Search results for: General regression neural network

Authors: Mario Mastriani

Abstract:

We describe a novel method for removing noise (in wavelet domain) of unknown variance from microarrays. The method is based on the following procedure: We apply 1) Bidimentional Discrete Wavelet Transform (DWT-2D) to the Noisy Microarray, 2) scaling and rounding to the coefficients of the highest subbands (to obtain integer and positive coefficients), 3) bit-slicing to the new highest subbands (to obtain bit-planes), 4) then we apply the Systholic Boolean Orthonormalizer Network (SBON) to the input bit-plane set and we obtain two orthonormal otput bit-plane sets (in a Boolean sense), we project a set on the other one, by means of an AND operation, and then, 5) we apply re-assembling, and, 6) rescaling. Finally, 7) we apply Inverse DWT-2D and reconstruct a microarray from the modified wavelet coefficients. Denoising results compare favorably to the most of methods in use at the moment.

Keywords: Bit-Plane, Boolean Orthonormalization Process, Denoising, Microarrays, Wavelets

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Authors: Morteza Raei Dehaghi, Seyed Mohammad Mirhashemi

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The current study explored the effect of economic development, financial development and institutional quality on environmental destruction in upper-middle income countries during the time period of 1999-2011. The dependent variable is logarithm of carbon dioxide emissions that can be considered as an index for destruction or quality of the environment given to its effects on the environment. Financial development and institutional development variables as well as some control variables were considered. In order to study cross-sectional correlation among the countries under study, Pesaran and Friz test was used. Since the results of both tests show cross-sectional correlation in the countries under study, seemingly unrelated regression method was utilized for model estimation. The results disclosed that Kuznets’ environmental curve hypothesis is confirmed in upper-middle income countries and also, financial development and institutional quality have a significant effect on environmental quality. The results of this study can be considered by policy makers in countries with different income groups to have access to a growth accompanied by improved environmental quality.

Keywords: Economic Development, Environmental Destruction, Financial Development, Institutional Development, Seemingly Unrelated Regression.

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Authors: H. Aoudia, Y. Touati, E. H. Teguig, A. Ali Cherif

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Conceiving and developing routing protocols for wireless sensor networks requires considerations on constraints such as network lifetime and energy consumption. In this paper, we propose a hybrid hierarchical routing protocol named HHRP combining both clustering mechanism and multipath optimization taking into account residual energy and RSSI measures. HHRP consists of classifying dynamically nodes into clusters where coordinators nodes with extra privileges are able to manipulate messages, aggregate data and ensure transmission between nodes according to TDMA and CDMA schedules. The reconfiguration of the network is carried out dynamically based on a threshold value which is associated with the number of nodes belonging to the smallest cluster. To show the effectiveness of the proposed approach HHRP, a comparative study with LEACH protocol is illustrated in simulations.

Keywords: Routing protocols, energy optimization, clustering.

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

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Authors: T. Kerdchuen

Abstract:

This paper proposes the stochastic tabu search (STS) for improving the measurement scheme for power system state estimation. If the original measured scheme is not observable, the additional measurements with minimum number of measurements are added into the system by STS so that there is no critical measurement pair. The random bit flipping and bit exchanging perturbations are used for generating the neighborhood solutions in STS. The Pδ observable concept is used to determine the network observability. Test results of 10 bus, IEEE 14 and 30 bus systems are shown that STS can improve the original measured scheme to be observable without critical measurement pair. Moreover, the results of STS are superior to deterministic tabu search (DTS) in terms of the best solution hit.

Keywords: Measurement Scheme, Power System StateEstimation, Network Observability, Stochastic Tabu Search (STS).

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Authors: Mario Mastriani

Abstract:

Super-resolution is nowadays used for a high-resolution image produced from several low-resolution noisy frames. In this work, we consider the problem of high-quality interpolation of a single noise-free image. Such images may come from different sources, i.e., they may be frames of videos, individual pictures, etc. On the other hand, in the encoder we apply a downsampling via bidimen-sional interpolation of each frame, and in the decoder we apply a upsampling by which we restore the original size of the image. If the compression ratio is very high, then we use a convolutive mask that restores the edges, eliminating the blur. Finally, both, the encoder and the complete decoder are implemented on General-Purpose computation on Graphics Processing Units (GPGPU) cards. In fact, the mentioned mask is coded inside texture memory of a GPGPU.

Keywords: General-Purpose computation on Graphics ProcessingUnits, Image Compression, Interpolation, Super-resolution.

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Authors: V.A. Baronenko, S.I. Bugreeva, K.R. Mekhdieva

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Differentiated impact of team sports (basketball, indoor soccer, handball) on general haemodynamics and aerobic potential of students who specialize in technical subjects is detected only on the fourth year of studies in the institute of higher education. Those who play basketball and indoor soccer have shown increase of stroke and minute volume of blood indices, pumping and contractile function of the heart, oxygenation of blood and oxygen delivery to tissues, aerobic energy supply and balance of sympathetic and parasympathetic activity of the nervous regulation mechanism of the circulatory system. Those who play handball have shown these indices statistically decreased. On the whole playing basketball and indoor soccer optimizes the strategy for adaptation of students to the studying process, but playing handball does the opposite thing. The leading factor for adaptation of students is: those who play basketball have increase of minute blood volume which stipulates velocity of the system blood circulation and well-timed oxygen delivery to tissues; those who play indoor soccer have increase of power and velocity of contractile function of the heart; those who play handball have increase of resistance of thorax to the system blood flow which minimizes contractile function of the heart, blood oxygen saturation and delivery of oxygen to tissues.

Keywords: team sports, general haemodynamics, aerobic potential, strategy for adaptation.

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Authors: Yuan-Jye Tseng, Yen-Jung Wang

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A product development for green logistics model using the fuzzy analytic network process method is presented for evaluating the relationships among the product design, the manufacturing activities, and the green supply chain. In the product development stage, there can be alternative ways to design the detailed components to satisfy the design concept and product requirement. In different design alternative cases, the manufacturing activities can be different. In addition, the manufacturing activities can affect the green supply chain of the components and product. In this research, a fuzzy analytic network process evaluation model is presented for evaluating the criteria in product design, manufacturing activities, and green supply chain. The comparison matrices for evaluating the criteria among the three groups are established. The total relational values between the three groups represent the relationships and effects. In application, the total relational values can be used to evaluate the design alternative cases for decision-making to select a suitable design case and the green supply chain. In this presentation, an example product is illustrated. It shows that the model is useful for integrated evaluation of design and manufacturing and green supply chain for the purpose of product development for green logistics.

Keywords: Supply chain management, green supply chain, product development for logistics, fuzzy analytic network process.

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Authors: Farhad Kolahan, A. Hamid Khajavi

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Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.

Keywords: AWJ cutting, Mathematical modeling, Simulated Annealing, Optimization

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Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

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The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: Logistic Regression LoR, Kernel Density Estimator KDE, Handwriting, Confidence Interval, Repeatability, Reproducibility.

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Authors: Yu-Chi Shiue, Jyong Lin, Shih-Chang Chen

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With the increase of economic behavior and the upgrade of living standar, the ratio for people in Taiwan who own automobiles and motorcycles have recently increased with multiples. Therefore, parking issues will be a big challenge to facilitate traffic network and ensure urban life quality. The Parking Guidance and Information System is one of important systems for Advanced Traveler Information Services (ATIS). This research proposes a parking guidance and information system which integrates GPS and 3G network for a map on the Geographic Information System to solution inadequate of roadside information kanban. The system proposed in this study mainly includes Parking Host, Parking Guidance and Information Server, Geographic Map and Information System as well as Parking Guidance and Information Browser. The study results show this system can increase driver-s efficiency to find parking space and efficiently enhance parking convenience in comparison with roadside kanban system.

Keywords: Geographic Information System, 3G, GPS, parkinginformation

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Authors: Zina Saheb, Ezz El-Masry, Jean-François Bousquet

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This paper presents an enhanced efficiency simultaneous dual band energy harvesting system for wireless body area network. A bulk biasing is used to enhance the efficiency of the adapted rectifier design to reduce V_th of MOSFET. The presented circuit harvests the radio frequency (RF) energy from two frequency bands: 1 GHz and 2.4 GHz. It is designed with TSMC 65-nm CMOS technology and high quality factor dual matching network to boost the input voltage. Full circuit analysis and modeling is demonstrated. The simulation results demonstrate a harvester with an efficiency of 23% at 1 GHz and 46% at 2.4 GHz at an input power as low as -30 dBm.

Keywords: Energy harvester, simultaneous, dual band, CMOS, differential rectifier, voltage boosting, TSMC 65nm.

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Authors: L. Sellami, D. Idoughi, P. F. Tiako

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Cloud computing provides infrastructure to the enterprise through the Internet allowing access to cloud services at anytime and anywhere. This pervasive aspect of the services, the distributed nature of data and the wide use of information make cloud computing vulnerable to intrusions that violate the security of the cloud. This requires the use of security mechanisms to detect malicious behavior in network communications and hosts such as intrusion detection systems (IDS). In this article, we focus on the detection of intrusion into the cloud sing IDSs. We base ourselves on client authentication in the computing cloud. This technique allows to detect the abnormal use of ubiquitous service and prevents the intrusion of cloud computing. This is an approach based on client authentication data. Our IDS provides intrusion detection inside and outside cloud computing network. It is a double protection approach: The security user node and the global security cloud computing.

Keywords: Cloud computing, intrusion detection system, privacy, trust.

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Authors: Wei Yang, Xiaohui Cui, Weiping Zhu, Liqun Liu

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The rapid development of the Confucius Institute is attracting more and more attention from mainstream media around the world. Mainstream media plays a large role in public information dissemination and public opinion. This study presents efforts to analyze the correlation and functional relationship between domestic and foreign mainstream media by analyzing the amount of reports on the Confucius Institute. Three kinds of correlation calculation methods, the Pearson correlation coefficient (PCC), the Spearman correlation coefficient (SCC), and the Kendall rank correlation coefficient (KCC), were applied to analyze the correlations among mainstream media from three regions: mainland of China; Hong Kong and Macao (the two special administration regions of China denoted as SARs); and overseas countries excluding China, such as the United States, England, and Canada. Further, the paper measures the functional relationships among the regions using a regression model. The experimental analyses found high correlations among mainstream media from the different regions. Additionally, we found that there is a linear relationship between the mainstream media of overseas countries and those of the SARs by analyzing the amount of reports on the Confucius Institute based on a data set obtained by crawling the websites of 106 mainstream media during the years 2004 to 2014.

Keywords: Confucius Institute, correlation analysis, mainstream media, regression model.

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Authors: H. Rafiei, M. Rabbani

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A novel concept to balance and tradeoff between make-to-stock and make-to-order has been hybrid MTS/MTO production context. One of the most important decisions involved in the hybrid MTS/MTO environment is determining whether a product is manufactured to stock, to order, or hybrid MTS/MTO strategy. In this paper, a model based on analytic network process is developed to tackle the addressed decision. Since the regarded decision deals with the uncertainty and ambiguity of data as well as experts- and managers- linguistic judgments, the proposed model is equipped with fuzzy sets theory. An important attribute of the model is its generality due to diverse decision factors which are elicited from the literature and developed by the authors. Finally, the model is validated by applying to a real case study to reveal how the proposed model can actually be implemented.

Keywords: Fuzzy analytic network process, Hybrid make-tostock/ make-to-order, Order partitioning, Production planning.

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Authors: Eric Jacob Bacon, Chaoyang Jin, Dianning He, Shuaishuai Hu, Lanbo Wang, Han Li, Shouliang Qi

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Refractory epilepsy is a complicated type of epilepsy that can be difficult to diagnose. Recent technological advancements have made resting-state functional magnetic resonance (rsfMRI) a vital technique for studying brain activity. However, there is still much to learn about rsfMRI. Investigating rsfMRI connectivity may aid in the detection of abnormal activities. In this paper, we propose studying the functional connectivity of rsfMRI candidates to diagnose epilepsy. 45 rsfMRI candidates, comprising 26 with refractory epilepsy and 19 healthy controls, were enrolled in this study. A data-driven approach known as Independent Component Analysis (ICA) was used to achieve our goal. First, rsfMRI data from both patients and healthy controls were analyzed using group ICA. The components that were obtained were then spatially sorted to find and select meaningful ones. A two-sample t-test was also used to identify abnormal networks in patients and healthy controls. Finally, based on the fractional amplitude of low-frequency fluctuations (fALFF), a chi-square statistic test was used to distinguish the network properties of the patient and healthy control groups. The two-sample t-test analysis yielded abnormal in the default mode network, including the left superior temporal lobe and the left supramarginal. The right precuneus was found to be abnormal in the dorsal attention network. In addition, the frontal cortex showed an abnormal cluster in the medial temporal gyrus. In contrast, the temporal cortex showed an abnormal cluster in the right middle temporal gyrus and the right fronto-operculum gyrus. Finally, the chi-square statistic test was significant, producing a p-value of 0.001 for the analysis. This study offers evidence that investigating rsfMRI connectivity provides an excellent diagnosis option for refractory epilepsy.

Keywords: Independent Component Analysis, Resting State Network, refractory epilepsy, rsfMRI.

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Authors: Alla V. Goncharova, Tatyana A. Karpenyuk, Yana S. Tsurkan, Rosa U. Beisembaeva, Togzhan D. Mukasheva, Ludmila V. Ignatova, Ramza Z. Berzhanova

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In this work the effect of culturing conditions of filamentous fungi Penicillium raistrickii, Penicillium anatolicum, Fusarium sp. on biomass yield, the content of total lipids and fatty acids was studied. It has been established that in time the process of lipids accumulation correlated with biomass growth of cultures, reaching maximum values in stationary growth phase.

Biomass yield and accumulation of general lipids was increased by adding zinc to the culture medium. The more intensive accumulation of biomass and general lipids was observed at temperature 18°C. Lowering the temperature of culturing has changed the ratio of saturated: Unsaturated fatty acids in the direction of increasing the latter.

Keywords: Biomass, culturing conditions, fungi, fatty acids (FA), growth dynamics, lipids.

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Authors: S. Pazi, C. Chatwin

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ICT services are a key element of communications and important for socio-economic development. In recognition of the importance of this, the Tanzanian Government started to implement a National ICT Broadband Infrastructure Fibre Optic Backbone (NICTBB) in 2009; this development was planned to be implemented in four phases using an optical dense wavelength division multiplexing (DWDM) network technology in collaboration with the Chinese Government through the Chinese International Telecommunications Construction Corporation (CITCC) under a bilateral agreement. This paper briefly explores the NICTBB network technologies implementation, operations and Internet bandwidth costs. It also provides an in depth assessment of the delivery of ICT services such as e-services and m-services in both urban and rural areas following commissioning of the NICTBB system. Following quantitative and qualitative approaches, the study shows that there have been significant improvements in utilization efficiency, effectiveness and the reliability of the ICT service such as e-services and m-services the NICTCBB was commissioned.

Keywords: NICTBB, DWDM, Optic Fibre, Internet, ICT services, e-services, m-services.

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Authors: Sh. Jamali, A. Eftekhari

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Transmission control protocol (TCP) Vegas detects network congestion in the early stage and successfully prevents periodic packet loss that usually occurs in TCP Reno. It has been demonstrated that TCP Vegas outperforms TCP Reno in many aspects. However, TCP Vegas suffers several problems that affect its congestion avoidance mechanism. One of the most important weaknesses in TCP Vegas is that alpha and beta depend on a good expected throughput estimate, which as we have seen, depends on a good minimum RTT estimate. In order to make the system more robust alpha and beta must be made responsive to network conditions (they are currently chosen statically). This paper proposes a modified Vegas algorithm, which can be adjusted to present good performance compared to other transmission control protocols (TCPs). In order to do this, we use PSO algorithm to tune alpha and beta. The simulation results validate the advantages of the proposed algorithm in term of performance.

Keywords: Self-managing, Congestion control, TCP.

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Authors: Su Thet Mon Than, Khin Aung Lin, Mi Sandar Mon

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This paper is intended to assist anyone with some general technical experience, but perhaps limited specific knowledge of heat transfer equipment. A characteristic of heat exchanger design is the procedure of specifying a design, heat transfer area and pressure drops and checking whether the assumed design satisfies all requirements or not. The purpose of this paper is how to design the oil cooler (heat exchanger) especially for shell-and-tube heat exchanger which is the majority type of liquid-to-liquid heat exchanger. General design considerations and design procedure are also illustrated in this paper and a flow diagram is provided as an aid of design procedure. In design calculation, the MatLAB and AutoCAD software are used. Fundamental heat transfer concepts and complex relationships involved in such exchanger are also presented in this paper. The primary aim of this design is to obtain a high heat transfer rate without exceeding the allowable pressure drop. This computer program is highly useful to design the shell-and-tube type heat exchanger and to modify existing deign.

Keywords: Shell-and-Tube Heat Exchanger, MatLAB and AutoCAD

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Authors: Muhammad Marsudi, Dzuraidah Abdul Wahab, Che Hassan Che Haron

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Modeling of a manufacturing system enables one to identify the effects of key design parameters on the system performance and as a result to make correct decision. This paper proposes a manufacturing system modeling approach using a spreadsheet model based on queuing network theory, in which a static capacity planning model and stochastic queuing model are integrated. The model was used to improve the existing system utilization in relation to product design. The model incorporates few parameters such as utilization, cycle time, throughput, and batch size. The study also showed that the validity of developed model is good enough to apply and the maximum value of relative error is 10%, far below the limit value 32%. Therefore, the model developed in this study is a valuable alternative model in evaluating a manufacturing system

Keywords: Manufacturing system, product design, spreadsheet model, utilization.

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Authors: Tsung-Hsien Yu, Ya-Hsuan Chou, Ming-Wei Chen, Chi-Ming Chen, Yi-Hsuan Li

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Observations and long-term trends indicate that climate change impacts would be significant and affects Taiwan directly and severely. Taiwan engages not only in mitigation, but also in adaptation. However, there are cognitive gaps on adaptation between government and populace. Besides, a vision of zero-carbon and renewable energy 100% will be adopted in future. Therefore, the objectives of this article are to 1) hold a National Forum for knowing differences between the strategies of zero-carbon and renewable energy 100% and cognitions of general populace, and 2) plan a clear roadmap for the vision, strategy, and measures. In this forum, we set 5 group topics, 5 presumed themes, and issues mentioned review for concluding the critical issues. Finally, there are 4 strategies and 14 critical issues which correlate with the vision and strategy of government and the cognition of the general populace.

Keywords: Cognitive gap, world café, renewable energy, zero-carbon.

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Authors: Sumitra Nuanmeesri

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The research focus on study, analyze and design the model of the infrastructure and computer networks for distance education, online learning via new media, e-learning and blended learning. The collected information from study and analyze process that information was evaluated by the index of item objective congruence (IOC) by 9 specialists to design model. The results of evaluate the model with the mean and standard deviation by the sample of 9 specialists value is 3.85. The results showed that the infrastructure and computer networks are designed to be appropriate to a great extent appropriate to a great extent.

Keywords: Blended Learning, New Media, Infrastructure and Computer Network, Tele-Education, Online Learning.

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Authors: Kawpong Polyorat

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Since the outbreak of mad cow disease and bird flu, consumers have become more concerned with meat quality and safety. As a result, meat traceability is adopted as one approach to handle consumers’ concern in this issue. Nevertheless, in Thailand, meat traceability is rarely used as a marketing tool to persuade consumers. As a consequence, the present study attempts to understand consumer trust in the meat traceability system by conducting a study in this country to examine the impact of three types of consumer knowledge on this trust. The study results reveal that out of three types of consumer knowledge, marketplace knowledge was the sole predictor of consumer trust in meat traceability and it has a positive influence. General product class knowledge and knowledge in meat products with traceability, however, did not significantly influence consumer trust. The research results provide several implications and directions for future study.

Keywords: Consumer knowledge, marketing, product knowledge, traceability.

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Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

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The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: Information Gain (IG), Intrusion Detection System (IDS), K-means Clustering, Weka.

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Authors: Zulkeflee Kusin, Mohamad Shanudin Zakaria

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Hierarchical Mobile IPv6 (HMIPv6) was designed to support IP micro-mobility management in the Next Generation Networks (NGN) framework. The main design behind this protocol is the usage of Mobility Anchor Point (MAP) located at any level router of network to support hierarchical mobility management. However, the distance MAP selection in HMIPv6 causes MAP overloaded and increase frequent binding update as the network grows. Therefore, to address the issue in designing MAP selection scheme, we propose a dynamic load control mechanism integrates with a speed detection mechanism (DMS-DLC). From the experimental results we obtain that the proposed scheme gives better distribution in MAP load and increase handover speed.

Keywords: Dynamic load control, HMIPv6, Mobility AnchorPoint, MAP selection scheme

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Authors: A. El-S. Makled, M. K. Al-Tamimi

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A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO₂) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: Hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters.

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Authors: S. Youthao, M. Jaroensutasinee, K. Jaroensutasinee

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This study investigated climatic factors associated with influenza cases in Southern Thailand. The main aim for use regression analysis to investigate possible causual relationship of climatic factors and variability between the border of the Andaman Sea and the Gulf of Thailand. Southern Thailand had the highest Influenza incidences among four regions (i.e. north, northeast, central and southern Thailand). In this study, there were 14 climatic factors: mean relative humidity, maximum relative humidity, minimum relative humidity, rainfall, rainy days, daily maximum rainfall, pressure, maximum wind speed, mean wind speed, sunshine duration, mean temperature, maximum temperature, minimum temperature, and temperature difference (i.e. maximum – minimum temperature). Multiple stepwise regression technique was used to fit the statistical model. The results indicated that the mean wind speed and the minimum relative humidity were positively associated with the number of influenza cases on the Andaman Sea side. The maximum wind speed was positively associated with the number of influenza cases on the Gulf of Thailand side.

Keywords: Influenza, Climatic Factor, Relative Humidity, Rainfall, Pressure, Wind Speed, sunshine duration, Temperature, Andaman Sea, Gulf of Thailand, Southern Thailand.

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Authors: Ning Gong, Michael Korostelev, Qiangguo Ren, Li Bai, Saroj Biswas, Frank Ferrese

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This paper investigates the joint effect of the interconnected (n,k)-star network topology and Multi-Agent automated control on restoration and reconfiguration of power systems. With the increasing trend in development in Multi-Agent control technologies applied to power system reconfiguration in presence of faulty components or nodes. Fault tolerance is becoming an important challenge in the design processes of the distributed power system topology. Since the reconfiguration of a power system is performed by agent communication, the (n,k)-star interconnected network topology is studied and modeled in this paper to optimize the process of power reconfiguration. In this paper, we discuss the recently proposed (n,k)-star topology and examine its properties and advantages as compared to the traditional multi-bus power topologies. We design and simulate the topology model for distributed power system test cases. A related lemma based on the fault tolerance and conditional diagnosability properties is presented and proved both theoretically and practically. The conclusion is reached that (n,k)-star topology model has measurable advantages compared to standard bus power systems while exhibiting fault tolerance properties in power restoration, as well as showing efficiency when applied to power system route discovery.

Keywords: (n, k)-star Topology, Fault Tolerance, Conditional Diagnosability, Multi-Agent System, Automated Power System.

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Authors: Hichem Sassi, Tawfik Najeh, Noureddine Liouane

Abstract:

Information of nodes’ locations is an important criterion for lots of applications in Wireless Sensor Networks. In the hop-based range-free localization methods, anchors transmit the localization messages counting a hop count value to the whole network. Each node receives this message and calculates its own distance with anchor in hops and then approximates its own position. However the estimative distances can provoke large error, and affect the localization precision. To solve the problem, this paper proposes an algorithm, which makes the unknown nodes fix the nearest anchor as a reference and select two other anchors which are the most accurate to achieve the estimated location. Compared to the DV-Hop algorithm, experiment results illustrate that proposed algorithm has less average localization error and is more effective.

Keywords: Wireless Sensors Networks, Localization problem, localization average error, DV–Hop Algorithm, MATLAB.

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