Search results for: mathematical data analysis.

Authors: H. C. Chinwenyi, H. D. Ibrahim, J. O. Adekunle

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The incubation period is defined as the time from infection with a microorganism to development of symptoms. In this research, two disease models: one with incubation period and another without incubation period were studied. The study involves the use of a  mathematical model with a single incubation period. The test for the existence and stability of the disease free and the endemic equilibrium states for both models were carried out. The fourth order Runge-Kutta method was used to solve both models numerically. Finally, a computer program in MATLAB was developed to run the numerical experiments. From the results, we are able to show that the endemic equilibrium state of the model with incubation period is locally asymptotically stable whereas the endemic equilibrium state of the model without incubation period is unstable under certain conditions on the given model parameters. It was also established that the disease free equilibrium states of the model with and without incubation period are locally asymptotically stable. Furthermore, results from numerical experiments using empirical data obtained from Nigeria Centre for Disease Control (NCDC) showed that the overall population of the infected people for the model with incubation period is higher than that without incubation period. We also established from the results obtained that as the transmission rate from susceptible to infected population increases, the peak values of the infected population for the model with incubation period decrease and are always less than those for the model without incubation period.

Keywords: Asymptotic stability, incubation period, Routh-Hurwitz criterion, Runge Kutta method.

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Authors: S. Hariharan, P. Muthuchidambaranathan

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In this paper, we consider a multi user multiple input multiple output (MU-MIMO) based cooperative reporting system for cognitive radio network. In the reporting network, the secondary users forward the primary user data to the common fusion center (FC). The FC is equipped with linear equalizers and an energy detector to make the decision about the spectrum. The primary user data are considered to be a digital video broadcasting - terrestrial (DVB-T) signal. The sensing channel and the reporting channel are assumed to be an additive white Gaussian noise and an independent identically distributed Raleigh fading respectively. We analyzed the detection probability of MU-MIMO system with linear equalizers and arrived at the closed form expression for average detection probability. Also the system performance is investigated under various MIMO scenarios through Monte Carlo simulations.

Keywords: Cooperative MU-MIMO, DVB-T, Linear Equalizers.

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Authors: Pa Pa Lin

Abstract:

This research work is concerned with the eigenvalue problem for the integral operators which are obtained by linearization of a nonlocal evolution equation. The purpose of section II.A is to describe the nature of the problem and the objective of the project. The problem is related to the “stable solution" of the evolution equation which is the so-called “instanton" that describe the interface between two stable phases. The analysis of the instanton and its asymptotic behavior are described in section II.C by imposing the Green function and making use of a probability kernel. As a result , a classical Theorem which is important for an instanton is proved. Section III devoted to a study of the integral operators related to interface dynamics which concern the analysis of the Cauchy problem for the evolution equation with initial data close to different phases and different regions of space.

Keywords: Evolution, Green function, instanton, integral operators.

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Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel

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Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.

Keywords: Educational data visualization, high-level petri nets, instructional design, learning analytics.

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Authors: Abdulfattah M. Alkherraz, Zaineb I. Lusta, Ahmed E. Zubi

Abstract:

The environmental pollution by heavy metals became  more problematic nowadays. To solve the problem of Cadmium  accumulation in human organs which lead to dangerous effects on  human health, and to determine its concentration, the organic legand  1-phenyl-3-benzoyl-2-thiourea was used to extract the cadmium ions  from its solution. This legand as one of thiourea derivatives was  successfully synthesized. The legand was characterized by NMR and  CHN elemental analysis, and used to extract the cadmium from its  solutions by formation of a stable complex at neutral pH. The  complex was characterized by elemental analysis and melting point.  The concentrations of cadmium ions before and after the extraction  were determined by Atomic Absorption Spectrophotometer (AAS).  The data show the percentage of the extract was more than 98.7% of  the concentration of cadmium used in the study

Keywords: Thiourea derivatives, cadmium extraction.

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Authors: Tadeusz Nowicki, Radosław Pytlak, Robert Waszkowski, Jerzy Bertrandt, Anna Kłos

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This paper presents methods for formal modeling of activities in the area of sanitary inspectors outbreak of food-borne diseases. The models allow you to measure the characteristics of the activities of sanitary inspection and as a result allow improving the performance of sanitary services and thus food security.

Keywords: Food-borne disease, epidemic, sanitary inspection, mathematical models.

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Authors: Siti Azrina B. A. Aziz, Siti Hafizah A. Hamid

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New approaches to analyze and visualize data stream in real-time basis is important in making a prompt decision by the decision maker. Financial market trading and surveillance, large-scale emergency response and crowd control are some example scenarios that require real-time analytic and data visualization. This situation has led to the development of techniques and tools that support humans in analyzing the source data. With the emergence of Big Data and social media, new techniques and tools are required in order to process the streaming data. Today, ranges of tools which implement some of these functionalities are available. In this paper, we present chronological evolution evaluation of technologies for supporting of real-time analytic and visualization of the data stream. Based on the past research papers published from 2002 to 2014, we gathered the general information, main techniques, challenges and open issues. The techniques for streaming text visualization are identified based on Text Visualization Browser in chronological order. This paper aims to review the evolution of streaming text visualization techniques and tools, as well as to discuss the problems and challenges for each of identified tools.

Keywords: Information visualization, visual analytics, text mining, visual text analytics tools, big data visualization.

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Authors: Imelda Smit

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Systems Analysis and Design is a key subject in Information Technology courses, but students do not find it easy to cope with, since it is not “precise" like programming and not exact like Mathematics. It is a subject working with many concepts, modeling ideas into visual representations and then translating the pictures into a real life system. To complicate matters users who are not necessarily familiar with computers need to give their inputs to ensure that they get the system the need. Systems Analysis and Design also covers two fields, namely Analysis, focusing on the analysis of the existing system and Design, focusing on the design of the new system. To be able to test the analysis and design of a system, it is necessary to develop a system or at least a prototype of the system to test the validity of the analysis and design. The skills necessary in each aspect differs vastly. Project Management Skills, Database Knowledge and Object Oriented Principles are all necessary. In the context of a developing country where students enter tertiary education underprepared and the digital divide is alive and well, students need to be motivated to learn the necessary skills, get an opportunity to test it in a “live" but protected environment – within the framework of a university. The purpose of this article is to improve the learning experience in Systems Analysis and Design through reviewing the underlying teaching principles used, the teaching tools implemented, the observations made and the reflections that will influence future developments in Systems Analysis and Design. Action research principles allows the focus to be on a few problematic aspects during a particular semester.

Keywords: Action Research, Project Development, Systems Analysis and Design, Technology in Teaching.

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Authors: Wimalin S. Laosiritaworn, Pongsak Holimchayachotikul

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this article proposed a methodology for computer numerical control (CNC) machine scoring. The case study company is a manufacturer of hard disk drive parts in Thailand. In this company, sample of parts manufactured from CNC machine are usually taken randomly for quality inspection. These inspection data were used to make a decision to shut down the machine if it has tendency to produce parts that are out of specification. Large amount of data are produced in this process and data mining could be very useful technique in analyzing them. In this research, data mining techniques were used to construct a machine scoring model called 'machine priority assessment model (MPAM)'. This model helps to ensure that the machine with higher risk of producing defective parts be inspected before those with lower risk. If the defective prone machine is identified sooner, defective part and rework could be reduced hence improving the overall productivity. The results showed that the proposed method can be successfully implemented and approximately 351,000 baht of opportunity cost could have saved in the case study company.

Keywords: Computer Numerical Control, Data Mining, HardDisk Drive.

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Authors: Ehsan Ghanaei, Feridun Esmaeilzadeh, Jamshid Fathi Kaljahi

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In the previous multi-solid models,¤ò approach is used for the calculation of fugacity in the liquid phase. For the first time, in the proposed multi-solid thermodynamic model,γ approach has been used for calculation of fugacity in the liquid mixture. Therefore, some activity coefficient models have been studied that the results show that the predictive Wilson model is more appropriate than others. The results demonstrate γ approach using the predictive Wilson model is in more agreement with experimental data than the previous multi-solid models. Also, by this method, generates a new approach for presenting stability analysis in phase equilibrium calculations. Meanwhile, the run time in γ approach is less than the previous methods used ¤ò approach. The results of the new model present 0.75 AAD % (Average Absolute Deviation) from the experimental data which is less than the results error of the previous multi-solid models obviously.

Keywords: Multi-solid thermodynamic model, PredictiveWilson model, Wax formation.

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Authors: Hung-Ming Lai, Andreas Albrecht, Kathleen Steinhöfel

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Cancers could normally be marked by a number of differentially expressed genes which show enormous potential as biomarkers for a certain disease. Recent years, cancer classification based on the investigation of gene expression profiles derived by high-throughput microarrays has widely been used. The selection of discriminative genes is, therefore, an essential preprocess step in carcinogenesis studies. In this paper, we have proposed a novel gene selector using information-theoretic measures for biological discovery. This multivariate filter is a four-stage framework through the analyses of feature relevance, feature interdependence, feature redundancy-dependence and subset rankings, and having been examined on the colon cancer data set. Our experimental result show that the proposed method outperformed other information theorem based filters in all aspect of classification errors and classification performance.

Keywords: Colon cancer, feature interdependence, feature subset selection, gene selection, microarray data analysis.

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Authors: Anwaar Ahmed, Muhammad Bilal Khurshid, Samuel Labi

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The effect of trucks on the level of service is determined by considering passenger car equivalents (PCE) of trucks. The current version of Highway Capacity Manual (HCM) uses a single PCE value for all tucks combined. However, the composition of truck traffic varies from location to location; therefore, a single PCE value for all trucks may not correctly represent the impact of truck traffic at specific locations. Consequently, present study developed separate PCE values for single-unit and combination trucks to replace the single value provided in the HCM on different freeways. Site specific PCE values, were developed using concept of spatial lagging headways (that is the distance between rear bumpers of two vehicles in a traffic stream) measured from field traffic data. The study used data from four locations on a single urban freeway and three different rural freeways in Indiana. Three-stage-leastsquares (3SLS) regression techniques were used to generate models that predicted lagging headways for passenger cars, single unit trucks (SUT), and combination trucks (CT). The estimated PCE values for single-unit and combination truck for basic urban freeways (level terrain) were: 1.35 and 1.60, respectively. For rural freeways the estimated PCE values for single-unit and combination truck were: 1.30 and 1.45, respectively. As expected, traffic variables such as vehicle flow rates and speed have significant impacts on vehicle headways. Study results revealed that the use of separate PCE values for different truck classes can have significant influence on the LOS estimation.

Keywords: Level of Service, Capacity Analysis, Lagging Headway.

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Authors: Md Tasbirul Islam, Pablo Dias, Nazmul Huda

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E-waste/Waste electrical and electronic equipment (WEEE) is one of the fastest growing waste streams across the globe. This paper aims to compare the e-waste management system in Switzerland and Australia in terms of four features - legislative initiatives, disposal practice, collection and financial mechanisms. The qualitative content analysis is employed as a research method in the study. Data were collected from various published academic research papers, industry reports, and web sources. In addition, a questionnaire survey is conducted in Australia to understand the public awareness and opinions on the features. The results of the study provide valuable insights to policymakers in Australia developing better e-waste management system in conjunction with the public consensus, and the state-of-the-art operational strategies currently being practiced in Switzerland.

Keywords: E-waste management, WEEE, awareness, pro-environmental behavior, Australia, Switzerland.

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Authors: Pasayev, A., C. Askerov, R. Sadiqov, C. Ardil

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In contrast to existing of calculation of temperature field of a profile part a blade with convective cooling which are not taking into account multi connective in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM AND FDM) numerical methods from the point of view of a realization on the PC. The theoretical substantiation of these methods is proved by the appropriate theorems.

Keywords: multi coherent systems, method of the boundary integrated equations, singular operators, gas turbines

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Authors: Tang Hong, Zhang Lufeng, Chen Hua, Zhang Jianbo

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Today many developers use the Java components collected from the Internet as external LIBs to design and develop their own software. However, some unknown security bugs may exist in these components, such as SQL injection bug may comes from the components which have no specific check for the input string by users. To check these bugs out is very difficult without source code. So a novel method to check the bugs in Java bytecode based on points-to dataflow analysis is in need, which is different to the common analysis techniques base on the vulnerability pattern check. It can be used as an assistant tool for security analysis of Java bytecode from unknown softwares which will be used as extern LIBs.

Keywords: Java bytecode, points-to dataflow, vulnerability analysis

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Authors: Mehrdad Hashemi, Mitra Behrooz Aghdam, Reza Mahdian, Ahmad Reza Kamyab

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Cytogenetic analysis still remains the gold standard method for prenatal diagnosis of trisomy 21 (Down syndrome, DS). Nevertheless, the conventional cytogenetic analysis needs live cultured cells and is too time-consuming for clinical application. In contrast, molecular methods such as FISH, QF-PCR, MLPA and quantitative Real-time PCR are rapid assays with results available in 24h. In the present study, we have successfully used a novel MGB TaqMan probe-based real time PCR assay for rapid diagnosis of trisomy 21 status in Down syndrome samples. We have also compared the results of this molecular method with corresponding results obtained by the cytogenetic analysis. Blood samples obtained from DS patients (n=25) and normal controls (n=20) were tested by quantitative Real-time PCR in parallel to standard G-banding analysis. Genomic DNA was extracted from peripheral blood lymphocytes. A high precision TaqMan probe quantitative Real-time PCR assay was developed to determine the gene dosage of DSCAM (target gene on 21q22.2) relative to PMP22 (reference gene on 17p11.2). The DSCAM/PMP22 ratio was calculated according to the formula; ratio=2 -ΔΔCT. The quantitative Real-time PCR was able to distinguish between trisomy 21 samples and normal controls with the gene ratios of 1.49±0.13 and 1.03±0.04 respectively (p value <0.001). These results represent the presence of 3 copies of target gene in DS samples Vs 2 copies in normal controls. The results of quantitative Real-time PCR were in complete agreement with results of cytogenetic analysis. This study confirms previous reports regarding successful implementation of quantitative Real-time PCR for detection of trisomy 21. However, the assay has been improved by using MGB probes and more accurate data analysis. This assay, in particular, when performed in combination with another molecular assay such as QF-PCR or MLPA, can be used as a reliable technique for rapid prenatal diagnosis of trisomy 21.

Keywords: Trisomy 21, Real-time PCR, MGB-TaqMan Probes, Gene Dosage.

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Authors: Zhichao Zhao, Yi Liu, Shunping Xiao

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A new data fusion method called joint probability density matrix (JPDM) is proposed, which can associate and fuse measurements from spatially distributed heterogeneous sensors to identify the real target in a surveillance region. Using the probabilistic grids representation, we numerically combine the uncertainty regions of all the measurements in a general framework. The NP-hard multisensor data fusion problem has been converted to a peak picking problem in the grids map. Unlike most of the existing data fusion method, the JPDM method dose not need association processing, and will not lead to combinatorial explosion. Its convergence to the CRLB with a diminishing grid size has been proved. Simulation results are presented to illustrate the effectiveness of the proposed technique.

Keywords: Cramer-Rao lower bound (CRLB), data fusion, probabilistic grids, joint probability density matrix, localization, sensor network.

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Authors: Fetah Eren, Ismail Sahin, Ismail Celik, Ahmet Oguz Akturk

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The aim of this study is to discover secondary school students’ perceptions related to information technologies and the connections between concepts in their cognitive structures. A word association test consisting of six concepts related to information technologies is used to collect data from 244 secondary school students. Concept maps that present students’ cognitive structures are drawn with the help of frequency data. Data are analyzed and interpreted according to the connections obtained as a result of the concept maps. It is determined students associate most with these concepts—computer, Internet, and communication of the given concepts, and associate least with these concepts—computer-assisted education and information technologies. These results show the concepts, Internet, communication, and computer, are an important part of students’ cognitive structures. In addition, students mostly answer computer, phone, game, Internet and Facebook as the key concepts. These answers show students regard information technologies as a means for entertainment and free time activity, not as a means for education.

Keywords: Word association test, cognitive structure, information technology, secondary school.

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents comparative analysis of photovoltaic systems (PVS) and propose practical techniques to improve operational efficiency of the PVS. The best engineering and construction practices for PVS are identified and field oriented recommendation are made. Comparative analysis of central and string inverter based, as well as 600 and 1000VDC PVS are performed. In addition, direct current (DC) and alternating current (AC) photovoltaic (PV) module based systems are compared. Comparison shows that 1000V DC String Inverters based PVS is the best choice.

Keywords: Photovoltaic module, photovoltaic systems, operational efficiency improvement, comparative analysis.

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Authors: Messaouda Annab

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The rapid development of technology has led to an important context in which different languages and structures are used in the same conversations. This paper investigates the practice of language borrowing within social media platform, namely, Facebook among Algerian Vernacular Arabic (AVA) students. In other words, this study will explore how Algerian students have incorporated lexical English borrowing in their online conversations. This paper will examine the relationships between language, culture and identity among a multilingual group. The main objective is to determine the cultural and linguistic functions that borrowing fulfills in social media and to explain the possible factors underlying English borrowing. The nature of the study entails the use of an online research method that includes ten online Facebook conversations in the form of private messages collected from Bachelor and Masters Algerian students recruited from the English department at the University of Oum El-Bouaghi. The analysis of data revealed that social media platform provided the users with opportunities to shift from one language to another. This practice was noticed in students’ online conversations. English borrowing was the most relevant language performance in accordance with Arabic which is the mother tongue of the chosen sample. The analysis has assumed that participants are skilled in more than one language.

Keywords: Borrowing, language performance, linguistic background, social media.

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Authors: Wookyong Kwon, Sangmoon Lee

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In this paper, a sampled-data model predictive tracking control method is presented for mobile robots which is modeled as constrained continuous-time linear parameter varying (LPV) systems. The presented sampled-data predictive controller is designed by linear matrix inequality approach. Based on the input delay approach, a controller design condition is derived by constructing a new Lyapunov function. Finally, a numerical example is given to demonstrate the effectiveness of the presented method.

Keywords: Model predictive control, sampled-data control, linear parameter varying systems, LPV.

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Authors: Wuttigrai Ngamsirijit

Abstract:

Talent management in today’s modern organizations has become data-driven due to a demand for objective human resource decision making and development of analytics technologies. HR managers have been faced with some obstacles in exploiting data and information to obtain their effective talent management decisions. These include process-based data and records; insufficient human capital-related measures and metrics; lack of capabilities in data modeling in strategic manners; and, time consuming to add up numbers and make decisions. This paper proposes a framework of talent management through integration of talent value chain and human capital analytics approaches. It encompasses key data, measures, and metrics regarding strategic talent management decisions along the organizational and talent value chain. Moreover, specific predictive and prescriptive models incorporating these data and information are recommended to help managers in understanding the state of talent, gaps in managing talent and the organization, and the ways to develop optimized talent strategies.    

Keywords: Decision making, human capital analytics, talent management, talent value chain.

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Authors: Mina Alibeigi, Sattar Hashemi, Ali Hamzeh

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Since dealing with high dimensional data is computationally complex and sometimes even intractable, recently several feature reductions methods have been developed to reduce the dimensionality of the data in order to simplify the calculation analysis in various applications such as text categorization, signal processing, image retrieval, gene expressions and etc. Among feature reduction techniques, feature selection is one the most popular methods due to the preservation of the original features. In this paper, we propose a new unsupervised feature selection method which will remove redundant features from the original feature space by the use of probability density functions of various features. To show the effectiveness of the proposed method, popular feature selection methods have been implemented and compared. Experimental results on the several datasets derived from UCI repository database, illustrate the effectiveness of our proposed methods in comparison with the other compared methods in terms of both classification accuracy and the number of selected features.

Keywords: Feature, Feature Selection, Filter, Probability Density Function

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Authors: Fabrice Poirion, Benedicte Puig

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Mathematical justifications are given for a simulation technique of multivariate nonGaussian random processes and fields based on Rosenblatt-s transformation of Gaussian processes. Different types of convergences are given for the approaching sequence. Moreover an original numerical method is proposed in order to solve the functional equation yielding the underlying Gaussian process autocorrelation function.

Keywords: Simulation, nonGaussian, random field, multivariate, stochastic process.

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Authors: Ghassan A. Abed, Bayan M. Sabbar

Abstract:

The society of 3^rd Generation Partnership Project (3GPP) is completed developing Long Term Evolution Advanced (LTE-Advanced) systems as a standard 4G cellular system. This generation goals to produce conditions for a new radio-access technology geared to higher data rates, low latency, and better spectral efficiency. LTE-Advanced is an evolutionary step in the continuing development of LTE where the description in this article is based on LTE release 10. This paper provides a model of the traffic links of 4G system represented by LTE-Advanced system with the effect of the Transmission Control Protocols (TCP) and Stream Control Transmission Protocol (SCTP) in term of throughput and packet loss. Furthermore, the article presents the investigation and the analysis the behavior of SCTP and TCP variants over the 4G cellular systems. The traffic model and the scenario of the simulation developed using the network simulator NS-2 using different TCP source variants.

Keywords: LTE-Advanced, LTE, SCTP, TCP, 4G, NS-2.

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Authors: Paramet Nualmuenwai, Chutima Prommak

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This paper presents the IP traffic analysis. The traffic was collected from the network of Suranaree University of Technology using the software based on the Simple Network Management Protocol (SNMP). In particular, we analyze the distribution of the aggregated traffic during the hours of peak load and light load. The traffic profiles including the parameters described the traffic distributions were derived. From the statistical analysis applying three different methods, including the Kolmogorov Smirnov test, Anderson Darling test, and Chi-Squared test, we found that the IP traffic distribution is a non-normal distribution and the distributions during the peak load and the light load are different. The experimental study and analysis show high uncertainty of the IP traffic.

Keywords: IP traffic analysis, IP traffic distribution, Traffic uncertainty

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Authors: Nasehi, B., Mortazavi, S. A., Razavi, S.

Abstract:

The influence of full-fat soy flour (FFSF) and extrusion conditions on the mechanical characteristics of dry spaghetti were evaluated. Process was performed with screw speed of 10-40rpm and water circulating temperature of 35-70°C. Data analysis using mixture design showed that this enrichment resulted in significant differences in mechanical strength.

Keywords: Pasta, Mixture design, Enrichment, Texture.

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Authors: S. Deelers, S. Auwatanamongkol

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In this paper, we propose an algorithm to compute initial cluster centers for K-means clustering. Data in a cell is partitioned using a cutting plane that divides cell in two smaller cells. The plane is perpendicular to the data axis with the highest variance and is designed to reduce the sum squared errors of the two cells as much as possible, while at the same time keep the two cells far apart as possible. Cells are partitioned one at a time until the number of cells equals to the predefined number of clusters, K. The centers of the K cells become the initial cluster centers for K-means. The experimental results suggest that the proposed algorithm is effective, converge to better clustering results than those of the random initialization method. The research also indicated the proposed algorithm would greatly improve the likelihood of every cluster containing some data in it.

Keywords: Clustering algorithm, K-means algorithm, Datapartitioning, Initial cluster centers.

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Authors: M. Hassan, I. Osman, M. Yahia

Abstract:

This Paper proposes a new facial feature extraction approach, Wash-Hadamard Transform (WHT). This approach is based on correlation between local pixels of the face image. Its primary advantage is the simplicity of its computation. The paper compares the proposed approach, WHT, which was traditionally used in data compression with two other known approaches: the Principal Component Analysis (PCA) and the Discrete Cosine Transform (DCT) using the face database of Olivetti Research Laboratory (ORL). In spite of its simple computation, the proposed algorithm (WHT) gave very close results to those obtained by the PCA and DCT. This paper initiates the research into WHT and the family of frequency transforms and examines their suitability for feature extraction in face recognition applications.

Keywords: Face Recognition, Facial Feature Extraction, Principal Component Analysis, and Discrete Cosine Transform, Wash-Hadamard Transform.

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

Abstract:

In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: Outlier detection, generative adversary networks, semi-supervised learning.

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