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

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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.

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...

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

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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.     

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...

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.

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.

Cooperation between partners in logistics outsourcing

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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.

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

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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.

Methods for Analyzing Multivariate Phenotypes in Genetic Association Studies

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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.

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...

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.

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

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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.

PROGRAMMING OF METHODS FOR THE NEEDS OF LOGISTICS DISTRIBUTION SOLVING PROBLEMS

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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.

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

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.

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

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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.

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...

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)

Classification of Specialized Farms Applying Multivariate Statistical Methods

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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.

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

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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.

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

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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.

Multivariate Methods Based Soft Measurement for Wine Quality Evaluation

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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.

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

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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.

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

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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.

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.

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...

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

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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.

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.

Local Strategy Combined with a Wavelength Selection Method for Multivariate Calibration

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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.

Analysis Of The Logistics Intermediaries Choice Methods In The Supply Chains

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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.

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.

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...

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

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.

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

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.

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

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...

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

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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.

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

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...

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.

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.

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...

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 ...

Comparative multivariate analyses of transient otoacoustic emissions and distorsion products in normal and impaired hearing.

Science.gov (United States)

Stamate, Mirela Cristina; Todor, Nicolae; Cosgarea, Marcel

2015-01-01

The clinical utility of otoacoustic emissions as a noninvasive objective test of cochlear function has been long studied. Both transient otoacoustic emissions and distorsion products can be used to identify hearing loss, but to what extent they can be used as predictors for hearing loss is still debated. Most studies agree that multivariate analyses have better test performances than univariate analyses. The aim of the study was to determine transient otoacoustic emissions and distorsion products performance in identifying normal and impaired hearing loss, using the pure tone audiogram as a gold standard procedure and different multivariate statistical approaches. The study included 105 adult subjects with normal hearing and hearing loss who underwent the same test battery: pure-tone audiometry, tympanometry, otoacoustic emission tests. We chose to use the logistic regression as a multivariate statistical technique. Three logistic regression models were developed to characterize the relations between different risk factors (age, sex, tinnitus, demographic features, cochlear status defined by otoacoustic emissions) and hearing status defined by pure-tone audiometry. The multivariate analyses allow the calculation of the logistic score, which is a combination of the inputs, weighted by coefficients, calculated within the analyses. The accuracy of each model was assessed using receiver operating characteristics curve analysis. We used the logistic score to generate receivers operating curves and to estimate the areas under the curves in order to compare different multivariate analyses. We compared the performance of each otoacoustic emission (transient, distorsion product) using three different multivariate analyses for each ear, when multi-frequency gold standards were used. We demonstrated that all multivariate analyses provided high values of the area under the curve proving the performance of the otoacoustic emissions. Each otoacoustic emission test presented high

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.

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.

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.

Education in logistics and training of non-logistic personnel

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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

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 ...

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

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.

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....

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.

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.

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.

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.

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.

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

Science.gov (United States)

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

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...

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

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

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.

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...

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...

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

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.

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

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.

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).

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.

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.

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.

Logistic regression analysis of factors associated with avascular necrosis of the femoral head following femoral neck fractures in middle-aged and elderly patients.

Science.gov (United States)

Ai, Zi-Sheng; Gao, You-Shui; Sun, Yuan; Liu, Yue; Zhang, Chang-Qing; Jiang, Cheng-Hua

2013-03-01

Risk factors for femoral neck fracture-induced avascular necrosis of the femoral head have not been elucidated clearly in middle-aged and elderly patients. Moreover, the high incidence of screw removal in China and its effect on the fate of the involved femoral head require statistical methods to reflect their intrinsic relationship. Ninety-nine patients older than 45 years with femoral neck fracture were treated by internal fixation between May 1999 and April 2004. Descriptive analysis, interaction analysis between associated factors, single factor logistic regression, multivariate logistic regression, and detailed interaction analysis were employed to explore potential relationships among associated factors. Avascular necrosis of the femoral head was found in 15 cases (15.2 %). Age × the status of implants (removal vs. maintenance) and gender × the timing of reduction were interactive according to two-factor interactive analysis. Age, the displacement of fractures, the quality of reduction, and the status of implants were found to be significant factors in single factor logistic regression analysis. Age, age × the status of implants, and the quality of reduction were found to be significant factors in multivariate logistic regression analysis. In fine interaction analysis after multivariate logistic regression analysis, implant removal was the most important risk factor for avascular necrosis in 56-to-85-year-old patients, with a risk ratio of 26.00 (95 % CI = 3.076-219.747). The middle-aged and elderly have less incidence of avascular necrosis of the femoral head following femoral neck fractures treated by cannulated screws. The removal of cannulated screws can induce a significantly high incidence of avascular necrosis of the femoral head in elderly patients, while a high-quality reduction is helpful to reduce avascular necrosis.

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

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.

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

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

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.

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

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.

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.

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.

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

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.

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...

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....

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

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 ...

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

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

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.

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

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.

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.

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.

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

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.

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...

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.

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.

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.

Using Logistic Regression To Predict the Probability of Debris Flows Occurring in Areas Recently Burned By Wildland Fires

Science.gov (United States)

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.

2003-01-01

Logistic regression was used to predict the probability of debris flows occurring in areas recently burned by wildland fires. Multiple logistic regression is conceptually similar to multiple linear regression because statistical relations between one dependent variable and several independent variables are evaluated. In logistic regression, however, the dependent variable is transformed to a binary variable (debris flow did or did not occur), and the actual probability of the debris flow occurring is statistically modeled. Data from 399 basins located within 15 wildland fires that burned during 2000-2002 in Colorado, Idaho, Montana, and New Mexico were evaluated. More than 35 independent variables describing the burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows were delineated from National Elevation Data using a Geographic Information System (GIS). (2) Data describing the burn severity, geology, land surface gradient, rainfall, and soil properties were determined for each basin. These data were then downloaded to a statistics software package for analysis using logistic regression. (3) Relations between the occurrence/non-occurrence of debris flows and burn severity, geology, land surface gradient, rainfall, and soil properties were evaluated and several preliminary multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combination produced the most effective model. The multivariate model that best predicted the occurrence of debris flows was selected. (4) The multivariate logistic regression model was entered into a GIS, and a map showing the probability of debris flows was constructed. The most effective model incorporates the percentage of each basin with slope greater than 30 percent, percentage of land burned at medium and high burn severity

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 ...

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.

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...

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

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.

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.

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

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)

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

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.

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...

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)

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.

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

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....

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

Logistic regression applied to natural hazards: rare event logistic regression with replications

Science.gov (United States)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

Multivariate Normal Tissue Complication Probability Modeling of Heart Valve Dysfunction in Hodgkin Lymphoma Survivors

International Nuclear Information System (INIS)

Cella, Laura; Liuzzi, Raffaele; Conson, Manuel; D’Avino, Vittoria; Salvatore, Marco; Pacelli, Roberto

2013-01-01

Purpose: To establish a multivariate normal tissue complication probability (NTCP) model for radiation-induced asymptomatic heart valvular defects (RVD). Methods and Materials: Fifty-six patients treated with sequential chemoradiation therapy for Hodgkin lymphoma (HL) were retrospectively reviewed for RVD events. Clinical information along with whole heart, cardiac chambers, and lung dose distribution parameters was collected, and the correlations to RVD were analyzed by means of Spearman's rank correlation coefficient (Rs). For the selection of the model order and parameters for NTCP modeling, a multivariate logistic regression method using resampling techniques (bootstrapping) was applied. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). Results: When we analyzed the whole heart, a 3-variable NTCP model including the maximum dose, whole heart volume, and lung volume was shown to be the optimal predictive model for RVD (Rs = 0.573, P<.001, AUC = 0.83). When we analyzed the cardiac chambers individually, for the left atrium and for the left ventricle, an NTCP model based on 3 variables including the percentage volume exceeding 30 Gy (V30), cardiac chamber volume, and lung volume was selected as the most predictive model (Rs = 0.539, P<.001, AUC = 0.83; and Rs = 0.557, P<.001, AUC = 0.82, respectively). The NTCP values increase as heart maximum dose or cardiac chambers V30 increase. They also increase with larger volumes of the heart or cardiac chambers and decrease when lung volume is larger. Conclusions: We propose logistic NTCP models for RVD considering not only heart irradiation dose but also the combined effects of lung and heart volumes. Our study establishes the statistical evidence of the indirect effect of lung size on radio-induced heart toxicity

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.

Customer satisfaction with the quality of the logistic services

Directory of Open Access Journals (Sweden)

Małgorzata Lisińska-Kuśnierz

2014-03-01

Full Text Available Background: Logistics services are evaluated mainly by measuring customer satisfaction. Measurement of the customer satisfaction provides the information about how organizations operate as well as how to effectively satisfy customer needs. The aim of this paper is to propose an evaluation model of the customer satisfaction of the quality of the logistic services provided. The research in this paper was focused on the evaluation of the level of customer satisfaction in the context of logistics service as well as on the analysis of importance of ten logistic services attributes influencing customer satisfaction. Methods: The research was conducted on the basis of the questionnaire designed for purchasers of logistic services. The subjects of the research were companies which are using refrigerated transport. Results: To define relation between level of customer satisfaction in the context of logistic service and logistic service attributes impacting this satisfaction Pearson's correlation method was used. In turn the model to evaluate the customer satisfaction in the context of logistic services in scope of refrigerated transport was built using multiple regression and stepwise regression methods.

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.

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

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,

Logistic regression applied to natural hazards: rare event logistic regression with replications

Directory of Open Access Journals (Sweden)

M. Guns

2012-06-01

Full Text Available Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

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...

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

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 ...

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...

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.

Using the Logistic Regression model in supporting decisions of establishing marketing strategies

Directory of Open Access Journals (Sweden)

Cristinel CONSTANTIN

2015-12-01

Full Text Available This paper is about an instrumental research regarding the using of Logistic Regression model for data analysis in marketing research. The decision makers inside different organisation need relevant information to support their decisions regarding the marketing strategies. The data provided by marketing research could be computed in various ways but the multivariate data analysis models can enhance the utility of the information. Among these models we can find the Logistic Regression model, which is used for dichotomous variables. Our research is based on explanation the utility of this model and interpretation of the resulted information in order to help practitioners and researchers to use it in their future investigations

Predicting Success in Product Development: The Application of Principal Component Analysis to Categorical Data and Binomial Logistic Regression

Directory of Open Access Journals (Sweden)

Glauco H.S. Mendes

2013-09-01

Full Text Available Critical success factors in new product development (NPD in the Brazilian small and medium enterprises (SMEs are identified and analyzed. Critical success factors are best practices that can be used to improve NPD management and performance in a company. However, the traditional method for identifying these factors is survey methods. Subsequently, the collected data are reduced through traditional multivariate analysis. The objective of this work is to develop a logistic regression model for predicting the success or failure of the new product development. This model allows for an evaluation and prioritization of resource commitments. The results will be helpful for guiding management actions, as one way to improve NPD performance in those industries.

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.

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.

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...

[Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

Science.gov (United States)

Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

2015-05-12

To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

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...

Robust mislabel logistic regression without modeling mislabel probabilities.

Science.gov (United States)

Hung, Hung; Jou, Zhi-Yu; Huang, Su-Yun

2018-03-01

Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting a conventional logistic regression can then lead to biased estimation. One common resolution is to fit a mislabel logistic regression model, which takes into consideration of mislabeled responses. Another common method is to adopt a robust M-estimation by down-weighting suspected instances. In this work, we propose a new robust mislabel logistic regression based on γ-divergence. Our proposal possesses two advantageous features: (1) It does not need to model the mislabel probabilities. (2) The minimum γ-divergence estimation leads to a weighted estimating equation without the need to include any bias correction term, that is, it is automatically bias-corrected. These features make the proposed γ-logistic regression more robust in model fitting and more intuitive for model interpretation through a simple weighting scheme. Our method is also easy to implement, and two types of algorithms are included. Simulation studies and the Pima data application are presented to demonstrate the performance of γ-logistic regression. © 2017, The International Biometric Society.

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.

Evaluation of functional outcome of the floating knee injury using multivariate analysis.

Science.gov (United States)

Yokoyama, Kazuhiko; Tsukamoto, Tatsuro; Aoki, Shinichi; Wakita, Ryuji; Uchino, Masataka; Noumi, Takashi; Fukushima, Nobuaki; Itoman, Moritoshi

2002-11-01

The objective of this study is to evaluate significant contributing factors affecting the functional prognosis of floating knee injuries using multivariate analysis. A total of 68 floating knee injuries (67 patients) were treated at Kitasato University Hospital from 1986 to 1999. Both the femoral fractures and the tibial fractures were managed surgically by various methods. The functional results of these injuries were evaluated using the grading system of Karlström and Olerud. Follow-up periods ranged from 2 to 19 years (mean 50.2 months) after the original injury. We defined satisfactory (S) outcomes as those cases with excellent or good results and unsatisfactory (US) outcomes as those cases with acceptable or poor results. Logistic regression analysis was used as a multivariate analysis, and the dependent variables were defined as a satisfactory outcome or as an unsatisfactory outcome. The explanatory variables were predicting factors influencing the functional outcome such as age at trauma, gender, severity of soft-tissue injury in the femur and the tibia, AO fracture grade in the femur and the tibia, Fraser type (type I or type II), Injury Severity Score (ISS), and fixation time after injury (less than 1 week or more than 1 week) in the femur and the tibia. The final functional results were as follows: 25 cases had excellent results, 15 cases good results, 16 cases acceptable results, and 12 cases poor results. The predictive logistic regression equation was as follows: Log 1-p/p = 3.12-1.52 x Fraser type - 1.65 x severity of soft-tissue injury in the tibia - 1.31 x fixation time after injury in the tibia - 0.821 x AO fracture grade in the tibia + 1.025 x fixation time after injury in the femur - 0.687 x AO fracture grade in the femur ( p=0.01). Among the variables, Fraser type and the severity of soft-tissue injury in the tibia were significantly related to the final result. The multivariate analysis showed that both the involvement of the knee joint and

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.

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.

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.

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...

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.

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...

Sample size determination for logistic regression on a logit-normal distribution.

Science.gov (United States)

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

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. ...

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

Empirical Study of E-logistics System Based on Tibet Logistics Industry

OpenAIRE

Liu, Yu

2013-01-01

With the rapid growth of E-logistics in the global logistics industry, it is important to get insight into E-logistics system in Chinese logistics industry. Regarding the current situation of E-logistics of Chinese logistics industry, there are still many problems to be concerned and resolved. This paper will review the concepts and theoretical background of E-logistics System from previous researches. After acknowledging the essential issues on E-logistics System, a research model is designe...

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

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

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)

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).

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: ...

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.

Indices system design of distribution logistics, transport logistics and materials flow as parts of controlling in enterprise´s logistics

Directory of Open Access Journals (Sweden)

Andrea Rosová

2010-02-01

Full Text Available There is necessary to think about two aspects while applying controlling in logistics. The main aim of the logistics in relationto business economics is assessing support to the invested financial capital resources – it is the first aspect. The second one is basedon the target of controlling – continuous monitoring of company’s economy. In order to make a logistics controlling successful and withrequired results it is necessary to utilize any logistics controlling tools. One of the tools in logistics controlling is a set of indicators.Important part of controlling logistics system is monitoring and evaluation of logistics markers. Logistic markers representsynthetic view to logistic performance and logistic costs by the means of interaction rate so that it can evaluate logistic activities area,cost economy and final productivity of logistics activities in company.This contribution deals with markers system proposal of distribution logistics, transport logistics and materials flow control.System of markers is designed with regard to basic facilities and specifications, who has to copy character and disposition rememberedsubsystems enterprise’s logistics system.

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...

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.

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

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.

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.

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.

Using Logistic Regression to Predict the Probability of Debris Flows in Areas Burned by Wildfires, Southern California, 2003-2006

Science.gov (United States)

Rupert, Michael G.; Cannon, Susan H.; Gartner, Joseph E.; Michael, John A.; Helsel, Dennis R.

2008-01-01

Logistic regression was used to develop statistical models that can be used to predict the probability of debris flows in areas recently burned by wildfires by using data from 14 wildfires that burned in southern California during 2003-2006. Twenty-eight independent variables describing the basin morphology, burn severity, rainfall, and soil properties of 306 drainage basins located within those burned areas were evaluated. The models were developed as follows: (1) Basins that did and did not produce debris flows soon after the 2003 to 2006 fires were delineated from data in the National Elevation Dataset using a geographic information system; (2) Data describing the basin morphology, burn severity, rainfall, and soil properties were compiled for each basin. These data were then input to a statistics software package for analysis using logistic regression; and (3) Relations between the occurrence or absence of debris flows and the basin morphology, burn severity, rainfall, and soil properties were evaluated, and five multivariate logistic regression models were constructed. All possible combinations of independent variables were evaluated to determine which combinations produced the most effective models, and the multivariate models that best predicted the occurrence of debris flows were identified. Percentage of high burn severity and 3-hour peak rainfall intensity were significant variables in all models. Soil organic matter content and soil clay content were significant variables in all models except Model 5. Soil slope was a significant variable in all models except Model 4. The most suitable model can be selected from these five models on the basis of the availability of independent variables in the particular area of interest and field checking of probability maps. The multivariate logistic regression models can be entered into a geographic information system, and maps showing the probability of debris flows can be constructed in recently burned areas of

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

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.

Multivariate Local Polynomial Regression with Application to Shenzhen Component Index

Directory of Open Access Journals (Sweden)

Liyun Su

2011-01-01

Full Text Available This study attempts to characterize and predict stock index series in Shenzhen stock market using the concepts of multivariate local polynomial regression. Based on nonlinearity and chaos of the stock index time series, multivariate local polynomial prediction methods and univariate local polynomial prediction method, all of which use the concept of phase space reconstruction according to Takens' Theorem, are considered. To fit the stock index series, the single series changes into bivariate series. To evaluate the results, the multivariate predictor for bivariate time series based on multivariate local polynomial model is compared with univariate predictor with the same Shenzhen stock index data. The numerical results obtained by Shenzhen component index show that the prediction mean squared error of the multivariate predictor is much smaller than the univariate one and is much better than the existed three methods. Even if the last half of the training data are used in the multivariate predictor, the prediction mean squared error is smaller than the univariate predictor. Multivariate local polynomial prediction model for nonsingle time series is a useful tool for stock market price prediction.

Handbook of univariate and multivariate data analysis with IBM SPSS

CERN Document Server

Ho, Robert

2013-01-01

Using the same accessible, hands-on approach as its best-selling predecessor, the Handbook of Univariate and Multivariate Data Analysis with IBM SPSS, Second Edition explains how to apply statistical tests to experimental findings, identify the assumptions underlying the tests, and interpret the findings. This second edition now covers more topics and has been updated with the SPSS statistical package for Windows.New to the Second EditionThree new chapters on multiple discriminant analysis, logistic regression, and canonical correlationNew section on how to deal with missing dataCoverage of te

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

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.

Logistics potentials in business competitive advantage creation

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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.

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....

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

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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.

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...

Multivariate Analysis and Machine Learning in Cerebral Palsy Research.

Science.gov (United States)

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.

SPD-based Logistics Management Model of Medical Consumables in Hospitals

Science.gov (United States)

LIU, Tongzhu; SHEN, Aizong; HU, Xiaojian; TONG, Guixian; GU, Wei; YANG, Shanlin

2016-01-01

Background: With the rapid development of health services, the progress of medical science and technology, and the improvement of materials research, the consumption of medical consumables (MCs) in medical activities has increased in recent years. However, owing to the lack of effective management methods and the complexity of MCs, there are several management problems including MC waste, low management efficiency, high management difficulty, and frequent medical accidents. Therefore, there is urgent need for an effective logistics management model to handle these problems and challenges in hospitals. Methods: We reviewed books and scientific literature (by searching the articles published from 2010 to 2015 in Engineering Village database) to understand supply chain related theories and methods and performed field investigations in hospitals across many cities to determine the actual state of MC logistics management of hospitals in China. Results: We describe the definition, physical model, construction, and logistics operation processes of the supply, processing, and distribution (SPD) of MC logistics because of the traditional SPD model. With the establishment of a supply-procurement platform and a logistics lean management system, we applied the model to the MC logistics management of Anhui Provincial Hospital with good effects. Conclusion: The SPD model plays a critical role in optimizing the logistics procedures of MCs, improving the management efficiency of logistics, and reducing the costs of logistics of hospitals in China. PMID:27957435

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

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.

Relationship Between Logistics Service's Perceived Value and Outsourcing of Logistics Activities

Directory of Open Access Journals (Sweden)

Klavdij Logožar

2006-07-01

Full Text Available Outsourcing has become increasingly popular in recentyears, and is often quoted as a means of coping with rapidchanges in technology and in the business environment. Thescope of third -party logistics may range from a relatively limitedcombination of activities (e. g. transportation and warehousingto a comprehensive set of logistics services. The authorsfirst define the reasons for outsourcing with the emphasis onbusiness logistics. They particularly point out the motivationsfor logistics outsourcing, the possibilities of logistics outsourcing,and they present the process of outsourcing partner selectionas well. Finally, they analyze the specific issues of logisticsservice's perceived value in outsourcing logistics activities onthe basis of the survey carried out in Slovenian companies. Thepurpose of the survey was to measure the customers' perceptionof different characteristics of logistics provider which can be decisivewhen manufacturing firms are trying to make a decisionwhether to outsource and which logistics provider to select. Thepaper creates a framework for the selection of the importantand perceived characteristics of logistics provider relevant tocustomer in the process of the logistics supplier selection.

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

Matrix logistics indicators assessment of distributed transport hub

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Igor Arefyev

2014-06-01

Full Text Available Background: The paper is devoted to the distributed transport hub substantiation and assessment. The paper  was an example of the technique and form an array of logistical factors as variables that determine this condition. Experience in organizing multimodal transport showed that the "bottleneck" of transport logistics are items of cargo handling ports, terminals, freight stations and warehouses. At the core of the solution of these problems is the problem of estimating the variables determine the Multi-purpose Hubs. The aim is to develop a method of forming the system of logistical multiplying factors determine the role of each of the types in the technologiacal process of distributed Multi-purpose Hubs. Methods: The assessment model for the formation of Distributed Transport Units  can be based on formal methods to predict the behavior of complex systems engineering complexes. Then one of the approaches to the solution of the problem may be the matrix method of technological factors. Results and conclusions: The proposed methodology of the selection and validation of logistic coefficients has the practical importance in the models development for assessing the condition and behavior of Distributed Transport.

A Newton Algorithm for Multivariate Total Least Squares Problems

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WANG Leyang

2016-04-01

Full Text Available In order to improve calculation efficiency of parameter estimation, an algorithm for multivariate weighted total least squares adjustment based on Newton method is derived. The relationship between the solution of this algorithm and that of multivariate weighted total least squares adjustment based on Lagrange multipliers method is analyzed. According to propagation of cofactor, 16 computational formulae of cofactor matrices of multivariate total least squares adjustment are also listed. The new algorithm could solve adjustment problems containing correlation between observation matrix and coefficient matrix. And it can also deal with their stochastic elements and deterministic elements with only one cofactor matrix. The results illustrate that the Newton algorithm for multivariate total least squares problems could be practiced and have higher convergence rate.

Intelligent Decision Support and Big Data for Logistics and Supply Chain Management

DEFF Research Database (Denmark)

Voss, Stefan; Sebastian, Hans-Jürgen; Pahl, Julia

2017-01-01

Intelligent Decision Support and Big Data for Logistics and Supply Chain Management” features theoretical developments, real-world applications and information systems related to solving decision problems in logistics and supply chain management. Methods include optimization, heuristics, metaheur......Intelligent Decision Support and Big Data for Logistics and Supply Chain Management” features theoretical developments, real-world applications and information systems related to solving decision problems in logistics and supply chain management. Methods include optimization, heuristics......, metaheuristics and matheuristics, simulation, agent technologies, and descriptive methods. In a sense, we were and are representing the future of logistics over the years....

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

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.

Assessment of socio-economic potential of regions for placement of the logistic infrastructure objects

Directory of Open Access Journals (Sweden)

Aleksandr Nelevich Rakhmangulov

2014-06-01

Full Text Available Currently, at the regional markets, there is a disproportion between the growing demand for transportation and logistics services and the availability of facilities needed for their implementation, which is because the high logistics costs and does not meet the strategic objectives of the country to create a common economic space. The article describes the system of market factors that have the most significant influence on the distribution of logistics facilities. Study and evaluation of potential changes in the region of logistics facility disposition are proposed to perform using simulation techniques and statistical data analysis. The article presents the engineered multivariate statistical models that control the kind and effect of correlation between socio-economic development factors of regions, as well as a simulation model, which allows to assess the dynamics of these factors and predict demand for logistics infrastructure facilities. The choice of region (subject dislocation of the logistics center is proposed to realize by the developed technique based on the calculation of the integrated index that takes into account differences in the level of socio-economic and infrastructural development of the regions. This technique in conjunction with a simulation model is applicable to a variety of administrative and territorial levels (region, city and allows to take into account both the current demand in the logistics infrastructure and demand dynamics. The technique given in the article can be used to assess the level of attractiveness of the Russian Federation in the development of public and private investment projects for the development of logistics infrastructure

The influence of logistics potentials on business management

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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.  

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...

Multivariate Analysis and Machine Learning in Cerebral Palsy Research

Directory of Open Access Journals (Sweden)

Jing Zhang

2017-12-01

Full Text Available Cerebral palsy (CP, a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.

Input saturation in nonlinear multivariable processes resolved by nonlinear decoupling

Directory of Open Access Journals (Sweden)

Jens G. Balchen

1995-04-01

Full Text Available A new method is presented for the resolution of the problem of input saturation in nonlinear multivariable process control by means of elementary nonlinear decoupling (END. Input saturation can have serious consequences particularly in multivariable control because it may lead to very undesirable system behaviour and quite often system instability. Many authors have searched for systematic techniques for designing multivariable control systems in which saturation may occur in any of the control variables (inputs, manipulated variables. No generally accepted method seems to have been presented so far which gives a solution in closed form. The method of elementary nonlinear decoupling (END can be applied directly to the case of saturation control variables by deriving as many control strategies as there are combinations of saturating control variables. The method is demonstrated by the multivariable control of a simulated Fluidized Catalytic Cracker (FCC with very convincing results.

Research on Logistics Service Providers Selection Based on AHP and VIKOR

Science.gov (United States)

Shan, Lu

The logistics service providers supply a kind of service which is a service product, thus there is a plenty of uncertainty and fuzzy in selecting logistics service providers. AHP is first used to calculate the weights of logistics services providers evaluations and then VIKOR method developed for multi-criteria optimization determining a compromise solution is applied to select the logistics services providers. The latter method provides a maximum "group utility" for the "majority" and minimum of an individual regret for the "opponent". This decision making process of logistics services providers selection is verified to be scientific and feasible through the empirical research.

Late rectal toxicity after conformal radiotherapy of prostate cancer (I): multivariate analysis and dose-response

International Nuclear Information System (INIS)

Skwarchuk, Mark W.; Jackson, Andrew; Zelefsky, Michael J.; Venkatraman, Ennapadam S.; Cowen, Didier M.; Levegruen, Sabine; Burman, Chandra M.; Fuks, Zvi; Leibel, Steven A.; Ling, C. Clifton

2000-01-01

Purpose: The purpose of this paper is to use the outcome of a dose escalation protocol for three-dimensional conformal radiation therapy (3D-CRT) of prostate cancer to study the dose-response for late rectal toxicity and to identify anatomic, dosimetric, and clinical factors that correlate with late rectal bleeding in multivariate analysis. Methods and Materials: Seven hundred forty-three patients with T1c-T3 prostate cancer were treated with 3D-CRT with prescribed doses of 64.8 to 81.0 Gy. The 5-year actuarial rate of late rectal toxicity was assessed using Kaplan-Meier statistics. A retrospective dosimetric analysis was performed for patients treated to 70.2 Gy (52 patients) or 75.6 Gy (119 patients) who either exhibited late rectal bleeding (RTOG Grade 2/3) within 30 months after treatment (i.e., 70.2 Gy--13 patients, 75.6 Gy--36 patients) or were nonbleeding for at least 30 months (i.e., 70.2 Gy--39 patients, 75.6 Gy--83 patients). Univariate and multivariate logistic regression was performed to correlate late rectal bleeding with several anatomic, dosimetric, and clinical variables. Results: A dose response for ≥ Grade 2 late rectal toxicity was observed. By multivariate analysis, the following factors were significantly correlated with ≥ Grade 2 late rectal bleeding for patients prescribed 70.2 Gy: 1) enclosure of the outer rectal contour by the 50% isodose on the isocenter slice (i.e., Iso50) (p max (p max

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)

E-commerce influence on changes in logistics processes

Directory of Open Access Journals (Sweden)

Jadwiga Żurek

2015-06-01

Full Text Available   Background: The aim of this publication is to address the changes in retail trade, which have a direct influence on the development of e-commerce which in turn causes modifications to logistics chain management strategies and methods of flow control. Materials: The article has been written on the basis of an analysis of subject literature together with determining the influence of e-commerce to changes in logistics processes. The publications included in this study have been selected in order to present the subject of e-commerce development as well as evaluate changes in methods of flow control. The analysis has been prepared based on the author's experience and available reports and publications. Results: As a result of the conducted analysis, an assessment of the proficiency level of the changes in logistics processes on the local and international market as well as of the trends for these changes has been made. Conclusions: With the development of e-commerce, a new logistics chain management strategy began to appear, which covered both the process of handling the online and offline sales channel. Therefore, it can be concluded that properly adapted flow control methods will be the means for achieving the goal. Tasks will include: streamlining flow processes, improving the efficiency of logistic processes as well as adjusting them to market requirements.    

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.

Application of a Methodology to calculate logistical cost

Directory of Open Access Journals (Sweden)

Joaquín Mock-Díaz

2017-12-01

Full Text Available At present time, the managerial environment constantly becomes more aggressive and unstable. For that reason, companies are forced to improve on a regular basis their management, to increase their economic efficiency and their effectiveness and have a better performance. Within this context, the objective of this research is to apply a methodology to determine logistical costs, in a service−providing company, which allows assessing the behavior of such costs during the year 2016. A financial assessment performed to the logistical activities proved the existence of a high cost of opportunity, element mainly dependent on inventory rotation. For the purposes of this study, several scientific methods were used; the historical−logical method, to analyze the historical evolution of logistics; and the analysis−synthesis method to gather the elements and main ideas that characterize it.

A new multivariate zero-adjusted Poisson model with applications to biomedicine.

Science.gov (United States)

Liu, Yin; Tian, Guo-Liang; Tang, Man-Lai; Yuen, Kam Chuen

2018-05-25

Recently, although advances were made on modeling multivariate count data, existing models really has several limitations: (i) The multivariate Poisson log-normal model (Aitchison and Ho, ) cannot be used to fit multivariate count data with excess zero-vectors; (ii) The multivariate zero-inflated Poisson (ZIP) distribution (Li et al., 1999) cannot be used to model zero-truncated/deflated count data and it is difficult to apply to high-dimensional cases; (iii) The Type I multivariate zero-adjusted Poisson (ZAP) distribution (Tian et al., 2017) could only model multivariate count data with a special correlation structure for random components that are all positive or negative. In this paper, we first introduce a new multivariate ZAP distribution, based on a multivariate Poisson distribution, which allows the correlations between components with a more flexible dependency structure, that is some of the correlation coefficients could be positive while others could be negative. We then develop its important distributional properties, and provide efficient statistical inference methods for multivariate ZAP model with or without covariates. Two real data examples in biomedicine are used to illustrate the proposed methods. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[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.

Research challenges in municipal solid waste logistics management.

Science.gov (United States)

Bing, Xiaoyun; Bloemhof, Jacqueline M; Ramos, Tania Rodrigues Pereira; Barbosa-Povoa, Ana Paula; Wong, Chee Yew; van der Vorst, Jack G A J

2016-02-01

During the last two decades, EU legislation has put increasing pressure on member countries to achieve specified recycling targets for municipal household waste. These targets can be obtained in various ways choosing collection methods, separation methods, decentral or central logistic systems, etc. This paper compares municipal solid waste (MSW) management practices in various EU countries to identify the characteristics and key issues from a waste management and reverse logistics point of view. Further, we investigate literature on modelling municipal solid waste logistics in general. Comparing issues addressed in literature with the identified issues in practice result in a research agenda for modelling municipal solid waste logistics in Europe. We conclude that waste recycling is a multi-disciplinary problem that needs to be considered at different decision levels simultaneously. A holistic view and taking into account the characteristics of different waste types are necessary when modelling a reverse supply chain for MSW recycling. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Research on support effectiveness modeling and simulating of aviation materiel autonomic logistics system

Science.gov (United States)

Zhou, Yan; Zhou, Yang; Yuan, Kai; Jia, Zhiyu; Li, Shuo

2018-05-01

Aiming at the demonstration of autonomic logistics system to be used at the new generation of aviation materiel in our country, the modeling and simulating method of aviation materiel support effectiveness considering autonomic logistics are studied. Firstly, this paper introduced the idea of JSF autonomic logistics and analyzed the influence of autonomic logistics on support effectiveness from aspects of reliability, false alarm rate, troubleshooting time, and support delay time and maintenance level. On this basis, the paper studies the modeling and simulating methods of support effectiveness considering autonomic logistics, and puts forward the maintenance support simulation process considering autonomic logistics. Finally, taking the typical aviation materiel as an example, this paper analyzes and verifies the above-mentioned support effectiveness modeling and simulating method of aviation materiel considering autonomic logistics.

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.

Operation Mode and Optimum Design of China's Agricultural Modern Logistics System

OpenAIRE

Qin, Shi-bo

2012-01-01

Using comparative analysis and logical reasoning methods, in combination with traditional logistics theory and practice, and on the basis of objective demand of modern agricultural development for logistics service, we analyze features of logistics function. Besides, we discuss functional elements and service contents of agricultural modern logistics. In addition, we explore innovation model of agricultural modern logistics and systematized operation of supply chain. Finally, it is concluded ...

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

Multivariate Variables Recognition using Hotelling’s T2 and MEWMA via ANN’s

Directory of Open Access Journals (Sweden)

Chiñas-Sánchez Pamela

2014-01-01

Full Text Available In this article, a method for multivariate pattern recognition using artificial neural networks (ANN is proposed. The method is useful for monitoring multiple variables during the statistical process control. It employs descriptive statistics and multivariate control techniques. Three different ANN’s are evaluated to identify the network with higher efficiency during pattern recognition of multivariate variables tasks from data bases. Two data bases are analyzed; the first one is generated by simulation using the Montecarlo method, and the second data base was obtained from a public data base repository. The method consists of three stages: multivariate variables generation, multivariate analysis and pattern recognition using ANN’s. Several multivariate scenarios were generated using a combination of 2, 3 and 4 patterns in multivariate variables for the Hotelling’s T2 and MEWMA statistics that were analyzed to know its behavior and to determine their statistical characteristics. The pattern recognition task was evaluated using the ANN. In both study cases, experimental results showed an improved efficiency when using the Perceptron and the Backpropagation networks compared to the RBF network.

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.

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.

Logistics Outsourcing and The Role of Logistics Service Providers: A Study About Steel Pipe Production Enterprises in Turkey

OpenAIRE

Yıldız, Mehmet Selami; Turan, İlker

2015-01-01

Specialization requirement led the outsourcing preferred intensely by firms. Evidently “logistics activities” constitute an important part in the outsourced business activities. In this study, interviews were conducted with the managers from Turkey's steel pipe production enterprises who have knowledge of logistics management. Fourteen steel pipe enterprises were included in the study. The collected data were analyzed by using quantitative methods and data were obtained by interview and face-...

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...

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...

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.

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.

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.

Application of multivariate statistical techniques in microbial ecology.

Science.gov (United States)

Paliy, O; Shankar, V

2016-03-01

Recent advances in high-throughput methods of molecular analyses have led to an explosion of studies generating large-scale ecological data sets. In particular, noticeable effect has been attained in the field of microbial ecology, where new experimental approaches provided in-depth assessments of the composition, functions and dynamic changes of complex microbial communities. Because even a single high-throughput experiment produces large amount of data, powerful statistical techniques of multivariate analysis are well suited to analyse and interpret these data sets. Many different multivariate techniques are available, and often it is not clear which method should be applied to a particular data set. In this review, we describe and compare the most widely used multivariate statistical techniques including exploratory, interpretive and discriminatory procedures. We consider several important limitations and assumptions of these methods, and we present examples of how these approaches have been utilized in recent studies to provide insight into the ecology of the microbial world. Finally, we offer suggestions for the selection of appropriate methods based on the research question and data set structure. © 2016 John Wiley & Sons Ltd.

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

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

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...

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.)

Determination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish women.

Science.gov (United States)

Akkus, Zeki; Camdeviren, Handan; Celik, Fatma; Gur, Ali; Nas, Kemal

2005-09-01

To determine the risk factors of osteoporosis using a multiple binary logistic regression method and to assess the risk variables for osteoporosis, which is a major and growing health problem in many countries. We presented a case-control study, consisting of 126 postmenopausal healthy women as control group and 225 postmenopausal osteoporotic women as the case group. The study was carried out in the Department of Physical Medicine and Rehabilitation, Dicle University, Diyarbakir, Turkey between 1999-2002. The data from the 351 participants were collected using a standard questionnaire that contains 43 variables. A multiple logistic regression model was then used to evaluate the data and to find the best regression model. We classified 80.1% (281/351) of the participants using the regression model. Furthermore, the specificity value of the model was 67% (84/126) of the control group while the sensitivity value was 88% (197/225) of the case group. We found the distribution of residual values standardized for final model to be exponential using the Kolmogorow-Smirnow test (p=0.193). The receiver operating characteristic curve was found successful to predict patients with risk for osteoporosis. This study suggests that low levels of dietary calcium intake, physical activity, education, and longer duration of menopause are independent predictors of the risk of low bone density in our population. Adequate dietary calcium intake in combination with maintaining a daily physical activity, increasing educational level, decreasing birth rate, and duration of breast-feeding may contribute to healthy bones and play a role in practical prevention of osteoporosis in Southeast Anatolia. In addition, the findings of the present study indicate that the use of multivariate statistical method as a multiple logistic regression in osteoporosis, which maybe influenced by many variables, is better than univariate statistical evaluation.

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

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.

Multivariate Receptor Models for Spatially Correlated Multipollutant Data

KAUST Repository

Jun, Mikyoung

2013-08-01

The goal of multivariate receptor modeling is to estimate the profiles of major pollution sources and quantify their impacts based on ambient measurements of pollutants. Traditionally, multivariate receptor modeling has been applied to multiple air pollutant data measured at a single monitoring site or measurements of a single pollutant collected at multiple monitoring sites. Despite the growing availability of multipollutant data collected from multiple monitoring sites, there has not yet been any attempt to incorporate spatial dependence that may exist in such data into multivariate receptor modeling. We propose a spatial statistics extension of multivariate receptor models that enables us to incorporate spatial dependence into estimation of source composition profiles and contributions given the prespecified number of sources and the model identification conditions. The proposed method yields more precise estimates of source profiles by accounting for spatial dependence in the estimation. More importantly, it enables predictions of source contributions at unmonitored sites as well as when there are missing values at monitoring sites. The method is illustrated with simulated data and real multipollutant data collected from eight monitoring sites in Harris County, Texas. Supplementary materials for this article, including data and R code for implementing the methods, are available online on the journal web site. © 2013 Copyright Taylor and Francis Group, LLC.

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....

SPD-based Logistics Management Model of Medical Consumables in Hospitals.

Science.gov (United States)

Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei; Yang, Shanlin

2016-10-01

With the rapid development of health services, the progress of medical science and technology, and the improvement of materials research, the consumption of medical consumables (MCs) in medical activities has increased in recent years. However, owing to the lack of effective management methods and the complexity of MCs, there are several management problems including MC waste, low management efficiency, high management difficulty, and frequent medical accidents. Therefore, there is urgent need for an effective logistics management model to handle these problems and challenges in hospitals. We reviewed books and scientific literature (by searching the articles published from 2010 to 2015 in Engineering Village database) to understand supply chain related theories and methods and performed field investigations in hospitals across many cities to determine the actual state of MC logistics management of hospitals in China. We describe the definition, physical model, construction, and logistics operation processes of the supply, processing, and distribution (SPD) of MC logistics because of the traditional SPD model. With the establishment of a supply-procurement platform and a logistics lean management system, we applied the model to the MC logistics management of Anhui Provincial Hospital with good effects. The SPD model plays a critical role in optimizing the logistics procedures of MCs, improving the management efficiency of logistics, and reducing the costs of logistics of hospitals in China.

Research on the Environmental Performance Evaluation of Electronic Waste Reverse Logistics Enterprise

Science.gov (United States)

Yang, Yu-Xiang; Chen, Fei-Yang; Tong, Tong

According to the characteristic of e-waste reverse logistics, environmental performance evaluation system of electronic waste reverse logistics enterprise is proposed. We use fuzzy analytic hierarchy process method to evaluate the system. In addition, this paper analyzes the enterprise X, as an example, to discuss the evaluation method. It's important to point out attributes and indexes which should be strengthen during the process of ewaste reverse logistics and provide guidance suggestions to domestic e-waste reverse logistics enterprises.

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...

Problems of logistic systems sustainable development in delivery chains

Directory of Open Access Journals (Sweden)

2011-12-01

Full Text Available Background: Realization of supply chains management paradigm, covering significantly more volumes of logistic space, logically leads to complication of logistic systems, which, in its turn, arises significant number of problems of both theoretical and practical character. In our opinion, not all the aspects of logistic systems design and their sustainable functioning have received by the present time corresponding coverage in scientific literature. More detailed consideration requires specific problems of logistic systems interaction with their environment. We can talk about formation of new scientific direction (which we suggest to name logistic environics, being applied addition to classical approach to design of logistic systems. Methods: the formalized description of interaction process for logistic systems with the environment was presented and discussed  from ecological, social, economical, organizational and technological, technical, natural scientific positions. Results and conclusions: There is an interaction between logistics systems and the environment, but formalized description of logistic systems interaction process with the environment requires performance of complex interdisciplinary research from many different positions.

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.

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,

Depth-weighted robust multivariate regression with application to sparse data

KAUST Repository

Dutta, Subhajit; Genton, Marc G.

2017-01-01

A robust method for multivariate regression is developed based on robust estimators of the joint location and scatter matrix of the explanatory and response variables using the notion of data depth. The multivariate regression estimator possesses desirable affine equivariance properties, achieves the best breakdown point of any affine equivariant estimator, and has an influence function which is bounded in both the response as well as the predictor variable. To increase the efficiency of this estimator, a re-weighted estimator based on robust Mahalanobis distances of the residual vectors is proposed. In practice, the method is more stable than existing methods that are constructed using subsamples of the data. The resulting multivariate regression technique is computationally feasible, and turns out to perform better than several popular robust multivariate regression methods when applied to various simulated data as well as a real benchmark data set. When the data dimension is quite high compared to the sample size it is still possible to use meaningful notions of data depth along with the corresponding depth values to construct a robust estimator in a sparse setting.

Depth-weighted robust multivariate regression with application to sparse data

KAUST Repository

Dutta, Subhajit

2017-04-05

A robust method for multivariate regression is developed based on robust estimators of the joint location and scatter matrix of the explanatory and response variables using the notion of data depth. The multivariate regression estimator possesses desirable affine equivariance properties, achieves the best breakdown point of any affine equivariant estimator, and has an influence function which is bounded in both the response as well as the predictor variable. To increase the efficiency of this estimator, a re-weighted estimator based on robust Mahalanobis distances of the residual vectors is proposed. In practice, the method is more stable than existing methods that are constructed using subsamples of the data. The resulting multivariate regression technique is computationally feasible, and turns out to perform better than several popular robust multivariate regression methods when applied to various simulated data as well as a real benchmark data set. When the data dimension is quite high compared to the sample size it is still possible to use meaningful notions of data depth along with the corresponding depth values to construct a robust estimator in a sparse setting.

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.

Regional logistics land allocation policies: stimulating spatial concentration of logistics firms

NARCIS (Netherlands)

Heuvel, van den F.P.; Langen, de P.W.; Donselaar, van K.H.; Fransoo, J.C.

2013-01-01

Although spatial concentration of logistics firms in logistics concentration areas can be beneficial for society at large, there is not much research on the relationship between land allocation policies and logistics concentration areas. This paper analyzes land allocation policies by means of a

Regional logistics land allocation policies : stimulating spatial concentration of logistics firms

NARCIS (Netherlands)

Heuvel, van den F.P.; Langen, de P.W.; Donselaar, van K.H.; Fransoo, J.C.

2013-01-01

Although spatial concentration of logistics firms in logistics concentration areas can be beneficial for society at large, there is not much research on the relationship between land allocation policies and logistics concentration areas. This paper analyzes land allocation policies by means of a

Generalized Enhanced Multivariance Product Representation for Data Partitioning: Constancy Level

International Nuclear Information System (INIS)

Tunga, M. Alper; Demiralp, Metin

2011-01-01

Enhanced Multivariance Product Representation (EMPR) method is used to represent multivariate functions in terms of less-variate structures. The EMPR method extends the HDMR expansion by inserting some additional support functions to increase the quality of the approximants obtained for dominantly or purely multiplicative analytical structures. This work aims to develop the generalized form of the EMPR method to be used in multivariate data partitioning approaches. For this purpose, the Generalized HDMR philosophy is taken into consideration to construct the details of the Generalized EMPR at constancy level as the introductory steps and encouraging results are obtained in data partitioning problems by using our new method. In addition, to examine this performance, a number of numerical implementations with concluding remarks are given at the end of this paper.

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...

Comparing Johnson’s SBB, Weibull and Logit-Logistic bivariate distributions for modeling tree diameters and heights using copulas

Energy Technology Data Exchange (ETDEWEB)

Cardil Forradellas, A.; Molina Terrén, D.M.; Oliveres, J.; Castellnou, M.

2016-07-01

Aim of study: In this study we compare the accuracy of three bivariate distributions: Johnson’s SBB, Weibull-2P and LL-2P functions for characterizing the joint distribution of tree diameters and heights. Area of study: North-West of Spain. Material and methods: Diameter and height measurements of 128 plots of pure and even-aged Tasmanian blue gum (Eucalyptus globulus Labill.) stands located in the North-west of Spain were considered in the present study. The SBB bivariate distribution was obtained from SB marginal distributions using a Normal Copula based on a four-parameter logistic transformation. The Plackett Copula was used to obtain the bivariate models from the Weibull and Logit-logistic univariate marginal distributions. The negative logarithm of the maximum likelihood function was used to compare the results and the Wilcoxon signed-rank test was used to compare the related samples of these logarithms calculated for each sample plot and each distribution. Main results: The best results were obtained by using the Plackett copula and the best marginal distribution was the Logit-logistic. Research highlights: The copulas used in this study have shown a good performance for modeling the joint distribution of tree diameters and heights. They could be easily extended for modelling multivariate distributions involving other tree variables, such as tree volume or biomass. (Author)

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...

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).

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

Perceived safety management practices in the logistics sector.

Science.gov (United States)

Auyong, Hui-Nee; Zailani, Suhaiza; Surienty, Lilis

2016-03-09

Malaysia's progress on logistics has been slowed to keep pace with its growth in trade. The Government has been pressing companies to improve the safety of their activities in order to reduce society's loss due to occupational accidents and illnesses. Occupational safety and health is a crucial part of a workplace because every worker has to take care of his/her own safety and health. The main occupational safety and health (OSH) national policy in Malaysia is the enactment of the Occupational Safety and Health Act (OSHA) 1994. Only those companies which have excellent health and safety care have good quality and productive employees. This study investigated safety management practices in the logistics sector. The present study is concerned with the human factors to safety in the logistics industry. The authors examined the perceived safety management practices of workers in the logistics sector. The purpose was to identify the perception of safety management practices of Malaysian logistics personnel. Survey questionnaires were distributed to assess logistics personnel about management commitment. The quantitative method using the availability sampling method was applied. The data gathered from the survey were analysed using SPSS software. The responses to the survey were rated according to the Likert scale type, with '1' indicating strongly disagree and '5' indicating strongly agree. One hundred and three employees of logistics functions completed the survey. The highest mean scores were found for fire apparatus, prioritisation of safety, and safety policy. The results from this study also emphasise the importance of the management's commitment in enhancing workplace safety. Specifically, companies should maintain good relations between the employer and the employee to help reduce workplace injuries.

Performance evaluation on aquatic product cold-chain logistics

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Wenbing Wu

2015-11-01

Full Text Available Purpose: The requirements for high quality and diversification aquatic products are increasing with the improvement of Chinese living standard. However, the distribution between place of production and place of consumption are uneven, which results in large cold-chain logistics demand for aquatic products. At present, the low-level development of cold chain logistics has a bad impact on the circulation of aquatic products in China. So it is very urgent to develop cold-chain logistics in China. Design/methodology/approach: In order to do this, we apply performance evaluation, a well-known management tool, to study Chinese aquatic product cold-chain logistics. In this paper we first propose SISP(Subjects, Indexes, Standards, and Phases of performance evaluation model and ACSSN model(Aquatic product, Customer, Supply Chain, Society, and Node enterprises of supply chain for aquatic products cold-chain logistics performance evaluation. Then an ANP-Fuzzy method is proposed to evaluate the operational performance of Shandong Oriental Ocean Sci-Tech Co., Ltd. Furthermore, a system dynamic model is built to simulate the impact of temperature on the profits in aquatic products cold-chain sales section. Findings: We find out within a reasonable temperature range, lower temperature brings higher profit level. Also, performance improvement methods are proposed and the simulation of performance evaluation system is developed. Practical implications: Our findings can help to improve the level of aquatic product cold-chain logistics in China. Originality/value: The paper proposes the SISP (Subjects, Indexes, Standards, and Phases of performance evaluation model and ACSSN model (Aquatic product, Customer, Supply Chain, Society, and Node enterprises of supply chain for aquatic products cold-chain logistics performance evaluation.

Research on the optimization of vehicle distribution routes in logistics enterprises

Science.gov (United States)

Fan, Zhigou; Ma, Mengkun

2018-01-01

With the rapid development of modern logistics, the vehicle routing problem has become one of the urgent problems in the logistics industry. The rationality of distribution route planning directly affects the efficiency and quality of logistics distribution. This paper first introduces the definition of logistics distribution and the three methods of optimizing the distribution routes, and then analyzes the current vehicle distribution route by using a representative example, finally puts forward the optimization schemes of logistics distribution route.

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...

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).

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

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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.

WHY DO LOGISTICS AND TRANSPORT MATTER FOR DEVELOPMENT

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Nedelescu-Ionescu Daniela

2014-07-01

Full Text Available In face of the challenges of global competition, business firms are concentrating more on the needs of customers and seeking ways to reduce costs, improve quality and meet the ever-rising expectation of their customers. To these ends, many of them have identified logistics as an area to build cost and service advantages. Logistical activities have always been vital to organizations, and therefore business logistics and supply chain management represents a synthesis of many concepts, principles, and methods from the more traditional areas of production, purchasing, transportation, economics, as well as from the disciplines of applied mathematics, and organizational behaviour. It concentrates on important activities of management such as planning, organizing, and controlling, and also on a three-way relationship of related transportation, inventory, and location strategies, which are at the heart of good logistics planning and decision making. Selecting a good logistics strategy may yield a competitive advantage. Transportation provides the flow of materials, products and persons between production facilities, warehouses, distribution centers, terminals and customer locations. The progress in techniques and management principles improves the moving load, delivery speed, service quality, operation costs, the usage of facilities and energy saving. A strong system needs a clear frame of logistics and a proper transport implements and techniques to link the producing procedures. The transportation takes a crucial part in the management of logistic. Without well-developed transportation systems, logistics could not bring its advantages into full play. A good transport system in logistics activities could provide better logistics efficiency, reduce operation cost, and promote service quality. The process determines the efficiency of moving products and energy saving. Improvements in transportation and logistics make valuable contribution to production

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

Boosted Multivariate Trees for Longitudinal Data

Science.gov (United States)

Pande, Amol; Li, Liang; Rajeswaran, Jeevanantham; Ehrlinger, John; Kogalur, Udaya B.; Blackstone, Eugene H.; Ishwaran, Hemant

2017-01-01

Machine learning methods provide a powerful approach for analyzing longitudinal data in which repeated measurements are observed for a subject over time. We boost multivariate trees to fit a novel flexible semi-nonparametric marginal model for longitudinal data. In this model, features are assumed to be nonparametric, while feature-time interactions are modeled semi-nonparametrically utilizing P-splines with estimated smoothing parameter. In order to avoid overfitting, we describe a relatively simple in sample cross-validation method which can be used to estimate the optimal boosting iteration and which has the surprising added benefit of stabilizing certain parameter estimates. Our new multivariate tree boosting method is shown to be highly flexible, robust to covariance misspecification and unbalanced designs, and resistant to overfitting in high dimensions. Feature selection can be used to identify important features and feature-time interactions. An application to longitudinal data of forced 1-second lung expiratory volume (FEV1) for lung transplant patients identifies an important feature-time interaction and illustrates the ease with which our method can find complex relationships in longitudinal data. PMID:29249866

4th International Conference on Dynamics in Logistics

CERN Document Server

Pannek, Jürgen; Thoben, Klaus-Dieter

2016-01-01

This contributed volume brings together research papers presented at the 4th International Conference on Dynamics in Logistics, held in Bremen, Germany in February 2014. The conference focused on the identification, analysis and description of the dynamics of logistics processes and networks. Topics covered range from the modeling and planning of processes, to innovative methods like autonomous control and knowledge management, to the latest technologies provided by radio frequency identification, mobile communication, and networking. The growing dynamic poses wholly new challenges: logistics processes and networks must be(come) able to rapidly and flexibly adapt to constantly changing conditions. The book primarily addresses the needs of researchers and practitioners from the field of logistics, but will also be beneficial for graduate students.

[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.

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.

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

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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.

Multivariate calibration applied to the quantitative analysis of infrared spectra

Energy Technology Data Exchange (ETDEWEB)

Haaland, D.M.

1991-01-01

Multivariate calibration methods are very useful for improving the precision, accuracy, and reliability of quantitative spectral analyses. Spectroscopists can more effectively use these sophisticated statistical tools if they have a qualitative understanding of the techniques involved. A qualitative picture of the factor analysis multivariate calibration methods of partial least squares (PLS) and principal component regression (PCR) is presented using infrared calibrations based upon spectra of phosphosilicate glass thin films on silicon wafers. Comparisons of the relative prediction abilities of four different multivariate calibration methods are given based on Monte Carlo simulations of spectral calibration and prediction data. The success of multivariate spectral calibrations is demonstrated for several quantitative infrared studies. The infrared absorption and emission spectra of thin-film dielectrics used in the manufacture of microelectronic devices demonstrate rapid, nondestructive at-line and in-situ analyses using PLS calibrations. Finally, the application of multivariate spectral calibrations to reagentless analysis of blood is presented. We have found that the determination of glucose in whole blood taken from diabetics can be precisely monitored from the PLS calibration of either mind- or near-infrared spectra of the blood. Progress toward the non-invasive determination of glucose levels in diabetics is an ultimate goal of this research. 13 refs., 4 figs.

A review of multivariate analyses in imaging genetics

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Jingyu eLiu

2014-03-01

Full Text Available Recent advances in neuroimaging technology and molecular genetics provide the unique opportunity to investigate genetic influence on the variation of brain attributes. Since the year 2000, when the initial publication on brain imaging and genetics was released, imaging genetics has been a rapidly growing research approach with increasing publications every year. Several reviews have been offered to the research community focusing on various study designs. In addition to study design, analytic tools and their proper implementation are also critical to the success of a study. In this review, we survey recent publications using data from neuroimaging and genetics, focusing on methods capturing multivariate effects accommodating the large number of variables from both imaging data and genetic data. We group the analyses of genetic or genomic data into either a prior driven or data driven approach, including gene-set enrichment analysis, multifactor dimensionality reduction, principal component analysis, independent component analysis (ICA, and clustering. For the analyses of imaging data, ICA and extensions of ICA are the most widely used multivariate methods. Given detailed reviews of multivariate analyses of imaging data available elsewhere, we provide a brief summary here that includes a recently proposed method known as independent vector analysis. Finally, we review methods focused on bridging the imaging and genetic data by establishing multivariate and multiple genotype-phenotype associations, including sparse partial least squares, sparse canonical correlation analysis, sparse reduced rank regression and parallel ICA. These methods are designed to extract latent variables from both genetic and imaging data, which become new genotypes and phenotypes, and the links between the new genotype-phenotype pairs are maximized using different cost functions. The relationship between these methods along with their assumptions, advantages, and

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...

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...

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...

Logistic discriminant analysis of breast cancer using ultrasound measurement

International Nuclear Information System (INIS)

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

2004-01-01

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

Multivariate Analysis and Prediction of Dioxin-Furan ...

Science.gov (United States)

Peer Review Draft of Regional Methods Initiative Final Report Dioxins, which are bioaccumulative and environmentally persistent, pose an ongoing risk to human and ecosystem health. Fish constitute a significant source of dioxin exposure for humans and fish-eating wildlife. Current dioxin analytical methods are costly, time-consuming, and produce hazardous by-products. A Danish team developed a novel, multivariate statistical methodology based on the covariance of dioxin-furan congener Toxic Equivalences (TEQs) and fatty acid methyl esters (FAMEs) and applied it to North Atlantic Ocean fishmeal samples. The goal of the current study was to attempt to extend this Danish methodology to 77 whole and composite fish samples from three trophic groups: predator (whole largemouth bass), benthic (whole flathead and channel catfish) and forage fish (composite bluegill, pumpkinseed and green sunfish) from two dioxin contaminated rivers (Pocatalico R. and Kanawha R.) in West Virginia, USA. Multivariate statistical analyses, including, Principal Components Analysis (PCA), Hierarchical Clustering, and Partial Least Squares Regression (PLS), were used to assess the relationship between the FAMEs and TEQs in these dioxin contaminated freshwater fish from the Kanawha and Pocatalico Rivers. These three multivariate statistical methods all confirm that the pattern of Fatty Acid Methyl Esters (FAMEs) in these freshwater fish covaries with and is predictive of the WHO TE

Logistics costs of the enterprise

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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.

Logistics in Estonian business companies

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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.

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)

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.

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)

Production and Logistics Performance of Czech and Slovak Companies

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Polakova Veronika

2013-03-01

Full Text Available This contribution deals with the issues of production and logistics performance of Czech and Slovak companies. The goal of the research was to analyze logistic processes, methods of industrial engineering, methods and evaluation of manufacturing, software tools utilized for measurement and management of performance, which are currently applied in manufacturing companies in the Czech and Slovak Republic. This analysis was done with the utilization of qualitativeresearch conducted in 80 selected manufacturing companies in 2009. The results are compared in the continuity with the conclusions from previous researches on manufacturing and logistic factors of the competitiveness of Czech industrial manufacturers carried out during the period 2000-2001 in the framework of the research project of the Faculty of Economics and Management completed in 2004.

Research on simulation based material delivery system for an automobile company with multi logistics center

Science.gov (United States)

Luo, D.; Guan, Z.; Wang, C.; Yue, L.; Peng, L.

2017-06-01

Distribution of different parts to the assembly lines is significant for companies to improve production. Current research investigates the problem of distribution method optimization of a logistics system in a third party logistic company that provide professional services to an automobile manufacturing case company in China. Current research investigates the logistics leveling the material distribution and unloading platform of the automobile logistics enterprise and proposed logistics distribution strategy, material classification method, as well as logistics scheduling. Moreover, the simulation technology Simio is employed on assembly line logistics system which helps to find and validate an optimization distribution scheme through simulation experiments. Experimental results indicate that the proposed scheme can solve the logistic balance and levels the material problem and congestion of the unloading pattern in an efficient way as compared to the original method employed by the case company.

Effectiveness of Multivariate Time Series Classification Using Shapelets

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A. P. Karpenko

2015-01-01

Full Text Available Typically, time series classifiers require signal pre-processing (filtering signals from noise and artifact removal, etc., enhancement of signal features (amplitude, frequency, spectrum, etc., classification of signal features in space using the classical techniques and classification algorithms of multivariate data. We consider a method of classifying time series, which does not require enhancement of the signal features. The method uses the shapelets of time series (time series shapelets i.e. small fragments of this series, which reflect properties of one of its classes most of all.Despite the significant number of publications on the theory and shapelet applications for classification of time series, the task to evaluate the effectiveness of this technique remains relevant. An objective of this publication is to study the effectiveness of a number of modifications of the original shapelet method as applied to the multivariate series classification that is a littlestudied problem. The paper presents the problem statement of multivariate time series classification using the shapelets and describes the shapelet–based basic method of binary classification, as well as various generalizations and proposed modification of the method. It also offers the software that implements a modified method and results of computational experiments confirming the effectiveness of the algorithmic and software solutions.The paper shows that the modified method and the software to use it allow us to reach the classification accuracy of about 85%, at best. The shapelet search time increases in proportion to input data dimension.

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

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 ...

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

Decision-making on reverse logistics in the construction industry

Directory of Open Access Journals (Sweden)

Thanwadee Chinda

2016-02-01

Full Text Available With the growing competition, many construction organizations attempt to improve their productivity, quality, and efficiency. Construction waste management, by means of reverse logistics, becomes a key issue to improve the productivity, and raise the company’s green image. In this study, four reverse logistics methods-direct reuse, remanufacturing, recycling, and landfill-are considered to manage construction and demolition (C&D waste. Two factors (economic and site-specific with their 15 sub-factors affecting the decisions to implement the reverse logistics are examined. The hierarchy model of reverse logistics decisions, developed through the analytic hierarchy process, reveal the importance of the economic factor over the site-specific factor. It is suggested that the transportation cost, the processing cost, the specific sorting technology, and the limited project time must be first considered before making decisions on reverse logistics plans. The construction company can utilize the developed hierarchy model to decide on the most appropriate reverse logistics plan to achieve the best benefits.

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.

Extracting bb Higgs Decay Signals using Multivariate Techniques

Energy Technology Data Exchange (ETDEWEB)

Smith, W Clarke; /George Washington U. /SLAC

2012-08-28

For low-mass Higgs boson production at ATLAS at {radical}s = 7 TeV, the hard subprocess gg {yields} h{sup 0} {yields} b{bar b} dominates but is in turn drowned out by background. We seek to exploit the intrinsic few-MeV mass width of the Higgs boson to observe it above the background in b{bar b}-dijet mass plots. The mass resolution of existing mass-reconstruction algorithms is insufficient for this purpose due to jet combinatorics, that is, the algorithms cannot identify every jet that results from b{bar b} Higgs decay. We combine these algorithms using the neural net (NN) and boosted regression tree (BDT) multivariate methods in attempt to improve the mass resolution. Events involving gg {yields} h{sup 0} {yields} b{bar b} are generated using Monte Carlo methods with Pythia and then the Toolkit for Multivariate Analysis (TMVA) is used to train and test NNs and BDTs. For a 120 GeV Standard Model Higgs boson, the m{sub h{sup 0}}-reconstruction width is reduced from 8.6 to 6.5 GeV. Most importantly, however, the methods used here allow for more advanced m{sub h{sup 0}}-reconstructions to be created in the future using multivariate methods.

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

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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.

Multivariate normal tissue complication probability modeling of gastrointestinal toxicity after external beam radiotherapy for localized prostate cancer

International Nuclear Information System (INIS)

Cella, Laura; D’Avino, Vittoria; Liuzzi, Raffaele; Conson, Manuel; Doria, Francesca; Faiella, Adriana; Loffredo, Filomena; Salvatore, Marco; Pacelli, Roberto

2013-01-01

The risk of radio-induced gastrointestinal (GI) complications is affected by several factors other than the dose to the rectum such as patient characteristics, hormonal or antihypertensive therapy, and acute rectal toxicity. Purpose of this work is to study clinical and dosimetric parameters impacting on late GI toxicity after prostate external beam radiotherapy (RT) and to establish multivariate normal tissue complication probability (NTCP) model for radiation-induced GI complications. A total of 57 men who had undergone definitive RT for prostate cancer were evaluated for GI events classified using the RTOG/EORTC scoring system. Their median age was 73 years (range 53–85). The patients were assessed for GI toxicity before, during, and periodically after RT completion. Several clinical variables along with rectum dose-volume parameters (Vx) were collected and their correlation to GI toxicity was analyzed by Spearman’s rank correlation coefficient (Rs). Multivariate logistic regression method using resampling techniques was applied to select model order and parameters for NTCP modeling. Model performance was evaluated through the area under the receiver operating characteristic curve (AUC). At a median follow-up of 30 months, 37% (21/57) patients developed G1-2 acute GI events while 33% (19/57) were diagnosed with G1-2 late GI events. An NTCP model for late mild/moderate GI toxicity based on three variables including V65 (OR = 1.03), antihypertensive and/or anticoagulant (AH/AC) drugs (OR = 0.24), and acute GI toxicity (OR = 4.3) was selected as the most predictive model (Rs = 0.47, p < 0.001; AUC = 0.79). This three-variable model outperforms the logistic model based on V65 only (Rs = 0.28, p < 0.001; AUC = 0.69). We propose a logistic NTCP model for late GI toxicity considering not only rectal irradiation dose but also clinical patient-specific factors. Accordingly, the risk of G1-2 late GI increases as V65 increases, it is higher for patients experiencing

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.

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...

A measure of emergence of a logistic group interaction

Directory of Open Access Journals (Sweden)

V. Novikov

2012-06-01

Full Text Available Background: The nature of the relations between group members is a very important part of the integrity of the logistics process. The identification of rating among the participants is certainly the most necessary condition for the quality of the logistics process. It can distinguished four types of emergence rating: direct participation rating, direct impact rating, participation rating and impact rating. The aim of this paper was to create the method to determine the mutual relationships among various elements of logistic group. Methods: The technique is based on the processing of the matrix of pairwise interactions obtained on the basis of a questionnaire survey of all members of the group and expressed as a score on the selected scale of assessments. The computation algorithm is based in particular on the traveling salesman problem using an original method of optimization and is implemented in Visual Studio C #. Results: 16 types of leaderships were distinguished and described by the use of statistical methods. Conclusions: The developed method of calculating the measure of emergence can be used not only for a group of students, but also for the definition of the rate of emergence in any collective system.

Total Logistic Plant Solutions

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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

DTW-APPROACH FOR UNCORRELATED MULTIVARIATE TIME SERIES IMPUTATION

OpenAIRE

Phan , Thi-Thu-Hong; Poisson Caillault , Emilie; Bigand , André; Lefebvre , Alain

2017-01-01

International audience; Missing data are inevitable in almost domains of applied sciences. Data analysis with missing values can lead to a loss of efficiency and unreliable results, especially for large missing sub-sequence(s). Some well-known methods for multivariate time series imputation require high correlations between series or their features. In this paper , we propose an approach based on the shape-behaviour relation in low/un-correlated multivariate time series under an assumption of...

Score Normalization using Logistic Regression with Expected Parameters

NARCIS (Netherlands)

Aly, Robin

State-of-the-art score normalization methods use generative models that rely on sometimes unrealistic assumptions. We propose a novel parameter estimation method for score normalization based on logistic regression. Experiments on the Gov2 and CluewebA collection indicate that our method is

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

Energy Technology Data Exchange (ETDEWEB)

Gutierrez, M Ranferi; Reyes, M A [Depto de Fisica, Universidad de Guanajuato, Apdo. Postal E143, 37150 Leon, Gto. (Mexico); Rosu, H C, E-mail: hcr@ipicyt.edu.m [IPICyT, Instituto Potosino de Investigacion Cientifica y Tecnologica, Apdo Postal 3-74 Tangamanga, 78231 San Luis PotosI (Mexico)

2010-05-21

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{sub n+1} = rx{sub n}(1 - x{sub 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{sub n+1} - x{sub n} = rx{sub n}(1 - x{sub 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.

Marketing in the business activity of logistics service providers

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Marcin Świtała

2013-09-01

Full Text Available Background: This article is a discussion on the role of marketing in the activity of logistics service providers. The strong competition and changing purchasing preferences should motivate the transport, forwarding and logistics sector managers to apply the marketing approach in practice. Methods: Results of direct research, conducted among a targeted group of 100 companies from the transport, forwarding and logistics sector, constitute the source basis. The sample group was divided into three categories of logistics providers: 2PL, 3PL and 4PL. The statistical analysis was based on three different non-parametric tests (Kruskal-Wallis, Chi-square and V Kramer.  Results and conclusions:  Currently, marketing does not play a key role in the activity of logistics services providers. The prevailing opinion is that importance of marketing in the company is average. The respondents have assessed in a similar way their activity compared to the activities of the competition. However, it was found that with the increase of the level of specialization (2PL-4PL, the awareness of impact of marketing on the logistics services sector also increased. The logistics services providers, who offer a wide range of logistics services, asses their competitive position in a better light.  

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

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.

The Design of Integrated Logistics Management System of an Industrial Company

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Hart Martin

2017-01-01

Full Text Available In the contemporary global business markets environment, when the business markets are getting more and more commercial, there are growing demand for effective management of material flows. The effectivity and effectiveness of planning, management and control the material flows across an industrial company and its distribution networks, represents one of the main pillar regarding the high level of competitive advantage within the frame of supply chains. Thus, the company information management system design should have also included a module of integrated logistics management system to ensure required level of material flow management effectivity and effectiveness. The article deals with brief description of the issues on company management, company information management systems and logistics management. Further it’s stated the methodology to created integrated logistics management system, which is containing the methodics to design logistics management sub-systems of purchasing, manufacturing, distribution and reverse material flows. The essential methodics of the stated methodology is the methodics to create independent demand forecasting sub-system.

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.

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

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.

Logistički informacioni sistem / Logistics information system

Directory of Open Access Journals (Sweden)

Marko D. Andrejić

2010-01-01

taking also into account compatibility with future allies and partners. Defense systems were among the first to accept the challenge (because they were forced to to introduce information technology in their management system and, with the help of innovations in this area, to increase the performance effectiveness under the conditions of environment dynamic changes. Information technology development mostly followed development of large military projects aimed at solving management or technology issues within military industry complex and management in the most technologically developed defense systems. These science and defense practice efforts resulted in many new methods and techniques such as the method of system analysis and information system design, methods of operational research and simulation, pattern recognition, expert systems for individual processes in management, as well as those for information retrieval and their implementation in decision making. Over time, partial innovations reached a high level of synthesis, leading to new management systems able to function in most complex task conditions. Mastering the procedure of creating autonomous partial information systems-where the operational research methods helped to optimally apply some of their particular values - has led to the creation of integrated automated information systems for management support. Our recent defense theory and practice have not concentrated enough on logistics information systems in professional journals, neither from the organizational nor from the technological point of view. Experiences gained from operational practice and knowledge acquired by visiting foreign armies, practical needs as well as modern times demands and current trends in the development of defense systems pointed out that it is necessary to pay more attention to this logistics segment in military journals. Logistics information systems cannot be researched, developed and introduced into operational practice

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.

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.

Color Fringe Correction by the Color Difference Prediction Using the Logistic Function.

Science.gov (United States)

Jang, Dong-Won; Park, Rae-Hong

2017-05-01

This paper proposes a new color fringe correction method that preserves the object color well by the color difference prediction using the logistic function. We observe two characteristics between normal edge (NE) and degraded edge (DE) due to color fringe: 1) the DE has relatively smaller R-G and B-G correlations than the NE and 2) the color difference in the NE can be fitted by the logistic function. The proposed method adjusts the color difference of the DE to the logistic function by maximizing the R-G and B-G correlations in the corrected color fringe image. The generalized logistic function with four parameters requires a high computational load to select the optimal parameters. In experiments, a one-parameter optimization can correct color fringe gracefully with a reduced computational load. Experimental results show that the proposed method restores well the original object color in the DE, whereas existing methods give monochromatic or distorted color.

Activity-based Management of Logistic Costs in a Manufacturing Company: A Case of Increased Visibility of Logistics Costs in a Slovenian Paper Manufacturing Company

Directory of Open Access Journals (Sweden)

Julijana Krajnc

2012-01-01

Full Text Available Both the transparent reporting of logistics costs and the related accounting of their cost drivers present a significant factor for the successful management of material flows and the related logistics activities in production companies. These costs, which are mainly reported as part of overhead (indirect costs in such companies, usually remain hidden or are not explicitly visible when the traditional method of accounting is applied. The aim of this research is to create a model of activity-based accounting of logistics costs in a production company, and to test its efficiency in the disclosure of logistics costs compared with traditional cost accounting. The application of the model in a production company shows that an activity-based approach discloses as much as 108% more logistics costs at the level of a group of products than the traditional cost-accounting approach. Further, detailed information on logistics costs obtained in this way enables their more efficient management. Key words: logistics costs; activity-based costing; cost allocation; cost visibility; cost management

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-

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.

EVALUATION OF LOGISTICS CUSTOMER SERVICE IN A MARKETING COMPANY

Directory of Open Access Journals (Sweden)

María Esther Debrosse-Carballo

2016-01-01

Full Text Available The objective of the article is to present the application of a procedure that allows evaluating the level of logistic service offered by a marketing company. In order to reach the objective as a source of secondary was used information: company documents and logistics reports. As primary sources were used the interviews and surveys carried out to all the experts and selected customers. At the stage of processing and analysis of the information tools were used such as: service evaluation matrix, ABC Method for classifying customers, Indicators for evaluating the Logistic Service. This analysis permit to the enterprise know and evaluate the levels of satisfaction of its customer, facilitating to trace strategies that make possible elevate the quality of the logistic service. 

Efficient Design of Distribution Logistics by Using a Model-Based Decision Support System

OpenAIRE

J. Becker; R. Arnold

2016-01-01

The design of distribution logistics has a decisive impact on a company's logistics costs and performance. Hence, such solutions make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistics costs and performance. In contrast to previous procedures of business process re-engineering (BPR), this method maps distribution logistics holistically under variable distribution structure...

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.

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

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

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

MULTIVARIATERESIDUES : A Mathematica package for computing multivariate residues

Science.gov (United States)

Larsen, Kasper J.; Rietkerk, Robbert

2018-01-01

Multivariate residues appear in many different contexts in theoretical physics and algebraic geometry. In theoretical physics, they for example give the proper definition of generalized-unitarity cuts, and they play a central role in the Grassmannian formulation of the S-matrix by Arkani-Hamed et al. In realistic cases their evaluation can be non-trivial. In this paper we provide a Mathematica package for efficient evaluation of multivariate residues based on methods from computational algebraic geometry.

Diagnostical Procedure for Logistical Management in Turistical Entities

Directory of Open Access Journals (Sweden)

Libia Arlen Fergusson-Álvarez

2016-06-01

Full Text Available This research aims to design a diagnostic procedure of the logistics management for turistical entities, they could be hotels or not. This procedure was validated in Commercial Branch Caracol Santiago de Cuba and finally, different actions for the detected problems were proposed with the objective of improving the logistics management of the organization. To develop this research various tools and techniques served as support, such as: surveys, SPSS software (Statistical Package for Social Sciences 15.0 version and Decision 1.0 version, exponential smoothing, Cronbach's Alpha, the coefficient of Kendall W, financial and logistical indicators, the ABC or Pareto Method, the matrices for the classification of stocks and suppliers, among others. This research made possible the design of a diagnostic procedure for logistical management for turistical entities. And it was validated in the Comercial Branch Caracol Santiago, which allowed the proposition of improvement actions for increasing customer satisfaction.

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

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.

Multivariate spectral-analysis of movement-related EEG data

International Nuclear Information System (INIS)

Andrew, C. M.

1997-01-01

The univariate method of event-related desynchronization (ERD) analysis, which quantifies the temporal evolution of power within specific frequency bands from electroencephalographic (EEG) data recorded during a task or event, is extended to an event related multivariate spectral analysis method. With this method, time courses of cross-spectra, phase spectra, coherence spectra, band-averaged coherence values (event-related coherence, ERCoh), partial power spectra and partial coherence spectra are estimated from an ensemble of multivariate event-related EEG trials. This provides a means of investigating relationships between EEG signals recorded over different scalp areas during the performance of a task or the occurrence of an event. The multivariate spectral analysis method is applied to EEG data recorded during three different movement-related studies involving discrete right index finger movements. The first study investigates the impact of the EEG derivation type on the temporal evolution of interhemispheric coherence between activity recorded at electrodes overlying the left and right sensorimotor hand areas during cued finger movement. The question results whether changes in coherence necessarily reflect changes in functional coupling of the cortical structures underlying the recording electrodes. The method is applied to data recorded during voluntary finger movement and a hypothesis, based on an existing global/local model of neocortical dynamics, is formulated to explain the coherence results. The third study applies partial spectral analysis too, and investigates phase relationships of, movement-related data recorded from a full head montage, thereby providing further results strengthening the global/local hypothesis. (author)

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

SIMULATION OF LOGISTICS PROCESSES

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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.

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...

Directional outlyingness for multivariate functional data

KAUST Repository

Dai, Wenlin

2018-04-07

The direction of outlyingness is crucial to describing the centrality of multivariate functional data. Motivated by this idea, classical depth is generalized to directional outlyingness for functional data. Theoretical properties of functional directional outlyingness are investigated and the total outlyingness can be naturally decomposed into two parts: magnitude outlyingness and shape outlyingness which represent the centrality of a curve for magnitude and shape, respectively. This decomposition serves as a visualization tool for the centrality of curves. Furthermore, an outlier detection procedure is proposed based on functional directional outlyingness. This criterion applies to both univariate and multivariate curves and simulation studies show that it outperforms competing methods. Weather and electrocardiogram data demonstrate the practical application of our proposed framework.

Forecasting multivariate volatility in larger dimensions: some practical issues

OpenAIRE

Adam E Clements; Ayesha Scott; Annastiina Silvennoinen

2012-01-01

The importance of covariance modelling has long been recognised in the field of portfolio management and large dimensional multivariate problems are increasingly becoming the focus of research. This paper provides a straightforward and commonsense approach toward investigating whether simpler moving average based correlation forecasting methods have equal predictive accuracy as their more complex multivariate GARCH counterparts for large dimensional problems. We find simpler forecasting techn...

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...

New analytical techniques for traffic management on the basis of system studies in logistics

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Олександр Павлович Кіркін

2017-07-01

Full Text Available In today's market conditions, it is necessary for enterprises to constantly maintain their competitiveness. This is achieved through raising customer service standards and use of the latest management techniques. In most cases, enterprises adhere to the logistic principles to optimize production. Over time, however, the development of logistics resulted in emergence of its principal subdivisions: transport, storage, etc. Thus, nowadays there are several parallel methodological developments in the field of logistics and making up logistics chains and systems at different stages of the life cycle of the goods. System research in the field of warehouse logistics showed that the majority of its analytical models of management are based on task conflict. Similar tasks of managing traffic flows in transport logistics are solved by methods of SMO, graph theory, linear programming and differential equations of state etc. These methods are not more accurate than the methods of warehouse logistics, have similar important assumptions and simplifications, and require appropriate mathematical training and knowledge in the field of transport, and sometimes lack visible correlation with economic performance. New analytical techniques for the management of transportation systems based on task conflict will reduce the time and resources for optimization and finding solutions. Methods of warehousing logistics can only be used for the continuous transport quantities (intensity, speed, performance, capacity, execution of works, etc.. In the static condition the search for the optimal service intensity can be found in warehouse logistics. In the study of object in dynamics it is better to use transport approach. Some problems such as supplement of warehouse logistics models with elements of the transport task, are still to be decided

The Third Party Logistics Partner Selection of B2C E-Commerce Enterprise

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Xu Wei

2017-01-01

Full Text Available In recent years, with the rapid development of Internet, e-commerce enterprises in China is at an alarming rate of sustainable development, the B2C e-commerce in the online shopping market accounted for a large proportion, with the rapid change of the market and customer needs to establish a flexible distribution service is one of the many e-commerce companies need to solve. Using self logistics capital occupancy bigger; the logistics alliance, with the risk of internal information disclosure; and on the third party logistics, not only capital and manpower can be effectively used, helps enterprises to strengthen the core business. Therefore, it is very important to choose the appropriate third party logistics providers to reduce operating costs and improve the market influence. This paper analyses the existing problems in the third party logistics, the establishment of a more complete index system, according to the actual situation of the suppliers, using the improved AHP method and the entropy coefficient method to get the comprehensive weight, finally get the approximation method to meet the business requirements of the logistics service providers use the ideal, for commercial enterprises to third party logistics service provider selection and puts forward some available models.

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 ...

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.

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.

IMPROVING MARKETING LOGISTICS MANAGEMENT OF ENTERPRISES OF AGRO-INDUSTRIAL COMPLEX

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Raisa Bilovol

2016-11-01

Full Text Available The Purpose of the paper is to prove the need of improving marketing logistics management at enterprises of agro-industrial complex with the use of balanced scorecard method that will allow objectively evaluate its effectiveness. Methodology. The survey is based on the use of general scientific research methods, methods of analysis and synthesis, method of abstraction. Results. Research of state sales of agricultural products in agrarian enterprises helped us to identify and organize the following disadvantages: intermediary structures that are engaged in marketing of agricultural products significantly increase their costs that excess in 2-4 times the original price of agricultural products; inadequacy of agricultural market infrastructure and lack of wholesale and retail markets for agricultural products; low level of development of information electronic communications; backwardness of transport infrastructure and poor quality of roads, particularly in rural areas; high level of physical and moral deterioration of transport; low level of development of industrial and technological base of agricultural enterprises warehousing. Practical implications. We systemized and proposed indicators of evaluation of marketing logistics at enterprises of the agro-industrial complex based on the Balanced Scorecard in key areas: financial and cost-effectiveness indicators; indicators of internal logistics business processes; quality and development staff; indicators in the direction of working with clients. To the financial indicators and indicators of economic efficiency we included such as sales per 1 employer at marketing department (Qs/employer, proportion of logistics cost of marketing in the total cost of the enterprise (%, coefficient of the implementation of marketing plan (Cm, ROI in logistics marketing (%, profitability of marketing channels (%. Internal logistics business processes in enterprises of the agro-industrial complex represented by such

Research challenges in municipal solid waste logistics management

NARCIS (Netherlands)

Bing, Xiaoyun; Bloemhof-Ruwaard, Jacqueline; Ramos, Tania Rodrigues Pereira; Barbosa-Povoa, Ana Paula; Wong, Chee Yew; Vorst, van der J.G.A.J.

2016-01-01

During the last two decades, EU legislation has put increasing pressure on member countries to achieve specified recycling targets for municipal household waste. These targets can be obtained in various ways choosing collection methods, separation methods, decentral or central logistic systems,

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.

The logic of logistics: theory, algorithms and applications for logistics management

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Claudio Barbieri da Cunha

2010-04-01

Full Text Available

Nesse texto o autor apresenta uma resenha acerca do livro "The logic of logistics: theory, algorithms and applications for logistics management", de autoria de Julien Bramel e David Simchi-Levi, publicado pela Springer-Verlag, em 1997.

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.

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

Network structure of multivariate time series.

Science.gov (United States)

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

Logistics outsourcing and performance of manufacturing small and medium-sized enterprises in Nairobi

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Joash Mageto

2018-06-01

Full Text Available Background: Logistics outsourcing has been accepted as a strategy through which small and medium-sized enterprises (SMEs can access the logistics capabilities they lack internally at a lower cost. However, the actual effect of logistics outsourcing on firm performance, especially among the SMEs in Nairobi, remains unknown.   Aim: The study aimed to investigate the relationship between logistics outsourcing and firm performance of manufacturing SMEs in Nairobi.   Setting: The study sampled manufacturing SMEs in Nairobi City County.   Method: In this study, a convergent parallel mixed methods design was applied. Survey data were collected from 163 manufacturing SMEs. The data were analysed using structural equation modelling to test the relationship between logistics outsourcing and firm performance. Additionally, in-depth interviews were conducted in five manufacturing SMEs. Thematic analysis was used to analyse interview data to provide more insight in the quantitative data.   Results: The anticipated direct link between logistics outsourcing and performance of manufacturing SMEs was not statistically significant. However, the study revealed a statistically significant indirect positive effect of logistics outsourcing on the performance of manufacturing SMEs through logistics outsourcing performance as a mediator variable. This article further highlights reasons and the process of logistics outsourcing and deduces a logistics outsourcing model for manufacturing SMEs to help improve their firm’s performance.   Conclusion: The established relationship and deduced logistics outsourcing model is likely to guide SME managers as to how to manage logistics outsourcing to improve performance. The finding that logistics outsourcing has a positive indirect effect on the performance of manufacturing SMEs through logistics outsourcing performance makes a significant contribution to theory.

The Efficiency and Productivity Analysis of Large Logistics Providers Services in Korea

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Hong Gyun Park

2015-12-01

Full Text Available In the fierce competition at the global logistics markets, Korean logistics providers were deemed more vulnerable than global logistics providers in terms of the quality and price competitiveness. To strengthen their competitiveness, logistics providers in Korea have focused on delivering integrated logistics services. In this regard, the Korean government has enacted the “Integrated Logistics Industry Certification Act” in 2006 to assist integrated logistics providers to offer logistics services based on their specialization and differentiation. It has been several years since the system was implemented, and the evaluation of the system implementation was necessary. Hence, in our study, we attempt to examine the efficiency and productivity of fourteen certified Korean logistics providers employing the DEA (Data Envelopment Analysis method with a five-year panel data since the inception of the Act. Through our static and dynamic analyses, We found that Pantos Logistics and HYUNDAI Glovis are running their businesses at the highest level of efficiency and Hanjin Transportation was the most stable company in their logistics operation.

An assessment on the use of bivariate, multivariate and soft computing techniques for collapse susceptibility in GIS environ

Science.gov (United States)

Yilmaz, Işik; Marschalko, Marian; Bednarik, Martin

2013-04-01

The paper presented herein compares and discusses the use of bivariate, multivariate and soft computing techniques for collapse susceptibility modelling. Conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) models representing the bivariate, multivariate and soft computing techniques were used in GIS based collapse susceptibility mapping in an area from Sivas basin (Turkey). Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index (TWI), stream power index (SPI), Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from the models, and they were then compared by means of their validations. However, Area Under Curve (AUC) values obtained from all three models showed that the map obtained from soft computing (ANN) model looks like more accurate than the other models, accuracies of all three models can be evaluated relatively similar. The results also showed that the conditional probability is an essential method in preparation of collapse susceptibility map and highly compatible with GIS operating features.

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

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

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

Optimalization of production inside logistics chain for 21st century

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Drago Pupavac

2006-12-01

Full Text Available In today’s world numerous logistics chains exist, competing for similar jobs in different markets throughout the world. By connecting the supply and demand, i.e. production and consumption, logistics chains create national, regional and global logistics network which task is to maximise total generated value. Generated valueis defined as the difference between the price of finished product or service and the input necessary to create such products. The chain profitability is shown by the difference between the income obtained through sale of products or services and total expenditure in that chain. Accordingly, this scientific debate researches the possibilityof production optimisation within logistic chain by application of dynamic programming method with emphasis on information technologies.

Analysis of reverse logistics management for glass bottles at a spirits company

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Roger Augusto Luna

2014-12-01

Full Text Available Issues related to reverse logistics demonstrate increasing relevance as a set of factors such as those of a strategic, competitive, economic and ecological nature become relevant in the current context. Organizations are finding opportunities in reverse logistics for differentiating products offered to its customers and consumers. This article aims to analyze the process of reverse logistics of bottles in a spirits manufacturing company. For this study, we used a case study method, where company logistics executives were interviewed. As a result of the research, we identify current reverse logistics processes and their drivers, in order to support the understanding of problems and actions taken by the company to be deployed the reverse logistics process for bottles.

Risk assessment and management logistics chains

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Vladimir Vikulov

2014-03-01

Full Text Available Background: In the context of economic globalization and increasing complexity of economic relations enterprises need methods and techniques to improve and sustain their position on the global market. Integration processes offer business new opportunities, but at the same time present new challenges for the management, including the key objectives of the risk management. Method: On the basis of analysis tools known from the pertinent literature (Supply Chain Management and Supply Chain Risk Management methods, methods of probability theory, methods of risk management, methods of statistics the authors of this paper proposed their own risk assessment method and the method of management of logistics chains. The proposed tool is a specific hybrid of solutions known from the literature. Results: The presented method has been successfully used within the frames of economic-mathematical model of industrial enterprises. Indicators of supply chain risks, including risks caused by supplier are considered in this paper. Authors formed a method of optimizing the level of supply chain risk in the integration with suppliers and customers. Conclusion: Every organization, which starting the process of integration with supplier and customers, needs to use tools, methodologies and techniques for identification of "weak links" in the supply chain. The proposed method allows to fix risk origin places in various links of the supply chain and to identify "weak links" of a logistic chain that may occur in the future. The method is a useful tool for managing not only risks and risk situations, but also to improve the efficiency of current assets management by providing the ability to optimize the level of risk in the current assets management of the industrial enterprise.

Multivariate phase type distributions - Applications and parameter estimation

DEFF Research Database (Denmark)

Meisch, David

The best known univariate probability distribution is the normal distribution. It is used throughout the literature in a broad field of applications. In cases where it is not sensible to use the normal distribution alternative distributions are at hand and well understood, many of these belonging...... and statistical inference, is the multivariate normal distribution. Unfortunately only little is known about the general class of multivariate phase type distribution. Considering the results concerning parameter estimation and inference theory of univariate phase type distributions, the class of multivariate...... projects and depend on reliable cost estimates. The Successive Principle is a group analysis method primarily used for analyzing medium to large projects in relation to cost or duration. We believe that the mathematical modeling used in the Successive Principle can be improved. We suggested a novel...

A New Advanced Logistics Supply Chain for Food Management Based on Green Logistics Theory

OpenAIRE

Lanqing Liu

2013-01-01

The study aims to investigate the advanced logistics supply chain for food management using green logistics. To protect the food logistics environment and prevent the environmental pollution, it is crucial to establish powerful modern supply chains to support the food management in transportation. The construction speed of the food companies is very fast; however, the food supply lags behind the food companies. As a result, the environmental pollution caused in the food logistics becomes seve...

Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

Science.gov (United States)

Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

2017-04-01

The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

RISK ANALYSIS AND EVALUATION FOR CRITICAL LOGISTICAL INFRASTRUCTURE

Directory of Open Access Journals (Sweden)

Sascha Düerkop

2016-12-01

Full Text Available Logistical infrastructure builds the backbone of an economy. Without an effective logistical infrastructure in place, the supply for both enterprises and consumers might not be met. But even a high-quality logistical infrastructure can be threatened by risks. Thus, it is important to identify, analyse, and evaluate risks for logistical infrastructure that might threaten logistical processes. Only if those risks are known and their impact estimated, decision makers can implement counteractive measures to reduce risks. In this article, we develop a network-based approach that allows for the evaluation of risks and their consequences onto the logistical network. We will demonstrate the relevance of this approach by applying it to the logistics network of the central German state of Hesse. Even though transport data is extensively tracked and recorded nowadays, typical daily risks, like accidents on a motorway, and extraordinary risks, like a bridge at risk to collapse, terrorist attacks or climate-related catastrophes, are not systematically anticipated. Several studies unveiled recently that the overall impact for an economy of possible failures of single nodes and/or edges in a network are not calculated, and particularly critical edges are not identified in advance. We address this information gap by a method that helps to identify and quantify risks in a given network. To reach this objective, we define a mathematical optimization model that quantifies the current “risk-related costs” of the overall network and quantify the risk by investigating the change of the overall costs in the case a risk is realized.

Multivariate statistical analysis a high-dimensional approach

CERN Document Server

Serdobolskii, V

2000-01-01

In the last few decades the accumulation of large amounts of in­ formation in numerous applications. has stimtllated an increased in­ terest in multivariate analysis. Computer technologies allow one to use multi-dimensional and multi-parametric models successfully. At the same time, an interest arose in statistical analysis with a de­ ficiency of sample data. Nevertheless, it is difficult to describe the recent state of affairs in applied multivariate methods as satisfactory. Unimprovable (dominating) statistical procedures are still unknown except for a few specific cases. The simplest problem of estimat­ ing the mean vector with minimum quadratic risk is unsolved, even for normal distributions. Commonly used standard linear multivari­ ate procedures based on the inversion of sample covariance matrices can lead to unstable results or provide no solution in dependence of data. Programs included in standard statistical packages cannot process 'multi-collinear data' and there are no theoretical recommen­ ...

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

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.

The logic of logistics theory, algorithms, and applications for logistics management

CERN Document Server

Simchi-Levi, David; Bramel, Julien

2014-01-01

Fierce competition in today's global market provides a powerful motivation for developing ever more sophisticated logistics systems. This book, written for the logistics manager and researcher, presents a survey of the modern theory and application of logistics. The goal of the book is to present the state of the art in the science of logistics management. This third edition includes new chapters on the subjects of game theory, the power of process flexibility, supply chain competition and collaboration. Among the other materials new to the edition are sections on discrete convex analysis and its applications to stochastic inventory models, as well as extended discussions of integrated inventory and pricing models. The material presents a timely and authoritative survey of the field that will make an invaluable companion to the work of many researchers and practitioners.   Review of earlier edition:   "The present book focuses on the application of operational research and mathematical modelling technique...

The cross-validated AUC for MCP-logistic regression with high-dimensional data.

Science.gov (United States)

Jiang, Dingfeng; Huang, Jian; Zhang, Ying

2013-10-01

We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

Characteristics of Logistics Outsourcing in Bulgaria: The Perspectives of the Logistics Service Providers and their Customers

Directory of Open Access Journals (Sweden)

Rakovska Miroslava

2016-10-01

Full Text Available The increased demand and supply of logistics services bring together the logistics service providers (LSPs and the companies that outsource logistics activities. LSPs stand in between those companies and their customers, thus playing an essential role for supply chain integration. If the two parties have different viewpoints of the processes in the supply chain, the fulfillment of the goal to satisfy the end customers may be hindered. The purpose of this article is two-fold: First, to investigate the characteristics of logistics outsourcing in Bulgaria from the perspectives of the logistics service providers and their customers, and more specifically, to compare their viewpoints concerning the motives for outsourcing, the methods and contents of communication and some relationship management aspects; Second, to assess the relations of the communication and relationship management aspects to customer satisfaction. This article is based on empirical data provided by 138 manufacturing and trading companies and 136 LSPs and collected through two structured questionnaires designed to address the researched issues. The data were analyzed using descriptive statistics and the independent samples t-test. The research found that the service related reasons for logistics outsourcing are prevailing and that LSPs overestimate, compared to manufacturing and trading companies, motives related to service, organizational capabilities and relationships, while more manufacturing and trading companies concern as important the availability of logistics assets and the provision of value-added services. The research also found that both the LSPs and their customers consider that the extent of sharing of knowledge and information essential for material flow integration is very low and that the usage of team meetings and joint teams is quite rare. Also, customers do not view their relationships with the LSPs as so collaborative as viewed by the LSPs. Furthermore, the

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....

Assessment of logistic outsourcing of the innovatively-active enterprise

OpenAIRE

E.A. Belovodskaya; D.A. Latunova

2013-01-01

Assessment of logistic outsourcing of the innovatively-active enterpriseThe aim of the article. The object of this article is a comparative analysis, systematization of assessment methods and methodological approach development to assess the logistics outsourcing assessment of the innovatively active enterprise. The results of the analysis. Due to our research, five approaches for outsourcing assessment were identified.The first approach suggests such way of outsourcing efficiency assessment:...

Simulation and optimization of logistics distribution for an engine production line

Energy Technology Data Exchange (ETDEWEB)

Song, L.; Jin, S.; Tang, P.

2016-07-01

In order to analyze and study the factors about Logistics distribution system, solve the problems of out of stock on the production line and improve the efficiency of the assembly line. Using the method of industrial engineering, put forward the optimization scheme of distribution system. The simulation model of logistics distribution system for engine assembly line was build based on Witness software. The optimization plan is efficient to improve Logistics distribution efficiency, production of assembly line efficiency and reduce the storage of production line. Based on the study of the modeling and simulation of engine production logistics distribution system, the result reflects some influence factors about production logistics system, which has reference value to improving the efficiency of the production line. (Author)

Ensemble preprocessing of near-infrared (NIR) spectra for multivariate calibration

International Nuclear Information System (INIS)

Xu Lu; Zhou Yanping; Tang Lijuan; Wu Hailong; Jiang Jianhui; Shen Guoli; Yu Ruqin

2008-01-01

Preprocessing of raw near-infrared (NIR) spectral data is indispensable in multivariate calibration when the measured spectra are subject to significant noises, baselines and other undesirable factors. However, due to the lack of sufficient prior information and an incomplete knowledge of the raw data, NIR spectra preprocessing in multivariate calibration is still trial and error. How to select a proper method depends largely on both the nature of the data and the expertise and experience of the practitioners. This might limit the applications of multivariate calibration in many fields, where researchers are not very familiar with the characteristics of many preprocessing methods unique in chemometrics and have difficulties to select the most suitable methods. Another problem is many preprocessing methods, when used alone, might degrade the data in certain aspects or lose some useful information while improving certain qualities of the data. In order to tackle these problems, this paper proposes a new concept of data preprocessing, ensemble preprocessing method, where partial least squares (PLSs) models built on differently preprocessed data are combined by Monte Carlo cross validation (MCCV) stacked regression. Little or no prior information of the data and expertise are required. Moreover, fusion of complementary information obtained by different preprocessing methods often leads to a more stable and accurate calibration model. The investigation of two real data sets has demonstrated the advantages of the proposed method

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.

Evolution dynamics modeling and simulation of logistics enterprise's core competence based on service innovation

Science.gov (United States)

Yang, Bo; Tong, Yuting

2017-04-01

With the rapid development of economy, the development of logistics enterprises in China is also facing a huge challenge, especially the logistics enterprises generally lack of core competitiveness, and service innovation awareness is not strong. Scholars in the process of studying the core competitiveness of logistics enterprises are mainly from the perspective of static stability, not from the perspective of dynamic evolution to explore. So the author analyzes the influencing factors and the evolution process of the core competence of logistics enterprises, using the method of system dynamics to study the cause and effect of the evolution of the core competence of logistics enterprises, construct a system dynamics model of evolution of core competence logistics enterprises, which can be simulated by vensim PLE. The analysis for the effectiveness and sensitivity of simulation model indicates the model can be used as the fitting of the evolution process of the core competence of logistics enterprises and reveal the process and mechanism of the evolution of the core competence of logistics enterprises, and provide management strategies for improving the core competence of logistics enterprises. The construction and operation of computer simulation model offers a kind of effective method for studying the evolution of logistics enterprise core competence.

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.

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

Science.gov (United States)

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-03-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states.

The Logistics Knowledge Portal: Gateway to More Individualized Learning in Logistics.

Science.gov (United States)

Neumann, Gaby; Krzyzaniak, Stanislaw; Lassen, Carl Christian

This paper describes a research and development project initiated by a network of European logistics educators to promote all types, forms, and levels of logistics education by benefiting from the educational potential of multimedia/hypermedia as well as information technology and telecommunications. The main outcome of this project will be a…

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.

Application of innovative technologies in the development of logistics in the crisis period

Directory of Open Access Journals (Sweden)

M. L. Kashirina

2016-01-01

Full Text Available Modern Russia goes through a difficult period of crisis and exchange of sanctions that have left a definite imprint on the Russian players in the logistics market. Logistics, as a so-called satellite, the motor trade is in their systems a huge potential. It is a sort of “blood arteries of the country” – water, road, rail, air. Any changes in international economic relations are automatically projected onto the market of logistics services. This article discusses the position of logistics in today's economic situation, as well as methods and means of adaptation and optimization under these conditions. The article reveals the undeniable advantages of the WMS – system, and describes a method for effective solutions for cost optimization in logistics as a cross – docking. This article also describes the idea and in fractional reveals the essence of this method of cost optimization solutions. In the process of studying the article becomes abundantly clear that this system has a distinct advantage in the absence of the need for investment funds, the only necessity of the system is an effective HR management and monitoring processes. There is confirmation of the fact that in difficult times of crisis, logistics has a huge potential and opportunities for growth and optimization. We give evidence that the innovative WMS technology strengthens its position and deeper embedded in the system of logistics and cross-docking, in turn, is one of the effective ways of making cost optimization in logistics at this time in this situation.

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.

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

Science.gov (United States)

Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W

2015-08-01

Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

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.

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...

Resource Allocation Optimization Model of Collaborative Logistics Network Based on Bilevel Programming

Directory of Open Access Journals (Sweden)

Xiao-feng Xu

2017-01-01

Full Text Available Collaborative logistics network resource allocation can effectively meet the needs of customers. It can realize the overall benefit maximization of the logistics network and ensure that collaborative logistics network runs orderly at the time of creating value. Therefore, this article is based on the relationship of collaborative logistics network supplier, the transit warehouse, and sellers, and we consider the uncertainty of time to establish a bilevel programming model with random constraints and propose a genetic simulated annealing hybrid intelligent algorithm to solve it. Numerical example shows that the method has stronger robustness and convergence; it can achieve collaborative logistics network resource allocation rationalization and optimization.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

Science.gov (United States)

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

Risks Analysis of Logistics Financial Business Based on Evidential Bayesian Network

Directory of Open Access Journals (Sweden)

Ying Yan

2013-01-01

Full Text Available Risks in logistics financial business are identified and classified. Making the failure of the business as the root node, a Bayesian network is constructed to measure the risk levels in the business. Three importance indexes are calculated to find the most important risks in the business. And more, considering the epistemic uncertainties in the risks, evidence theory associate with Bayesian network is used as an evidential network in the risk analysis of logistics finance. To find how much uncertainty in root node is produced by each risk, a new index, epistemic importance, is defined. Numerical examples show that the proposed methods could provide a lot of useful information. With the information, effective approaches could be found to control and avoid these sensitive risks, thus keep logistics financial business working more reliable. The proposed method also gives a quantitative measure of risk levels in logistics financial business, which provides guidance for the selection of financing solutions.

The logic of logistics theory, algorithms, and applications for logistics and supply chain management

CERN Document Server

Simchi-Levi, David; Bramel, Julien

2005-01-01

Fierce competition in today's global market provides a powerful motivation for developing ever more sophisticated logistics systems. This book, written for the logistics manager and researcher, presents a survey of the modern theory and application of logistics. The goal of the book is to present the state of the art in the science of logistics management. As a result, the authors have written a timely and authoritative survey of this field that many practitioners and researchers will find makes an invaluable companion to their work.

Outsourcing Wholesale Logistics, A Model for Future Systems

National Research Council Canada - National Science Library

McDaniels, Lloyd

2002-01-01

.... This paper outlines the method to reduce those costs by providing incentives to simultaneously increase operational readiness and reduce logistics requirements of the system at both the wholesale and retail levels...

Lasso and probabilistic inequalities for multivariate point processes

DEFF Research Database (Denmark)

Hansen, Niels Richard; Reynaud-Bouret, Patricia; Rivoirard, Vincent

2015-01-01

Due to its low computational cost, Lasso is an attractive regularization method for high-dimensional statistical settings. In this paper, we consider multivariate counting processes depending on an unknown function parameter to be estimated by linear combinations of a fixed dictionary. To select...... for multivariate Hawkes processes are proven, which allows us to check these assumptions by considering general dictionaries based on histograms, Fourier or wavelet bases. Motivated by problems of neuronal activity inference, we finally carry out a simulation study for multivariate Hawkes processes and compare our...... methodology with the adaptive Lasso procedure proposed by Zou in (J. Amer. Statist. Assoc. 101 (2006) 1418–1429). We observe an excellent behavior of our procedure. We rely on theoretical aspects for the essential question of tuning our methodology. Unlike adaptive Lasso of (J. Amer. Statist. Assoc. 101 (2006...

Development of multivariate NTCP models for radiation-induced hypothyroidism: a comparative analysis

International Nuclear Information System (INIS)

Cella, Laura; Liuzzi, Raffaele; Conson, Manuel; D’Avino, Vittoria; Salvatore, Marco; Pacelli, Roberto

2012-01-01

Hypothyroidism is a frequent late side effect of radiation therapy of the cervical region. Purpose of this work is to develop multivariate normal tissue complication probability (NTCP) models for radiation-induced hypothyroidism (RHT) and to compare them with already existing NTCP models for RHT. Fifty-three patients treated with sequential chemo-radiotherapy for Hodgkin’s lymphoma (HL) were retrospectively reviewed for RHT events. Clinical information along with thyroid gland dose distribution parameters were collected and their correlation to RHT was analyzed by Spearman’s rank correlation coefficient (Rs). Multivariate logistic regression method using resampling methods (bootstrapping) was applied to select model order and parameters for NTCP modeling. Model performance was evaluated through the area under the receiver operating characteristic curve (AUC). Models were tested against external published data on RHT and compared with other published NTCP models. If we express the thyroid volume exceeding X Gy as a percentage (V x (%)), a two-variable NTCP model including V 30 (%) and gender resulted to be the optimal predictive model for RHT (Rs = 0.615, p < 0.001. AUC = 0.87). Conversely, if absolute thyroid volume exceeding X Gy (V x (cc)) was analyzed, an NTCP model based on 3 variables including V 30 (cc), thyroid gland volume and gender was selected as the most predictive model (Rs = 0.630, p < 0.001. AUC = 0.85). The three-variable model performs better when tested on an external cohort characterized by large inter-individuals variation in thyroid volumes (AUC = 0.914, 95% CI 0.760–0.984). A comparable performance was found between our model and that proposed in the literature based on thyroid gland mean dose and volume (p = 0.264). The absolute volume of thyroid gland exceeding 30 Gy in combination with thyroid gland volume and gender provide an NTCP model for RHT with improved prediction capability not only within our patient population but also in an

Fourier expansions and multivariable Bessel functions concerning radiation programmes

International Nuclear Information System (INIS)

Dattoli, G.; Richetta, M.; Torre, A.; Chiccoli, C.; Lorenzutta, S.; Maino, G.

1996-01-01

The link between generalized Bessel functions and other special functions is investigated using the Fourier series and the generalized Jacobi-Anger expansion. A new class of multivariable Hermite polynomials is then introduced and their relevance to physical problems discussed. As an example of the power of the method, applied to radiation physics, we analyse the role played by multi-variable Bessel functions in the description of radiation emitted by a charge constrained to a nonlinear oscillation. (author)

Intermodal transport as an integral part of logistics system

Directory of Open Access Journals (Sweden)

Agnieszka Bitkowska

2016-06-01

Full Text Available The experience of companies that are successful in the carriage of goods prove that intermodal transport is now a major factor in determining the success of logistics system. A modern approach to the transport is based on intermodal transport. The article is based on the method of external observation. It presents the essence of intermodal transport and its benefits. It specifies transportation as an integral part of logistics system.

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

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

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.

A Novel Intensive Distribution Logistics Network Design and Profit Allocation Problem considering Sharing Economy

Directory of Open Access Journals (Sweden)

Mi Gan

2018-01-01

Full Text Available The rapid growth of logistics distribution highlights the problems including the imperfect infrastructure of logistics distribution network, the serious shortage of distribution capacity of each individual enterprise, and the high cost of distribution in China. While the development of sharing economy makes it possible to achieve the integration of whole social logistic resources, big data technology can grasp customer’s logistics demand accurately on the basis of analyzing the customer’s logistics distribution preference, which contributes to the integration and optimization of the whole logistics resources. This paper proposes a kind of intensive distribution logistics network considering sharing economy, which assumes that all the social logistics suppliers build a strategic alliance, and individual idle logistics resources are also used to deal with distribution needs. Analyzing customer shopping behavior by the big data technology to determine customer’s logistics preference on the basis of dividing the customer’s logistics preference into high speed, low cost, and low pollution and then constructing the corresponding objective function model according to different logistics preferences, we obtain the intensive distribution logistics network model and solve it with heuristic algorithm. Furthermore, this paper analyzes the mechanism of interest distribution of the participants in the distribution network and puts forward an improved interval Shapley value method considering both satisfaction and contribution, with case verifying the feasibility and effectiveness of the model. The results showed that, compared with the traditional Shapley method, distribution coefficient calculated by the improved model could be fairer, improve stakeholder satisfaction, and promote the sustainable development of the alliance as well.

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.

Simulation and optimization of logistics distribution for an engine production line

Directory of Open Access Journals (Sweden)

Lijun Song

2016-02-01

Full Text Available Purpose: In order to analyze and study the factors about Logistics distribution system, solve the problems of out of stock on the production line and improve the efficiency of the assembly line. Design/methodology/approach: Using the method of industrial engineering, put forward the optimization scheme of distribution system. The simulation model of logistics distribution system for engine assembly line was build based on Witness software. Findings: The optimization plan is efficient to improve Logistics distribution efficiency, production of assembly line efficiency and reduce the storage of production line Originality/value: Based on the study of the modeling and simulation of engine production logistics distribution system, the result reflects some influence factors about production logistics system, which has reference value to improving the efficiency of the production line.

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.

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.

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

International Production and Global Logistics Operations : Management Issues in Global Logistics with Offshored Production Systems

OpenAIRE

Korrmann, Franziska

2011-01-01

This paper is directed at discussing some of the management issues, problems and solutions of logistics in the context of offshored productive activities The introduction includes a discussion of the logistics topics and an introduction of the economic logic of offshoring. The main part analyses the logistics topics with regard to the internationally fragmented production. The topics of logistics include: Information flow and integration, transportation, inventory management, warehousing and ...

Logistical modelling of managerial decisions in social and marketing business systems

Directory of Open Access Journals (Sweden)

Oleksandr Velychko

2017-10-01

Full Text Available Logistical modelling of business systems within the context of mathematical logistics, logistical management, operational research as well as rationalistic provision of logistics at an enterprise have been considered in the article. The research was carried out on the methodological basis which included the authors’ developments and implied conveying familiar knowledge on new objects within the field of linear programming. Scientific novelty concerns the development of categorical toolkit as well as the existing methodical approaches of rationalistic logistics to managerial decisions. Rational areas of using terms “logistical model” and “model of logistics” in business environment have been determined. The authors’ methodology of constructing logistical models in management of separate social and marketing systems of enterprises according to minimization and maximization criteria is presented. Ways of using modelling at not conventional objects of logistical support for managerial decisions have been suggested in the context of studying the moral psychological climate of staff and complex estimation of socioeconomic measures of staff management improvement. The procedure of logistical optimization in the system of distributing and advertising activity of the enterprise has been developed. Approbation of the developed models has been carried out and possibilities for further model’s complication by output data, variables, and limitations under specific practical conditions have been grounded.

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

Advanced colorectal neoplasia risk stratification by penalized logistic regression.

Science.gov (United States)

Lin, Yunzhi; Yu, Menggang; Wang, Sijian; Chappell, Richard; Imperiale, Thomas F

2016-08-01

Colorectal cancer is the second leading cause of death from cancer in the United States. To facilitate the efficiency of colorectal cancer screening, there is a need to stratify risk for colorectal cancer among the 90% of US residents who are considered "average risk." In this article, we investigate such risk stratification rules for advanced colorectal neoplasia (colorectal cancer and advanced, precancerous polyps). We use a recently completed large cohort study of subjects who underwent a first screening colonoscopy. Logistic regression models have been used in the literature to estimate the risk of advanced colorectal neoplasia based on quantifiable risk factors. However, logistic regression may be prone to overfitting and instability in variable selection. Since most of the risk factors in our study have several categories, it was tempting to collapse these categories into fewer risk groups. We propose a penalized logistic regression method that automatically and simultaneously selects variables, groups categories, and estimates their coefficients by penalizing the [Formula: see text]-norm of both the coefficients and their differences. Hence, it encourages sparsity in the categories, i.e. grouping of the categories, and sparsity in the variables, i.e. variable selection. We apply the penalized logistic regression method to our data. The important variables are selected, with close categories simultaneously grouped, by penalized regression models with and without the interactions terms. The models are validated with 10-fold cross-validation. The receiver operating characteristic curves of the penalized regression models dominate the receiver operating characteristic curve of naive logistic regressions, indicating a superior discriminative performance. © The Author(s) 2013.

Logistics Cost Calculation of Implementation Warehouse Management System: A Case Study

Directory of Open Access Journals (Sweden)

Kučera Tomáš

2017-01-01

Full Text Available Warehouse management system can take full advantage of the resources and provide efficient warehousing services. The paper aims to show advantages and disadvantages of the warehouse management system in a chosen enterprise, which is focused on logistics services and transportation. The paper can bring new innovative approach for warehousing and presents how logistics enterprise can reduce logistics costs. This approach includes cost reduction of the establishment, operation and savings in the overall assessment of the implementation of the warehouse management system. The innovative warehouse management system will be demonstrated as the case study, which is classified as a qualitative scientific method, in the chosen logistics enterprise. The paper is based on the research of the world literature, analyses of the internal logistics processes, data and finally enterprise documents. The paper discovers costs related to personnel costs, handling equipment costs and costs for material identification. Implementation of the warehouse management system will reduce overall logistics costs of warehousing and extend the warehouse management system to other parts of the logistics chain.

Multivariate Analysis of Multiple Datasets: a Practical Guide for Chemical Ecology.

Science.gov (United States)

Hervé, Maxime R; Nicolè, Florence; Lê Cao, Kim-Anh

2018-03-01

Chemical ecology has strong links with metabolomics, the large-scale study of all metabolites detectable in a biological sample. Consequently, chemical ecologists are often challenged by the statistical analyses of such large datasets. This holds especially true when the purpose is to integrate multiple datasets to obtain a holistic view and a better understanding of a biological system under study. The present article provides a comprehensive resource to analyze such complex datasets using multivariate methods. It starts from the necessary pre-treatment of data including data transformations and distance calculations, to the application of both gold standard and novel multivariate methods for the integration of different omics data. We illustrate the process of analysis along with detailed results interpretations for six issues representative of the different types of biological questions encountered by chemical ecologists. We provide the necessary knowledge and tools with reproducible R codes and chemical-ecological datasets to practice and teach multivariate methods.

Factors associated with utilization of long-acting and permanent contraceptive methods among women who have decided not to have more children in Gondar city.

Science.gov (United States)

Zenebe, Chernet Baye; Adefris, Mulat; Yenit, Melaku Kindie; Gelaw, Yalemzewod Assefa

2017-09-06

Despite the fact that long acting family planning methods reduce population growth and improve maternal health, their utilization remains poor. Therefore, this study assessed the prevalence of long acting and permanent family planning method utilization and associated factors among women in reproductive age groups who have decided not to have more children in Gondar city, northwest Ethiopia. An institution based cross-sectional study was conducted from August to October, 2015. Three hundred seventeen women who have decided not to have more children were selected consecutively into the study. A structured and pretested questionnaire was used to collect data. Both bivariate and multi-variable logistic regressions analyses were used to identify factors associated with utilization of long acting and permanent family planning methods. The multi-variable logistic regression analysis was used to investigate factors associated with the utilization of long acting and permanent family planning methods. The Adjusted Odds Ratio (AOR) with the corresponding 95% Confidence Interval (CI) was used to show the strength of associations, and variables with a P-value of <0.05 were considered statistically significant. In this study, the overall prevalence of long acting and permanent contraceptive (LAPCM) method utilization was 34.7% (95% CI: 29.5-39.9). According to the multi-variable logistic regression analysis, utilization of long acting and permanent contraceptive methods was significantly associated with women who had secondary school, (AOR: 2279, 95% CI: 1.17, 4.44), college, and above education (AOR: 2.91, 95% CI: 1.36, 6.24), history of previous utilization (AOR: 3.02, 95% CI: 1.69, 5.38), and information about LAPCM (AOR: 8.85, 95% CI: 2.04, 38.41). In this study the prevalence of long acting and permanent family planning method utilization among women who have decided not to have more children was high compared with previous studies conducted elsewhere. Advanced educational

Sparse logistic principal components analysis for binary data

KAUST Repository

Lee, Seokho; Huang, Jianhua Z.; Hu, Jianhua

2010-01-01

with a criterion function motivated from a penalized Bernoulli likelihood. A Majorization-Minimization algorithm is developed to efficiently solve the optimization problem. The effectiveness of the proposed sparse logistic PCA method is illustrated

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...

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)

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...

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

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...

Logistics, electronic commerce, and the environment

Science.gov (United States)

Sarkis, Joseph; Meade, Laura; Talluri, Srinivas

2002-02-01

Organizations realize that a strong supporting logistics or electronic logistics (e-logistics) function is important from both commercial and consumer perspectives. The implications of e-logistics models and practices cover the forward and reverse logistics functions of organizations. They also have direct and profound impact on the natural environment. This paper will focus on a discussion of forward and reverse e-logistics and their relationship to the natural environment. After discussion of the many pertinent issues in these areas, directions of practice and implications for study and research are then described.

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%.

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...

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...

Logistics-production, logistics-marketing and external integration: Their impact on performance

OpenAIRE

Giménez, Cristina; Ventura, Eva

2003-01-01

Highly competitive environments are leading companies to implement Supply Chain Management (SCM) to improve performance and gain a competitive advantage. SCM involves integration, co-ordination and collaboration across organisations and throughout the supply chain. It means that SCM requires internal (intraorganisational) and external (interorganisational) integration. This paper examines the Logistics-Production and Logistics- Marketing interfaces and their relation with the external integra...

The Challenge of Moving from Performance Based Logistics to an Operational Logistics Framework

National Research Council Canada - National Science Library

Bryant, Russell E

2005-01-01

... and qualified forces for the combatant commanders of the 21st century. One focal area is within the logistics area of overall warfighter support, commonly referred to as performance based logistics (PBL...

Formation of the mechanism of realisation of the logistics strategy of river ports

Directory of Open Access Journals (Sweden)

Tymoshchuk Olena M.

2013-03-01

Full Text Available The article identifies the role of river ports in the logistical chain of supplies of the transportation system of Ukraine. It envisages to use the developed logistics strategy for creation of river logistics centres on the basis of river ports with a high level of logistical attractiveness, which would become organisers of cargo delivery at a certain stage of movement of goods and a connecting logistical link at the junction of transport elements of the system (systems of managing the process of transportation, information support, selection of optimal technological schemes of cargo treatment in the port and optimal interaction of adjacent types of transport, methods of management (organisational, economic, technical and technological, and legal, logistical principles and technologies, which would allow achievement of effective realisation of the logistics strategy of a river port. The article offers to create a separate commercial structure – information logistics centre, which would ensure information support of the logistical movement of goods and optimal managerial decision making.

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...

Various forms of indexing HDMR for modelling multivariate classification problems

Energy Technology Data Exchange (ETDEWEB)

Aksu, Çağrı [Bahçeşehir University, Information Technologies Master Program, Beşiktaş, 34349 İstanbul (Turkey); Tunga, M. Alper [Bahçeşehir University, Software Engineering Department, Beşiktaş, 34349 İstanbul (Turkey)

2014-12-10

The Indexing HDMR method was recently developed for modelling multivariate interpolation problems. The method uses the Plain HDMR philosophy in partitioning the given multivariate data set into less variate data sets and then constructing an analytical structure through these partitioned data sets to represent the given multidimensional problem. Indexing HDMR makes HDMR be applicable to classification problems having real world data. Mostly, we do not know all possible class values in the domain of the given problem, that is, we have a non-orthogonal data structure. However, Plain HDMR needs an orthogonal data structure in the given problem to be modelled. In this sense, the main idea of this work is to offer various forms of Indexing HDMR to successfully model these real life classification problems. To test these different forms, several well-known multivariate classification problems given in UCI Machine Learning Repository were used and it was observed that the accuracy results lie between 80% and 95% which are very satisfactory.

Multivariate statistical characterization of groundwater quality in Ain ...

African Journals Online (AJOL)

Administrator

depends much on the sustainability of the available water resources. Water of .... 18 wells currently in use were selected based on the preliminary field survey carried out to ... In recent times, multivariate statistical methods have been applied ...

Logistics Service Provider Selection through an Integrated Fuzzy Multicriteria Decision Making Approach

OpenAIRE

Gülşen Akman; Kasım Baynal

2014-01-01

Nowadays, the demand of third-party logistics provider becomes an increasingly important issue for companies to improve their customer service and to decrease logistics costs. This paper presents an integrated fuzzy approach for the evaluation and selection of 3rd party logistics service providers. This method consists of two techniques: (1) use fuzzy analytic hierarchy process to identify weights of evaluation criteria; (2) apply fuzzy technique for order preference by similarity to ideal so...

Reverse Logistics Systems: Persepsi dan Harapan Konsumen

Directory of Open Access Journals (Sweden)

Farida Pulansari

2016-12-01

Full Text Available Complaint is a signal that indicates important information directly by customers. Complaint will give valuable information to company to plan recovery strategies to maintain customer satisfaction and loyalty. Hence, Electronic Waste (E-waste becomes a hot issue internationally, domestically and locally. There are many kind of regulations, strategy, methods or approach to minimize of E-waste. The goal of this research is design of House of Reverse Logistics (HRL to understanding the customer needs and wants for Reverse Logistics (RL implementation. This research adopted Quality Function Deployment (QFD method to construct the HRL. Differences among them are determination of the customer needs and wants. HRL insert five perspectives i.e. Input, Structure, Process, Output and Social & Organization. In other hand, QFD only inserts consumer perspective. The results showed the highest factors of consumer dissatisfaction comes from: 20% of third-party services mechanism, 10% from collaboration RL system (collection centers, recycling centers, disposal center ,10% comes the standardization of servicing system and 60% of others

Subset selection from generalized logistic populations

NARCIS (Netherlands)

Laan, van der M.J.; Laan, van der P.

1997-01-01

We give an introduction to the logistic and generalized logistic distributions. These generalized logistic distributions Type-I, Type-II and Type-III are indexed by a real valued parameter. They have been derived as mixtures with the standard logistic distribution and for discrete values of the

Conversion from laparoscopic to open cholecystectomy: Multivariate analysis of preoperative risk factors