the logistic center are divided into equal unit areas.

  2. A design method of compensators for multi-variable control system with PID controllers 'CHARLY'

    International Nuclear Information System (INIS)

    Fujiwara, Toshitaka; Yamada, Katsumi

    1985-01-01

    A systematic design method of compensators for a multi-variable control system having usual PID controllers in its loops is presented in this paper. The method itself is able: to determine the main manipulating variable corresponding to each controlled variable with a sensitivity analysis in the frequency domain. to tune PID controllers sufficiently to realize adequate control actions with a searching technique of minimum values of cost functionals. to design compensators improving the control preformance and to simulate a total system for confirming the designed compensators. In the phase of compensator design, the state variable feed-back gain is obtained by means of the OPTIMAL REGULATOR THEORY for the composite system of plant and PID controllers. The transfer function type compensators the configurations of which were previously given are, then, designed to approximate the frequency responces of the above mentioned state feed-back system. An example is illustrated for convenience. (author)

  3. Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

    Science.gov (United States)

    Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

    2018-04-01

    Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

  4. Modelling Status Food Security Households Disease Sufferers Pulmonary Tuberculosis Uses the Method Regression Logistics Binary

    Science.gov (United States)

    Wulandari, S. P.; Salamah, M.; Rositawati, A. F. D.

    2018-04-01

    Food security is the condition where the food fulfilment is managed well for the country till the individual. Indonesia is one of the country which has the commitment to create the food security becomes main priority. However, the food necessity becomes common thing means that it doesn’t care about nutrient standard and the health condition of family member, so in the fulfilment of food necessity also has to consider the disease suffered by the family member, one of them is pulmonary tuberculosa. From that reasons, this research is conducted to know the factors which influence on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya by using binary logistic regression method. The analysis result by using binary logistic regression shows that the variables wife latest education, house density and spacious house ventilation significantly affect on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya, where the wife education level is University/equivalent, the house density is eligible or 8 m2/person and spacious house ventilation 10% of the floor area has the opportunity to become food secure households amounted to 0.911089. While the chance of becoming food insecure households amounted to 0.088911. The model household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya has been conformable, and the overall percentages of those classifications are at 71.8%.

  5. An Improved Method to Control the Critical Parameters of a Multivariable Control System

    Science.gov (United States)

    Subha Hency Jims, P.; Dharmalingam, S.; Wessley, G. Jims John

    2017-10-01

    The role of control systems is to cope with the process deficiencies and the undesirable effect of the external disturbances. Most of the multivariable processes are highly iterative and complex in nature. Aircraft systems, Modern Power Plants, Refineries, Robotic systems are few such complex systems that involve numerous critical parameters that need to be monitored and controlled. Control of these important parameters is not only tedious and cumbersome but also is crucial from environmental, safety and quality perspective. In this paper, one such multivariable system, namely, a utility boiler has been considered. A modern power plant is a complex arrangement of pipework and machineries with numerous interacting control loops and support systems. In this paper, the calculation of controller parameters based on classical tuning concepts has been presented. The controller parameters thus obtained and employed has controlled the critical parameters of a boiler during fuel switching disturbances. The proposed method can be applied to control the critical parameters like elevator, aileron, rudder, elevator trim rudder and aileron trim, flap control systems of aircraft systems.

  6. Comparison of multivariate methods for studying the G×E interaction

    Directory of Open Access Journals (Sweden)

    Deoclécio Domingos Garbuglio

    2015-12-01

    Full Text Available The objective of this work was to evaluate three statistical multivariate methods for analyzing adaptability and environmental stratification simultaneously, using data from maize cultivars indicated for planting in the State of Paraná-Brazil. Under the FGGE and GGE methods, the genotypic effect adjusts the G×E interactions across environments, resulting in a high percentage of explanation associated with a smaller number of axes. Environmental stratification via the FGGE and GGE methods showed similar responses, while the AMMI method did not ensure grouping of environments. The adaptability analysis revealed low divergence patterns of the responses obtained through the three methods. Genotypes P30F35, P30F53, P30R50, P30K64 and AS 1570 showed high yields associated with general adaptability. The FGGE method allowed differences in yield responses in specific regions and the impact in locations belonging to the same environmental group (through rE to be associated with the level of the simple portion of the G×E interaction.

  7. COMPARISON OF ULTRASOUND IMAGE FILTERING METHODS BY MEANS OF MULTIVARIABLE KURTOSIS

    Directory of Open Access Journals (Sweden)

    Mariusz Nieniewski

    2017-06-01

    Full Text Available Comparison of the quality of despeckled US medical images is complicated because there is no image of a human body that would be free of speckles and could serve as a reference. A number of various image metrics are currently used for comparison of filtering methods; however, they do not satisfactorily represent the visual quality of images and medical expert’s satisfaction with images. This paper proposes an innovative use of relative multivariate kurtosis for the evaluation of the most important edges in an image. Multivariate kurtosis allows one to introduce an order among the filtered images and can be used as one of the metrics for image quality evaluation. At present there is no method which would jointly consider individual metrics. Furthermore, these metrics are typically defined by comparing the noisy original and filtered images, which is incorrect since the noisy original cannot serve as a golden standard. In contrast to this, the proposed kurtosis is the absolute measure, which is calculated independently of any reference image and it agrees with the medical expert’s satisfaction to a large extent. The paper presents a numerical procedure for calculating kurtosis and describes results of such calculations for a computer-generated noisy image, images of a general purpose phantom and a cyst phantom, as well as real-life images of thyroid and carotid artery obtained with SonixTouch ultrasound machine. 16 different methods of image despeckling are compared via kurtosis. The paper shows that visually more satisfactory despeckling results are associated with higher kurtosis, and to a certain degree kurtosis can be used as a single metric for evaluation of image quality.

  8. Identification and analysis of reverse logistics barriers using fuzzy Delphi method and AHP

    DEFF Research Database (Denmark)

    Bouzon, Marina; Govindan, Kannan; Rodriguez, Carlos M Taboada

    2016-01-01

    enacted National Policy on solid waste. To bridge this gap, this paper identifies and evaluates the barriers for RL in the Brazilian context. An eleven-step research methodology is proposed. First, literature was thoroughly reviewed. fuzzy Delphi method (FDM) was used to obtain the critical list...... a systematic literature review process, a list of most common RL barriers accepted by Brazilian organizations, and a priority ranking of RL barriers for the electrical-electronic industry sector in Brazil. The "Economic related issues" category of barriers seems to be the first priority. The financial burden...... the reverse flow must be taken. However, most existing research on the barriers for RL implementation is focused on developed countries. Among the most important emerging economies, Brazil, the largest Latin America economy, faces challenges such as a deficient logistics infrastructure and the recently...

  9. Forensic classification of counterfeit banknote paper by X-ray fluorescence and multivariate statistical methods.

    Science.gov (United States)

    Guo, Hongling; Yin, Baohua; Zhang, Jie; Quan, Yangke; Shi, Gaojun

    2016-09-01

    Counterfeiting of banknotes is a crime and seriously harmful to economy. Examination of the paper, ink and toners used to make counterfeit banknotes can provide useful information to classify and link different cases in which the suspects use the same raw materials. In this paper, 21 paper samples of counterfeit banknotes seized from 13 cases were analyzed by wavelength dispersive X-ray fluorescence. After measuring the elemental composition in paper semi-quantitatively, the normalized weight percentage data of 10 elements were processed by multivariate statistical methods of cluster analysis and principle component analysis. All these paper samples were mainly classified into 3 groups. Nine separate cases were successfully linked. It is demonstrated that elemental composition measured by XRF is a useful way to compare and classify papers used in different cases. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  10. Reducing false-positive incidental findings with ensemble genotyping and logistic regression based variant filtering methods.

    Science.gov (United States)

    Hwang, Kyu-Baek; Lee, In-Hee; Park, Jin-Ho; Hambuch, Tina; Choe, Yongjoon; Kim, MinHyeok; Lee, Kyungjoon; Song, Taemin; Neu, Matthew B; Gupta, Neha; Kohane, Isaac S; Green, Robert C; Kong, Sek Won

    2014-08-01

    As whole genome sequencing (WGS) uncovers variants associated with rare and common diseases, an immediate challenge is to minimize false-positive findings due to sequencing and variant calling errors. False positives can be reduced by combining results from orthogonal sequencing methods, but costly. Here, we present variant filtering approaches using logistic regression (LR) and ensemble genotyping to minimize false positives without sacrificing sensitivity. We evaluated the methods using paired WGS datasets of an extended family prepared using two sequencing platforms and a validated set of variants in NA12878. Using LR or ensemble genotyping based filtering, false-negative rates were significantly reduced by 1.1- to 17.8-fold at the same levels of false discovery rates (5.4% for heterozygous and 4.5% for homozygous single nucleotide variants (SNVs); 30.0% for heterozygous and 18.7% for homozygous insertions; 25.2% for heterozygous and 16.6% for homozygous deletions) compared to the filtering based on genotype quality scores. Moreover, ensemble genotyping excluded > 98% (105,080 of 107,167) of false positives while retaining > 95% (897 of 937) of true positives in de novo mutation (DNM) discovery in NA12878, and performed better than a consensus method using two sequencing platforms. Our proposed methods were effective in prioritizing phenotype-associated variants, and an ensemble genotyping would be essential to minimize false-positive DNM candidates. © 2014 WILEY PERIODICALS, INC.

  11. The crux of the method: assumptions in ordinary least squares and logistic regression.

    Science.gov (United States)

    Long, Rebecca G

    2008-10-01

    Logistic regression has increasingly become the tool of choice when analyzing data with a binary dependent variable. While resources relating to the technique are widely available, clear discussions of why logistic regression should be used in place of ordinary least squares regression are difficult to find. The current paper compares and contrasts the assumptions of ordinary least squares with those of logistic regression and explains why logistic regression's looser assumptions make it adept at handling violations of the more important assumptions in ordinary least squares.

  12. Simultaneous chemometric determination of pyridoxine hydrochloride and isoniazid in tablets by multivariate regression methods.

    Science.gov (United States)

    Dinç, Erdal; Ustündağ, Ozgür; Baleanu, Dumitru

    2010-08-01

    The sole use of pyridoxine hydrochloride during treatment of tuberculosis gives rise to pyridoxine deficiency. Therefore, a combination of pyridoxine hydrochloride and isoniazid is used in pharmaceutical dosage form in tuberculosis treatment to reduce this side effect. In this study, two chemometric methods, partial least squares (PLS) and principal component regression (PCR), were applied to the simultaneous determination of pyridoxine (PYR) and isoniazid (ISO) in their tablets. A concentration training set comprising binary mixtures of PYR and ISO consisting of 20 different combinations were randomly prepared in 0.1 M HCl. Both multivariate calibration models were constructed using the relationships between the concentration data set (concentration data matrix) and absorbance data matrix in the spectral region 200-330 nm. The accuracy and the precision of the proposed chemometric methods were validated by analyzing synthetic mixtures containing the investigated drugs. The recovery results obtained by applying PCR and PLS calibrations to the artificial mixtures were found between 100.0 and 100.7%. Satisfactory results obtained by applying the PLS and PCR methods to both artificial and commercial samples were obtained. The results obtained in this manuscript strongly encourage us to use them for the quality control and the routine analysis of the marketing tablets containing PYR and ISO drugs. Copyright © 2010 John Wiley & Sons, Ltd.

  13. Methods of measuring the level of logistics serving in international business

    Directory of Open Access Journals (Sweden)

    Simona BĂLĂŞESCU

    2015-06-01

    Full Text Available This paper raise the issue of logistics service of customers in international markets. The study aims optimizing logistics serving using the case of a company in Romania which has several foreign customers. The main objectives of the investigation are related to the measurement of logistic service level for the company’s foreign clients and to an evaluation of the present potential of the logistic serving strategy of this company. The instruments used for the analysis are the economic outputs, information from foreign customers and the theory about the level of logistic serving. The results of the analysis are used for making a proposal of a set of projects aiming the improvement of the serving quality of foreign customers.

  14. Search for the top quark at D0 using multivariate methods

    International Nuclear Information System (INIS)

    Bhat, P.C.

    1995-07-01

    We report on the search for the top quark in p bar p collisions at the Fermilab Tevatron (√s = 1.8 TeV) in the di-lepton and lepton+jets channels using multivariate methods. An H-matrix analysis of the eμ data corresponding to an integrated luminosity of 13.5±1.6 pb -1 yields one event whose likelihood to be a top quark event, assuming m top = 180 GeV/c 2 , is ten times more than that of WW and eighteen times more than that of Z → ττ. A neural network analysis of the e+jets channel using a data sample corresponding to an integrated luminosity of 47.9±5.7 pb -1 shows an excess of events in the signal region and yields a cross-section for t bar t production of 6.7±2.3 (stat.) pb, assuming a top mass of 200 GeV/c 2 . An analysis of the e+jets data using the probability density estimation method yields a cross-section that is consistent with the above result

  15. Multivariate optimization of a solar water heating system using the Simplex method

    CERN Document Server

    Michelson, E

    1982-01-01

    Two Simplex computer library packages for multivariate optimization have been tested on an hour-by-hour simulation of a solar water heating system. The two packages are: MINUITS written at CERN (Geneva) , and the E04CCF routine which is part of the UK Numerical Algorithms Group Library. Technical and economic optima have been derived for three of the following variables simultaneously: collector area, tilt, azimuth, and store volume. The two packages give the same results. The meteorological data used were one (composite) year for Hamburg (Germany) and 1964 for Kew (UK). The Hamburg data were also condensed to form a year consisting of 60 averaged days. The optima derived with the 60-day year were very close to those obtained with the 365-day year. The Simplex method, which is a direct search method, is known to be very robust. It is particularly suited to hour-by-hour simulations of solar heating systems since the function being minimized is not monotonically decreasing towards the minimum in sufficient sign...

  16. Study on Maritime Logistics Warehousing Center Model and Precision Marketing Strategy Optimization Based on Fuzzy Method and Neural Network Model

    OpenAIRE

    Xiao Kefeng; Hu Xiaolan

    2017-01-01

    The bulk commodity, different with the retail goods, has a uniqueness in the location selection, the chosen of transportation program and the decision objectives. How to make optimal decisions in the facility location, requirement distribution, shipping methods and the route selection and establish an effective distribution system to reduce the cost has become a burning issue for the e-commerce logistics, which is worthy to be deeply and systematically solved. In this paper, Logistics warehou...

  17. Solution identification and quantitative analysis of fiber-capacitive drop analyzer based on multivariate statistical methods

    Science.gov (United States)

    Chen, Zhe; Qiu, Zurong; Huo, Xinming; Fan, Yuming; Li, Xinghua

    2017-03-01

    A fiber-capacitive drop analyzer is an instrument which monitors a growing droplet to produce a capacitive opto-tensiotrace (COT). Each COT is an integration of fiber light intensity signals and capacitance signals and can reflect the unique physicochemical property of a liquid. In this study, we propose a solution analytical and concentration quantitative method based on multivariate statistical methods. Eight characteristic values are extracted from each COT. A series of COT characteristic values of training solutions at different concentrations compose a data library of this kind of solution. A two-stage linear discriminant analysis is applied to analyze different solution libraries and establish discriminant functions. Test solutions can be discriminated by these functions. After determining the variety of test solutions, Spearman correlation test and principal components analysis are used to filter and reduce dimensions of eight characteristic values, producing a new representative parameter. A cubic spline interpolation function is built between the parameters and concentrations, based on which we can calculate the concentration of the test solution. Methanol, ethanol, n-propanol, and saline solutions are taken as experimental subjects in this paper. For each solution, nine or ten different concentrations are chosen to be the standard library, and the other two concentrations compose the test group. By using the methods mentioned above, all eight test solutions are correctly identified and the average relative error of quantitative analysis is 1.11%. The method proposed is feasible which enlarges the applicable scope of recognizing liquids based on the COT and improves the concentration quantitative precision, as well.

  18. Complex logistics audit system

    Directory of Open Access Journals (Sweden)

    Zuzana Marková

    2010-02-01

    Full Text Available Complex logistics audit system is a tool for realization of logistical audit in the company. The current methods for logistics auditare based on “ad hok” analysis of logisticsl system. This paper describes system for complex logistics audit. It is a global diagnosticsof logistics processes and functions of enterprise. The goal of logistics audit is to provide comparative documentation for managementabout state of logistics in company and to show the potential of logistics changes in order to achieve more effective companyperformance.

  19. Comparison of multivariate and univariate statistical process control and monitoring methods

    International Nuclear Information System (INIS)

    Leger, R.P.; Garland, WM.J.; Macgregor, J.F.

    1996-01-01

    Work in recent years has lead to the development of multivariate process monitoring schemes which use Principal Component Analysis (PCA). This research compares the performance of a univariate scheme and a multivariate PCA scheme used for monitoring a simple process with 11 measured variables. The multivariate PCA scheme was able to adequately represent the process using two principal components. This resulted in a PCA monitoring scheme which used two charts as opposed to 11 charts for the univariate scheme and therefore had distinct advantages in terms of both data representation, presentation, and fault diagnosis capabilities. (author)

  20. 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

  1. Using multivariate machine learning methods and structural MRI to classify childhood onset schizophrenia and healthy controls

    Directory of Open Access Journals (Sweden)

    Deanna eGreenstein

    2012-06-01

    Full Text Available Introduction: Multivariate machine learning methods can be used to classify groups of schizophrenia patients and controls using structural magnetic resonance imaging (MRI. However, machine learning methods to date have not been extended beyond classification and contemporaneously applied in a meaningful way to clinical measures. We hypothesized that brain measures would classify groups, and that increased likelihood of being classified as a patient using regional brain measures would be positively related to illness severity, developmental delays and genetic risk. Methods: Using 74 anatomic brain MRI sub regions and Random Forest, we classified 98 COS patients and 99 age, sex, and ethnicity-matched healthy controls. We also used Random Forest to determine the likelihood of being classified as a schizophrenia patient based on MRI measures. We then explored relationships between brain-based probability of illness and symptoms, premorbid development, and presence of copy number variation associated with schizophrenia. Results: Brain regions jointly classified COS and control groups with 73.7% accuracy. Greater brain-based probability of illness was associated with worse functioning (p= 0.0004 and fewer developmental delays (p=0.02. Presence of copy number variation (CNV was associated with lower probability of being classified as schizophrenia (p=0.001. The regions that were most important in classifying groups included left temporal lobes, bilateral dorsolateral prefrontal regions, and left medial parietal lobes. Conclusions: Schizophrenia and control groups can be well classified using Random Forest and anatomic brain measures, and brain-based probability of illness has a positive relationship with illness severity and a negative relationship with developmental delays/problems and CNV-based risk.

  2. Estimation of typhoon rainfall in GaoPing River: A Multivariate Maximum Entropy Method

    Science.gov (United States)

    Pei-Jui, Wu; Hwa-Lung, Yu

    2016-04-01

    The heavy rainfall from typhoons is the main factor of the natural disaster in Taiwan, which causes the significant loss of human lives and properties. Statistically average 3.5 typhoons invade Taiwan every year, and the serious typhoon, Morakot in 2009, impacted Taiwan in recorded history. Because the duration, path and intensity of typhoon, also affect the temporal and spatial rainfall type in specific region , finding the characteristics of the typhoon rainfall type is advantageous when we try to estimate the quantity of rainfall. This study developed a rainfall prediction model and can be divided three parts. First, using the EEOF(extended empirical orthogonal function) to classify the typhoon events, and decompose the standard rainfall type of all stations of each typhoon event into the EOF and PC(principal component). So we can classify the typhoon events which vary similarly in temporally and spatially as the similar typhoon types. Next, according to the classification above, we construct the PDF(probability density function) in different space and time by means of using the multivariate maximum entropy from the first to forth moment statistically. Therefore, we can get the probability of each stations of each time. Final we use the BME(Bayesian Maximum Entropy method) to construct the typhoon rainfall prediction model , and to estimate the rainfall for the case of GaoPing river which located in south of Taiwan.This study could be useful for typhoon rainfall predictions in future and suitable to government for the typhoon disaster prevention .

  3. A method of signal transmission path analysis for multivariate random processes

    International Nuclear Information System (INIS)

    Oguma, Ritsuo

    1984-04-01

    A method for noise analysis called ''STP (signal transmission path) analysis'' is presentd as a tool to identify noise sources and their propagation paths in multivariate random proceses. Basic idea of the analysis is to identify, via time series analysis, effective network for the signal power transmission among variables in the system and to make use of its information to the noise analysis. In the present paper, we accomplish this through two steps of signal processings; first, we estimate, using noise power contribution analysis, variables which have large contribution to the power spectrum of interest, and then evaluate the STPs for each pair of variables to identify STPs which play significant role for the generated noise to transmit to the variable under evaluation. The latter part of the analysis is executed through comparison of partial coherence function and newly introduced partial noise power contribution function. This paper presents the procedure of the STP analysis and demonstrates, using simulation data as well as Borssele PWR noise data, its effectiveness for investigation of noise generation and propagation mechanisms. (author)

  4. Comprehensive Logistics

    CERN Document Server

    Gudehus, Timm

    2012-01-01

    Modern logistics comprises operative logistics, analytical logistics and management of logistic networks. Central task of operative logistics is the efficient supply of required goods at the right place within the right time. Tasks of analytical logistics are designing optimal networks and systems, developing strategies for planning, scheduling and operation, and organizing efficient order and performance processes. Logistic management plans, implements and operates logistic networks and schedules orders, stocks and resources. This reference-book offers a unique survey of modern logistics. It contains proven strategies, rules and tools for the solution of a multitude of logistic problems. The analytically derived algorithms and formulas can be used for the computer-based planning of logistic systems and for the dynamic scheduling of orders and resources in supply networks. They enable significant improvements of performance, quality and costs. Their application is demonstrated by several examples from industr...

  5. MODELS AND METHODS FOR LOGISTICS HUB LOCATION: A REVIEW TOWARDS TRANSPORTATION NETWORKS DESIGN

    Directory of Open Access Journals (Sweden)

    Carolina Luisa dos Santos Vieira

    Full Text Available ABSTRACT Logistics hubs affect the distribution patterns in transportation networks since they are flow-concentrating structures. Indeed, the efficient moving of goods throughout supply chains depends on the design of such networks. This paper presents a literature review on the logistics hub location problem, providing an outline of modeling approaches, solving techniques, and their applicability to such context. Two categories of models were identified. While multi-criteria models may seem best suited to find optimal locations, they do not allow an assessment of the impact of new hubs on goods flow and on the transportation network. On the other hand, single-criterion models, which provide location and flow allocation information, adopt network simplifications that hinder an accurate representation of the relationshipbetween origins, destinations, and hubs. In view of these limitations we propose future research directions for addressing real challenges of logistics hubs location regarding transportation networks design.

  6. Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods.

    Science.gov (United States)

    Amini, Payam; Maroufizadeh, Saman; Samani, Reza Omani; Hamidi, Omid; Sepidarkish, Mahdi

    2017-06-01

    Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods. This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6-21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used. The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB ( p logistic regression model for the classification of risk groups for PTB.

  7. A Determination Method of Optimal Customization Degree of Logistics Service Supply Chain with Mass Customization Service

    Directory of Open Access Journals (Sweden)

    Weihua Liu

    2014-01-01

    Full Text Available Customization degree is a very important field of mass customization. Its improvement could enhance customer satisfaction and further increase customer demand while correspondingly it will increase service price and decrease customer satisfaction and demand. Therefore this paper discusses how to deal with such issues in logistics service supply chain (LSSC with a logistics service integrator (LSI and a customer. With the establishment of customer demand function for logistics services and profit functions of the LSI and the customer, three different decision modes are proposed (i.e., customization degree dominated by LSI, customization degree dominated by customer, and customization degree decided by concentrated supply chain; many interesting findings are achieved. Firstly, to achieve customization cooperation between LSI and customer, measures should be taken to make the unit increase cost of the customized logistics services lower than a certain value. Secondly, there are differences between the optimal customization degree dominated by LSI and that dominated by customer. And in both cases, the dominator could realize more profit than the follower. Thirdly, with the profit secondary distribution strategy, the modified decentralized decision mode could accomplish the maximum profit achieved in centralized decision mode and meanwhile get the optimal customization degree.

  8. Multivariate normative comparison, a novel method for more reliably detecting cognitive impairment in HIV infection

    NARCIS (Netherlands)

    Su, Tanja; Schouten, Judith; Geurtsen, Gert J.; Wit, Ferdinand W.; Stolte, Ineke G.; Prins, Maria; Portegies, Peter; Caan, Matthan W. A.; Reiss, Peter; Majoie, Charles B.; Schmand, Ben A.

    2015-01-01

    The objective of this study is to assess whether multivariate normative comparison (MNC) improves detection of HIV-1-associated neurocognitive disorder (HAND) as compared with Frascati and Gisslén criteria. One-hundred and three HIV-1-infected men with suppressed viremia on combination

  9. Warehouse Logistics

    OpenAIRE

    Panibratetc, Anastasiia

    2015-01-01

    This research is a review of warehouse logistics on the example of Kannustalo Oy, located in Kannus, Western region of Finland. Kannustalo is an international company of designing, manufacturing and assembling block and turn-key houses. The research subject is logistics process in warehouse system of industrial company. In my work I discussed about theoretical aspect of logistics, logistic functions and processes. Later I considered warehouse as a part of logistics system and provided inf...

  10. Validation of multivariate classification methods using analytical fingerprints – concept and case study on organic feed for laying hens

    NARCIS (Netherlands)

    Alewijn, Martin; Voet, van der Hilko; Ruth, van Saskia

    2016-01-01

    Multivariate classification methods based on analytical fingerprints have found many applications in the food and feed area, but practical applications are still scarce due to a lack of a generally accepted validation procedure. This paper proposes a new approach for validation of this type of

  11. Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis

    NARCIS (Netherlands)

    Eekhout, I.; Wiel, M.A. van de; Heymans, M.W.

    2017-01-01

    Background. Multiple imputation is a recommended method to handle missing data. For significance testing after multiple imputation, Rubin’s Rules (RR) are easily applied to pool parameter estimates. In a logistic regression model, to consider whether a categorical covariate with more than two levels

  12. A Selection Model to Logistic Centers Based on TOPSIS and MCGP Methods: The Case of Airline Industry

    Directory of Open Access Journals (Sweden)

    Kou-Huang Chen

    2014-01-01

    Full Text Available The location selection of a logistics center is a crucial decision relating to cost and benefit analysis in airline industry. However, it is difficult to be solved because there are many conflicting and multiple objectives in location problems. To solve the problem, this paper integrates fuzzy technique for order preference by similarity to an ideal solution (TOPSIS and multichoice goal programming (MCGP to obtain an appropriate logistics center from many alternative locations for airline industry. The proposed method in this paper will offer the decision makers (DMs to set multiple aspiration levels for the decision criteria. A numerical example of application is also presented.

  13. Cooperation between partners in logistics outsourcing

    Directory of Open Access Journals (Sweden)

    Andreja KRIŽMAN

    2009-01-01

    Full Text Available The purpose of this article is to present the research results from a study of impact of cooperation between logistics service providers (LSP and their customers on logistics outsourcing performance conducted in the Slovenian market. On the basis of the existing literature and some new argumentations, derived from in-depth interviews with logistics experts of providers and customers, the measurement and structural models were empirically analyzed. Existing measurement scales for the constructs of cooperation, and outsourcing performance were slightly modified for this analysis. Their purification and measurement for validity and reliability were performed. Multivariate statistical methods (EFA, CFA and SEM - Partial Least Squares were utilized and hypotheses were tested. Cooperation between partners has a significant impact on the relationship and reduces problems in logistics performance. Cooperation in the model explain 58.5% of the variance of goal achievement and 36.6% of the variance of goal exceedance logistics of outsourcing performance.

  14. APPLICATION OF METHODS OF LOGISTICS AND PROJECT MANAGEMENT FOR THE CONSTRUCTION OF MANAGEMENT MODEL OF BUSINESS PROCESSES IN THE NETWORK

    Directory of Open Access Journals (Sweden)

    Наталія Іванівна ЧУХРАЙ

    2016-02-01

    Full Text Available In terms of the dynamic development of network economy for effective decision-making managers of enterprises should be combined methods of logistics and project management to obtain the positive synergistic effect. It is shown that the basis of objective measures aimed at minimizing transaction costs. Solving this problem is associated with the development of the structural shell of business enterprises, which continue to evolve rapidly. Organization joint coordinated work in the same virtual information field together geographically separated users opens up entirely new possibilities for improving the mechanisms of project management and logistics. It was reviewed the evolution tool of business process and identified key business processes in networks. The analysis of support for business processes in logistics networks contains a list of basic management mechanisms. It was developed the model of economic and mathematical business process management in structural shell business. The semantic content of the objective function is to minimize transaction costs.

  15. Solution Method of Multi-Product Two-Stage Logistics Problem with Constraints of Delivery Course

    Science.gov (United States)

    Ataka, Shinichiro; Gen, Mitsuo

    The logistics network design is one of the important phase of Supply Chain Management (SCM) and it is the problem that should be optimized for long-term promotion of efficiency of the whole supply chain. Usually a plant produces different type of products. Even if it is a factory of the same company, delivery is different by a kind of a produced product. The restrictions which this model has are deeply concerned with TP in the real world. In this paper, we consider the logistics network design problems with multi-products and constraints for delivery course. To solve the problem, we used a hybrid priority-based Genetic Algorithm (h-priGA), and we tried the comparison experiment with priority-based Genetic Algorithm (priGA)and h-priGA, we show it about the effectiveness of h-priGA.

  16. Reverse Logistics

    OpenAIRE

    Kulikova, Olga

    2016-01-01

    This thesis was focused on the analysis of the concept of reverse logistics and actual reverse processes which are implemented in mining industry and finding solutions for the optimization of reverse logistics in this sphere. The objective of this paper was the assessment of the development of reverse logistics in mining industry on the example of potash production. The theoretical part was based on reverse logistics and mining waste related literature and provided foundations for further...

  17. Precise Positioning Method for Logistics Tracking Systems Using Personal Handy-Phone System Based on Mahalanobis Distance

    Science.gov (United States)

    Yokoi, Naoaki; Kawahara, Yasuhiro; Hosaka, Hiroshi; Sakata, Kenji

    Focusing on the Personal Handy-phone System (PHS) positioning service used in physical distribution logistics, a positioning error offset method for improving positioning accuracy is invented. A disadvantage of PHS positioning is that measurement errors caused by the fluctuation of radio waves due to buildings around the terminal are large, ranging from several tens to several hundreds of meters. In this study, an error offset method is developed, which learns patterns of positioning results (latitude and longitude) containing errors and the highest signal strength at major logistic points in advance, and matches them with new data measured in actual distribution processes according to the Mahalanobis distance. Then the matching resolution is improved to 1/40 that of the conventional error offset method.

  18. An alternative method to predict the S-shaped curve for logistic characteristics of phonon transport in silicon thin film

    International Nuclear Information System (INIS)

    Awad, M.M.

    2014-01-01

    The S-shaped curve was observed by Yilbas and Bin Mansoor (2013). In this study, an alternative method to predict the S-shaped curve for logistic characteristics of phonon transport in silicon thin film is presented by using an analytical prediction method. This analytical prediction method was introduced by Bejan and Lorente in 2011 and 2012. The Bejan and Lorente method is based on two-mechanism flow of fast “invasion” by convection and slow “consolidation” by diffusion.

  19. What makes a pattern? Matching decoding methods to data in multivariate pattern analysis

    Directory of Open Access Journals (Sweden)

    Philip A Kragel

    2012-11-01

    Full Text Available Research in neuroscience faces the challenge of integrating information across different spatial scales of brain function. A promising technique for harnessing information at a range of spatial scales is multivariate pattern analysis (MVPA of functional magnetic resonance imaging (fMRI data. While the prevalence of MVPA has increased dramatically in recent years, its typical implementations for classification of mental states utilize only a subset of the information encoded in local fMRI signals. We review published studies employing multivariate pattern classification since the technique’s introduction, which reveal an extensive focus on the improved detection power that linear classifiers provide over traditional analysis techniques. We demonstrate using simulations and a searchlight approach, however, that nonlinear classifiers are capable of extracting distinct information about interactions within a local region. We conclude that for spatially localized analyses, such as searchlight and region of interest, multiple classification approaches should be compared in order to match fMRI analyses to the properties of local circuits.

  20. A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

    Science.gov (United States)

    Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

    2012-01-01

    From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

  1. [Monitoring method of extraction process for Schisandrae Chinensis Fructus based on near infrared spectroscopy and multivariate statistical process control].

    Science.gov (United States)

    Xu, Min; Zhang, Lei; Yue, Hong-Shui; Pang, Hong-Wei; Ye, Zheng-Liang; Ding, Li

    2017-10-01

    To establish an on-line monitoring method for extraction process of Schisandrae Chinensis Fructus, the formula medicinal material of Yiqi Fumai lyophilized injection by combining near infrared spectroscopy with multi-variable data analysis technology. The multivariate statistical process control (MSPC) model was established based on 5 normal batches in production and 2 test batches were monitored by PC scores, DModX and Hotelling T2 control charts. The results showed that MSPC model had a good monitoring ability for the extraction process. The application of the MSPC model to actual production process could effectively achieve on-line monitoring for extraction process of Schisandrae Chinensis Fructus, and can reflect the change of material properties in the production process in real time. This established process monitoring method could provide reference for the application of process analysis technology in the process quality control of traditional Chinese medicine injections. Copyright© by the Chinese Pharmaceutical Association.

  2. Modification of the method of construction of value chain industrial enterprises with regard to financial involvement of staff of logistics

    Directory of Open Access Journals (Sweden)

    Butrin A.G.

    2017-01-01

    Full Text Available The article presents the author’s method of building an efficient value chain in an industrial plant, based on a well-known concept of the value of M. Porter, and other members of the Harvard Business School. Its novelty lies in the fact that, first, the operation captured still poorly known financial stream; second, extended value chain border due to the inclusion of all members of the value within the supply chain management concept. This will speed up capital turnover and reduce costs in terms of integration of all participants in the value chain. Cash flow still remains little known in the concepts of financial management and financial logistics. However, the adaptation of key provisions in the crisis lie is the effective use of financial logistics methods.

  3. Estimating traffic volume on Wyoming low volume roads using linear and logistic regression methods

    Directory of Open Access Journals (Sweden)

    Dick Apronti

    2016-12-01

    Full Text Available Traffic volume is an important parameter in most transportation planning applications. Low volume roads make up about 69% of road miles in the United States. Estimating traffic on the low volume roads is a cost-effective alternative to taking traffic counts. This is because traditional traffic counts are expensive and impractical for low priority roads. The purpose of this paper is to present the development of two alternative means of cost-effectively estimating traffic volumes for low volume roads in Wyoming and to make recommendations for their implementation. The study methodology involves reviewing existing studies, identifying data sources, and carrying out the model development. The utility of the models developed were then verified by comparing actual traffic volumes to those predicted by the model. The study resulted in two regression models that are inexpensive and easy to implement. The first regression model was a linear regression model that utilized pavement type, access to highways, predominant land use types, and population to estimate traffic volume. In verifying the model, an R2 value of 0.64 and a root mean square error of 73.4% were obtained. The second model was a logistic regression model that identified the level of traffic on roads using five thresholds or levels. The logistic regression model was verified by estimating traffic volume thresholds and determining the percentage of roads that were accurately classified as belonging to the given thresholds. For the five thresholds, the percentage of roads classified correctly ranged from 79% to 88%. In conclusion, the verification of the models indicated both model types to be useful for accurate and cost-effective estimation of traffic volumes for low volume Wyoming roads. The models developed were recommended for use in traffic volume estimations for low volume roads in pavement management and environmental impact assessment studies.

  4. Design of a multivariable controller for a CANDU 600 MWe nuclear power plant using the INA method

    International Nuclear Information System (INIS)

    Roy, N.; Boisvert, J.; Mensah, S.

    1984-04-01

    The development of large and complex nuclear and process plants requires high-performance control systems, designed with rigorous multivariable techniques. This work is part of an analytical study demonstrating the real potential of multivariable methods. It covers every step in the design of a multi-variable controller for a Gentilly-2 type CANDU 600 MWe nuclear power plant using the Inverse Nyquist Array (INA) method. First the linear design model and its preliminary modifications are described. The design tools are reviewed and the operations required to achieve open-loop diagonal dominance are thoroughly described. Analysis of the closed-loop system is then performed and a feedback matrix is selected to meet the design specifications. The performance of the controller on the linear model is verified by simulation. Finally, the controller is implemented on the reference non-linear model to assess its overall performance. The results show that the INA method can be used successfully to design controllers for large and complex systems

  5. Study on Maritime Logistics Warehousing Center Model and Precision Marketing Strategy Optimization Based on Fuzzy Method and Neural Network Model

    Directory of Open Access Journals (Sweden)

    Xiao Kefeng

    2017-08-01

    Full Text Available The bulk commodity, different with the retail goods, has a uniqueness in the location selection, the chosen of transportation program and the decision objectives. How to make optimal decisions in the facility location, requirement distribution, shipping methods and the route selection and establish an effective distribution system to reduce the cost has become a burning issue for the e-commerce logistics, which is worthy to be deeply and systematically solved. In this paper, Logistics warehousing center model and precision marketing strategy optimization based on fuzzy method and neural network model is proposed to solve this problem. In addition, we have designed principles of the fuzzy method and neural network model to solve the proposed model because of its complexity. Finally, we have solved numerous examples to compare the results of lingo and Matlab, we use Matlab and lingo just to check the result and to illustrate the numerical example, we can find from the result, the multi-objective model increases logistics costs and improves the efficiency of distribution time.

  6. Analysis and assessment on heavy metal sources in the coastal soils developed from alluvial deposits using multivariate statistical methods.

    Science.gov (United States)

    Li, Jinling; He, Ming; Han, Wei; Gu, Yifan

    2009-05-30

    An investigation on heavy metal sources, i.e., Cu, Zn, Ni, Pb, Cr, and Cd in the coastal soils of Shanghai, China, was conducted using multivariate statistical methods (principal component analysis, clustering analysis, and correlation analysis). All the results of the multivariate analysis showed that: (i) Cu, Ni, Pb, and Cd had anthropogenic sources (e.g., overuse of chemical fertilizers and pesticides, industrial and municipal discharges, animal wastes, sewage irrigation, etc.); (ii) Zn and Cr were associated with parent materials and therefore had natural sources (e.g., the weathering process of parent materials and subsequent pedo-genesis due to the alluvial deposits). The effect of heavy metals in the soils was greatly affected by soil formation, atmospheric deposition, and human activities. These findings provided essential information on the possible sources of heavy metals, which would contribute to the monitoring and assessment process of agricultural soils in worldwide regions.

  7. Relationship Between Green Logistics Tendency and Logistics Performance: A Comparative Case Study on Logistics Service Providers

    OpenAIRE

    Ayşenur DOĞRU; Cemile SOLAK FIŞKIN

    2016-01-01

    Increasing concerns related to environmental side effects of the logistics services and competition between the logistics service providers are two pressuring factors on logistics service providers. This study seeks to explore the relation between green logistics tendency and logistic performance from the perspective of logistics service providers. In order to reach this aim, two logistics service providers are investigated by comparative case study method. Findings showed the effects of g...

  8. A multiresolution approach for the convergence acceleration of multivariate curve resolution methods.

    Science.gov (United States)

    Sawall, Mathias; Kubis, Christoph; Börner, Armin; Selent, Detlef; Neymeyr, Klaus

    2015-09-03

    Modern computerized spectroscopic instrumentation can result in high volumes of spectroscopic data. Such accurate measurements rise special computational challenges for multivariate curve resolution techniques since pure component factorizations are often solved via constrained minimization problems. The computational costs for these calculations rapidly grow with an increased time or frequency resolution of the spectral measurements. The key idea of this paper is to define for the given high-dimensional spectroscopic data a sequence of coarsened subproblems with reduced resolutions. The multiresolution algorithm first computes a pure component factorization for the coarsest problem with the lowest resolution. Then the factorization results are used as initial values for the next problem with a higher resolution. Good initial values result in a fast solution on the next refined level. This procedure is repeated and finally a factorization is determined for the highest level of resolution. The described multiresolution approach allows a considerable convergence acceleration. The computational procedure is analyzed and is tested for experimental spectroscopic data from the rhodium-catalyzed hydroformylation together with various soft and hard models. Copyright © 2015 Elsevier B.V. All rights reserved.

  9. Smart logistics

    NARCIS (Netherlands)

    Woensel, van T.

    2012-01-01

    This lecture focuses on Smart Logistics referring to these intelligent managerial decisions related to the design, operations and control of the transportation chain processes in an efficient and cost-effective way. The starting point for Smart Logistics is the key observation that the real-life

  10. Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

    Science.gov (United States)

    Maione, Camila; Barbosa, Rommel Melgaço

    2018-01-24

    Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

  11. Ergonomics, automation and logistics: practical and effective combination of working methods, a case study of a baking company.

    Science.gov (United States)

    Quintana, Leonardo; Arias, Claudia; Cordoba, Jorge; Moroy, Magda; Pulido, Jean; Ramirez, Angela

    2012-01-01

    The aim of this study was to combine three different analytical methods from three different disciplines to diagnose the ergonomic conditions, manufacturing and supply chain operation of a baking company. The study explores a summary of comprehensive working methods that combines the ergonomics, automation and logistics study methods in the diagnosis of working conditions and productivity. The participatory approach of this type of study that involves the feelings and first-hand knowledge of workers of the operation are determining factors in defining points of action and ergonomic interventions, as well as defining opportunities in the automation of manufacturing and logistics, to cope with the needs of the company. The study identified an ergonomic situation (high prevalence of wrist-hand pain), and the combination of interdisciplinary techniques applied allowed to improve this condition in the company. This type of study allows a primary basis of the opportunities presented by the combination of specialized methods of different disciplines, for the definition of comprehensive action plans for the company. Additionally, it outlines opportunities for improvement and recommendations to mitigate the burden associated with occupational diseases and as an end result improve the quality of life and productivity of workers.

  12. Robust multivariate analysis

    CERN Document Server

    J Olive, David

    2017-01-01

    This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given.  The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory.   The robust techniques  are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis.  A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...

  13. Hydrochemical analysis of groundwater using multivariate statistical methods - The Volta region, Ghana

    Science.gov (United States)

    Banoeng-Yakubo, B.; Yidana, S.M.; Nti, E.

    2009-01-01

    Q and R-mode multivariate statistical analyses were applied to groundwater chemical data from boreholes and wells in the northern section of the Volta region Ghana. The objective was to determine the processes that affect the hydrochemistry and the variation of these processes in space among the three main geological terrains: the Buem formation, Voltaian System and the Togo series that underlie the area. The analyses revealed three zones in the groundwater flow system: recharge, intermediate and discharge regions. All three zones are clearly different with respect to all the major chemical parameters, with concentrations increasing from the perceived recharge areas through the intermediate regions to the discharge areas. R-mode HCA and factor analysis (using varimax rotation and Kaiser Criterion) were then applied to determine the significant sources of variation in the hydrochemistry. This study finds that groundwater hydrochemistry in the area is controlled by the weathering of silicate and carbonate minerals, as well as the chemistry of infiltrating precipitation. This study finds that the ??D and ??18O data from the area fall along the Global Meteoric Water Line (GMWL). An equation of regression derived for the relationship between ??D and ??18O bears very close semblance to the equation which describes the GMWL. On the basis of this, groundwater in the study area is probably meteoric and fresh. The apparently low salinities and sodicities of the groundwater seem to support this interpretation. The suitability of groundwater for domestic and irrigation purposes is related to its source, which determines its constitution. A plot of the sodium adsorption ratio (SAR) and salinity (EC) data on a semilog axis, suggests that groundwater serves good irrigation quality in the area. Sixty percent (60%), 20% and 20% of the 67 data points used in this study fall within the medium salinity - low sodicity (C2-S1), low salinity -low sodicity (C1-S1) and high salinity - low

  14. Cellulose I crystallinity determination using FT-Raman spectroscopy : univariate and multivariate methods

    Science.gov (United States)

    Umesh P. Agarwal; Richard S. Reiner; Sally A. Ralph

    2010-01-01

    Two new methods based on FT–Raman spectroscopy, one simple, based on band intensity ratio, and the other using a partial least squares (PLS) regression model, are proposed to determine cellulose I crystallinity. In the simple method, crystallinity in cellulose I samples was determined based on univariate regression that was first developed using the Raman band...

  15. SOLVING TRANSPORT LOGISTICS PROBLEMS IN A VIRTUAL ENTERPRISE THROUGH ARTIFICIAL INTELLIGENCE METHODS

    OpenAIRE

    PAVLENKO, Vitaliy; PAVLENKO, Tetiana; MOROZOVA, Olga; KUZNETSOVA, Anna; VOROPAI, Olena

    2017-01-01

    The paper offers a solution to the problem of material flow allocation within a virtual enterprise by using artificial intelligence methods. The research is based on the use of fuzzy relations when planning for optimal transportation modes to deliver components for manufactured products. The Fuzzy Logic Toolbox is used to determine the optimal route for transportation of components for manufactured products. The methods offered have been exemplified in the present research. The authors have b...

  16. Computational Logistics

    DEFF Research Database (Denmark)

    Pacino, Dario; Voss, Stefan; Jensen, Rune Møller

    2013-01-01

    This book constitutes the refereed proceedings of the 4th International Conference on Computational Logistics, ICCL 2013, held in Copenhagen, Denmark, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in to...... in topical sections named: maritime shipping, road transport, vehicle routing problems, aviation applications, and logistics and supply chain management.......This book constitutes the refereed proceedings of the 4th International Conference on Computational Logistics, ICCL 2013, held in Copenhagen, Denmark, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized...

  17. Computational Logistics

    DEFF Research Database (Denmark)

    This book constitutes the refereed proceedings of the 4th International Conference on Computational Logistics, ICCL 2013, held in Copenhagen, Denmark, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in to...... in topical sections named: maritime shipping, road transport, vehicle routing problems, aviation applications, and logistics and supply chain management.......This book constitutes the refereed proceedings of the 4th International Conference on Computational Logistics, ICCL 2013, held in Copenhagen, Denmark, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized...

  18. [Methods of the multivariate statistical analysis of so-called polyetiological diseases using the example of coronary heart disease].

    Science.gov (United States)

    Lifshits, A M

    1979-01-01

    General characteristics of the multivariate statistical analysis (MSA) is given. Methodical premises and criteria for the selection of an adequate MSA method applicable to pathoanatomic investigations of the epidemiology of multicausal diseases are presented. The experience of using MSA with computors and standard computing programs in studies of coronary arteries aterosclerosis on the materials of 2060 autopsies is described. The combined use of 4 MSA methods: sequential, correlational, regressional, and discriminant permitted to quantitate the contribution of each of the 8 examined risk factors in the development of aterosclerosis. The most important factors were found to be the age, arterial hypertension, and heredity. Occupational hypodynamia and increased fatness were more important in men, whereas diabetes melitus--in women. The registration of this combination of risk factors by MSA methods provides for more reliable prognosis of the likelihood of coronary heart disease with a fatal outcome than prognosis of the degree of coronary aterosclerosis.

  19. Improving Healthcare Logistics Processes

    DEFF Research Database (Denmark)

    Feibert, Diana Cordes

    logistics processes in hospitals and aims to provide theoretically and empirically based evidence for improving these processes to both expand the knowledge base of healthcare logistics and provide a decision tool for hospital logistics managers to improve their processes. Case studies were conducted...... processes. Furthermore, a method for benchmarking healthcare logistics processes was developed. Finally, a theoretically and empirically founded framework was developed to support managers in making an informed decision on how to improve healthcare logistics processes. This study contributes to the limited...... literature concerned with the improvement of logistics processes in hospitals. Furthermore, the developed framework provides guidance for logistics managers in hospitals on how to improve their processes given the circumstances in which they operate....

  20. Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

    Science.gov (United States)

    Dai, Huanping; Micheyl, Christophe

    2012-11-01

    Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.

  1. SOLVING TRANSPORT LOGISTICS PROBLEMS IN A VIRTUAL ENTERPRISE THROUGH ARTIFICIAL INTELLIGENCE METHODS

    Directory of Open Access Journals (Sweden)

    Vitaliy PAVLENKO

    2017-06-01

    Full Text Available The paper offers a solution to the problem of material flow allocation within a virtual enterprise by using artificial intelligence methods. The research is based on the use of fuzzy relations when planning for optimal transportation modes to deliver components for manufactured products. The Fuzzy Logic Toolbox is used to determine the optimal route for transportation of components for manufactured products. The methods offered have been exemplified in the present research. The authors have built a simulation model for component transportation and delivery for manufactured products using the Simulink graphical environment for building models.

  2. A Comparison of Multivariate and Pre-Processing Methods for Quantitative Laser-Induced Breakdown Spectroscopy of Geologic Samples

    Science.gov (United States)

    Anderson, R. B.; Morris, R. V.; Clegg, S. M.; Bell, J. F., III; Humphries, S. D.; Wiens, R. C.

    2011-01-01

    The ChemCam instrument selected for the Curiosity rover is capable of remote laser-induced breakdown spectroscopy (LIBS).[1] We used a remote LIBS instrument similar to ChemCam to analyze 197 geologic slab samples and 32 pressed-powder geostandards. The slab samples are well-characterized and have been used to validate the calibration of previous instruments on Mars missions, including CRISM [2], OMEGA [3], the MER Pancam [4], Mini-TES [5], and Moessbauer [6] instruments and the Phoenix SSI [7]. The resulting dataset was used to compare multivariate methods for quantitative LIBS and to determine the effect of grain size on calculations. Three multivariate methods - partial least squares (PLS), multilayer perceptron artificial neural networks (MLP ANNs) and cascade correlation (CC) ANNs - were used to generate models and extract the quantitative composition of unknown samples. PLS can be used to predict one element (PLS1) or multiple elements (PLS2) at a time, as can the neural network methods. Although MLP and CC ANNs were successful in some cases, PLS generally produced the most accurate and precise results.

  3. A Ten-Step Design Method for Simulation Games in Logistics Management

    NARCIS (Netherlands)

    Fumarola, M.; Van Staalduinen, J.P.; Verbraeck, A.

    2011-01-01

    Simulation games have often been found useful as a method of inquiry to gain insight in complex system behavior and as aids for design, engineering simulation and visualization, and education. Designing simulation games are the result of creative thinking and planning, but often not the result of a

  4. A method to screen obstructive sleep apnea using multi-variable non-intrusive measurements

    International Nuclear Information System (INIS)

    De Silva, S; Abeyratne, U R; Hukins, C

    2011-01-01

    Obstructive sleep apnea (OSA) is a serious sleep disorder. The current standard OSA diagnosis method is polysomnography (PSG) testing. PSG requires an overnight hospital stay while physically connected to 10–15 channels of measurement. PSG is expensive, inconvenient and requires the extensive involvement of a sleep technologist. As such, it is not suitable for community screening. OSA is a widespread disease and more than 80% of sufferers remain undiagnosed. Simplified, unattended and cheap OSA screening methods are urgently needed. Snoring is commonly associated with OSA but is not fully utilized in clinical diagnosis. Snoring contains pseudo-periodic packets of energy that produce characteristic vibrating sounds familiar to humans. In this paper, we propose a multi-feature vector that represents pitch information, formant information, a measure of periodic structure existence in snore episodes and the neck circumference of the subject to characterize OSA condition. Snore features were estimated from snore signals recorded in a sleep laboratory. The multi-feature vector was applied to a neural network for OSA/non-OSA classification and K-fold cross-validated using a random sub-sampling technique. We also propose a simple method to remove a specific class of background interference. Our method resulted in a sensitivity of 91 ± 6% and a specificity of 89 ± 5% for test data for AHI THRESHOLD = 15 for a database consisting of 51 subjects. This method has the potential as a non-intrusive, unattended technique to screen OSA using snore sound as the primary signal

  5. Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

    Science.gov (United States)

    Liou, Jyun-you; Smith, Elliot H.; Bateman, Lisa M.; McKhann, Guy M., II; Goodman, Robert R.; Greger, Bradley; Davis, Tyler S.; Kellis, Spencer S.; House, Paul A.; Schevon, Catherine A.

    2017-08-01

    Objective. Epileptiform discharges, an electrophysiological hallmark of seizures, can propagate across cortical tissue in a manner similar to traveling waves. Recent work has focused attention on the origination and propagation patterns of these discharges, yielding important clues to their source location and mechanism of travel. However, systematic studies of methods for measuring propagation are lacking. Approach. We analyzed epileptiform discharges in microelectrode array recordings of human seizures. The array records multiunit activity and local field potentials at 400 micron spatial resolution, from a small cortical site free of obstructions. We evaluated several computationally efficient statistical methods for calculating traveling wave velocity, benchmarking them to analyses of associated neuronal burst firing. Main results. Over 90% of discharges met statistical criteria for propagation across the sampled cortical territory. Detection rate, direction and speed estimates derived from a multiunit estimator were compared to four field potential-based estimators: negative peak, maximum descent, high gamma power, and cross-correlation. Interestingly, the methods that were computationally simplest and most efficient (negative peak and maximal descent) offer non-inferior results in predicting neuronal traveling wave velocities compared to the other two, more complex methods. Moreover, the negative peak and maximal descent methods proved to be more robust against reduced spatial sampling challenges. Using least absolute deviation in place of least squares error minimized the impact of outliers, and reduced the discrepancies between local field potential-based and multiunit estimators. Significance. Our findings suggest that ictal epileptiform discharges typically take the form of exceptionally strong, rapidly traveling waves, with propagation detectable across millimeter distances. The sequential activation of neurons in space can be inferred from clinically

  6. Performance Evaluation of Multivariate Analysis Methods on the $Z \\gamma$ Final State

    CERN Document Server

    Amos, Kieran Robert

    2017-01-01

    The performance of various machine learning algorithms are evaluated for their separation power of the $Z\\gamma$ Electroweak process (with $Z\\rightarrow\\ell\\ell$ and $\\ell=e,\\mu$) against the various backgrounds that populate the selection.\\\\ The Boosted Decision Tree method is found to deliver the best performance and is compared to that of neural net analysis and previously used methods using $36.1\\, \\text{fb}^{-1}$ of data obtained at $\\sqrt{s}=13\\, \\text{TeV}$ from the ATLAS detector in 2015 and 2016.

  7. Hydrate formation during wet granulation studied by spectroscopic methods and multivariate analysis

    DEFF Research Database (Denmark)

    Jørgensen, Anna; Rantanen, Jukka; Karjalainen, Milja

    2002-01-01

    PURPOSE: The aim was to follow hydrate formation of two structurally related drugs, theophylline and caffeine, during wet granulation using fast and nondestructive spectroscopic methods. METHODS: Anhydrous theophylline and caffeine were granulated with purified water. Charge-coupled device (CCD......) Raman spectroscopy was compared with near-infrared spectroscopy (NIR) in following hydrate formation of drugs during wet granulation (off-line). To perform an at-line process analysis, the effect of water addition was monitored by NIR spectroscopy and principal components analysis (PCA). The changes...

  8. Multisite-multivariable sensitivity analysis of distributed watershed models: enhancing the perceptions from computationally frugal methods

    Science.gov (United States)

    This paper assesses the impact of different likelihood functions in identifying sensitive parameters of the highly parameterized, spatially distributed Soil and Water Assessment Tool (SWAT) watershed model for multiple variables at multiple sites. The global one-factor-at-a-time (OAT) method of Morr...

  9. Tuning method for multi-variable control system with PID controllers

    International Nuclear Information System (INIS)

    Fujiwara, Toshitaka

    1983-01-01

    Control systems, including thermal and nuclear power plants, generally and mainly use PID controllers consisting of proportional, integral and differential actions. These systems consist of multiple control loops which interfere with each other. Therefore, it is present status that the fine control of the system is carried out by the trial and error method because the adjusting procedure for a single control loop cannot be applied to a multi-loop system in most cases. In this report, a method to effectively adjust PID controller parameters in a short time in a control system which consists of multi-loops that interfere with each other. This method makes adjustment by using the control area as the evaluation function, which is the time-dependent integration of control deviation, the input to the PID controllers. In other words, the evaluation function is provided for each control result for every parameter (gain constant, reset rate, and differentiation time), and all parameters are simultaneously changed in the direction of minimizing the values of these evaluation functions. In the report, the principle of tuning method, the evaluation function for each of three parameters, and the adjusting system configuration for separately using for actual plant tuning and for control system design are described. It also shows the examples of application to the actual tuning of the control system for a thermal power plant and to a control system design. (Wakatsuki, Y.)

  10. 1 H NMR study and multivariate data analysis of reindeer skin tanning methods.

    Science.gov (United States)

    Zhu, Lizheng; Ilott, Andrew J; Del Federico, Eleonora; Kehlet, Cindie; Klokkernes, Torunn; Jerschow, Alexej

    2017-04-01

    Reindeer skin clothing has been an essential component in the lives of indigenous people of the arctic and sub-arctic regions, keeping them warm during harsh winters. However, the skin processing technology, which often conveys the history and tradition of the indigenous group, has not been well documented. In this study, NMR spectra and relaxation behaviors of reindeer skin samples treated with a variety of vegetable tannin extracts, oils and fatty substances are studied and compared. With the assistance of principal component analysis (PCA), one can recognize patterns and identify groupings of differently treated samples. These methods could be important aids in efforts to conserve museum leather artifacts with unknown treatment methods and in the analysis of reindeer skin tanning processes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  11. Multivariate analysis method for energy calibration and improved mass assignment in recoil spectrometry

    International Nuclear Information System (INIS)

    El Bouanani, Mohamed; Hult, Mikael; Persson, Leif; Swietlicki, Erik; Andersson, Margaretha; Oestling, Mikael; Lundberg, Nils; Zaring, Carina; Cohen, D.D.; Dytlewski, Nick; Johnston, P.N.; Walker, S.R.; Bubb, I.F.; Whitlow, H.J.

    1994-01-01

    Heavy ion recoil spectrometry is rapidly becoming a well established analysis method, but the associated data analysis processing is still not well developed. The pronounced nonlinear response of silicon detectors for heavy ions leads to serious limitation and complication in mass gating, which is the principal factor in obtaining energy spectra with minimal cross talk between elements. To overcome the above limitation, a simple empirical formula with an associated multiple regression method is proposed for the absolute energy calibration of the time of flight-energy dispersive detector telescope used in recoil spectrometry. A radical improvement in mass assignment was realized, which allows a more accurate and improved depth profiling with the important feature of making the data processing much easier. ((orig.))

  12. Evaluation of Extraction Protocols for Simultaneous Polar and Non-Polar Yeast Metabolite Analysis Using Multivariate Projection Methods

    Directory of Open Access Journals (Sweden)

    Nicolas P. Tambellini

    2013-07-01

    Full Text Available Metabolomic and lipidomic approaches aim to measure metabolites or lipids in the cell. Metabolite extraction is a key step in obtaining useful and reliable data for successful metabolite studies. Significant efforts have been made to identify the optimal extraction protocol for various platforms and biological systems, for both polar and non-polar metabolites. Here we report an approach utilizing chemoinformatics for systematic comparison of protocols to extract both from a single sample of the model yeast organism Saccharomyces cerevisiae. Three chloroform/methanol/water partitioning based extraction protocols found in literature were evaluated for their effectiveness at reproducibly extracting both polar and non-polar metabolites. Fatty acid methyl esters and methoxyamine/trimethylsilyl derivatized aqueous compounds were analyzed by gas chromatography mass spectrometry to evaluate non-polar or polar metabolite analysis. The comparative breadth and amount of recovered metabolites was evaluated using multivariate projection methods. This approach identified an optimal protocol consisting of 64 identified polar metabolites from 105 ion hits and 12 fatty acids recovered, and will potentially attenuate the error and variation associated with combining metabolite profiles from different samples for untargeted analysis with both polar and non-polar analytes. It also confirmed the value of using multivariate projection methods to compare established extraction protocols.

  13. Application of multivariate statistical methods in analyzing expectation surveys in Central Bank of Nigeria

    OpenAIRE

    Raymond, Ogbuka Obinna

    2017-01-01

    In analyzing survey data, most researchers and analysts make use of statistical methods with straight forward statistical approaches. More common, is the use of one‐way, two‐way or multi‐way tables, and graphical displays such as bar charts, line charts, etc. A brief overview of these approaches and a good discussion on aspects needing attention during the data analysis process can be found in Wilson & Stern (2001). In most cases however, analysis procedures that go beyond simp...

  14. A multivariate quadrature based moment method for LES based modeling of supersonic combustion

    Science.gov (United States)

    Donde, Pratik; Koo, Heeseok; Raman, Venkat

    2012-07-01

    The transported probability density function (PDF) approach is a powerful technique for large eddy simulation (LES) based modeling of scramjet combustors. In this approach, a high-dimensional transport equation for the joint composition-enthalpy PDF needs to be solved. Quadrature based approaches provide deterministic Eulerian methods for solving the joint-PDF transport equation. In this work, it is first demonstrated that the numerical errors associated with LES require special care in the development of PDF solution algorithms. The direct quadrature method of moments (DQMOM) is one quadrature-based approach developed for supersonic combustion modeling. This approach is shown to generate inconsistent evolution of the scalar moments. Further, gradient-based source terms that appear in the DQMOM transport equations are severely underpredicted in LES leading to artificial mixing of fuel and oxidizer. To overcome these numerical issues, a semi-discrete quadrature method of moments (SeQMOM) is formulated. The performance of the new technique is compared with the DQMOM approach in canonical flow configurations as well as a three-dimensional supersonic cavity stabilized flame configuration. The SeQMOM approach is shown to predict subfilter statistics accurately compared to the DQMOM approach.

  15. Comparison between different uncertainty propagation methods in multivariate analysis: An application in the bivariate case

    International Nuclear Information System (INIS)

    Mullor, R.; Sanchez, A.; Martorell, S.; Martinez-Alzamora, N.

    2011-01-01

    Safety related systems performance optimization is classically based on quantifying the effects that testing and maintenance activities have on reliability and cost (R+C). However, R+C quantification is often incomplete in the sense that important uncertainties may not be considered. An important number of studies have been published in the last decade in the field of R+C based optimization considering uncertainties. They have demonstrated that inclusion of uncertainties in the optimization brings the decision maker insights concerning how uncertain the R+C results are and how this uncertainty does matter as it can result in differences in the outcome of the decision making process. Several methods of uncertainty propagation based on the theory of tolerance regions have been proposed in the literature depending on the particular characteristics of the variables in the output and their relations. In this context, the objective of this paper focuses on the application of non-parametric and parametric methods to analyze uncertainty propagation, which will be implemented on a multi-objective optimization problem where reliability and cost act as decision criteria and maintenance intervals act as decision variables. Finally, a comparison of results of these applications and the conclusions obtained are presented.

  16. Comparison between different uncertainty propagation methods in multivariate analysis: An application in the bivariate case

    Energy Technology Data Exchange (ETDEWEB)

    Mullor, R. [Dpto. Estadistica e Investigacion Operativa, Universidad Alicante (Spain); Sanchez, A., E-mail: aisanche@eio.upv.e [Dpto. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica Valencia, Camino de Vera s/n 46022 (Spain); Martorell, S. [Dpto. Ingenieria Quimica y Nuclear, Universidad Politecnica Valencia (Spain); Martinez-Alzamora, N. [Dpto. Estadistica e Investigacion Operativa Aplicadas y Calidad, Universidad Politecnica Valencia, Camino de Vera s/n 46022 (Spain)

    2011-06-15

    Safety related systems performance optimization is classically based on quantifying the effects that testing and maintenance activities have on reliability and cost (R+C). However, R+C quantification is often incomplete in the sense that important uncertainties may not be considered. An important number of studies have been published in the last decade in the field of R+C based optimization considering uncertainties. They have demonstrated that inclusion of uncertainties in the optimization brings the decision maker insights concerning how uncertain the R+C results are and how this uncertainty does matter as it can result in differences in the outcome of the decision making process. Several methods of uncertainty propagation based on the theory of tolerance regions have been proposed in the literature depending on the particular characteristics of the variables in the output and their relations. In this context, the objective of this paper focuses on the application of non-parametric and parametric methods to analyze uncertainty propagation, which will be implemented on a multi-objective optimization problem where reliability and cost act as decision criteria and maintenance intervals act as decision variables. Finally, a comparison of results of these applications and the conclusions obtained are presented.

  17. Measuring Group Synchrony: A Cluster-Phase Method for Analyzing Multivariate Movement Time-Series

    Directory of Open Access Journals (Sweden)

    Michael eRichardson

    2012-10-01

    Full Text Available A new method for assessing group synchrony is introduced as being potentially useful for objectively determining degree of group cohesiveness or entitativity. The cluster-phase method of Frank and Richardson (2010 was used to analyze movement data from the rocking chair movements of six-member groups who rocked their chairs while seated in a circle facing the center. In some trials group members had no information about others’ movements (their eyes were shut or they had their eyes open and gazed at a marker in the center of the group. As predicted, the group level synchrony measure was able to distinguish between situations where synchrony would have been possible and situations where it would be impossible. Moreover, other aspects of the analysis illustrated how the cluster phase measures can be used to determine the type of patterning of group synchrony, and, when integrated with multi-level modeling, can be used to examine individual-level differences in synchrony and dyadic level synchrony as well.

  18. Simultaneous spectrophotometric determination of uranium and zirconium using cloud point extraction and multivariate methods

    International Nuclear Information System (INIS)

    Ghasemi, Jahan B.; Hashemi, Beshare; Shamsipur, Mojtaba

    2012-01-01

    A cloud point extraction (CPE) process using the nonionic surfactant Triton X-114 to simultaneous extraction and spectrophotometric determination of uranium and zirconium from aqueous solution using partial least squares (PLS) regression is investigated. The method is based on the complexation reaction of these cations with Alizarin Red S (ARS) and subsequent micelle-mediated extraction of products. The chemical parameters affecting the separation phase and detection process were studied and optimized. Under the optimum experimental conditions (i.e. pH 5.2, Triton X-114 = 0.20%, equilibrium time 10 min and cloud point 45 C), calibration graphs were linear in the range of 0.01-3 mg L -1 with detection limits of 2.0 and 0.80 μg L -1 for U and Zr, respectively. The experimental calibration set was composed of 16 sample solutions using an orthogonal design for two component mixtures. The root mean square error of predictions (RMSEPs) for U and Zr were 0.0907 and 0.1117, respectively. The interference effect of some anions and cations was also tested. The method was applied to the simultaneous determination of U and Zr in water samples.

  19. Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods.

    Science.gov (United States)

    Jiménez-Carvelo, Ana M; González-Casado, Antonio; Pérez-Castaño, Estefanía; Cuadros-Rodríguez, Luis

    2017-03-01

    A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.

  20. A new multivariate empirical mode decomposition method for improving the performance of SSVEP-based brain-computer interface

    Science.gov (United States)

    Chen, Yi-Feng; Atal, Kiran; Xie, Sheng-Quan; Liu, Quan

    2017-08-01

    Objective. Accurate and efficient detection of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG) is essential for the related brain-computer interface (BCI) applications. Approach. Although the canonical correlation analysis (CCA) has been applied extensively and successfully to SSVEP recognition, the spontaneous EEG activities and artifacts that often occur during data recording can deteriorate the recognition performance. Therefore, it is meaningful to extract a few frequency sub-bands of interest to avoid or reduce the influence of unrelated brain activity and artifacts. This paper presents an improved method to detect the frequency component associated with SSVEP using multivariate empirical mode decomposition (MEMD) and CCA (MEMD-CCA). EEG signals from nine healthy volunteers were recorded to evaluate the performance of the proposed method for SSVEP recognition. Main results. We compared our method with CCA and temporally local multivariate synchronization index (TMSI). The results suggest that the MEMD-CCA achieved significantly higher accuracy in contrast to standard CCA and TMSI. It gave the improvements of 1.34%, 3.11%, 3.33%, 10.45%, 15.78%, 18.45%, 15.00% and 14.22% on average over CCA at time windows from 0.5 s to 5 s and 0.55%, 1.56%, 7.78%, 14.67%, 13.67%, 7.33% and 7.78% over TMSI from 0.75 s to 5 s. The method outperformed the filter-based decomposition (FB), empirical mode decomposition (EMD) and wavelet decomposition (WT) based CCA for SSVEP recognition. Significance. The results demonstrate the ability of our proposed MEMD-CCA to improve the performance of SSVEP-based BCI.

  1. Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

    Science.gov (United States)

    Morris, Richard; Anderson, R.; Clegg, S. M.; Bell, J. F., III

    2010-01-01

    the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

  2. Evaluation of the Risk of Grade 3 Oral and Pharyngeal Dysphagia Using Atlas-Based Method and Multivariate Analyses of Individual Patient Dose Distributions

    Energy Technology Data Exchange (ETDEWEB)

    Otter, Sophie [Department of Clinical Oncology, Royal Marsden Hospital, Sutton and London (United Kingdom); Schick, Ulrike; Gulliford, Sarah [Department of Clinical Oncology, Royal Marsden Hospital, Sutton and London (United Kingdom); The Institute of Cancer Research, London (United Kingdom); Lal, Punita [Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow India (India); Franceschini, Davide [Department of Radiotherapy and Radiosurgery, Humanitas Research Hospital, Milan (Italy); Newbold, Katie; Nutting, Christopher; Harrington, Kevin [Department of Clinical Oncology, Royal Marsden Hospital, Sutton and London (United Kingdom); The Institute of Cancer Research, London (United Kingdom); Bhide, Shreerang, E-mail: shreerang.bhide@icr.ac.uk [Department of Clinical Oncology, Royal Marsden Hospital, Sutton and London (United Kingdom); The Institute of Cancer Research, London (United Kingdom); Department of Radiotherapy and Radiosurgery, Humanitas Research Hospital, Milan (Italy)

    2015-11-01

    Purpose: The study aimed to apply the atlas of complication incidence (ACI) method to patients receiving radical treatment for head and neck squamous cell carcinomas (HNSCC), to generate constraints based on dose-volume histograms (DVHs), and to identify clinical and dosimetric parameters that predict the risk of grade 3 oral mucositis (g3OM) and pharyngeal dysphagia (g3PD). Methods and Materials: Oral and pharyngeal mucosal DVHs were generated for 253 patients who received radiation (RT) or chemoradiation (CRT). They were used to produce ACI for g3OM and g3PD. Multivariate analysis (MVA) of the effect of dosimetry, clinical, and patient-related variables was performed using logistic regression and bootstrapping. Receiver operating curve (ROC) analysis was also performed, and the Youden index was used to find volume constraints that discriminated between volumes that predicted for toxicity. Results: We derived statistically significant dose-volume constraints for g3OM over the range v28 to v70. Only 3 statistically significant constraints were derived for g3PD v67, v68, and v69. On MVA, mean dose to the oral mucosa predicted for g3OM and concomitant chemotherapy and mean dose to the inferior constrictor (IC) predicted for g3PD. Conclusions: We have used the ACI method to evaluate incidences of g3OM and g3PD and ROC analysis to generate constraints to predict g3OM and g3PD derived from entire individual patient DVHs. On MVA, the strongest predictors were radiation dose (for g3OM) and concomitant chemotherapy (for g3PD).

  3. Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

    Science.gov (United States)

    Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

    2011-01-01

    Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

  4. LOGISTICS - EVOLUTION THROUGH INNOVATION

    Directory of Open Access Journals (Sweden)

    Petrache Alexandru Constantin

    2015-07-01

    Full Text Available The current economic conditions, the rapidity with which the exchange of information, resources and products in the market takes place makes the logistics seem appreciably less significant. However, the importance of logistics has been presented in the military field, through strategies that have led to wining of the great wars that mankind has seen, through the supply of troops with food or moving military equipment. The literature in the field of logistics has numerous works on this topic. But while most focuses on efficient ways of carrying out the component activities of logistics or the strategies of organizations with regard to logistics or its functions, research on dynamics of logistics is underdeveloped. To be able to propose new methods or strategies of logistic activities is necessary to understand the development of this concept, determinant factors and economic and social conditions that gave rise to such developments. Thus, after a presentation of the main landmarks of the historical development of logistics we highlight the importance of the innovation within an organization's value chain innovation, in particular, and how to conduct the business in general. Using generations of innovation identified in the literature, we determine the generation of logistics development, taking into account innovation and how to conduct business. In addition for a better highlight of the own vision over the logistics generations identified, we will present the graphical concept for each generation in part. Last but not least, for each generation identified we try to allocate the chronological landmarks featured in order to reinforce the importance played by innovation in the development of the logistics industry and to give future directions of research within this topic. The study took into account the information presented in articles, books and websites of the relevant specialty in logistics and innovation to be able to build and expose a

  5. Simultaneous Detemination of Atorvastatin Calcium and Amlodipine Besylate by Spectrophotometry and Multivariate Calibration Methods in Pharmaceutical Formulations

    Directory of Open Access Journals (Sweden)

    Amir H. M. Sarrafi

    2011-01-01

    Full Text Available Resolution of binary mixture of atorvastatin (ATV and amlodipine (AML with minimum sample pretreatment and without analyte separation has been successfully achieved using a rapid method based on partial least square analysis of UV–spectral data. Multivariate calibration modeling procedures, traditional partial least squares (PLS-2, interval partial least squares (iPLS and synergy partial least squares (siPLS, were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. The simultaneous determination of both analytes was possible by PLS processing of sample absorbance between 220-425 nm. The correlation coefficients (R and root mean squared error of cross validation (RMSECV for ATV and AML in synthetic mixture were 0.9991, 0.9958 and 0.4538, 0.2411 in best siPLS models respectively. The optimized method has been used for determination of ATV and AML in amostatin commercial tablets. The proposed method are simple, fast, inexpensive and do not need any separation or preparation methods.

  6. Evaluating online data of water quality changes in a pilot drinking water distribution system with multivariate data exploration methods.

    Science.gov (United States)

    Mustonen, Satu M; Tissari, Soile; Huikko, Laura; Kolehmainen, Mikko; Lehtola, Markku J; Hirvonen, Arja

    2008-05-01

    The distribution of drinking water generates soft deposits and biofilms in the pipelines of distribution systems. Disturbances in water distribution can detach these deposits and biofilms and thus deteriorate the water quality. We studied the effects of simulated pressure shocks on the water quality with online analysers. The study was conducted with copper and composite plastic pipelines in a pilot distribution system. The online data gathered during the study was evaluated with Self-Organising Map (SOM) and Sammon's mapping, which are useful methods in exploring large amounts of multivariate data. The objective was to test the usefulness of these methods in pinpointing the abnormal water quality changes in the online data. The pressure shocks increased temporarily the number of particles, turbidity and electrical conductivity. SOM and Sammon's mapping were able to separate these situations from the normal data and thus make those visible. Therefore these methods make it possible to detect abrupt changes in water quality and thus to react rapidly to any disturbances in the system. These methods are useful in developing alert systems and predictive applications connected to online monitoring.

  7. A Timed Colored Petri Net Simulation-Based Self-Adaptive Collaboration Method for Production-Logistics Systems

    OpenAIRE

    Zhengang Guo; Yingfeng Zhang; Xibin Zhao; Xiaoyu Song

    2017-01-01

    Complex and customized manufacturing requires a high level of collaboration between production and logistics in a flexible production system. With the widespread use of Internet of Things technology in manufacturing, a great amount of real-time and multi-source manufacturing data and logistics data is created, that can be used to perform production-logistics collaboration. To solve the aforementioned problems, this paper proposes a timed colored Petri net simulation-based self-adaptive colla...

  8. Simultaneous Determination of 6-Mercaptopurine and its Oxidative Metabolites in Synthetic Solutions and Human Plasma using Spectrophotometric Multivariate Calibration Methods

    Directory of Open Access Journals (Sweden)

    Mohammad-Reza Rashidi

    2011-06-01

    Full Text Available Introduction: 6-Mercaptopurine (6MP is an important chemotherapeutic drug in the conventional treatment of childhood acute lymphoblastic leukemia (ALL. It is catabolized to 6-thiouric acid (6TUA through 8-hydroxo-6-mercaptopurine (8OH6MP or 6-thioxanthine (6TX intermediates. Methods: High-performance liquid chromatography (HPLC is usually used to determine the contents of therapeutic drugs, metabolites and other important biomedical analytes in biological samples. In the present study, the multivariate calibration methods, partial least squares (PLS-1 and principle component regression (PCR have been developed and validated for the simultaneous determination of 6MP and its oxidative metabolites (6TUA, 8OH6MP and 6TX without analyte separation in spiked human plasma. Mixtures of 6MP, 8-8OH6MP, 6TX and 6TUA have been resolved by PLS-1 and PCR to their UV spectra. Results: Recoveries (% obtained for 6MP, 8-8OH6MP, 6TX and 6TUA were 94.5-97.5, 96.6-103.3, 95.1-96.9 and 93.4-95.8, respectively, using PLS-1 and 96.7-101.3, 96.2-98.8, 95.8-103.3 and 94.3-106.1, respectively, using PCR. The NAS (Net analyte signal concept was used to calculate multivariate analytical figures of merit such as limit of detection (LOD, selectivity and sensitivity. The limit of detections for 6MP, 8-8OH6MP, 6TX and 6TUA were calculated to be 0.734, 0.439, 0.797 and 0.482 µmol L-1, respectively, using PLS and 0.724, 0.418, 0783 and 0.535 µmol L-1, respectively, using PCR. HPLC was also applied as a validation method for simultaneous determination of these thiopurines in the synthetic solutions and human plasma. Conclusion: Combination of spectroscopic techniques and chemometric methods (PLS and PCR has provided a simple but powerful method for simultaneous analysis of multicomponent mixtures.

  9. Comparison of projection skills of deterministic ensemble methods using pseudo-simulation data generated from multivariate Gaussian distribution

    Science.gov (United States)

    Oh, Seok-Geun; Suh, Myoung-Seok

    2017-07-01

    The projection skills of five ensemble methods were analyzed according to simulation skills, training period, and ensemble members, using 198 sets of pseudo-simulation data (PSD) produced by random number generation assuming the simulated temperature of regional climate models. The PSD sets were classified into 18 categories according to the relative magnitude of bias, variance ratio, and correlation coefficient, where each category had 11 sets (including 1 truth set) with 50 samples. The ensemble methods used were as follows: equal weighted averaging without bias correction (EWA_NBC), EWA with bias correction (EWA_WBC), weighted ensemble averaging based on root mean square errors and correlation (WEA_RAC), WEA based on the Taylor score (WEA_Tay), and multivariate linear regression (Mul_Reg). The projection skills of the ensemble methods improved generally as compared with the best member for each category. However, their projection skills are significantly affected by the simulation skills of the ensemble member. The weighted ensemble methods showed better projection skills than non-weighted methods, in particular, for the PSD categories having systematic biases and various correlation coefficients. The EWA_NBC showed considerably lower projection skills than the other methods, in particular, for the PSD categories with systematic biases. Although Mul_Reg showed relatively good skills, it showed strong sensitivity to the PSD categories, training periods, and number of members. On the other hand, the WEA_Tay and WEA_RAC showed relatively superior skills in both the accuracy and reliability for all the sensitivity experiments. This indicates that WEA_Tay and WEA_RAC are applicable even for simulation data with systematic biases, a short training period, and a small number of ensemble members.

  10. Mapping erosion susceptibility by a multivariate statistical method: A case study from the Ayvalık region, NW Turkey

    Science.gov (United States)

    Akgün, Aykut; Türk, Necdet

    2011-09-01

    Erosion is one of the most important natural hazard phenomena in the world, and it poses a significant threat to Turkey in terms of land degredation and desertification. To cope with this problem, we must determine which areas are erosion-prone. Many studies have been carried out and different models and methods have been used to this end. In this study, we used a logistic regression to prepare an erosion susceptibility map for the Ayvalık region in Balıkesir (NW Turkey). The following were our assessment parameters: weathering grades of rocks, slope gradient, structural lineament density, drainage density, land cover, stream power index (SPI) and profile curvature. These were processed by Idrisi Kilimanjaro GIS software. We used logistic regression analysis to relate predictor variables to the occurrence or non-occurrence of gully erosion sites within geographic cells, and then we used this relationship to produce a probability map for future erosion sites. The results indicate that lineament density, weathering grades of rocks and drainage density are the most important variables governing erosion susceptibility. Other variables, such as land cover and slope gradient, were revealed as secondary important variables. Highly weathered basalt, andesite, basaltic andesite and lacustrine sediments were the units most susceptible to erosion. In order to calculate the prediction accuracy of the erosion susceptibility map generated, we compared it with the map showing the gully erosion areas. On the basis of this comparison, the area under curvature (AUC) value was found to be 0.81. This result suggests that the erosion susceptibility map we generated is accurate.

  11. Application of AHP method for optimal selection of the IT system supporting business operations in the logistics enterprise

    Directory of Open Access Journals (Sweden)

    Anna Baj-Rogowska

    2015-12-01

    The paper consists of three parts. The first one includes an overview of IT systems supporting the logistics management in a company. Then a theoretical background of the Analytic Hierarchy Process is presented as the basis for deliberations contained in the third part, which offers a way to solve the problem of IT system selection that can be used by any logistics company.

  12. New methods to measure and model logistics and goods effects by the use of the CLG-DSS Model

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Jensen, Anders Vestergaard

    2004-01-01

    This paper concerns the assessment and modelling of so-called logistics and goods effects (LG-effects) as part of a wider economic analysis by use of the developed CLG-DSS model. The results presented are based an on-going study, Task 9 about evaluation modelling and decision support systems (DSS......) in the Centre for Logistics and Goods Transport (CLG) 2001-2005 funded by the Danish Council for Technical-Scientific Research (STVF). Within the area of research on logistics the interaction between logistics and transportation is of great relevance. Task 9 and other recent studies have found that several...... companies are taking account of logistics and transport by setting up, among other things, specific departments to improve their handling. Some aspects in the transport sector concerning goods movement and consequences have not so far got the attention they deserve. In CLG Task 9 four LG-effects have been...

  13. International Logistics Science Conference

    CERN Document Server

    Hompel, Michael; Meier, J

    2014-01-01

    The importance of logistics in all its variations is still increasing. New technologies emerge, new planning methods and algorithms are developed, only to face a market with a growing complexity and the need of weighting monetary costs against ecological impact. Mastering these challenges requires a scientific viewpoint on logistics, but always with applications in mind. This volume presents up-to-date logistics research in all its diversity and interconnectedness. It grew out of the “International Logistics Science Conference” (ILSC) held in Dortmund in September 2013, bringing together leading scientists and young academics from nine different countries. The conference was jointly organized by the “Efficiency Cluster Logistics” and the “Fraunhofer Institute for Material Flow and Logistics”. The Program Committee used a double blind review process to choose the 12 strongest contributions, which were then grouped in four areas: - Sustainability logistics, including electric mobility, smart inform...

  14. Comparative evaluation of the powder and compression properties of various grades and brands of microcrystalline cellulose by multivariate methods.

    Science.gov (United States)

    Haware, Rahul V; Bauer-Brandl, Annette; Tho, Ingunn

    2010-01-01

    The present work challenges a newly developed approach to tablet formulation development by using chemically identical materials (grades and brands of microcrystalline cellulose). Tablet properties with respect to process and formulation parameters (e.g. compression speed, added lubricant and Emcompress fractions) were evaluated by 2(3)-factorial designs. Tablets of constant true volume were prepared on a compaction simulator at constant pressure (approx. 100 MPa). The highly repeatable and accurate force-displacement data obtained was evaluated by simple 'in-die' Heckel method and work descriptors. Relationships and interactions between formulation, process and tablet parameters were identified and quantified by multivariate analysis techniques; principal component analysis (PCA) and partial least square regressions (PLS). The method proved to be able to distinguish between different grades of MCC and even between two different brands of the same grade (Avicel PH 101 and Vivapur 101). One example of interaction was studied in more detail by mixed level design: The interaction effect of lubricant and Emcompress on elastic recovery of Avicel PH 102 was demonstrated to be complex and non-linear using the development tool under investigation.

  15. Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods.

    Science.gov (United States)

    Dong, Jian-Jun; Li, Qing-Liang; Yin, Hua; Zhong, Cheng; Hao, Jun-Guang; Yang, Pan-Fei; Tian, Yu-Hong; Jia, Shi-Ru

    2014-10-15

    Sensory evaluation is regarded as a necessary procedure to ensure a reproducible quality of beer. Meanwhile, high-throughput analytical methods provide a powerful tool to analyse various flavour compounds, such as higher alcohol and ester. In this study, the relationship between flavour compounds and sensory evaluation was established by non-linear models such as partial least squares (PLS), genetic algorithm back-propagation neural network (GA-BP), support vector machine (SVM). It was shown that SVM with a Radial Basis Function (RBF) had a better performance of prediction accuracy for both calibration set (94.3%) and validation set (96.2%) than other models. Relatively lower prediction abilities were observed for GA-BP (52.1%) and PLS (31.7%). In addition, the kernel function of SVM played an essential role of model training when the prediction accuracy of SVM with polynomial kernel function was 32.9%. As a powerful multivariate statistics method, SVM holds great potential to assess beer quality. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Development of a quantitative multivariable radiographic method to evaluate anatomic changes associated with laminitis in the forefeet of donkeys.

    Science.gov (United States)

    Collins, Simon N; Dyson, Sue J; Murray, Rachel C; Newton, J Richard; Burden, Faith; Trawford, Andrew F

    2012-08-01

    To establish and validate an objective method of radiographic diagnosis of anatomic changes in laminitic forefeet of donkeys on the basis of data from a comprehensive series of radiographic measurements. 85 donkeys with and 85 without forelimb laminitis for baseline data determination; a cohort of 44 donkeys with and 18 without forelimb laminitis was used for validation analyses. For each donkey, lateromedial radiographic views of 1 weight-bearing forelimb were obtained; images from 11 laminitic and 2 nonlaminitic donkeys were excluded (motion artifact) from baseline data determination. Data from an a priori selection of 19 measurements of anatomic features of laminitic and nonlaminitic donkey feet were analyzed by use of a novel application of multivariate statistical techniques. The resultant diagnostic models were validated in a blinded manner with data from the separate cohort of laminitic and nonlaminitic donkeys. Data were modeled, and robust statistical rules were established for the diagnosis of anatomic changes within laminitic donkey forefeet. Component 1 scores ≤ -3.5 were indicative of extreme anatomic change, and scores from -2.0 to 0.0 denoted modest change. Nonlaminitic donkeys with a score from 0.5 to 1.0 should be considered as at risk for laminitis. Results indicated that the radiographic procedures evaluated can be used for the identification, assessment, and monitoring of anatomic changes associated with laminitis. Screening assessments by use of this method may enable early detection of mild anatomic change and identification of at-risk donkeys.

  17. Optimization of cloud point extraction and solid phase extraction methods for speciation of arsenic in natural water using multivariate technique.

    Science.gov (United States)

    Baig, Jameel A; Kazi, Tasneem G; Shah, Abdul Q; Arain, Mohammad B; Afridi, Hassan I; Kandhro, Ghulam A; Khan, Sumaira

    2009-09-28

    The simple and rapid pre-concentration techniques viz. cloud point extraction (CPE) and solid phase extraction (SPE) were applied for the determination of As(3+) and total inorganic arsenic (iAs) in surface and ground water samples. The As(3+) was formed complex with ammonium pyrrolidinedithiocarbamate (APDC) and extracted by surfactant-rich phases in the non-ionic surfactant Triton X-114, after centrifugation the surfactant-rich phase was diluted with 0.1 mol L(-1) HNO(3) in methanol. While total iAs in water samples was adsorbed on titanium dioxide (TiO(2)); after centrifugation, the solid phase was prepared to be slurry for determination. The extracted As species were determined by electrothermal atomic absorption spectrometry. The multivariate strategy was applied to estimate the optimum values of experimental factors for the recovery of As(3+) and total iAs by CPE and SPE. The standard addition method was used to validate the optimized methods. The obtained result showed sufficient recoveries for As(3+) and iAs (>98.0%). The concentration factor in both cases was found to be 40.

  18. Inferring Weighted Directed Association Networks from Multivariate Time Series with the Small-Shuffle Symbolic Transfer Entropy Spectrum Method

    Directory of Open Access Journals (Sweden)

    Yanzhu Hu

    2016-09-01

    Full Text Available Complex network methodology is very useful for complex system exploration. However, the relationships among variables in complex systems are usually not clear. Therefore, inferring association networks among variables from their observed data has been a popular research topic. We propose a method, named small-shuffle symbolic transfer entropy spectrum (SSSTES, for inferring association networks from multivariate time series. The method can solve four problems for inferring association networks, i.e., strong correlation identification, correlation quantification, direction identification and temporal relation identification. The method can be divided into four layers. The first layer is the so-called data layer. Data input and processing are the things to do in this layer. In the second layer, we symbolize the model data, original data and shuffled data, from the previous layer and calculate circularly transfer entropy with different time lags for each pair of time series variables. Thirdly, we compose transfer entropy spectrums for pairwise time series with the previous layer’s output, a list of transfer entropy matrix. We also identify the correlation level between variables in this layer. In the last layer, we build a weighted adjacency matrix, the value of each entry representing the correlation level between pairwise variables, and then get the weighted directed association network. Three sets of numerical simulated data from a linear system, a nonlinear system and a coupled Rossler system are used to show how the proposed approach works. Finally, we apply SSSTES to a real industrial system and get a better result than with two other methods.

  19. A PERFORMANCE COMPARISON BETWEEN ARTIFICIAL NEURAL NETWORKS AND MULTIVARIATE STATISTICAL METHODS IN FORECASTING FINANCIAL STRENGTH RATING IN TURKISH BANKING SECTOR

    Directory of Open Access Journals (Sweden)

    MELEK ACAR BOYACIOĞLU

    2013-06-01

    Full Text Available Financial strength rating indicates the fundamental financial strength of a bank. The aim of financial strength rating is to measure a bank’s fundamental financial strength excluding the external factors. External factors can stem from the working environment or can be linked with the outside protective support mechanisms. With the evaluation, the rating of a bank free from outside supportive factors is being sought. Also the financial fundamental, franchise value, the variety of assets and working environment of a bank are being evaluated in this context. In this study, a model has been developed in order to predict the financial strength rating of Turkish banks. The methodology of this study is as follows: Selecting variables to be used in the model, creating a data set, choosing the techniques to be used and the evaluation of classification success of the techniques. It is concluded that the artificial neural network system shows a better performance in terms of classification of financial strength rating in comparison to multivariate statistical methods in the raining set. On the other hand, there is no meaningful difference could be found in the validation set in which the prediction performances of the employed techniques are tested.

  20. Integrated Application of Multivariate Statistical Methods to Source Apportionment of Watercourses in the Liao River Basin, Northeast China

    Directory of Open Access Journals (Sweden)

    Jiabo Chen

    2016-10-01

    Full Text Available Source apportionment of river water pollution is critical in water resource management and aquatic conservation. Comprehensive application of various GIS-based multivariate statistical methods was performed to analyze datasets (2009–2011 on water quality in the Liao River system (China. Cluster analysis (CA classified the 12 months of the year into three groups (May–October, February–April and November–January and the 66 sampling sites into three groups (groups A, B and C based on similarities in water quality characteristics. Discriminant analysis (DA determined that temperature, dissolved oxygen (DO, pH, chemical oxygen demand (CODMn, 5-day biochemical oxygen demand (BOD5, NH4+–N, total phosphorus (TP and volatile phenols were significant variables affecting temporal variations, with 81.2% correct assignments. Principal component analysis (PCA and positive matrix factorization (PMF identified eight potential pollution factors for each part of the data structure, explaining more than 61% of the total variance. Oxygen-consuming organics from cropland and woodland runoff were the main latent pollution factor for group A. For group B, the main pollutants were oxygen-consuming organics, oil, nutrients and fecal matter. For group C, the evaluated pollutants primarily included oxygen-consuming organics, oil and toxic organics.

  1. Determination of main fruits in adulterated nectars by ATR-FTIR spectroscopy combined with multivariate calibration and variable selection methods.

    Science.gov (United States)

    Miaw, Carolina Sheng Whei; Assis, Camila; Silva, Alessandro Rangel Carolino Sales; Cunha, Maria Luísa; Sena, Marcelo Martins; de Souza, Scheilla Vitorino Carvalho

    2018-07-15

    Grape, orange, peach and passion fruit nectars were formulated and adulterated by dilution with syrup, apple and cashew juices at 10 levels for each adulterant. Attenuated total reflectance Fourier transform mid infrared (ATR-FTIR) spectra were obtained. Partial least squares (PLS) multivariate calibration models allied to different variable selection methods, such as interval partial least squares (iPLS), ordered predictors selection (OPS) and genetic algorithm (GA), were used to quantify the main fruits. PLS improved by iPLS-OPS variable selection showed the highest predictive capacity to quantify the main fruit contents. The selected variables in the final models varied from 72 to 100; the root mean square errors of prediction were estimated from 0.5 to 2.6%; the correlation coefficients of prediction ranged from 0.948 to 0.990; and, the mean relative errors of prediction varied from 3.0 to 6.7%. All of the developed models were validated. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Water Quality Assessment and Pollution Source Identification of the Eastern Poyang Lake Basin Using Multivariate Statistical Methods

    Directory of Open Access Journals (Sweden)

    Weili Duan

    2016-01-01

    Full Text Available Multivariate statistical methods including cluster analysis (CA, discriminant analysis (DA and component analysis/factor analysis (PCA/FA, were applied to explore the surface water quality datasets including 14 parameters at 28 sites of the Eastern Poyang Lake Basin, Jiangxi Province of China, from January 2012 to April 2015, characterize spatiotemporal variation in pollution and identify potential pollution sources. The 28 sampling stations were divided into two periods (wet season and dry season and two regions (low pollution and high pollution, respectively, using hierarchical CA method. Four parameters (temperature, pH, ammonia-nitrogen (NH4-N, and total nitrogen (TN were identified using DA to distinguish temporal groups with close to 97.86% correct assignations. Again using DA, five parameters (pH, chemical oxygen demand (COD, TN, Fluoride (F, and Sulphide (S led to 93.75% correct assignations for distinguishing spatial groups. Five potential pollution sources including nutrients pollution, oxygen consuming organic pollution, fluorine chemical pollution, heavy metals pollution and natural pollution, were identified using PCA/FA techniques for both the low pollution region and the high pollution region. Heavy metals (Cuprum (Cu, chromium (Cr and Zinc (Zn, fluoride and sulfide are of particular concern in the study region because of many open-pit copper mines such as Dexing Copper Mine. Results obtained from this study offer a reasonable classification scheme for low-cost monitoring networks. The results also inform understanding of spatio-temporal variation in water quality as these topics relate to water resources management.

  3. Potential shallow aquifers characterization through an integrated geophysical method: multivariate approach by means of k-means algorithms

    Directory of Open Access Journals (Sweden)

    Stefano Bernardinetti

    2017-06-01

    Full Text Available The need to obtain a detailed hydrogeological characterization of the subsurface and its interpretation for the groundwater resources management, often requires to apply several and complementary geophysical methods. The goal of the approach in this paper is to provide a unique model of the aquifer by synthesizing and optimizing the information provided by several geophysical methods. This approach greatly reduces the degree of uncertainty and subjectivity of the interpretation by exploiting the different physical and mechanic characteristics of the aquifer. The studied area, into the municipality of Laterina (Arezzo, Italy, is a shallow basin filled by lacustrine and alluvial deposits (Pleistocene and Olocene epochs, Quaternary period, with alternated silt, sand with variable content of gravel and clay where the bottom is represented by arenaceous-pelitic rocks (Mt. Cervarola Unit, Tuscan Domain, Miocene epoch. This shallow basin constitutes the unconfined superficial aquifer to be exploited in the nearly future. To improve the geological model obtained from a detailed geological survey we performed electrical resistivity and P wave refraction tomographies along the same line in order to obtain different, independent and integrable data sets. For the seismic data also the reflected events have been processed, a remarkable contribution to draw the geologic setting. Through the k-means algorithm, we perform a cluster analysis for the bivariate data set to individuate relationships between the two sets of variables. This algorithm allows to individuate clusters with the aim of minimizing the dissimilarity within each cluster and maximizing it among different clusters of the bivariate data set. The optimal number of clusters “K”, corresponding to the individuated geophysical facies, depends to the multivariate data set distribution and in this work is estimated with the Silhouettes. The result is an integrated tomography that shows a finite

  4. Determination of vegetable oils and fats adulterants in diesel oil by high performance liquid chromatography and multivariate methods.

    Science.gov (United States)

    Brandão, Luiz Filipe Paiva; Braga, Jez Willian Batista; Suarez, Paulo Anselmo Ziani

    2012-02-17

    The current legislation requires the mandatory addition of biodiesel to all Brazilian road diesel oil A (pure diesel) marketed in the country and bans the addition of vegetable oils for this type of diesel. However, cases of irregular addition of vegetable oils directly to the diesel oil may occur, mainly due to the lower cost of these raw materials compared to the final product, biodiesel. In Brazil, the situation is even more critical once the country is one of the largest producers of oleaginous products in the world, especially soybean, and also it has an extensive road network dependent on diesel. Therefore, alternatives to control the quality of diesel have become increasingly necessary. This study proposes an analytical methodology for quality control of diesel with intention to identify and determine adulterations of oils and even fats of vegetable origin. This methodology is based on detection, identification and quantification of triacylglycerols on diesel (main constituents of vegetable oils and fats) by high performance liquid chromatography in reversed phase with UV detection at 205nm associated with multivariate methods. Six different types of oils and fats were studied (soybean, frying oil, corn, cotton, palm oil and babassu) and two methods were developed for data analysis. The first one, based on principal component analysis (PCA), nearest neighbor classification (KNN) and univariate regression, was used for samples adulterated with a single type of oil or fat. In the second method, partial least square regression (PLS) was used for the cases where the adulterants were mixtures of up to three types of oils or fats. In the first method, the techniques of PCA and KNN were correctly classified as 17 out of 18 validation samples on the type of oil or fat present. The concentrations estimated for adulterants showed good agreement with the reference values, with mean errors of prediction (RMSEP) ranging between 0.10 and 0.22% (v/v). The PLS method was

  5. A logistics sector’s perspective of factors and risks within the business environment that influence supply chains’ effectiveness: An explorative mixed method study

    Directory of Open Access Journals (Sweden)

    Johanna A. Badenhorst-Weiss

    2015-09-01

    Full Text Available Background: Supply chains in South Africa operate in a challenging business environment. This environment influences the efficiency and effectiveness of South African businesses and supply chains. These factors further influence the competitiveness of products produced in the country, the economic growth and development of South Africa. Objectives: The purpose of this study was two-fold: Firstly, to obtain insight into the main business environment risks and other factors, from a logistics perspective; and secondly, to demonstrate the use of methodology not often used in logistics research − the sequential mixed method. Method: The explorative study was conducted amongst logistics service providers and cargo owners in 2013 by means of a sequential mixed method study, consisting of a survey to determine the importance of risk factors in the business environment, followed by a qualitative study in the form of a focus group discussion to obtain richer data and insight into these risks and factors. The results of these two methods were integrated with industry literature. Results: It was found that increasing transportation costs, operational management of infrastructure and human resources-related problems pose the biggest challenges in the logistics industry. In addition, it was found that the mixed method research study has application possibilities in logistics research. Conclusion: The factors identified as particularly problematic for the logistics industry, namely ineffective operational management of infrastructure, the general conditions in the labour market and increasing costs (to some extent are outside the control of individual organisations. However, organisations can control how they react and mitigate these risk factors. It is shown that these factors and risks can change overnight. The use of the explorative mixed method in obtaining qualitative and quantitative inputs and integrating it with existing literature proved to be a

  6. Measuring efficiency in logistics

    Directory of Open Access Journals (Sweden)

    Milan Milovan Andrejić

    2013-06-01

    Full Text Available Dynamic market and environmental changes greatly affect operating of logistics systems. Logistics systems have to realize their activities and processes in an efficient way. The main objective of this paper is to analyze different aspects of efficiency measurement in logistics and to propose appropriate models of measurement. Measuring efficiency in logistics is a complex process that requires consideration of all subsystems, processes and activities as well as the impact of various financial, operational, environmental, quality and other factors. The proposed models have a basis in the Data Envelopment Analysis method. They could help managers in decision making and corrective actions processes. The tests and results of the model show the importance of input and output variables selection.

  7. Comparative urine analysis by liquid chromatography-mass spectrometry and multivariate statistics : Method development, evaluation, and application to proteinuria

    NARCIS (Netherlands)

    Kemperman, Ramses F. J.; Horvatovich, Peter L.; Hoekman, Berend; Reijmers, Theo H.; Muskiet, Frits A. J.; Bischoff, Rainer

    2007-01-01

    We describe a platform for the comparative profiling of urine using reversed-phase liquid chromatography-mass spectrometry (LC-MS) and multivariate statistical data analysis. Urinary compounds were separated by gradient elution and subsequently detected by electrospray Ion-Trap MS. The lower limit

  8. Education in logistics and training of non-logistic personnel

    Directory of Open Access Journals (Sweden)

    Marko D. Andrejić

    2011-01-01

    Full Text Available The significance of education in logistics and education and training of cadets who belong to non-logistic services (non-logistic personnel will be presented. The logistical aspects of education of non-logistic personnel are elaborated as well as the knowledge in the area of logistics which is necessary to be transferred through the educational process to non-logistic personnel for the successful accomplishment of their functional duties. A general approach and the methods of logistics education and improvement of non-logistic personnel are presented as well as the institutional prerequisites necessary for improving the quality of logistics education and training. The quality of the knowledge in this area and its implementation into the methods of thinking and decision making of non-logistic personnel affect the cooperation between the non-logistic and the logistic personnel, directly contributing to the quality of life and working conditions of units and institutions as well as to the quality and synergy in task accomplishments in the framework defined by the missions of the Army of Serbia. The necessary content and means of its transfer to cadets are discussed since they are supposed to be available at all levels and forms of education, depending on the previous cadet education levels. The theoretical bases and experiences shown are of general character and they have a universal application in the process of education. Introduction In our recent defense theory and operational practice, logistics education of non-logistic personnel is not sufficiently analyzed either in organizational or technological aspects, considering the concept and the logic of a systematic and a situational approach. The analysis of the experiences gained from operational practice shows a slight decrease in the quality of task accomplishment due to the lack of necessary logistic knowledge and habits as well as an increased communication gap between logistic and non-logistic

  9. The method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processes

    KAUST Repository

    Schillinger, Dominik

    2013-07-01

    The method of separation can be used as a non-parametric estimation technique, especially suitable for evolutionary spectral density functions of uniformly modulated and strongly narrow-band stochastic processes. The paper at hand provides a consistent derivation of method of separation based spectrum estimation for the general multi-variate and multi-dimensional case. The validity of the method is demonstrated by benchmark tests with uniformly modulated spectra, for which convergence to the analytical solution is demonstrated. The key advantage of the method of separation is the minimization of spectral dispersion due to optimum time- or space-frequency localization. This is illustrated by the calibration of multi-dimensional and multi-variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed. © 2013 Elsevier Ltd.

  10. Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

    Science.gov (United States)

    Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

    2018-03-01

    This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

  11. Prediction of UT1-UTC, LOD and AAM χ3 by combination of least-squares and multivariate stochastic methods

    Science.gov (United States)

    Niedzielski, Tomasz; Kosek, Wiesław

    2008-02-01

    This article presents the application of a multivariate prediction technique for predicting universal time (UT1-UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ 3). The multivariate predictions of LOD and UT1-UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ 3 time-series as the explanatory variable for the computation of LOD or UT1-UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ 3 data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ 3 predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1-UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1-UTC based on LS extrapolation or on LS + AR. In particular, the UT1-UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ 3 time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ 3 reveal the best accuracy for LS + AR.

  12. Multivariate interpolation

    Directory of Open Access Journals (Sweden)

    Pakhnutov I.A.

    2017-04-01

    Full Text Available the paper deals with iterative interpolation methods in forms of similar recursive procedures defined by a sort of simple functions (interpolation basis not necessarily real valued. These basic functions are kind of arbitrary type being defined just by wish and considerations of user. The studied interpolant construction shows virtue of versatility: it may be used in a wide range of vector spaces endowed with scalar product, no dimension restrictions, both in Euclidean and Hilbert spaces. The choice of basic interpolation functions is as wide as possible since it is subdued nonessential restrictions. The interpolation method considered in particular coincides with traditional polynomial interpolation (mimic of Lagrange method in real unidimensional case or rational, exponential etc. in other cases. The interpolation as iterative process, in fact, is fairly flexible and allows one procedure to change the type of interpolation, depending on the node number in a given set. Linear interpolation basis options (perhaps some nonlinear ones allow to interpolate in noncommutative spaces, such as spaces of nondegenerate matrices, interpolated data can also be relevant elements of vector spaces over arbitrary numeric field. By way of illustration, the author gives the examples of interpolation on the real plane, in the separable Hilbert space and the space of square matrices with vektorvalued source data.

  13. Logistics of LEP installation

    International Nuclear Information System (INIS)

    Genier, C.; Capper, S.

    1988-01-01

    The size of the LEP project, coupled with the tight construction schedules, calls for organized planning, logistics, monitoring and control. This is being carried out at present using tools such as ORACLE the Relational Database Management System, running on a VAX cluster for data storage and transfer, micro-computers for on-site follow-up, and PC's running Professional ORACLE, DOS and XENIX linked to a communications network to receive data feedback concerning transport and handling means. Following over 2 years of installations, this paper presents the methods used for the logistics of installation and their results

  14. Development of infill drilling recovery models for carbonates reservoirs using neural networks and multivariate statistical as a novel method

    International Nuclear Information System (INIS)

    Soto, R; Wu, Ch. H; Bubela, A M

    1999-01-01

    This work introduces a novel methodology to improve reservoir characterization models. In this methodology we integrated multivariate statistical analyses, and neural network models for forecasting the infill drilling ultimate oil recovery from reservoirs in San Andres and Clearfork carbonate formations in west Texas. Development of the oil recovery forecast models help us to understand the relative importance of dominant reservoir characteristics and operational variables, reproduce recoveries for units included in the database, forecast recoveries for possible new units in similar geological setting, and make operational (infill drilling) decisions. The variety of applications demands the creation of multiple recovery forecast models. We have developed intelligent software (Soto, 1998), oilfield intelligence (01), as an engineering tool to improve the characterization of oil and gas reservoirs. 01 integrates neural networks and multivariate statistical analysis. It is composed of five main subsystems: data input, preprocessing, architecture design, graphic design, and inference engine modules. One of the challenges in this research was to identify the dominant and the optimum number of independent variables. The variables include porosity, permeability, water saturation, depth, area, net thickness, gross thickness, formation volume factor, pressure, viscosity, API gravity, number of wells in initial water flooding, number of wells for primary recovery, number of infill wells over the initial water flooding, PRUR, IWUR, and IDUR. Multivariate principal component analysis is used to identify the dominant and the optimum number of independent variables. We compared the results from neural network models with the non-parametric approach. The advantage of the non-parametric regression is that it is easy to use. The disadvantage is that it retains a large variance of forecast results for a particular data set. We also used neural network concepts to develop recovery

  15. Production-logistic system in the aspect of strategies for production planning and control and for logistic customer service

    Directory of Open Access Journals (Sweden)

    Łukasz Hadaś

    2014-09-01

    Full Text Available Background: The authors made multi-dimensional review of production and logistic strategies in order to prove their coherence in shaping internal and external supply chain. The paper is concluded with definition of production-logistic system as an object of modeling in transformation of business systems of manufacturing companies. Material and methods: The paper is based on analysis of state of the art presented in the literature on the subject of production and logistics strategies. Publications of key importance were selected to identify genesis and basic assumptions of strategies and their functioning. Comparative synthesis of logistic and production strategies identified is developed with respect to authors' experience in application of predefined tools and methods characteristic for strategies identified. Results: The result of the work conducted is consolidation of production and logistic strategies according to multi-variant customer service and original definition of production and logistic system. Conclusions: Production system and logistic system can and should be treated as equal elements in context of material flows management in internal and external supply chains. Such approach enables modeling of both systems as coherent elements realizing selected strategy of customer service.     

  16. Transient multivariable sensor evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Vilim, Richard B.; Heifetz, Alexander

    2017-02-21

    A method and system for performing transient multivariable sensor evaluation. The method and system includes a computer system for identifying a model form, providing training measurement data, generating a basis vector, monitoring system data from sensor, loading the system data in a non-transient memory, performing an estimation to provide desired data and comparing the system data to the desired data and outputting an alarm for a defective sensor.

  17. Logistic discriminant parametric mapping: a novel method for the pixel-based differential diagnosis of Parkinson's disease

    International Nuclear Information System (INIS)

    Acton, P.D.; Mozley, P.D.; Kung, H.F.; Pennsylvania Univ., Philadelphia, PA

    1999-01-01

    Positron emission tomography (PET) and single-photon emission tomography (SPET) imaging of the dopaminergic system is a powerful tool for distinguishing groups of patients with neurodegenerative disorders, such as Parkinson's disease (PD). However, the differential diagnosis of individual subjects presenting early in the progress of the disease is much more difficult, particularly using region-of-interest analysis where small localized differences between subjects are diluted. In this paper we present a novel pixel-based technique using logistic discriminant analysis to distinguish between a group of PD patients and age-matched healthy controls. Simulated images of an anthropomorphic head phantom were used to test the sensitivity of the technique to striatal lesions of known size. The methodology was applied to real clinical SPET images of binding of technetium-99m labelled TRODAT-1 to dopamine transporters in PD patients (n=42) and age-matched controls (n=23). The discriminant model was trained on a subset (n=17) of patients for whom the diagnosis was unequivocal. Logistic discriminant parametric maps were obtained for all subjects, showing the probability distribution of pixels classified as being consistent with PD. The probability maps were corrected for correlated multiple comparisons assuming an isotropic Gaussian point spread function. Simulated lesion sizes measured by logistic discriminant parametric mapping (LDPM) gave strong correlations with the known data (r 2 =0.985, P<0.001). LDPM correctly classified all PD patients (sensitivity 100%) and only misclassified one control (specificity 95%). All patients who had equivocal clinical symptoms associated with early onset PD (n=4) were correctly assigned to the patient group. Statistical parametric mapping (SPM) had a sensitivity of only 24% on the same patient group. LDPM is a powerful pixel-based tool for the differential diagnosis of patients with PD and healthy controls. The diagnosis of disease even

  18. Rainfall induced landslide susceptibility mapping using weight-of-evidence, linear and quadratic discriminant and logistic model tree method

    Science.gov (United States)

    Hong, H.; Zhu, A. X.

    2017-12-01

    Climate change is a common phenomenon and it is very serious all over the world. The intensification of rainfall extremes with climate change is of key importance to society and then it may induce a large impact through landslides. This paper presents GIS-based new ensemble data mining techniques that weight-of-evidence, logistic model tree, linear and quadratic discriminant for landslide spatial modelling. This research was applied in Anfu County, which is a landslide-prone area in Jiangxi Province, China. According to a literature review and research the study area, we select the landslide influencing factor and their maps were digitized in a GIS environment. These landslide influencing factors are the altitude, plan curvature, profile curvature, slope degree, slope aspect, topographic wetness index (TWI), Stream Power Index (SPI), Topographic Wetness Index (SPI), distance to faults, distance to rivers, distance to roads, soil, lithology, normalized difference vegetation index and land use. According to historical information of individual landslide events, interpretation of the aerial photographs, and field surveys supported by the government of Jiangxi Meteorological Bureau of China, 367 landslides were identified in the study area. The landslide locations were divided into two subsets, namely, training and validating (70/30), based on a random selection scheme. In this research, Pearson's correlation was used for the evaluation of the relationship between the landslides and influencing factors. In the next step, three data mining techniques combined with the weight-of-evidence, logistic model tree, linear and quadratic discriminant, were used for the landslide spatial modelling and its zonation. Finally, the landslide susceptibility maps produced by the mentioned models were evaluated by the ROC curve. The results showed that the area under the curve (AUC) of all of the models was > 0.80. At the same time, the highest AUC value was for the linear and quadratic

  19. Simultaneous determination of some antiprotozoal drugs in different combined dosage forms by mean centering of ratio spectra and multivariate calibration with model updating methods

    Directory of Open Access Journals (Sweden)

    Abdelaleem Eglal A

    2012-04-01

    Full Text Available Abstract Background Metronidazole (MET and Diloxanide Furoate (DF, act as antiprotozoal drugs, in their ternary mixtures with Mebeverine HCl (MEH, an effective antispasmodic drug. This work concerns with the development and validation of two simple, specific and cost effective methods mainly for simultaneous determination of the proposed ternary mixture. In addition, the developed multivariate calibration model has been updated to determine Metronidazole benzoate (METB in its binary mixture with DF in Dimetrol® suspension. Results Method (I is the mean centering of ratio spectra spectrophotometric method (MCR that depends on using the mean centered ratio spectra in two successive steps that eliminates the derivative steps and therefore the signal to noise ratio is enhanced. The developed MCR method has been successfully applied for determination of MET, DF and MEH in different laboratory prepared mixtures and in tablets. Method (II is the partial least square (PLS multivariate calibration method that has been optimized for determination of MET, DF and MEH in Dimetrol ® tablets and by updating the developed model, it has been successfully used for prediction of binary mixtures of DF and Metronidazole Benzoate ester (METB in Dimetrol ® suspension with good accuracy and precision without reconstruction of the calibration set. Conclusion The developed methods have been validated; accuracy, precision and specificity were found to be within the acceptable limits. Moreover results obtained by the suggested methods showed no significant difference when compared with those obtained by reported methods. Graphical Abstract

  20. Intelligent multivariate process supervision

    International Nuclear Information System (INIS)

    Visuri, Pertti.

    1986-01-01

    This thesis addresses the difficulties encountered in managing large amounts of data in supervisory control of complex systems. Some previous alarm and disturbance analysis concepts are reviewed and a method for improving the supervision of complex systems is presented. The method, called multivariate supervision, is based on adding low level intelligence to the process control system. By using several measured variables linked together by means of deductive logic, the system can take into account the overall state of the supervised system. Thus, it can present to the operators fewer messages with higher information content than the conventional control systems which are based on independent processing of each variable. In addition, the multivariate method contains a special information presentation concept for improving the man-machine interface. (author)

  1. Correlating phospholipid fatty acids (PLFA) in a landfill leachate polluted aquifer with biogeochemical factors by multivariate statistical methods

    DEFF Research Database (Denmark)

    Ludvigsen, Liselotte; Albrechtsen, Hans-Jørgen; Rootzén, Helle

    1997-01-01

    Different multivariate statistical analyses were applied to phospholipid fatty acids representing the biomass composition and to different biogeochemical parameters measured in 37 samples from a landfill contaminated aquifer at Grindsted Landfill (Denmark). Principal component analysis...... and correspondence analysis were used to identify groups of samples showing similar patterns with respect to biogeochemical variables and phospholipid fatty acid composition. The principal component analysis revealed that for the biogeochemical parameters the first principal component was linked to the pollution...... was used to allocate samples of phospholipid fatty acids into predefined classes. A large percentages of samples were classified correctly when discriminating samples into groups of dissolved organic carbon and specific conductivity, indicating that the biomass is highly influenced by the pollution...

  2. Understanding the groundwater dynamics in the Southern Rift Valley Lakes Basin (Ethiopia). Multivariate statistical analysis method, oxygen (δ 18O) and deuterium (δ 2H)

    International Nuclear Information System (INIS)

    Girum Admasu Nadew; Zebene Lakew Tefera

    2013-01-01

    Multivariate statistical analysis is very important to classify waters of different hydrochemical groups. Statistical techniques, such as cluster analysis, can provide a powerful tool for analyzing water chemistry data. This method is used to test water quality data and determine if samples can be grouped into distinct populations that may be significant in the geologic context, as well as from a statistical point of view. Multivariate statistical analysis method is applied to the geochemical data in combination with δ 18 O and δ 2 H isotopes with the objective to understand the dynamics of groundwater using hierarchical clustering and isotope analyses. The geochemical and isotope data of the central and southern rift valley lakes have been collected and analyzed from different works. Isotope analysis shows that most springs and boreholes are recharged by July and August rainfalls. The different hydrochemical groups that resulted from the multivariate analysis are described and correlated with the geology of the area and whether it has any interaction with a system or not. (author)

  3. Multivariate statistics exercises and solutions

    CERN Document Server

    Härdle, Wolfgang Karl

    2015-01-01

    The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The last part introduces a wide variety of exercises in applied multivariate data analysis. The book demonstrates the application of simple calculus and basic multivariate methods in real life situations. It contains altogether more than 250 solved exercises which can assist a university teacher in setting up a modern multivariate analysis course. All computer-based exercises are available in the R language. All R codes and data sets may be downloaded via the quantlet download center  www.quantlet.org or via the Springer webpage. For interactive display of low-dimensional projections of a multivariate data set, we recommend GGobi.

  4. Managing Reverse Logistics or Reversing Logistics Management?

    OpenAIRE

    Brito, Marisa

    2004-01-01

    textabstractIn the past, supply chains were busy fine-tuning the logistics from raw material to the end customer. Today an increasing flow of products is going back in the chain. Thus, companies have to manage reverse logistics as well.This thesis contributes to a better understanding of reverse logistics. The thesis brings insights on reverse logistics decision-making and it lays down theoretical principles for reverse logistics as a research field.In particular it puts together a framework ...

  5. Multivariate wavelet frames

    CERN Document Server

    Skopina, Maria; Protasov, Vladimir

    2016-01-01

    This book presents a systematic study of multivariate wavelet frames with matrix dilation, in particular, orthogonal and bi-orthogonal bases, which are a special case of frames. Further, it provides algorithmic methods for the construction of dual and tight wavelet frames with a desirable approximation order, namely compactly supported wavelet frames, which are commonly required by engineers. It particularly focuses on methods of constructing them. Wavelet bases and frames are actively used in numerous applications such as audio and graphic signal processing, compression and transmission of information. They are especially useful in image recovery from incomplete observed data due to the redundancy of frame systems. The construction of multivariate wavelet frames, especially bases, with desirable properties remains a challenging problem as although a general scheme of construction is well known, its practical implementation in the multidimensional setting is difficult. Another important feature of wavelet is ...

  6. Potential application of digital image-processing method and fitted logistic model to the control of oriental fruit moths (Grapholita molesta Busck).

    Science.gov (United States)

    Zhao, Z G; Rong, E H; Li, S C; Zhang, L J; Zhang, Z W; Guo, Y Q; Ma, R Y

    2016-08-01

    Monitoring of oriental fruit moths (Grapholita molesta Busck) is a prerequisite for its control. This study introduced a digital image-processing method and logistic model for the control of oriental fruit moths. First, five triangular sex pheromone traps were installed separately within each area of 667 m2 in a peach orchard to monitor oriental fruit moths consecutively for 3 years. Next, full view images of oriental fruit moths were collected via a digital camera and then subjected to graying, separation and morphological analysis for automatic counting using MATLAB software. Afterwards, the results of automatic counting were used for fitting a logistic model to forecast the control threshold and key control period. There was a high consistency between automatic counting and manual counting (0.99, P model, oriental fruit moths had four occurrence peaks during a year, with a time-lag of 15-18 days between adult occurrence peak and the larval damage peak. Additionally, the key control period was from 28 June to 3 July each year, when the wormy fruit rate reached up to 5% and the trapping volume was approximately 10.2 per day per trap. Additionally, the key control period for the overwintering generation was 25 April. This study provides an automatic counting method and fitted logistic model with a great potential for application to the control of oriental fruit moths.

  7. A Stochastic Programming Approach with Improved Multi-Criteria Scenario-Based Solution Method for Sustainable Reverse Logistics Design of Waste Electrical and Electronic Equipment (WEEE

    Directory of Open Access Journals (Sweden)

    Hao Yu

    2016-12-01

    Full Text Available Today, the increased public concern about sustainable development and more stringent environmental regulations have become important driving forces for value recovery from end-of-life and end-of use products through reverse logistics. Waste electrical and electronic equipment (WEEE contains both valuable components that need to be recycled and hazardous substances that have to be properly treated or disposed of, so the design of a reverse logistics system for sustainable treatment of WEEE is of paramount importance. This paper presents a stochastic mixed integer programming model for designing and planning a generic multi-source, multi-echelon, capacitated, and sustainable reverse logistics network for WEEE management under uncertainty. The model takes into account both economic efficiency and environmental impacts in decision-making, and the environmental impacts are evaluated in terms of carbon emissions. A multi-criteria two-stage scenario-based solution method is employed and further developed in this study for generating the optimal solution for the stochastic optimization problem. The proposed model and solution method are validated through a numerical experiment and sensitivity analyses presented later in this paper, and an analysis of the results is also given to provide a deep managerial insight into the application of the proposed stochastic optimization model.

  8. Comprehensive analysis of Polygoni Multiflori Radix of different geographical origins using ultra-high-performance liquid chromatography fingerprints and multivariate chemometric methods

    Directory of Open Access Journals (Sweden)

    Li-Li Sun

    2018-01-01

    Full Text Available Polygoni Multiflori Radix (PMR is increasingly being used not just as a traditional herbal medicine but also as a popular functional food. In this study, multivariate chemometric methods and mass spectrometry were combined to analyze the ultra-high-performance liquid chromatograph (UPLC fingerprints of PMR from six different geographical origins. A chemometric strategy based on multivariate curve resolution–alternating least squares (MCR–ALS and three classification methods is proposed to analyze the UPLC fingerprints obtained. Common chromatographic problems, including the background contribution, baseline contribution, and peak overlap, were handled by the established MCR–ALS model. A total of 22 components were resolved. Moreover, relative species concentrations were obtained from the MCR–ALS model, which was used for multivariate classification analysis. Principal component analysis (PCA and Ward's method have been applied to classify 72 PMR samples from six different geographical regions. The PCA score plot showed that the PMR samples fell into four clusters, which related to the geographical location and climate of the source areas. The results were then corroborated by Ward's method. In addition, according to the variance-weighted distance between cluster centers obtained from Ward's method, five components were identified as the most significant variables (chemical markers for cluster discrimination. A counter-propagation artificial neural network has been applied to confirm and predict the effects of chemical markers on different samples. Finally, the five chemical markers were identified by UPLC–quadrupole time-of-flight mass spectrometer. Components 3, 12, 16, 18, and 19 were identified as 2,3,5,4′-tetrahydroxy-stilbene-2-O-β-d-glucoside, emodin-8-O-β-d-glucopyranoside, emodin-8-O-(6′-O-acetyl-β-d-glucopyranoside, emodin, and physcion, respectively. In conclusion, the proposed method can be applied for the

  9. In-plant logistics optimalization

    OpenAIRE

    Maroušek, Jan

    2008-01-01

    In a theoretical part of this work there is introduced a general view on logistics and its development, than a view on creating value for customer, basics of lean production, lean thinking and following methods as Six Sigma and Value Stream Mapping. At the end of the theoretical part there is mentioned outsourcing of logistics services and view on relationship between logistics provider and a client. In a practical part there is introduced a project of in-plant logistics optimalization in a f...

  10. Mineralization model for Chahar Gonbad copper-gold deposit (Sirjan, using mineralogical, alteration and geochemical data and multivariate statistical methods

    Directory of Open Access Journals (Sweden)

    Seayed Jaber Yousefi

    2012-04-01

    Full Text Available The study area is located in southeastern Iran, about 110 km southwest of Kerman. Geologically, the area is composed of ophiolitic rocks, volcanic rocks, intrusive bodies and sedimentary rocks. Vein mineralization within andesite, andesitic basalt, andesitic tuffs occurred along the Chahar Gonbad fault. Sulfide mineralization in the ore deposit has taken place as dissemination, veins and veinlets in which pyrite and chalcopyrite are the most important ores. In this area, argillic, phyllic and propylitic alteration types are observed. Such elements as Au, Bi, Cu, S and Se are more enriched than others and the enrichment factors for these elements in comparison with background concentration are 321, 503, 393, 703 and 208, and with respect to Clark concentration are 401, 222, 532, 101 and 156, respectively. According to multivariate analysis, three major mineralization phases are recognized in the deposit. During the first phase, hydrothermal calcite veins are enriched in As, Cd, Pb, Zn and Ca, the second phase is manifested by the enrichment of sulfide veins in Cu, Au, Ag, Bi, Fe and S and the third phase mineralization includes Ni, Mn, Se and Sb as an intermediate level between the two previous phases.

  11. Spatial and temporal variation of water quality of a segment of Marikina River using multivariate statistical methods.

    Science.gov (United States)

    Chounlamany, Vanseng; Tanchuling, Maria Antonia; Inoue, Takanobu

    2017-09-01

    Payatas landfill in Quezon City, Philippines, releases leachate to the Marikina River through a creek. Multivariate statistical techniques were applied to study temporal and spatial variations in water quality of a segment of the Marikina River. The data set included 12 physico-chemical parameters for five monitoring stations over a year. Cluster analysis grouped the monitoring stations into four clusters and identified January-May as dry season and June-September as wet season. Principal components analysis showed that three latent factors are responsible for the data set explaining 83% of its total variance. The chemical oxygen demand, biochemical oxygen demand, total dissolved solids, Cl - and PO 4 3- are influenced by anthropogenic impact/eutrophication pollution from point sources. Total suspended solids, turbidity and SO 4 2- are influenced by rain and soil erosion. The highest state of pollution is at the Payatas creek outfall from March to May, whereas at downstream stations it is in May. The current study indicates that the river monitoring requires only four stations, nine water quality parameters and testing over three specific months of the year. The findings of this study imply that Payatas landfill requires a proper leachate collection and treatment system to reduce its impact on the Marikina River.

  12. Multivariate methods for the analysis of complex and big data in forensic sciences. Application to age estimation in living persons.

    Science.gov (United States)

    Lefèvre, Thomas; Chariot, Patrick; Chauvin, Pierre

    2016-09-01

    Researchers handle increasingly higher dimensional datasets, with many variables to explore. Such datasets pose several problems, since they are difficult to handle and present unexpected features. As dimensionality increases, classical statistical analysis becomes inoperative. Variables can present redundancy, and the reduction of dataset dimensionality to its lowest possible value is often needed. Principal components analysis (PCA) has proven useful to reduce dimensionality but present several shortcomings. As others, forensic sciences will face the issues specific related to an evergrowing quantity of data to be integrated. Age estimation in living persons, an unsolved problem so far, could benefit from the integration of various sources of data, e.g., clinical, dental and radiological data. We present here novel multivariate techniques (nonlinear dimensionality reduction techniques, NLDR), applied to a theoretical example. Results were compared to those of PCA. NLDR techniques were then applied to clinical, dental and radiological data (13 variables) used for age estimation. The correlation dimension of these data was estimated. NLDR techniques outperformed PCA results. They showed that two living persons sharing similar characteristics may present rather different estimated ages. Moreover, data presented a very high informational redundancy, i.e., a correlation dimension of 2. NLDR techniques should be used with or preferred to PCA techniques to analyze complex and big data. Data routinely used for age estimation may not be considered suitable for this purpose. How integrating other data or approaches could improve age estimation in living persons is still uncertain. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  13. Information Logistics Research report 2

    NARCIS (Netherlands)

    Willems, A.; Hajdasinski, A.K.; Willems, J.

    2009-01-01

    The goal of this research report is to further explore the concept of Information Logistics (IL), which refers to the usage and dispatch of information and methods of logistics able to support those processes. This report is based upon 6 questions that examine IL in organizations, healthcare

  14. Models and Inference for Multivariate Spatial Extremes

    KAUST Repository

    Vettori, Sabrina

    2017-12-07

    The development of flexible and interpretable statistical methods is necessary in order to provide appropriate risk assessment measures for extreme events and natural disasters. In this thesis, we address this challenge by contributing to the developing research field of Extreme-Value Theory. We initially study the performance of existing parametric and non-parametric estimators of extremal dependence for multivariate maxima. As the dimensionality increases, non-parametric estimators are more flexible than parametric methods but present some loss in efficiency that we quantify under various scenarios. We introduce a statistical tool which imposes the required shape constraints on non-parametric estimators in high dimensions, significantly improving their performance. Furthermore, by embedding the tree-based max-stable nested logistic distribution in the Bayesian framework, we develop a statistical algorithm that identifies the most likely tree structures representing the data\\'s extremal dependence using the reversible jump Monte Carlo Markov Chain method. A mixture of these trees is then used for uncertainty assessment in prediction through Bayesian model averaging. The computational complexity of full likelihood inference is significantly decreased by deriving a recursive formula for the nested logistic model likelihood. The algorithm performance is verified through simulation experiments which also compare different likelihood procedures. Finally, we extend the nested logistic representation to the spatial framework in order to jointly model multivariate variables collected across a spatial region. This situation emerges often in environmental applications but is not often considered in the current literature. Simulation experiments show that the new class of multivariate max-stable processes is able to detect both the cross and inner spatial dependence of a number of extreme variables at a relatively low computational cost, thanks to its Bayesian hierarchical

  15. LOGISTICS OPTIMIZATION USING ONTOLOGIES

    OpenAIRE

    Hendi , Hayder; Ahmad , Adeel; Bouneffa , Mourad; Fonlupt , Cyril

    2014-01-01

    International audience; Logistics processes involve complex physical flows and integration of different elements. It is widely observed that the uncontrolled processes can decline the state of logistics. The optimization of logistic processes can support the desired growth and consistent continuity of logistics. In this paper, we present a software framework for logistic processes optimization. It primarily defines logistic ontologies and then optimize them. It intends to assist the design of...

  16. Management of Logistics Planning

    OpenAIRE

    Bjørnar Aas; Stein W. Wallace

    2010-01-01

    Logistics problems are gradually becoming more complex and a better understanding of logistics management as a subject is a key to deal with the new challenges. A core element of logistics management is logistics planning, which substitutes for low customer service levels, high waste, and the use of buffers and slacks in the execution of logistic activities. Furthermore, the availability of information and problem-solving capabilities are established as the core parts of logistics planning. B...

  17. Multivariate covariance generalized linear models

    DEFF Research Database (Denmark)

    Bonat, W. H.; Jørgensen, Bent

    2016-01-01

    are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...

  18. The Selection of Wagons for the Internal Transport of a Logistics Company: A Novel Approach Based on Rough BWM and Rough SAW Methods

    Directory of Open Access Journals (Sweden)

    Željko Stević

    2017-11-01

    Full Text Available The rationalization of logistics activities and processes is very important in the business and efficiency of every company. In this respect, transportation as a subsystem of logistics, whether internal or external, is potentially a huge area for achieving significant savings. In this paper, the emphasis is placed upon the internal transport logistics of a paper manufacturing company. It is necessary to rationalize the movement of vehicles in the company’s internal transport, that is, for the majority of the transport to be transferred to rail transport, because the company already has an industrial track installed in its premises. To do this, it is necessary to purchase at least two used wagons. The problem is formulated as a multi-criteria decision model with eight criteria and eight alternatives. The paper presents a new approach based on a combination of the Simple Additive Weighting (SAW method and rough numbers, which is used for ranking the potential solutions and selecting the most suitable one. The rough Best–Worst Method (BWM was used to determine the weight values of the criteria. The results obtained using a combination of these two methods in their rough form were verified by means of a sensitivity analysis consisting of a change in the weight criteria and comparison with the following methods in their conventional and rough forms: the Analytic Hierarchy Process (AHP, Technique for Ordering Preference by Similarity to Ideal Solution (TOPSIS and MultiAttributive Border Approximation area Comparison (MABAC. The results show very high stability of the model and ranks that are the same or similar in different scenarios.

  19. Non-linear multivariate and multiscale monitoring and signal denoising strategy using Kernel Principal Component Analysis combined with Ensemble Empirical Mode Decomposition method

    Science.gov (United States)

    Žvokelj, Matej; Zupan, Samo; Prebil, Ivan

    2011-10-01

    The article presents a novel non-linear multivariate and multiscale statistical process monitoring and signal denoising method which combines the strengths of the Kernel Principal Component Analysis (KPCA) non-linear multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD) to handle multiscale system dynamics. The proposed method which enables us to cope with complex even severe non-linear systems with a wide dynamic range was named the EEMD-based multiscale KPCA (EEMD-MSKPCA). The method is quite general in nature and could be used in different areas for various tasks even without any really deep understanding of the nature of the system under consideration. Its efficiency was first demonstrated by an illustrative example, after which the applicability for the task of bearing fault detection, diagnosis and signal denosing was tested on simulated as well as actual vibration and acoustic emission (AE) signals measured on purpose-built large-size low-speed bearing test stand. The positive results obtained indicate that the proposed EEMD-MSKPCA method provides a promising tool for tackling non-linear multiscale data which present a convolved picture of many events occupying different regions in the time-frequency plane.

  20. Multivariate methods and the search for single top-quark production in association with a $W$ boson in ATLAS

    CERN Document Server

    Kovesarki, Peter; Dingfelder, Jochen

    This thesis describes three machine learning algorithms that can be used for physics analyses. The first is a density estimator that was derived from the Green’s function identity of the Laplace operator and is capable of tagging data samples according to the signal purity. This latter task can also be performed with regression methods, and such an algorithm was implemented based on fast multi-dimensional polynomial regression. The accuracy was improved with a decision tree using smooth boundaries. Both methods apply rigorous checks against overtraining to make sure the results are drawn from statistically significant features. These two methods were applied in the search for the single top-quark production with a $W$ boson. Their separation power differ highly in favour for the regression method, mainly because it can exploit the extra information available during training. The third method is an unsupervised learning algorithm that offers finding an optimal coordinate system for a sample in the sense of m...

  1. Steganalysis using logistic regression

    Science.gov (United States)

    Lubenko, Ivans; Ker, Andrew D.

    2011-02-01

    We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.

  2. Application of multivariate statistical methods to classify archaeological pottery from Tel-Alramad site, Syria, based on x-ray fluorescence analysis

    International Nuclear Information System (INIS)

    Bakraji, E. H.

    2007-01-01

    Radioisotopic x-ray fluorescence (XRF) analysis has been utilized to determine the elemental composition of 55 archaeological pottery samples by the determination of 17 chemical elements. Fifty-four of them came from the Tel-Alramad Site in Katana town, near Damascus city, Syria, and one sample came from Brazil. The XRF results have been processed using two multivariate statistical methods, cluster and factor analysis, in order to determine similarities and correlation between the selected samples based on their elemental composition. The methodology successfully separates the samples where four distinct chemical groups were identified. (author)

  3. Multivariate methods and the search for single top-quark production in association with a W boson in ATLAS

    International Nuclear Information System (INIS)

    Koevesarki, Peter

    2012-11-01

    This thesis describes three machine learning algorithms that can be used for physics analyses. The first is a density estimator that was derived from the Green's function identity of the Laplace operator and is capable of tagging data samples according to the signal purity. This latter task can also be performed with regression methods, and such an algorithm was implemented based on fast multi-dimensional polynomial regression. The accuracy was improved with a decision tree using smooth boundaries. Both methods apply rigorous checks against overtraining to make sure the results are drawn from statistically significant features. These two methods were applied in the search for the single top-quark production with a W boson. Their separation power differ highly in favour for the regression method, mainly because it can exploit the extra information available during training. The third method is an unsupervised learning algorithm that offers finding an optimal coordinate system for a sample in the sense of maximal information entropy, which may aid future methods to model data.

  4. Linear model correction: A method for transferring a near-infrared multivariate calibration model without standard samples

    Science.gov (United States)

    Liu, Yan; Cai, Wensheng; Shao, Xueguang

    2016-12-01

    Calibration transfer is essential for practical applications of near infrared (NIR) spectroscopy because the measurements of the spectra may be performed on different instruments and the difference between the instruments must be corrected. For most of calibration transfer methods, standard samples are necessary to construct the transfer model using the spectra of the samples measured on two instruments, named as master and slave instrument, respectively. In this work, a method named as linear model correction (LMC) is proposed for calibration transfer without standard samples. The method is based on the fact that, for the samples with similar physical and chemical properties, the spectra measured on different instruments are linearly correlated. The fact makes the coefficients of the linear models constructed by the spectra measured on different instruments are similar in profile. Therefore, by using the constrained optimization method, the coefficients of the master model can be transferred into that of the slave model with a few spectra measured on slave instrument. Two NIR datasets of corn and plant leaf samples measured with different instruments are used to test the performance of the method. The results show that, for both the datasets, the spectra can be correctly predicted using the transferred partial least squares (PLS) models. Because standard samples are not necessary in the method, it may be more useful in practical uses.

  5. Multivariate methods and the search for single top-quark production in association with a W boson in ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Koevesarki, Peter

    2012-11-15

    This thesis describes three machine learning algorithms that can be used for physics analyses. The first is a density estimator that was derived from the Green's function identity of the Laplace operator and is capable of tagging data samples according to the signal purity. This latter task can also be performed with regression methods, and such an algorithm was implemented based on fast multi-dimensional polynomial regression. The accuracy was improved with a decision tree using smooth boundaries. Both methods apply rigorous checks against overtraining to make sure the results are drawn from statistically significant features. These two methods were applied in the search for the single top-quark production with a W boson. Their separation power differ highly in favour for the regression method, mainly because it can exploit the extra information available during training. The third method is an unsupervised learning algorithm that offers finding an optimal coordinate system for a sample in the sense of maximal information entropy, which may aid future methods to model data.

  6. Logistic innovations in transport

    Directory of Open Access Journals (Sweden)

    Mirosław Antonowicz

    2014-03-01

    Full Text Available Introduction: The article discusses the issue of logistic innovations in transport. The essentials of logistic innovations in transport together with some examples of specific innovations are presented. The role of the client's needs in transport innovations is indicated. The most vital postulates affecting the innovativeness of shipping companies and derived from the author's experience as well as scholarly publications, are time, safety, reliability as well as comprehensiveness of service offer. Following the analysis of the issue, and on the grounds of Kaizen's and Lean's method, the concept of continuous innovations is suggested as very useful for the development of transport. The potential of clusters as the source of logistic innovations in transport is emphasised. Methods: The discussion of the issue was preceded by the author's analysis of written sources on innovativeness, the evaluation of ratings of innovativeness as well as the analysis of rewarded innovative solutions in transport subsequent to the businesses participation in the programme of innovative solutions in transport. The role of innovation practical business operations is argued following the analysis of some strategic documents such as: 2011 White Paper and the Strategy for the Development of Transport by 2020 adopted by the Polish government in 2013. Aim: The aim of the article is to present the role and significance of the issue of logistic innovations in transport and to cite instances of practical solutions implemented by shipping companies, the solutions which resulted in measurable effects. Following the author's observation of the instances of innovative solutions as well as his analysis of the ratings of innovativeness, the article aims to present the conclusions as for the specific kinds of activities which are indispensable to foster innovativeness in transport. Conclusions: The conclusions derived from the author's analyses and observations show that logistic

  7. Logistic regression models

    CERN Document Server

    Hilbe, Joseph M

    2009-01-01

    This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

  8. Logistic chain modelling

    NARCIS (Netherlands)

    Slats, P.A.; Bhola, B.; Evers, J.J.M.; Dijkhuizen, G.

    1995-01-01

    Logistic chain modelling is very important in improving the overall performance of the total logistic chain. Logistic models provide support for a large range of applications, such as analysing bottlenecks, improving customer service, configuring new logistic chains and adapting existing chains to

  9. Managing Reverse Logistics or Reversing Logistics Management?

    NARCIS (Netherlands)

    M.P. de Brito (Marisa)

    2004-01-01

    textabstractIn the past, supply chains were busy fine-tuning the logistics from raw material to the end customer. Today an increasing flow of products is going back in the chain. Thus, companies have to manage reverse logistics as well.This thesis contributes to a better understanding of reverse

  10. Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)

    Science.gov (United States)

    Ozdemir, Adnan

    2011-07-01

    SummaryThe purpose of this study is to produce a groundwater spring potential map of the Sultan Mountains in central Turkey, based on a logistic regression method within a Geographic Information System (GIS) environment. Using field surveys, the locations of the springs (440 springs) were determined in the study area. In this study, 17 spring-related factors were used in the analysis: geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transport capacity index, distance to drainage, distance to fault, drainage density, and fault density map. The coefficients of the predictor variables were estimated using binary logistic regression analysis and were used to calculate the groundwater spring potential for the entire study area. The accuracy of the final spring potential map was evaluated based on the observed springs. The accuracy of the model was evaluated by calculating the relative operating characteristics. The area value of the relative operating characteristic curve model was found to be 0.82. These results indicate that the model is a good estimator of the spring potential in the study area. The spring potential map shows that the areas of very low, low, moderate and high groundwater spring potential classes are 105.586 km 2 (28.99%), 74.271 km 2 (19.906%), 101.203 km 2 (27.14%), and 90.05 km 2 (24.671%), respectively. The interpretations of the potential map showed that stream power index, relative permeability of lithologies, geology, elevation, aspect, wetness index, plan curvature, and drainage density play major roles in spring occurrence and distribution in the Sultan Mountains. The logistic regression approach has not yet been used to delineate groundwater potential zones. In this study, the logistic regression method was used to locate potential zones for groundwater springs in the Sultan Mountains. The evolved model

  11. Application of reflectance spectroscopies (FTIR-ATR & FT-NIR) coupled with multivariate methods for robust in vivo detection of begomovirus infection in papaya leaves

    Science.gov (United States)

    Haq, Quazi M. I.; Mabood, Fazal; Naureen, Zakira; Al-Harrasi, Ahmed; Gilani, Sayed A.; Hussain, Javid; Jabeen, Farah; Khan, Ajmal; Al-Sabari, Ruqaya S. M.; Al-khanbashi, Fatema H. S.; Al-Fahdi, Amira A. M.; Al-Zaabi, Ahoud K. A.; Al-Shuraiqi, Fatma A. M.; Al-Bahaisi, Iman M.

    2018-06-01

    Nucleic acid & serology based methods have revolutionized plant disease detection, however, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic infection, in addition, they need at least 1-2 days for sample harvesting, processing, and analysis. In this study, two reflectance spectroscopies i.e. Near Infrared reflectance spectroscopy (NIR) and Fourier-Transform-Infrared spectroscopy with Attenuated Total Reflection (FT-IR, ATR) coupled with multivariate exploratory methods like Principle Component Analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been deployed to detect begomovirus infection in papaya leaves. The application of those techniques demonstrates that they are very useful for robust in vivo detection of plant begomovirus infection. These methods are simple, sensitive, reproducible, precise, and do not require any lengthy samples preparation procedures.

  12. Application of reflectance spectroscopies (FTIR-ATR & FT-NIR) coupled with multivariate methods for robust in vivo detection of begomovirus infection in papaya leaves.

    Science.gov (United States)

    Haq, Quazi M I; Mabood, Fazal; Naureen, Zakira; Al-Harrasi, Ahmed; Gilani, Sayed A; Hussain, Javid; Jabeen, Farah; Khan, Ajmal; Al-Sabari, Ruqaya S M; Al-Khanbashi, Fatema H S; Al-Fahdi, Amira A M; Al-Zaabi, Ahoud K A; Al-Shuraiqi, Fatma A M; Al-Bahaisi, Iman M

    2018-06-05

    Nucleic acid & serology based methods have revolutionized plant disease detection, however, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic infection, in addition, they need at least 1-2days for sample harvesting, processing, and analysis. In this study, two reflectance spectroscopies i.e. Near Infrared reflectance spectroscopy (NIR) and Fourier-Transform-Infrared spectroscopy with Attenuated Total Reflection (FT-IR, ATR) coupled with multivariate exploratory methods like Principle Component Analysis (PCA) and Partial least square discriminant analysis (PLS-DA) have been deployed to detect begomovirus infection in papaya leaves. The application of those techniques demonstrates that they are very useful for robust in vivo detection of plant begomovirus infection. These methods are simple, sensitive, reproducible, precise, and do not require any lengthy samples preparation procedures. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. Regional collaborations and indigenous innovation capabilities in China: A multivariate method for the analysis of regional innovation systems

    OpenAIRE

    Zhao, S.L.; Cacciolatti, L.; Lee, Soo Hee; Song, W.

    2014-01-01

    In this study we analyse the emerging patterns of regional collaboration for innovation projects in China, using official government statistics of 30 Chinese regions. We propose the use of Ordinal Multidimensional Scaling and Cluster analysis as a robust method to study regional innovation systems. Our results show that regional collaborations amongst organisations can be categorised by means of eight dimensions: public versus private organisational mindset; public versus private resources; i...

  14. SEPARATION PHENOMENA LOGISTIC REGRESSION

    Directory of Open Access Journals (Sweden)

    Ikaro Daniel de Carvalho Barreto

    2014-03-01

    Full Text Available This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score. It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.

  15. Fungible weights in logistic regression.

    Science.gov (United States)

    Jones, Jeff A; Waller, Niels G

    2016-06-01

    In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  16. Prediction of gas chromatography/electron capture detector retention times of chlorinated pesticides, herbicides, and organohalides by multivariate chemometrics methods

    International Nuclear Information System (INIS)

    Ghasemi, Jahanbakhsh; Asadpour, Saeid; Abdolmaleki, Azizeh

    2007-01-01

    A quantitative structure-retention relationship (QSRR) study, has been carried out on the gas chromatograph/electron capture detector (GC/ECD) system retention times (t R s) of 38 diverse chlorinated pesticides, herbicides, and organohalides by using molecular structural descriptors. Modeling of retention times of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR) and partial least squares (PLS) regression. The stepwise regression using SPSS was used for the selection of the variables that resulted in the best-fitted models. Appropriate models with low standard errors and high correlation coefficients were obtained. Three types of molecular descriptors including electronic, steric and thermodynamic were used to develop a quantitative relationship between the retention times and structural properties. MLR and PLS analysis has been carried out to derive the best QSRR models. After variables selection, MLR and PLS methods used with leave-one-out cross validation for building the regression models. The predictive quality of the QSRR models were tested for an external prediction set of 12 compounds randomly chosen from 38 compounds. The PLS regression method was used to model the structure-retention relationships, more accurately. However, the results surprisingly showed more or less the same quality for MLR and PLS modeling according to squared regression coefficients R 2 which were 0.951 and 0.948 for MLR and PLS, respectively

  17. A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey

    Science.gov (United States)

    Ozdemir, Adnan; Altural, Tolga

    2013-03-01

    This study evaluated and compared landslide susceptibility maps produced with three different methods, frequency ratio, weights of evidence, and logistic regression, by using validation datasets. The field surveys performed as part of this investigation mapped the locations of 90 landslides that had been identified in the Sultan Mountains of south-western Turkey. The landslide influence parameters used for this study are geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transportation capacity index, distance to drainage, distance to fault, drainage density, fault density, and spring density maps. The relationships between landslide distributions and these parameters were analysed using the three methods, and the results of these methods were then used to calculate the landslide susceptibility of the entire study area. The accuracy of the final landslide susceptibility maps was evaluated based on the landslides observed during the fieldwork, and the accuracy of the models was evaluated by calculating each model's relative operating characteristic curve. The predictive capability of each model was determined from the area under the relative operating characteristic curve and the areas under the curves obtained using the frequency ratio, logistic regression, and weights of evidence methods are 0.976, 0.952, and 0.937, respectively. These results indicate that the frequency ratio and weights of evidence models are relatively good estimators of landslide susceptibility in the study area. Specifically, the results of the correlation analysis show a high correlation between the frequency ratio and weights of evidence results, and the frequency ratio and logistic regression methods exhibit correlation coefficients of 0.771 and 0.727, respectively. The frequency ratio model is simple, and its input, calculation and output processes are

  18. Multivariate optimization of an analytical method for the analysis of dog and cat foods by ICP OES.

    Science.gov (United States)

    da Costa, Silvânio Silvério Lopes; Pereira, Ana Cristina Lima; Passos, Elisangela Andrade; Alves, José do Patrocínio Hora; Garcia, Carlos Alexandre Borges; Araujo, Rennan Geovanny Oliveira

    2013-04-15

    Experimental design methodology was used to optimize an analytical method for determination of the mineral element composition (Al, Ca, Cd, Cr, Cu, Ba, Fe, K, Mg, Mn, P, S, Sr and Zn) of dog and cat foods. Two-level full factorial design was applied to define the optimal proportions of the reagents used for microwave-assisted sample digestion (2.0 mol L(-1) HNO3 and 6% m/v H2O2). A three-level factorial design for two variables was used to optimize the operational conditions of the inductively coupled plasma optical emission spectrometer, employed for analysis of the extracts. A radiofrequency power of 1.2 kW and a nebulizer argon flow of 1.0 L min(-1) were selected. The limits of quantification (LOQ) were between 0.03 μg g(-1) (Cr, 267.716 nm) and 87 μg g(-1) (Ca, 373.690 nm). The trueness of the optimized method was evaluated by analysis of five certified reference materials (CRMs): wheat flour (NIST 1567a), bovine liver (NIST 1577), peach leaves (NIST 1547), oyster tissue (NIST 1566b), and fish protein (DORM-3). The recovery values obtained for the CRMs were between 80 ± 4% (Cr) and 117 ± 5% (Cd), with relative standard deviations (RSDs) better than 5%, demonstrating that the proposed method offered good trueness and precision. Ten samples of pet food (five each of cat and dog food) were acquired at supermarkets in Aracaju city (Sergipe State, Brazil). Concentrations in the dog food ranged between 7.1 mg kg(-1) (Ba) and 2.7 g kg(-1) (Ca), while for cat food the values were between 3.7 mg kg(-1) (Ba) and 3.0 g kg(-1) (Ca). The concentrations of Ca, K, Mg, P, Cu, Fe, Mn, and Zn in the food were compared with the guidelines of the United States' Association of American Feed Control Officials (AAFCO) and the Brazilian Ministry of Agriculture, Livestock, and Food Supply (Ministério da Agricultura, Pecuária e Abastecimento-MAPA). Copyright © 2013 Elsevier B.V. All rights reserved.

  19. A kernel version of multivariate alteration detection

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

    2013-01-01

    Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations.......Based on the established methods kernel canonical correlation analysis and multivariate alteration detection we introduce a kernel version of multivariate alteration detection. A case study with SPOT HRV data shows that the kMAD variates focus on extreme change observations....

  20. Introduction to multivariate discrimination

    Science.gov (United States)

    Kégl, Balázs

    2013-07-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyperparameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  1. Introduction to multivariate discrimination

    International Nuclear Information System (INIS)

    Kegl, B.

    2013-01-01

    Multivariate discrimination or classification is one of the best-studied problem in machine learning, with a plethora of well-tested and well-performing algorithms. There are also several good general textbooks [1-9] on the subject written to an average engineering, computer science, or statistics graduate student; most of them are also accessible for an average physics student with some background on computer science and statistics. Hence, instead of writing a generic introduction, we concentrate here on relating the subject to a practitioner experimental physicist. After a short introduction on the basic setup (Section 1) we delve into the practical issues of complexity regularization, model selection, and hyper-parameter optimization (Section 2), since it is this step that makes high-complexity non-parametric fitting so different from low-dimensional parametric fitting. To emphasize that this issue is not restricted to classification, we illustrate the concept on a low-dimensional but non-parametric regression example (Section 2.1). Section 3 describes the common algorithmic-statistical formal framework that unifies the main families of multivariate classification algorithms. We explain here the large-margin principle that partly explains why these algorithms work. Section 4 is devoted to the description of the three main (families of) classification algorithms, neural networks, the support vector machine, and AdaBoost. We do not go into the algorithmic details; the goal is to give an overview on the form of the functions these methods learn and on the objective functions they optimize. Besides their technical description, we also make an attempt to put these algorithm into a socio-historical context. We then briefly describe some rather heterogeneous applications to illustrate the pattern recognition pipeline and to show how widespread the use of these methods is (Section 5). We conclude the chapter with three essentially open research problems that are either

  2. Study on the Method of Grass Yield Model in the Source Region of Three Rivers with Multivariate Data

    International Nuclear Information System (INIS)

    You, Haoyan; Luo, Chengfeng; Liu, Zhengjun; Wang, Jiao

    2014-01-01

    This paper uses remote sensing and GIS technology to analyse the Source Region of Three Rivers (SRTR) to establish a grass yield estimation model during 2010 with remote sensing data, meteorological data, grassland type data and ground measured data. Analysis of the correlation between ground measured data, vegetation index based HJ-1A/B satellite data, meteorological data and grassland type data were used to establish the grass yield model. The grass yield model was studied by several statistical methods, such as multiple linear regression and Geographically Weighted Regression (GWR). The model's precision was validated. Finally, the best model to estimate the grass yield of Maduo County in SRTR was contrasted with the TM degraded grassland interpretation image of Maduo County from 2009. The result shows that: (1) Comparing with the multiple linear regression model, the GWR model gave a much better fitting result with the quality of fit increasing significantly from less than 0.3 to more than 0.8; (2) The most sensitive factors affecting the grass yield in SRTR were precipitation from May to August and drought index from May to August. From calculation of the five vegetation indices, MSAVI fitted the best; (3) The Maduo County grass yield estimated by the optimal model was consistent with the TM degraded grassland interpretation image, the spatial distribution of grass yield in Maduo County for 2010 showed a ''high south and low north'' pattern

  3. Likelihood estimators for multivariate extremes

    KAUST Repository

    Huser, Raphaë l; Davison, Anthony C.; Genton, Marc G.

    2015-01-01

    The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.

  4. Likelihood estimators for multivariate extremes

    KAUST Repository

    Huser, Raphaël

    2015-11-17

    The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.

  5. Using the expected detection delay to assess the performance of different multivariate statistical process monitoring methods for multiplicative and drift faults.

    Science.gov (United States)

    Zhang, Kai; Shardt, Yuri A W; Chen, Zhiwen; Peng, Kaixiang

    2017-03-01

    Using the expected detection delay (EDD) index to measure the performance of multivariate statistical process monitoring (MSPM) methods for constant additive faults have been recently developed. This paper, based on a statistical investigation of the T 2 - and Q-test statistics, extends the EDD index to the multiplicative and drift fault cases. As well, it is used to assess the performance of common MSPM methods that adopt these two test statistics. Based on how to use the measurement space, these methods can be divided into two groups, those which consider the complete measurement space, for example, principal component analysis-based methods, and those which only consider some subspace that reflects changes in key performance indicators, such as partial least squares-based methods. Furthermore, a generic form for them to use T 2 - and Q-test statistics are given. With the extended EDD index, the performance of these methods to detect drift and multiplicative faults is assessed using both numerical simulations and the Tennessee Eastman process. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Logistic Fuel Processor Development

    National Research Council Canada - National Science Library

    Salavani, Reza

    2004-01-01

    The Air Base Technologies Division of the Air Force Research Laboratory has developed a logistic fuel processor that removes the sulfur content of the fuel and in the process converts logistic fuel...

  7. Comparative study of the efficiency of computed univariate and multivariate methods for the estimation of the binary mixture of clotrimazole and dexamethasone using two different spectral regions

    Science.gov (United States)

    Fayez, Yasmin Mohammed; Tawakkol, Shereen Mostafa; Fahmy, Nesma Mahmoud; Lotfy, Hayam Mahmoud; Shehata, Mostafa Abdel-Aty

    2018-04-01

    Three methods of analysis are conducted that need computational procedures by the Matlab® software. The first is the univariate mean centering method which eliminates the interfering signal of the one component at a selected wave length leaving the amplitude measured to represent the component of interest only. The other two multivariate methods named PLS and PCR depend on a large number of variables that lead to extraction of the maximum amount of information required to determine the component of interest in the presence of the other. Good accurate and precise results are obtained from the three methods for determining clotrimazole in the linearity range 1-12 μg/mL and 75-550 μg/mL with dexamethasone acetate 2-20 μg/mL in synthetic mixtures and pharmaceutical formulation using two different spectral regions 205-240 nm and 233-278 nm. The results obtained are compared statistically to each other and to the official methods.

  8. Development of achiral and chiral 2D HPLC methods for analysis of albendazole metabolites in microsomal fractions using multivariate analysis for the in vitro metabolism.

    Science.gov (United States)

    Belaz, Kátia Roberta A; Pereira-Filho, Edenir Rodrigues; Oliveira, Regina V

    2013-08-01

    In this work, the development of two multidimensional liquid chromatography methods coupled to a fluorescence detector is described for direct analysis of microsomal fractions obtained from rat livers. The chiral multidimensional method was then applied for the optimization of the in vitro metabolism of albendazole by experimental design. Albendazole was selected as a model drug because of its anthelmintics properties and recent potential for cancer treatment. The development of two fully automated achiral-chiral and chiral-chiral high performance liquid chromatography (HPLC) methods for the determination of albendazole (ABZ) and its metabolites albendazole sulphoxide (ABZ-SO), albendazole sulphone (ABZ-SO2) and albendazole 2-aminosulphone (ABZ-SO2NH2) in microsomal fractions are described. These methods involve the use of a phenyl (RAM-phenyl-BSA) or octyl (RAM-C8-BSA) restricted access media bovine serum albumin column for the sample clean-up, followed by an achiral phenyl column (15.0×0.46cmI.D.) or a chiral amylose tris(3,5-dimethylphenylcarbamate) column (15.0×0.46cmI.D.). The chiral 2D HPLC method was applied to the development of a compromise condition for the in vitro metabolism of ABZ by means of experimental design involving multivariate analysis. Copyright © 2013 Elsevier B.V. All rights reserved.

  9. Reverse logistics - a framework

    NARCIS (Netherlands)

    M.P. de Brito (Marisa); R. Dekker (Rommert)

    2002-01-01

    textabstractIn this paper we define and compare Reverse Logistics definitions. We start by giving an understanding framework of Reverse Logistics: the why-what-how. By this means, we put in context the driving forces for Reverse Logistics, a typology of return reasons, a classification of

  10. Logistics strategic decisions

    NARCIS (Netherlands)

    Steadie Seifi, M.; Farahani, R.Z.; Rezapour, S.; Kardar, L.

    2011-01-01

    Logistics has an important economic role because it swallows the biggest part of capital and supports the flow and movement of many economic transactions. Therefore, designing the best logistics strategies is vital. In this chapter, we take a look at different kinds of logistics decisions,

  11. Toward sustainable logistics

    NARCIS (Netherlands)

    Soysal, Mehmet; Bloemhof-Ruwaard, Jacqueline M.

    2017-01-01

    The fast evolution of sustainability leads to the development of a new fast-growing concept called sustainable logistics management. This research addresses recent business trends and challenges in logistics and their implications for sustainable logistics management. Additionally, we discuss policy

  12. Toward sustainable logistics

    NARCIS (Netherlands)

    Soysal, Mehmet; Bloemhof-Ruwaard, Jacqueline M.

    2018-01-01

    The fast evolution of sustainability leads to the development of a new fast-growing concept called sustainable logistics management. This research addresses recent business trends and challenges in logistics and their implications for sustainable logistics management. Additionally, we discuss policy

  13. The Relationship between Logistics Sophistication and Drivers of the Outsourcing of Logistics Activities

    Directory of Open Access Journals (Sweden)

    Peter Wanke

    2008-10-01

    Full Text Available A strong link has been established between operational excellence and the degree of sophistication of logistics organization, a function of factors such as performance monitoring, investment in Information Technology [IT] and the formalization of logistics organization, as proposed in the Bowersox, Daugherty, Dröge, Germain and Rogers (1992 Leading Edge model. At the same time, shippers have been increasingly outsourcing their logistics activities to third party providers. This paper, based on a survey with large Brazilian shippers, addresses a gap in the literature by investigating the relationship between dimensions of logistics organization sophistication and drivers of logistics outsourcing. To this end, the dimensions behind the logistics sophistication construct were first investigated. Results from factor analysis led to the identification of six dimensions of logistics sophistication. By means of multivariate logistical regression analyses it was possible to relate some of these dimensions, such as the formalization of the logistics organization, to certain drivers of the outsourcing of logistics activities of Brazilian shippers, such as cost savings. These results indicate the possibility of segmenting shippers according to characteristics of their logistics organization, which may be particularly useful to logistics service providers.

  14. Multivariate Statistical Process Control

    DEFF Research Database (Denmark)

    Kulahci, Murat

    2013-01-01

    As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...... amount of cross correlation, practitioners are often recommended to use latent structures methods such as Principal Component Analysis to summarize the data in only a few linear combinations of the original variables that capture most of the variation in the data. Applications of these control charts...

  15. Impact of Disturbing Factors on Cooperation in Logistics Outsourcing Performance: The Empirical Model

    Directory of Open Access Journals (Sweden)

    Andreja Križman

    2010-05-01

    Full Text Available The purpose of this paper is to present the research results of a study conducted in the Slovene logistics market of conflicts and opportunism as disturbing factors while examining their impact on cooperation in logistics outsourcing performance. Relationship variables are proposed that directly or indirectly affect logistics performance and conceptualize the hypotheses based on causal linkages for the constructs. On the basis of extant literature and new argumentations that are derived from in-depth interviews of logistics experts, including providers and customers, the measurement and structural models are empirically analyzed. Existing measurement scales for the constructs are slightly modified for this analysis. Purification testing and measurement for validity and reliability are performed. Multivariate statistical methods are utilized and hypotheses are tested. The results show that conflicts have a significantly negative impact on cooperation between customers and logistics service providers (LSPs, while opportunism does not play an important role in these relationships. The observed antecedents of logistics outsourcing performance in the model account for 58.4% of the variance of the goal achievement and 36.5% of the variance of the exceeded goal. KEYWORDS: logistics outsourcing performance; logistics customer–provider relationships; conflicts and cooperation in logistics outsourcing; PLS path modelling

  16. Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

    Science.gov (United States)

    Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

    2017-07-01

    Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  17. A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression.

    Science.gov (United States)

    Delwiche, Stephen R; Reeves, James B

    2010-01-01

    In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly smoothing operations or derivatives. While such operations are often useful in reducing the number of latent variables of the actual decomposition and lowering residual error, they also run the risk of misleading the practitioner into accepting calibration equations that are poorly adapted to samples outside of the calibration. The current study developed a graphical method to examine this effect on partial least squares (PLS) regression calibrations of near-infrared (NIR) reflection spectra of ground wheat meal with two analytes, protein content and sodium dodecyl sulfate sedimentation (SDS) volume (an indicator of the quantity of the gluten proteins that contribute to strong doughs). These two properties were chosen because of their differing abilities to be modeled by NIR spectroscopy: excellent for protein content, fair for SDS sedimentation volume. To further demonstrate the potential pitfalls of preprocessing, an artificial component, a randomly generated value, was included in PLS regression trials. Savitzky-Golay (digital filter) smoothing, first-derivative, and second-derivative preprocess functions (5 to 25 centrally symmetric convolution points, derived from quadratic polynomials) were applied to PLS calibrations of 1 to 15 factors. The results demonstrated the danger of an over reliance on preprocessing when (1) the number of samples used in a multivariate calibration is low (<50), (2) the spectral response of the analyte is weak, and (3) the goodness of the calibration is based on the coefficient of determination (R(2)) rather than a term based on residual error. The graphical method has application to the evaluation of other preprocess functions and various

  18. Integrated Logistics Support Analysis of the International Space Station Alpha: An Overview of the Maintenance Time Dependent Parameter Prediction Methods Enhancement

    Science.gov (United States)

    Sepehry-Fard, F.; Coulthard, Maurice H.

    1995-01-01

    The objective of this publication is to introduce the enhancement methods for the overall reliability and maintainability methods of assessment on the International Space Station. It is essential that the process to predict the values of the maintenance time dependent variable parameters such as mean time between failure (MTBF) over time do not in themselves generate uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. Furthermore, the very acute problems of micrometeorite, Cosmic rays, flares, atomic oxygen, ionization effects, orbital plumes and all the other factors that differentiate maintainable space operations from non-maintainable space operations and/or ground operations must be accounted for. Therefore, these parameters need be subjected to a special and complex process. Since reliability and maintainability strongly depend on the operating conditions that are encountered during the entire life of the International Space Station, it is important that such conditions are accurately identified at the beginning of the logistics support requirements process. Environmental conditions which exert a strong influence on International Space Station will be discussed in this report. Concurrent (combined) space environments may be more detrimental to the reliability and maintainability of the International Space Station than the effects of a single environment. In characterizing the logistics support requirements process, the developed design/test criteria must consider both the single and/or combined environments in anticipation of providing hardware capability to withstand the hazards of the International Space Station profile. The effects of the combined environments (typical) in a matrix relationship on the International Space Station will be shown. The combinations of the environments where the total effect is more damaging than the cumulative effects of the environments acting singly, may include a

  19. Applied multivariate statistics with R

    CERN Document Server

    Zelterman, Daniel

    2015-01-01

    This book brings the power of multivariate statistics to graduate-level practitioners, making these analytical methods accessible without lengthy mathematical derivations. Using the open source, shareware program R, Professor Zelterman demonstrates the process and outcomes for a wide array of multivariate statistical applications. Chapters cover graphical displays, linear algebra, univariate, bivariate and multivariate normal distributions, factor methods, linear regression, discrimination and classification, clustering, time series models, and additional methods. Zelterman uses practical examples from diverse disciplines to welcome readers from a variety of academic specialties. Those with backgrounds in statistics will learn new methods while they review more familiar topics. Chapters include exercises, real data sets, and R implementations. The data are interesting, real-world topics, particularly from health and biology-related contexts. As an example of the approach, the text examines a sample from the B...

  20. KSC ISS Logistics Support

    Science.gov (United States)

    Tellado, Joseph

    2014-01-01

    The presentation contains a status of KSC ISS Logistics Operations. It basically presents current top level ISS Logistics tasks being conducted at KSC, current International Partner activities, hardware processing flow focussing on late Stow operations, list of KSC Logistics POC's, and a backup list of Logistics launch site services. This presentation is being given at the annual International Space Station (ISS) Multi-lateral Logistics Maintenance Control Panel meeting to be held in Turin, Italy during the week of May 13-16. The presentatiuon content doesn't contain any potential lessons learned.

  1. Total Logistic Plant Solutions

    Directory of Open Access Journals (Sweden)

    Dusan Dorcak

    2016-02-01

    Full Text Available The Total Logistics Plant Solutions, plant logistics system - TLPS, based on the philosophy of advanced control processes enables complex coordination of business processes and flows and the management and scheduling of production in the appropriate production plans and planning periods. Main attributes of TLPS is to create a comprehensive, multi-level, enterprise logistics information system, with a certain degree of intelligence, which accepts the latest science and research results in the field of production technology and logistics. Logistic model of company understands as a system of mutually transforming flows of materials, energy, information, finance, which is realized by chain activities and operations

  2. A standards-based method for compositional analysis by energy dispersive X-ray spectrometry using multivariate statistical analysis: application to multicomponent alloys.

    Science.gov (United States)

    Rathi, Monika; Ahrenkiel, S P; Carapella, J J; Wanlass, M W

    2013-02-01

    Given an unknown multicomponent alloy, and a set of standard compounds or alloys of known composition, can one improve upon popular standards-based methods for energy dispersive X-ray (EDX) spectrometry to quantify the elemental composition of the unknown specimen? A method is presented here for determining elemental composition of alloys using transmission electron microscopy-based EDX with appropriate standards. The method begins with a discrete set of related reference standards of known composition, applies multivariate statistical analysis to those spectra, and evaluates the compositions with a linear matrix algebra method to relate the spectra to elemental composition. By using associated standards, only limited assumptions about the physical origins of the EDX spectra are needed. Spectral absorption corrections can be performed by providing an estimate of the foil thickness of one or more reference standards. The technique was applied to III-V multicomponent alloy thin films: composition and foil thickness were determined for various III-V alloys. The results were then validated by comparing with X-ray diffraction and photoluminescence analysis, demonstrating accuracy of approximately 1% in atomic fraction.

  3. [Analysis on traditional Chinese medicine prescriptions treating cancer-related anorexia syndrome based on grey system theory combined with multivariate analysis method and discovery of new prescriptions].

    Science.gov (United States)

    Chen, Song-Lin; Chen, Cong; Zhu, Hui; Li, Jing; Pang, Yan

    2016-01-01

    Cancer-related anorexia syndrome (CACS) is one of the main causes for death at present as well as a syndrome seriously harming patients' quality of life, treatment effect and survival time. In current clinical researches, there are fewer reports about empirical traditional Chinese medicine(TCM) prescriptions and patent prescriptions treating CACS, and prescription rules are rarely analyzed in a systematic manner. As the hidden rules are not excavated, it is hard to have an innovative discovery and knowledge of clinical medication. In this paper, the grey screening method combined with the multivariate statistical method was used to build the ″CACS prescriptions database″. Based on the database, totally 359 prescriptions were selected, the frequency of herbs in prescription was determined, and commonly combined drugs were evolved into 4 new prescriptions for different syndromes. Prescriptions of TCM in treatment of CACS gave priority to benefiting qi for strengthening spleen, also laid emphasis on replenishing kidney essence, dispersing stagnated liver-qi and dispersing lung-qi. Moreover, interdependence and mutual promotion of yin and yang should be taken into account to reflect TCM's holism and theory for treatment based on syndrome differentiation. The grey screening method, as a valuable traditional Chinese medicine research-supporting method, can be used to subjectively and objectively analyze prescription rules; and the new prescriptions can provide reference for the clinical use of TCM for treating CACS and the drug development. Copyright© by the Chinese Pharmaceutical Association.

  4. Characterization of plasma-functionalized surfaces by means of Tof-SIMS and multivariate analysis methods; Charakterisierung von plasmafunktionalisierten Oberflaechen mittels ToF-SIMS und multivariaten Analysemethoden

    Energy Technology Data Exchange (ETDEWEB)

    Gradowski, M. von

    2006-11-13

    The basic principles and opportunities of surface characterisation of selected functionalised samples via ToF-SIMS (time-of-flight secondary ion mass spectrometry) are presented. One major focus of the project was the investigation of non-cohesive surface layers which could exhibit either domain like structure or well defined single functionalised surfaces. By means of ToF-SIMS with the ability of displaying the lateral distribution of surface fragments information on the structure and surface density of specific fragments on the investigated film can be obtained. The combination of the ToF-SIMS experiment with a multivariate algorithm (partial least squares, PLS) provides an interesting opportunity to quantitatively determine surface properties such as elemental and molecular concentrations. Due to the fact that the ToF-SIMS spectrum consist of a huge amount of intensities, a single one-dimensional correlation (e.g. CF{sub 3} fragment intensity <-{yields} CF{sub 3} concentration) would disregard the rest of the spectral information. The large number of fragment intensities in the spectrum is representative for the chemical structure of the analysed surface. Therefore, it is crucial to consider this total information for the quantification of surface properties (element concentration, water contact angle etc.). Furthermore, this method allows the determination of surface properties with a lateral resolution of a few microns only. This can be used for chemically structured surfaces which for many applications show micrometer sized surface structures. Finally, a successful application of the multivariate models is presented for samples from the biological and medical area. Human fibroblasts and pancreas cells have been cultivated on plasma functionalised surfaces in order to study the influence of the functionalisation on the cell growth. The samples have been covered by TEM grids with meshes in the {mu}m range before the plasma treatment to generate structured

  5. Mass movement susceptibility mapping - A comparison of logistic regression and Weight of evidence methods in Taounate-Ain Aicha region (Central Rif, Morocco

    Directory of Open Access Journals (Sweden)

    JEMMAH A I

    2018-01-01

    Full Text Available Taounate region is known by a high density of mass movements which cause several human and economic losses. The goal of this paper is to assess the landslide susceptibility of Taounate using the Weight of Evidence method (WofE and the Logistic Regression method (LR. Seven conditioning factors were used in this study: lithology, fault, drainage, slope, elevation, exposure and land use. Over the years, this site and its surroundings have experienced repeated landslides. For this reason, landslide susceptibility mapping is mandatory for risk prevention and land-use management. In this study, we have focused on recent large-scale mass movements. Finally, the ROC curves were established to evaluate the degree of fit of the model and to choose the best landslide susceptibility zonation. A total mass movements location were detected; 50% were randomly selected as input data for the entire process using the Spatial Data Model (SDM and the remaining locations were used for validation purposes. The obtained WofE’s landslide susceptibility map shows that high to very high susceptibility zones contain 62% of the total of inventoried landslides, while the same zones contain only 47% of landslides in the map obtained by the LR method. This landslide susceptibility map obtained is a major contribution to various urban and regional development plans under the Taounate Region National Development Program.

  6. Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

    Science.gov (United States)

    Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

    2017-05-01

    This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

  7. La aplicación de Técnicas de Ordenación Multivariadasen la Entomología Application of Multivariate ordenation methods in Entomology

    Directory of Open Access Journals (Sweden)

    Arnaldo Mangeaud

    2004-12-01

    Full Text Available Los métodos de ordenación son herramientas multivariadas muy utilizadas en la Entomología. En este foro se presenta una introducción a éstos y breves explicaciones sobre distintas Técnicas: Análisis de Componentes Principales (ACP, Análisis de Redundancia (AR, Análisis de Correspondencia. (AC, de Correspondencia Canónica (ACC y de Correspondencia Detendenciada (ACD, Análisis de Coordenadas Principales (AcoP, Análisis Factoriales (AF, Modelos de Ecuaciones Estructurales (MEE y Método de Procrustes.Ordenation methods are multivariate technics used a lot in Entomology. At this forum is presented an introduction to ordination methods and a short explanation over different technics: Principal Component Analysis (PCA, Redundancy Analysis (RA. Correspondence Analysis (CA. Canonical Correspondence Analysis (CCA. Detrended Correspondence Analysis (DCA Principal Coordinate Analysis (PcoA. Factor Analysis (FA, Structural Equation Models (SEM and Procrustes method.

  8. Logistics service management; differentiating the logistics service

    NARCIS (Netherlands)

    Veeken, van der D.J.M.; Rutten, W.G.M.M.

    1998-01-01

    In this article a model is described, which enables differentiation of the logistics service that a company offers to its customers. Differentiating this service is essential for businesses with a large variation within their customer and/or products portfolio. The model consists of four phases:

  9. Application of multivariable analysis methods to the quantitative detection of gas by tin dioxide micro-sensors; Application des methodes d'analyse multivariables a la detection quantitative de gaz par microcapteurs a base de dioxyde d'etain

    Energy Technology Data Exchange (ETDEWEB)

    Perdreau, N.

    2000-01-17

    The electric conductivity of tin dioxide depends on the temperature of the material and on the nature and environment of the surrounding gas. This work shows that the treatment by multivariable analysis methods of electric conductance signals of one sensor allows to determine concentrations of binary or ternary mixtures of ethanol (0-80 ppm), carbon monoxide (0-300 ppm) and methane (0-1000 ppm). A part of this study has consisted of the design and the implementation of an automatic testing bench allowing to acquire the electric conductance of four sensors in thermal cycle and under gaseous cycles. It has also revealed some disturbing effects (humidity,..) of the measurement. Two techniques of sensor fabrication have been used to obtain conductances (depending of temperature) distinct for each gas, reproducible for the different sensors and enough stable with time to allow the exploitation of the signals by multivariable analysis methods (tin dioxide under the form of thin layers obtained by reactive evaporation or under the form of sintered powder bars). In a last part, it has been shown that the quantitative determination of gas by the application of chemo-metry methods is possible although the relation between the electric conductances in one part and the temperatures and concentrations in another part is non linear. Moreover, the modelling with the 'Partial Least Square' method and a pretreatment allows to obtain performance data comparable to those obtained with neural networks. (O.M.)

  10. Logistics Innovation Process Revisited

    DEFF Research Database (Denmark)

    Gammelgaard, Britta; Su, Shong-Iee Ivan; Yang, Su-Lan

    2011-01-01

    Purpose – The purpose of this paper is to learn more about logistics innovation processes and their implications for the focal organization as well as the supply chain, especially suppliers. Design/methodology/approach – The empirical basis of the study is a longitudinal action research project...... that was triggered by the practical needs of new ways of handling material flows of a hospital. This approach made it possible to revisit theory on logistics innovation process. Findings – Apart from the tangible benefits reported to the case hospital, five findings can be extracted from this study: the logistics...... innovation process model may include not just customers but also suppliers; logistics innovation in buyer-supplier relations may serve as an alternative to outsourcing; logistics innovation processes are dynamic and may improve supplier partnerships; logistics innovations in the supply chain are as dependent...

  11. MODELING SNAKE MICROHABITAT FROM RADIOTELEMETRY STUDIES USING POLYTOMOUS LOGISTIC REGRESSION

    Science.gov (United States)

    Multivariate analysis of snake microhabitat has historically used techniques that were derived under assumptions of normality and common covariance structure (e.g., discriminant function analysis, MANOVA). In this study, polytomous logistic regression (PLR which does not require ...

  12. WAREOOUSE LOGISTICS MANAGEMENT

    OpenAIRE

    Drago Pupavac

    2012-01-01

    Warehouse Logistics Management involves the management of storage facilities and equipment, stock, employees and technology with the aim of efficient storage, accommodation, and distribution of goods and more importantly profitably. In conditions of economic crisis and lower inventory turns, logistics managers put emphasis on those measures as a function of storage logistics cost reductions that require minimal investment. Accordingly, the fundamental objective of this scientific paper is to ...

  13. A screening method based on UV-Visible spectroscopy and multivariate analysis to assess addition of filler juices and water to pomegranate juices.

    Science.gov (United States)

    Boggia, Raffaella; Casolino, Maria Chiara; Hysenaj, Vilma; Oliveri, Paolo; Zunin, Paola

    2013-10-15

    Consumer demand for pomegranate juice has considerably grown, during the last years, for its potential health benefits. Since it is an expensive functional food, cheaper fruit juices addition (i.e., grape and apple juices) or its simple dilution, or polyphenols subtraction are deceptively used. At present, time-consuming analyses are used to control the quality of this product. Furthermore these analyses are expensive and require well-trained analysts. Thus, the purpose of this study was to propose a high-speed and easy-to-use shortcut. Based on UV-VIS spectroscopy and chemometrics, a screening method is proposed to quickly screening some common fillers of pomegranate juice that could decrease the antiradical scavenging capacity of pure products. The analytical method was applied to laboratory prepared juices, to commercial juices and to representative experimental mixtures at different levels of water and filler juices. The outcomes were evaluated by means of multivariate exploratory analysis. The results indicate that the proposed strategy can be a useful screening tool to assess addition of filler juices and water to pomegranate juices. Copyright © 2012 Elsevier Ltd. All rights reserved.

  14. Application of a multivariate analysis method for non-target screening detection of persistent transformation products during the cork boiling wastewater treatment.

    Science.gov (United States)

    Ponce-Robles, L; Oller, I; Agüera, A; Trinidad-Lozano, M J; Yuste, F J; Malato, S; Perez-Estrada, L A

    2018-08-15

    Cork boiling wastewater is a very complex mixture of naturally occurring compounds leached and partially oxidized during the boiling cycles. The effluent generated is recalcitrant and could cause a significant environmental impact. Moreover, if this untreated industrial wastewater enters a municipal wastewater treatment plant it could hamper or reduce the efficiency of most activated sludge degradation processes. Despite the efforts to treat the cork boiling wastewater for reusing purposes, is still not well-known how safe these compounds (original compounds and oxidation by-products) will be. The purpose of this work was to apply an HPLC-high resolution mass spectrometry method and subsequent non-target screening using a multivariate analysis method (PCA), to explore relationships between samples (treatments) and spectral features (masses or compounds) that could indicate changes in formation, degradation or polarity, during coagulation/flocculation (C/F) and photo-Fenton (PhF). Although, most of the signal intensities were reduced after the treatment line, 16 and 4 new peaks were detected to be formed after C/F and PhF processes respectively. The use of this non-target approach showed to be an effective strategy to explore, classify and detect transformation products during the treatment of an unknown complex mixture. Copyright © 2018 Elsevier B.V. All rights reserved.

  15. Management and logistics

    OpenAIRE

    Jereb, Borut; Drašković, Mimo; Gorenak, Irena; Bauk, Sanja; Fošner, Maja; Rosi, Bojan; Pupavac, Drago; Topolšek, Darja; Dorokhov, Oleksandr; Kramar, Uroš; Ivanović, Željko; Sternad, Marjan; Knez, Matjaž; Mlaker Kač, Sonja; Malyaretz, Ludmila

    2018-01-01

    The scientific monograph titled Logistics and Management – selected topics is the result of a bilateral project, lasting from 2013 to 2015 and titled “Preparation of a joint scientific monograph in the field of logistics and management issued at the Faculty of Logistics in Celje and the Maritime Faculty of Kotor”. The project was managed by Professor Maja Fošner, PhD, from the Faculty of Logistics at the University of Maribor, and Professor Veselin Draskovic, PdD, from the Maritime Faculty of...

  16. Behavioral Operations in Logistics

    NARCIS (Netherlands)

    J. de Vries (Jelle)

    2016-01-01

    markdownabstractIn the world of logistics, a considerable share of all work is automated and performed by machines or robots. An examination of the existing logistics research reflects this image, since a substantial share of the studies focus on automated processes, and perfectly predictable

  17. Green Maritime Logistics

    DEFF Research Database (Denmark)

    Psaraftis, Harilaos N.

    2016-01-01

    By green maritime logistics we mean achieving an acceptable environmental performance of the maritime transport logistical supply chain while at the same time respecting traditional economic criteria. In this paper the environmental focus is on maritime emissions. Achieving such goal may involve ...

  18. Allocation algorithm for athletes group to form tactical tasks in game team sports using the methods of multivariate analysis (illustrated women Ukrainian team basketball with hearing impairments

    Directory of Open Access Journals (Sweden)

    Zh.L. Kozina

    2014-12-01

    Full Text Available Purpose : develop and prove experimentally allocation algorithm athletes in groups to form a tactical tasks in team sports game using methods of multivariate analysis. Material : The study involved 12 basketball hearing impaired 20-25 years old - female players team of Ukraine on basketball. Analyzed the results of testing and competitive activity 12 basketball players with hearing impairments - Lithuanian team players. Results : An algorithm for distribution by groups of athletes for the formation of tactical tasks. The algorithm consists of the following steps: 1 - testing of athletes; 2 - A hierarchical cluster analysis performance testing; 3 - Distribution of sportsmen groups, analysis of the characteristics of athletes, the formation of tactical tasks. Found higher rates of reaction rate at the offensive players. We pivot revealed a higher level of absolute strength. The defenders found a higher frequency of movement and jumping. Conclusions : The algorithm is the basis for determining the best options mutual combination players in the development and implementation of tactical combinations, the selection of partners when working in pairs and triples in training.

  19. Dating and classification of Syrian excavated pottery from Tell Saka Site, by means of thermoluminescence analysis, and multivariate statistical methods, based on PIXE analysis

    International Nuclear Information System (INIS)

    Bakraji, E.H.; Ahmad, M.; Salman, N.; Haloum, D.; Boutros, N.; Abboud, R.

    2011-01-01

    Thermoluminescence (TL) dating and Proton Induced X-ray Emission (PIXE) techniques have been utilized for the study of archaeological pottery fragment samples from Tell Saka Site, which is located at 25 km south east of Damascus city, Syria. Four samples were chosen randomly from the site, two from third level and two from fourth level for dating using TL technique and the results were in good agreement with the date assigned by archaeologists. Twenty-eight sherds were analyzed using PIXE technique in order to identify and characterize the elemental composition of pottery excavated from third and fourth levels, using 3 MV tandem accelerator in Damascus. The analysis provided almost 20 elements (Na, Mg, Al, Si, P, S, K, Ca, Ti, Mn, Fe, Co, Ni, Cu, Zn, Rb, Sr, Y, Zr, Nb). However, only 14 elements as follows: K, Ca, Ti, Mn, Fe, Co, Ni, Cu, Zn, Rb, Sr, Y, Zr, Nb were chosen for statistical analysis and have been processed using two multivariate statistical methods, Cluster and Factor analysis. The studied pottery were classify into two well defined groups. (author)

  20. Estrogenic compound profiles in an urbanized industry-impacted coastal bay and potential risk assessment by pollution indices and multivariative statistical methods.

    Science.gov (United States)

    Wang, Zaosheng; Li, Rui; Wu, Fengchang; Feng, Chenglian; Ye, Chun; Yan, Changzhou

    2017-01-15

    The occurrence and distribution of target estrogenic compounds in a highly urbanized industry-impacted coastal bay were investigated, and contamination profiles were evaluated by estimating total estradiol equivalents (∑EEQs) and risk quotients (RQs). Phenolic compounds were the most abundant xenoestrogens, but seldom showed contribution to the ∑EEQs. The diethylstilbestrol (DES) and 17α-ethinylestradiol (EE2) were the major contributors followed by 17β-estradiol (E2) in comparison with a slight contribution from estrone (E1) and estriol (E3). Both ∑EEQs and RQs indicated likely adverse effects posed on resident organisms. Further, multivariate statistical method comprehensively revealed pollution status by visualized factor scores and identified multiple "hotspots" of estrogenic sources, demonstrating the presence of complex pollution risk gradients inside and particularly outside of bay area. Overall, this study favors the integrative utilization of pollution indices and factor analysis as powerful tool to scientifically diagnose the pollution characterization of human-derived chemicals for better management decisions in aquatic environments. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. SIMULATION OF LOGISTICS PROCESSES

    Directory of Open Access Journals (Sweden)

    Yu. Taranenko

    2016-08-01

    Full Text Available The article deals with the theoretical basis of the simulation. The study shows the simulation of logistic processes in industrial countries is an integral part of many economic projects aimed at the creation or improvement of logistics systems. The paper was used model Beer Game for management of logistics processes in the enterprise. The simulation model implements in AnyLogic package. AnyLogic product allows us to consider the logistics processes as an integrated system, which allows reaching better solutions. Logistics process management involves pooling the sales market, production and distribution to ensure the temporal level of customer service at the lowest cost overall. This made it possible to conduct experiments and to determine the optimal size of the warehouse at the lowest cost.

  2. Logistics and logistics support in crisis management and citizen protection

    OpenAIRE

    HOLEJŠOVSKÝ, Jan

    2010-01-01

    ABSTRAKT LOGISTICS AND LOGISTICS SUPPORT IN CRISIS MANAGEMENT AND CITIZEN PROTECTION The graduation thesis on topic "Logistics and logistics support in crisis management and citizen protection" is divided into several chapters, which in summary are a material presenting information about logistics and logistics support in crisis management and citizen protection. This was one of the aims at this work. Chapters I., II., III., IV. describe logistics and logistics support, crisis management, cit...

  3. Logistics potentials in business competitive advantage creation

    Directory of Open Access Journals (Sweden)

    Rafał Matwiejczuk

    2013-12-01

    Full Text Available Background: Companies constantly search for ways to achieve and sustain long-term competitive advantage. Among the factors influencing the competitive advantage creation there are so called logistics potentials, which constitute a component part of a business strategic potentials. Logistics resources, logistics capabilities and logistics competences are the main components of the logistics potentials structure and hierarchy. Methods: In order to recognize the logistics potentials which determine the competitive advantage creation one may use the assumptions and elements of contemporary management concepts, including strategic management. In particular the article deals with Resource-Based View (RBV, Dynamic Capabilities Concept (DCC and - first of all - Competence-Based Management (CBM. Results and conclusions: Several significant research projects have presented a wide scope and a large number of possibilities of logistics potentials (and logistics competences in particular influence on business competitive advantage creation. The article briefly presents the research results conducted by: (1 Michigan State University (USA, (2 European Logistics Association (ELA in cooperation with A.T. Kearney, (3 Computer Sciences Corporation and (4 Capgemini. The research results have pointed out to differentiated but at the same distinctive symptoms of logistics competences influence on competitive advantage creation. The article also refers to the results of the research carried out by the Chair of Logistics & Marketing at Opole University (Poland in companies operating in Poland. The research has been mainly dealing with the significance of logistics competences in competitive advantage creation.

  4. An Objective Screening Method for Major Depressive Disorder Using Logistic Regression Analysis of Heart Rate Variability Data Obtained in a Mental Task Paradigm

    Directory of Open Access Journals (Sweden)

    Guanghao Sun

    2016-11-01

    Full Text Available Background and Objectives: Heart rate variability (HRV has been intensively studied as a promising biological marker of major depressive disorder (MDD. Our previous study confirmed that autonomic activity and reactivity in depression revealed by HRV during rest and mental task (MT conditions can be used as diagnostic measures and in clinical evaluation. In this study, logistic regression analysis (LRA was utilized for the classification and prediction of MDD based on HRV data obtained in an MT paradigm.Methods: Power spectral analysis of HRV on R-R intervals before, during, and after an MT (random number generation was performed in 44 drug-naïve patients with MDD and 47 healthy control subjects at Department of Psychiatry in Shizuoka Saiseikai General Hospital. Logit scores of LRA determined by HRV indices and heart rates discriminated patients with MDD from healthy subjects. The high frequency (HF component of HRV and the ratio of the low frequency (LF component to the HF component (LF/HF correspond to parasympathetic and sympathovagal balance, respectively.Results: The LRA achieved a sensitivity and specificity of 80.0% and 79.0%, respectively, at an optimum cutoff logit score (0.28. Misclassifications occurred only when the logit score was close to the cutoff score. Logit scores also correlated significantly with subjective self-rating depression scale scores (p < 0.05.Conclusion: HRV indices recorded during a mental task may be an objective tool for screening patients with MDD in psychiatric practice. The proposed method appears promising for not only objective and rapid MDD screening, but also evaluation of its severity.

  5. FUTURE CIRCULAR COLLIDER LOGISTICS STUDY

    CERN Document Server

    Beißert, Ulrike; Kuhlmann, Gerd; Nettsträter, Andreas; Prasse, Christian; Wohlfahrt, Andreas

    2018-01-01

    The Large Hadron Collider (LHC) at the European Organization for Nuclear Research CERN in Geneva is the largest and most powerful collider in the world. CERN and its research and experimental infrastructure is not only a focus for the science community but is also very much in the public eye. With the Future Circular Collider (FCC) Study, CERN has begun to examine the feasibility of a new underground accelerator ring with a length of approximately 100 kilometres. Logistics is of great importance for the construction, assembly and operation of the FCC. During the planning, construction and assembly of the LHC, logistics proved to be one of the key factors. As the FCC is even larger than the LHC, logistics will also become more and more significant. This report therefore shows new concepts, methods and analytics for logistics, supply chain and transport concepts as part of the FCC study. This report deals with three different logistics aspects for the planning and construction phase of FCC: 1. A discussion of d...

  6. Physics background in luminosity measurement at ILC and measurement of the proton b-content at H1 using multivariate method

    Energy Technology Data Exchange (ETDEWEB)

    Pandurovic, Mila

    2011-12-15

    difference of the charm and beauty flavoured hadrons compared to the light ones. Thus there are several sensitive observables like impact parameter based significances of tracks, transverse momenta of tracks and jets, jets masses and multiplicities, that can be used to distinguish between events containing heavy flavours with respect to the light ones. These observables are combined in the most optimal way using the multivariate analysis techniques (TMVA). Output of the chosen multivariate method is further used in the Barlow-Beeston fit to fit the data with the corresponding b, c and light-flavor Monte Carlo samples. In this way, a proton b-content is determined in different Q{sup 2} bins. The measured values are found to be in agreement with the LO theory prediction. The dominant component of the systematic error is coming from the choice of a QCD production model of heavy quarks as well as from the choice of a fragmentation function. Although the systematic error is somewhat larger than in the previous measurements at H1, this method allows statistics of the sample to be better preserved with the statistical error below one percent in all Q{sup 2} bins.

  7. Security in Logistics

    Science.gov (United States)

    Cempírek, Václav; Nachtigall, Petr; Široký, Jaromír

    2016-12-01

    This paper deals with security of logistic chains according to incorrect declaration of transported goods, fraudulent transport and forwarding companies and possible threats caused by political influences. The main goal of this paper is to highlight possible logistic costs increase due to these fraudulent threats. An analysis of technological processes will beis provided, and an increase of these transport times considering the possible threatswhich will beis evaluated economic costs-wise. In the conclusion, possible threat of companies'` efficiency in logistics due to the costs`, means of transport and increase in human resources` increase will beare pointed out.

  8. Applied logistic regression

    CERN Document Server

    Hosmer, David W; Sturdivant, Rodney X

    2013-01-01

     A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

  9. Continuous multivariate exponential extension

    International Nuclear Information System (INIS)

    Block, H.W.

    1975-01-01

    The Freund-Weinman multivariate exponential extension is generalized to the case of nonidentically distributed marginal distributions. A fatal shock model is given for the resulting distribution. Results in the bivariate case and the concept of constant multivariate hazard rate lead to a continuous distribution related to the multivariate exponential distribution (MVE) of Marshall and Olkin. This distribution is shown to be a special case of the extended Freund-Weinman distribution. A generalization of the bivariate model of Proschan and Sullo leads to a distribution which contains both the extended Freund-Weinman distribution and the MVE

  10. FEEDBACK AND LOGISTICS CONTROLLING

    Directory of Open Access Journals (Sweden)

    Mehesne Berek Szilvia

    2015-07-01

    Full Text Available The following things led to that the feedback, the supervision and improvement of the processes have become more pronounced: continuous rise in the importance of logistics; increase in complexity of its content; its activity becoming more complex. These activities are necessary for the optimum information supply. The intensification of market competition requires the corporations to possess exact and up-to-date information about their activities. Complexity of the logistics system presumes a parallel application of an effective feedback, supervision and management system simultaneously with the given logistics system. The indispensability of logistics is also proved by the fact that it can be found sporadically (in the form of logistics departments or in a complex way in case of each organization. The logistical approach means a huge support in the management since it contains the complexity, the handling as a unit in order to ensure a harmony of the different corporate departments and part activities. In addition to the professional application of a logistics system, there is an opportunity to coordinate the relations inside an organization as well as between the organizations and to handle them as a unit. The sine qua non of the success of logistical processes is a harmony of the devices applied. The controlling system is a device for feeding back the processes of a corporate system. By means of the checkpoints intercalated into the processes, the logistics controlling provides information for the leadership which contributes even more to the complex approach of logistics system. By dint of the logistics controlling, the monitoring and coordination of every logistical part activity become possible with the help of information supply ensured by the logistics controlling. The logistics controlling reviews, assesses and coordinates; these activities have an effect on the cost and income management. Its reason is to be searched in the built

  11. Logistics and Inventory System -

    Data.gov (United States)

    Department of Transportation — The Logistics and Inventory System (LIS) is the agencys primary supply/support automation tool. The LIS encompasses everything from order entry by field specialists...

  12. Green Logistics Management

    Science.gov (United States)

    Chang, Yoon S.; Oh, Chang H.

    Nowadays, environmental management becomes a critical business consideration for companies to survive from many regulations and tough business requirements. Most of world-leading companies are now aware that environment friendly technology and management are critical to the sustainable growth of the company. The environment market has seen continuous growth marking 532B in 2000, and 590B in 2004. This growth rate is expected to grow to 700B in 2010. It is not hard to see the environment-friendly efforts in almost all aspects of business operations. Such trends can be easily found in logistics area. Green logistics aims to make environmental friendly decisions throughout a product lifecycle. Therefore for the success of green logistics, it is critical to have real time tracking capability on the product throughout the product lifecycle and smart solution service architecture. In this chapter, we introduce an RFID based green logistics solution and service.

  13. Multivariate GARCH models

    DEFF Research Database (Denmark)

    Silvennoinen, Annastiina; Teräsvirta, Timo

    This article contains a review of multivariate GARCH models. Most common GARCH models are presented and their properties considered. This also includes nonparametric and semiparametric models. Existing specification and misspecification tests are discussed. Finally, there is an empirical example...

  14. Multivariate Time Series Search

    Data.gov (United States)

    National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...

  15. Basin Characterisation by Means of Joint Inversion of Electromagnetic Geophysical Data, Borehole Data and Multivariate Statistical Methods: The Loop Head Peninsula, Western Ireland, Case Study

    Science.gov (United States)

    Campanya, J. L.; Ogaya, X.; Jones, A. G.; Rath, V.; McConnell, B.; Haughton, P.; Prada, M.

    2016-12-01

    The Science Foundation Ireland funded project IRECCSEM project (www.ireccsem.ie) aims to evaluate Ireland's potential for onshore carbon sequestration in saline aquifers by integrating new electromagnetic geophysical data with existing geophysical and geological data. One of the objectives of this component of IRECCSEM is to characterise the subsurface beneath the Loop Head Peninsula (part of Clare Basin, Co. Clare, Ireland), and identify major electrical resistivity structures that can guide an interpretation of the carbon sequestration potential of this area. During the summer of 2014, a magnetotelluric (MT) survey was carried out on the Loop Head Peninsula, and data from a total of 140 sites were acquired, including audio-magnetotelluric (AMT), and broadband magnetotelluric (BBMT). The dataset was used to generate shallow three-dimensional (3-D) electrical resistivity models constraining the subsurface to depths of up to 3.5 km. The three-dimensional (3-D) joint inversions were performed using three different types of electromagnetic data: MT impedance tensor (Z), geomagnetic transfer functions (T), and inter-station horizontal magnetic transfer-functions (H). The interpretation of the results was complemented with second-derivative models of the resulting electrical resistivity models, and a quantitative comparison with borehole data using multivariate statistical methods. Second-derivative models were used to define the main interfaces between the geoelectrical structures, facilitating superior comparison with geological and seismic results, and also reducing the influence of the colour scale when interpreting the results. Specific analysis was performed to compare the extant borehole data with the electrical resistivity model, identifying those structures that are better characterised by the resistivity model. Finally, the electrical resistivity model was also used to propagate some of the physical properties measured in the borehole, when a good relation was

  16. Conference Logistics Management 2013

    CERN Document Server

    Haasis, Hans-Dietrich; Kopfer, Herbert; Kotzab, Herbert; Schönberger, Jörn

    2015-01-01

    This contributed volume contains the collected research papers presented at the Logistik-Management-Konferenz 2013 organized by the VHB Wissenschaftliche Kommission Logistik, held in Bremen 2013. The papers reflect the current state-of-the-art in logistics and supply chain management, focusing on environmental sustainability in logistics and supply chain network dynamics and control. The target audience primarily comprises research experts in the field as well as practitioners but the book may also be beneficial for graduate students.

  17. Understanding logistic regression analysis

    OpenAIRE

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...

  18. Graphics for the multivariate two-sample problem

    International Nuclear Information System (INIS)

    Friedman, J.H.; Rafsky, L.C.

    1981-01-01

    Some graphical methods for comparing multivariate samples are presented. These methods are based on minimal spanning tree techniques developed for multivariate two-sample tests. The utility of these methods is illustrated through examples using both real and artificial data

  19. Research on the Logistics Supply Chain in Port Logistics Transportation

    OpenAIRE

    Wang Yan-liang

    2013-01-01

    The aim of this study is to improve and increase the logistics system effectiveness and to solve the problem of optimal movement of different flows. Logistics transport carrying the world on material resources transfer exchange important mission and economic development and our lives are closely linked, logistics chain logistics transport occupies an important position and in the e logistics chain in port logistics has play a decisive role. For many coastal countries port logistics is the eco...

  20. Logistic management materials-technical support railway enterprises

    OpenAIRE

    Dykan, V.; Borozenetc, T.

    2014-01-01

    The essence of logistics management. Determine the feasibility of applying the principles of logistics management in organizing the logistics of railway transport. Discussed measures to develop suppliers in the implementation of logistics management logistics. Identified the need to develop and implement regulatory and methodical system to improve materials-technical support through the introduction of modern logistics principles. Applied systemic campaign to organize the materials-technical ...

  1. Involvement, knowledge sharing and proactive improvement as antecedents of logistics outsourcing performance

    Directory of Open Access Journals (Sweden)

    Andreja Križman

    2010-11-01

    Full Text Available The purpose of this article is to present the research results of a study on the impact of the drivers of logistics outsourcing performance: involvement, knowledge sharing, and innovation. The sample was derived from companies in the Slovenian market who choose to outsource their logistics services to logistics service providers. The article also attempts to contribute to the theoretical and methodological findings and managerial implications in logistics outsourcing discussions. On the basis of the existing literature and some new arguments derived from in-depth interviews with logistics experts, the measurement and structural models were empirically analysed on a sample of manufacturing and retail companies involved in an ongoing relationship with a logistics service provider. Measurement scales for the constructs, their development, refinement and measurement for validity and reliability were performed. Multivariate statistical methods (EFA, CFA and SEM – Partial Least Squares were utilised. Five hypotheses were tested and confirmed. The logistics outsourcing performance (the goal achievement and the goal exceedance is well explained by involvement, knowledge sharing, and innovation.

  2. Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China

    Science.gov (United States)

    Li, Zhi; Jin, Jiming

    2017-11-01

    Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs) at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i) spatial downscaling of ESMs using a transfer function method, (ii) temporal downscaling of ESMs using a single-site weather generator, and (iii) reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011-2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT) for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011-2040 to 1961-2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its variance ratios of 2011-2040 to 1961-2005 increased

  3. Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China

    Directory of Open Access Journals (Sweden)

    Z. Li

    2017-11-01

    Full Text Available Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i spatial downscaling of ESMs using a transfer function method, (ii temporal downscaling of ESMs using a single-site weather generator, and (iii reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011–2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011–2040 to 1961–2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its

  4. Simulation of multivariate diffusion bridges

    DEFF Research Database (Denmark)

    Bladt, Mogens; Finch, Samuel; Sørensen, Michael

    We propose simple methods for multivariate diffusion bridge simulation, which plays a fundamental role in simulation-based likelihood and Bayesian inference for stochastic differential equations. By a novel application of classical coupling methods, the new approach generalizes a previously...... proposed simulation method for one-dimensional bridges to the mulit-variate setting. First a method of simulating approzimate, but often very accurate, diffusion bridges is proposed. These approximate bridges are used as proposal for easily implementable MCMC algorithms that produce exact diffusion bridges...

  5. Review on Doctoral Dissertation: Drago Pupavac: Logistics operator – the factor of dynamic optimization of global logistics chains

    Directory of Open Access Journals (Sweden)

    Ratko Zelenika

    2007-05-01

    Full Text Available The main objective of the scientific research of this doctoral thesis is the effect of the logistics operator in the function of cutting total costs of the global logistics chain. In order to achieve the objective of the research, a number of scientific methods have been applied such as survey methods, methods of dynamic programming and mixed convex programming. Owing to the applied scientific methodology,Drago Pupovac, M.Sc. has successfully interpreted the obtained results by proving that the selective model approach to active participants of the logistics chain gives the logistics operator the insight into potential logistics network, depicts skills of individual operators in the logistics network, specifies logistics activitiesof each logistics venture, provides information on costs of specific logistics activities and in that way proves that it enables logistics operator to optimize logistics chains by protecting them from the demand instability and changes.

  6. Logistic regression for dichotomized counts.

    Science.gov (United States)

    Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

    2016-12-01

    Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

  7. Multivariate refined composite multiscale entropy analysis

    International Nuclear Information System (INIS)

    Humeau-Heurtier, Anne

    2016-01-01

    Multiscale entropy (MSE) has become a prevailing method to quantify signals complexity. MSE relies on sample entropy. However, MSE may yield imprecise complexity estimation at large scales, because sample entropy does not give precise estimation of entropy when short signals are processed. A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. Nevertheless, RCMSE is for univariate signals only. The simultaneous analysis of multi-channel (multivariate) data often over-performs studies based on univariate signals. We therefore introduce an extension of RCMSE to multivariate data. Applications of multivariate RCMSE to simulated processes reveal its better performances over the standard multivariate MSE. - Highlights: • Multiscale entropy quantifies data complexity but may be inaccurate at large scale. • A refined composite multiscale entropy (RCMSE) has therefore recently been proposed. • Nevertheless, RCMSE is adapted to univariate time series only. • We herein introduce an extension of RCMSE to multivariate data. • It shows better performances than the standard multivariate multiscale entropy.

  8. Efficiency and Logistics

    CERN Document Server

    Hompel, Michael; Klumpp, Matthias

    2013-01-01

    The „EffizienzCluster LogistikRuhr“ was a winner in the Leading Edge Science Cluster competition run by the German federal Ministry of Education and Research. The mission and aim of the „EffizienzCluster LogistikRuhr“ is to facilitate tomorrow’s individuality – in the sense of individual goods supply, mobility, and production – using 75 percent of today’s resources. Efficiency – both in economical and ecological terms – is enabled by state-of-the-art and innovative logistical solutions including transportation, production and intralogistics. These proceedings “Efficiency and Logistics” give first answers from 27 research projects as an insight into the current state of research of Europe’s leading research and development cluster in logistics and as a contribution to the discussion on how logistics as a science can help to cope with foreseeable resource shortage and sustainability as global challenges.

  9. Logistics innovation development

    DEFF Research Database (Denmark)

    Pedrosa, Alex; Blazevic, Vera; Jasmand, Claudia

    2014-01-01

    to investigate the role of boundary-spanning employees in deepening and broadening customer knowledge while developing logistics service innovations. Findings The results show that boundary-spanning employees’ engage sequentially in deepening and broadening customer knowledge throughout the logistics innovation...... development process. In particular it shows that deepening customer knowledge tends to occur in one-to-one interactions. When boundary-spanning employees engage in broadening customer knowledge, they develop a rich understanding of current customer. Research limitations/implications (if applicable) In general......Purpose This paper aims to investigate the microfoundations—boundary-spanning employees activities and behaviors—of deepening and broadening customer knowledge during logistics innovation development. Design/methodology/approach A multiple case study approach (six case studies) was adopted...

  10. Green Maritime Logistics

    DEFF Research Database (Denmark)

    Psaraftis, Harilaos N.

    2014-01-01

    Typical problems in maritime logistics include, among others, optimal ship speed, ship routing and scheduling, fleet deployment, fleet size and mix, weather routing, intermodal network design, modal split, transshipment, queuing at ports, terminal management, berth allocation, and total supply...... chain management. The traditional analysis of these problems has been in terms of cost- benefit and other optimization criteria from the point of view of the logistics provider, carrier, shipper, or other end-user. Such traditional analysis by and large either ignores environmental issues, or considers...... them of secondary importance. Green maritime logistics tries to bring the environmental dimension into the problem, and specifically the dimension of emissions reduction, by analyzing various trade-offs and exploring ‘win-win’ solutions. This talk takes a look at the trade-offs that are at stake...

  11. Multivariate Birkhoff interpolation

    CERN Document Server

    Lorentz, Rudolph A

    1992-01-01

    The subject of this book is Lagrange, Hermite and Birkhoff (lacunary Hermite) interpolation by multivariate algebraic polynomials. It unifies and extends a new algorithmic approach to this subject which was introduced and developed by G.G. Lorentz and the author. One particularly interesting feature of this algorithmic approach is that it obviates the necessity of finding a formula for the Vandermonde determinant of a multivariate interpolation in order to determine its regularity (which formulas are practically unknown anyways) by determining the regularity through simple geometric manipulations in the Euclidean space. Although interpolation is a classical problem, it is surprising how little is known about its basic properties in the multivariate case. The book therefore starts by exploring its fundamental properties and its limitations. The main part of the book is devoted to a complete and detailed elaboration of the new technique. A chapter with an extensive selection of finite elements follows as well a...

  12. Applied multivariate statistical analysis

    CERN Document Server

    Härdle, Wolfgang Karl

    2015-01-01

    Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners.  It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.  All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.  All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...

  13. Understanding logistic regression analysis.

    Science.gov (United States)

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

  14. Rise of humanitarian logistics

    CSIR Research Space (South Africa)

    Maspero, EL

    2008-07-01

    Full Text Available but was described as fairly routine for a company of Walmart’s size with 117 distribution centres spread around the country. The nonchalant response by Rollin Ford, (Walmart’s executive vice president of logistics and supply chain) says it all, “that’s what we do...%20and%20challenges%22 [3] Boorstin, J. 2005. New lessons to learn. Fortune. 3 October. [4] Davidson, A.L. 2006. Key Performance Indicators in Humanitarian Logistics. MLOG Thesis, 2006. Viewed 24 October 2006. [5] http...

  15. LOGISTIC ACTIVITIES IN BELARUS: TRENDS AND CHALLENGES

    Directory of Open Access Journals (Sweden)

    P. V. Bozhanov

    2017-01-01

    Full Text Available Main results of investigations on logistics activities in the Republic of Belarus at year-end 2016 are presented in the paper. The paper identifies and analyzes basic components of this activity on the basis of economic evaluation of indices presented in annual State statistical reporting on logistics and transport and freight forwarding activities of the Republican organizations according to form 1-logistics (Mintrans – Ministry of Transport and Communications of the Republic of Belarus, a report of the Ministry of Transport and Communications of the Republic of Belarus on the results of the implementation of Republican Program for development of logistics systems and transit potential of the Republic of Belarus for the period of 2016–2020, World Bank reports on logistics performance index, some indices of logistics infrastructure position and also results of electronic questionnaire of the largest logistics centers of the Republic of Belarus. Methods of comparative analysis, generalization and economic analysis have been used in the process of research. The analysis has shown that a network of logistics centers with various specialization and forms of property are located and operating in all regions of the Republic of Belarus. Most of them are situated in the Minsk region near the II and IX trans-European transport corridors and in the Brest region near the border with Poland. Structure of the logistics centers includes temporary storage warehouses, customs warehouses, warehouses for general use, container terminals, car parking, customs clearance office, and automotive, railway and other cargo transport facilities. Indices of logistics activity in the Republic of Belarus demonstrate its development in 2016. Storage space of logistics centers and main financial and volumetric indices of logistics activity which are included in the State statistical reporting have been increased during in recent times. These facts testify to the demand for

  16. Logistics Reduction: RFID Enabled Autonomous Logistics Management (REALM)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Advanced Exploration Systems (AES) Logistics Reduction (LR) project Radio-frequency identification (RFID) Enabled Autonomous Logistics Management (REALM) task...

  17. Human Exposure Risk Assessment Due to Heavy Metals in Groundwater by Pollution Index and Multivariate Statistical Methods: A Case Study from South Africa

    OpenAIRE

    Vetrimurugan Elumalai; K. Brindha; Elango Lakshmanan

    2017-01-01

    Heavy metals in surface and groundwater were analysed and their sources were identified using multivariate statistical tools for two towns in South Africa. Human exposure risk through the drinking water pathway was also assessed. Electrical conductivity values showed that groundwater is desirable to permissible for drinking except for six locations. Concentration of aluminium, lead and nickel were above the permissible limit for drinking at all locations. Boron, cadmium, iron and manganese ex...

  18. Logistics and Planning of Output Volume

    Directory of Open Access Journals (Sweden)

    V. I. Pokhabov

    2005-01-01

    Full Text Available On the basis of logistics conception the paper considers an adaptation of an enterprise to environmental changes with due account of its emergement properties. Taking into account emergement properties of an enterprise a logistics method for planning an optimum movement of the material flow is proposed in the paper.

  19. Assessment of laboratory logistics management information system ...

    African Journals Online (AJOL)

    Introduction: Logistics management information system for health commodities remained poorly implemented in most of developing countries. To assess the status of laboratory logistics management information system for HIV/AIDS and tuberculosis laboratory commodities in public health facilities in Addis Ababa. Methods: ...

  20. Roadmap towards a smart logistics ecosystem

    NARCIS (Netherlands)

    Hofman, W.J.; Bastiaansen, H.J.M.

    2014-01-01

    Currently, the fundamentals of a technical infrastructure for a logistics ‘systems-of-systems’ are laid, facilitating improved, more effective and efficient logistics services based on higher levels of self-organization. Through situation awareness with enhanced methods for sharing (real-time) data,

  1. Bayesian logistic regression analysis

    NARCIS (Netherlands)

    Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.

    2012-01-01

    In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an

  2. Logistics. Crucial link

    International Nuclear Information System (INIS)

    Wells, M.

    1996-01-01

    The article relates to offshore cost reduction in the UK and Norwegian sectors. Improvements within logistics and industrial co-operation are discussed being inspired by the joint government and industry NORSOK programme and the similar UK CRINE programme. Examples on cost reduction in various projects are given. 1 fig

  3. and Multinomial Logistic Regression

    African Journals Online (AJOL)

    This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).

  4. NATO Logistics Handbook

    National Research Council Canada - National Science Library

    2007-01-01

    ...), is intended as a simple guide to logistics in NATO. It does not attempt to examine current issues or provide answers to the problems that logisticians will face, but it rather aims at introducing them to some of the basic principles, policies...

  5. Logistics innovation development

    DEFF Research Database (Denmark)

    Pedrosa, Alex; Blazevic, Vera; Jasmand, Claudia

    2015-01-01

    Purpose – The purpose of this paper is to investigate the microfoundations of customer knowledge acquisition during logistics innovation development. Specifically, the authors explore the activities and behaviors of employees with customer contact (i.e. boundary-spanning employees (BSEs)) to deepen...

  6. Logistics Services Communication

    CERN Multimedia

    2006-01-01

    Members of the personnel are invited to take note that only parcels corresponding to official orders or contracts will be handled at CERN. Individuals are not authorisedto have private merchandise delivered to them at CERN and private deliveries will not be accepted by the Goods Reception services. Thank you for your understanding. Logistics Services - FI Department - 79947

  7. Logistics Services Communication

    CERN Document Server

    2006-01-01

    Members of the personnel are invited to take note that only parcels corresponding to official orders or contracts will be handled at CERN. Individuals are not authorised to have private merchandise delivered to them at CERN and private deliveries will not be accepted by the Goods Reception services. Thank you for your understanding. Logistics Services - FI Department - 79947

  8. Logistics, Management and Efficiency

    OpenAIRE

    Mircea UDRESCU; Sandu CUTURELA

    2014-01-01

    The problem related to the efficiency of the management for organization is general being the concern off all managers. In the present essay we consider that the efficacy of the organization begins from the structural systemization of the organizational management into general management, management of logistics and management of production which demands a new managerial process, more competitive based on economic efficiency.

  9. Logistics Takes Command

    NARCIS (Netherlands)

    Marullo, F.

    2015-01-01

    The term "logistics" derives from the Greek logizomai standing for the art of reckoning, organising, planning. Through time it achieved a strict military connotation, dealing with the composition, lodging and movements of troops, the arrangement of provisions in hostile territories, the

  10. A MULTIVARIATE WEIBULL DISTRIBUTION

    Directory of Open Access Journals (Sweden)

    Cheng Lee

    2010-07-01

    Full Text Available A multivariate survival function of Weibull Distribution is developed by expanding the theorem by Lu and Bhattacharyya. From the survival function, the probability density function, the cumulative probability function, the determinant of the Jacobian Matrix, and the general moment are derived.

  11. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole; Hansen, Peter Reinhard; Lunde, Asger

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement noise of certain types and can also handle non-synchronous trading. It is the first estimator...

  12. Multivariate data analysis

    DEFF Research Database (Denmark)

    Hansen, Michael Adsetts Edberg

    Interest in statistical methodology is increasing so rapidly in the astronomical community that accessible introductory material in this area is long overdue. This book fills the gap by providing a presentation of the most useful techniques in multivariate statistics. A wide-ranging annotated set...

  13. Multivariate pattern dependence.

    Directory of Open Access Journals (Sweden)

    Stefano Anzellotti

    2017-11-01

    Full Text Available When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analysis. In the present article, we introduce and apply multivariate pattern dependence (MVPD: a technique to study the statistical dependence between brain regions in humans in terms of the multivariate relations between their patterns of responses. MVPD characterizes the responses in each brain region as trajectories in region-specific multidimensional spaces, and models the multivariate relationship between these trajectories. We applied MVPD to the posterior superior temporal sulcus (pSTS and to the fusiform face area (FFA, using a searchlight approach to reveal interactions between these seed regions and the rest of the brain. Across two different experiments, MVPD identified significant statistical dependence not detected by standard functional connectivity. Additionally, MVPD outperformed univariate connectivity in its ability to explain independent variance in the responses of individual voxels. In the end, MVPD uncovered different connectivity profiles associated with different representational subspaces of FFA: the first principal component of FFA shows differential connectivity with occipital and parietal regions implicated in the processing of low-level properties of faces, while the second and third components show differential connectivity with anterior temporal regions implicated in the processing of invariant representations of face identity.

  14. Multivariable control in nuclear power stations

    International Nuclear Information System (INIS)

    Parent, M.; McMorran, P.D.

    1982-11-01

    Multivariable methods have the potential to improve the control of large systems such as nuclear power stations. Linear-quadratic optimal control is a multivariable method based on the minimization of a cost function. A related technique leads to the Kalman filter for estimation of plant state from noisy measurements. A design program for optimal control and Kalman filtering has been developed as part of a computer-aided design package for multivariable control systems. The method is demonstrated on a model of a nuclear steam generator, and simulated results are presented

  15. A robust optimization model for green regional logistics network design with uncertainty in future logistics demand

    Directory of Open Access Journals (Sweden)

    Dezhi Zhang

    2015-12-01

    Full Text Available This article proposes a new model to address the design problem of a sustainable regional logistics network with uncertainty in future logistics demand. In the proposed model, the future logistics demand is assumed to be a random variable with a given probability distribution. A set of chance constraints with regard to logistics service capacity and environmental impacts is incorporated to consider the sustainability of logistics network design. The proposed model is formulated as a two-stage robust optimization problem. The first-stage problem before the realization of future logistics demand aims to minimize a risk-averse objective by determining the optimal location and size of logistics parks with CO2 emission taxes consideration. The second stage after the uncertain logistics demand has been determined is a scenario-based stochastic logistics service route choices equilibrium problem. A heuristic solution algorithm, which is a combination of penalty function method, genetic algorithm, and Gauss–Seidel decomposition approach, is developed to solve the proposed model. An illustrative example is given to show the application of the proposed model and solution algorithm. The findings show that total social welfare of the logistics system depends very much on the level of uncertainty in future logistics demand, capital budget for logistics parks, and confidence levels of the chance constraints.

  16. Space Station fluid management logistics

    Science.gov (United States)

    Dominick, Sam M.

    1990-01-01

    Viewgraphs and discussion on space station fluid management logistics are presented. Topics covered include: fluid management logistics - issues for Space Station Freedom evolution; current fluid logistics approach; evolution of Space Station Freedom fluid resupply; launch vehicle evolution; ELV logistics system approach; logistics carrier configuration; expendable fluid/propellant carrier description; fluid carrier design concept; logistics carrier orbital operations; carrier operations at space station; summary/status of orbital fluid transfer techniques; Soviet progress tanker system; and Soviet propellant resupply system observations.

  17. Multicriteria Optimisation in Logistics Forwarder Activities

    Directory of Open Access Journals (Sweden)

    Tanja Poletan Jugović

    2007-05-01

    Full Text Available Logistics forwarder, as organizer and planner of coordinationand integration of all the transport and logistics chains elements,uses adequate ways and methods in the process of planningand decision-making. One of these methods, analysed inthis paper, which could be used in optimisation of transportand logistics processes and activities of logistics forwarder, isthe multicriteria optimisation method. Using that method, inthis paper is suggested model of multicriteria optimisation of logisticsforwarder activities. The suggested model of optimisationis justified in keeping with method principles of multicriteriaoptimization, which is included in operation researchmethods and it represents the process of multicriteria optimizationof variants. Among many different processes of multicriteriaoptimization, PROMETHEE (Preference Ranking OrganizationMethod for Enrichment Evaluations and Promcalc& Gaia V. 3.2., computer program of multicriteria programming,which is based on the mentioned process, were used.

  18. Activities and Education in Logistics

    Directory of Open Access Journals (Sweden)

    Jasmina Pašagić Škrinjar

    2008-03-01

    Full Text Available Logistic approach to traffic means new business policy,economy and ownership, new internal organization, externaland internal communication, different corporate cultures, humanresources management using scientific methods, trainingand education, changed management type and awarding system,knowledge of information technology, communicationskills, electronic commerce, etc. Education is part of all theseelements. The introduction of logistics in all the business activitieshas been imposed due to the following reasons: because ofthe life-cycle shortening of the product and its delivery, becauseof sudden technological development, because of productionand market globalization, because of the increase in competitiveness.This paper describes first various logistic activities with theindication of practical and scientific approaches. The logisticsapproach in the traffic activities requires upgrading of the professionaland scientific level to a higher one which means additionaltraining and acquiring of new skills as well as new technologiesfor the employees.The basic aim of research was to specifY the basic logisticsactivities and problems in order to indicate the need of differentforms of education. Fast technological and social changes requireconstant improvement and modification of professionalknowledge and acqui1ing of new scientific methods and skills.

  19. Essentials of multivariate data analysis

    CERN Document Server

    Spencer, Neil H

    2013-01-01

    ""… this text provides an overview at an introductory level of several methods in multivariate data analysis. It contains in-depth examples from one data set woven throughout the text, and a free [Excel] Add-In to perform the analyses in Excel, with step-by-step instructions provided for each technique. … could be used as a text (possibly supplemental) for courses in other fields where researchers wish to apply these methods without delving too deeply into the underlying statistics.""-The American Statistician, February 2015

  20. Waste acceptance and logistics

    International Nuclear Information System (INIS)

    Carlson, James H.

    1992-01-01

    There are three major components which are normally highlighted when the Civilian Radioactive Waste Management Program is discussed - the repository, the monitored retrievable storage facility, and the transportation system. These are clearly the major physical system elements and they receive the greatest external attention. However, there will not be a successful, operative waste management system without fully operational waste acceptance plans and logistics arrangements. This paper will discuss the importance of developing, on a parallel basis to the normally considered waste management system elements, the waste acceptance and logistics arrangements to enable the timely transfer of spent nuclear fuel from more than one hundred and twenty waste generators to the Federal government. The paper will also describe the specific activities the Program has underway to make the necessary arrangements. (author)

  1. Humanitarian logistics and sustainability

    CERN Document Server

    Leeuw, Sander; Regattieri, Alberto; Souza, Robert

    2015-01-01

    This contributed volume combines conceptual and strategic research articles dealing with the "why" and "to what end" of sustainable operations in humanitarian logistics, as well as operational research contributions regarding the "how" from the United Nations as well as from researchers and organizations from different countries (Germany, Australia, Singapore, Italy, Denmark, Jordan). The target audience primarily comprises research experts, decision makers  and practitioners in the field, but the book may also be beneficial for graduate students.

  2. Knowledge Enabled Logistics (KEL)

    Science.gov (United States)

    2010-09-01

    any penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN...decentralization of work, globalization, telecommuting , emphasis on constant learning, and greater use of teams within the workplace. While these...visible within military Command and Control (C2) operations. The focus of the current report is on C2 within a logistics domain. 2.1

  3. A comparison of three methods of assessing differential item functioning (DIF) in the Hospital Anxiety Depression Scale: ordinal logistic regression, Rasch analysis and the Mantel chi-square procedure.

    Science.gov (United States)

    Cameron, Isobel M; Scott, Neil W; Adler, Mats; Reid, Ian C

    2014-12-01

    It is important for clinical practice and research that measurement scales of well-being and quality of life exhibit only minimal differential item functioning (DIF). DIF occurs where different groups of people endorse items in a scale to different extents after being matched by the intended scale attribute. We investigate the equivalence or otherwise of common methods of assessing DIF. Three methods of measuring age- and sex-related DIF (ordinal logistic regression, Rasch analysis and Mantel χ(2) procedure) were applied to Hospital Anxiety Depression Scale (HADS) data pertaining to a sample of 1,068 patients consulting primary care practitioners. Three items were flagged by all three approaches as having either age- or sex-related DIF with a consistent direction of effect; a further three items identified did not meet stricter criteria for important DIF using at least one method. When applying strict criteria for significant DIF, ordinal logistic regression was slightly less sensitive. Ordinal logistic regression, Rasch analysis and contingency table methods yielded consistent results when identifying DIF in the HADS depression and HADS anxiety scales. Regardless of methods applied, investigators should use a combination of statistical significance, magnitude of the DIF effect and investigator judgement when interpreting the results.

  4. Multivariate calculus and geometry

    CERN Document Server

    Dineen, Seán

    2014-01-01

    Multivariate calculus can be understood best by combining geometric insight, intuitive arguments, detailed explanations and mathematical reasoning. This textbook has successfully followed this programme. It additionally provides a solid description of the basic concepts, via familiar examples, which are then tested in technically demanding situations. In this new edition the introductory chapter and two of the chapters on the geometry of surfaces have been revised. Some exercises have been replaced and others provided with expanded solutions. Familiarity with partial derivatives and a course in linear algebra are essential prerequisites for readers of this book. Multivariate Calculus and Geometry is aimed primarily at higher level undergraduates in the mathematical sciences. The inclusion of many practical examples involving problems of several variables will appeal to mathematics, science and engineering students.

  5. Multivariate rational data fitting

    Science.gov (United States)

    Cuyt, Annie; Verdonk, Brigitte

    1992-12-01

    Sections 1 and 2 discuss the advantages of an object-oriented implementation combined with higher floating-point arithmetic, of the algorithms available for multivariate data fitting using rational functions. Section 1 will in particular explain what we mean by "higher arithmetic". Section 2 will concentrate on the concepts of "object orientation". In sections 3 and 4 we shall describe the generality of the data structure that can be dealt with: due to some new results virtually every data set is acceptable right now, with possible coalescence of coordinates or points. In order to solve the multivariate rational interpolation problem the data sets are fed to different algorithms depending on the structure of the interpolation points in then-variate space.

  6. A logistics professional

    International Nuclear Information System (INIS)

    Jaeaeskelaeinen, A.

    1998-01-01

    Finland's oil, chemicals, and energy company, Neste, has achieved an enviable standard of logistics serving the markets around the Baltic Rim. Neste's safe and efficient transportation services are handled by its own fleet of tankers, time-chartered vessels, contract road tankers, and rail. Neste's terminals play an important part in the company's logistics network. The company operates four terminals of its own in Finland, and works with other oil companies at three of their terminals. Neste's own terminals are located at the company's refineries at Porvoo and Naantali, and at Kokkola and Kemi on the Gulf of Bothnia. Outside Finland the completion of a new terminal at Riga in Latvia, to enhance the logistics services provided to Neste's network of service stations and direct sales customers in the Baltic countries. This joins a terminal at Muuga near Tallinn in Estonia, which has been operational for some five years. Construction work began on a terminal in St. Petersburg in December 1997 to serve customers in the St. Petersburg and Vyborg areas. Completion is scheduled for autumn 1999

  7. Multivariate meta-analysis: Potential and promise

    Science.gov (United States)

    Jackson, Dan; Riley, Richard; White, Ian R

    2011-01-01

    The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

  8. Logistics costs of the enterprise

    Directory of Open Access Journals (Sweden)

    Andrea Rosová

    2007-06-01

    Full Text Available The article describe a problem of specification and systematization of enterprise’s logistics costs. With in a growing division of labour, also logistics costs increase their part in enterprises total costs.Almost all decisions about products and production in general, influence logistics processes even logistics costs and performances.In present is not clear enough, which of the cost-particles are relevant fot logistics costs, because some of logistics cost-particles accounts within overhead are charged together with costs of other sorts.Substantive step in the process of the monitoring and evidence of logistics costs is definition of this, that costs of enterprise´s processes will be inclusive in logistics costs and determining points of contact with the others departments (acquisition, production, sale etc.. After the specification of meditation processes, there is a need to choose applicable parameters for the expression of logistics performances. Besides logistics costs is needed to know logistics performances equivalent herewith at a cost of, therefore from the control side have for enterprise bigger value indices expressive correlation costs and performances(e.g. share of logistics unit costs performance.At the proposal and evidence of logistics costs and performances is needed consistently entertain an individual conditions of enterprise. Because the area of processes included strongly affects the size of account logistics costs and its share part in total costs of enterprise. Logistics costs are flow line between economy and logistics of the enterprise.

  9. Multivariate multiscale entropy of financial markets

    Science.gov (United States)

    Lu, Yunfan; Wang, Jun

    2017-11-01

    In current process of quantifying the dynamical properties of the complex phenomena in financial market system, the multivariate financial time series are widely concerned. In this work, considering the shortcomings and limitations of univariate multiscale entropy in analyzing the multivariate time series, the multivariate multiscale sample entropy (MMSE), which can evaluate the complexity in multiple data channels over different timescales, is applied to quantify the complexity of financial markets. Its effectiveness and advantages have been detected with numerical simulations with two well-known synthetic noise signals. For the first time, the complexity of four generated trivariate return series for each stock trading hour in China stock markets is quantified thanks to the interdisciplinary application of this method. We find that the complexity of trivariate return series in each hour show a significant decreasing trend with the stock trading time progressing. Further, the shuffled multivariate return series and the absolute multivariate return series are also analyzed. As another new attempt, quantifying the complexity of global stock markets (Asia, Europe and America) is carried out by analyzing the multivariate returns from them. Finally we utilize the multivariate multiscale entropy to assess the relative complexity of normalized multivariate return volatility series with different degrees.

  10. Control Multivariable por Desacoplo

    Directory of Open Access Journals (Sweden)

    Fernando Morilla

    2013-01-01

    Full Text Available Resumen: La interacción entre variables es una característica inherente de los procesos multivariables, que dificulta su operación y el diseño de sus sistemas de control. Bajo el paradigma de Control por desacoplo se agrupan un conjunto de metodologías, que tradicionalmente han estado orientadas a eliminar o reducir la interacción, y que recientemente algunos investigadores han reorientado con objetivos de solucionar un problema tan complejo como es el control multivariable. Parte del material descrito en este artículo es bien conocido en el campo del control de procesos, pero la mayor parte de él son resultados de varios años de investigación de los autores en los que han primado la generalización del problema, la búsqueda de soluciones de fácil implementación y la combinación de bloques elementales de control PID. Esta conjunción de intereses provoca que no siempre se pueda conseguir un desacoplo perfecto, pero que sí se pueda conseguir una considerable reducción de la interacción en el nivel básico de la pirámide de control, en beneficio de otros sistemas de control que ocupan niveles jerárquicos superiores. El artículo resume todos los aspectos básicos del Control por desacoplo y su aplicación a dos procesos representativos: una planta experimental de cuatro tanques acoplados y un modelo 4×4 de un sistema experimental de calefacción, ventilación y aire acondicionado. Abstract: The interaction between variables is inherent in multivariable processes and this fact may complicate their operation and control system design. Under the paradigm of decoupling control, several methodologies that traditionally have been addressed to cancel or reduce the interactions are gathered. Recently, this approach has been reoriented by several researchers with the aim to solve such a complex problem as the multivariable control. Parts of the material in this work are well known in the process control field; however, most of them are

  11. Strategies on the Implementation of China's Logistics Information Network

    Science.gov (United States)

    Dong, Yahui; Li, Wei; Guo, Xuwen

    The economic globalization and trend of e-commerce network have determined that the logistics industry will be rapidly developed in the 21st century. In order to achieve the optimal allocation of resources, a worldwide rapid and sound customer service system should be established. The establishment of a corresponding modern logistics system is the inevitable choice of this requirement. It is also the inevitable choice for the development of modern logistics industry in China. The perfect combination of modern logistics and information network can better promote the development of the logistics industry. Through the analysis of Status of Logistics Industry in China, this paper summed up the domestic logistics enterprise logistics information system in the building of some common problems. According to logistics information systems planning methods and principles set out logistics information system to optimize the management model.

  12. Multivariate realised kernels

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Hansen, Peter Reinhard; Lunde, Asger

    2011-01-01

    We propose a multivariate realised kernel to estimate the ex-post covariation of log-prices. We show this new consistent estimator is guaranteed to be positive semi-definite and is robust to measurement error of certain types and can also handle non-synchronous trading. It is the first estimator...... which has these three properties which are all essential for empirical work in this area. We derive the large sample asymptotics of this estimator and assess its accuracy using a Monte Carlo study. We implement the estimator on some US equity data, comparing our results to previous work which has used...

  13. Sparse Linear Identifiable Multivariate Modeling

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2011-01-01

    and bench-marked on artificial and real biological data sets. SLIM is closest in spirit to LiNGAM (Shimizu et al., 2006), but differs substantially in inference, Bayesian network structure learning and model comparison. Experimentally, SLIM performs equally well or better than LiNGAM with comparable......In this paper we consider sparse and identifiable linear latent variable (factor) and linear Bayesian network models for parsimonious analysis of multivariate data. We propose a computationally efficient method for joint parameter and model inference, and model comparison. It consists of a fully...

  14. Logistics in Estonian business companies

    Directory of Open Access Journals (Sweden)

    A. Kiisler

    2008-12-01

    Full Text Available The article describes logistics survey in Estonia carried out in 2007 as a part of the LogOnBaltic project. The level of logistics in Estonian manufacturing, trading and logistics companies is explored through logistics costs, performance indicators, outsourcing, ICT use and logistics self-estimation of the companies responded. Responses from 186 Estonian companies were gathered through a web-based survey (38% of manufacturing, 38% of trading and 24% of logistics sector. Logistics costs as the percentage of turnover make in average 13.8% in manufacturing and 13.3% in trading. Transportation and inventory carrying cost form around 70% of overall logistics costs. Considering the logistics indicators surveyed, Estonian companies show up with relatively low perfect order fulfillment rates, short customer order fulfillment cycles and effective management of cash flows. The most widely outsourced logistics function is international transportation followed by domestic transportation, freight forwarding and reverse logistics. By 2010, the outsourcing of IT systems in logistics followed by inventory management, warehousing and product customization is expected to increase more substantially. The awareness of logistics importance is still low among Estonian companies. Only 27–44% of those agree that logistics has a considerable impact on profitability, competitive advantage, top management or customer service level.

  15. Exploratory multivariate analysis by example using R

    CERN Document Server

    Husson, Francois; Pages, Jerome

    2010-01-01

    Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and hierarchical cluster analysis.The authors take a geometric point of view that provides a unified vision for exploring multivariate data tables. Within this framework, they present the prin

  16. Multivariate survival analysis and competing risks

    CERN Document Server

    Crowder, Martin J

    2012-01-01

    Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate data and distributions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametric methods. There are many books covering survival analysis, but very few that cover the multivariate case in any depth. Written for a graduate-level audience in statistics/biostatistics, this book includes practical exercises and R code for the examples. The author is renowned for his clear writing style, and this book continues that trend. It is an excellent reference for graduate students and researchers looking for grounding in this burgeoning field of research.

  17. Logistic service providers and sustainable physical distribution

    Directory of Open Access Journals (Sweden)

    Stef Weijers

    2012-06-01

    Full Text Available Background: Logistic Service Providers main concern was to ensure reliability for a low price (Christopher, 2005. Dutch Logistic Service Providers still have these two aspects at the top of their list, but also have to take in a new aspect: sustainability. 88% Of the investigated Logistic Service Providers have included sustainability in the company's goals. These Logistic Service Providers have developed different strategies to achieve a higher level of sustainability. This paper presents the results of a study into what Logistic Service Providers say what they are doing, or intend to do, to improve sustainability for their transport services. In this way insight is given in the attitude of Dutch Logistic Service Providers towards sustainability and how they intend to translate this into business practise: internal solutions or new methods incorporating external partners. Methods: Various methods of the investigations were used, among which the analysis of the statements about the sustainabilityon the websites of various companies as well as the questionnaire per Internet. The research covered 50 largest logistics companies operating in the Netherlands and 60 companies that competed for the award "Lean and Green" advertised in the Netherlands. In addition, the Internet survey was answered by 41 companies that belong to the network of our university. Results: The investigation has shown that sustainability is handled by the logistics company as an integral part of the corporate strategy. In contrast, shippers depend in the choice of logistics services primarily on such classical aspects as the reliability or the price and the sustainability play a minor role. Conclusions: Trying to find methods to improve the sustainability, Dutch logistics service providers, in the first place, look for solutions that increase the efficiency and therefore the cost reduction potential. Solutions, which require the involvement of clients, were less often

  18. Planning and management of logistic cycle

    Directory of Open Access Journals (Sweden)

    V. N. Kudashkin

    2017-01-01

    Full Text Available We are considering planning and managing of logistic cycle, its impact on the content of the main processes that comprise the cycle to implement the order for the supply of material resources for industrial consumption, as well as its practical use, effectiveness, and prospects.This research paper is made on the basis of the information, received from textbooks and scientific literature of domestic and foreign authors, as well as from other sources. The main methods, used in this work are as follows: method of system analysis, method of the theory of operations’ research, prognostics. Application of these methods allows forecasting material flows, creating the integrated management systems and controlling their movements, developing systems of logistic service, to optimize supply stock and solve a number of other tasks.A logistic approach to form a modern system of logistics will save time, reduce costs for the purchase of material resources, their delivery and storage.In modern conditions of the market economy, the considered time parameters of the logistic chain are essential for manufacturing enterprises because their records significantly increase the efficiency of the logistical system.Logistics is equipped with a special complex of economic and mathematical models, the main feature of which is the adaptability, i.e. ability to solve complex optimization problems in the operational mode and in the process of the management of material flows. The primary role of these models in a market economy is to identify quickly points of compromise.Dynamics to functional cycles gives the necessity to align resource needs «input» and «output». «Input» functional cycle is an order that specifies requirements for a product or service. Logistical system, which is able to complete fully the order of any size, as a rule, needs in the «combined» functional cycles, including different transactions and operations at different stages. The «output» of

  19. Segmentation and profiling consumers in a multi-channel environment using a combination of self-organizing maps (SOM method, and logistic regression

    Directory of Open Access Journals (Sweden)

    Seyed Ali Akbar Afjeh

    2014-05-01

    Full Text Available Market segmentation plays essential role on understanding the behavior of people’s interests in purchasing various products and services through various channels. This paper presents an empirical investigation to shed light on consumer’s purchasing attitude as well as gathering information in multi-channel environment. The proposed study of this paper designed a questionnaire and distributed it among 800 people who were at least 18 years of age and had some experiences on purchasing goods and services on internet, catalog or regular shopping centers. Self-organizing map, SOM, clustering technique was performed based on consumer’s interest in gathering information as well as purchasing products through internet, catalog and shopping centers and determined four segments. There were two types of questions for the proposed study of this paper. The first group considered participants’ personal characteristics such as age, gender, income, etc. The second group of questions was associated with participants’ psychographic characteristics including price consciousness, quality consciousness, time pressure, etc. Using multinominal logistic regression technique, the study determines consumers’ behaviors in each four segments.

  20. Empty Container Logistics

    Directory of Open Access Journals (Sweden)

    Jakov Karmelić

    2012-05-01

    Full Text Available Within the whole world container traffic, the largest share of containers is in the status of repositioning. Container repositioning results from the need for harmonization between the point of empty container accumulation and the point of demand, and waiting time for the availability of the first next transport of cargo. This status of containers on the container market is the consequence of imbalances in the worldwide trade distribution on most important shipping routes. The need for fast and effective reallocation of empty containers causes high costs and often represents an obstacle affecting the efficiency of port container terminals and inland carriers.In accordance with the above issue, this paper is mainly focused on the analysis of the data concerning global container capacities and the roots of container equipment imbalances, with the aim of determining the importance of empty container management and the need for empty container micro-logistic planning at the spread port area.

  1. Human Exposure Risk Assessment Due to Heavy Metals in Groundwater by Pollution Index and Multivariate Statistical Methods: A Case Study from South Africa

    Directory of Open Access Journals (Sweden)

    Vetrimurugan Elumalai

    2017-04-01

    Full Text Available Heavy metals in surface and groundwater were analysed and their sources were identified using multivariate statistical tools for two towns in South Africa. Human exposure risk through the drinking water pathway was also assessed. Electrical conductivity values showed that groundwater is desirable to permissible for drinking except for six locations. Concentration of aluminium, lead and nickel were above the permissible limit for drinking at all locations. Boron, cadmium, iron and manganese exceeded the limit at few locations. Heavy metal pollution index based on ten heavy metals indicated that 85% of the area had good quality water, but 15% was unsuitable. Human exposure dose through the drinking water pathway indicated no risk due to boron, nickel and zinc, moderate risk due to cadmium and lithium and high risk due to silver, copper, manganese and lead. Hazard quotients were high in all sampling locations for humans of all age groups, indicating that groundwater is unsuitable for drinking purposes. Highly polluted areas were located near the coast, close to industrial operations and at a landfill site representing human-induced pollution. Factor analysis identified the four major pollution sources as: (1 industries; (2 mining and related activities; (3 mixed sources- geogenic and anthropogenic and (4 fertilizer application.

  2. Application of multivariate splines to discrete mathematics

    OpenAIRE

    Xu, Zhiqiang

    2005-01-01

    Using methods developed in multivariate splines, we present an explicit formula for discrete truncated powers, which are defined as the number of non-negative integer solutions of linear Diophantine equations. We further use the formula to study some classical problems in discrete mathematics as follows. First, we extend the partition function of integers in number theory. Second, we exploit the relation between the relative volume of convex polytopes and multivariate truncated powers and giv...

  3. Limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method for the parameter estimation on geographically weighted ordinal logistic regression model (GWOLR)

    Science.gov (United States)

    Saputro, Dewi Retno Sari; Widyaningsih, Purnami

    2017-08-01

    In general, the parameter estimation of GWOLR model uses maximum likelihood method, but it constructs a system of nonlinear equations, making it difficult to find the solution. Therefore, an approximate solution is needed. There are two popular numerical methods: the methods of Newton and Quasi-Newton (QN). Newton's method requires large-scale time in executing the computation program since it contains Jacobian matrix (derivative). QN method overcomes the drawback of Newton's method by substituting derivative computation into a function of direct computation. The QN method uses Hessian matrix approach which contains Davidon-Fletcher-Powell (DFP) formula. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is categorized as the QN method which has the DFP formula attribute of having positive definite Hessian matrix. The BFGS method requires large memory in executing the program so another algorithm to decrease memory usage is needed, namely Low Memory BFGS (LBFGS). The purpose of this research is to compute the efficiency of the LBFGS method in the iterative and recursive computation of Hessian matrix and its inverse for the GWOLR parameter estimation. In reference to the research findings, we found out that the BFGS and LBFGS methods have arithmetic operation schemes, including O(n2) and O(nm).

  4. Multivariable calculus with applications

    CERN Document Server

    Lax, Peter D

    2017-01-01

    This text in multivariable calculus fosters comprehension through meaningful explanations. Written with students in mathematics, the physical sciences, and engineering in mind, it extends concepts from single variable calculus such as derivative, integral, and important theorems to partial derivatives, multiple integrals, Stokes’ and divergence theorems. Students with a background in single variable calculus are guided through a variety of problem solving techniques and practice problems. Examples from the physical sciences are utilized to highlight the essential relationship between calculus and modern science. The symbiotic relationship between science and mathematics is shown by deriving and discussing several conservation laws, and vector calculus is utilized to describe a number of physical theories via partial differential equations. Students will learn that mathematics is the language that enables scientific ideas to be precisely formulated and that science is a source for the development of mathemat...

  5. A Study on Reverse Logistics

    OpenAIRE

    Reddy, Dhananjaya

    2011-01-01

    In the competitive world of manufacturing, companies are often searching for new ways to improve their process, customer satisfaction and stay ahead in the game with their competitors. Reverse logistics has been considered a strategy to bring these things to life for the past decade or so. This thesis work tries to shed some light on the basics of reverse logistics and how reverse logistics can be used as a management strategy. This paper points out the fundamentals of reverse logistics and l...

  6. Multivariate Analyses and Evaluation of Heavy Metals by Chemometric BCR Sequential Extraction Method in Surface Sediments from Lingdingyang Bay, South China

    Directory of Open Access Journals (Sweden)

    Linglong Cao

    2015-04-01

    Full Text Available Sediments in estuary areas are recognized as the ultimate reservoirs for numerous contaminants, e.g., toxic metals. Multivariate analyses by chemometric evaluation were performed to classify metal ions (Cu, Zn, As, Cr, Pb, Ni and Cd in superficial sediments from Lingdingyang Bay and to determine whether or not there were potential contamination risks based on the BCR sequential extraction scheme. The results revealed that Cd was mainly in acid-soluble form with an average of 75.99% of its total contents and thus of high potential availability, indicating significant anthropogenic sources, while Cr, As, Ni were enriched in the residual fraction which could be considered as the safest ingredients to the environment. According to the proportion of secondary to primary phases (KRSP, Cd had the highest bioavailable fraction and represented high or very high risk, followed by Pb and Cu with medium risks in most of samples. The combined evaluation of the Pollution Load Index (PLI and the mean Effect Range Median Quotient (mERM-Q highlighted that the greatest potential environmental risk area was in the northwest of Lingdingyang Bay. Almost all of the sediments had a 21% probability of toxicity. Additionally, Principal Component Analysis (PCA revealed that the survey region was significantly affected by two main sources of anthropogenic contributions: PC1 showed increased loadings of variables in acid-soluble and reducible fractions that were consistent with the input from industrial wastes (such as manufacturing, metallurgy, chemical industry and domestic sewages; PC2 was characterized by increased loadings of variables in residual fraction that could be attributed to leaching and weathering of parent rocks. The results obtained demonstrated the need for appropriate remediation measures to alleviate soil pollution problem due to the more aggregation of potentially risky metals. Therefore, it is of crucial significance to implement the targeted

  7. The Emergence of City Logistics

    DEFF Research Database (Denmark)

    Gammelgaard, Britta; Aastrup, Jesper

    2014-01-01

    Purpose: Many city logistics projects in Europe have failed. The purpose of this article is to increase understanding of how city logistics emerge. A better understanding of the complex organizational processes with many actors and stakeholders in city logistics projects may prevent further failu...

  8. A binary logistic regression model with complex sampling design of ...

    African Journals Online (AJOL)

    2017-09-03

    Sep 3, 2017 ... Bi-variable and multi-variable binary logistic regression model with complex sampling design was fitted. .... Data was entered into STATA-12 and analyzed using. SPSS-21. .... lack of access/too far or costs too much. 35. 1.2.

  9. [Appliancation of logistics in resources management of medical asset].

    Science.gov (United States)

    Miroshnichenko, Iu V; Goriachev, A B; Bunin, S A

    2011-06-01

    The usage of basic regulations of logistics in practical activity for providing joints and military units with medical asset is theoretically justified. The role of logistics in organizing, building and functioning of military (armed forces) medical supply system is found out. The methods of solving urgent problems of improvement the resources management of medical asset on the basis of logistics are presented.

  10. A new approach to the logistic function with some applications

    OpenAIRE

    Rzadkowski, Grzegorz; Głażewska, Iwona; Sawińska, Katarzyna

    2014-01-01

    In the present paper we propose a new approach to investigate the logistic function, commonly used in mathematical models in economics and management. The approach is based on indicating in a given time series, having a logistic trend, some characteristic points corresponding to zeroes of successive derivatives of the logistic function. We give also examples of application of this method.

  11. The method of separation for evolutionary spectral density estimation of multi-variate and multi-dimensional non-stationary stochastic processes

    KAUST Repository

    Schillinger, Dominik; Stefanov, Dimitar; Stavrev, Atanas

    2013-01-01

    -variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed

  12. Comparison of Chemical Constituents in Scrophulariae Radix Processed by Different Methods based on UFLC-MS Combined with Multivariate Statistical Analysis.

    Science.gov (United States)

    Wang, Shengnan; Hua, Yujiao; Zou, Lisi; Liu, Xunhong; Yan, Ying; Zhao, Hui; Luo, Yiyuan; Liu, Juanxiu

    2018-02-01

    Scrophulariae Radix is one of the most popular traditional Chinese medicines (TCMs). Primary processing of Scrophulariae Radix is an important link which closely related to the quality of products in this TCM. The aim of this study is to explore the influence of different processing methods on chemical constituents in Scrophulariae Radix. The difference of chemical constituents in Scrophulariae Radix processed by different methods was analyzed by using ultra fast liquid chromatography-triple quadrupole-time of flight mass spectrometry coupled with principal component analysis and orthogonal partial least squares discriminant analysis. Furthermore, the contents of 12 index differential constituents in Scrophulariae Radix processed by different methods were simultaneously determined by using ultra fast liquid chromatography coupled with triple quadrupole-linear ion trap mass spectrometry. Gray relational analysis was performed to evaluate the different processed samples according to the contents of 12 constituents. All of the results demonstrated that the quality of Scrophulariae Radix processed by "sweating" method was better. This study will provide the basic information for revealing the change law of chemical constituents in Scrophulariae Radix processed by different methods and facilitating selection of the suitable processing method of this TCM. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Reference model analysis of suitability for logistics management

    Directory of Open Access Journals (Sweden)

    Cezary Mańkowski

    2011-12-01

    Full Text Available Reference models are one of the many instruments aspiring to find into a set of different concepts, methods and techniques used in managing the logistics. Therefore, the aim of this paper is to present the results of assessing the suitability of reference models for solving logistical problems. This evaluation indicates that they are universal, support the realization of all the logistics management function in various areas, such as logistics of manufacturing glass products.

  14. Managing logistical processes in franchise retail trade networks

    OpenAIRE

    Grigorenko Tatyana N.; Kochubey Dmitriy V.

    2013-01-01

    The article analyses approaches to organisation of internal logistics of franchise trade networks and methodical provision of assessment of results of logistical activity at companies of franchise networks. The article justifies urgency of application of referent models of management of supply chains in construction of a system of management of logistical activity of franchise networks. It offers classification of models of management of internal logistics of franchise retail trade networks. ...

  15. Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

    Science.gov (United States)

    Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun

    2014-12-01

    Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.

  16. Logistics centres development in Latvia

    Directory of Open Access Journals (Sweden)

    I. Kabashkin

    2007-12-01

    Full Text Available In the situation where a large increase in trade and freight transport volumes in the Baltic Sea region (BSR is expected and in which the BSR is facing a major economic restructuring, eff orts to achieve more integrated and sustainable transport and communication links within the BSR are needed. One of these eff orts is the development of logistics centres (LCs and their networking, which will continue to have an impact on improving communication links, spatial planning practices and approaches, logistics chain development and the promotion of sustainable transport modes. These factors will refl ect on logistics processes both in major gateway cities and in remote BSR areas. The importance of logistics systems as a whole is not seen clearly enough. Logistics actors see that logistics operations are not appreciated as much as other fi elds of activity. In addition, logistics centres and the importance of logistics activities to the business life of areas and the employment rate should be brought up better. In the paper main goal and tasks of national approach to LCs development are discussed. Strategic focus of new activities in this area is on the integration of various networks within and between logistics centres in order to improve and develop the quality of logistics networks as well as to spatially widen the networking activities. The key objectives are to integrate the links between logistics centres, ports and other logistics operators in a functional and sustainable way, to promote spatial integration by creating sustainable and integrated approaches to spatial planning of logistics centres and transport infrastructure, to improve ICT-based networking and communication practices of the fi elds of transport and logistics and to increase the competence of logistics centres and associated actors by organising educational and training events. The current activities include, for example, the creation of measures for transport networking and

  17. Acoustic multivariate condition monitoring - AMCM

    Energy Technology Data Exchange (ETDEWEB)

    Rosenhave, P E [Vestfold College, Maritime Dept., Toensberg (Norway)

    1998-12-31

    In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.

  18. Acoustic multivariate condition monitoring - AMCM

    Energy Technology Data Exchange (ETDEWEB)

    Rosenhave, P.E. [Vestfold College, Maritime Dept., Toensberg (Norway)

    1997-12-31

    In Norway, Vestfold College, Maritime Department presents new opportunities for non-invasive, on- or off-line acoustic monitoring of rotating machinery such as off-shore pumps and diesel engines. New developments within acoustic sensor technology coupled with chemometric data analysis of complex signals now allow condition monitoring of hitherto unavailable flexibility and diagnostic specificity. Chemometrics paired with existing knowledge yields a new and powerful tool for condition monitoring. By the use of multivariate techniques and acoustics it is possible to quantify wear and tear as well as predict the performance of working components in complex machinery. This presentation describes the AMCM method and one result of a feasibility study conducted onboard the LPG/C `Norgas Mariner` owned by Norwegian Gas Carriers as (NGC), Oslo. (orig.) 6 refs.

  19. A quantitative structure- property relationship of gas chromatographic/mass spectrometric retention data of 85 volatile organic compounds as air pollutant materials by multivariate methods

    Directory of Open Access Journals (Sweden)

    Sarkhosh Maryam

    2012-05-01

    Full Text Available Abstract A quantitative structure-property relationship (QSPR study is suggested for the prediction of retention times of volatile organic compounds. Various kinds of molecular descriptors were calculated to represent the molecular structure of compounds. Modeling of retention times of these compounds as a function of the theoretically derived descriptors was established by multiple linear regression (MLR and artificial neural network (ANN. The stepwise regression was used for the selection of the variables which gives the best-fitted models. After variable selection ANN, MLR methods were used with leave-one-out cross validation for building the regression models. The prediction results are in very good agreement with the experimental values. MLR as the linear regression method shows good ability in the prediction of the retention times of the prediction set. This provided a new and effective method for predicting the chromatography retention index for the volatile organic compounds.

  20. On logistic regression analysis of dichotomized responses.

    Science.gov (United States)

    Lu, Kaifeng

    2017-01-01

    We study the properties of treatment effect estimate in terms of odds ratio at the study end point from logistic regression model adjusting for the baseline value when the underlying continuous repeated measurements follow a multivariate normal distribution. Compared with the analysis that does not adjust for the baseline value, the adjusted analysis produces a larger treatment effect as well as a larger standard error. However, the increase in standard error is more than offset by the increase in treatment effect so that the adjusted analysis is more powerful than the unadjusted analysis for detecting the treatment effect. On the other hand, the true adjusted odds ratio implied by the normal distribution of the underlying continuous variable is a function of the baseline value and hence is unlikely to be able to be adequately represented by a single value of adjusted odds ratio from the logistic regression model. In contrast, the risk difference function derived from the logistic regression model provides a reasonable approximation to the true risk difference function implied by the normal distribution of the underlying continuous variable over the range of the baseline distribution. We show that different metrics of treatment effect have similar statistical power when evaluated at the baseline mean. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  1. The Emergence of City Logistics

    DEFF Research Database (Denmark)

    Gammelgaard, Britta

    2015-01-01

    is therefore to increase understanding of how city logistics emerge, and secondarily, to investigate whether such processes can be managed at all. Design/methodology/approach: – A paradigm shift in urban planning creates new ways of involving stakeholders in new sustainability measures such as city logistics...... dialectic forces were at play. City logistics schemes are still in an innovation phase. The biggest challenge in managing a process toward city logistics is to convince the many public and private stakeholders of their mutual interest and goals. Research limitations/implications: – Urban goods transport...... city logistics projects may fail. Thereby, cities become more environmentally and socially sustainable. Originality/value: – Insights into a city logistics project from a change management perspective has not previously been reported in literature....

  2. Discrimination of edible oils and fats by combination of multivariate pattern recognition and FT-IR spectroscopy: A comparative study between different modeling methods

    Science.gov (United States)

    Javidnia, Katayoun; Parish, Maryam; Karimi, Sadegh; Hemmateenejad, Bahram

    2013-03-01

    By using FT-IR spectroscopy, many researchers from different disciplines enrich the experimental complexity of their research for obtaining more precise information. Moreover chemometrics techniques have boosted the use of IR instruments. In the present study we aimed to emphasize on the power of FT-IR spectroscopy for discrimination between different oil samples (especially fat from vegetable oils). Also our data were used to compare the performance of different classification methods. FT-IR transmittance spectra of oil samples (Corn, Colona, Sunflower, Soya, Olive, and Butter) were measured in the wave-number interval of 450-4000 cm-1. Classification analysis was performed utilizing PLS-DA, interval PLS-DA, extended canonical variate analysis (ECVA) and interval ECVA methods. The effect of data preprocessing by extended multiplicative signal correction was investigated. Whilst all employed method could distinguish butter from vegetable oils, iECVA resulted in the best performances for calibration and external test set with 100% sensitivity and specificity.

  3. Outsourcing Operational Logistics: Buyer Beware

    Science.gov (United States)

    2003-05-16

    This logistics system takes far too many people to conduct support missions and does not provide the desired customer performance in terms of...FINAL 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER OUTSOURCING OPERATIONAL LOGISTICS: BUYER BEWARE (U) 5b. GRANT NUMBER 5c...Form 298 (Rev. 8-98) 1 (Unclassified Paper) NAVAL WAR COLLEGE Newport, R.I. OUTSOURCING OPERATIONAL LOGISTICS: BUYER BEWARE By LAMONT WOODY Lieutenant

  4. Logistics Reduction: Heat Melt Compactor

    Data.gov (United States)

    National Aeronautics and Space Administration — The Advanced Exploration Systems (AES) Logistics Reduction (LR) project Heat Melt Compactor (HMC) technology is a waste management technology. Currently, there are...

  5. Situational Awareness and Logistics Division

    Data.gov (United States)

    Federal Laboratory Consortium — Volpe's Situational Awareness and Logistics Division researches, develops, implements, and analyzes advanced systems to protect, enhance, and ensure resilienceof the...

  6. Multivariate Time Series Decomposition into Oscillation Components.

    Science.gov (United States)

    Matsuda, Takeru; Komaki, Fumiyasu

    2017-08-01

    Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

  7. A note on Verhulst's logistic equation and related logistic maps

    International Nuclear Information System (INIS)

    Gutierrez, M Ranferi; Reyes, M A; Rosu, H C

    2010-01-01

    We consider the Verhulst logistic equation and a couple of forms of the corresponding logistic maps. For the case of the logistic equation we show that using the general Riccati solution only changes the initial conditions of the equation. Next, we consider two forms of corresponding logistic maps reporting the following results. For the map x n+1 = rx n (1 - x n ) we propose a new way to write the solution for r = -2 which allows better precision of the iterative terms, while for the map x n+1 - x n = rx n (1 - x n+1 ) we show that it behaves identically to the logistic equation from the standpoint of the general Riccati solution, which is also provided herein for any value of the parameter r.

  8. Development of a perfusion reversed-phase high performance liquid chromatography method for the characterisation of maize products using multivariate analysis.

    Science.gov (United States)

    Rodriguez-Nogales, J M; Garcia, M C; Marina, M L

    2006-02-03

    A perfusion reversed-phase high performance liquid chromatography (RP-HPLC) method has been designed to allow rapid (3.4 min) separations of maize proteins with high resolution. Several factors, such as extraction conditions, temperature, detection wavelength and type and concentration of ion-pairing agent were optimised. A fine optimisation of the gradient elution was also performed by applying experimental design. Commercial maize products for human consumption (flours, precocked flours, fried snacks and extruded snacks) were characterised for the first time by perfusion RP-HPLC and their chromatographic profiles allowed a differentiation among products relating the different technological process used for their preparation. Furthermore, applying discriminant analysis makes it possible to group the samples according with the technological process suffered by maize products, obtaining a good prediction in 92% of the samples.

  9. A comparison of dependence function estimators in multivariate extremes

    KAUST Repository

    Vettori, Sabrina; Huser, Raphaë l; Genton, Marc G.

    2017-01-01

    Various nonparametric and parametric estimators of extremal dependence have been proposed in the literature. Nonparametric methods commonly suffer from the curse of dimensionality and have been mostly implemented in extreme-value studies up to three dimensions, whereas parametric models can tackle higher-dimensional settings. In this paper, we assess, through a vast and systematic simulation study, the performance of classical and recently proposed estimators in multivariate settings. In particular, we first investigate the performance of nonparametric methods and then compare them with classical parametric approaches under symmetric and asymmetric dependence structures within the commonly used logistic family. We also explore two different ways to make nonparametric estimators satisfy the necessary dependence function shape constraints, finding a general improvement in estimator performance either (i) by substituting the estimator with its greatest convex minorant, developing a computational tool to implement this method for dimensions $$D\\ge 2$$D≥2 or (ii) by projecting the estimator onto a subspace of dependence functions satisfying such constraints and taking advantage of Bernstein–Bézier polynomials. Implementing the convex minorant method leads to better estimator performance as the dimensionality increases.

  10. A comparison of dependence function estimators in multivariate extremes

    KAUST Repository

    Vettori, Sabrina

    2017-05-11

    Various nonparametric and parametric estimators of extremal dependence have been proposed in the literature. Nonparametric methods commonly suffer from the curse of dimensionality and have been mostly implemented in extreme-value studies up to three dimensions, whereas parametric models can tackle higher-dimensional settings. In this paper, we assess, through a vast and systematic simulation study, the performance of classical and recently proposed estimators in multivariate settings. In particular, we first investigate the performance of nonparametric methods and then compare them with classical parametric approaches under symmetric and asymmetric dependence structures within the commonly used logistic family. We also explore two different ways to make nonparametric estimators satisfy the necessary dependence function shape constraints, finding a general improvement in estimator performance either (i) by substituting the estimator with its greatest convex minorant, developing a computational tool to implement this method for dimensions $$D\\\\ge 2$$D≥2 or (ii) by projecting the estimator onto a subspace of dependence functions satisfying such constraints and taking advantage of Bernstein–Bézier polynomials. Implementing the convex minorant method leads to better estimator performance as the dimensionality increases.

  11. Simulations of full multivariate Tweedie with flexible dependence structure

    DEFF Research Database (Denmark)

    Cuenin, Johann; Jørgensen, Bent; Kokonendji, Célestin C.

    2016-01-01

    The paper introduces a variables-in-common method for constructing and simulating multivariate Tweedie distribution, based on linear combinations of independent univariate Tweedie variables. The method is facilitated by the convolution and scaling properties of the Tweedie distributions, using....... The method allows simulation of multivariate distributions from many known, including the Gaussian, Poisson, non-central gamma, gamma and inverse Gaussian distributions....

  12. Multivariate analysis for the optimization of microfluidics-assisted nanoprecipitation method intended for the loading of small hydrophilic drugs into PLGA nanoparticles.

    Science.gov (United States)

    Chiesa, E; Dorati, R; Modena, T; Conti, B; Genta, I

    2018-01-30

    Design of Experiment-assisted evaluation of critical process (total flow rate, TFR, flow rate ratio, FRR) and formulation (polymer concentration and structure, drug:polymer ratio) variables in a novel microfluidics-based device, a staggered herringbone micromixer (SHM), for poly(lactic-co-glycolic acid) copolymer (PLGA) nanoparticles (NPs) manufacturing was performed in order to systematically evaluate and mathematically describe their effects on NPs sizes and drug encapsulation; a small hydrophilic moiety, N-acetylcysteine, was chosen as challenging model drug. SHM-assisted nanoprecipitation method consistently yielded NPs with tailor made sizes (in the range of 100-900 nm) and polydispersity index range from 0.061 to 0.286. Significant effects on NPs sizes were highlighted for TFR and FRR: increasing TFR (from 5 to 15 mL/min) and decreasing FRR (from 1:1 to 1:5 v/v, acetonitrile: buffer) NPs with mean diameter <200 nm were obtained. SHM technique allowed for flexible, application-specific tuning of PLGA NPs size using organic solvents with relatively low toxicity (acetone, acetonitrile), varying aqueous phase composition (Tris buffer vs PVA aqueous solution) and PLGA characteristics (Mw ranging from 25-90 kDa, capped or un-capped PLGA, different lactide:glycolide molar ratio). A very satisfactory N-Ac encapsulation efficiency (more than 67%) and a prolonged release (by 168 h) were achieved. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Multivariate optimization of a headspace solid-phase microextraction method followed by gas chromatography with mass spectrometry for the determination of terpenes in Nicotiana langsdorffii.

    Science.gov (United States)

    Ardini, Francisco; Carro, Marina Di; Abelmoschi, Maria Luisa; Grotti, Marco; Magi, Emanuele

    2014-07-01

    A simple and sensitive procedure based on headspace solid-phase microextraction and gas chromatography with mass spectrometry was developed for the determination of five terpenes (α-pinene, limonene, linalool, α-terpineol, and geraniol) in the leaves of Nicotiana langsdorffii. The microextraction conditions (extraction temperature, equilibration time, and extraction time) were optimized by means of a Doehlert design. The experimental design showed that, for α-pinene and limonene, a low temperature and a long extraction time were needed for optimal extraction, while linalool, α-terpineol, and geraniol required a high temperature and a long extraction time. The chosen compromise conditions were temperature 60°C, equilibration time 15 min and extraction time 50 min. The main analytical figures of the optimized method were evaluated; LODs ranged from 0.07 ng/g (α-pinene) to 8.0 ng/g (geraniol), while intraday and interday repeatability were in the range 10-17% and 9-13%, respectively. Finally, the procedure was applied to in vitro wild-type and transgenic specimens of N. langsdorffii subjected to abiotic stresses (chemical and heat stress). With the exception of geraniol (75-374 ng/g), low concentration levels of terpenes were measured (ng/g level or lower); some interesting variations in terpene concentration induced by abiotic stress were observed. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Model Checking Multivariate State Rewards

    DEFF Research Database (Denmark)

    Nielsen, Bo Friis; Nielson, Flemming; Nielson, Hanne Riis

    2010-01-01

    We consider continuous stochastic logics with state rewards that are interpreted over continuous time Markov chains. We show how results from multivariate phase type distributions can be used to obtain higher-order moments for multivariate state rewards (including covariance). We also generalise...

  15. Outsourcing Operational Logistics: Buyer Beware

    National Research Council Canada - National Science Library

    Woody, Lamont

    2003-01-01

    One of the key tasks from U.S. Secretary of Defense Donald H. Rumsfeld to his Service Chiefs is to reduce DOD's overall logistic cost and footprint while transforming the warfighter-to-logistics (tooth-to-tail) force structure...

  16. Logistic Regression: Concept and Application

    Science.gov (United States)

    Cokluk, Omay

    2010-01-01

    The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

  17. Simulation Integrated Design for Logistics

    NARCIS (Netherlands)

    Veeke, H.P.M.

    2003-01-01

    The design of an innovative logistic system is a complex problem in the solution of which many disciplines are involved. Each discipline developed its own way of conceptual modeling for a logistic system based on a mono disciplinary perception. In essence this leads to a communication problem

  18. Transport, logistics and the region

    NARCIS (Netherlands)

    Langen, de P.W.

    2010-01-01

    Cargo transport and logistics have a huge impact on sustainable (regional) economic development. Two broad (policy) challenges are center stage: enhancing co-location of logistics activities and improving efficiency in intermodal transport chains. Academic research can provide relevant insights for

  19. Application of the Multivariated Systemic Method to the determination of the environmental quality of the estuary of Ría of Huelva

    Directory of Open Access Journals (Sweden)

    Ricardo Arribas de Paz

    2004-12-01

    Full Text Available The estuary of Ría of Huelva, recognized like Reserve of the Biosphere by UNESCO, is affected by spills of diverse origin. The method Sistémico Multivariado (MSM, applied prior to harbor works or in economy, has been used to characterize the estuary in risk terms and environmental reliability. After determining the variables that take part and to describe the mechanisms of performance of toxics, these have been classified in cancerigenic and noncancerigenic. Criteria defined by Environmental Protection Agency have been used (EPA-EEUU, the “dose of reference” for the noncancerigenic ones, the “factor of fall” for the cancerigenic ones, paying attention to the “components of failure”. The reliability of the system has been analyzed and the one of each component, with which it must have the system “Ría of Huelva”, following methodology MSM on determination of the permissible reliability of a design system. The reliability of the system is despicable for the physiological conditions of the studied fish, meaning that determined species are condemned to their extinction or its absence of the place. One has seen the applicability of the MSM the characterization of the environmental state of certain environmental factors and ecosystems. Also it has been possible to state the precarious situation of the piscicolas species in Ría of Huelva and the importance of the synergic effect, in the model proposed, on the conditions that undergo the affected populations, in front of the model additive used habitually by the EPA.

  20. A self-consistent, multivariate method for the determination of gas-phase rate coefficients, applied to reactions of atmospheric VOCs and the hydroxyl radical

    Science.gov (United States)

    Shaw, Jacob T.; Lidster, Richard T.; Cryer, Danny R.; Ramirez, Noelia; Whiting, Fiona C.; Boustead, Graham A.; Whalley, Lisa K.; Ingham, Trevor; Rickard, Andrew R.; Dunmore, Rachel E.; Heard, Dwayne E.; Lewis, Ally C.; Carpenter, Lucy J.; Hamilton, Jacqui F.; Dillon, Terry J.

    2018-03-01

    Gas-phase rate coefficients are fundamental to understanding atmospheric chemistry, yet experimental data are not available for the oxidation reactions of many of the thousands of volatile organic compounds (VOCs) observed in the troposphere. Here, a new experimental method is reported for the simultaneous study of reactions between multiple different VOCs and OH, the most important daytime atmospheric radical oxidant. This technique is based upon established relative rate concepts but has the advantage of a much higher throughput of target VOCs. By evaluating multiple VOCs in each experiment, and through measurement of the depletion in each VOC after reaction with OH, the OH + VOC reaction rate coefficients can be derived. Results from experiments conducted under controlled laboratory conditions were in good agreement with the available literature for the reaction of 19 VOCs, prepared in synthetic gas mixtures, with OH. This approach was used to determine a rate coefficient for the reaction of OH with 2,3-dimethylpent-1-ene for the first time; k = 5.7 (±0.3) × 10-11 cm3 molecule-1 s-1. In addition, a further seven VOCs had only two, or fewer, individual OH rate coefficient measurements available in the literature. The results from this work were in good agreement with those measurements. A similar dataset, at an elevated temperature of 323 (±10) K, was used to determine new OH rate coefficients for 12 aromatic, 5 alkane, 5 alkene and 3 monoterpene VOC + OH reactions. In OH relative reactivity experiments that used ambient air at the University of York, a large number of different VOCs were observed, of which 23 were positively identified. Due to difficulties with detection limits and fully resolving peaks, only 19 OH rate coefficients were derived from these ambient air samples, including 10 reactions for which data were previously unavailable at the elevated reaction temperature of T = 323 (±10) K.

  1. Complementary biomarker-based methods for characterising Arctic sea ice conditions: A case study comparison between multivariate analysis and the PIP25 index

    Science.gov (United States)

    Köseoğlu, Denizcan; Belt, Simon T.; Smik, Lukas; Yao, Haoyi; Panieri, Giuliana; Knies, Jochen

    2018-02-01

    The discovery of IP25 as a qualitative biomarker proxy for Arctic sea ice and subsequent introduction of the so-called PIP25 index for semi-quantitative descriptions of sea ice conditions has significantly advanced our understanding of long-term paleo Arctic sea ice conditions over the past decade. We investigated the potential for classification tree (CT) models to provide a further approach to paleo Arctic sea ice reconstruction through analysis of a suite of highly branched isoprenoid (HBI) biomarkers in ca. 200 surface sediments from the Barents Sea. Four CT models constructed using different HBI assemblages revealed IP25 and an HBI triene as the most appropriate classifiers of sea ice conditions, achieving a >90% cross-validated classification rate. Additionally, lower model performance for locations in the Marginal Ice Zone (MIZ) highlighted difficulties in characterisation of this climatically-sensitive region. CT model classification and semi-quantitative PIP25-derived estimates of spring sea ice concentration (SpSIC) for four downcore records from the region were consistent, although agreement between proxy and satellite/observational records was weaker for a core from the west Svalbard margin, likely due to the highly variable sea ice conditions. The automatic selection of appropriate biomarkers for description of sea ice conditions, quantitative model assessment, and insensitivity to the c-factor used in the calculation of the PIP25 index are key attributes of the CT approach, and we provide an initial comparative assessment between these potentially complementary methods. The CT model should be capable of generating longer-term temporal shifts in sea ice conditions for the climatically sensitive Barents Sea.

  2. Quality of investments in logistics

    Directory of Open Access Journals (Sweden)

    Borut Jereb

    2014-06-01

    Full Text Available The issue problem of paper is that base on researches connected with analysis of investments in logistics based on the review of 100 pooled manuscripts from different sources (scientific journals and online magazines from 1996 to 2012 it was showed that there don't exist quality as well as leadership has no a good overview of the investment in logistics. It was claimed that the quality point of view should be demanding part of investments in logistics. Val Log was proposed as an answer to the issues of managing quality of investments in logistics at the tactical level in organizations. By Val Log it is possible to overcome the myth that logistics projects cost money while business projects bring money. Val Log also provides detailed instructions for goals and metrics for each process. By doing changes the quality should be the obvious pillar of our affords doing it.

  3. Risk assessment of logistics outsourcing based on BP neural network

    Science.gov (United States)

    Liu, Xiaofeng; Tian, Zi-you

    The purpose of this article is to evaluate the risk of the enterprises logistics outsourcing. To get this goal, the paper first analysed he main risks existing in the logistics outsourcing, and then set up a risk evaluation index system of the logistics outsourcing; second applied BP neural network into the logistics outsourcing risk evaluation and used MATLAB to the simulation. It proved that the network error is small and has strong practicability. And this method can be used by enterprises to evaluate the risks of logistics outsourcing.

  4. Space Shuttle Orbiter logistics - Managing in a dynamic environment

    Science.gov (United States)

    Renfroe, Michael B.; Bradshaw, Kimberly

    1990-01-01

    The importance and methods of monitoring logistics vital signs, logistics data sources and acquisition, and converting data into useful management information are presented. With the launch and landing site for the Shuttle Orbiter project at the Kennedy Space Center now totally responsible for its own supportability posture, it is imperative that logistics resource requirements and management be continually monitored and reassessed. Detailed graphs and data concerning various aspects of logistics activities including objectives, inventory operating levels, customer environment, and data sources are provided. Finally, some lessons learned from the Shuttle Orbiter project and logistics options which should be considered by other space programs are discussed.

  5. A self-consistent, multivariate method for the determination of gas-phase rate coefficients, applied to reactions of atmospheric VOCs and the hydroxyl radical

    Directory of Open Access Journals (Sweden)

    J. T. Shaw

    2018-03-01

    Full Text Available Gas-phase rate coefficients are fundamental to understanding atmospheric chemistry, yet experimental data are not available for the oxidation reactions of many of the thousands of volatile organic compounds (VOCs observed in the troposphere. Here, a new experimental method is reported for the simultaneous study of reactions between multiple different VOCs and OH, the most important daytime atmospheric radical oxidant. This technique is based upon established relative rate concepts but has the advantage of a much higher throughput of target VOCs. By evaluating multiple VOCs in each experiment, and through measurement of the depletion in each VOC after reaction with OH, the OH + VOC reaction rate coefficients can be derived. Results from experiments conducted under controlled laboratory conditions were in good agreement with the available literature for the reaction of 19 VOCs, prepared in synthetic gas mixtures, with OH. This approach was used to determine a rate coefficient for the reaction of OH with 2,3-dimethylpent-1-ene for the first time; k =  5.7 (±0.3  ×  10−11 cm3 molecule−1 s−1. In addition, a further seven VOCs had only two, or fewer, individual OH rate coefficient measurements available in the literature. The results from this work were in good agreement with those measurements. A similar dataset, at an elevated temperature of 323 (±10 K, was used to determine new OH rate coefficients for 12 aromatic, 5 alkane, 5 alkene and 3 monoterpene VOC + OH reactions. In OH relative reactivity experiments that used ambient air at the University of York, a large number of different VOCs were observed, of which 23 were positively identified. Due to difficulties with detection limits and fully resolving peaks, only 19 OH rate coefficients were derived from these ambient air samples, including 10 reactions for which data were previously unavailable at the elevated reaction temperature of T =  323 (±10 K.

  6. Multivariate statistics high-dimensional and large-sample approximations

    CERN Document Server

    Fujikoshi, Yasunori; Shimizu, Ryoichi

    2010-01-01

    A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic

  7. Fully conditional specification in multivariate imputation

    NARCIS (Netherlands)

    van Buuren, S.; Brand, J. P.L.; Groothuis-Oudshoorn, C. G.M.; Rubin, D. B.

    2006-01-01

    The use of the Gibbs sampler with fully conditionally specified models, where the distribution of each variable given the other variables is the starting point, has become a popular method to create imputations in incomplete multivariate data. The theoretical weakness of this approach is that the

  8. Application of correlation constrained multivariate curve resolution alternating least-squares methods for determination of compounds of interest in biodiesel blends using NIR and UV-visible spectroscopic data.

    Science.gov (United States)

    de Oliveira, Rodrigo Rocha; de Lima, Kássio Michell Gomes; Tauler, Romà; de Juan, Anna

    2014-07-01

    This study describes two applications of a variant of the multivariate curve resolution alternating least squares (MCR-ALS) method with a correlation constraint. The first application describes the use of MCR-ALS for the determination of biodiesel concentrations in biodiesel blends using near infrared (NIR) spectroscopic data. In the second application, the proposed method allowed the determination of the synthetic antioxidant N,N'-Di-sec-butyl-p-phenylenediamine (PDA) present in biodiesel mixtures from different vegetable sources using UV-visible spectroscopy. Well established multivariate regression algorithm, partial least squares (PLS), were calculated for comparison of the quantification performance in the models developed in both applications. The correlation constraint has been adapted to handle the presence of batch-to-batch matrix effects due to ageing effects, which might occur when different groups of samples were used to build a calibration model in the first application. Different data set configurations and diverse modes of application of the correlation constraint are explored and guidelines are given to cope with different type of analytical problems, such as the correction of matrix effects among biodiesel samples, where MCR-ALS outperformed PLS reducing the relative error of prediction RE (%) from 9.82% to 4.85% in the first application, or the determination of minor compound with overlapped weak spectroscopic signals, where MCR-ALS gave higher (RE (%)=3.16%) for prediction of PDA compared to PLS (RE (%)=1.99%), but with the advantage of recovering the related pure spectral profile of analytes and interferences. The obtained results show the potential of the MCR-ALS method with correlation constraint to be adapted to diverse data set configurations and analytical problems related to the determination of biodiesel mixtures and added compounds therein. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Multivariable nonlinear analysis of foreign exchange rates

    Science.gov (United States)

    Suzuki, Tomoya; Ikeguchi, Tohru; Suzuki, Masuo

    2003-05-01

    We analyze the multivariable time series of foreign exchange rates. These are price movements that have often been analyzed, and dealing time intervals and spreads between bid and ask prices. Considering dealing time intervals as event timing such as neurons’ firings, we use raster plots (RPs) and peri-stimulus time histograms (PSTHs) which are popular methods in the field of neurophysiology. Introducing special processings to obtaining RPs and PSTHs time histograms for analyzing exchange rates time series, we discover that there exists dynamical interaction among three variables. We also find that adopting multivariables leads to improvements of prediction accuracy.

  10. A MATLAB companion for multivariable calculus

    CERN Document Server

    Cooper, Jeffery

    2001-01-01

    Offering a concise collection of MatLab programs and exercises to accompany a third semester course in multivariable calculus, A MatLab Companion for Multivariable Calculus introduces simple numerical procedures such as numerical differentiation, numerical integration and Newton''s method in several variables, thereby allowing students to tackle realistic problems. The many examples show students how to use MatLab effectively and easily in many contexts. Numerous exercises in mathematics and applications areas are presented, graded from routine to more demanding projects requiring some programming. Matlab M-files are provided on the Harcourt/Academic Press web site at http://www.harcourt-ap.com/matlab.html.* Computer-oriented material that complements the essential topics in multivariable calculus* Main ideas presented with examples of computations and graphics displays using MATLAB * Numerous examples of short code in the text, which can be modified for use with the exercises* MATLAB files are used to implem...

  11. Using Cultural Algorithms to Improve Intelligent Logistics

    Science.gov (United States)

    Ochoa, Alberto; García, Yazmani; Yañez, Javier; Teymanoglu, Yaddik

    Today the issue of logistics is a very important within companies to the extent that some have departments devoted exclusively to it. This has evolved over time and today is a fundamental aspect in the fight business seeking to consolidate or remain leaders in their field. With the above we know that logistics can be divided into different classes, however, in this regard, our study is based on the timely distribution to the customer with a lower cost, higher sales and better utilization of space resulting in excellent service. Finally, prepare a comparative analysis of the results with respect to another method of optimization solution space.

  12. Radiosurgery and the double logistic product formula

    International Nuclear Information System (INIS)

    Flickinger, J.C.; Steiner, L.

    1990-01-01

    The double logistic product formula is proposed as a method for predicting the probability of developing brain necrosis after high dose irradiation of small target volumes as used in stereotactic radiosurgery. Dose-response data observed for the production of localized radiation necreosis for treating intractable pain with the original Leksell gamma unit were used to choose the best fitting parameters for the double logistic product formula. This model can be used with either exponential or linear quadratic formulas to account for the effects of dose, fractionation and time in addition to volume. Dose-response predictions for stereotactic radiosurgery with different sized collimators are presented. (author). 41 refs.; 5 figs.; 1 tab

  13. The PIT-trap-A "model-free" bootstrap procedure for inference about regression models with discrete, multivariate responses.

    Science.gov (United States)

    Warton, David I; Thibaut, Loïc; Wang, Yi Alice

    2017-01-01

    Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not identically distributed (thus not amenable to bootstrapping)-common examples including logistic or Poisson regression and generalizations to handle clustered or multivariate data, such as generalised estimating equations. We propose a bootstrap method based on probability integral transform (PIT-) residuals, which we call the PIT-trap, which assumes data come from some marginal distribution F of known parametric form. This method can be understood as a type of "model-free bootstrap", adapted to the problem of discrete and highly multivariate data. PIT-residuals have the key property that they are (asymptotically) pivotal. The PIT-trap thus inherits the key property, not afforded by any other residual resampling approach, that the marginal distribution of data can be preserved under PIT-trapping. This in turn enables the derivation of some standard bootstrap properties, including second-order correctness of pivotal PIT-trap test statistics. In multivariate data, bootstrapping rows of PIT-residuals affords the property that it preserves correlation in data without the need for it to be modelled, a key point of difference as compared to a parametric bootstrap. The proposed method is illustrated on an example involving multivariate abundance data in ecology, and demonstrated via simulation to have improved properties as compared to competing resampling methods.

  14. Logistics management skills development: A Zimbabwean case

    Directory of Open Access Journals (Sweden)

    Jacobus N. Cronjé

    2015-02-01

    Full Text Available Background: Since logistics emerged as an applied discipline during the latter part of the 20th century, there has been an increased need for skills development in logistics and supply chain management. However, literature suggests a general shortage of educated and skilled logistics and supply chain managers worldwide. Objectives: The purpose of this article was to benchmark an in-house training programme in logistics management in the beverage industry of Zimbabwe with international best practice. Method: A case study approach was followed focusing on the programme curriculum, content and delivery. The article reports on the nature and effectiveness of the programme. The curriculum was benchmarked with skills requirements identified in literature. Relevance was evaluated based on participant perceptions over a period of 3 years using questionnaires with both closed- and open-ended questions. Results: Findings suggested that the programme offering is in line with international practice whilst it also addresses particular issues in Third World countries. Participants perceived the programme as being practical and valuable for enhancing their job performance and career development. Conclusion: The article provides a framework for evaluating logistics training programmes. Future research could include an evaluation that measures changes in on-the-job behaviour of participants.

  15. Logistics planning and logistics planning factors for humanitarian operations

    OpenAIRE

    Sullivan, Donna Marie.

    1995-01-01

    Due to the increasing demand on the military to conduct humanitarian operations, the need for logistics planning factors that are applicable to these operations has arisen. This thesis develops a model for humanitarian operations and employs the model to develop logistics planning factors for material consumption and a computer-assisted planning aid relating to the support of the victim population. U.S. Navy (U.S.N.) author.

  16. A primer of multivariate statistics

    CERN Document Server

    Harris, Richard J

    2014-01-01

    Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why

  17. Use of multivariate extensions of generalized linear models in the analysis of data from clinical trials

    OpenAIRE

    ALONSO ABAD, Ariel; Rodriguez, O.; TIBALDI, Fabian; CORTINAS ABRAHANTES, Jose

    2002-01-01

    In medical studies the categorical endpoints are quite often. Even though nowadays some models for handling this multicategorical variables have been developed their use is not common. This work shows an application of the Multivariate Generalized Linear Models to the analysis of Clinical Trials data. After a theoretical introduction models for ordinal and nominal responses are applied and the main results are discussed. multivariate analysis; multivariate logistic regression; multicategor...

  18. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.

    2015-12-03

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  19. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.

    2015-05-08

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  20. Multivariate localization methods for ensemble Kalman filtering

    Science.gov (United States)

    Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.

    2015-12-01

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  1. Multivariate localization methods for ensemble Kalman filtering

    OpenAIRE

    S. Roh; M. Jun; I. Szunyogh; M. G. Genton

    2015-01-01

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of ...

  2. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.; Jun, M.; Szunyogh, I.; Genton, Marc G.

    2015-01-01

    the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function

  3. Multivariate localization methods for ensemble Kalman filtering

    KAUST Repository

    Roh, S.; Jun, M.; Szunyogh, I.; Genton, Marc G.

    2015-01-01

    In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.

  4. Development of logistics information systems

    Directory of Open Access Journals (Sweden)

    Milan Ž. Dronjak

    2012-10-01

    Full Text Available An adequate logistics information system provides real time automated data processing, distribution and of information according to Terrain Commander's requirements, which leads to timely fulfillment of logistic demands of units. SAP ERP The SAP ERP application is the integrated (ERP software capable of working with complex organisational structures, personnel, equipment, and finance. It enables planning and combining forces for every type of operations. The system also enables the determination of the readiness status of modelled forces. ISL The Information System for Logistics (ISL is a comprehensive information system of the Ministry of Defence (MoD and the Army of the Czech Republic that covers many areas: acquisition, supply, ammunition and equipment maintenance, logistics, etc. The ISL provides support for military logistics in all important areas of consumer and acquisition logistics, satisfaying all kinds of Defence Forces needs in the country and abroad. LOGFAS The information system LOGFAS comprises Logistics Database (LOGBASE, Movement and Transportation software (M&T, Allied Command Europe Resource Optimisation Software System (ACROSS and Logistic Reporting System (LOGREP. The Logistics Database LOGBASE represents a logistics information source and also a database related to assets, forces, geography, infrastructure, targets, supplies, movements and medical data. The main software tools which rely on the LOGBASE are M&T, ACROSS and LOGREP. GCSS-Army The original impetus to create the SALE came in the mid-90s when the United States Department of Defense (DoD started a logistics modernisation programme. One of tasks was to build The Single Army Logistics Enterprise (SALE for the purpose of covering the whole organisational structure of the DoD. There are three components of the SALE: GCSS-Army, PLM+ and LMP. Each of them uses the commercial Enterprise Resource Planning SAP Software with a Web access. The main component, GCSS

  5. I - Multivariate Classification and Machine Learning in HEP

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    Traditional multivariate methods for classification (Stochastic Gradient Boosted Decision Trees and Multi-Layer Perceptrons) are explained in theory and practise using examples from HEP. General aspects of multivariate classification are discussed, in particular different regularisation techniques. Afterwards, data-driven techniques are introduced and compared to MC-based methods.

  6. Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

    Directory of Open Access Journals (Sweden)

    Santana Isabel

    2011-08-01

    Full Text Available Abstract Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI, but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing.

  7. Logistics in smallpox: the legacy.

    Science.gov (United States)

    Wickett, John; Carrasco, Peter

    2011-12-30

    Logistics, defined as "the time-related positioning of resources" was critical to the implementation of the smallpox eradication strategy of surveillance and containment. Logistical challenges in the smallpox programme included vaccine delivery, supplies, staffing, vehicle maintenance, and financing. Ensuring mobility was essential as health workers had to travel to outbreaks to contain them. Three examples illustrate a range of logistic challenges which required imagination and innovation. Standard price lists were developed to expedite vehicle maintenance and repair in Bihar, India. Innovative staffing ensured an adequate infrastructure for vehicle maintenance in Bangladesh. The use of disaster relief mechanisms in Somalia provided airlifts, vehicles and funding within 27 days of their initiation. In contrast the Expanded Programme on Immunization (EPI) faces more complex logistical challenges. Copyright © 2011 Elsevier Ltd. All rights reserved.

  8. Multiagent Systems in Logistics Environment

    National Research Council Canada - National Science Library

    Kumara, R

    2000-01-01

    ... the cost added to the price of the products. This is a typical logistics problem. Under some assumptions, this problem can be solved through negotiation in a forum of candidate transportation companies...

  9. Logistics Reduction and Repurposing Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The project enables a largely mission-independent, cradle-to-grave-to-cradle approach to minimize logistics contributions to total mission architecture mass. The...

  10. Case Study on Logistics Performance

    Directory of Open Access Journals (Sweden)

    Shahryar Sorooshian

    2013-05-01

    Full Text Available The paper presents research carried out at a medium‐size manufacturing organization in east Asia. The study tries to highlight the importance of supply chain management; specifically, our aim for this study is to understand logistics and performance measurement in the logistics and supply chain, and we include a theoretical discussion of online data collected and a case study of the logistic performance of a real organization. The study also examines the performance of the selected company, identifies the problems and provides recommendations for improvements. This study can be a guide for business advisers and those interested in analysing company performance, especially from a logistics viewpoint. We also suggest the methodology of this case study for those who want to have a better understanding of a business environment before starting their own business, or for benchmarking practice during strategic planning.

  11. Defense Logistics Agency Revenue Eliminations

    National Research Council Canada - National Science Library

    1996-01-01

    The issue of revenue eliminations was identified during our work on the Defense Logistics Agency portion of the Audit of Revenue Accounts in the FY 1996 Financial Statements of the Defense Business Operations Fund...

  12. Joint Logistics, Fact or Fiction?

    National Research Council Canada - National Science Library

    Carroll, Walton

    1998-01-01

    ...) and the evolution of Joint doctrine to meet these new demands. The focus of this examination remains at the strategic level and the ability of the Services to meet the logistical demands of the modern theater battlefield...

  13. Multivariate Welch t-test on distances

    OpenAIRE

    Alekseyenko, Alexander V.

    2016-01-01

    Motivation: Permutational non-Euclidean analysis of variance, PERMANOVA, is routinely used in exploratory analysis of multivariate datasets to draw conclusions about the significance of patterns visualized through dimension reduction. This method recognizes that pairwise distance matrix between observations is sufficient to compute within and between group sums of squares necessary to form the (pseudo) F statistic. Moreover, not only Euclidean, but arbitrary distances can be used. This method...

  14. OWI transportation/logistics program

    International Nuclear Information System (INIS)

    Shappert, L.B.; Joy, D.S.; Heiskell, M.M.; Turner, D.W.

    1978-01-01

    In development of a comprehensive plan to assure the availability of a transport system by 1985 capable of moving commercial radioactive wastes to federal waste repositories, a series of concerns were identified as having the potential to interfere seriously with the overall objective. These are tabulated and briefly reviewed. Activities to counteract these concerns were formulated. Logistics models were then developed. The spent fuel logistics model is described

  15. INFORMATION SECURITY IN LOGISTICS COOPERATION

    Directory of Open Access Journals (Sweden)

    Tomasz Małkus

    2015-03-01

    Full Text Available Cooperation of suppliers of raw materials, semi-finished products, finished products, wholesalers, retailers in the form of the supply chain, as well as outsourcing of specialized logistics service require ensuring adequate support of information. It concerns the use of appropriate computer tools. The security of information in such conditions of collaboration becomes the important problem for parties of contract. The objective of the paper is to characterize main issues relating to security of information in logistics cooperation.

  16. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

    The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...

  17. NASA Space Rocket Logistics Challenges

    Science.gov (United States)

    Neeley, James R.; Jones, James V.; Watson, Michael D.; Bramon, Christopher J.; Inman, Sharon K.; Tuttle, Loraine

    2014-01-01

    The Space Launch System (SLS) is the new NASA heavy lift launch vehicle and is scheduled for its first mission in 2017. The goal of the first mission, which will be uncrewed, is to demonstrate the integrated system performance of the SLS rocket and spacecraft before a crewed flight in 2021. SLS has many of the same logistics challenges as any other large scale program. Common logistics concerns for SLS include integration of discreet programs geographically separated, multiple prime contractors with distinct and different goals, schedule pressures and funding constraints. However, SLS also faces unique challenges. The new program is a confluence of new hardware and heritage, with heritage hardware constituting seventy-five percent of the program. This unique approach to design makes logistics concerns such as commonality especially problematic. Additionally, a very low manifest rate of one flight every four years makes logistics comparatively expensive. That, along with the SLS architecture being developed using a block upgrade evolutionary approach, exacerbates long-range planning for supportability considerations. These common and unique logistics challenges must be clearly identified and tackled to allow SLS to have a successful program. This paper will address the common and unique challenges facing the SLS programs, along with the analysis and decisions the NASA Logistics engineers are making to mitigate the threats posed by each.

  18. The system for statistical analysis of logistic information

    Directory of Open Access Journals (Sweden)

    Khayrullin Rustam Zinnatullovich

    2015-05-01

    Full Text Available The current problem for managers in logistic and trading companies is the task of improving the operational business performance and developing the logistics support of sales. The development of logistics sales supposes development and implementation of a set of works for the development of the existing warehouse facilities, including both a detailed description of the work performed, and the timing of their implementation. Logistics engineering of warehouse complex includes such tasks as: determining the number and the types of technological zones, calculation of the required number of loading-unloading places, development of storage structures, development and pre-sales preparation zones, development of specifications of storage types, selection of loading-unloading equipment, detailed planning of warehouse logistics system, creation of architectural-planning decisions, selection of information-processing equipment, etc. The currently used ERP and WMS systems did not allow us to solve the full list of logistics engineering problems. In this regard, the development of specialized software products, taking into account the specifics of warehouse logistics, and subsequent integration of these software with ERP and WMS systems seems to be a current task. In this paper we suggest a system of statistical analysis of logistics information, designed to meet the challenges of logistics engineering and planning. The system is based on the methods of statistical data processing.The proposed specialized software is designed to improve the efficiency of the operating business and the development of logistics support of sales. The system is based on the methods of statistical data processing, the methods of assessment and prediction of logistics performance, the methods for the determination and calculation of the data required for registration, storage and processing of metal products, as well as the methods for planning the reconstruction and development

  19. Multivariate missing data in hydrology - Review and applications

    Science.gov (United States)

    Ben Aissia, Mohamed-Aymen; Chebana, Fateh; Ouarda, Taha B. M. J.

    2017-12-01

    Water resources planning and management require complete data sets of a number of hydrological variables, such as flood peaks and volumes. However, hydrologists are often faced with the problem of missing data (MD) in hydrological databases. Several methods are used to deal with the imputation of MD. During the last decade, multivariate approaches have gained popularity in the field of hydrology, especially in hydrological frequency analysis (HFA). However, treating the MD remains neglected in the multivariate HFA literature whereas the focus has been mainly on the modeling component. For a complete analysis and in order to optimize the use of data, MD should also be treated in the multivariate setting prior to modeling and inference. Imputation of MD in the multivariate hydrological framework can have direct implications on the quality of the estimation. Indeed, the dependence between the series represents important additional information that can be included in the imputation process. The objective of the present paper is to highlight the importance of treating MD in multivariate hydrological frequency analysis by reviewing and applying multivariate imputation methods and by comparing univariate and multivariate imputation methods. An application is carried out for multiple flood attributes on three sites in order to evaluate the performance of the different methods based on the leave-one-out procedure. The results indicate that, the performance of imputation methods can be improved by adopting the multivariate setting, compared to mean substitution and interpolation methods, especially when using the copula-based approach.

  20. Multivariate Statistical Process Control Charts: An Overview

    OpenAIRE

    Bersimis, Sotiris; Psarakis, Stelios; Panaretos, John

    2006-01-01

    In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as p...

  1. Factors Associated with Increased Pain in Primary Dysmenorrhea: Analysis Using a Multivariate Ordered Logistic Regression Model.

    Science.gov (United States)

    Tomás-Rodríguez, María I; Palazón-Bru, Antonio; Martínez-St John, Damian R J; Navarro-Cremades, Felipe; Toledo-Marhuenda, José V; Gil-Guillén, Vicente F

    2017-04-01

    In the literature about primary dysmenorrhea (PD), either a pain gradient has been studied just in women with PD or pain was assessed as a binary variable (presence or absence). Accordingly, we decided to carry out a study in young women to determine possible factors associated with intense pain. A cross-sectional observational study. A Spanish University in 2016. A total of 306 women, aged 18-30 years. A questionnaire was filled in by the participants to assess associated factors with dysmenorrhoea. Our outcome measure was the Andersch and Milsom scale (grade from 0 to 3). grade 0 (menstruation is not painful and daily activity is unaffected), grade 1 (menstruation is painful but seldom inhibits normal activity, analgesics are seldom required, and mild pain), grade 2 (daily activity affected, analgesics required and give relief so that absence from work or school is unusual, and moderate pain), and grade 3 (activity clearly inhibited, poor effect of analgesics, vegetative symptoms and severe pain). Factors significantly associated with more extreme pain: a higher menstrual flow (odds ratio [OR], 2.11; P < .001), a worse quality of life (OR, 0.97; P < .001) and use of medication for PD (OR, 8.22; P < .001). We determined factors associated with extreme pain in PD in a novel way. Further studies are required to corroborate our results. Copyright © 2016 North American Society for Pediatric and Adolescent Gynecology. Published by Elsevier Inc. All rights reserved.

  2. Multivariate Generalized Multiscale Entropy Analysis

    Directory of Open Access Journals (Sweden)

    Anne Humeau-Heurtier

    2016-11-01

    Full Text Available Multiscale entropy (MSE was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii the computation of the sample entropy for each coarse-grained time series. A refined composite MSE (rcMSE—based on the same steps as MSE—also exists. Compared to MSE, rcMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy for short time series. The multivariate versions of MSE (MMSE and rcMSE (MrcMSE have also been introduced. In the coarse-graining step used in MSE, rcMSE, MMSE, and MrcMSE, the mean value is used to derive representations of the original data at different resolutions. A generalization of MSE was recently published, using the computation of different moments in the coarse-graining procedure. However, so far, this generalization only exists for univariate signals. We therefore herein propose an extension of this generalized MSE to multivariate data. The multivariate generalized algorithms of MMSE and MrcMSE presented herein (MGMSE and MGrcMSE, respectively are first analyzed through the processing of synthetic signals. We reveal that MGrcMSE shows better performance than MGMSE for short multivariate data. We then study the performance of MGrcMSE on two sets of short multivariate electroencephalograms (EEG available in the public domain. We report that MGrcMSE may show better performance than MrcMSE in distinguishing different types of multivariate EEG data. MGrcMSE could therefore supplement MMSE or MrcMSE in the processing of multivariate datasets.

  3. Logistics Management: New trends in the Reverse Logistics

    Science.gov (United States)

    Antonyová, A.; Antony, P.; Soewito, B.

    2016-04-01

    Present level and quality of the environment are directly dependent on our access to natural resources, as well as their sustainability. In particular production activities and phenomena associated with it have a direct impact on the future of our planet. Recycling process, which in large enterprises often becomes an important and integral part of the production program, is usually in small and medium-sized enterprises problematic. We can specify a few factors, which have direct impact on the development and successful application of the effective reverse logistics system. Find the ways to economically acceptable model of reverse logistics, focusing on converting waste materials for renewable energy, is the task in progress.

  4. Annual National Logistics Conference and Exhibition (26th) (BRIEFING CHARTS)

    Science.gov (United States)

    2010-04-15

    Operations Division, Office of the Chief of Naval Operations (OPNAV N41) Luncheon Speaker · BrigGen Mike Dana , USMC, Director of Logistics...Speaker u BrigGen Mike Dana , USMC, Director of Logistics & Engineering, J4, NORAD and USNORTHCOM u Col Alex Vohr, USMC, Director of Logistics, J4...are the Core Elements of a Curriculum on Contemporary Strategy, and What are the Best Methods of Teaching Them? Dr Richard Betts, Arnold A. Saltzman

  5. Challenges of Green Logistics in Southeast Europe

    OpenAIRE

    Beškovnik, Bojan; Jakomin, Livio

    2010-01-01

    This paper describes the trends towards green logistics in global aspect and challenges of adopting green logistics in the region of Southeast Europe. Modern logistics with supply chain management is experiencing a period of important evolution. From reversible logistics, we came to green logistics, which is a wider concept of environmentally friendly thinking. Reverse logistics includes processes of movements and transportation of waste from users to recycling plants; meanwhile, green logist...

  6. Procesoptimerende multivariable regulatorer til kraftværkskedler. Process Optimizing Multivariable Controllers for Powerplant Boilers

    DEFF Research Database (Denmark)

    Hansen, T.

    The purpose of this Ph.D. thesis is twofold: The first purpose is to devise a new method for application of multivariable controllers in boiler control systems in which they act as optional process optimizing extensions to conventional control systems and in such a way that the safety measures...... mentioned, the concept is applicable to new as well as existing plants. The seccond purpose is to suggest specific methods for experimental modelling and multivariable controller design which are possible to use under the conceptual framework, implement them and test them in a boiler application....

  7. Multivariate Bonferroni-type inequalities theory and applications

    CERN Document Server

    Chen, John

    2014-01-01

    Multivariate Bonferroni-Type Inequalities: Theory and Applications presents a systematic account of research discoveries on multivariate Bonferroni-type inequalities published in the past decade. The emergence of new bounding approaches pushes the conventional definitions of optimal inequalities and demands new insights into linear and Fréchet optimality. The book explores these advances in bounding techniques with corresponding innovative applications. It presents the method of linear programming for multivariate bounds, multivariate hybrid bounds, sub-Markovian bounds, and bounds using Hamil

  8. Planning model of purchasing logistics in outsourcing

    Directory of Open Access Journals (Sweden)

    Igor JAKOMIN

    2014-03-01

    Full Text Available It is often the case that when preparing their offers, potential outsourcers of logistic activities do not thoroughly research all the activities that have an influence on the process of logistics. Consequently, they prepare relatively expensive offers (that can later lead to greater unexpected costs which, in many cases, business partners decide against and persist with their own existing methods of doing business. The original contribution to science in this article is a model that will aid better understanding of dealing with problems and will, in practice, serve as a tool for the successful execution of business offers by outsourcers. Following research we have discovered, and are able to confirm, that despite the high start-up costs of the outsourcing, in the long term the company can reduce logistic costs. The model presented serves as an in-depth analysis of the company which enables the definition of favourable and optimal offers for outsourcing. The model shown helps to minimise the influence of mistrust and emphasises the importance of reducing the logistic costs with outsourcing.

  9. An optimal hierarchical decision model for a regional logistics network with environmental impact consideration.

    Science.gov (United States)

    Zhang, Dezhi; Li, Shuangyan; Qin, Jin

    2014-01-01

    This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

  10. An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

    Directory of Open Access Journals (Sweden)

    Dezhi Zhang

    2014-01-01

    Full Text Available This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users’ demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators’ service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

  11. An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

    Science.gov (United States)

    Zhang, Dezhi; Li, Shuangyan

    2014-01-01

    This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level. PMID:24977209

  12. Production-logistic system in the aspect of strategies for production planning and control and for logistic customer service

    OpenAIRE

    Łukasz Hadaś; Agnieszka Stachowiak; Piotr Cyplik

    2014-01-01

    Background: The authors made multi-dimensional review of production and logistic strategies in order to prove their coherence in shaping internal and external supply chain. The paper is concluded with definition of production-logistic system as an object of modeling in transformation of business systems of manufacturing companies. Material and methods: The paper is based on analysis of state of the art presented in the literature on the subject of production and logistics strategies. Publ...

  13. Multivariate Process Control with Autocorrelated Data

    DEFF Research Database (Denmark)

    Kulahci, Murat

    2011-01-01

    As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control and monitoring. This new high dimensional data...... often exhibit not only cross-­‐correlation among the quality characteristics of interest but also serial dependence as a consequence of high sampling frequency and system dynamics. In practice, the most common method of monitoring multivariate data is through what is called the Hotelling’s T2 statistic....... In this paper, we discuss the effect of autocorrelation (when it is ignored) on multivariate control charts based on these methods and provide some practical suggestions and remedies to overcome this problem....

  14. Multivariate stochastic simulation with subjective multivariate normal distributions

    Science.gov (United States)

    P. J. Ince; J. Buongiorno

    1991-01-01

    In many applications of Monte Carlo simulation in forestry or forest products, it may be known that some variables are correlated. However, for simplicity, in most simulations it has been assumed that random variables are independently distributed. This report describes an alternative Monte Carlo simulation technique for subjectively assesed multivariate normal...

  15. REGIONAL LOGISTICS CENTER: FORMATION AND FUNCTIONING SPESIFIC

    Directory of Open Access Journals (Sweden)

    Oleg Tkach

    2017-08-01

    Full Text Available In this article the essence of the definition of logistics centers is defined, the main provisions concerning the formation of the logistics center are defined. The formation of a logistic hub is analyzed. The structure of the transport-logistic center is proposed. The basic requirements for the location of the regional logistics center and the principles of its operation are determined. The financial and financial mechanism of a typical logistics center and their effective functioning are presented. It is proved that the most important component of the logistics center is transport. Key words: logistics centers, logistics, hub, distribution centers, transport and logistics centers, regional logistic centers, logistics complex, transport, transport-logistic system.

  16. The transport performance evaluation system building of logistics enterprises

    Directory of Open Access Journals (Sweden)

    Xueli Wang

    2013-09-01

    Full Text Available Purpose: modern logistics has a significant role in today’s society, logistics cost accounts for 35% to 50% of total logistics costs, so it’s great significance to improve the transport performance of logistics enterprises. Design/methodology/approach: the authors select the transportation performance evaluation index of logistics enterprise, with the aid of the fuzzy theory and analytic hierarchy process (AHP, adopt the combining method of quantitative and qualitative analysis, construct the transport performance evaluation system of logistics enterprises. Findings: the choice of transport performance evaluation indicator system for Logistics enterprise is in a state of "high", which indicates the indicator selection is reasonable. Research limitations/implications: the selected indicators with experts’ subjective factors can not accurately quantify. Practical implications: it has important practical significance to promote the development of modern logistics enterprises and save social cost. Originality/value: current research methods mainly include the PDCA cycle model, key performance indicators (KPI and benchmarking method, principal component analysis method, etc. The authors for the first time with the aid of fuzzy theory and analytic hierarchy process (AHP, adopt the combining method of quantitative and qualitative research on transport performance problems.

  17. Logistics require savvy negotiation, patience

    International Nuclear Information System (INIS)

    Talboy, R.G.

    1991-01-01

    In the Soviet Union, logistics are affected by the extraordinary political, social and physical environment, so that operations are virtually all art, rather than science. Furthermore, this art, as it applies to a particular project, probably does not lend itself to broad generalizations about what would work somewhere else. Each project will have its own idiosyncrasies, depending on its type and location in the vast Soviet republics, and upon the personalities involved. This article discusses only the logistics that worked out and are still evolving for the project with which the author was associated

  18. Logistics background study: underground mining

    Energy Technology Data Exchange (ETDEWEB)

    Hanslovan, J. J.; Visovsky, R. G.

    1982-02-01

    Logistical functions that are normally associated with US underground coal mining are investigated and analyzed. These functions imply all activities and services that support the producing sections of the mine. The report provides a better understanding of how these functions impact coal production in terms of time, cost, and safety. Major underground logistics activities are analyzed and include: transportation and personnel, supplies and equipment; transportation of coal and rock; electrical distribution and communications systems; water handling; hydraulics; and ventilation systems. Recommended areas for future research are identified and prioritized.

  19. Seasonality and the logistic map

    International Nuclear Information System (INIS)

    Silva, Emily; Peacock-Lopez, Enrique

    2017-01-01

    Nonlinear difference equations, such as the logistic map, have been used to study chaos and also to model population dynamics. Here we propose a model that extends the “lose + lose = win” behavior found in Parrondo’s Paradox, where switching between chaotic parameters in the logistic map yields periodic behavior (“chaos + chaos = order”). The model uses twelve parameters each reflecting the conditions of one of the twelve months. In this paper we study the effects of smooth-transitioning parameters and the robust system that emerges.

  20. Multivariate Matrix-Exponential Distributions

    DEFF Research Database (Denmark)

    Bladt, Mogens; Nielsen, Bo Friis

    2010-01-01

    be written as linear combinations of the elements in the exponential of a matrix. For this reason we shall refer to multivariate distributions with rational Laplace transform as multivariate matrix-exponential distributions (MVME). The marginal distributions of an MVME are univariate matrix......-exponential distributions. We prove a characterization that states that a distribution is an MVME distribution if and only if all non-negative, non-null linear combinations of the coordinates have a univariate matrix-exponential distribution. This theorem is analog to a well-known characterization theorem...

  1. Complications from arteriovenous malformation radiosurgery: multivariate analysis and risk modeling

    International Nuclear Information System (INIS)

    Flickinger, John C.; Kondziolka, Douglas; Pollock, Bruce E.; Maitz, Ann H.; Lunsford, L. Dade

    1997-01-01

    Purpose/Objective: To assess the relationships of radiosurgery treatment parameters to the development of complications from radiosurgery for arteriovenous malformations (AVM). Methods and Materials: We evaluated follow-up imaging and clinical data in 307 AVM patients who received gamma knife radiosurgery at the University of Pittsburgh between 1987 and 1993. All patients had regular clinical or imaging follow up for a minimum of 2 years (range: 24-96 months, median = 44 months). Results: Post-radiosurgical imaging (PRI) changes developed in 30.5% of patients with regular follow-up magnetic resonance imaging, and were symptomatic in 10.7% of all patients at 7 years. PRI changes resolved within 3 years developed significantly less often (p = 0.0274) in patients with symptoms (52.8%) compared to asymptomatic patients (94.8%). The 7-year actuarial rate for developing persistent symptomatic PRI changes was 5.05%. Multivariate logistic regression modeling found that the 12 Gy volume was the only independent variable that correlated significantly with PRI changes (p < 0.0001) while symptomatic PRI changes were correlated with both 12 Gy volume (p = 0.0013) and AVM location (p 0.0066). Conclusion: Complications from AVM radiosurgery can be predicted with a statistical model relating the risks of developing symptomatic post-radiosurgical imaging changes to 12 Gy treatment volume and location

  2. Synthetic environmental indicators: A conceptual approach from the multivariate statistics

    International Nuclear Information System (INIS)

    Escobar J, Luis A

    2008-01-01

    This paper presents a general description of multivariate statistical analysis and shows two methodologies: analysis of principal components and analysis of distance, DP2. Both methods use techniques of multivariate analysis to define the true dimension of data, which is useful to estimate indicators of environmental quality.

  3. Planning and management of logistic cycle

    OpenAIRE

    V. N. Kudashkin

    2017-01-01

    We are considering planning and managing of logistic cycle, its impact on the content of the main processes that comprise the cycle to implement the order for the supply of material resources for industrial consumption, as well as its practical use, effectiveness, and prospects.This research paper is made on the basis of the information, received from textbooks and scientific literature of domestic and foreign authors, as well as from other sources. The main methods, used in this work are as ...

  4. The influence of logistics potentials on business management

    Directory of Open Access Journals (Sweden)

    Rafał Matwiejczuk

    2012-09-01

    Full Text Available Background: Logistics is more and more often perceived as an integrated potential of changes in a business management system. Among the particular potentials, the key importance is assigned to logistics resources, capabilities, and particularly competences. Methods: The article points at exploitation of possibilities of logistics potentials in achieving desired changes in business management and reaching desired market and economic effects by a company. Except for literature studies, empirical research has been conducted in 111 companies operating in Poland.  Results and conclusions:  Research results have shown several symptoms of logistics influence on business management system. The significance of logistics potentials in business management system capacity development has been partially confirmed. Due to logistics potentials, the company can be more effective and efficient in reaching expected market and economic outcomes.  

  5. Halal Logistics Implementation in Malaysia: A Practical View

    Science.gov (United States)

    Sham, Rohana; Zuraidah Rasi, Raja; Abdamia, Noranita; Mohamed, Suhana; Thahira Bibi, TKM

    2017-08-01

    Concept of halal is not only acceptable world wide by the Muslim society but also to the non Muslim. However, the implementing of halal logistics in daily operation experience a few difficulties especially on the implementation part. Although there are many academic research paper that highlight the issue of halal logistics and the critical success factor, until today, halal logistics in Malaysia is still experiencing a hiccup. This paper try to highlight a few simple ways of implementation of halal logistics that could enhance the total implementation concept at the very least cost to create benefit to all society. The Paper deals with a few aspect of possible implementation and practice to facilitate the halal logistics approach in daily operation. The main objective is to look at the possible method of implementation and critical success factors towards the implementation of halal logistics operation in daily goods movement in Malaysia.

  6. Análise de rentabilidade de uma rede logística: novo método de cálculo Logistic network profitability analysis: a new computing method

    Directory of Open Access Journals (Sweden)

    Reinaldo Pacheco da Costa

    2008-12-01

    Full Text Available Este artigo apresenta um método de cálculo de rentabilidade econômica de unidades operacionais (UOs de empresas de transporte de carga fracionada que operam através de uma rede logística com múltiplas UOs. O cálculo da rentabilidade econômica de cada uma destas UOs é um problema complexo. Devido ao intercâmbio de cargas entre UOs, as receitas de uma UO estão interligadas com as receitas de outras UOs. Os métodos tradicionais de contabilização enfrentam dificuldades quando empregados para determinar a rentabilidade econômica de UOs de uma rede logística de UOs interdependentes. O método descrito neste artigo elimina estas dificuldades por meio do conceito de margem de contribuição.This paper offers a method for evaluating the profitability of operation sites (OS of less-than-truckload (LTL carriers conveying shipments through a network with multiple OS. The evaluation of the profitability of each one of these OS is a complex problem. Due to exchanges of shipments between OS, the revenues of one OS are intertwined with the revenues of other OS. Traditional accounting methods show themselves cumbersome when employed to evaluate the profitability of OS of a logistical network of interdependent OS. The method described in this paper overcomes these difficulties by means of the concept of contribution margin.

  7. Logistics Dynamics and Demographic Change

    NARCIS (Netherlands)

    Klumpp, Matthias; Abidi, Hella; Bioly, Sascha; Buchkremer, Rüdiger; Ebener, Stefan; Sandhaus, Gregor; Freitag, Michael; Kotzab, Herbert; Pannek, Jürgen

    2016-01-01

    Change and dynamics in logistics are interestingly driven at the same time by external as well as internal forces. This contribution outlines a big data literature review methodology to overview recognizable external changes and analyzes the interaction of one major trend—demographic change—further

  8. CONCEPTUAL ISSUES REGARDING REVERSE LOGISTICS

    Directory of Open Access Journals (Sweden)

    Ioana Olariu

    2013-12-01

    Full Text Available As the power of consumers is growing, the product return for customer service and customer retention has become a common practice in the competitive market, which propels the recent practice of reverse logistics in companies. Many firms attracted by the value available in the flow, have proactively participated in handling returned products at the end of their usefulness or from other parts of the product life cycle. Reverse logistics is the flow and management of products, packaging, components and information from the point of consumption to the point of origin. It is a collection of practices similar to those of supply chain management, but in the opposite direction, from downstream to upstream. It involves activities such as reuse, repair, remanufacture, refurbish, reclaim and recycle. For the conventional forward logistics systems, the flow starts upstream as raw materials, later as manufactured parts and components to be assembled and continues downstream to reach customers as final products to be disposed once they reach their economic or useful lives. In reverse logistics, the disposed products are pushed upstream to be repaired, remanufactured, refurbished, and disassembled into components to be reused or as raw material to be recycled for later use.

  9. A Framework for Reverse Logistics

    NARCIS (Netherlands)

    M.P. de Brito (Marisa); R. Dekker (Rommert)

    2003-01-01

    textabstractReverse Logistics has been stretching out worldwide, involving all the layers of supply chains in various industry sectors. While some actors in the chain have been forced to take products back, others have pro-actively done so, attracted by the value in used products One way or the

  10. Quantitative Models for Reverse Logistics

    NARCIS (Netherlands)

    M. Fleischmann (Moritz)

    2000-01-01

    markdownabstractEconomic, marketing, and legislative considerations are increasingly leading companies to take back and recover their products after use. From a logistics perspective, these initiatives give rise to new goods flows from the user back to the producer. The management of these goods

  11. Woody biomass logistics [Chapter 14

    Science.gov (United States)

    Robert Keefe; Nathaniel Anderson; John Hogland; Ken Muhlenfeld

    2014-01-01

    The economics of using woody biomass as a fuel or feedstock for bioenergy applications is often driven by logistical considerations. Depending on the source of the woody biomass, the acquisition cost of the material is often quite low, sometimes near zero. However, the cost of harvesting, collection, processing, storage, and transportation from the harvest site to end...

  12. Sustainable logistics. Sustainability of logistic centres by means of evaluation of emissions, protection of ressources and energy efficiency; Sustainable logistics. Nachhaltigkeit von Logistikzentren durch Emissionsbewertung, Ressourcenschonung und Energieeffizienz

    Energy Technology Data Exchange (ETDEWEB)

    Zadek, Hartmut; Schulz, Robert (eds.)

    2011-07-01

    The discussion on climate change and availability of limited resources shows that resource conservation and energy efficiency in today's targets of companies are under-represented. Cost efficiency and increase of the shareholder value with respect to a measurable success determine the daily operations. The author of the contribution under consideration considers logistics centers and supply processes for manufacturing companies. After describing basic approaches to sustainability in logistics an inventory follows based on a study of logistics service providers and manufacturing companies. Methods and tools for the evaluation of CO{sub 2} emissions and resource consumption are presented. A guideline for the development of buildings, energy audits and renewable energies is considered, identified solutions to energy-efficient logistics and modernization are given, selected best-practice examples of sustainable logistics centers are presented. The contribution ends with strategic derivation targeted at policy and state as well as companies and management.

  13. The Multivariate Gaussian Probability Distribution

    DEFF Research Database (Denmark)

    Ahrendt, Peter

    2005-01-01

    This technical report intends to gather information about the multivariate gaussian distribution, that was previously not (at least to my knowledge) to be found in one place and written as a reference manual. Additionally, some useful tips and tricks are collected that may be useful in practical ...

  14. A "Model" Multivariable Calculus Course.

    Science.gov (United States)

    Beckmann, Charlene E.; Schlicker, Steven J.

    1999-01-01

    Describes a rich, investigative approach to multivariable calculus. Introduces a project in which students construct physical models of surfaces that represent real-life applications of their choice. The models, along with student-selected datasets, serve as vehicles to study most of the concepts of the course from both continuous and discrete…

  15. SELECTED PROBLEMS OF REVERSE LOGISTICS IN POLAND

    OpenAIRE

    Agata Mesjasz-Lech

    2009-01-01

    This paper presents the essence of reverse logistics and directions of physical and information flows between logistic network partners. It also analyses effects of implementation of the principles of reverse logistics in Poland in the years 2004-2007

  16. Desempenho de sistemas consorciados de cenoura e alface avaliados através de métodos uni e multivariados Biological performance of carrot and lettuce intercropping systems as assessed through uni- and multivariate methods

    Directory of Open Access Journals (Sweden)

    Francisco Bezerra Neto

    2007-12-01

    , observou-se diferença significativa entre os valores dos índices combinados (produtividade equivalente de cenoura, eficiência produtiva, uso eficiente da terra e escore da variável canônica apenas quando eles foram avaliados através do escore normalizado da variável canônica, com maior eficiência dos sistemas quando a cenoura foi consorciada com a alface 'Lucy Brown'. Os sistemas consorciados de cenoura 'Alvorada' + alface 'Lucy Brown' ou de cenoura 'Brasília' + alface 'Lucy Brown' são aqueles a serem indicados ao produtor.Intercropping experiments' data analysis is usually a complex task, as compared to those data analysis from sole crops. In these cases are recommended univariate analysis of variance for each crop yield; intercropping combined systems yields; productive efficiency measured with data envelopment analysis (DEA models; and multivariate analysis. In this work we evaluated the biological performance of carrot and crisphead lettuce intercropping systems through uni- and multivariate methods. Two experiments (one in intercropping and another in sole crop were carried out in a randomized complete block design with four replications. The intercropping experiment was designed in a 2 x 4 + 2 factorial scheme, with the treatments stemmed from the combination of two carrot cultivars (Alvorada and Brasília with four crisphead lettuce cultivars (Lucy Brown, Tainá, Laurel and Verônica plus two carrot cultivars in sole crop. The treatments of the experiment in sole crop consisted of those crisphead lettuce cvs. tested in intercropping experiment. The evaluated traits in lettuce and carrot crops were shoot fresh mass and commercial root yield, respectively. Uni- and multivariate analyses of variance were accomplished on these crop traits in function of the tested treatment-factors. The multivariate approach was more informative as compared to the univariated method, as it allowed better discrimination of the treatment-factors, beyond the description of the

  17. Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure.

    Science.gov (United States)

    Li, Yanming; Nan, Bin; Zhu, Ji

    2015-06-01

    We propose a multivariate sparse group lasso variable selection and estimation method for data with high-dimensional predictors as well as high-dimensional response variables. The method is carried out through a penalized multivariate multiple linear regression model with an arbitrary group structure for the regression coefficient matrix. It suits many biology studies well in detecting associations between multiple traits and multiple predictors, with each trait and each predictor embedded in some biological functional groups such as genes, pathways or brain regions. The method is able to effectively remove unimportant groups as well as unimportant individual coefficients within important groups, particularly for large p small n problems, and is flexible in handling various complex group structures such as overlapping or nested or multilevel hierarchical structures. The method is evaluated through extensive simulations with comparisons to the conventional lasso and group lasso methods, and is applied to an eQTL association study. © 2015, The International Biometric Society.

  18. INTERNATIONAL LOGISTICS SYSTEMS DESIGN AND EFFECTIVENESS EVALUATION

    Directory of Open Access Journals (Sweden)

    N. V. Khalipova

    2015-08-01

    Full Text Available Purpose. In the paper the question of the development of a methodological approach to the determination of logistics systems’ performance and grounding of the most effective goods’ delivery schemes, based on the theory of functions and sets of multiple objects, vector optimization approaches and discrete maximum principle for multi-stage processes (phase method is considered. Methodology. To achieve the goals of the research, the model of logistic system represented by multiple object that defined by the structure and content. The object is represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and inhomogeneous sets (sequences, corteges, which at each stage of cargo delivery present sets of technological operations of their processing, choices and decisions algorithms. Multiple structure of objects is constructive three, consisting of the carrier, signatures and axiomatic. To determine the effective scheme of delivery, applied discrete maximum principle using vector optimization criterion. Findings. In this article, logistics system of delivery is presented in the form of a multi-stage (phase of the process. Each stage reviews a plurality of discrete activities sets, which includes the possible technology cycles of operations in goods handling. At each stage of a multi-phase delivery process from the supplier to the consumer, these sets are different. Considered a model example solving the problem of vector optimization options for delivery of goods by the road in the international logistics system for the five-step process. Optimization performed on the basis of three indicators. Originality. In this paper, the choice of the most effective way of delivery goods produced using the theory of functions and sets of multiple objects, using the discrete maximum principle for multi-stage processes, based on the vector optimization criterion. At each of its stages are formed a plurality of valid solutions as

  19. Crisis Management- Operational Logistics & Asset Visibility Technologies

    National Research Council Canada - National Science Library

    Braunbeck, Richard A; Mastria, Michael F

    2006-01-01

    The purpose of this MBA Project was to identify and explore logistical frameworks that leverage technology to overcome problems associated with coordinated logistics operations during crisis management...

  20. Logistics Support of Naval Expeditionary Units

    National Research Council Canada - National Science Library

    Nilsen, Jan

    2004-01-01

    .... Based on literature from strategic management, logistics, and supply chain management, the research evaluates the existing theater logistics capabilities and the requirements of the supported expeditionary units...