Search results for: distance and open learning

Authors: Danilo López, Nelson Vera, Luis Pedraza

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This paper analyzes fundamental ideas and concepts related to neural networks, which provide the reader a theoretical explanation of Long Short-Term Memory (LSTM) networks operation classified as Deep Learning Systems, and to explicitly present the mathematical development of Backward Pass equations of the LSTM network model. This mathematical modeling associated with software development will provide the necessary tools to develop an intelligent system capable of predicting the behavior of licensed users in wireless cognitive radio networks.

Keywords: Neural networks, multilayer perceptron, long short-term memory, recurrent neuronal network, mathematical analysis.

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: AlexNet, Deep learning, image recognition, 6D posture estimation.

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Authors: Sepideh Samadzadehyazdi, Mohammad Javad Khalili, Sarvenaz Samadzadehyazdi, Mohammad Javad Mahdavinejad

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The term ‘Windphil Architecture’ refers to the building that facilitates natural ventilation by architectural elements. Natural ventilation uses the natural forces of wind pressure and stacks effect to direct the movement of air through buildings. Natural ventilation is increasingly being used in contemporary buildings to minimize the consumption of non-renewable energy and it is an effective way to improve indoor air quality. The main objective of this paper is to identify the strategies of using natural ventilation in Iranian modern buildings. In this regard, the research method is ‘descriptive-analytical’ that is based on comparative techniques. To simulate wind flow in the interior spaces of case studies, FLUENT software has been used. Research achievements show that it is possible to use natural ventilation to create a thermally comfortable indoor environment. The natural ventilation strategies could be classified into two groups of environmental characteristics such as public space structure, and architectural characteristics including building form and orientation, openings, central courtyards, wind catchers, roof, wall wings, semi-open spaces and the heat capacity of materials. Having investigated modern buildings of Iran, innovative elements like wind catchers and wall wings are less used than the traditional architecture. Instead, passive ventilation strategies have been more considered in the building design as for the roof structure and openings.

Keywords: Natural ventilation strategies, wind catchers, wind flow, Iranian modern buildings.

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Authors: S. A. Razavi Alavi, M. Torabi Angaji, Z. Gholami

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In the process of polyethylene extrusion polymer material similar to powder or granule is under compression, melting and transmission operation and on base of special form, extrudate has been produced. Twin-screw extruders are applicable in industries because of their high capacity. The powder mixing with chemical additives and melting with thermal and mechanical energy in three zones (feed, compression and metering zone) and because of gear pump and screw's pressure, converting to final product in latest plate. Extruders with twin-screw and short distance between screws are better than other types because of their high capacity and good thermal and mechanical stress. In this paper, process of polyethylene extrusion and various tapes of extruders are studied. It is necessary to have an exact control on process to producing high quality products with safe operation and optimum energy consumption. The granule size is depending on granulator motor speed. Results show at constant feed rate a decrease in granule size was found whit Increase in motor speed. Relationships between HDPE feed rate and speed of granulator motor, main motor and gear pump are calculated following as: x = HDPE feed flow rate, yM = Main motor speed yM = (-3.6076e-3) x^4+ (0.24597) x^3+ (-5.49003) x^2+ (64.22092) x+61.66786 (1) x = HDPE feed flow rate, yG = Gear pump speed yG = (-2.4996e-3) x^4+ (0.18018) x^3+ (-4.22794) x^2+ (48.45536) x+18.78880 (2) x = HDPE feed flow rate, y = Granulator motor speed 10th Degree Polynomial Fit: y = a+bx+cx^2+dx^3... (3) a = 1.2751, b = 282.4655, c = -165.2098, d = 48.3106, e = -8.18715, f = 0.84997 g = -0.056094, h = 0.002358, i = -6.11816e-5 j = 8.919726e-7, k = -5.59050e-9

Keywords: Extrusion, Extruder, Granule, HDPE, Polymer, Twin-Screw extruder.

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Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Keywords: Feature Selection, Learning with Kernels, Support Vector Machine, Genetic Algorithm, and Classification.

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: Network Intrusion Detection, Machine learning, Artificial Neural Network.

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, three feature selection methods are evaluated: Random Selection, Information Gain (IG) and Support Vector Machine feature selection (called SVM_FS). We show that the best results were obtained with SVM_FS method for a relatively small dimension of the feature vector. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Feature Selection, Learning with Kernels, SupportVector Machine, and Classification.

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

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Artificial Neural Network (ANN)s can be modeled for High Energy Particle analysis with special emphasis on shower core location. The work describes the use of an ANN based system which has been configured to predict locations of cores of showers in the range 1010.5 to 1020.5 eV. The system receives density values as inputs and generates coordinates of shower events recorded for values captured by 20 core positions and 80 detectors in an area of 100 meters. Twenty ANNs are trained for the purpose and the positions of shower events optimized by using cooperative ANN learning. The results derived with variations of input upto 50% show success rates in the range of 90s.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

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In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: Camshift Algorithm, Computer Vision, Kalman Filter, Object tracking.

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Authors: B. R. Faleye, M. I. Titocan, M. P. Ibitola

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Investigation was carried out at Opic Estate in Isheri-Osun River Basin environment using Electrical Resistivity method to study saltwater intrusion into a fresh water aquifer system from the proximal estuarine water body. The investigation is aimed at aquifer characterisation using electrical resistivity method in order to provide the depth to which fresh water fit for both domestic and industrial consumption. The 2D Electrical Resistivity and Vertical Electrical Resistivity techniques alongside Laboratory analysis of water samples obtained from the boreholes were adopted. Three traverses were investigated using Wenner and Pole-Dipole array with multi-electrode system consisting of 84 electrodes and a spread of 581 m, 664 m and 830 m were attained on the traverses. The main lithologies represented in the study area are Sand, Clay and Clayey Sand of which Sand constitutes the aquifer in the study area. Vertical Electrical Sounding data obtained at different lateral distance on the traverses have indicated that the water in the aquifer in the subsurface is brackish. Brackish water is represented by lowelectrical resistivity value signature while fresh water is characterized by relatively high electrical resistivity and in some regionfresh water is existent at depth greater than 200 m. Results of laboratory analysis of samples showed that the pH, Salinity, Total Dissolved Solid and Conductivity indicated existence of water with poor quality, indicating that salinity, TDS and Conductivity is higher in the Northern part of the study area. The 2D electrical resistivity and Vertical Electrical Sounding methods indicate that fresh water region is at ≥200m depth. Aquifers not fit for domestic use in the study area occur downwards to about 200 m in depth. In conclusion, it is recommended that wells should be sunkbeyond 220 m for the possible procurement of portable fresh water.

Keywords: 2D electrical resistivity, aquifer, brackish water, lithologies, freshwater, opic estate.

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Authors: C. Cruz, A. Breda

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Emotions are manifestations of everything that happens around us, influencing, consequently, our actions. People experience emotions continuously when socialize with friends, when facing complex situations, and when at school, among many other situations. Although the influence of emotions in the teaching and learning process is nothing new, its study in the academic field has been more popular in recent years, distinguishing between positive (e.g., enjoyment and curiosity) and negative emotions (e.g., boredom and frustration). There is no doubt that emotions play an important role in the students’ learning process since the development of knowledge involves thoughts, actions, and emotions. Nowadays, one of the most significant changes in acquiring knowledge, accessing information, and communicating is the way we do it through technological and digital resources. Faced with an increasingly frequent use of technological or digital means with different purposes, whether in the acquisition of knowledge or in communicating with others, the emotions involved in these processes change naturally. The speed with which the Internet provides information reduces the excitement for searching for the answer, the gratification of discovering something through our own effort, the patience, the capacity for effort, and resilience. Thus, technological and digital devices are bringing changes to the emotional domain. For this reason and others, it is essential to educate children from an early age to understand that it is not possible to have everything with just one click and to deal with negative emotions. Currently, many curriculum guidelines highlight the importance of the development of so-called soft skills, in which the emotional domain is present, in academic contexts. Within the scope of the Portuguese reality, the “Students’ profile by the end of compulsory schooling” and the “Health education reference” also emphasize the importance of emotions in education. There are several resources to stimulate good emotions in articulation with cognitive development. One of the most predictable and not very used resources in the most diverse areas of knowledge after pre-school education is the literature. Due to its characteristics, in the narrative or in the illustrations, literature provides the reader with a journey full of emotions. On the other hand, literature makes it possible to establish bridges between narrative and different areas of knowledge, reconciling the cognitive and emotional domains. This study results from the presentation session of a children's book, entitled “From the Outside to Inside and from the Inside to Outside”, to children attending the 2nd, 3rd, and 4th years of basic education in the Portuguese education system. In this book, rationale and emotion are in constant dialogue, so in this session, based on excerpts from the book dramatized by the authors, some questions were asked to the children in a large group, with an aim to explore their perception regarding certain emotions or events that trigger them. According to the aim of this study, qualitative, descriptive, and interpretative research was carried out based on participant observation and audio records.

Keywords: Emotions, children’s literature, basic education, soft skills.

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Authors: Vitomir Struc, Nikola Pavesic

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Over the past decades, automatic face recognition has become a highly active research area, mainly due to the countless application possibilities in both the private as well as the public sector. Numerous algorithms have been proposed in the literature to cope with the problem of face recognition, nevertheless, a group of methods commonly referred to as appearance based have emerged as the dominant solution to the face recognition problem. Many comparative studies concerned with the performance of appearance based methods have already been presented in the literature, not rarely with inconclusive and often with contradictory results. No consent has been reached within the scientific community regarding the relative ranking of the efficiency of appearance based methods for the face recognition task, let alone regarding their susceptibility to appearance changes induced by various environmental factors. To tackle these open issues, this paper assess the performance of the three dominant appearance based methods: principal component analysis, linear discriminant analysis and independent component analysis, and compares them on equal footing (i.e., with the same preprocessing procedure, with optimized parameters for the best possible performance, etc.) in face verification experiments on the publicly available XM2VTS database. In addition to the comparative analysis on the XM2VTS database, ten degraded versions of the database are also employed in the experiments to evaluate the susceptibility of the appearance based methods on various image degradations which can occur in "real-life" operating conditions. Our experimental results suggest that linear discriminant analysis ensures the most consistent verification rates across the tested databases.

Keywords: Biometrics, face recognition, appearance based methods, image degradations, the XM2VTS database.

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Authors: S. Pattanapairoj, D. Chetchotsak

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This paper proposed classification models that would be used as a proxy for hard disk drive (HDD) functional test equitant which required approximately more than two weeks to perform the HDD status classification in either “Pass" or “Fail". These models were constructed by using committee network which consisted of a number of single neural networks. This paper also included the method to solve the problem of sparseness data in failed part, which was called “enforce learning method". Our results reveal that the constructed classification models with the proposed method could perform well in the sparse data conditions and thus the models, which used a few seconds for HDD classification, could be used to substitute the HDD functional tests.

Keywords: Sparse data, Classifications, Committee network

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Authors: Nidhi Gadura

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Given the increase in the number of students and administrators asking for online courses the author developed two partially online courses. One was a biology majors at genetics course while the other was a non-majors at biology course. The student body at Queensborough Community College is generally underprepared and has work and family obligations. As an educator, one has to be mindful about changing the pedagogical approach, therefore, special care was taken when designing the course material. Despite the initial concerns, both of these partially online courses were received really well by students. Lessons learnt were that student engagement is the key to success in an online course. Good practices to run a successful online course for underprepared students are discussed in this paper. Also discussed are the lessons learnt for making the eLearning environment better for all the students in the class, overachievers and underachievers alike.

Keywords: Partially online course, pedagogy, student engagement, community college.

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Authors: Ferhat Erdal, Osman Tunca, Serkan Tas, Serdar Carbas

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Web-expanded steel beams provide an easy and economical solution for the systems having longer structural members. The main goal of manufacturing these beams is to increase the moment of inertia and section modulus, which results in greater strength and rigidity. Until recently, there were two common types of open web-expanded beams: with hexagonal openings, also called castellated beams, and beams with circular openings referred to as cellular beams, until the generation of sinusoidal web-expanded beams. In the present research, the optimum design of a new generation beams, namely sinusoidal web-expanded beams, will be carried out and the design results will be compared with castellated and cellular beam solutions. Thanks to a reduced fabrication process and substantial material savings, the web-expanded beam with sinusoidal holes (Angelina™ Beam) meets the economic requirements of steel design problems while ensuring optimum safety. The objective of this research is to carry out non-linear finite element analysis (FEA) of the web-expanded beam with sinusoidal holes. The FE method has been used to predict their entire response to increasing values of external loading until they lose their load carrying capacity. FE model of each specimen that is utilized in the experimental studies is carried out. These models are used to simulate the experimental work to verify of test results and to investigate the non-linear behavior of failure modes such as web-post buckling, shear buckling and vierendeel bending of beams.

Keywords: Steel structures, web-expanded beams, Angelina™ beam, optimum design, failure modes, finite element analysis.

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Authors: T.C. Manjunath, B. Bandyopadhyay

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This paper features the modeling and design of a Fast Output Sampling (FOS) Feedback control technique for the Active Vibration Control (AVC) of a smart flexible aluminium cantilever beam for a Single Input Single Output (SISO) case. Controllers are designed for the beam by bonding patches of piezoelectric layer as sensor / actuator to the master structure at different locations along the length of the beam by retaining the first 2 dominant vibratory modes. The entire structure is modeled in state space form using the concept of piezoelectric theory, Euler-Bernoulli beam theory, Finite Element Method (FEM) and the state space techniques by dividing the structure into 3, 4, 5 finite elements, thus giving rise to three types of systems, viz., system 1 (beam divided into 3 finite elements), system 2 (4 finite elements), system 3 (5 finite elements). The effect of placing the sensor / actuator at various locations along the length of the beam for all the 3 types of systems considered is observed and the conclusions are drawn for the best performance and for the smallest magnitude of the control input required to control the vibrations of the beam. Simulations are performed in MATLAB. The open loop responses, closed loop responses and the tip displacements with and without the controller are obtained and the performance of the proposed smart system is evaluated for vibration control.

Keywords: Smart structure, Finite element method, State spacemodel, Euler-Bernoulli theory, SISO model, Fast output sampling, Vibration control, LMI

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Authors: Omid A. Zargar

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In this project three type of tools, straight cylindrical, taper cylindrical and triangular tool all made of High speed steel (Wc-Co) used for the friction stir welding (FSW) aluminum alloy H20–H20 and the mechanical properties of the welded joint tested by tensile test and vicker hardness test. Besides, mentioned mechanical properties compared with each other to make conclusion. The result helped design of welding parameter optimization for different types of friction stir process like rotational speed, depth of welding, travel speed, type of material, type of joint, work piece dimension, joint dimension, tool material and tool geometry. Previous investigations in different types of materials work pieces; joint type, machining parameter and preheating temperature take placed. In this investigation 3 mentioned tool types that are popular in FSW tested and the results completed other aspects of the process. Hope this paper can open a new horizon in experimental investigation of mechanical properties for friction stir welded joint with other different type of tools like oval shape probe, paddle shape probe, three flat sided probe, and three sided re-entrant probe and other materials and alloys like titanium or steel in near future.

Keywords: Friction stir welding (FSW), tool, CNC milling machine, aluminum alloy H20, Vickers hardness test, tensile test, straight cylindrical tool, taper cylindrical tool, triangular tool.

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: Feature selection, mass spectrometry, biomarker discovery, cancer.

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Authors: Hanh Thi My Nguyen

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The purpose of this research is to examine the experiences of parents of children who are deaf or hard of hearing in supporting their children to access education in Vietnam. Parents play a crucial role in supporting their children to gain full access to education. It was widely reported that parents of those children confronted a range of problems to support their children to access education. To author’s best knowledge, there has been a lack of research exploring the experiences of those parents in literature. This research examines factors affecting those parents in supporting their children to access education. To conduct the study, qualitative approach using a phenomenological research design was chosen to explore the central phenomena. Ten parents of children who were diagnosed as deaf or hard of hearing and aged 6-9 years were recruited through the support of the Association of Parents of Children with Hearing Impairment. Participants were interviewed via telephone with a mix of open and closed questions; interviews were audio recorded, transcribed and thematically analysed. The research results show that there are nine main factors that affected the parents in this study in making decisions relating to education for their children including: lack of information resources, perspectives of those parents on communication approaches, the families’ financial capacity, the psychological impact on the participants after their children’ diagnosis, the attitude of family members, attitude of school administrators, lack of local schools and qualified teachers, and current education system for the deaf in Vietnam. Apart from those factors, the lack of knowledge of the participants’ partners about deaf education and the partners’ employment are barriers to educational access and successful communication with their child.

Keywords: Access to education, deaf, hard of hearing, parents experience.

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Authors: H. Nakamura

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This study analyzes international strategic alliances in the information industry. The purpose of this study is to clarify the strategic intention of an international alliance. Secondly, it investigates the influence of differences in the target markets of partner companies on alliances. Using an international strategy theory approach to analyze the global strategies of global companies, the study compares a database business and an electronic publishing business. In particular, these cases emphasized factors attributable to "people" and "learning", reliability and communication between organizations and the evolution of the IT infrastructure. The theory evolved in this study validates the effectiveness of these strategies.

Keywords: Database business, electronic library, international strategic alliances, partner selection.

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Authors: Shorena Pharjiani

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Present empirical paper investigates the relationship between FDI and economic growth by 10 selected industries in 10 Central and Eastern European countries from the period 1995 to 2012. Different estimation approaches were used to explore the connection between FDI and economic growth, for example OLS, RE, FE with and without time dummies. Obtained empirical results leads to some main consequences: First, the Central and East European countries (CEEC) attracted foreign direct investment, which raised the productivity of industries they entered in. It should be concluded that the linkage between FDI and output growth by industries is positive and significant enough to suggest that foreign firm’s participation enhanced the productivity of the industries they occupied. There had been an endogeneity problem in the regression and fixed effects estimation approach was used which partially corrected the regression analysis in order to make the results less biased. Second, it should be stressed that the results show that time has an important role in making FDI operational for enhancing output growth by industries via total factor productivity. Third, R&D positively affected economic growth and at the same time, it should take some time for research and development to influence economic growth. Fourth, the general trends masked crucial differences at the country level: over the last 20 years, the analysis of the tables and figures at the country level show that the main recipients of FDI of the 11 Central and Eastern European countries were Hungary, Poland and the Czech Republic. The main reason was that these countries had more open door policies for attracting the FDI. Fifth, according to the graphical analysis, while Hungary had the highest FDI inflow in this region, it was not reflected in the GDP growth as much as in other Central and Eastern European countries.

Keywords: Central and East European countries (CEEC), economic growth, FDI, panel data.

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Authors: Maria E. Eggink

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Innovation plays an important role in economic growth and development. Evolutionary economics has entrepreneurs at the centre of the innovation system, but includes all other participants as contributors to the performance of the innovation system. Education and training institutions, one of the participants in the innovation system, contributes in different ways to human capital. The gap in literature on the competence building as part of human capital in the analysis of innovation systems is addressed in this paper. The Mpumalanga Province of South Africa is used as a case study. It was found that the absence of a university, the level of education, the quality and performance in the education sector and the condition of the education infrastructure have not been conducive to learning.

Keywords: Education institutions, human capital, innovation systems, Mpumalanga Province.

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Authors: Shigeaki Sakurai, Ryohei Orihara

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This paper proposes a new method for analyzing textual data. The method deals with items of textual data, where each item is described based on various viewpoints. The method acquires 2- class classification models of the viewpoints by applying an inductive learning method to items with multiple viewpoints. The method infers whether the viewpoints are assigned to the new items or not by using the models. The method extracts expressions from the new items classified into the viewpoints and extracts characteristic expressions corresponding to the viewpoints by comparing the frequency of expressions among the viewpoints. This paper also applies the method to questionnaire data given by guests at a hotel and verifies its effect through numerical experiments.

Keywords: Text mining, Multiple viewpoints, Differential analysis, Questionnaire data

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Authors: Benazeer Md. Shahzada, Verelst Jan, Van Grembergen Wim, Mannaert Herwig

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This article is an extension and a practical application approach of Wheeler-s NEBIC theory (Net Enabled Business Innovation Cycle). NEBIC theory is a new approach in IS research and can be used for dynamic environment related to new technology. Firms can follow the market changes rapidly with support of the IT resources. Flexible firms adapt their market strategies, and respond more quickly to customers changing behaviors. When every leading firm in an industry has access to the same IT resources, the way that these IT resources are managed will determine the competitive advantages or disadvantages of firm. From Dynamic Capabilities Perspective and from newly introduced NEBIC theory by Wheeler, we know that only IT resources cannot deliver customer value but good configuration of those resources can guarantee customer value by choosing the right emerging technology, grasping the right economic opportunities through business innovation and growth. We found evidences in literature that SOA (Service Oriented Architecture) is a promising emerging technology which can deliver the desired economic opportunity through modularity, flexibility and loose-coupling. SOA can also help firms to connect in network which can open a new window of opportunity to collaborate in innovation and right kind of outsourcing. There are many articles and research reports indicates that failure rate in outsourcing is very high but at the same time research indicates that successful outsourcing projects adds tangible and intangible benefits to the service consumer. Business executives and policy makers in the west should not afraid of outsourcing but they should choose the right strategy through the use of emerging technology to significantly reduce the failure rate in outsourcing.

Keywords: Absorptive capacity, Dynamic Capability, Netenabled business innovation cycle, Service oriented architecture.

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Authors: Daria Topousis, Keri Murphy, Jeanne Holm

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Following the loss of NASA's Space Shuttle Columbia in 2003, it was determined that problems in the agency's organization created an environment that led to the accident. One component of the proposed solution resulted in the formation of the NASA Engineering Network (NEN), a suite of information retrieval and knowledge-sharing tools. This paper describes the implementation of communities of practice, which are formed along engineering disciplines. Communities of practice enable engineers to leverage their knowledge and best practices to collaborate and take information learning back to their jobs and embed it into the procedures of the agency. This case study offers insight into using traditional engineering disciplines for virtual collaboration, including lessons learned during the creation and establishment of NASA-s communities.

Keywords: Collaboration, communities of practice, knowledge management, virtual teams.

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Authors: Hossein Mohammadzadeh, Mojtaba Heydarizad

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Among various water resources, the surface water has a dominant role in providing water supply in the arid and semi-arid region of Iran. Andarokh-Kardeh basin is located in 50 km from Mashhad city - the second biggest city of Iran (NE of Iran), draining by Kardeh river which provides a significant portion of potable and irrigation water needs for Mashhad. The stable isotopes (¹⁸O, ²H,¹³C-DIC, and ¹³C-DOC), as reliable and precious water fingerprints, have been measured in Kardeh river (Kharket, Mareshk, Jong, All and Kardeh stations) and in Kardeh dam reservoirs (at five different sites S1 to S5) during March to June 2011 and June 2012. On δ¹⁸O vs. δ²H diagram, the river samples were plotted between Global and Eastern Mediterranean Meteoric Water lines (GMWL and EMMWL) which demonstrate that various moisture sources are providing humidity for precipitation events in this area. The enriched δ¹⁸O and δ²H values (-6.5 ‰ and -44.5 ‰ VSMOW) of Kardeh dam reservoir are compared to Kardeh river (-8.6‰and-54.4‰), and its deviation from Mashhad meteoric water line (MMWL- δ²H=7.16δ¹⁸O+11.22) is due to evaporation from the open surface water body. The enriched value of δ ¹³C-DIC and high amount of DIC values (-7.9 ‰ VPDB and 57.23 ppm) in the river and Kardeh dam reservoir (-7.3 ‰ VPDB and 55.53 ppm) is due to dissolution of Mozdooran Carbonate Formation lithology (Jm1 to Jm3 units) (contains enriched δ¹³C DIC values of 9.2‰ to 27.7‰ VPDB) in the region. Because of the domination of C3 vegetations in Andarokh_Kardeh basin, the δ¹³C-DOC isotope of the river (-28.4‰ VPDB) and dam reservoir (-32.3‰ VPDB) demonstrate depleted values. Higher DOC concentration in dam reservoir (2.57 ppm) compared to the river (0.72 ppm) is due to more biologogical activities and organic matters in dam reservoir.

Keywords: Dam reservoir, Iran, Kardeh river, Khorasan razavi, Stable isotopes.

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Authors: Gordana Kordić, Petra Palić

Abstract:

The European countries that during the past two decades based their exchange rate regimes on currency board arrangement (CBA) are usually analysed from the perspective of corner solution choice’s stabilisation effects. There is an open discussion on the positive and negative background of a strict exchange rate regime choice, although it should be seen as part of the transition process towards the monetary union membership. The focus of the paper is on the Baltic countries that after two decades of a rigid exchange rate arrangement and strongly influenced by global crisis are finishing their path towards the euro zone. Besides the stabilising capacity, the CBA is highly vulnerable regime, with limited developing potential. The rigidity of the exchange rate (and monetary) system, despite the ensured credibility, do not leave enough (or any) space for the adjustment and/or active crisis management. Still, the Baltics are in a process of recovery, with fiscal consolidation measures combined with (painful and politically unpopular) measures of internal devaluation. Today, two of them (Estonia and Latvia) are members of euro zone, fulfilling their ultimate transition targets, but de facto exchanging one fixed regime with another. The paper analyses the challenges for the CBA in unstable environment since the fixed regimes rely on imported stability and are sensitive to external shocks. With limited monetary instruments, these countries were oriented to the fiscal policies and used a combination of internal devaluation and tax policy measures. Despite their rather quick recovery, our second goal is to analyse the long term influence that the measures had on the national economy.

Keywords: Currency Board Arrangement, internal devaluation, exchange rate regime, Great recession.

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Authors: Amr A. El Hanafy, Muhammad Qureshi, Jamal Sabir, Mohamed Mutawakil, Mohamed M. Ahmed, Hassan El Ashmaoui, Hassan Ramadan, Mohamed Abou-Alsoud, Mahmoud Abdel Sadek

Abstract:

Domestic goats (Capra hircus) are extremely diverse species and principal animal genetic resource of the developing world. These facilitate a persistent supply of meat, milk, fibre, and skin and are considered as important revenue generators in small pastoral environments. This study aimed to fingerprint β-LG gene at PCR-RFLP level in native Saudi goat breeds (Ardi, Habsi and Harri) in an attempt to have a preliminary image of β-LG genotypic patterns in Saudi breeds as compared to other foreign breeds such as Indian and Egyptian. Also, the Phylogenetic analysis was done to investigate evolutionary trends and similarities among the caprine β-LG gene with that of the other domestic specie, viz. cow, buffalo and sheep. Blood samples were collected from 300 animals (100 for each breed) and genomic DNA was extracted. A fragment of the β-LG gene (427bp) was amplified using specific primers. Subsequent digestion with Sac II restriction endonuclease revealed two alleles (A and B) and three different banding patterns or genotypes i.e. AA, AB and BB. The statistical analysis showed a general trend that β-LG AA genotype had higher milk yield than β-LG AB and β-LG BB genotypes. Nucleotide sequencing of the selected β-LG fragments was done and submitted to GenBank NCBI (Accession No. KJ544248, KJ588275, KJ588276, KJ783455, KJ783456 and KJ874959). Phylogenetic analysis on the basis of nucleotide sequences of native Saudi goats indicated evolutional similarity with the GenBank reference sequences of goat, Bubalus bubalis and Bos taurus. However, the origin of sheep which is the most closely related from the evolutionary point of view, was located some distance away.

Keywords: β-Lactoglobulin, Saudi goats, PCR-RFLP, Phylogenetic analysis.

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Authors: Khin May Win, Nan Sai Moon Kham

Abstract:

Identification of cancer genes that might anticipate the clinical behaviors from different types of cancer disease is challenging due to the huge number of genes and small number of patients samples. The new method is being proposed based on supervised learning of classification like support vector machines (SVMs).A new solution is described by the introduction of the Maximized Margin (MM) in the subset criterion, which permits to get near the least generalization error rate. In class prediction problem, gene selection is essential to improve the accuracy and to identify genes for cancer disease. The performance of the new method was evaluated with real-world data experiment. It can give the better accuracy for classification.

Keywords: Microarray data, feature selection, recursive featureelimination, support vector machines.

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Authors: Marinela Mircea

Abstract:

The development of information and communication technology, the increased use of the internet, as well as the effects of the recession within the last years, have lead to the increased use of cloud computing based solutions, also called on-demand solutions. These solutions offer a large number of benefits to organizations as well as challenges and risks, mainly determined by data visualization in different geographic locations on the internet. As far as the specific risks of cloud environment are concerned, data security is still considered a peak barrier in adopting cloud computing. The present study offers an approach upon ensuring the security of cloud data, oriented towards the whole data life cycle. The final part of the study focuses on the assessment of data security in the cloud, this representing the bases in determining the potential losses and the premise for subsequent improvements and continuous learning.

Keywords: cloud computing, data life cycle, data security, security assessment.

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