Search results for: computer mediate communication.

Authors: Apetsi K. Ampiah, Zhao Xin

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Earthquakes over the years have been known to cause devastating damage on buildings and induced huge loss on human life and properties. It is for this reason that engineers have devised means of protecting buildings and thus protecting human life. Since the invention of devices such as the viscous and friction dampers, scientists/researchers have been able to incorporate these devices into buildings and other engineering structures. The viscous damper is a hydraulic device which dissipates the seismic forces by pushing fluid through an orifice, producing a damping pressure which creates a force. In the friction damper, the force is mainly resisted by converting the kinetic energy into heat by friction. Devices such as viscous and friction dampers are able to absorb almost all the earthquake energy, allowing the structure to remain undamaged (or with some amount of damage) and ready for immediate reuse (with some repair works). Comparing these two devices presents the engineer with adequate information on the merits and demerits of these devices and in which circumstances their use would be highly favorable. This paper examines the performance of both viscous and friction dampers under different ground motions. A two-storey frame installed with both devices under investigation are modeled in commercial computer software and analyzed under different ground motions. The results of the performance of the structure are then tabulated and compared. Also included in this study is the ease of installation and maintenance of these devices.

Keywords: Friction damper, seismic, slip load, viscous damper.

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Authors: Murat Dicleli, Ali Salem Milani

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In this paper, a summary of analytical and experimental studies into the behavior of a new hysteretic damper, designed for seismic protection of structures is presented. The Multidirectional Torsional Hysteretic Damper (MRSD) is a patented invention in which a symmetrical arrangement of identical cylindrical steel cores is so configured as to yield in torsion while the structure experiences planar movements due to earthquake shakings. The new device has certain desirable properties. Notably, it is characterized by a variable and controllable-via-design post-elastic stiffness. The mentioned property is a result of MRSD’s kinematic configuration which produces this geometric hardening, rather than being a secondary large-displacement effect. Additionally, the new system is capable of reaching high force and displacement capacities, shows high levels of damping, and very stable cyclic response. The device has gone through many stages of design refinement, multiple prototype verification tests and development of design guide-lines and computer codes to facilitate its implementation in practice. Practicality of the new device, as offspring of an academic sphere, is assured through extensive collaboration with industry in its final design stages, prototyping and verification test programs.

Keywords: Seismic, isolation, damper, adaptive stiffness.

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Authors: Sangbum Park, Namki Lee, Youngjoon Han, Hernsoo Hahn

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In this paper, we propose the robust water level detection method based on the accumulated histogram under small changed image which is acquired from water level surveillance camera. In general surveillance system, this is detecting and recognizing invasion from searching area which is in big change on the sequential images. However, in case of a water level detection system, these general surveillance techniques are not suitable due to small change on the water surface. Therefore the algorithm introduces the accumulated histogram which is emphasizing change of water surface in sequential images. Accumulated histogram is based on the current image frame. The histogram is cumulating differences between previous images and current image. But, these differences are also appeared in the land region. The band pass filter is able to remove noises in the accumulated histogram Finally, this algorithm clearly separates water and land regions. After these works, the algorithm converts from the water level value on the image space to the real water level on the real space using calibration table. The detected water level is sent to the host computer with current image. To evaluate the proposed algorithm, we use test images from various situations.

Keywords: accumulated histogram, water level detection, band pass filter.

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Authors: Sungkuk Chun, Kwangjin Hong, Keechul Jung

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In this paper, we propose an improved 3D star skeleton technique, which is a suitable skeletonization for human posture representation and reflects the 3D information of human posture. Moreover, the proposed technique is simple and then can be performed in real-time. The existing skeleton construction techniques, such as distance transformation, Voronoi diagram, and thinning, focus on the precision of skeleton information. Therefore, those techniques are not applicable to real-time posture recognition since they are computationally expensive and highly susceptible to noise of boundary. Although a 2D star skeleton was proposed to complement these problems, it also has some limitations to describe the 3D information of the posture. To represent human posture effectively, the constructed skeleton should consider the 3D information of posture. The proposed 3D star skeleton contains 3D data of human, and focuses on human action and posture recognition. Our 3D star skeleton uses the 8 projection maps which have 2D silhouette information and depth data of human surface. And the extremal points can be extracted as the features of 3D star skeleton, without searching whole boundary of object. Therefore, on execution time, our 3D star skeleton is faster than the “greedy" 3D star skeleton using the whole boundary points on the surface. Moreover, our method can offer more accurate skeleton of posture than the existing star skeleton since the 3D data for the object is concerned. Additionally, we make a codebook, a collection of representative 3D star skeletons about 7 postures, to recognize what posture of constructed skeleton is.

Keywords: computer vision, gesture recognition, skeletonization, human posture representation.

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Authors: Gaurav Bhanjana, Ganga Ram Chaudhary, Sandeep Kumar, Neeraj Dilbaghi

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Main sources of endocrine disrupting compounds in the ecosystem are hormones, pesticides, phthalates, flame retardants, dioxins, personal-care products, coplanar polychlorinated biphenyls (PCBs), bisphenol A, and parabens. These endocrine disrupting compounds are responsible for learning disabilities, brain development problems, deformations of the body, cancer, reproductive abnormalities in females and decreased sperm count in human males. Although discharge of these chemical compounds into the environment cannot be stopped, yet their amount can be retarded through proper evaluation and detection techniques. The available techniques for determination of these endocrine disrupting compounds mainly include high performance liquid chromatography (HPLC), mass spectroscopy (MS) and gas chromatography-mass spectrometry (GC–MS). These techniques are accurate and reliable but have certain limitations like need of skilled personnel, time consuming, interference and requirement of pretreatment steps. Moreover, these techniques are laboratory bound and sample is required in large amount for analysis. In view of above facts, new methods for detection of endocrine disrupting compounds should be devised that promise high specificity, ultra sensitivity, cost effective, efficient and easy-to-operate procedure. Nowadays, electrochemical sensors/biosensors modified with nanomaterials are gaining high attention among researchers. Bioelement present in this system makes the developed sensors selective towards analyte of interest. Nanomaterials provide large surface area, high electron communication feature, enhanced catalytic activity and possibilities of chemical modifications. In most of the cases, nanomaterials also serve as an electron mediator or electrocatalyst for some analytes.

Keywords: Sensors, endocrine disruptors, nanoparticles, electrochemical, microscopy.

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Authors: Kaznah Alshammari, Thomas Beach, Yacine Rezgui

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Technological advances in the construction sector are helping to make smart cities a reality by means of Cyber-Physical Systems (CPS). CPS integrate information and the physical world through the use of Information Communication Technologies (ICT). An increasingly common goal in the built environment is to integrate Building Information Models (BIM) with Internet of Things (IoT) and sensor technologies using CPS. Future advances could see the adoption of digital twins, creating new opportunities for CPS using monitoring, simulation and optimisation technologies. However, researchers often fail to fully consider the security implications. To date, it is not widely possible to assimilate BIM data and cybersecurity concepts and, therefore, security has thus far been overlooked. This paper reviews the empirical literature concerning IoT applications in the built environment and discusses real-world applications of the IoT intended to enhance construction practices, people’s lives and bolster cybersecurity. Specifically, this research addresses two research questions: (a) How suitable are the current IoT and CPS security stacks to address the cybersecurity threats facing digital twins in the context of smart buildings and districts? and (b) What are the current obstacles to tackling cybersecurity threats to the built environment CPS? To answer these questions, this paper reviews the current state-of-the-art research concerning digital twins in the built environment, the IoT, BIM, urban cities and cybersecurity. The results of the findings of this study confirmed the importance of using digital twins in both IoT and BIM. Also, eight reference zones across Europe have gained special recognition for their contributions to the advancement of IoT science. Therefore, this paper evaluates the use of digital twins in CPS to arrive at recommendations for expanding BIM specifications to facilitate IoT compliance, bolster cybersecurity and integrate digital twin and city standards in the smart cities of the future.

Keywords: BIM, cybersecurity, digital twins, IoT, urban cities.

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Authors: Tsung-Chia Chen

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The orthogonal processes to shape the triangle steel plate into a equilateral vertical steel are examined by an incremental elasto-plastic finite-element method based on an updated Lagrangian formulation. The highly non-linear problems due to the geometric changes, the inelastic constitutive behavior and the boundary conditions varied with deformation are taken into account in an incremental manner. On the contact boundary, a modified Coulomb friction mode is specially considered. A weighting factor r-minimum is employed to limit the step size of loading increment to linear relation. In particular, selective reduced integration was adopted to formulate the stiffness matrix. The simulated geometries of verticality could clearly demonstrate the vertical processes until unloading. A series of experiments and simulations were performed to validate the formulation in the theory, leading to the development of the computer codes. The whole deformation history and the distribution of stress, strain and thickness during the forming process were obtained by carefully considering the moving boundary condition in the finite-element method. Therefore, this modeling can be used for judging whether a equilateral vertical steel can be shaped successfully. The present work may be expected to improve the understanding of the formation of the equilateral vertical steel.

Keywords: Elasto-plastic, finite element, orthogonal pressing process, vertical steel.

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Authors: R. F. B. Gonçalves, E. N. Iwama, J. A. F. F. Rocco, K. Iha

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Propellants based on Hydroxyl Terminated Polybutadiene/Ammonium Perchlorate (HTPB/AP) are the most commonly used in most of the rocket engines used by the Brazilian Armed Forces. This work aimed at the possibility of extending its useful life (currently in 10 years) by performing kinetic-chemical analyzes of its energetic material via Differential Scanning Calorimetry (DSC) and also performing computer simulation of aging process using the software Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). Thermal analysis via DSC was performed in triplicates and in three heating ratios (5 ºC, 10 ºC, and 15 ºC) of rocket motor with 11 years shelf-life, using the Arrhenius equation to obtain its activation energy, using Ozawa and Kissinger kinetic methods, allowing comparison with manufacturing period data (standard motor). In addition, the kinetic parameters of internal pressure of the combustion chamber in 08 rocket engines with 11 years of shelf-life were also acquired, for comparison purposes with the engine start-up data.

Keywords: Shelf-life, thermal analysis, Ozawa method, Kissinger method, LAMMPS software, thrust.

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Authors: Marcia T. Mitchell

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This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely Cµ programming. In this domain all the keywords and programming concepts are known and understood.

Keywords: Natural language understanding, computational linguistics, knowledge representation, linguistic theories.

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Authors: Norazah Mohd Suki, Norbayah Mohd Suki

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This research aims to examine the influence of mediating effect of corporate social responsibility on the relationship between consumer awareness of green marketing and purchase intentions in the retail setting. Data from 200 valid questionnaires was analyzed using the partial least squares (PLS) approach for the analysis of structural equation models with SmartPLS computer program version 2.0 as research data does not necessarily have a multivariate normal distribution and is less sensitive to sample size than other covariance approaches. PLS results revealed that corporate social responsibility partially mediated the link between consumer awareness of green marketing and purchase intentions of the product in the retail setting. Marketing managers should allocate a sufficient portion of their budget to appropriate corporate social responsibility activities by engaging in voluntary programs for positive return on investment leading to increased business profitability and long run business sustainability. The outcomes of the mediating effects of corporate social responsibility add a new impetus to the growing literature and preceding discoveries on consumer green marketing awareness, which is inadequately researched in the Malaysian setting. Direction for future research is also presented.

Keywords: Green marketing awareness, corporate social responsibility, partial least squares, purchase intention.

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Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

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Background modeling and subtraction in video analysis has been widely used as an effective method for moving objects detection in many computer vision applications. Recently, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are the most frequently occurred problems in the practical situation. This paper presents a favorable two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean value of each RGB color channel. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the output of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate very competitive performance compared to previous models.

Keywords: Background subtraction, codebook model, local binary pattern, dynamic background, illumination changes.

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Authors: L. Grinis

Abstract:

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: C. Ardil

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The COVID-19 pandemic has revealed the complex and multifaceted relationship between societal structures and public health, emphasizing the need for a holistic approach to understanding pandemic responses. This study utilizes a clinical sociological perspective to analyze the social impacts of pandemics, with a particular focus on how social determinants such as income, education, race, and geographical location influence vulnerability and resilience. It explores the critical role of risk perception, communication strategies, and community dynamics in shaping public adherence to precautionary measures like mask-wearing, social distancing, and vaccination. By examining the ways in which social norms, structural inequalities, and trust in institutions affect public behavior, this study provides insights into the challenges of managing health crises in diverse communities. Comparative case studies and policy analysis are employed to highlight the variations in pandemic responses across different countries and regions, illustrating the importance of coordinated strategies and community-based interventions. The findings underscore that effective pandemic response requires addressing underlying social inequities, fostering community cohesion, and ensuring equitable access to healthcare and information. This study contributes to a deeper understanding of the broader societal implications of pandemics and offers recommendations for building more resilient, inclusive public health systems capable of mitigating the impact of future global health emergencies.

Keywords: Behavioral medicine, clinical sociology, community health, COVID-19, COVID-19 pandemic, epidemiology, infectious diseases, pandemics, precautions, psychology, public health, risks, social determinants, social dynamics, social psychiatry, social psychology, socioeconomic status, structural functionalism

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Authors: Guillermo Romero-Jiménez, Luis A. Jiménez-Fraustro, Mayolo Salinas-Camacho, Heriberto Avalos-Valenzuela

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A geothermal power plant multiple simulator for operators training is presented. The simulator is designed to be installed in a wireless local area network and has a capacity to train one to six operators simultaneously, each one with an independent simulation session. The sessions must be supervised only by one instructor. The main parts of this multiple simulator are: instructor and operator-s stations. On the instructor station, the instructor controls the simulation sessions, establishes training exercises and supervises each power plant operator in individual way. This station is hosted in a Main Personal Computer (NS) and its main functions are: to set initial conditions, snapshots, malfunctions or faults, monitoring trends, and process and soft-panel diagrams. On the other hand the operators carry out their actions over the power plant simulated on the operator-s stations; each one is also hosted in a PC. The main software of instructor and operator-s stations are executed on the same NS and displayed in PCs through graphical Interactive Process Diagrams (IDP). The geothermal multiple simulator has been installed in the Geothermal Simulation Training Center (GSTC) of the Comisi├│n Federal de Electricidad, (Federal Commission of Electricity, CFE), Mexico, and is being utilized as a part of the training courses for geothermal power plant operators.

Keywords: Geothermal power plant, multiple simulator, training operator.

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Authors: Hikmat A. M. Abd-El-Jaber, Tengku M. T. Sembok

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The information on the Web increases tremendously. A number of search engines have been developed for searching Web information and retrieving relevant documents that satisfy the inquirers needs. Search engines provide inquirers irrelevant documents among search results, since the search is text-based rather than semantic-based. Information retrieval research area has presented a number of approaches and methodologies such as profiling, feedback, query modification, human-computer interaction, etc for improving search results. Moreover, information retrieval has employed artificial intelligence techniques and strategies such as machine learning heuristics, tuning mechanisms, user and system vocabularies, logical theory, etc for capturing user's preferences and using them for guiding the search based on the semantic analysis rather than syntactic analysis. Although a valuable improvement has been recorded on search results, the survey has shown that still search engines users are not really satisfied with their search results. Using ontologies for semantic-based searching is likely the key solution. Adopting profiling approach and using ontology base characteristics, this work proposes a strategy for finding the exact meaning of the query terms in order to retrieve relevant information according to user needs. The evaluation of conducted experiments has shown the effectiveness of the suggested methodology and conclusion is presented.

Keywords: information retrieval, user profiles, semantic Web, ontology, search engine.

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Authors: N. I. Bazid, I. N. Umar

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Due to the advancement of Internet technology, online learning is widely used in higher education institutions. Online learning offers several means of communication, including online forum. Through online forum, students and instructors are able to discuss and share their knowledge and expertise without having a need to attend the face-to-face, ordinary classroom session. The purposes of this study are to analyze the students’ levels of participation and critical thinking, types of action and factors influencing their participation in online forum. A total of 41 postgraduate students undertaking a course in educational technology from a public university in Malaysia were involved in this study. In this course, the students participated in a weekly online forum as part of the course requirement. Based on the log data file extracted from the online forum, the students’ type of actions (view, add, update, delete posts) and their levels of participation (passive, moderate or active) were identified. In addition, the messages posted in the forum were analyzed to gauge their level of critical thinking. Meanwhile, the factors that might influence their online forum participation were measured using a 24-items questionnaire. Based on the log data, a total of 105 posts were sent by the participants. In addition, the findings show that (i) majority of the students are moderate participants, with an average of two to three posts per person, (ii) viewing posts are the most frequent type of action (85.1%), and followed by adding post (9.7%). Furthermore, based on the posts they made, the most frequent type of critical thinking observed was justification (50 input or 19.0%), followed by linking ideas and interpretation (47 input or 18%), and novelty (38 input or 14.4%). The findings indicate that online forum allows for social interaction and can be used to measure the students’ critical thinking skills. In order to achieve this, monitoring students’ activities in the online forum is recommended.

Keywords: Critical thinking, learning management system, level of online participation, online forum.

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Authors: Sunil Patel, Pallab Maji

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To study the effect of adversarial attack environment must be controlled. Autonomous driving includes mainly 5 phases sense, perceive, map, plan, and drive. Autonomous vehicles sense their surrounding with the help of different sensors like cameras, radars, and lidars. Deep learning techniques are considered Blackbox and found to be vulnerable to adversarial attacks. In this research, we study the effect of the various known adversarial attacks with the help of the Unreal Engine-based, high-fidelity, real-time raytraced simulated environment. The goal of this experiment is to find out if adversarial attacks work in moving vehicles and if an unknown network may be targeted. We discovered that the existing Blackbox and Whitebox attacks have varying effects on different traffic signs. We observed that attacks that impair detection in static scenarios do not have the same effect on moving vehicles. It was found that some adversarial attacks with hardly noticeable perturbations entirely blocked the recognition of certain traffic signs. We observed that the daylight condition has a substantial impact on the model's performance by simulating the interplay of light on traffic signs. Our findings have been found to closely resemble outcomes encountered in the real world.

Keywords: Adversarial attack simulation, computer simulation, ray-traced environment, realistic simulation, unreal engine.

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Authors: Jehad Al Dallal

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Program slicing is the task of finding all statements in a program that directly or indirectly influence the value of a variable occurrence. The set of statements that can affect the value of a variable at some point in a program is called a program slice. In several software engineering applications, such as program debugging and measuring program cohesion and parallelism, several slices are computed at different program points. In this paper, algorithms are introduced to compute all backward and forward static slices of a computer program by traversing the program representation graph once. The program representation graph used in this paper is called Program Dependence Graph (PDG). We have conducted an experimental comparison study using 25 software modules to show the effectiveness of the introduced algorithm for computing all backward static slices over single-point slicing approaches in computing the parallelism and functional cohesion of program modules. The effectiveness of the algorithm is measured in terms of time execution and number of traversed PDG edges. The comparison study results indicate that using the introduced algorithm considerably saves the slicing time and effort required to measure module parallelism and functional cohesion.

Keywords: Backward slicing, cohesion measure, forward slicing, parallelism measure, program dependence graph, program slicing, static slicing.

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Authors: Yao-Hong Tsai

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Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: Unmanned aerial vehicle, object tracking, deep learning, collision avoidance.

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Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

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At present actual tourism indicators cannot be calculated in Georgia, making it impossible to perform their quantitative analysis. Therefore, the study conducted by us is highly important from a theoretical as well as practical standpoint. The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors and to calculate statistical attractiveness indices of the tourism potential of Georgia. During the research, the method involving random and proportional selection has been applied. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from major Georgian airports, and a representative population of foreign visitors and a rule of selection of respondents were determined. The results show a trend of growth in tourist numbers and the share of tourists from post-soviet countries are constantly increasing. The level of satisfaction with tourist facilities and quality of service has improved, but still we have a problem of disparity between the service quality and the prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher. Attractiveness of popular cities of Georgia has increased by 43%.

Keywords: Tourist, expenses, indexes, statistics, analysis.

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: Intelligent transportation systems, object detection, video processing, road traffic, vehicle counting, vehicle classification.

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Authors: Maha ALjohani, James Blustein

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Communicating users' needs, goals and problems help designers and developers overcome challenges faced by end users. Personas are used to represent end users’ needs. In our research, creating personas allowed the following questions to be answered: Who are the potential user groups? What do they want to achieve by using the service? What are the problems that users face? What should the service provide to them? To develop realistic personas, we conducted a focus group discussion with undergraduate and graduate students and also interviewed a university librarian. The personas were created to help evaluating the Institutional Repository that is based on the DSpace system. The profiles helped to communicate users' needs, abilities, tasks, and problems, and the task scenarios used in the heuristic evaluation were based on these personas. Four personas resulted of a focus group discussion with undergraduate and graduate students and from interviewing a university librarian. We then used these personas to create focused task-scenarios for a heuristic evaluation on the system interface to ensure that it met users' needs, goals, problems and desires. In this paper, we present the process that we used to create the personas that led to devise the task scenarios used in the heuristic evaluation as a follow up study of the DSpace university repository.

Keywords: Heuristic Evaluation, Institutional Repositories, User Experience, Human Computer Interaction, User Profiles, Personas, Task Scenarios, Heuristics.

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

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

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

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Authors: Salama Meghriche, Amer Draa, Mohammed Boulemden

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Heart failure is the most common reason of death nowadays, but if the medical help is given directly, the patient-s life may be saved in many cases. Numerous heart diseases can be detected by means of analyzing electrocardiograms (ECG). Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decision-making process, from classification to diagnostic procedures. This work concentrates on a review followed by a novel method. The purpose of the review is to assess the evidence of healthcare benefits involving the application of artificial neural networks to the clinical functions of diagnosis, prognosis and survival analysis, in ECG signals. The developed method is based on a compound neural network (CNN), to classify ECGs as normal or carrying an AtrioVentricular heart Block (AVB). This method uses three different feed forward multilayer neural networks. A single output unit encodes the probability of AVB occurrences. A value between 0 and 0.1 is the desired output for a normal ECG; a value between 0.1 and 1 would infer an occurrence of an AVB. The results show that this compound network has a good performance in detecting AVBs, with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy value is 87.9%.

Keywords: Artificial neural networks, Electrocardiogram(ECG), Feed forward multilayer neural network, Medical diagnosis, Pattern recognitionm, Signal processing.

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Authors: A. Galashev

Abstract:

Absorption spectra of infra-red (IR) radiation of the disperse water medium absorbing the most important greenhouse gases: CO2 , N2O , CH4 , C2H2 , C2H6 have been calculated by the molecular dynamics method. Loss of the absorbing ability at the formation of clusters due to a reduction of the number of centers interacting with IR radiation, results in an anti-greenhouse effect. Absorption of O3 molecules by the (H2O)50 cluster is investigated at its interaction with Cl- ions. The splitting of ozone molecule on atoms near to cluster surface was observed. Interaction of water cluster with Cl- ions causes the increase of integrated intensity of emission spectra of IR radiation, and also essential reduction of the similar characteristic of Raman spectrum. Relative integrated intensity of absorption of IR radiation for small water clusters was designed. Dependences of the quantity of weight on altitude for vapor of monomers, clusters, droplets, crystals and mass of all moisture were determined. The anti-greenhouse effect of clusters was defined as the difference of increases of average global temperature of the Earth, caused by absorption of IR radiation by free water molecules forming clusters, and absorption of clusters themselves. The greenhouse effect caused by clusters makes 0.53 K, and the antigreenhouse one is equal to 1.14 K. The increase of concentration of CO2 in the atmosphere does not always correlate with the amplification of greenhouse effect.

Keywords: Greenhouse gases, infrared absorption and Raman spectra, molecular dynamics method, water clusters.

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Authors: Haitao Yang, Zhenjiang Ruan, Fei Xu, Lanting Xia

Abstract:

Industry data centers often need to sync data changes reliably and instantly from a large-scale of heterogeneous autonomous relational databases accessed via the not-so-reliable Internet, for which a practical generic sync middleware of low maintenance and operation costs is most wanted. To this demand, this paper presented a generic sync middleware system (GSMS), which has been developed, applied and optimized since 2006, holding the principles or advantages that it must be SyncML-compliant and transparent to data application layer logic without referring to implementation details of databases synced, does not rely on host computer operating systems deployed, and its construction is light weighted and hence of low cost. Regarding these hard commitments of developing GSMS, in this paper we stressed the significant optimization breakthrough of GSMS sync delay being well below a fraction of millisecond per record sync. A series of ultimate tests with GSMS sync performance were conducted for a persuasive example, in which the source relational database underwent a broad range of write loads (from one thousand to one million intensive writes within a few minutes). All these tests showed that the performance of GSMS is competent and smooth even under ultimate write loads.

Keywords: Heterogeneous massive data, instantly sync intensive writes, Internet generic middleware design, optimization.

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Authors: Zarita Zainuddin, Kumatha Thinakaran, Mohammed Shuaib

Abstract:

In today-s modern world, the number of vehicles is increasing on the road. This causes more people to choose walking instead of traveling using vehicles. Thus, proper planning of pedestrians- paths is important to ensure the safety of pedestrians in a walking area. Crowd dynamics study the pedestrians- behavior and modeling pedestrians- movement to ensure safety in their walking paths. To date, many models have been designed to ease pedestrians- movement. The Social Force Model is widely used among researchers as it is simpler and provides better simulation results. We will discuss the problem regarding the ritual of circumambulating the Ka-aba (Tawaf) where the entrances to this area are usually congested which worsens during the Hajj season. We will use the computer simulation model SimWalk which is based on the Social Force Model to simulate the movement of pilgrims in the Tawaf area. We will first discuss the effect of uni and bi-directional flows at the gates. We will then restrict certain gates to the area as the entrances only and others as exits only. From the simulations, we will study the effect of the distance of other entrances from the beginning line and their effects on the duration of pilgrims circumambulate Ka-aba. We will distribute the pilgrims at the different entrances evenly so that the congestion at the entrances can be reduced. We would also discuss the various locations and designs of barriers at the exits and its effect on the time taken for the pilgrims to exit the Tawaf area.

Keywords: circumambulation, Ka'aba, pedestrian flow, SFM, Tawaf , entrance, exit

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Authors: Mustafa Qaseem Hielat, Ahmad Mohammad Al-Shabatat

Abstract:

Jordan exerts many efforts to nurture their academically gifted students in special schools since 2001. During the past nine years of launching these schools, their learning and excellence environments were believed to be distinguished compared to public schools. This study investigated the environments of gifted students compared with other non-gifted, using a survey instrument that measures the dimensions of family, peers, teachers, school- support, society, and resources –dimensions rooted deeply in supporting gifted education, learning, and achievement. A total number of 109 were selected from excellence schools for academically gifted students, and 119 non-gifted students were selected from public schools. Around 8.3% of the non-gifted students reported that they “Never" received any support from their surrounding environments, 14.9% reported “Seldom" support, 23.7% reported “ Often" support, 26.0% reported “Frequent" support, and 32.8% reported “Very frequent" support. Where the gifted students reported more “Never" support than the non-gifted did with 11.3%, “Seldom" support with 15.4%, “Often" support with 26.6%, “Frequent" support with 29.0%, and reported “Very frequent" support less than the non-gifted students with 23.6%. Unexpectedly, statistical differences were found between the two groups favoring non-gifted students in perception of their surrounding environments in specific dimensions, namely, school- support, teachers, and society. No statistical differences were found in the other dimensions of the survey, namely, family, peers, and resources. As the differences were found in teachers, school- support, and society, the nurturing environments for the excellence schools need to be revised to adopt more creative teaching styles, rich school atmosphere and infrastructures, interactive guiding for the students and their parents, promoting for the excellence environments, and re-build successful identification models. Thus, families, schools, and society should increase their cooperation, communication, and awareness of the gifted supportive environments. However, more studies to investigate other aspects of promoting academic giftedness and excellence are recommended.

Keywords: Academic giftedness, Supportive environment, Excellence schools, Gifted grouping, Gifted nurturing.

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Authors: Hadi Firouzi, Majid Nili Ahmadabadi, Babak N. Araabi

Abstract:

Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.

Keywords: Concept learning, probabilistic decision making, reinforcement learning.

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Authors: R.S.Sabeenian, V.Palanisamy

Abstract:

Texture classification is a trendy and a catchy technology in the field of texture analysis. Textures, the repeated patterns, have different frequency components along different orientations. Our work is based on Texture Classification and its applications. It finds its applications in various fields like Medical Image Classification, Computer Vision, Remote Sensing, Agricultural Field, and Textile Industry. Weed control has a major effect on agriculture. A large amount of herbicide has been used for controlling weeds in agriculture fields, lawns, golf courses, sport fields, etc. Random spraying of herbicides does not meet the exact requirement of the field. Certain areas in field have more weed patches than estimated. So, we need a visual system that can discriminate weeds from the field image which will reduce or even eliminate the amount of herbicide used. This would allow farmers to not use any herbicides or only apply them where they are needed. A machine vision precision automated weed control system could reduce the usage of chemicals in crop fields. In this paper, an intelligent system for automatic weeding strategy Multi Resolution Combined Statistical & spatial Frequency is used to discriminate the weeds from the crops and to classify them as narrow, little and broad weeds.

Keywords: crop weed discrimination, MRCSF, MRFM, Weeddetection, Spatial Frequency.

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