data analysis IEEE PAPER 2017





Spatial PanelData Analysis .
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Since the turn of the century, the spatial econometrics literature has shifted its interest from the specification and estimation of econometric relationships based on cross-sectionaldata to spatial panels. Spatial panels refer to georeferenced pointdataover time of individuals,

GFA: ExploratoryAnalysisof MultipleDataSources with Group FactorAnalysis
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Abstract The R package GFA provides a full pipeline for factoranalysisof multipledata sources that are represented as matrices with co-occurring samples. It allows learning dependencies between subsets of thedatasources, decomposed into latent factors. The

Monte Carlo Methods for BayesianData Analysisin Astronomy
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Abstract Monte Carlo based Bayesiandata analysishas now become the method of choice for analyzing and interpretingdatain almost all disciplines of science. In astronomy, over the last decade, we have also seen a steady increase in the number of papers that employ Using ExploratoryData Analysisto Improve the Fresh Foods Ordering Process in Retail Stores
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Summary: With the advent of the information era and abundance of availability ofdata , the approaches used by quality professionals can be significantly complemented by the art of datascience. This case study demonstrates how explorativedata analysisand basic

Compositionaldata analysisof household waste recycling centres in Denmark
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Abstract The Danish government has set a target of 50% recycling rates for household waste by 2022. To achieve this goal, the Danish municipalities should increase the source separation of household waste. While significant knowledge and experiences were locally

Detecting delays in motor skill development of children throughdata analysisof a smart play device
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ABSTRACT This paper describes experiments with a game device that was used for early detection of delays in motor skill development in primary school children. Children play a game by bi-manual manipulation of the device which continuously collects accelerometer

Dynamic PanelData Analysisof CO2 Emissions Driving Forces
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Abstract Interaction between human beings and their natural environment has led to threats to ecosystems. To study this relationship, several sociological theories have been developed, among them treadmill of destruction, world system position, ecological In [1], we described a novel approach to deal with the local depth estimation in shallow coastal areas through marine radardata . The reconstruction technique is based on the maximization of the normalized scalar product (NSP) between the theoretical and the differences in time spent sedentary and in physical activity during leisure: A comparison ofdataanalyzed using a traditional approach and compositionaldata analysis
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Abstract AIM:Data analysisin studies of time spent sedentary and in physical activities does not usually consider the fact that these behaviors are expressed in terms of proportions of a finite time and therefore statistically dependent in a compositional fashion. The aim of this

Low levels of calcium or vitamin D, which is more important in systemic lupus erythematosus patients? An extensivedata analysis
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Objective Several reports have indicated an association between systemic lupus erythematosus (SLE) and low levels of vitamin D. We examined several blood work parameters in SLE patients and controls and performed an extensivedata analysisin order

Analysisof Mahatma Gandhi National Rural Employment Guarantee Act UsingDataMining
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Abstract Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) aims at livelihood security of people in rural areas by guaranteeing hundred days of wage employment in a financial year to a rural household whose adult members volunteer to do Pre-processing influences on multivariatedata analysisof time-of-flight secondary ion mass spectroscopydataand images
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Time-of-Flight Secondary Ion Mass Spectroscopy (ToF-SIMS) has been used in the investigation and examination of biological compounds for more than three decades. Currently, ToF-SIMS dataanalyses are quite daunting tasks and there exists problems with their interpretation. Multivariate In my general chemistry course at the University of Debrecen, I teach that chemistry became an independent science at the end of the 18th century largely thanks to the introduction of systematic quantitative measurements, which was pioneered by Antoine Laurent Lavoisier

The reality of routine practice: a pooleddata analysison chronic wounds treated with TLC-NOSF wound dressings
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Objective: A number of randomised controlled trials (RCT) have compared control groups with TLC-NOSF dressings (UrgoStart) on chronic wounds. Our aim was to determine whether the clinical trials results translate into routine management of such wounds, by Videodata analysishas become an increasingly important research area with widespread applications in automatic surveillance of transportation infrastructure including roads, rail and airports. As the amount of videodatacollected grows, so does the opportunity for further

The categorization experiment: Experimental design anddata analysis
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The long history of categorization experiments indicates that many important design choices can critically affect the quality of the resultingdata . Unfortunately, the optimal choices depend on the goals of the experiment, so there is no single template that a new researcher

The Role of Family on Current Lifestyle Choices: A Qualitative SecondaryData Analysisof Interracial and Same-Race Couples
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1 ; College of Education 2 ; University of Arizona, Tucson, AZ Qualitativedataanalysisand
interpretations were based on 14 romantic couples 7 same-race couples (Non-Hispanic White
partners) and 7 interracial couples (Non-Hispanic White partner and Hispanic partner).4. How

Impact of GUT Microbiota on the Type 2 Diabetes Mellitus: NGS Meta- Data Analysis
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Abstract: Metagenomic sequencing is one of the important applications by the Next Generation Sequencing (NGS). The metagenomeanalysisis useful to study the characteristics of composite microbial groups including uncultivable microbes in various

Lens Depth Function and k-Relative Neighborhood Graph: Versatile Tools for OrdinalData Analysis
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Abstract In recent years it has become popular to study machine learning problems in a setting of ordinal distance information rather than numerical distance measurements. By ordinal distance information we refer to binary answers to distance comparisons such as d

Towards a pragmatic approach to compositionaldata analysis
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Abstract: Compositionaldataare nonnegativedatawith the property of closure: that is, each set of values on their components, or so-called parts, has a fixed sum, usually 1 or 100%. The approach to compositionaldata analysisoriginated by John Aitchison uses ratios of Application of Fiber-optic TemperatureData Analysisin Hydraulic Fracturing Evaluation--A Case Study in Marcellus Shale
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Abstract Technology advancement is a key parameter to gain more information, and valuable insight in the area where we lack proper knowledge to make the right decision at the right time. Development of unconventional resources is an area where application of

PGEE: An R Package forAnalysisof LongitudinalDatawith High-Dimensional Covariates
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Abstract We introduce an R package PGEE that implements the penalized generalized estimating equations (GEE) procedure proposed by Wang et al.(2012) to analyze longitudinaldatawith a large number of covariates. The PGEE package includes three main Natural language processing is another area of bigdatainquiry in the field of Communications. In this vein of research, scholars explore the way that computers can develop an understanding of language and generate responses. Often studied along with

Consideration of Statistical vs. Biological Significances for OmicsData -based Pathway NetworkAnalysis
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ABSTRACT In the era of biological omics, an essential issue is how to mine the important biological information, including important signaling molecule patterns, signaling pathways, molecular networks, and pathwaynetwork systems, from big omicdatain combination with Following the genomics revolution, proteomics, metabolomics, and lipidomics studies have emerged, among others, as a natural follow-up either in the investigation of human biology or, similarly, in animal or plant studies. The combined use of these omics fields may lead to a

Factors Influencing Inter-regional Living-Cost Differentials: PanelData Analysisfor the Case of the US
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ABSTRACT This empirical study seeks to identify key factors that have influenced geographic (interstate) living-cost differentials in the US in recent years. However, given the evolving literature on the effects of economic freedom in recent years, unlike previous

SmartData Analysisfor Smart Water Networks
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ABSTRACT Water is an indispensable resource for human and economical welfare, and modern society depends on complex, interconnected infrastructures to provide safe water to consumers. Given this complexity, efficient numerical techniques are needed to support

ALGORITHM PERFORMANCE IN GENE EXPRESSIONDATA ANALYSISTHROUGH PRE-PROCESSING WITH PRINCIPAL COMPONENTANALYSISAND
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ABSTRACT: High volume ofdatafrom recent high-throughput omics technologies and the study of particular diseases, such as cancer, represent a challenge to create new platforms able to analyze complexdatasets, in order to extract biologically relevant information. The

The XMM-Newton ABC Guide: An Introduction to XMM-NewtonData Analysis
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4 Setting Up and Running SAS 10 4.1 Installation10 4.2 CalibrationData10 4.3 SAS Environmental Parameters and Invocation. 10 4.3. 1 SAS Helpful Hints . 11 4.4 SAS

Determinants of Credit Default Swap Spreads: A Four-Market PanelData Analysis
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Abstract This paper attempts to elucidate whether firm performance and macroeconomic conditions play a significant role in explaining credit default swap (CDS) spreads. Our panel dataset covers 112 reference entities in four markets (South Korea, Hong Kong, France, and

LANDSAT BIGDATA ANALYSISFOR DETECTING LONG-TERM WATER QUALITY CHANGES: A CASE STUDY IN THE HAN RIVER, SOUTH KOREA.
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JC Seonga,*, CS Hwangb, R. Gibbsa, K. Roha, MR Mehdic, C. Ohd, JJ Jeonge a Dept. of Geosciences, University of West Georgia, Carrollton, Georgia, USA (jseong@ westga. edu, rgibbs2@ my. westga. edu, rkwanhun@ westga. edu) b Dept. of Geography, Kyunghee

RECONCILIATION OF CORE AND LOGDATA ANALYSISIN FRESH WATER FLUVIAL RESERVOIRS OF KRISHNA GODAVARI BASIN, EAST COAST, INDIA
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ABSTRACT Fresh water fluvial reservoirs of Krishna Godavari basin are generally very complex and heterogeneous, ranging from very coarse to very fine/silty sand sequences. Low resistivity pays does not indicate any particular lithological cause of lowering of

Parallel Implementation of the Ensemble Empirical Mode Decomposition (PEEMD) and Its Application 2 for Earth ScienceData Analysis3
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To efficiently perform multiscaleanalysisof high-resolution, global, multiple-16 dimensional datasets, we have deployed the parallel ensemble empirical mode 17 decomposition (PEEMD) package by implementing three-level parallelism into the 18 ensemble Empirical

Quality ControlData Analysis
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D Lorenz, L Medalie, J Martin - 2017 - rdrr.io Most of the examples will use datasets supplied in the smwrQW package, but the Statistical Concepts section will use small, artificial datasets, with known properties to illustrate the use of the functions. The artificialdataare classlcensrather than classqw,but the statistical methods

THCM Coupled Model for Hydrate-Bearing Sediments:Data Analysisand Design of New Field Experiments (Marine and Permafrost Settings)
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ABSTRACT Stability conditions constrain the occurrence of gas hydrates to submarine sediments and permafrost regions. The amount of technically recoverable methane trapped in gas hydrate may exceed 104tcf. Gas hydrates are a potential energy resource, can This book comprises a collection of research contributions toward high-dimensionaldata analysis . In thisdata -centric world, we are often challenged withdatasets containing many predictors in the model at hand. In a host of situations, the number of predictors may very

Event Classification from SensorDatausing SpectralAnalysisin Robotic Finishing Processes.
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Abstract: Process monitoring using indirect methods leverages on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of bigdatamanagement andanalysis . Due to uncertainty in the frequency of events

Applications of Clustering Algorithms in theAnalysisof Mass SpectrometryData
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ABSTRACT Mass spectrometry (MS) is an experimental technique in chemistry that is used to assist in the identification of chemical compounds by means of fragmentation. However due to the amount of noise in thedata , current methods ofanalysisare very manual and

Frequency of worsening liver function in severe dengue hepatitis patients receiving paracetamol: A retrospectiveanalysisof hospitaldata
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Abstract Objective: To determine the frequency of worsening liver function among hospital in patients with severe dengue hepatitis receiving paracetamol. Methods: This retrospective study was conducted at the Department of Medicine, Aga Khan University Hospital, Karachi,

A collection of sport activity datasets fordata analysisanddatamining 2017a
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This technical report presents a collection of sport activity datasets fordatamining purposes. It is following the three previously published collections in 2015 [1] and 2016 [2, 3] and covers various sports and different types of athletes (professionals and amateurs).Data

Biostatistics andData Analysis
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The course will address issues relating to research in the fields of biology and medicine using mathematical method and especially from probability theory. This approach will quantify accurately, significant relationships between different phenomena related to human Editorial Note: WebData Analysisin Pervasive Multimedia Environment
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Editorial Note: WebDataAnalysisin Pervasive Multimedia Environment Published online: 20
Science+Business Media New York 2017 Multimedia Tools and
Applications gratefully acknowledges the editorial work of the scholars listed below on the special

Towards integrateddata analysisof divertor diagnostics with ray-tracing
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Building a better understanding of divertor physics for ITER and DEMO will require developing techniques that can integrate information from multiple diagnostics into a unified analysisof the underlying plasma properties. The charge-exchange recombination and

DA. 1 The State of the Art in Privacy-PreservingData Analysis
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Abstract This document describes recent developments in privacy-preservingdata analysis , with particular focus on secure multiparty computation and machine learning. As the availability and accessibility of measurement and storage devices increases, so too does the

BigData Analysisin Smart Manufacturing: A Review
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Abstract The technological evolution emerges a unified (Industrial) Internet of Things network, where loosely coupled smart manufacturing devices build smart manufacturing systems and enable comprehensive collaboration possibilities that increase the dynamic

Analysisof Student Learning Experience by Mining Social MediaData
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Abstract: Many issues like depression, suicide, anger, anxiety are increasing among students. These issues are necessary to seek out and analyze, but students never discuss their issues with anyone. Today Social media is very popular medium where individuals

ComparativeAnalysisbetween Rough set theory andDatamining algorithms on their prediction
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Abstract During the last few years there is a remarkable increase in development ofData mining techniques. Nowadays, various organizations store their information as a kind of databases. So huge amount ofdataand their informations are available in repositories. To

VisualAnalysisof LargeDataTextAn Empirical Study Based on Sohu NewsData
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Abstract The arrival of the era of bigdata , making it very important to extract value from the massivedata .Datamining on the basis of the new requirements. Open source R software integrates a variety ofdata analysisand visualization methods, with powerfuldata analysis

Modelling Animal Activity as Curves: An Approach Using Wavelet-Based FunctionalData Analysis
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Abstract Temporal activity patterns in animals emerge from complex interactions between choices made by organisms as responses to biotic interactions and challenges posed by external factors. Temporal activity pattern is an inherently continuous process, even being

What Users Dont Expect about ExploratoryData Analysison Approximate Query Processing Systems.
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ABSTRACT Pangloss implementsOptimistic Visualization , a method that gives analysts confidence to use approximate results for exploratorydata analysis . In this paper, we outline how analysts experience with an approximate visualization system did not match their

An Application of Generalized Entropy Optimization Methods in SurvivalData Analysis
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Abstract In this paper, survivaldata analysisis realized by applying Generalized Entropy Optimization Methods (GEOM). It is known that all statistical distributions can be obtained as MaxEnt distribution by choosing corresponding moment functions. However, Generalized

Automating ComplexData Analysis : A Disruptive Business Opportunity
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ABSTRACT Complexdata analysisis a multi-billion dollar business. Majordata analysistool makers alone report revenues totaling over $4 billion per year: SAS Institute ($3.2 Billion), IBM SPSS ($0.3-1.0 Billion), MathWorks ($850 Million), Wolfram Research (at least $40 STREAMLINE-StreamlinedAnalysisofDataat Rest andDatain Motion.
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ABSTRACT STREAMLINE aims for improving the overall workflow of bigdataanalytics systems. For this goal, it combines research in different areas to reduce the complexity of the work withdataat rest anddatain motion in a unified fashion. As a foundation STREAMLINE

AnalysisofDataUsingDataMining tool Orange
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Abstract:DataMining is a process of computing models or design in large collection ofdata . There are many tools to analyze, visualize and extractdatausingdatamining. However all the tools are not compatible to perform allanalysisoperations, In this paper we have

Using pRoloc for spatial proteomicsdata analysis
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Abstract This tutorial illustrates the usage of the pRoloc R package for theanalysisand interpretation of spatial proteomicsdata . It walks the reader through the creation of MSnSet instances, that hold the quantitative proteomicsdataand meta- dataand introduces several

Impact of socioeconomic factors on nutritional diet in Vietnam from 2004 to 2014: new insights using compositionaldata analysis
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Abstract This paper contributes to theanalysisof the impact of socioeconomic factors, like food expenditure level and urbanization, on diet patterns in Vietnam, from 2004 to 2014. Contrary to the existing literature, we focus on the diet balance in terms of macronutrients

Feature Ranking BasedDataClassification for Large ScaleData AnalysisUsing J48 Algorithm
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DataMining is a technique used in various domains to give meaning to the availabledata and different types ofDatato be handled like numericaldata , non-numericdata , image dataetc. In classification tree modelling thedatais classified to make predictions about

Language-agnosticdata analysisworkflows and reproducible research
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This talk: language-agnostic (or polyglot)analysisworkflowsIll show how it is possible to work in multiple languages and switch between them without leaving the workflow you started Additionally, Ill demonstrate how an entire workflow can be encapsulated in a markdown file

Treatment Delay and Total Delay among Pulmonary Tuberculosis Patients in the North of Iran: Application SurvivalData Analysis
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Background: Tuberculosis (TB) remains the leading cause of death among infectious diseases worldwide. Identifying the factors associated with the treatment delay and total delay would be helpful in the prevention of tuberculosis and in reducing the burden on the

ArrayUDF: User-Defined ScientificData Analysison Arrays
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ABSTRACT User-Defined Functions (UDF) allow application programmers to specify analysisoperations ondata , while leaving thedatamanagement tasks to the system. This general approach enables numerous customanalysisfunctions and is at the heart of the

A BigData AnalysisApproach for Rail Failure Risk Assessment
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Railway infrastructure monitoring is a vital task to ensure rail transportation safety. A rail failure could result in not only a considerable impact on train delays and maintenance costs, but also on safety of passengers. In this article, the aim is to assess the risk of a rail failure by

Advertising recommendation system based on dynamicdata analysison Turkish speaking Twitter users
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Original scientific paper Online environments and especially social networks have become a great alternative to advertisement publishing. In order to accomplish effective advertising it is important that the contents coincide with the expectations of the target audience.

FROM THE CLASSROOM TO THE WORKPLACE: HOW SOCIAL SCIENCE STUDENTS ARE LEARNING TO DODATA ANALYSISFOR REAL.
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ABSTRACT In British social science degree programmes, methods courses have a bad press, and statistics courses in particular are not well-liked by most students. A nationallycoordinated, strategic investment in quantitative skills training, Q-Step, is an

DataReduction Techniques for Scientific Visualization andData Analysis
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The classic paradigm for scientific visualization anddata analysisis post-hoc, where simulation codes write results on the file system and visualization routines read them back to operate. This paradigm sees file I/O as an increasing bottleneck, in terms of both transfer

Using Blundell-Bond Estimator In Dynamic PanelData Analysis : Case Of Money Demand Function With The Inclusion Of Financial Innovation
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Abstract The banking system has experienced rapid and significant technological changes in recent years that is the subject of this paper; however, the individual effect of most of these innovations has not been estimated. The demand for money is a very important for the

Adata analysisworkflow to enhance clay and organic carbon models using proximal Vis-NIRdata
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Adataanalysisworkflow to enhance clay and organic carbon models using proximal


Critical Factors of the New Islamic Supply Chain Model Through the Lens of DescriptiveData Analysis
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Abstract This empirical paper is endeavoured to confirm the critical factors of the Islamic supply chain model in Malaysia. The seven (7) constructs are inclusive of halal integrity, halal logistics practicesindustry; halal logistics service providers; halal collaboration When China started to push for proteome research in 2010, Dr. John Bergeron from McGill University had just finalized with colleagues a report from a Human Proteome Organization (HUPO) test sample working group, which had sent an equimolar mixture of 20 highly

Bigdata analysis : Trump effect on trade narratives
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In 1933, President Franklin D. Roosevelt began to broadcast his famousfireside chatsa critical move that helped to lift the economy out of the Great Depression by restoring peoples confidence in the banking sector and the economic system as a whole. Since then,

Analysisof Team Tutoring TrainingData
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ABSTRACT In 2015, the Army identified intelligent tutoring as a key tool for preparing soldiers in an ever-changing world. Intelligent tutoring uses targeted feedback to train soldiers in critical skills. Not only can tutoring train individuals, it can also train teams. As

NEW TECHNIQUE OF ACADEMICDATA ANALYSISBY FUZZY VARIANCE
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ABSTRACT Background: The importance of academicdatacounts by the modern society. Theanalysisof the academicdatais more important than previous statement. The objective of academicdata analysisis to explore more information for future academic improvements.

GAGE GPSData AnalysisPlan
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GPSdata analysisfor initially the Plate Boundary Observatory (PBO) and currently the Geodesy Advancing Geosciences and EarthScope (GAGE) project is carried out in two phases.Analysiscenters (ACs) at the Central Washington University (CWU) and New Hollstein (2011) delineates six areas where qualitative research is helpful in social network research:(a) exploration of networks,(b) network practices,(c) network orientation and assessments,(d) how networks matter,(e) understanding network dynamics, and (f)

Drug-induced sedation endoscopy:datacapture,data analysisand sedation administration
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The article Sleep Endoscopy Midazolam: Sedation Level Evaluation with Bispectral Analysisby Abdullah et al. is the first study to examine in detail the effect of midazolam using bispectralanalysisduring drug-induced sedation endoscopy (DISE)[1]. Our interest in

FunctionalData Analysisof SpectroscopicDatawith Application to Classification of Colon Polyps
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Abstract In this study, two functional logistic regression models with functional principal component basis (FPCA) and functional partial least squares basis (FPLS) have been developed to distinguish precancerous adenomatous polyps from hyperplastic polyps for the

Literature Review and Challenges ofDataMining Techniques for Social NetworkAnalysis
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AbstractDatamining is the extraction of projecting information from largedatasets, is a great innovative technology. The overall goal of thedatamining process is to extract information from adataset and transform it into an understandable structure for further use.

Systematic complaintdata analysisin a supply chain network context to recognise the quality targets of welding production
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The network context has moved into a focus of discussions on enhancing productivity and profitability of manufacturing in welding production. At the same time, the quality of manufacturing is taken under consideration in both internal and external functions of

Are the temperature of Indian cities Increasing?: Some Insights Using Change PointAnalysiswith FunctionalData
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Abstract In recent years there has been considerable concern expressed worldwide regarding increase in temperature popularly called the global warming problem. In this paper we examine monthly temperaturedataof nine Indian cities for the period 1961 to

Expectile Matrix Factorization for SkewedData Analysis .
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Abstract Matrix factorization is a popular approach to solving matrix estimation problems based on partial observations. Existing matrix factorization is based on least squares and aims to yield a low-rank matrix to interpret the conditional sample means given the

SecondaryData Analysisof Survey Responses: Using a Step-by-Step Guide
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Abstract Secondarydata , often collected for billing purposes or administrative decision making, may also be useful in the development of a program of research. In order to utilize secondarydata , it must be managed, understood, and made ready foranalysis . The purpose CSE PROJECTS

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