Search results for: information of interest

Authors: Yessine Hadj Kacem, Adel Mahfoudhi, Hedi Tmar, Mohamed Abid

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Unified Modeling Language (UML) extensions for real time embedded systems (RTES) co-design, are taking a growing interest by a great number of industrial and research communities. The extension mechanism is provided by UML profiles for RTES. It aims at improving an easily-understood method of system design for non-experts. On the other hand, one of the key items of the co- design methods is the Hardware/Software partitioning and scheduling tasks. Indeed, it is mandatory to define where and when tasks are implemented and run. Unfortunately the main goals of co-design are not included in the usual practice of UML profiles. So, there exists a need for mapping used models to an execution platform for both schedulability test and HW/SW partitioning. In the present work, test schedulability and design space exploration are performed at an early stage. The proposed approach adopts Model Driven Engineering MDE. It starts from UML specification annotated with the recent profile for the Modeling and Analysis of Real Time Embedded systems MARTE. Following refinement strategy, transformation rules allow to find a feasible schedule that satisfies timing constraints and to define where tasks will be implemented. The overall approach is experimented for the design of a football player robot application.

Keywords: MDE, UML profile, scheduling analysis, HW/SW partitioning.

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Authors: Jessica Lòpez Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane, El Hassane Ettifouri

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Pretrained transformer-based models have shown high performance in natural language generation task. However, a new wave of interest has surged: automatic programming language generation. This task consists of translating natural language instructions to a programming code. Despite the fact that well-known pretrained models on language generation have achieved good performance in learning programming languages, effort is still needed in automatic code generation. In this paper, we introduce JaCoText, a model based on Transformers neural network. It aims to generate java source code from natural language text. JaCoText leverages advantages of both natural language and code generation models. More specifically, we study some findings from the state of the art and use them to (1) initialize our model from powerful pretrained models, (2) explore additional pretraining on our java dataset, (3) carry out experiments combining the unimodal and bimodal data in the training, and (4) scale the input and output length during the fine-tuning of the model. Conducted experiments on CONCODE dataset show that JaCoText achieves new state-of-the-art results.

Keywords: Java code generation, Natural Language Processing, Sequence-to-sequence Models, Transformers Neural Networks.

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an  enormous number of applications, cyber-threats have significantly  increased accordingly. Thus, accurate detection of malicious traffic in  a timely manner is a critical concern in today’s Internet for security.  One approach for intrusion detection is to use Machine Learning (ML)  techniques. Several methods based on ML algorithms have been  introduced over the past years, but they are largely limited in terms of  detection accuracy and/or time and space complexity to run. In this  work, we present a novel method for intrusion detection that  incorporates a set of supervised learning algorithms. The proposed  technique provides high accuracy and outperforms existing techniques  that simply utilizes a single learning method. In addition, our  technique relies on partial flow information (rather than full  information) for detection, and thus, it is light-weight and desirable for  online operations with the property of early identification. With the  mid-Atlantic CCDC intrusion dataset publicly available, we show that  our proposed technique yields a high degree of detection rate over 99%  with a very low false alarm rate (0.4%). 

 

Keywords: Intrusion Detection, Supervised Learning, Traffic Classification.

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Authors: Fantazi Walid, Ezzedine Tahar, Bargaoui Zoubeida

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This research presents the main ideas to implement an intelligent system composed by communicating wireless sensors measuring environmental data linked to drought indicators (such as air temperature, soil moisture , etc...). On the other hand, the setting up of a spatio temporal database communicating with a Web mapping application for a monitoring in real time in activity 24:00 /day, 7 days/week is proposed to allow the screening of the drought parameters time evolution and their extraction. Thus this system helps detecting surfaces touched by the phenomenon of drought. Spatio-temporal conceptual models seek to answer the users who need to manage soil water content for irrigating or fertilizing or other activities pursuing crop yield augmentation. Effectively, spatiotemporal conceptual models enable users to obtain a diagram of readable and easy data to apprehend. Based on socio-economic information, it helps identifying people impacted by the phenomena with the corresponding severity especially that this information is accessible by farmers and stakeholders themselves. The study will be applied in Siliana watershed Northern Tunisia.

Keywords: WSN, database spatio-temporal, GIS, web-mapping, indicator of drought.

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Authors: Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

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In this paper, the optimum design for renewable energy system powered an aquaculture pond was determined. Hybrid Optimization Model for Electric Renewable (HOMER) software program, which is developed by U.S National Renewable Energy Laboratory (NREL), is used for analyzing the feasibility of the stand alone and hybrid system in this study. HOMER program determines whether renewable energy resources satisfy hourly electric demand or not. The program calculates energy balance for every 8760 hours in a year to simulate operation of the system. This optimization compares the demand for the electrical energy for each hour of the year with the energy supplied by the system for that hour and calculates the relevant energy flow for each component in the model. The essential principle is to minimize the total system cost while HOMER ensures control of the system. Moreover the feasibility analysis of the energy system is also studied. Wind speed, solar irradiance, interest rate and capacity shortage are the parameters which are taken into consideration. The simulation results indicate that the hybrid system is the best choice in this study, yielding lower net present cost. Thus, it provides higher system performance than PV or wind stand alone systems.

Keywords: Wind stand-alone system, Photovoltaic stand-alone system, Hybrid system, Optimum system sizing, feasibility, Cost analysis.

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Authors: A. Bagheri Garmarudi, M. Khanmohammadi, N. Khoddami, K. Shabani

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Determination of nano particle size is substantial since the nano particle size exerts a significant effect on various properties of nano materials. Accordingly, proposing non-destructive, accurate and rapid techniques for this aim is of high interest. There are some conventional techniques to investigate the morphology and grain size of nano particles such as scanning electron microscopy (SEM), atomic force microscopy (AFM) and X-ray diffractometry (XRD). Vibrational spectroscopy is utilized to characterize different compounds and applied for evaluation of the average particle size based on relationship between particle size and near infrared spectra [1,4] , but it has never been applied in quantitative morphological analysis of nano materials. So far, the potential application of nearinfrared (NIR) spectroscopy with its ability in rapid analysis of powdered materials with minimal sample preparation, has been suggested for particle size determination of powdered pharmaceuticals. The relationship between particle size and diffuse reflectance (DR) spectra in near infrared region has been applied to introduce a method for estimation of particle size. Back propagation artificial neural network (BP-ANN) as a nonlinear model was applied to estimate average particle size based on near infrared diffuse reflectance spectra. Thirty five different nano TiO2 samples with different particle size were analyzed by DR-FTNIR spectrometry and the obtained data were processed by BP- ANN.

Keywords: near infrared, particle size, chemometrics, neuralnetwork, nano structure.

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Authors: Ammar Anwar Khan, Nissar R. Wani, Nazar Malik, Abdulrehman Al-Arainy, and Saad Alghuwainem

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Power cables are vulnerable to failure due to aging or defects that occur with the passage of time under continuous operation and loading stresses. PD detection and characterization provide information on the location, nature, form and extent of the degradation. As a result, PD monitoring has become an important part of condition based maintenance (CBM) program among power utilities. Online partial discharge (PD) localization of defect sources in power cable system is possible using the time of flight method. The information regarding the time difference between the main and reflected pulses and cable length can help in locating the partial discharge source along the cable length. However, if the length of the cable is not known and the defect source is located at the extreme ends of the cable or in the middle of the cable, then double ended measurement is required to indicate the location of PD source. Use of multiple sensors can also help in discriminating the cable PD or local/ external PD. This paper presents the experience and results from online partial discharge measurements conducted in the laboratory and the challenges in partial discharge source localization.

Keywords: Power cables, partial discharge localization, HFCT, condition based monitoring.

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Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: Academic performance prediction system, prediction model, educational data mining, dominant factors, feature selection methods, student performance.

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Authors: Abbas Siefi, Mohammad Javad Karimifar

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We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.

Keywords: Spatial design of experiments, maximum entropy sampling, computer experiments, genetic algorithm.

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Authors: Jooyeon Yook, Wonjun Ko

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As the Social network game(SNG) is rising dramatically worldwide, an interesting aspect has appeared in the demographic analysis. That is the ratio of the game users by gender. Although the ratio of male and female users in online game was 60:40% previously, the ratio of male and female users in SNG stood at 47:53% which shows that the ratio of female users is higher than that of male users. Here, it should be noted that 35% in those 53% female users are the first-time users of game. This fact suggests that women who were not interested in game previously has taken an interest in SNG. Notwithstanding this issue, there have been little studies on the female users of SNG although there are many studies that analyzed the tendency of female users- online game play. This study conducted the analyzed how the game-playing tendency of SNG gamers was manifested in the game by gender. For that, this study will identify the tendency of SNG users by gender based on the preceding studies that analyzed the online game users by gender. The subject of this study was confined to the farm and urban construction simulation games which were offered based on the mobile application platform. Regarding the methodology of study, the first focus group interview(FGI) was conducted with the male and female users who had played games on Social network service(SNS) until recently. Later, the second one-on-one in-depth interview was conducted to gain an insight into the psychological state of the subjects.

Keywords: Social network Game, Gender, Play inclination, Game psychology

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Authors: Mangesh S. Deshpande, Raghunath S. Holambe

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Mel Frequency Cepstral Coefficient (MFCC) features are widely used as acoustic features for speech recognition as well as speaker recognition. In MFCC feature representation, the Mel frequency scale is used to get a high resolution in low frequency region, and a low resolution in high frequency region. This kind of processing is good for obtaining stable phonetic information, but not suitable for speaker features that are located in high frequency regions. The speaker individual information, which is non-uniformly distributed in the high frequencies, is equally important for speaker recognition. Based on this fact we proposed an admissible wavelet packet based filter structure for speaker identification. Multiresolution capabilities of wavelet packet transform are used to derive the new features. The proposed scheme differs from previous wavelet based works, mainly in designing the filter structure. Unlike others, the proposed filter structure does not follow Mel scale. The closed-set speaker identification experiments performed on the TIMIT database shows improved identification performance compared to other commonly used Mel scale based filter structures using wavelets.

Keywords: Speaker identification, Wavelet transform, Feature extraction, MFCC, GMM.

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Authors: Surinder Deswal

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There has been a growing interest in the oxygenation by plunging water jets in the last few years due to their inherent advantages, like energy-efficient, low operation cost, etc. Though a lot of work has been reported on the oxygen-transfer by single plunging water jets but very few studies have been carried out using multiple plunging jets. In this paper, volumetric oxygen-transfer coefficient and oxygen-transfer efficiency has been studied experimentally for multiple inclined plunging jets (having jet plunge angle of 60 0 ) in a pool of water for different configurations, in terms of varying number of jets and jet diameters. This research suggests that the volumetric oxygen-transfer coefficient and oxygentransfer efficiency of the multiple inclined plunging jets for air-water system are significantly higher than those of a single vertical as well as inclined plunging jet for same flow area and other similar conditions. The study also reveals that the oxygen-transfer increase with increase in number of multiple jets under similar conditions, which will be most advantageous and energy-efficient in practical situations when large volumes of wastewaters are to be treated. A relationship between volumetric oxygen-transfer coefficient and jet parameters is also proposed. The suggested relationship predicts the volumetric oxygen-transfer coefficient for multiple inclined plunging jet(s) within a scatter of ±15 percent. The relationship will be quite useful in scale-up and in deciding optimum configuration of multiple inclined plunging jet aeration system.

Keywords: Multiple inclined plunging jets, jet plunge angle, volumetric oxygen-transfer coefficient, oxygen-transfer efficiency.

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Authors: Muhammad Yasir Babar, Ebrahim Panah

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Over the past 20 years, internet has seen continual advancement and with the advent of online technology, various types of web-based games have been developed. Games are frequently being used among different age groups from baby boomers to generation Z. Games are not only used for entertainment but also utilized as a learning approach transmitting education to a level that is more interesting and effective for students. One of the popular web-based education games is Kahoot with growing popularity and usage, which is being used in different fields of studies. However, little knowledge is available on university students’ perception of Kahoot environment and application for learning subjects. Hence, the objective of the current study is to investigate students’ perceptions of Kahoot application and environment as a learning tool. The study employed a survey approach by distributing Google Forms –created questionnaire, with high level of reliability index, to 62 students (11 males and 51 females). The findings show that students have positive attitudes towards Kahoot application and its environment for learning. Regarding Kahoot application, it was indicated that activities created using Kahoot are more interesting for students, Kahoot is useful for collaborative learning, and Kahoot enhances interest in learning lesson. In terms of Kahoot environment, it was found that using this application through mobile is easy for students, its design is simple and useful, Kahoot-created activities can easily be shared, and the application can easily be used on any platform. The findings of the study have implications for instructors, policymakers and curriculum developers.

Keywords: Application, environment, Kahoot, learning tool.

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Authors: N. B. Fedosenko, A.A Iatcenko, S.A. Levanov

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The paper shows some ability to manage two-phase flows arising from the use of unsteady effects. In one case, we consider the condition of fragmentation of the interface between the two components leads to the intensification of mixing. The problem is solved when the temporal and linear scale are small for the appearance of the developed mixing layer. Showing that exist such conditions for unsteady flow velocity at the surface of the channel, which will lead to the creation and fragmentation of vortices at Re numbers of order unity. Also showing that the Re is not a criterion of similarity for this type of flows, but we can introduce a criterion that depends on both the Re, and the frequency splitting of the vortices. It turned out that feature of this situation is that streamlines behave stable, and if we analyze the behavior of the interface between the components it satisfies all the properties of unstable flows. The other problem we consider the behavior of solid impurities in the extensive system of channels. Simulated unsteady periodic flow modeled breaths. Consider the behavior of the particles along the trajectories. It is shown that, depending on the mass and diameter of the particles, they can be collected in a caustic on the channel walls, stop in a certain place or fly back. Of interest is the distribution of particle velocity in frequency. It turned out that by choosing a behavior of the velocity field of the carrier gas can affect the trajectory of individual particles including force them to fly back.

Keywords: Two-phase, mixing, separating, flow control

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Authors: S. Logeswari, K. Premalatha

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Search is the most obvious application of information retrieval. The variety of widely obtainable biomedical data is enormous and is expanding fast. This expansion makes the existing techniques are not enough to extract the most interesting patterns from the collection as per the user requirement. Recent researches are concentrating more on semantic based searching than the traditional term based searches. Algorithms for semantic searches are implemented based on the relations exist between the words of the documents. Ontologies are used as domain knowledge for identifying the semantic relations as well as to structure the data for effective information retrieval. Annotation of data with concepts of ontology is one of the wide-ranging practices for clustering the documents. In this paper, indexing based on concept and annotation are proposed for clustering the biomedical documents. Fuzzy c-means (FCM) clustering algorithm is used to cluster the documents. The performances of the proposed methods are analyzed with traditional term based clustering for PubMed articles in five different diseases communities. The experimental results show that the proposed methods outperform the term based fuzzy clustering.

Keywords: MeSH Ontology, Concept Indexing, Annotation, semantic relations, Fuzzy c-means.

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Authors: J. A. Batsis, G. G. Boateng, L. M. Seo, C. L. Petersen, K. L. Fortuna, E. V. Wechsler, R. J. Peterson, S. B. Cook, D. Pidgeon, R. S. Dokko, R. J. Halter, D. F. Kotz

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Resistance exercise bands are a core component of any physical activity strengthening program. Strength training can mitigate the development of sarcopenia, the loss of muscle mass or strength and function with aging. Yet, the adherence of such behavioral exercise strategies in a home-based setting are fraught with issues of monitoring and compliance. Our group developed a Bluetooth-enabled resistance exercise band capable of transmitting data to an open-source platform. In this work, we developed an application to capture this information in real-time, and conducted three usability studies in two mixed-aged groups of participants (n=6 each) and a group of older adults with obesity participating in a weight-loss intervention (n=20). The system was favorable, acceptable and provided iterative information that could assist in future deployment on ubiquitous platforms. Our formative work provides the foundation to deliver home-based monitoring interventions in a high-risk, older adult population.

Keywords: Application, mHealth, older adult, resistance exercise band, sarcopenia.

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Authors: Asif Ansari, T.C.Manjunath, C. Ardil

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In today-s competitive environment, the security concerns have grown tremendously. In the modern world, possession is known to be 9/10-ths of the law. Hence, it is imperative for one to be able to safeguard one-s property from worldly harms such as thefts, destruction of property, people with malicious intent etc. Due to the advent of technology in the modern world, the methodologies used by thieves and robbers for stealing have been improving exponentially. Therefore, it is necessary for the surveillance techniques to also improve with the changing world. With the improvement in mass media and various forms of communication, it is now possible to monitor and control the environment to the advantage of the owners of the property. The latest technologies used in the fight against thefts and destruction are the video surveillance and monitoring. By using the technologies, it is possible to monitor and capture every inch and second of the area in interest. However, so far the technologies used are passive in nature, i.e., the monitoring systems only help in detecting the crime but do not actively participate in stopping or curbing the crime while it takes place. Therefore, we have developed a methodology to detect the motion in a video stream environment and this is an idea to ensure that the monitoring systems not only actively participate in stopping the crime, but do so while the crime is taking place. Hence, a system is used to detect any motion in a live streaming video and once motion has been detected in the live stream, the software will activate a warning system and capture the live streaming video.

Keywords: Motion, Detection, System, Video, Crime, Matlab, Surveillance.

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Authors: Shih-Wen Hsiao, Yi-Cheng Tsao

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In the field of reverse engineering and creative industries, applying 3D scanning process to obtain geometric forms of the objects is a mature and common technique. For instance, organic objects such as faces and nonorganic objects such as products could be scanned to acquire the geometric information for further application. However, although the data resolution of 3D scanning device is increasing and there are more and more abundant complementary applications, the penetration rate of 3D scanning for the public is still limited by the relative high price of the devices. On the other hand, Kinect, released by Microsoft, is known for its powerful functions, considerably low price, and complete technology and database support. Therefore, related studies can be done with the applying of Kinect under acceptable cost and data precision. Due to the fact that Kinect utilizes optical mechanism to extracting depth information, limitations are found due to the reason of the straight path of the light. Thus, various angles are required sequentially to obtain the complete 3D information of the object when applying a single Kinect for 3D scanning. The integration process which combines the 3D data from different angles by certain algorithms is also required. This sequential scanning process costs much time and the complex integration process often encounter some technical problems. Therefore, this paper aimed to apply multiple Kinects simultaneously on the field of developing a rapid 3D mannequin scan platform and proposed suggestions on the number and angles of Kinects. In the content, a method of establishing the coordination based on the relation between mannequin and the specifications of Kinect is proposed, and a suggestion of angles and number of Kinects is also described. An experiment of applying multiple Kinect on the scanning of 3D mannequin is constructed by Microsoft API, and the results show that the time required for scanning and technical threshold can be reduced in the industries of fashion and garment design.

Keywords: 3D scan, depth sensor, fashion and garment design, mannequin, multiple kinect sensor.

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Authors: Leila Maleki, Ahmad Esmali Kooraneh, Hossein Taghi Derakhshi

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Neural activity in the human brain starts from the early stages of prenatal development. This activity or signals generated by the brain are electrical in nature and represent not only the brain function but also the status of the whole body. At the present moment, three methods can record functional and physiological changes within the brain with high temporal resolution of neuronal interactions at the network level: the electroencephalogram (EEG), the magnet oencephalogram (MEG), and functional magnetic resonance imaging (fMRI); each of these has advantages and shortcomings. EEG recording with a large number of electrodes is now feasible in clinical practice. Multichannel EEG recorded from the scalp surface provides very valuable but indirect information about the source distribution. However, deep electrode measurements yield more reliable information about the source locations intracranial recordings and scalp EEG are used with the source imaging techniques to determine the locations and strengths of the epileptic activity. As a source localization method, Low Resolution Electro-Magnetic Tomography (LORETA) is solved for the realistic geometry based on both forward methods, the Boundary Element Method (BEM) and the Finite Difference Method (FDM). In this paper, we review the findings EEG- LORETA about epilepsy.

Keywords: Epilepsy, EEG, EEG- Loreta, loreta analysis.

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Authors: L. Grinis

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Turbulent flow in complex geometries receives considerable attention due to its importance in many engineering applications. It has been the subject of interest for many researchers. Some of these interests include the design of storm water channels. The design of these channels requires testing through physical models. The main practical limitation of physical models is the so called “scale effect”, that is, the fact that in many cases only primary physical mechanisms can be correctly represented, while secondary mechanisms are often distorted. These observations form the basis of our study, which centered on problems associated with the design of storm water channels near the Dead Sea, in Israel. To help reach a final design decision we used different physical models. Our research showed good coincidence with the results of laboratory tests and theoretical calculations, and allowed us to study different effects of fluid flow in an open channel. We determined that problems of this nature cannot be solved only by means of theoretical calculation and computer simulation. This study demonstrates the use of physical models to help resolve very complicated problems of fluid flow through baffles and similar structures. The study applies these models and observations to different construction and multiphase water flows, among them, those that include sand and stone particles, a significant attempt to bring to the testing laboratory a closer association with reality.

Keywords: Baffles, open channel, physical modeling.

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Authors: Mohamad Azmi Haniffa, Fakhruldin Mohd Hashim

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Pipeline infrastructures normally represent high cost of investment and the pipeline must be free from risks that could cause environmental hazard and potential threats to personnel safety. Pipeline integrity such monitoring and management become very crucial to provide unimpeded transportation and avoiding unnecessary production deferment. Thus proper cleaning and inspection is the key to safe and reliable pipeline operation and plays an important role in pipeline integrity management program and has become a standard industry procedure. In view of this, understanding the motion (dynamic behavior), prediction and control of the PIG speed is important in executing pigging operation as it offers significant benefits, such as estimating PIG arrival time at receiving station, planning for suitable pigging operation, and improves efficiency of pigging tasks. The objective of this paper is to review recent developments in speed control system of pipeline PIGs. The review carried out would serve as an industrial application in a form of quick reference of recent developments in pipeline PIG speed control system, and further initiate others to add-in/update the list in the future leading to knowledge based data, and would attract active interest of others to share their view points.

Keywords: Pipeline Inspection Gauge (PIG), In Line Inspection Tools (ILI), PIG motion, PIG speed control system

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Authors: Somi Nah

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The genre of fantasy depicts a world of imagine that triggers popular interest from a created view of world, and a fantasy is defined as a story that illustrates a world of imagine where scientific or horror elements are stand in its center. This study is not focused on the narrative of the fantasy, i.e. not on the adventurous story, but is concentrated on the image of the fantasy to work on its relationship with intended themes and differences among cultures due to meanings of materials. As for films, we have selected some films in the 2000's that are internationally recognized as expressing unique images of fantasy containing the theme of love in them. The selected films are 5 pieces including two European films, Amelie from Montmartre (2001) and The Science of Sleep (2005) and three Asian films, Citizen Dog from Thailand (2004), Memories of Matsuko from Japan (2006), and I'm a Cyborg, but That's OK from Korea (2006). These films share some common characteristics to the effect that they give tiny lessons and feelings for life with expressions of fantasy images as if they were fairy tales for adults and that they lead the audience to reflect on their days and revive forgotten dreams of childhood. We analyze the images of fantasy in each of the films on the basis of the elements of Mise-en-Scène (setting and props, costume, hair and make-up, facial expressions and body language, lighting and color, positioning of characters, and objects within a frame).

Keywords: Mise-en-scène, fantasy images, films, visualization.

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Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom

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Nowadays the promotion of the public transportation system in the Bangkok Metropolitan Area is increased such as the “Free Bus for Thai Citizen” Campaign and the prospect of the several MRT       routes to increase the convenient and comfortable to the Bangkok Metropolitan area citizens. But citizens do not make full use of them it because the citizens are lack of the data and information and also the confident to the public transportation system of Thailand especially in the time and safety aspects. This research is the Public Transport Planning System by Dijkstra Algorithm: Case Study Bangkok Metropolitan Area by focusing on buses, BTS and MRT schedules/routes to give the most information to passengers. They can choose the way and the routes easily by using Dijkstra STAR Algorithm of Graph Theory which also shows the fare of the trip. This Application was evaluated by 30 normal users to find the mean and standard deviation of the developed system. Results of the evaluation showed that system is at a good level of satisfaction (4.20 and 0.40). From these results we can conclude that the system can be used properly and effectively according to the objective.

Keywords: Dijkstra Algorithm, Graph Theory, Shortest Route, Public Transport, Bangkok Metropolitan Area.

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Authors: Zainah Abdullah, Aznur Hajar Abdullah

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This paper examines the impact of information and communication technology (ICT) usage, internal relationship, supplier-retailer relationship, logistics services and inventory management on convenience store suppliers- performance. Data was collected from 275 convenience store managers in Malaysia using a set of questionnaire. The multiple linear regression results indicate that inventory management, supplier-retailer relationship, logistics services and internal relationship are predictors of supplier performance as perceived by convenience store managers. However, ICT usage is not a predictor of supplier performance. The study focuses only on convenience stores and petrol station convenience stores and concentrates only on managers. The results provide insights to suppliers who serve convenience stores and possibly similar retail format on factors to consider in improving their service to retailers. The results also provide insights to government in its aspiration to improve business operations of convenience store to consider ways to enhance the adoption of ICT by retailers and suppliers.

Keywords: Information and communication technology (ICT), internal relationship, inventory management, logistics services, supplier performance, supplier-retailer relationship.

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Authors: Ming Ling Lai, Zalilawati Yaacob, Normah Omar, Norashikin Abdul Aziz, Bee Wah Yap

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This paper aims to (1) analyze the profiles of transgressors (detected evaders); (2) examine reason(s) that triggered a tax audit, causes of tax evasion, audit timeframe and tax penalty charged; and (3) to assess if tax auditors followed the guidelines as stated in the 'Tax Audit Framework' when conducting tax audits. In 2011, the Inland Revenue Board Malaysia (IRBM) had audited and finalized 557 company cases. With official permission, data of all the 557 cases were obtained from the IRBM. Of these, a total of 421 cases with complete information were analyzed. About 58.1% was small and medium corporations and from the construction industry (32.8%). The selection for tax audit was based on risk analysis (66.8%), information from third party (11.1%), and firm with low profitability or fluctuating profit pattern (7.8%). The three persistent causes of tax evasion by firms were over claimed expenses (46.8%), fraudulent reporting of income (38.5%) and overstating purchases (10.5%). These findings are consistent with past literature. Results showed that tax auditors took six to 18 months to close audit cases. More than half of tax evaders were fined 45% on additional tax raised during audit for the first offence. The study found tax auditors did follow the guidelines in the 'Tax Audit Framework' in audit selection, settlement and penalty imposition.

Keywords: Corporate tax fraud, tax non-compliance, tax evasion, tax audit, fraudulent reporting.

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: Sanae Attioui, Said Najah

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The Earth's surface is constantly changing through forces of nature and human activities. Reliable, accurate, and timely change detection is critical to environmental monitoring, resource management, and planning activities. Recently, interest in deep learning algorithms, especially convolutional neural networks, has increased in the field of image change detection due to their powerful ability to extract multi-level image features automatically. However, these networks are prone to drawbacks that limit their applications, which reside in their inability to capture spatial relationships between image instances, as this necessitates a large amount of training data. As an alternative, Capsule Network has been proposed to overcome these shortcomings. Although its effectiveness in remote sensing image analysis has been experimentally verified, its application in change detection tasks remains very sparse. Motivated by its greater robustness towards improved hierarchical object representation, this study aims to apply a capsule network for PolSAR image Change Detection. The experimental results demonstrate that the proposed change detection method can yield a significantly higher detection rate compared to methods based on convolutional neural networks.

Keywords: Change detection, capsule network, deep network, Convolutional Neural Networks, polarimetric synthetic aperture radar images, PolSAR images.

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Authors: Boonlert Watjatrakul

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Mobile marketing through mobile messaging service has highly impressive growth as it enables e-business firms to communicate with their customers effectively. Educational institutions hence start using this service to enhance communication with their students. Previous studies, however, have limited understanding of applying mobile messaging service in education. This study proposes a theoretical model to understand the drivers of students- intentions to use the university-s mobile messaging service. The model indicates that social influence, perceived control and attitudes affect students- intention to use the university-s mobile messaging service. It also provides five antecedents of students- attitudes–perceived utility (information utility, entertainment utility, and social utility), innovativeness, information seeking, transaction specificity (content specificity, sender specificity, and time specificity) and privacy concern. The proposed model enables universities to understand what students concern about the use of a mobile messaging service in universities and handle the service more effectively. The paper discusses the model development and concludes with limitations and implications of the proposed model.

Keywords: education, intention, mobile marketing, mobile messaging.

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Authors: B. O. Diyaolu

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The opportunity provided by advances in technology as regard to sports betting is so numerous. Nigerian youth are not left out especially with the use of phones and visit to sports betting outlets. Today, it is more difficult to differentiate a true fan as there are quite a number of them that became fans as a result of betting on live games. This study investigated the influence of online sports events on betting among Nigerian youth. A descriptive survey research design was used and the population consists of all Nigerian youth that engages in betting and lives within the southwest zone of Nigeria. A simple random sampling technique was used to pick three states from the southwest zone of Nigeria. 2500 respondents comprising of males and females were sampled from the three states. A structured questionnaire on Online Sports Event Contribution to Sports Betting (OSECSB) was used. The instrument consists of three sections. Section A seeks information on the demographic data of the respondents. Section B seeks information on online sports events while section C was used to extract information on sports betting. The modified instrument which consists of 14 items has a reliability coefficient of 0.74. The hypothesis was tested at 0.05 significance level. The completed questionnaire was collated, coded, and analyzed using descriptive statistics of frequency counts, percentage and pie chart, and inferential statistics of multiple regressions. The findings of this study revealed that online sports betting is a significant predictor of an increase in sports betting among Nigerian youth. The media and television, as well as globalization and the internet, coupled with social media and various online platforms, have all contributed to the immense increase in sports betting. The increase in the advertisement of the betting platform during live matches, especially football, is becoming more alarming. In most organized international events, the media attention, as well as sponsorship rights, are now been given to one or two betting platforms. There is a need for all stakeholders to put in place school-based intervention programs to reorientate our youth about the consequences of addiction to betting. Such programs must include meta-analyses and emotional control towards sports betting.

Keywords: Betting platform, Nigerian fans, Nigerian youth, sports betting.

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Authors: Yuji Waizumi, Tohru Sato, Yoshiaki Nemoto

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Recently, Denial of Service(DoS) attacks and Distributed DoS(DDoS) attacks which are stronger form of DoS attacks from plural hosts have become security threats on the Internet. It is important to identify the attack source and to block attack traffic as one of the measures against these attacks. In general, it is difficult to identify them because information about the attack source is falsified. Therefore a method of identifying the attack source by tracing the route of the attack traffic is necessary. A traceback method which uses traffic patterns, using changes in the number of packets over time as criteria for the attack traceback has been proposed. The traceback method using the traffic patterns can trace the attack by matching the shapes of input traffic patterns and the shape of output traffic pattern observed at a network branch point such as a router. The traffic pattern is a shapes of traffic and unfalsifiable information. The proposed trace methods proposed till date cannot obtain enough tracing accuracy, because they directly use traffic patterns which are influenced by non-attack traffics. In this paper, a new traffic pattern matching method using Independent Component Analysis(ICA) is proposed.

Keywords: Distributed Denial of Service, Independent Component Analysis, Traffic pattern

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