Search results for: adaptive cluster sampling

Authors: Golnaz Salehi Mourkani

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Two conception of Integrity and authenticity, in texts have just applied respectively for adaptive reuse and conservation, which in comparison with word “Integrity” in texts related to adaptive reuse is much more seen than Authenticity, which is often applied with conservation. According to Stove, H., (2007) in some cases, this conception have used with this form “integrity/authenticity” in texts, that cause to infer one conception of both. In this article, with referring to definitions and comparison of aspects specialized to both concept of “Authenticity and Integrity” through literature review, it was attempted to examine common and distinctive aspects of each one, then with this method we can reach their differences in adaptive reuse.

Keywords: adaptive reuse, integrity, authenticity, conservation

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Authors: Bruna Luisa Ramos Prado Vasques, Mariane Rembold Petraglia, Antonio Petraglia

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This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence.

Keywords: adaptive filtering, multi-rate processing, normalized subband adaptive filter, source separation

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Authors: Alexander Sharashenidze

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This article discusses the role of tourism in the economics of Georgia, justifies the necessity of several governmental supporting tools for diversification of tourism product and increasing competitiveness. Tourism directions are characterized through discovering Georgian tourism potential, considering cultural and geographical features; tools of formating supplemental products and development opportunities of Tbilisi and, also regions are asserted in the case of conducting appropriate government policy. There are presented tools of suggesting innovative tourism products, improvement of service, decreasing taxes, also providing availability to them. The role of tourism cluster in improvement of national competitiveness is substantiated. Based on the analysis of competitive factors influencing the development of tourism cluster, conclusions are made, and recommendations are suggested.

Keywords: economic competitivness, enhancing competitiveness, Georgian economic, tourism cluster, tourism product

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Authors: Penchuk A. Vovkanych

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The adaptive changes in the respiratory system provide the background for the increase of aerobic capacity and sport results on the middle and long distances runners. Effect of such adaptive changes in the sport orienteering remains poorly investigated. Therefore our study was undertaken to reveal the adaptive changes in the respiration indices of high skilled orienteer athletes.

Keywords: adaptation, external, functional state, respiration, running, sport orienteering

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Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi

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In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.

Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index (PCI), average sample number (ASN), Bayesian approach

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Authors: Kanogkan Leerojanaprapa

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Textile and garment industry is used to a major exporting industry of Thailand. According to lacking of the nation's price-competitiveness by stopping the EU's GSP (Generalised Scheme of Preferences) and ‘Nationwide Minimum Wage Policy’ that Thailand’s employers must pay all employees at least 300 baht (about $10) a day, the supply chains of the Thai textile and garment industry is affected and need to be reformed. Therefore, either Thai textile or garment industry will be existed or not would be concerned. This is also challenged for the government to decide which industries should be promoted the future industries of Thailand. Recently Thai government launch The Cluster-based Special Economic Development Zones Policy for promoting business cluster (effect on September 16, 2015). They define a cluster as the concentration of interconnected businesses and related institutions that operate within the same geographic areas and textiles and garment is one of target industrial clusters and 9 provinces are targeted (Bangkok, Kanchanaburi, Nakhon Pathom, Ratchaburi, Samut Sakhon, Chonburi, Chachoengsao, Prachinburi, and Sa Kaeo). The cluster zone are defined to link west-east corridor connected to manufacturing source in Cambodia and Mynmar to Bangkok where are promoted to be design, sourcing, and trading hub. The Thai government will provide tax and non-tax incentives for targeted industries within the clusters and expects these businesses are scattered to where they can get the most benefit which will identify future industrial cluster. This research will show the difference between the current cluster and future cluster following the target provinces of the textile and garment. The current cluster is analysed from secondary data. The four characteristics of the numbers of plants in Spinning, weaving and finishing of textiles, Manufacture of made-up textile articles, except apparel, Manufacture of knitted and crocheted fabrics, and Manufacture of other textiles, not elsewhere classified in particular 77 provinces (in total) are clustered by K-means cluster analysis and Hierarchical Cluster Analysis. In addition, the cluster can be confirmed and showed which variables contribute the most to defined cluster solution with ANOVA test. The results of analysis can identify 22 provinces (which the textile or garment plants are located) into 3 clusters. Plants in cluster 1 tend to be large numbers of plants which is only Bangkok, Next plants in cluster 2 tend to be moderate numbers of plants which are Samut Prakan, Samut Sakhon and Nakhon Pathom. Finally plants in cluster 3 tend to be little numbers of plants which are other 18 provinces. The same methodology can be implemented in other industries for future study.

Keywords: ANOVA, hierarchical cluster analysis, industrial clusters, K -means cluster analysis, textile and garment industry

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Authors: Mert Turanli, Hakan Temeltas

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In this paper, we present an adaptive controller for decentralized coordination problem of multiple non-holonomic agents. The performance of the presented Multi-Agent Bounded Gain Forgetting (BGF) Composite Adaptive controller is compared against the tracking error criterion with a Feedback Linearization controller. By using the method, the sensor nodes move and reconfigure themselves in a coordinated way in response to a sensed environment. The multi-agent coordination is achieved through Centroidal Voronoi Tessellations and Coverage Control. Also, a consensus protocol is used for synchronization of the parameter vectors. The two controllers are given with their Lyapunov stability analysis and their stability is verified with simulation results. The simulations are carried out in MATLAB and ROS environments. Better performance is obtained with BGF Adaptive Controller.

Keywords: adaptive control, centroidal voronoi tessellations, composite adaptation, coordination, multi robots

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Authors: Navdeep Singh Randhawa

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Wireless communication system has been proved as the best for any communication. However, there are some undesirable threats of a wireless communication channel on the information transmitted through it, such as attenuation, distortions, delays and phase shifts of the signals arriving at the receiver end which are caused by its band limited and dispersive nature. One of the threat is ISI (Inter Symbol Interference), which has been found as a great obstacle in high speed communication. Thus, there is a need to provide perfect and accurate technique to remove this effect to have an error free communication. Thus, different equalization techniques have been proposed in literature. This paper presents the equalization techniques followed by the concept of adaptive filter equalizer, its algorithms (LMS and RLS) and applications of adaptive equalization technique.

Keywords: channel equalization, adaptive equalizer, least mean square, recursive least square

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Authors: Raghunath Arnab

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The two-phase sampling which is also known as double sampling was introduced in 1938. In two-phase sampling, samples are selected in phases. In the first phase, a relatively large sample of size is selected by some suitable sampling design and only information on the auxiliary variable is collected. During the second phase, a sample of size is selected either from, the sample selected in the first phase or from the entire population by using a suitable sampling design and information regarding the study and auxiliary variable is collected. Evidently, two phase sampling is useful if the auxiliary information is relatively easy and cheaper to collect than the study variable as well as if the strength of the relationship between the variables and is high. If the sample is selected in more than two phases, the resulting sampling design is called a multi-phase sampling. In this article we will consider how one can use data collected at the first phase sampling at the stages of estimation of the parameter, stratification, selection of sample and their combinations in the second phase in a unified setup applicable to any sampling design and wider classes of estimators. The problem of the estimation of variance will also be considered. The variance of estimator is essential for estimating precision of the survey estimates, calculation of confidence intervals, determination of the optimal sample sizes and for testing of hypotheses amongst others. Although, the variance is a non-negative quantity but its estimators may not be non-negative. If the estimator of variance is negative, then it cannot be used for estimation of confidence intervals, testing of hypothesis or measure of sampling error. The non-negativity properties of the variance estimators will also be studied in details.

Keywords: auxiliary information, two-phase sampling, varying probability sampling, unbiased estimators

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Authors: Abderrahmen Bouguerra, Kamel Kara, Djamel Saigaa, Samir Zeghlache, Keltoum Loukal

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In this paper, a Fault-Tolerant control of 2 DOF Helicopter (TRMS System) Based on Fuzzy Gain-Adaptive PID is presented. In particular, the introduction part of the paper presents a Fault-Tolerant Control (FTC), the first part of this paper presents a description of the mathematical model of TRMS, an adaptive PID controller is proposed for fault-tolerant control of a TRMS helicopter system in the presence of actuator faults, A fuzzy inference scheme is used to tune in real-time the controller gains, The proposed adaptive PID controller is compared with the conventional PID. The obtained results show the effectiveness of the proposed method.

Keywords: fuzzy control, gain-adaptive PID, helicopter model, PID control, TRMS system

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Authors: Lee Myung-Won, Kwak Keun-Chang

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

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Authors: Sushma Ghildyal, Sanjay Kumar Singh

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The present study was undertaken with the purpose to understand the relationship of lifestyle and Socio-Economic status with child obesity among 1000 boys aged from 16 to 18 years of Varanasi District of Uttar Pradesh State in India. The study was conducted in both urban and rural area of the District. Ten schools i.e. five from urban area and five from rural area were selected by using purposive sampling. Healthy boys of class 10th, 11th and 12th were taken as subjects for the study. Prior consent was obtained from school authority. Anthropometric measurements were taken from each subject. Anthropometric measurements were Standing Height, Weight, Biceps skin folds, Triceps skin folds, Sub-scapular skin folds and Supra-iliac skin folds taken by Lange’s skin fold caliper. Lifestyle and Socio-Economic Status were obtained by questionnaires. In order to assess the BMI, Body fat %, Lifestyle and Socio-Economic Status; descriptive analyses were done. To find out the significant association of obesity with lifestyle and Socio-Economic Status Chi-square test was used. To find out significant difference between obesity of Urban and Rural children t-test was applied. Level of significance was set at 0.05 level. The conclusions drawn were: (1) The result showed that in urban area Varanasi District of Uttar Pradesh 0.6% children were in very high level adaptive lifestyle, 6.2% were in high level adaptive lifestyle, 25.4% above average level adaptive lifestyle, 47.8% moderately adaptive lifestyle, 3.6% and 0.4% low and very low level adaptive lifestyle. (2) In rural area Varanasi District of Uttar Pradesh 0.00% children were in very high level adaptive lifestyle, 9.4% were in high level adaptive lifestyle, 24.8% average level adaptive lifestyle, 47.0% moderately adaptive lifestyle, 15.2% below average and 3.0% very low level adaptive lifestyle.(3) In urban area 12.8% were in upper class Socio-Economic Status, 56.6% in upper middle class Socio-Economic Status, 30.2% in middle class Socio-Economic Status and 0.2% in lower middle class Socio-Economic Status. (4) In rural area 1.4% were in upper class Socio-Economic Status, 15.2% in upper middle class Socio-Economic Status, 51.6% in middle class Socio-Economic Status and 0.8% in lower middle class Socio-Economic Status. (5) In urban area 21.2% children of 16-18 years were obese. (6) In rural area 0.2% children of 16-18 years were obese. (7) In overall Varanasi District of Uttar Pradesh 10.7% children of 16-18 years were obese. (8) There was no significant relationship of obesity with Lifestyle of urban area children of 16-18 years. (9) There was significant relationship of obesity with Socio-Economic Status of urban area children of 16-18 years (10) There was no significant relationship of obesity with Lifestyle of rural area children of 16-18 years of Varanasi District Uttar Pradesh. (11) There was significant relationship of obesity with Socio-Economic Status of rural area children of 16-18 years. (12) Results showed significant difference between urban and rural area children of 16-18 years in respect to obesity of Varanasi District of Uttar Pradesh.

Keywords: lifestyle, obesity, rural area, socio-economic status, urban area

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Authors: Mert Turanli, Hakan Temeltas

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In this paper, we propose a new approach to coverage control problem by using adaptive coordination and power aware control laws. Nonholonomic mobile nodes position themselves suboptimally according to a time-varying density function using Centroidal Voronoi Tesellations. The Lyapunov stability analysis of the adaptive and decentralized approach is given. A linear consensus protocol is used to establish synchronization among the mobile nodes. Also, repulsive forces prevent nodes from collision. Simulation results show that by using power aware control laws, energy consumption of the nodes can be reduced.

Keywords: power aware, coverage control, adaptive, consensus, nonholonomic, coordination

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Authors: Byoung-Hee Lee

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Wireless battery charger with adaptive rapid charging algorithm is proposed. The proposed wireless charger adopts voltage regulation technique to reduce the number of power conversion steps. Moreover, based on battery models, an adaptive rapid charging algorithm for Li-ion batteries is obtained. Rapid-charging performance with the proposed wireless battery charger and the proposed rapid charging algorithm has been experimentally verified to show more than 70% charging time reduction compared to conventional constant-current constant-voltage (CC-CV) charging without the degradation of battery lifetime.

Keywords: wireless, battery charger, adaptive, rapid-charging

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Authors: Ameen Jameel Alawneh

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A Mobile ad-hoc network (MANET) is a collection of wireless mobile hosts that dynamically form a temporary network without the aid of a system administrator. It has neither fixed infrastructure nor wireless ad hoc sessions. It inherently reaches several nodes with a single transmission, and each node functions as both a host and a router. The network maybe represented as a set of clusters each managed by clusterhead. The cluster size is not fixed and it depends on the movement of nodes. We proposed a clusterhead size algorithm (CHSize). This clustering algorithm can be used by several routing algorithms for ad hoc networks. An elected clusterhead is assigned for communication with all other clusters. Analysis and simulation of the algorithm has been implemented using GloMoSim networks simulator, MATLAB and MAPL11 proved that the proposed algorithm achieves the goals.

Keywords: simulation, MANET, Ad-hoc, cluster head size, linked cluster algorithm, loss and dropped packets

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Authors: Mamoun S. Ideis, Zein Salah

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Virtual Rehabilitation (VR) refers to using Virtual Reality’s hardware and simulations as means of exercising tools to rehabilitate patients in need. These patients will undergo their treatment exercises while playing different computer games, which helps achieve greater motivation for patients undergoing their therapeutic exercises. Virtual Rehabilitation systems adopt computer games as part of the treatment therapy. In this paper, we present a preliminary proposal to using adaptive computer games in Virtual Rehabilitation therapy. We also present some tips in designing those adaptive computer games by using different machine learning algorithms in order to create a personalized experience for each patient, which in turn, increases the potential benefits of the treatment that each patient receives. Furthermore, we propose a method of comparing the results of treatment using the adaptive computer games with the results of using static and classical computer games.

Keywords: virtual rehabilitation, physiotherapy, adaptive computer games, post-stroke, game design

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Authors: Mahmoud I. Syam

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Stratified double median ranked set sampling (SDMRSS) method is suggested for estimating the population mean. The SDMRSS is compared with the simple random sampling (SRS), stratified simple random sampling (SSRS), and stratified ranked set sampling (SRSS). It is shown that SDMRSS estimator is an unbiased of the population mean and more efficient than SRS, SSRS, and SRSS. Also, by SDMRSS, we can increase the efficiency of mean estimator for specific value of the sample size. SDMRSS is applied on real life examples, and the results of the example agreed the theoretical results.

Keywords: efficiency, double ranked set sampling, median ranked set sampling, ranked set sampling, stratified

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Authors: E. Izsó, M. Bartalné-Berceli, Sz. Gergely, A. Salgó

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The aims of this investigation is to elaborate near-infrared methods for testing and recognition of chemical components and quality in “Pannon wheat” allied (i.e. true to variety or variety identified) milling fractions as well as to develop spectroscopic methods following the milling processes and evaluate the stability of the milling technology by different types of milling products and according to sampling times, respectively. This wheat categories produced under industrial conditions where samples were collected versus sampling time and maximum or minimum yields. The changes of the main chemical components (such as starch, protein, lipid) and physical properties of fractions (particle size) were analysed by dispersive spectrophotometers using visible (VIS) and near-infrared (NIR) regions of the electromagnetic radiation. Close correlation were obtained between the data of spectroscopic measurement techniques processed by various chemometric methods (e.g. principal component analysis (PCA), cluster analysis (CA) and operation condition of milling technology. Its obvious that NIR methods are able to detect the deviation of the yield parameters and differences of the sampling times by a wide variety of fractions, respectively. NIR technology can be used in the sensitive monitoring of milling technology.

Keywords: near infrared spectroscopy, wheat categories, milling process, monitoring

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Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

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River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: cluster analysis, multivariate statistical techniques, river Hindon, water quality

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Authors: Sahar Mobeen, Anam Rafique, Irum Baig

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Acoustic echo cancellation in multichannel is a system identification application. In real time environment, signal changes very rapidly which required adaptive algorithms such as Least Mean Square (LMS), Leaky Least Mean Square (LLMS), Normalized Least Mean square (NLMS) and average (AFA) having high convergence rate and stable. LMS and NLMS are widely used adaptive algorithm due to less computational complexity and AFA used of its high convergence rate. This research is based on comparison of acoustic echo (generated in a room) cancellation thorough LMS, LLMS, NLMS, AFA and newly proposed average normalized leaky least mean square (ANLLMS) adaptive filters.

Keywords: LMS, LLMS, NLMS, AFA, ANLLMS

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Authors: Fariba Dortaj, Reza Asadinejad, Akram Dortaj, Atena Baziyar

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The aim of this study was to determine the effect of distance education (based on MOOC) on the components of academic engagement of Kerman PNU. The research was quasi-experimental method that cluster sampling with an appropriate volume was used in this study (one class in experimental group and one class in controlling group). Sampling method is single-stage cluster sampling. The statistical society is students of Kerman Payam Noor University, which) were selected 40 of them as sample (20 students in the control group and 20 students in experimental group). To test the hypothesis, it was used the analysis of univariate and Co-covariance to offset the initial difference (difference of control) in the experimental group and the control group. The instrument used in this study is academic engagement questionnaire of Zerang (2012) that contains component of cognitive, behavioral and motivational engagement. The results showed that there is no significant difference between mean scores of academic components of academic engagement in experimental group and the control group on the post-test, after elimination of the pre-test. The adjusted mean scores of components of academic engagement in the experimental group were higher than the adjusted average of scores after the test in the control group. The use of technology-based education in distance education has been effective in increasing cognitive engagement, motivational engagement and behavioral engagement among students. Experimental variable with the effect size 0.26, predicted 26% of cognitive engagement component variance. Experimental variable with the effect size 0.47, predicted 47% of the motivational engagement component variance. Experimental variable with the effect size 0.40, predicted 40% of behavioral engagement component variance. So teaching with technology (MOOC) has a positive impact on increasing academic engagement and academic performance of students in educational technology. The results suggest that technology (MOOC) is used to enrich the teaching of other lessons of PNU.

Keywords: educational technology, distance education, components of academic engagement, mooc technology

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Authors: Khattab Al Qaisi, Nicholas Bowring

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This paper presents the simulation results of the effects of sampling frequency on the total harmonic distortion (THD) of three-phase inverters using the space vector pulse width modulation (SVPWM) and space vector control (SVC) algorithms. The relationship between the variables was studied using curve fitting techniques, and it has been shown that, for 50 Hz inverters, there is an exponential relation between the sampling frequency and THD up to around 8500 Hz, beyond which the performance of the model becomes irregular, and there is an negative exponential relation between the sampling frequency and the marginal improvement to the THD. It has also been found that the performance of SVPWM is better than that of SVC with the same sampling frequency in most frequency range, including the range where the performance of the former is irregular.

Keywords: DSI, SVPWM, THD, DC-AC converter, sampling frequency, performance

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Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

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Authors: Te-Jen Chang, Ping-Sheng Huang, Shan-Ten Cheng, Chih-Lin Lin, I-Hui Pan, Tsung- Hsien Lin

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RSA system is a great contribution for the encryption and the decryption. It is based on the modular exponentiation. We call this system as “a large of numbers for calculation”. The operation of a large of numbers is a very heavy burden for CPU. For increasing the computational speed, in addition to improve these algorithms, such as the binary method, the sliding window method, the addition chain method, and so on, the cluster computer can be used to advance computational speed. The cluster system is composed of the computers which are installed the MPICH2 in laboratory. The parallel procedures of the modular exponentiation can be processed by combining the sliding window method with the addition chain method. It will significantly reduce the computational time of the modular exponentiation whose digits are more than 512 bits and even more than 1024 bits.

Keywords: cluster system, modular exponentiation, sliding window, addition chain

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Authors: Rosilah Hassan, Karam Dhafer Mayoof, Norngainy Mohd Tawil, Shamshubaridah Ramlee

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Application of adaptive online quiz system and a design are performed in this paper. The purpose of adaptive quiz system is to establish different questions automatically for each student and measure their competence on a definite area of discipline. This model determines students competencies in cases like distant-learning which experience challenges frequently. Questions are specialized to allow clear deductions about student gains; they are able to identify student competencies more effectively. Also, negative effects of questions requiring higher knowledge than competency over student’s morale and self-confidence are dismissed. The advantage of the system in the quiz management requires less total time for measuring and is more flexible. Self sufficiency of the system in terms of repeating, planning and assessment of the measurement process allows itself to be used in the individual education sets. Adaptive quiz technique prevents students from distraction and motivation loss, which is led by the questions with quite lower hardness level than student’s competency.

Keywords: e-learning, adaptive system, security, quiz database

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Authors: Yinjun Tu, Qiang Fang, Glenn I. Matthews, Shuenn-Yuh Lee

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This paper reports an efficient and rigorous self-adaptive stimulus artifacts removal approach for a mixed surface EMG (Electromyography) and stimulus signal during muscle stimulation. The recording of EMG and the stimulation of muscles were performing simultaneously. It is difficult to generate muscle fatigue feature from the mixed signal, which can be further used in closed loop system. A self-adaptive method is proposed in this paper, the stimulation frequency was calculated and verified firstly. Then, a mask was created based on this stimulation frequency to remove the undesired stimulus. 20 EMG signal recordings were analyzed, and the ANOVA (analysis of variance) approach illustrated that the decreasing trend of median power frequencies was successfully generated from the 'cleaned' EMG signal.

Keywords: EMG, FES, stimulus artefacts, self-adaptive

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Authors: Asma Afshari, Abdollah Jamshidi, Jamshid Razmyar, Mehrnaz Rad

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Clostridium perfringens is a serious pathogen which causes enteric diseases in domestic animals and food poisoning in humans. Spores can survive cooking processes and play an important role in the possible onset of disease. In this study RAPD-PCR and REP-PCR were used to examine the genetic diversity of 49isolates ofC. Perfringens type A from 3 different sources. The results of RAPD-PCR revealed the most genetic diversity among poultry isolates, while human isolates showed the least genetic diversity. Cluster analysis obtained from RAPD_PCR and based on the genetic distances split the 49 strains into five distinct major clusters (A, B, C, D, and E). Cluster A and C were composed of isolates from poultry meat, cluster B was composed of isolates from human feces, cluster D was composed of isolates from minced meat, poultry meat and human feces and cluster E was composed of isolates from minced meat. Further characterization of these strains by using (GTG) 5 fingerprint repetitive sequence-based PCR analysis did not show further differentiation between various types of strains. To our knowledge, this is the first study in which the genetic diversity of C. perfringens isolates from different types of meats and human feces has been investigated.

Keywords: C. perfringens, genetic diversity, RAPD-PCR, REP-PCR

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Authors: M. K. Benhaoua, A. E. H. Benyamina, T. Djeradi, P. Boulet

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In this paper, we propose adaptive routing that considers the routing of communications in order to optimize the overall performance. The routing technique uses a newly proposed Algorithm to route communications between the tasks. The routing we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed routing approach provides significant performance improvements when compared to those using static routing.

Keywords: multi-processor systems-on-chip (mpsocs), network-on-chip (noc), heterogeneous architectures, adaptive routin

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Authors: Dao Phuong Nam, Tran Van Tuyen, Do Trong Tan, Bui Minh Dinh, Nguyen Van Huong

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In this paper, we investigate the adaptive optimal control law for continuous-time systems with input disturbances and unknown parameters. This paper extends previous works to obtain the robust control law of uncertain systems. Through theoretical analysis, an adaptive dynamic programming (ADP) based optimal control is proposed to stabilize the closed-loop system and ensure the convergence properties of proposed iterative algorithm. Moreover, the global asymptotic stability (GAS) for closed system is also analyzed. The theoretical analysis for continuous-time systems and simulation results demonstrate the performance of the proposed algorithm for an inverted pendulum system.

Keywords: approximate/adaptive dynamic programming, ADP, adaptive optimal control law, input state stability, ISS, inverted pendulum

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Authors: Ashok V. Sutagundar, Sunilkumar S. Manvi

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Energy, delay and bandwidth are the prime issues of wireless sensor network (WSN). Energy usage optimization and efficient bandwidth utilization are important issues in WSN. Event triggered data aggregation facilitates such optimal tasks for event affected area in WSN. Reliable delivery of the critical information to sink node is also a major challenge of WSN. To tackle these issues, we propose an event driven dynamic clustering and data aggregation scheme for WSN that enhances the life time of the network by minimizing redundant data transmission. The proposed scheme operates as follows: (1) Whenever the event is triggered, event triggered node selects the cluster head. (2) Cluster head gathers data from sensor nodes within the cluster. (3) Cluster head node identifies and classifies the events out of the collected data using Bayesian classifier. (4) Aggregation of data is done using statistical method. (5) Cluster head discovers the paths to the sink node using residual energy, path distance and bandwidth. (6) If the aggregated data is critical, cluster head sends the aggregated data over the multipath for reliable data communication. (7) Otherwise aggregated data is transmitted towards sink node over the single path which is having the more bandwidth and residual energy. The performance of the scheme is validated for various WSN scenarios to evaluate the effectiveness of the proposed approach in terms of aggregation time, cluster formation time and energy consumed for aggregation.

Keywords: wireless sensor network, dynamic clustering, data aggregation, wireless communication

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