Search results for: Data Structure Normalization

Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

Abstract:

The purpose of this research aims to discover the knowledge for analysis student motivation behavior on e-Learning based on Data Mining Techniques, in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The data mining techniques was applied in this research including association rules, classification techniques. The results showed that using data mining technique can indicate the important variables that influence the student motivation behavior on e-Learning.

Keywords: association rule mining, classification techniques, e- Learning, Moodle log Motivation Behavior

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Authors: Matthew D. Baffa

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Infrared thermography is a non-destructive test method used to estimate surface temperatures based on the amount of electromagnetic energy radiated by building envelope components. These surface temperatures are indicators of various qualitative building envelope deficiencies such as locations and extent of heat loss, thermal bridging, damaged or missing thermal insulation, air leakage, and moisture presence in roof, floor, and wall assemblies. Although infrared thermography is commonly used for qualitative deficiency detection in buildings, this study assesses its use as a quantitative method to estimate the overall thermal conductance value (U-value) of the exterior above-grade walls of a study home. The overall U-value of exterior above-grade walls in a home provides useful insight into the energy consumption and thermal comfort of a home. Three methodologies from the literature were employed to estimate the overall U-value by equating conductive heat loss through the exterior above-grade walls to the sum of convective and radiant heat losses of the walls. Outdoor infrared thermography field measurements of the exterior above-grade wall surface and reflective temperatures and emissivity values for various components of the exterior above-grade wall assemblies were carried out during winter months at the study home using a basic thermal imager device. The overall U-values estimated from each methodology from the literature using the recorded field measurements were compared to the nominal exterior above-grade wall overall U-value calculated from materials and dimensions detailed in architectural drawings of the study home. The nominal overall U-value was validated through calendarization and weather normalization of utility bills for the study home as well as various estimated heat loss quantities from a HOT2000 computer model of the study home and other methods. Under ideal environmental conditions, the estimated overall U-values deviated from the nominal overall U-value between ±2% to ±33%. This study suggests infrared thermography can estimate the overall U-value of exterior above-grade walls in low-rise residential homes with a fair amount of accuracy.

Keywords: Emissivity, heat loss, infrared thermography, thermal conductance.

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Authors: M. Yilmaz, I. Yilmaz, M. Uysal

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The Earth system generates different phenomena that are observable at the surface of the Earth such as mass deformations and displacements leading to plate tectonics, earthquakes, and volcanism. The dynamic processes associated with the interior, surface, and atmosphere of the Earth affect the three pillars of geodesy: shape of the Earth, its gravity field, and its rotation. Geodesy establishes a characteristic structure in order to define, monitor, and predict of the whole Earth system. The traditional and new instruments, observables, and techniques in geodesy are related to the gravity field. Therefore, the geodesy monitors the gravity field and its temporal variability in order to transform the geodetic observations made on the physical surface of the Earth into the geometrical surface in which positions are mathematically defined. In this paper, the main components of the gravity field modeling, (Free-air and Bouguer) gravity anomalies are calculated via recent global models (EGM2008, EIGEN6C4, and GECO) over a selected study area. The model-based gravity anomalies are compared with the corresponding terrestrial gravity data in terms of standard deviation (SD) and root mean square error (RMSE) for determining the best fit global model in the study area at a regional scale in Turkey. The least SD (13.63 mGal) and RMSE (15.71 mGal) were obtained by EGM2008 for the Free-air gravity anomaly residuals. For the Bouguer gravity anomaly residuals, EIGEN6C4 provides the least SD (8.05 mGal) and RMSE (8.12 mGal). The results indicated that EIGEN6C4 can be a useful tool for modeling the gravity field of the Earth over the study area.

Keywords: Free-air gravity anomaly, Bouguer gravity anomaly, global model, land gravity.

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Authors: Sajid Abbas, Joon Pyo Hong, Jung-Ryun Lee, Seungryong Cho

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Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

Keywords: Computed tomography, Computed laminography, Compressive sending, Low-dose.

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: Real-Time Spatial Big Data, Quality Of Service, Vertical partitioning, Horizontal partitioning, Matching algorithm, Hamming distance, Stream query.

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Authors: Parchami A., Fatahian Dehkordi RF.

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The aim of the present investigation was to compare sex differences in thyroid gland structure of rabbits. Five adult male and five adult female (3.1-3.5 kg body weight) New Zealand white rabbits were used in the experiment. Results showed that at light microscopic level, there was no sex difference in microscopic appearance of the thyroid glands. At electron microscopic level, however, the mitochondria and the microvilli of the follicular cells are more numerous and the Golgi complex is also more extensive in male rabbits in comparison to females. Results obtained from micrometric measurements showed that the volume density of the follicles is higher in males than in females, but the differences are not statistically significant .The volume density of epithelium and the height of follicular cells are significantly greater in males than in females and reverse is true about the volume density of interstitium (p<0.05). The volume density of colloid is also greater in females (66±6) than in males (60±7) but the differences are not statistically significant .It was concluded that sex has limited effects on histomorphometric properties of thyroid gland in rabbits.

Keywords: Rabbit, Thyroid Gland, Sex difference, Electron microscope

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Authors: Suleiman M. Elhamali, K. M. Etmimi, A. Usha

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The paper presents the results of microhardness and microstructure of low carbon steel surface melted using carbon dioxide laser with a wavelength of 10.6μm and a maximum output power of 2000W. The processing parameters such as the laser power, and the scanning rate were investigated in this study. After surface melting two distinct regions formed corresponding to the melted zone MZ, and the heat affected zone HAZ. The laser melted region displayed a cellular fine structures while the HAZ displayed martensite or bainite structure. At different processing parameters, the original microstructure of this steel (Ferrite+Pearlite) has been transformed to new phases of martensitic and bainitic structures. The fine structure and the high microhardness are evidence of the high cooling rates which follow the laser melting. The melting pool and the transformed microstructure in the laser surface melted region of carbon steel showed clear dependence on laser power and scanning rate.

Keywords: Carbon steel, laser surface melting, microstructure, microhardness.

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Authors: Cheng Fang Hsu, Shinn-Jong Lin

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This paper aims at a new challenge of customer satisfaction on mobile customer relationship management. In this paper presents a conceptualization of mCRM on its unique characteristics of customer satisfaction. Also, this paper develops an empirical framework in conception of customer satisfaction in mCRM. A single-case study is applied as the methodology. In order to gain an overall view of the empirical case, this paper accesses to invisible and important information of company in this investigation. Interview is the key data source form the main informants of the company through which the issues are identified and the proposed framework is built. It supports the development of customer satisfaction in mCRM; links this theoretical framework into practice; and provides the direction for future research. Therefore, this paper is very useful for the industries as it helps them to understand how customer satisfaction changes the mCRM structure and increase the business competitive advantage. Finally, this paper provides a contribution in practice by linking a theoretical framework in conception of customer satisfaction in mCRM for companies to a practical real case.

Keywords: Customer Satisfaction; mCRM; MobileCommunication.

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Authors: E. Danso-Boateng

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The effects of enzyme action and heat pretreatment on oil extraction yield from sunflower kernels were analysed using hexane extraction with Soxhlet, and aqueous extraction with incubator shaker. Ground kernels of raw and heat treated kernels, each with and without Viscozyme treatment were used. Microscopic images of the kernels were taken to analyse the visible effects of each treatment on the cotyledon cell structure of the kernels. Heat pretreated kernels before both extraction processes produced enhanced oil extraction yields than the control, with steam explosion the most efficient. In hexane extraction, applying a combination of steam explosion and Viscozyme treatments to the kernels before the extraction gave the maximum oil extractable in 1 hour; while for aqueous extraction, raw kernels treated with Viscozyme gave the highest oil extraction yield. Remarkable cotyledon cell disruption was evident in kernels treated with Viscozyme; whereas steam explosion and conventional heat treated kernels had similar effects.

Keywords: Enzyme-assisted aqueous and hexane extraction, heatpretreatment, sunflower cotyledon structure, sunflower oil extraction

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Authors: Alexandra Aslanidou

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The General Data Protection Regulation (GDPR), concerning the protection of natural persons within the European Union with regard to the processing of personal data and on the free movement of such data, became applicable in the European Union (EU) on 25 May 2018 and transformed the way personal data were being treated under the Data Protection Directive (DPD) regime, generating sweeping organizational changes to both public sector and business. A social practice that is considerably influenced in the way of its day-to-day operations is Human Resource (HR) management, for which the importance of GDPR cannot be underestimated. That is because HR processes personal data coming in all shapes and sizes from many different systems and sources. The significance of the proper functioning of an HR department, specifically in human-centered, service-oriented environments such as the education field, is decisive due to the fact that HR operations in schools, conducted effectively, determine the quality of the provided services and consequently have a considerable impact on the success of the educational system. The purpose of this paper is to analyze the decisive role that GDPR plays in HR departments that operate in schools and in order to practically evaluate the aftermath of the Regulation during the first months of its applicability; a comparative use cases analysis in five highly dynamic schools, across three EU Member States, was attempted.

Keywords: General data protection regulation, human resource management, educational system.

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Authors: Nevine M. Labib, Michael N. Malek

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Data Mining aims at discovering knowledge out of data and presenting it in a form that is easily comprehensible to humans. One of the useful applications in Egypt is the Cancer management, especially the management of Acute Lymphoblastic Leukemia or ALL, which is the most common type of cancer in children. This paper discusses the process of designing a prototype that can help in the management of childhood ALL, which has a great significance in the health care field. Besides, it has a social impact on decreasing the rate of infection in children in Egypt. It also provides valubale information about the distribution and segmentation of ALL in Egypt, which may be linked to the possible risk factors. Undirected Knowledge Discovery is used since, in the case of this research project, there is no target field as the data provided is mainly subjective. This is done in order to quantify the subjective variables. Therefore, the computer will be asked to identify significant patterns in the provided medical data about ALL. This may be achieved through collecting the data necessary for the system, determimng the data mining technique to be used for the system, and choosing the most suitable implementation tool for the domain. The research makes use of a data mining tool, Clementine, so as to apply Decision Trees technique. We feed it with data extracted from real-life cases taken from specialized Cancer Institutes. Relevant medical cases details such as patient medical history and diagnosis are analyzed, classified, and clustered in order to improve the disease management.

Keywords: Data Mining, Decision Trees, Knowledge Discovery, Leukemia.

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Authors: M. R. Vaezi, R. Ghasemi, A. Akramizadeh

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Frequency stability of microgrids under islanded operation attracts particular attention recently. A new cooperative frequency control strategy based on centralized multi-agent system (CMAS) is proposed in this study. Based on this strategy, agents sent data and furthermore each component has its own to center operating decisions (MGCC).After deciding on the information, they are returned. Frequency control strategies include primary and secondary frequency control and disposal of multi-stage load in which this study will also provide a method and algorithm for load shedding. This could also be a big problem for the performance of micro-grid in times of disaster. The simulation results show the promising performance of the proposed structure of the controller based on multi agent systems.

Keywords: Frequency Control, Islanded Micro-grid, Load shedding, Multi-agent System.

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Authors: Hyoung-Muk Lim, Won-Jun Choi, Jae-Seon Yoon, Hyoung-Kyu Song

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Space-time block code(STBC) has been studied to get full diversity and full rate in multiple input multiple output(MIMO) system. Achieving full rate is difficult in cooperative communications due to the each user consumes the time slots for transmitting information in cooperation phase. So combining MIMO systems with cooperative communications has been researched for full diversity and full rate. In orthogonal frequency division multiple access (OFDMA) system, it is an alternative way that each user shares their allocated subchannels instead of using the MIMO system to improve the transmission rate. In this paper, a Decode-and-forward (DF) based cooperative communication scheme is proposed. The proposed scheme has improved transmission rate and reliability in multi-path fading channel of the OFDMA up-link condition by modified STBC structure and subchannel sharing.

Keywords: cooperation, improved rate, OFDMA, STBC.

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Authors: Souâd Demigha

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Early detection of breast cancer is considered as a major public health issue. Breast cancer screening is not generalized to the entire population due to a lack of resources, staff and appropriate tools. Systematic screening can result in a volume of data which can not be managed by present computer architecture, either in terms of storage capabilities or in terms of exploitation tools. We propose in this paper to design and develop a data warehouse system in radiology-senology (DWRS). The aim of such a system is on one hand, to support this important volume of information providing from multiple sources of data and images and for the other hand, to help assist breast cancer screening in diagnosis, education and research.

Keywords: Breast cancer screening, data warehouse, diagnosis, education, research.

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Authors: Vishal Awasthi, Tanya Soni, Vigya Awasthi, Swati Singh, Shivali Verma

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There is a growing demand for a network that grants a high level of data security and confidentiality. For this reason, the semantic web was introduced, which allows data to be shared and reused across applications while safeguarding users privacy and user’s will grab back control of their data. The earlier Web 1.0 and Web 2.0 versions were built on client-server architecture, in  which there was the risk of data theft and unconsented sale of user data. A decentralized version, Known as Web 3.0, that is mostly built on blockchain technology was interjected to resolve these issues. The recent research focuses on blockchain technology, deals with privacy, security, transparency, and innovation of decentralized applications (DApps), e.g. a Twitter Clone, Whatsapp clone. In this paper the Twitter Alike built on the Ethereum blockchain will replace traditional techniques with improved latency, throughput, and data ownership. The central principle of this DApp is smart contract implemented using Solidity which is an object- oriented and highlevel language. Consequently, this will provide a better Quality Services, high data security, and integrity for both present and future internet technologies.

Keywords: Blockchain, DApps, Ethereum, Semantic Web, Smart Contract, Solidity.

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Authors: Faisal Aburub, Wael Hadi

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Data mining is the process of extracting useful or hidden information from a large database. Extracted information can be used to discover relationships among features, where data objects are grouped according to logical relationships; or to predict unseen objects to one of the predefined groups. In this paper, we aim to investigate four well-known data mining algorithms in order to predict groundwater areas in Jordan. These algorithms are Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbor (kNN) and Classification Based on Association Rule (CBA). The experimental results indicate that the SVMs algorithm outperformed other algorithms in terms of classification accuracy, precision and F1 evaluation measures using the datasets of groundwater areas that were collected from Jordanian Ministry of Water and Irrigation.

Keywords: Classification, data mining, evaluation measures, groundwater.

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Authors: M. Rahmati, S.M. Mirzababaei

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With the advance of information technology in the new era the applications of Internet to access data resources has steadily increased and huge amount of data have become accessible in various forms. Obviously, the network providers and agencies, look after to prevent electronic attacks that may be harmful or may be related to terrorist applications. Thus, these have facilitated the authorities to under take a variety of methods to protect the special regions from harmful data. One of the most important approaches is to use firewall in the network facilities. The main objectives of firewalls are to stop the transfer of suspicious packets in several ways. However because of its blind packet stopping, high process power requirements and expensive prices some of the providers are reluctant to use the firewall. In this paper we proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. By discriminating these data, an administrator may take an approach action against the user. This method is very fast and can be used simply in adjacent with the Internet routers.

Keywords: Data Mining, Firewall, Optimization, Packetclassification, Statistical Pattern Recognition.

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Authors: M. Amirjan

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In the present study, the properties of Al-Al2O3 nanocomposite hollow sphere structures were investigated. For this reason, the Al-based nanocomposite hollow spheres with different amounts of nano-alumina reinforcement (0-10wt %) and different ratio of thickness to diameter (t/D: 0.06-0.3) were prepared via a powder metallurgy method. Then, the effect of mentioned parameters was studied on physical and quasi static mechanical properties of their related prepared structures (open/closed cell) such as density, hardness, strength, and energy absorption. It was found that, as the t/D ratio increases the relative density, compressive strength and energy absorption increase. The highest values of strength and energy absorption were obtained from the specimen with 5 wt. % of nanoparticle reinforcement, t/D of 0.3 (t=1 mm, D=400μm) as 22.88 MPa and 13.24 MJ/m3, respectively. The moderate specific strength of prepared composites in the present study showed the good consistency with the properties of others low carbon steel composite with similar structure.

Keywords: Hollow sphere structure foam, nanocomposite, t/D (thickness, diameter), powder metallurgy.

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Authors: Nawel Mezigheche, Abdelhacine Gouasmia, Allaeddine Athmani, Mouloud Merzoud

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Masonry infill walls are inevitable in the selfsupporting structures, but their contribution in the resistance to earthquake loads is generally neglected in the structural analyses. The principal aim of this work through a numerical study of masonry infill walls behavior in structures subjected to horizontal load is to propose by finite elements numerical modeling, a more reliable approach, faster and close to reality. In this study, 3D Finite Element Analysis was developed to study the behavior of masonry infill walls in structures subjected to horizontal load; the finite element software being used was ABAQUS, it is observed that more rigidity of the masonry filling is significant, more the structure is rigid, we can so conclude that the filling brings an additional rigidity to the structure not to be neglected; it is also observed that when the framework is subjected to horizontal loads, the framework separates from the filling on the level of the tended diagonal.

Keywords: Finite element, Masonry infill walls, Rigidity of the masonry, Tended diagonal.

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Authors: Khaled Ahmed Kadouh, Kamal Ali Albashiri

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This paper presents a designed algorithm involves improvement of transferring data over Simple Object Access Protocol (SOAP). The aim of this work is to establish whether using SOAP in exchanging XML messages has any added advantages or not. The results showed that XML messages without SOAP take longer time and consume more memory, especially with binary data.

Keywords: JAX-WS, SMTP, SOAP, Web service, XML.

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Authors: Hiroto Nakashima, Toshihiro Morita, Koichiro Ohgushi

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Laser Profiler (LP) data from aerial laser surveys have been increasingly used as topographical inputs to numerical simulations of flooding and inundation in river basins. LP data has great potential for reproducing topography, but its effective usage has not yet been fully established. In this study, flooding and inundation are simulated numerically using LP data for the Jobaru River basin of Japan’s Saga Plain. The analysis shows that the topography is reproduced satisfactorily in the computational domain with urban and agricultural areas requiring different grid sizes. A 2-D numerical simulation shows that flood flow behavior changes as grid size is varied.

Keywords: LP data, numerical simulation, topological analysis, mesh size.

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Authors: Peristera Baziana

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In this paper, we present a network configuration for a WDM LANs of passive star topology that assume that the set of data WDM channels is split into two separate sets of channels, with different access rights over them. Especially, a synchronous transmission WDMA access algorithm is adopted in order to increase the probability of successful transmission over the data channels and consequently to reduce the probability of data packets transmission cancellation in order to avoid the data channels collisions. Thus, a control pre-transmission access scheme is followed over a separate control channel. An analytical Markovian model is studied and the average throughput is mathematically derived. The performance is studied for several numbers of data channels and various values of control phase duration.

Keywords: Access algorithm, channels division, collisions avoidance, wavelength division multiplexing.

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Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: Road accident, machine learning, support vector machines.

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Authors: Mohammad S. Laghari, Gulzar A. Khuwaja

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Many problems in computer vision and image processing present potential for parallel implementations through one of the three major paradigms of geometric parallelism, algorithmic parallelism and processor farming. Static process scheduling techniques are used successfully to exploit geometric and algorithmic parallelism, while dynamic process scheduling is better suited to dealing with the independent processes inherent in the process farming paradigm. This paper considers the application of parallel or multi-computers to a class of problems exhibiting spatial data characteristic of the geometric paradigm. However, by using processor farming paradigm, a dynamic scheduling technique is developed to suit the MIMD structure of the multi-computers. A hybrid scheme of scheduling is also developed and compared with the other schemes. The specific problem chosen for the investigation is the Hough transform for line detection.

Keywords: Hough transforms, parallel computer, parallel paradigms, scheduling.

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Authors: Mikhail V. Khachaturyan, Inga A. Koryagina, Eugenia V. Klicheva

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In modern conditions, scientific judgment of problems in developing mechanisms of value creation and risk management acquires special relevance. Formation of economic knowledge has resulted in the constant analysis of consumer behavior for all players from national and world markets. Effective mechanisms development of the demand analysis, crucial for consumer's characteristics of future production, and the risks connected with the development of this production are the main objectives of control systems in modern conditions. The modern period of economic development is characterized by a high level of globalization of business and rigidity of competition. At the same time, the considerable share of new products and services costs has a non-material intellectual nature. The most successful in Russia is the contemporary development of small innovative firms. Such firms, through their unique technologies and new approaches to process management, which form the basis of their intellectual capital, can show flexibility and succeed in the market. As a rule, such enterprises should have very variable structure excluding the tough scheme of submission and demanding essentially new incentives for inclusion of personnel in innovative activity. Realization of similar structures, as well as a new approach to management, can be constructed based on value-oriented management which is directed to gradual change of consciousness of personnel and formation from groups of adherents included in the solution of the general innovative tasks. At the same time, valuable changes can gradually capture not only innovative firm staff, but also the structure of its corporate partners. Introduction of new technologies is the significant factor contributing to the development of new valuable imperatives and acceleration of the changing values systems of the organization. It relates to the fact that new technologies change the internal environment of the organization in a way that the old system of values becomes inefficient in new conditions. Introduction of new technologies often demands change in the structure of employee’s interaction and training in their new principles of work. During the introduction of new technologies and the accompanying change in the value system, the structure of the management of the values of the organization is changing. This is due to the need to attract more staff to justify and consolidate the new value system and bring their view into the motivational potential of the new value system of the organization.

Keywords: Value, risk, creation, problems, organization.

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Authors: Dias de J. C. Lilian, Lobato M. F. Fábio, de Santana L. Ádamo

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The occurrence of missing values in database is a serious problem for Data Mining tasks, responsible for degrading data quality and accuracy of analyses. In this context, the area has shown a lack of standardization for experiments to treat missing values, introducing difficulties to the evaluation process among different researches due to the absence in the use of common parameters. This paper proposes a testbed intended to facilitate the experiments implementation and provide unbiased parameters using available datasets and suited performance metrics in order to optimize the evaluation and comparison between the state of art missing values treatments.

Keywords: Data imputation, data mining, missing values treatment, testbed.

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Authors: Young-Seok Choi

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We present a family of data-reusing and affine projection algorithms. For identification of a noisy linear finite impulse response channel, a partial knowledge of a channel, especially noise, can be used to improve the performance of the adaptive filter. Motivated by this fact, the proposed scheme incorporates an estimate of a knowledge of noise. A constraint, called the adaptive noise constraint, estimates an unknown information of noise. By imposing this constraint on a cost function of data-reusing and affine projection algorithms, a cost function based on the adaptive noise constraint and Lagrange multiplier is defined. Minimizing the new cost function leads to the adaptive noise constrained (ANC) data-reusing and affine projection algorithms. Experimental results comparing the proposed schemes to standard data-reusing and affine projection algorithms clearly indicate their superior performance.

Keywords: Data-reusing, affine projection algorithm, error constraint, system identification.

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Authors: Sergun Kurtoglu

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The struggle between modern and postmodern understanding is also displayed in terms of the superiorities of quantitative and qualitative methods to each other which are evaluated within the scope of these understandings. By way of assuming that the quantitative researches (modern) are able to account for structure while the qualitative researches (postmodern) explain the process, these methods are turned into a means for worldviews specific to a period. In fact, process is not a functioning independent of structure. In addition to this issue, the ability of quantitative methods to provide scientific knowledge is also controversial so long as they exclude the dialectical method. For this reason, the critiques charged against modernism in terms of quantitative methods are, in a sense, legitimate. Nevertheless, the main issue is in which parameters postmodernist critique tries to legitimize its critiques and whether these parameters represent a point of view enabling democratic solutions. In this respect, the scientific knowledge covered in Turkish media as a means through which ordinary people have access to scientific knowledge will be evaluated by means of content analysis within a new objectivity conception.

Keywords: knowledge and objectivity, dialectic method, qualitative and quantitative methods, modernism/postmodernism.

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Authors: Oznur Korukcu, Kamile Kukulu, Mehmet Z. Firat

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The propose of this study is to investigate the factor structures of the W-DEQ, originally developed on UK and Swedish women, were confirmed in Turkish samples, and to obtain a new modified factor structure appropriate to Turkish culture. Statistical analyses of the data obtained were performed using SPSS© for Windows version 13.0 and the SAS statistical software Version 9.1. Both confirmatory and exploratory factor analysis of W-DEQ were performed in the study. Factor analysis yielded four factors related to hope, fear, lack of positive anticipation and riskiness. The alpha estimates of the total W-DEQ score were somewhat higher, being 0.92 for the parous and 0.90 for the nulliparous sample. These are well above the accepted limit of 0.70 and indicate excellent levels of internal reliability, thus showing that the questions were appropriate to the Turkish culture and useful scale for the evaluation of fear of childbirth in Turkish pregnants.

Keywords: Confirmatory factor analysis, cross-cultural research, exploratory factor analysis, fear of childbirth.

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Authors: Ines Hamdi, Mohamed Ben Ahmed

Abstract:

The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower

Keywords: Ontological model, spatio-temporal modeling, Genetic Regulatory Networks (GRNs), knowledge representation.

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