Search results for: Machine Tool

Authors: Mohammad Shahid Jamil, Mohamed Chabi

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In this study, students’ learning has been investigated and satisfaction in one of the course offered at Qatar University Foundation Program. Innovative teaching has been implied methodology that emphasizes on enhancing students’ thinking skills, decision making, and problem solving skills. Some interesting results were found which could be used to further improvement of the teaching methodology. In Fall 2012 in Foundation Program Math department at Qatar University has started implementing new ways of teaching Math by introducing MyMathLab (MML) as an innovative interactive tool in addition of the use Blackboard to support standard teaching such as Discussion board in Virtual class to engage students outside of classroom and to enhance independent, active learning that promote students’ critical thinking skills, decision making, and problem solving skills through the learning process.

Keywords: Blackboard, MyMathLab, study plan, discussion board, critical thinking, active and independent learning, problem solving.

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: Natural language processing, end user development; natural language interfaces, human computer interaction, data recognition, dialog systems, spreadsheet.

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Authors: Ahmad Javid Habib, Tetsuo Kidokoro

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There is an increasing demand for developing urban land to provide better living conditions for all citizens in Afghanistan. Most of the development will involve the acquisition of land. And the current land acquisition method practiced by central government is expropriation, which is a cash-based transaction method that imposes heavy fiscal burden on local municipalities and central government, and it does not protect ownership rights and social equity of landowners besides it relocates the urban poor to remote areas with limited access to jobs and public services. The questionnaire analysis, backed by observations of different case studies in countries where land readjustment is used as a collaborative land development tool indicates that the method plays a key role in valuing landowners’ rights, giving other community members and stakeholders the opportunity to collaboratively implement urban development projects. The practice of the method is reducing the heavy fiscal burden on the local and central governments and is a better option to deal with the current development challenges in Afghanistan.

Keywords: Collaboration, land readjustment, master plan, expropriation.

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Authors: Robert S. Giachetti, Emanuele Grossi

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Loosening of bolted joints in rotating machines can adversely affect their performance, cause mechanical damage, and lead to injuries. In this paper, two potential loosening phenomena in rotating applications are discussed. First, ‘precession,’ is governed by thread/nut contact forces, while the second is based on inertial effects of the fastened assembly. These mechanisms are reviewed within the context of historical usage of left-handed fasteners in rotating machines which appears absent in the literature and common machine design texts. Historically, to prevent loosening of wheel nuts, vehicle manufacturers have used right-handed and left-handed threads on different sides of the vehicle, but most modern vehicles have abandoned this custom and only use right-handed, tapered lug nuts on all sides of the vehicle. Other classical machines such as the bicycle continue to use different handed threads on each side while other machines such as, bench grinders, circular saws and brush cutters still use left-handed threads to fasten rotating components. Despite the continued use of left-handed fasteners, the rationale and analysis of left-handed threads to mitigate self-loosening of fasteners in rotating applications is not commonly, if at all, discussed in the literature or design textbooks. Without scientific literature to support these design selections, these implementations may be the result of experimental findings or aged institutional knowledge. Based on a review of rotating applications, historical documents and mechanical design references, a formal study of the paradoxical nature of left-handed threads in various applications is merited.

Keywords: Rotating machinery, self-loosening fasteners, wheel fastening, vibration loosening.

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Authors: Phatthanan Chaiyabut

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The purposes of this research were to identify the perception of customers towards Krung Thai Bank’s image and to understand the customer attitude towards Krung Thai Bank’s image in Bangkok, Thailand. This research utilized quantitative approach and used questionnaire as data collection tool. A sample size of 420 respondents was selected by simple random sampling. The findings revealed that the majority of respondents received information, news, and feeds concerning the bank through televisions the most. This information channel had significantly influenced on the customers and their decisions to utilize the bank’s products and services.

From the information concerning the attitudes towards overall image of the bank, it was found that the majority respondents rated the bank’s image at the good level. The top three average attitudes included the bank’s images in supports government's monetary policies, being renowned and stable, and contributing in economical amendments and developments, with the mean average of 4.01, 3.96 and 3.81 respectively. The attitudes toward the images included a business leader in banking, marketing, and competitions. Offering prompt services, and provided appropriate servicing time were rated moderate with the attitudes of 3.36 and 3.30 respectively.

Keywords: Attitude, Image, Krung Thai bank, Perception.

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Authors: Bundit Pungnirund

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The objective of this research was to study the influence of marketing mix on customers purchasing behavior. A total of 397 respondents were collected from customers who were the patronages of the Chatuchak Plaza market. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. Data were analyzed by using Statistical Package for the Social Sciences. The findings revealed that the majority of respondents were male with the age between 25-34 years old, hold undergraduate degree, married and stay together. The average income of respondents was between 10,001-20,000 baht. In terms of occupation, the majority worked for private companies. The research analysis disclosed that there were three variables of marketing mix which included price (X2), place (X3), and product (X1) which had an influence on the frequency of customer purchasing. These three variables can predict a purchase about 30 percent of the time by using the equation; Y1 = 6.851 + .921(X2) + .949(X3) + .591(X1). It also found that in terms of marketing mixed, there were two variables had an influence on the amount of customer purchasing which were physical characteristic (X6), and the process (X7). These two variables are 17 percent predictive of a purchasing by using the equation: Y2 = 2276.88 + 2980.97(X6) + 2188.09(X7).

Keywords: Influences, Marketing Mixed, Purchasing Behavior.

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Authors: Ágnes Vathy-Fogarassy, Balázs Feil, János Abonyi

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Most of fuzzy clustering algorithms have some discrepancies, e.g. they are not able to detect clusters with convex shapes, the number of the clusters should be a priori known, they suffer from numerical problems, like sensitiveness to the initialization, etc. This paper studies the synergistic combination of the hierarchical and graph theoretic minimal spanning tree based clustering algorithm with the partitional Gath-Geva fuzzy clustering algorithm. The aim of this hybridization is to increase the robustness and consistency of the clustering results and to decrease the number of the heuristically defined parameters of these algorithms to decrease the influence of the user on the clustering results. For the analysis of the resulted fuzzy clusters a new fuzzy similarity measure based tool has been presented. The calculated similarities of the clusters can be used for the hierarchical clustering of the resulted fuzzy clusters, which information is useful for cluster merging and for the visualization of the clustering results. As the examples used for the illustration of the operation of the new algorithm will show, the proposed algorithm can detect clusters from data with arbitrary shape and does not suffer from the numerical problems of the classical Gath-Geva fuzzy clustering algorithm.

Keywords: Clustering, fuzzy clustering, minimal spanning tree, cluster validity, fuzzy similarity.

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Authors: Fei Ping Por, Soon Fook Fong

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The proposed Multimedia Pronunciation Learning Management System (MPLMS) in this study is a technology with profound potential for inducing improvement in pronunciation learning. The MPLMS optimizes the digitised phonetic symbols with the integration of text, sound and mouth movement video. The components are designed and developed in an online management system which turns the web to a dynamic user-centric collection of consistent and timely information for quality sustainable learning. The aim of this study is to design and develop the MPLMS which serves as an innovative tool to improve English pronunciation. This paper discusses the iterative methodology and the three-phase Alessi and Trollip model in the development of MPLMS. To align with the flexibility of the development of educational software, the iterative approach comprises plan, design, develop, evaluate and implement is followed. To ensure the instructional appropriateness of MPLMS, the instructional system design (ISD) model of Alessi and Trollip serves as a platform to guide the important instructional factors and process. It is expected that the results of future empirical research will support the efficacy of MPLMS and its place as the premier pronunciation learning system.

Keywords: Design, development, multimedia, pronunciation, learning management system

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Authors: Nikhil, Bestamin Özkaya, Ari Visa, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

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The performance of a sucrose-based H2 production in a completely stirred tank reactor (CSTR) was modeled by neural network back-propagation (BP) algorithm. The H2 production was monitored over a period of 450 days at 35±1 ºC. The proposed model predicts H2 production rates based on hydraulic retention time (HRT), recycle ratio, sucrose concentration and degradation, biomass concentrations, pH, alkalinity, oxidation-reduction potential (ORP), acids and alcohols concentrations. Artificial neural networks (ANNs) have an ability to capture non-linear information very efficiently. In this study, a predictive controller was proposed for management and operation of large scale H2-fermenting systems. The relevant control strategies can be activated by this method. BP based ANNs modeling results was very successful and an excellent match was obtained between the measured and the predicted rates. The efficient H2 production and system control can be provided by predictive control method combined with the robust BP based ANN modeling tool.

Keywords: Back-propagation, biohydrogen, bioprocessmodeling, neural networks.

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Authors: Angel Daniel Muñoz Guzmán

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E-learning is becoming more and more common every day. For online, hybrid or traditional face-to-face programs, there are some e-teaching platforms like Google classroom, Blackboard, Moodle and Canvas, and there are platforms for full e-learning like Coursera, edX or Udemy. These tools are changing the way students acquire knowledge at schools; however, in today’s changing world that is not enough. As students’ needs and skills change and become more complex, new tools will need to be added to keep them engaged and potentialize their learning. This is especially important in the current global situation that is changing everything: the Covid-19 pandemic. Due to Covid-19, education had to make an unexpected switch from face-to-face courses to digital courses. In this study, the students’ learning experience is analyzed by applying different e-tools and following the Tec21 Model and a flexible and digital model, both developed by the Tecnologico de Monterrey University. The evaluation of the students’ learning experience has been made by the quantitative PrEmo method of emotions. Findings suggest that the quantity of e-tools used during a course does not affect the students’ learning experience as much as how a teacher links every available tool and makes them work as one in order to keep the student engaged and motivated.

Keywords: Student, experience, e-learning, e-teaching, e-tools, technology, education.

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Authors: Lingaraju Dumpala, Laxmi Mohan Kumar Chintada, Devadas Deepu, Pravin Kumar Yadav

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Friction stir welding is the new-fangled and cutting-edge technique in welding applications; it is widely used in the fields of transportation, aerospace, defense, etc. For thriving significant welding joints and properties of friction stir welded components, it is essential to carry out this advanced process in a prescribed systematic procedure. At this moment, Underwater Friction Stir Welding (UFSW) Process is the field of interest to do research work. In the continuous assessment, the study of UFSW process is to comprehend problems occurred in the past and the structure through which the mechanical properties of the welded joints can be value-added and contributes to conclude results an acceptable and resourceful joint. A meticulous criticism is given on how to modify the experimental setup from NFSW to UFSW. It can discern the influence of tool materials, feeds, spindle angle, load, rotational speeds and mechanical properties. By expending the DEFORM-3D simulation software, the achieved outcomes are validated.

Keywords: Underwater friction stir welding, al alloys, mechanical properties, normal friction stir welding.

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Authors: Jaflah H. Al-Ammary

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The increasing recognition of the need for education to be closely aligned with team playing, project based learning and problem solving approaches has increase the interest in collaborative learning among university and college instructors. Using online collaboration learning in learning can enhance the outcome and achievement of students as well as improve their communication, critical thinking and personnel skills. The current research aims at examining the effect of OCL on the student's achievement at Kingdom of Bahrain. Numbers of objectives were set to achieve the aim of the research include: investigating the current situation regarding the collaborative learning and OCL at the Kingdom of Bahrain by identifying the advantages and effectiveness of OCL as a learning tool over traditional learning, examining the factors that affect OCL as well as examining the impact of OCL on the student's achievement. To achieve these objectives, quantitative method was adopted. Two hundred and thirty one questionnaires were distributed to students in different local and private universities at Kingdom of Bahrain. The findings of the research show that most of the students prefer to use FTFCL in learning and that OCL is already adopted in some universities especially in University of Bahrain. Moreover, the most factors affecting the adopted OCL are perceived readiness, and guidance and support.

Keywords: Collaborative learning, perceived readiness, student achievement.

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Authors: Santanu Santra, Utpal Roy

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Quantum-dot Cellular Automata (QCA) is one of the most substitute emerging nanotechnologies for electronic circuits, because of lower power consumption, higher speed and smaller size in comparison with CMOS technology. The basic devices, a Quantum-dot cell can be used to implement logic gates and wires. As it is the fundamental building block on nanotechnology circuits. By applying XOR gate the hardware requirements for a QCA circuit can be decrease and circuits can be simpler in terms of level, delay and cell count. This article present a modest approach for implementing novel optimized XOR gate, which can be applied to design many variants of complex QCA circuits. Proposed XOR gate is simple in structure and powerful in terms of implementing any digital circuits. In order to verify the functionality of the proposed design some complex implementation of parity generator and parity checker circuits are proposed and simulating by QCA Designer tool and compare with some most recent design. Simulation results and physical relations confirm its usefulness in implementing every digital circuit.

Keywords: Clock, CMOS technology, Logic gates, QCA Designer, Quantum-dot Cellular Automata (QCA).

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Authors: Brehme D’napoli Reis de Mesquita, Marcus Vin´ıcius de Souza Almeida, Caio Vin´ıcius Silva do Carmo

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Educational robotics has emerged as a pedagogical tool, utilizing technological artifacts to engage students’ curiosity and interest. It fosters active learning of STEM education competencies while also cultivating essential behavioral skills. Robotic competitions provide students with platforms to collaboratively devise diverse solutions to shared problems, fostering experience exchange, collaboration, and personal growth. Despite the prevalence of current robotic competitions, especially in Brazil, simulating real-world challenges like natural disasters, there is a notable absence of industry-related tasks. This article presents an educational robotics initiative centered around material transportation within smart manufacturing using automated guided vehicles. The proposed robotics challenge was executed in a competition held in Ac¸ailˆandia city, Maranh˜ao, Brazil, yielding satisfactory results and inspiring teams to develop time-limited solution strategies.

Keywords: Educational robotics, STEM education, robotic competitions, material transportation, smart manufacturing.

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: Visual search, deep learning, convolutional neural network, machine learning.

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Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

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During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: Cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation.

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Authors: Bindu Sankar, Jaideep Chakraborty, Rashmi Nawlakha, A. Venkatesan, S. Raghupathy, T. Jayanthi, S.A.V. Satya Murty

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Component handling system is one of the important sub systems of Prototype Fast Breeder Reactor (PFBR) used for fuel handling. Core handling system is again a sub system of component handling system. Core handling system consists of in-vessel and ex-vessel subassembly handling. In-vessel core handling involves transfer arm, large rotatable plug and small rotatable plug operations. Modeling and simulation of in-vessel core handling is a part of development of Prototype Fast Breeder Reactor Operator Training Simulator. This paper deals with simulation and modeling of operations of transfer arm, large rotatable plug and small rotatable plug needed for in-vessel core handling. Process modeling was developed in house using platform independent Cµ code with OpenGL (Open Graphics Library). The control logic models and virtual panel were modeled using simulation tool.

Keywords: Animation, Core Handling System, Prototype Fast Breeder Reactor, Simulator

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Authors: Paua Ketan, Bhagate Rajkumar, Adiga Ganesh, M. Kiran

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Low gear noise is an important sound quality feature in modern passenger cars. Annoying gear noise from the gearbox is influenced by the gear design, gearbox shaft layout, manufacturing deviations in the components, assembly errors and the mounting arrangement of the complete gearbox. Geometrical deviations in the form of profile and lead errors are often present on the flanks of the inspected gears. Ghost frequencies of a gear are very challenging to identify in standard gear measurement and analysis process due to small wavelengths involved. In this paper, gear whine noise occurring at non-integral multiples of gear mesh frequency of passenger car gearbox is investigated and the root cause is identified using the displacement deviation analysis (DDA) method. DDA method is applied to identify ghost frequency excitations on the flanks of gears arising out of generation grinding. Frequency identified through DDA correlated with the frequency of vibration and noise on the end-of-line machine as well as vehicle level measurements. With the application of DDA method along with standard lead profile measurement, gears with ghost frequency geometry deviations were identified on the production line to eliminate defective parts and thereby eliminate ghost frequency noise from a vehicle. Further, displacement deviation analysis can be used in conjunction with the manufacturing process simulation to arrive at suitable countermeasures for arresting the ghost frequency.

Keywords: Displacement deviation analysis, gear whine, ghost frequency, sound quality.

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Authors: Syed Manzoor Qasim, Shuja Abbasi, Saleh Alshebeili, Bandar Almashary, Ateeq Ahmad Khan

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Higher-order Statistics (HOS), also known as cumulants, cross moments and their frequency domain counterparts, known as poly spectra have emerged as a powerful signal processing tool for the synthesis and analysis of signals and systems. Algorithms used for the computation of cross moments are computationally intensive and require high computational speed for real-time applications. For efficiency and high speed, it is often advantageous to realize computation intensive algorithms in hardware. A promising solution that combines high flexibility together with the speed of a traditional hardware is Field Programmable Gate Array (FPGA). In this paper, we present FPGA-based parallel architecture for the computation of third-order cross moments. The proposed design is coded in Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) and functionally verified by implementing it on Xilinx Spartan-3 XC3S2000FG900-4 FPGA. Implementation results are presented and it shows that the proposed design can operate at a maximum frequency of 86.618 MHz.

Keywords: Cross moments, Cumulants, FPGA, Hardware Implementation.

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Authors: Zaza Tabagari, Zaza Sanikidze, George Giorgobiani

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Abovepresented work deals with the new scope of application of information and communication technologies for the improvement of the election process in the biased environment. We are introducing a new concept of construction of the information-communication system for the election participant. It consists of four main components: Software, Physical Infrastructure, Structured Information and the Trained Stuff. The Structured Information is the bases of the whole system and is the collection of all possible events (irregularities among them) at the polling stations, which are structured in special templates, forms and integrated in mobile devices.The software represents a package of analytic modules, which operates with the dynamic database. The application of modern communication technologies facilities the immediate exchange of information and of relevant documents between the polling stations and the Server of the participant. No less important is the training of the staff for the proper functioning of the system. The e-training system with various modules should be applied in this respect. The presented methodology is primarily focused on the election processes in the countries of emerging democracies.It can be regarded as the tool for the monitoring of elections process by the political organization(s) and as one of the instruments to foster the spread of democracy in these countries.

Keywords: ICT, elections, structured information, dynamic databases, e-training.

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Authors: Jean François Chatelain, Imed Zaghbani, Joseph Monier

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The machining of Carbon Fiber Reinforced Plastics has come to constitute a significant challenge for many fields of industry. The resulting surface finish of machined parts is of primary concern for several reasons, including contact quality and impact on the assembly. Therefore, the characterization and prediction of roughness based on machining parameters are crucial for costeffective operations. In this study, a PCD tool comprised of two straight flutes was used to trim 32-ply carbon fiber laminates in a bid to analyze the effects of the feed rate and the cutting speed on the surface roughness. The results show that while the speed has but a slight impact on the surface finish, the feed rate for its part affects it strongly. A detailed study was also conducted on the effect of fiber orientation on surface roughness, for quasi-isotropic laminates used in aerospace. The resulting roughness profiles for the four-ply orientation lay-up were compared, and it was found that fiber angle is a critical parameter relating to surface roughness. One of the four orientations studied led to very poor surface finishes, and characteristic roughness profiles were identified and found to only relate to the ply orientations of multilayer carbon fiber laminates.

Keywords: Roughness, Detouring, Composites, Aerospace

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Authors: Atiqul Islam, Shamim Akhter, Tumnun E. Mursalin

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Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Keywords: Computer vision, image acquisition device, machine vision, multi-layer neural networks.

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Authors: Kitti Koonsanit, Chuleerat Jaruskulchai, Poonsak Miphokasap, Apisit Eiumnoh

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In the end of the day, meteorological data and environmental data becomes widely used such as plant varieties selection system. Variety plant selection for planted area is of almost importance for all crops, including varieties of sugarcane. Since sugarcane have many varieties. Variety plant non selection for planting may not be adapted to the climate or soil conditions for planted area. Poor growth, bloom drop, poor fruit, and low price are to be from varieties which were not recommended for those planted area. This paper presents plant varieties selection system for planted areas in Thailand from meteorological data and environmental data by the use of decision tree techniques. With this software developed as an environmental data analysis tool, it can analyze resulting easier and faster. Our software is a front end of WEKA that provides fundamental data mining functions such as classify, clustering, and analysis functions. It also supports pre-processing, analysis, and decision tree output with exporting result. After that, our software can export and display data result to Google maps API in order to display result and plot plant icons effectively.

Keywords: Plant varieties selection system, decision tree, expert recommendation.

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Authors: Shinpei Ogata, Yoshitaka Aoki, Hirotaka Okuda, Saeko Matsuura

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A key to success of high quality software development is to define valid and feasible requirements specification. We have proposed a method of model-driven requirements analysis using Unified Modeling Language (UML). The main feature of our method is to automatically generate a Web user interface mock-up from UML requirements analysis model so that we can confirm validity of input/output data for each page and page transition on the system by directly operating the mock-up. This paper proposes a support method to check the validity of a data life cycle by using a model checking tool “UPPAAL" focusing on CRUD (Create, Read, Update and Delete). Exhaustive checking improves the quality of requirements analysis model which are validated by the customers through automatically generated mock-up. The effectiveness of our method is discussed by a case study of requirements modeling of two small projects which are a library management system and a supportive sales system for text books in a university.

Keywords: CRUD, Model Checking, Model Driven Development, Requirements Analysis, Unified Modeling Language, UPPAAL.

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Authors: O. Boe, S-T. Kristiansen, R. Wold

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In this article we explore how computer assisted exercises may allow for bridging the traditional gap between theory and practice in professional education. To educate officers able to master the complexity of the battlefield the Norwegian Military Academy needs to develop a learning environment that allows for creating viable connections between the educational environment and the field of practice. In response to this challenge we explore the conditions necessary to make computer assisted training systems (CATS) a useful tool to create structural similarities between an educational context and the field of military practice. Although, CATS may facilitate work procedures close to real life situations, this case do demonstrate how professional competence also must build on viable learning theories and environments. This paper explores the conditions that allow for using simulators to facilitate professional competence from within an educational setting. We develop a generic didactic model that ascribes learning to participation in iterative cycles of action and reflection. The development of this model is motivated by the need to develop an interdisciplinary professional education rooted in the pattern of military practice.

Keywords: Development in higher education, experiential learning, professional education, simulation.

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: Communication signal, feature extraction, holder coefficient, improved cloud model.

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Authors: Nadira Kaimova

Abstract:

In this paper it was examined the influence of margin regulation on stock market volatility in EU 1993 – 2014. Regulating margin requirements or haircuts for securities financing transactions has for a long time been considered as a potential tool to limit the build-up of leverage and dampen volatility in financial markets. The margin requirement dictates how much investors can borrow against these securities. Margin can be an important part of investment. Using daily and monthly stock returns and there is no convincing evidence that EU Regulation margin requirements have served to dampen stock market volatility. In this paper was detected the expected negative relation between margin requirements and the amount of margin credit outstanding. Also, it confirmed that changes in margin requirements by the EU regulation have tended to follow than lead changes in market volatility. For the analysis have been used the modified Levene statistics to test whether the standard deviation of stock returns in the 25, 50 and 100 days preceding margin changes is the same as that in the succeeding 25, 50 and 100 days. The analysis started in May 1993 when it was first empowered to set the initial margin requirement and the last sample was in May 2014. To test whether margin requirements influence stock market volatility over the long term, the sample of stock returns was divided into 14 periods, according to the 14 changes in margin requirements.

Keywords: Levene statistic, Margin Regulation, Stock Market, Volatility.

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Authors: Jia-Rong Yeh, Tzu-Yu Lin, Jiann-Shing Shieh, Yun Chen

Abstract:

A mammal-s body can be seen as a blood vessel with complex tunnels. When heart pumps blood periodically, blood runs through blood vessels and rebounds from walls of blood vessels. Blood pressure signals can be measured with complex but periodic patterns. When an artery is clamped during a surgical operation, the spectrum of blood pressure signals will be different from that of normal situation. In this investigation, intestinal artery clamping operations were conducted to a pig for simulating the situation of intestinal blocking during a surgical operation. Similarity theory is a convenient and easy tool to prove that patterns of blood pressure signals of intestinal artery blocking and unblocking are surely different. And, the algorithm of Hilbert Huang Transform can be applied to extract the character parameters of blood pressure pattern. In conclusion, the patterns of blood pressure signals of two different situations, intestinal artery blocking and unblocking, can be distinguished by these character parameters defined in this paper.

Keywords: Blood pressure, spectrum, intestinal artery, similarity theory and Hilbert Huang Transform.

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Authors: Ishtiaq Ahmed, Muhammad Anjum Zia, Hafiz Muhammad Nasir Iqbal

Abstract:

The purpose of the present work was to study the production and process parameters optimization for the synthesis of cellulase from Trichoderma viride in solid state fermentation (SSF) using an agricultural wheat straw as substrates; as fungal conversion of lignocellulosic biomass for cellulase production is one among the major increasing demand for various biotechnological applications. An optimization of process parameters is a necessary step to get higher yield of product. Several kinetic parameters like pretreatment, extraction solvent, substrate concentration, initial moisture content, pH, incubation temperature and inoculum size were optimized for enhanced production of third most demanded industrially important cellulase. The maximum cellulase enzyme activity 398.10±2.43 μM/mL/min was achieved when proximally analyzed lignocellulosic substrate wheat straw inocubated at 2% HCl as pretreatment tool along with distilled water as extraction solvent, 3% substrate concentration 40% moisture content with optimum pH 5.5 at 45°C incubation temperature and 10% inoculum size.

Keywords: Cellulase, Lignocellulosic residue, Processoptimization, Proximal analysis, SSF, Trichoderma viride.

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Authors: S. Manzoor, A. Nadeem, M. Javed, ME. Babar

Abstract:

A major goal in animal genetics is to understand the role of common genetic variants in diseases susceptibility and production traits. Sahiwal cattle can be considered as a global animal genetic resource due to its relatively high milk producing ability, resistance against tropical diseases and heat tolerant. CYP11B1 gene provides instructions for making a mitochondrial enzyme called steroid 11-beta-hydroxylase. It catalyzes the 11deoxy-cortisol to cortisol and 11deoxycorticosterone to corticosterone in cattle. The bovine CYP11B1 gene is positioned on BTA14q12 comprises of eight introns and nine exons and protein is associated with mitochondrial epithelium. The present study was aimed to identify the single-nucleotide polymorphisms in CYP11B1 gene in Sahiwal cattle breed of Pakistan. Four polymorphic sites were identified in exon one of CYP11B1 gene through sequencing approach. Significant finding was the incidence of the C→T polymorphism in 5'-UTR, causing amino acid substitution from alanine to valine (A30V) in Sahiwal cattle breed. That Ala/Val polymorphism may serve as a powerful genetic tool for the development of DNA markers that can be used for the particular traits for different local cattle breeds.

Keywords: CYP11B1, single nucleotide polymorphism, sahiwal cattle, Pakistan.

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