Search results for: electrostatic application in industry

Authors: Lovorka Galetic, Zeljko Vukelic

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The advanced concepts of strategic and innovation management in the sphere of company dynamic and innovation capabilities, and achieving their mutual alignment and a synergy effect, are important elements in business today. This paper analyses the theory and empirically investigates the influence of a company’s dynamic capabilities on its innovation capabilities. A new multidimensional model of dynamic capabilities is presented, consisting of five factors appropriate to real time requirements, while innovation capabilities are considered pursuant to the official OECD and Eurostat standards. After examination of dynamic and innovation capabilities indicated their theoretical links, the empirical study testing the model and examining the influence of a company’s dynamic capabilities on its innovation capabilities showed significant results. In the study, a research model was posed to relate company dynamic and innovation capabilities. One side of the model features the variables that are the determinants of dynamic capabilities defined through their factors, while the other side features the determinants of innovation capabilities pursuant to the official standards. With regard to the research model, five hypotheses were set. The study was performed in late 2014 on a representative sample of large and very large Croatian enterprises with a minimum of 250 employees. The research instrument was a questionnaire administered to company top management. For both variables, the position of the company was tested in comparison to industry competitors, on a fivepoint scale. In order to test the hypotheses, correlation tests were performed to determine whether there is a correlation between each individual factor of company dynamic capabilities with the existence of its innovation capabilities, in line with the research model. The results indicate a strong correlation between a company’s possession of dynamic capabilities in terms of their factors, due to the new multi-dimensional model presented in this paper, with its possession of innovation capabilities. Based on the results, all five hypotheses were accepted. Ultimately, it was concluded that there is a strong association between the dynamic and innovation capabilities of a company. 

Keywords: Dynamic capabilities, innovation capabilities, competitive advantage, business results.

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Authors: Suleiman E. Al-lubani, Mohammad E. Matarneh, Hussien M. Al-Wedyan, Ala M. Rayes

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Aluminum alloy has an extensive range of industrial application due to its consistent mechanical properties and structural integrity. The heat treatment by precipitation technique affected the Magnesium, Silicon Manganese and copper crystals dissolved in the Aluminum alloy. The crystals dislocated to precipitate on the crystal’s boundaries of the Aluminum alloy when given a thermal energy increased its hardness. In this project various times and temperature were varied to find out the best combination of these variables to increase the precipitation of the metals on the Aluminum crystal’s boundaries which will lead to get the highest hardness. These specimens are then tested for their hardness and tensile strength. It is noticed that when the temperature increases, the precipitation increases and consequently the hardness increases. A threshold temperature value (264C0) of Aluminum alloy should not be reached due to the occurrence of recrystalization which causes the crystal to grow. This recrystalization process affected the ductility of the alloy and decrease hardness. In addition, and while increasing the temperature the alloy’s mechanical properties will decrease. The mechanical properties, namely tensile and hardness properties are investigated according to standard procedures. In this research, different temperature and time have been applied to increase hardening.The highest hardness at 100°c in 6 hours equals to 207.31 HBR, while at the same temperature and time the lowest elongation equals to 146.5.

Keywords: Aluminum alloy, recrystalization process, heat treatment, hardness properties, precipitation, intergranular breakage.

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Authors: Rasheed A. Adebayo, Mehluli M. Moyo, Ignatius V. Nsahlai

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Ruminants are known to relish roughage for productivity but the effect of its quality on digesta load in rumen, omasum, abomasum and other distal organs of the digestive tract is yet unknown. Reticulorumen fill is a strong indicator for long-term control of intake in ruminants. As such, the measurement and prediction of digesta load in these compartments may be crucial to productivity in the ruminant industry. The current study aimed at determining the effect of (a) diet quality on digesta load in digestive organs of goats, and (b) period of meal termination on the reticulorumen fill and digesta load in other distal compartments of the digestive tract of goats. Goats were fed with urea-treated hay (UTH), urea-sprayed hay (USH) and non-treated hay (NTH). At the end of eight weeks of a feeding trial period, upon termination of a meal in the morning, afternoon or evening, all goats were slaughtered in random groups of three per day to measure reticulorumen fill and digesta loads in other distal compartments of the digestive tract. Both diet quality and period affected (P < 0.05) the measure of reticulorumen fill. However, reticulorumen fill in the evening was larger (P < 0.05) than afternoon, while afternoon was similar (P > 0.05) to morning. Also, diet quality affected (P < 0.05) the wet omasal digesta load, wet abomasum, dry abomasum and dry caecum digesta loads but did not affect (P > 0.05) both wet and dry digesta loads in other compartments of the digestive tract. Period of measurement did not affect (P > 0.05) the wet omasal digesta load, and both wet and dry digesta loads in other compartments of the digestive tract except wet abomasum digesta load (P < 0.05) and dry caecum digesta load (P < 0.05). Both wet and dry reticulorumen fill were correlated (P < 0.05) with omasum (r = 0.623) and (r = 0.723), respectively. In conclusion, reticulorumen fill of goats decreased by improving the roughage quality; and the period of meal termination and measurement of the fill is a key factor to the quantity of digesta load.

Keywords: Digesta, goats, meal termination, reticulorumen fill.

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Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: Change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics.

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Authors: Shaukat Wasi, Zubair A. Shaikh, Sajid Qasmi, Hussain Sachwani, Rehman Lalani, Aamir Chagani

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Automatic Extraction of Event information from social text stream (emails, social network sites, blogs etc) is a vital requirement for many applications like Event Planning and Management systems and security applications. The key information components needed from Event related text are Event title, location, participants, date and time. Emails have very unique distinctions over other social text streams from the perspective of layout and format and conversation style and are the most commonly used communication channel for broadcasting and planning events. Therefore we have chosen emails as our dataset. In our work, we have employed two statistical NLP methods, named as Finite State Machines (FSM) and Hidden Markov Model (HMM) for the extraction of event related contextual information. An application has been developed providing a comparison among the two methods over the event extraction task. It comprises of two modules, one for each method, and works for both bulk as well as direct user input. The results are evaluated using Precision, Recall and F-Score. Experiments show that both methods produce high performance and accuracy, however HMM was good enough over Title extraction and FSM proved to be better for Venue, Date, and time.

Keywords: Emails, Event Extraction, Event Detection, Finite state machines, Hidden Markov Model.

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Authors: Marco Raciti Castelli, Ernesto Benini

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This paper presents a model for the evaluation of energy performance and aerodynamic forces acting on a small straight-bladed Darrieus-type vertical axis wind turbine depending on blade geometrical section. It consists of an analytical code coupled to a solid modeling software, capable of generating the desired blade geometry based on the desired blade design geometric parameters. Such module is then linked to a finite volume commercial CFD code for the calculation of rotor performance by integration of the aerodynamic forces along the perimeter of each blade for a full period of revolution.After describing and validating the computational model with experimental data, the results of numerical simulations are proposed on the bases of two candidate airfoil sections, that is a classical symmetrical NACA 0021 blade profile and the recently developed DU 06-W-200 non-symmetric and laminar blade profile.Through a full CFD campaign of analysis, the effects of blade geometrical section on angle of attack are first investigated and then the overall rotor torque and power are analyzed as a function of blade azimuthal position, achieving a numerical quantification of the influence of airfoil geometry on overall rotor performance.

Keywords: Wind turbine, NACA 0021, DU 06-W-200.

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Authors: Matthias Dehmer, Frank Emmert Streib, Alexander Mehler, Jürgen Kilian, Max Mühlhauser

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Due to the tremendous amount of information provided by the World Wide Web (WWW) developing methods for mining the structure of web-based documents is of considerable interest. In this paper we present a similarity measure for graphs representing web-based hypertext structures. Our similarity measure is mainly based on a novel representation of a graph as linear integer strings, whose components represent structural properties of the graph. The similarity of two graphs is then defined as the optimal alignment of the underlying property strings. In this paper we apply the well known technique of sequence alignments for solving a novel and challenging problem: Measuring the structural similarity of generalized trees. In other words: We first transform our graphs considered as high dimensional objects in linear structures. Then we derive similarity values from the alignments of the property strings in order to measure the structural similarity of generalized trees. Hence, we transform a graph similarity problem to a string similarity problem for developing a efficient graph similarity measure. We demonstrate that our similarity measure captures important structural information by applying it to two different test sets consisting of graphs representing web-based document structures.

Keywords: Graph similarity, hierarchical and directed graphs, hypertext, generalized trees, web structure mining.

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Authors: Eakong Atiptamvaree, Twittie Senivongse

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A new paradigm for software design and development models software by its business process, translates the model into a process execution language, and has it run by a supporting execution engine. This process-oriented paradigm promotes modeling of software by less technical users or business analysts as well as rapid development. Since business process models may be shared by different organizations and sometimes even by different business domains, it is interesting to apply a technique used in traditional software component technology to design reusable business processes. This paper discusses an approach to apply a technique for software component fabrication to the design of process-oriented software units, called process components. These process components result from decomposing a business process of a particular application domain into subprocesses with an aim that the process components can be reusable in different process-based software models. The approach is quantitative because the quality of process component design is measured from technical features of the process components. The approach is also strategic because the measured quality is determined against business-oriented component management goals. A software tool has been developed to measure how good a process component design is, according to the required managerial goals and comparing to other designs. We also discuss how we benefit from reusable process components.

Keywords: Business process model, process component, component management goals, measurement

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Authors: Prakash G L, Chaitra K Meti, Poojitha K, Divya R.K.

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Wireless Sensor Network is Multi hop Self-configuring Wireless Network consisting of sensor nodes. The deployment of wireless sensor networks in many application areas, e.g., aggregation services, requires self-organization of the network nodes into clusters. Efficient way to enhance the lifetime of the system is to partition the network into distinct clusters with a high energy node as cluster head. The different methods of node clustering techniques have appeared in the literature, and roughly fall into two families; those based on the construction of a dominating set and those which are based solely on energy considerations. Energy optimized cluster formation for a set of randomly scattered wireless sensors is presented. Sensors within a cluster are expected to be communicating with cluster head only. The energy constraint and limited computing resources of the sensor nodes present the major challenges in gathering the data. In this paper we propose a framework to study how partially correlated data affect the performance of clustering algorithms. The total energy consumption and network lifetime can be analyzed by combining random geometry techniques and rate distortion theory. We also present the relation between compression distortion and data correlation.

Keywords: Clusters, multi hop, random geometry, rate distortion.

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

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

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

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Authors: R. Green, T. Mazzuchi, S. Sarkani

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Through inward perceptions, we intuitively expect distributed software development to increase the risks associated with achieving cost, schedule, and quality goals. To compound this problem, agile software development (ASD) insists one of the main ingredients of its success is cohesive communication attributed to collocation of the development team. The following study identified the degree of communication richness needed to achieve comparable software quality (reduce pre-release defects) between distributed and collocated teams. This paper explores the relevancy of communication richness in various development phases and its impact on quality. Through examination of a large distributed agile development project, this investigation seeks to understand the levels of communication required within each ASD phase to produce comparable quality results achieved by collocated teams. Obviously, a multitude of factors affects the outcome of software projects. However, within distributed agile software development teams, the mode of communication is one of the critical components required to achieve team cohesiveness and effectiveness. As such, this study constructs a distributed agile communication model (DAC-M) for potential application to similar distributed agile development efforts using the measurement of the suitable level of communication. The results of the study show that less rich communication methods, in the appropriate phase, might be satisfactory to achieve equivalent quality in distributed ASD efforts.

Keywords: agile software development (ASD), distributedsoftware teams, media richness theory, software development.

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Authors: Christian C. Vaso, Rinlee Butch M. Cervera

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One of the most promising anode materials for solid oxide electrolysis cell (SOEC) application is the Sr-doped LaMnO₃ (LSM) which is known to have a high electronic conductivity but low ionic conductivity. To increase the ionic conductivity or diffusion of ions through the anode, Yttria-stabilized Zirconia (YSZ), which has good ionic conductivity, is proposed to be combined with LSM to create a composite electrode and to obtain a high mixed ionic and electronic conducting anode. In this study, composite of lanthanum strontium manganite and YSZ oxide, La_0.8Sr_0.2MnO₃/Zr_0.92Y_0.08O₂ (LSM/YSZ), with different wt.% compositions of LSM and YSZ were synthesized using solid-state reaction. The obtained prepared composite samples of 60, 50, and 40 wt.% LSM with remaining wt.% of 40, 50, and 60, respectively for YSZ were fully characterized for its microstructure by using powder X-ray diffraction (XRD), Thermogravimetric analysis (TGA), Fourier transform infrared (FTIR), and Scanning electron microscope/Energy dispersive spectroscopy (SEM/EDS) analyses. Surface morphology of the samples via SEM analysis revealed a well-sintered and densified pure LSM, while a more porous composite sample of LSM/YSZ was obtained. Electrochemical impedance measurements at intermediate temperature range (500-700 °C) of the synthesized samples were also performed which revealed that the 50 wt.% LSM with 50 wt.% YSZ (L50Y50) sample showed the highest total conductivity of 8.27x10^-1 S/cm at 600 ^oC with 0.22 eV activation energy.

Keywords: Ceramics, microstructure, fuel cells, electrochemical impedance spectroscopy.

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Authors: A. K. Al-Othman, K. M. EL-Nagger

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Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED). Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using one system. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED).

Keywords: Security Constrained Economic Dispatch, Direct Search method, optimization.

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Authors: Lamia Hammadi, Abdellah Ait Ouhman, Aomar Ibourk

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It is widely assumed that the case of Customs Supply Chain is classified as a complex system, due to not only the variety and large number of actors, but also their complex structural links, and the interactions between these actors, that’s why this system is subject to various types of Risks. The economic, political and social impacts of those risks are highly detrimental to countries, businesses and the public, for this reason, Risk management in the customs supply chain is becoming a crucial issue to ensure the sustainability, security and safety. The main characteristic of customs risk management approach is determining which goods and means of transport should be examined? To what extend? And where future compliance resources should be directed? The purposes of this article are, firstly to deal with the concept of customs supply chain, secondly present our risk management approach based on Cross Activity Based Costing (ABC) Method as an interactive tool to support decision making in customs risk management. Finally, analysis of case study of Moroccan customs to putting theory into practice and will thus draw together the various elements of a structured and efficient risk management approach.

Keywords: Cross ABC Method, Customs Supply Chain, Risk, Risk Management.

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Authors: S. Chiali, Z.Eberrichi, M.Malki

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The number of framework conceived for e-learning constantly increase, unfortunately the creators of learning materials and educational institutions engaged in e-formation adopt a “proprietor" approach, where the developed products (courses, activities, exercises, etc.) can be exploited only in the framework where they were conceived, their uses in the other learning environments requires a greedy adaptation in terms of time and effort. Each one proposes courses whose organization, contents, modes of interaction and presentations are unique for all learners, unfortunately the latter are heterogeneous and are not interested by the same information, but only by services or documents adapted to their needs. Currently the new tendency for the framework conceived for e-learning, is the interoperability of learning materials, several standards exist (DCMI (Dublin Core Metadata Initiative)[2], LOM (Learning Objects Meta data)[1], SCORM (Shareable Content Object Reference Model)[6][7][8], ARIADNE (Alliance of Remote Instructional Authoring and Distribution Networks for Europe)[9], CANCORE (Canadian Core Learning Resource Metadata Application Profiles)[3]), they converge all to the idea of learning objects. They are also interested in the adaptation of the learning materials according to the learners- profile. This article proposes an approach for the composition of courses adapted to the various profiles (knowledge, preferences, objectives) of learners, based on two ontologies (domain to teach and educational) and the learning objects.

Keywords: Adaptive educational hypermedia systems (AEHS), E-learning, Learner's model, Learning objects, Metadata, Ontology.

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Authors: Mohd Fairuz Iskandar Othman, Nazrulazhar Bahaman, Zulkiflee Muslim, Faizal Abdollah

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This paper discusses a curriculum approach that will give emphasis on practical portions of teaching network security subjects in information and communication technology courses. As we are well aware, the need to use a practice and application oriented approach in education is paramount. Research on active learning and cooperative groups have shown that students grasps more and have more tendency towards obtaining and realizing soft skills like leadership, communication and team work as opposed to the more traditional theory and exam based teaching and learning. While this teaching and learning paradigm is relatively new in Malaysia, it has been practiced widely in the West. This paper examines a certain approach whereby students learning wireless security are divided into and work in small and manageable groups where there will be 2 teams which consist of black hat and white hat teams. The former will try to find and expose vulnerabilities in a wireless network while the latter will try their best to prevent such attacks on their wireless networks using hardware, software, design and enforcement of security policy and etc. This paper will try to show that the approach taken plus the use of relevant and up to date software and hardware and with suitable environment setting will hopefully expose students to a more fruitful outcome in terms of understanding of concepts, theories and their motivation to learn.

Keywords: Curriculum approach, wireless networks, wirelesssecurity.

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Authors: F. Taouche-Kheloui, O. Fedaoui-Akmoussi, K. Ait tahar, Li. Alex

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Currently, the reduction of energy consumption, through the use of abundant and recyclable natural materials, for better thermal insulation represents an important area of research. To this end, the use of bio-sourced materials has been identified as one of the green sectors with a very high economic development potential for the future. Because of its role in reducing the consumption of fossil-based raw materials, it contributes significantly to the storage of atmospheric carbon, limits greenhouse gas emissions and creates new economic opportunities. This study constitutes a contribution to the elaboration and the experimental characterization of the thermal behavior of a sawdust-reduced mortar matrix. We have taken into account the influence of the size of the grain fibers of sawdust, hence the use of three different ranges and also different percentage in the different confections. The intended practical application consists of producing a light weight compound at a lower cost to ensure a better thermal and acoustic behavior compared to that existing in the field, in addition to the desired resistances. Improving energy performance, while reducing greenhouse gas emissions from the building sector, is amongst the objectives to be achieved. The results are very encouraging and highlight the value of the proposed design of organic-source mortar panels which have specific mechanical properties acceptable for their use, low densities, lower cost of manufacture and labor, and above all a positive impact on the environment.

Keywords: Mortar, sawdust waste, thermal, experimental, analysis.

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Authors: D. A. K. S. Gunaratna, N. D. Kodikara, H. L. Premaratne

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Automatic currency note recognition invariably depends on the currency note characteristics of a particular country and the extraction of features directly affects the recognition ability. Sri Lanka has not been involved in any kind of research or implementation of this kind. The proposed system “SLCRec" comes up with a solution focusing on minimizing false rejection of notes. Sri Lankan currency notes undergo severe changes in image quality in usage. Hence a special linear transformation function is adapted to wipe out noise patterns from backgrounds without affecting the notes- characteristic images and re-appear images of interest. The transformation maps the original gray scale range into a smaller range of 0 to 125. Applying Edge detection after the transformation provided better robustness for noise and fair representation of edges for new and old damaged notes. A three layer back propagation neural network is presented with the number of edges detected in row order of the notes and classification is accepted in four classes of interest which are 100, 500, 1000 and 2000 rupee notes. The experiments showed good classification results and proved that the proposed methodology has the capability of separating classes properly in varying image conditions.

Keywords: Artificial intelligence, linear transformation and pattern recognition.

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Authors: Eylem Koç, Hasan Arda Burhan

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Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.

Keywords: Analytic Network Process, BOCR, location selection, multi-actor decision making, multi-criteria decision making, real life problem.

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Authors: Mohammed Golam Sarwer, Lai Man Po, Kai Guo, Q.M. Jonathan Wu

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In H.264/AVC video encoding, rate-distortion optimization for mode selection plays a significant role to achieve outstanding performance in compression efficiency and video quality. However, this mode selection process also makes the encoding process extremely complex, especially in the computation of the ratedistortion cost function, which includes the computations of the sum of squared difference (SSD) between the original and reconstructed image blocks and context-based entropy coding of the block. In this paper, a transform-domain rate-distortion optimization accelerator based on fast SSD (FSSD) and VLC-based rate estimation algorithm is proposed. This algorithm could significantly simplify the hardware architecture for the rate-distortion cost computation with only ignorable performance degradation. An efficient hardware structure for implementing the proposed transform-domain rate-distortion optimization accelerator is also proposed. Simulation results demonstrated that the proposed algorithm reduces about 47% of total encoding time with negligible degradation of coding performance. The proposed method can be easily applied to many mobile video application areas such as a digital camera and a DMB (Digital Multimedia Broadcasting) phone.

Keywords: Context-adaptive variable length coding (CAVLC), H.264/AVC, rate-distortion optimization (RDO), sum of squareddifference (SSD).

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

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

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

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Authors: Abbas Siefi, Mohammad Javad Karimifar

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

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

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Authors: Jooyeon Yook, Wonjun Ko

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

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

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Authors: Denise Levy, Helen J. Khoury

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Nuclear technology is a controversial issue among a great share of the Brazilian population. Misinformation and common wrong beliefs confuse public’s perceptions and the scientific community is expected to offer a wider perspective on the benefits and risks resulting from ionizing radiation in everyday life. Attentive to the need of new approaches between science and society, the Nuclear Energy Museum, in northeast Brazil, is an initiative created to communicate the growing impact of the beneficial applications of nuclear technology in medicine, industry, agriculture and electric power generation. Providing accessible scientific information, the museum offers a rich learning environment, making use of different educational strategies, such as films, interactive panels and multimedia learning tools, which not only increase the enjoyment of visitors, but also maximize their learning potential. Developed according to modern active learning instructional strategies, multimedia materials are designed to present the increasingly role of nuclear science in modern life, transforming science education into a meaningful learning experience. In year 2016, nine different interactive computer-based activities were developed, presenting curiosities about ionizing radiation in different landmarks around the world, such as radiocarbon dating works in Egypt, nuclear power generation in France and X-radiography of famous paintings in Italy. Feedback surveys have reported a high level of visitors’ satisfaction, proving the high quality experience in learning nuclear science at the museum. The Nuclear Energy Museum is the first and, up to the present time, the only permanent museum in Brazil devoted entirely to nuclear science.

Keywords: Nuclear technology, multimedia learning tools, science museum, society and education.

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Authors: Enrique Claver Cortés, Bartolomé Marco Lajara, Eduardo Sánchez García, Pedro Seva Larrosa, Encarnación Manresa Marhuenda, Lorena Ruiz Fernández, Esther Poveda Pareja

Abstract:

In recent decades, the analysis of the effects of clustering as an essential factor for the development of innovations and the competitiveness of enterprises has raised great interest in different areas. Nowadays, companies have access to almost all tangible and intangible resources located and/or developed in any country in the world. However, despite the obvious advantages that this situation entails for companies, their geographical location has shown itself, increasingly clearly, to be a fundamental factor that positively influences their innovative performance and competitiveness. Industrial clusters could represent a unique level of analysis, positioned between the individual company and the industry, which makes them an ideal unit of analysis to determine the effects derived from company membership of a cluster. Also, the absorptive capacity (hereinafter 'AC') can mediate the process of innovation development by companies located in a cluster. The transformation and exploitation of knowledge could have a mediating effect between knowledge acquisition and innovative performance. The main objective of this work is to determine the key factors that affect the degree of generation and use of knowledge from the environment by companies and, consequently, their innovative performance and competitiveness. The elements analyzed are the companies' membership of a cluster and the AC. To this end, 30 most relevant papers published on this subject in the "Web of Science" database have been reviewed. Our findings show that, within a cluster, the knowledge coming from the companies' environment can significantly influence their innovative performance and competitiveness, although in this relationship, the degree of access and exploitation of the companies to this knowledge plays a fundamental role, which depends on a series of elements both internal and external to the company.

Keywords: Absorptive capacity, clusters, innovation, knowledge.

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Authors: Mohammad Hasan Raouf, Ebrahim Rasooli Anarmarzi, Hamid Lesani, Javad Olamaei

Abstract:

This paper proposes the application of a hierarchical fuzzy system (HFS) based on multi-input power system stabilizer (MPSS) and also Static Var Compensator (SVC) in multi-machine environment.The number of rules grows exponentially with the number of variables in a conventional fuzzy logic system. The proposed HFS method is developed to solve this problem. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. In fact, by using HFS the total number of involved rules increases only linearly with the number of input variables. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type Power system stabilizer (PSS). Phasor model of SVC is described and used in this paper. The performances of MPSS, Conventional power system stabilizer (CPSS), hierarchical Fuzzy Multi-input Power System Stabilizer (HFMPSS) and the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. By using digital simulations the comparative study is illustrated. It can be seen that the proposed PSS is performing satisfactorily within the whole range of disturbances.

Keywords: Power system stabilizer (PSS), hierarchical fuzzysystem (HFS), Static VAR compensator (SVC)

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Authors: E. Bruno, F. Lacarbonara, M. C. Placentino, D. Gramegna

Abstract:

Environmental decision making, particularly about hazardous waste management, is inherently exposed to a high potential conflict, principally because of the trade-off between sociopolitical, environmental, health and economic factors. The need to plan complex contexts has led to an increasing request for decision analytic techniques as support for the decision process. In this work, alternative systems of asbestos-containing waste management (ACW) in Puglia (Southern Italy) were explored by a multi-criteria decision analysis. In particular, through Analytic Hierarchy Process five alternatives management have been compared and ranked according to their performance and efficiency, taking into account environmental, health and socio-economic aspects. A separated valuation has been performed for different temporal scale. For short period results showed a narrow deviation between the disposal alternatives “mono-material landfill in public quarry" and “dedicate cells in existing landfill", with the best performance of the first one. While for long period “treatment plant to eliminate hazard from asbestos-containing waste" was prevalent, although high energy demand required to achieve the change of crystalline structure. A comparison with results from a participative approach in valuation process might be considered as future development of method application to ACW management.

Keywords: Multi-criteria decision analysis, Hazardous wastemanagement, Asbestos.

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Authors: Mahmud Gungor, Ali Aydin, Erdal Akyol, Suat Tasdelen

Abstract:

The understanding of geotechnical characteristics of near-surface material and the effects of the groundwater is very important problem in such as site studies. For showing the relations between seismic data and groundwater, we selected about 25 km2 as the study area. It has been presented which is a detailed work of seismic data and groundwater depths of Gokpinar Damp area. Seismic waves velocity (Vp and Vs) are very important parameters showing the soil properties. The seismic records were used the method of the multichannel analysis of surface waves near area of Gokpinar Damp area. Sixty sites in this area have been investigated with survey lines about 60 m in length. MASW (Multichannel analysis of surface wave) method has been used to generate onedimensional shear wave velocity profile at locations. These shear wave velocities are used to estimate equivalent shear wave velocity in the study area at every 2 and 5 m intervals up to a depth of 45 m. Levels of equivalent shear wave velocity of soil are used the classified of the study area. After the results of the study, it must be considered as components of urban planning and building design of Gokpinar Damp area, Denizli and the application and use of these results should be required and enforced by municipal authorities.

Keywords: Seismic data, Gokpinar Damp, urban planning, Denizli.

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Authors: Wei Zhang, Yao-Yu Li, Yi-Fan Zhu, Qun Li, Wei-Ping Wang

Abstract:

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in the form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studied with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

Keywords: admissible support vector kernel, reproducing kernel, structural prior knowledge, motivated support vector regression

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Authors: Wei Zhang, Yao-Yu Li, Yi-Fan Zhu, Qun Li, Wei-Ping Wang

Abstract:

It-s known that incorporating prior knowledge into support vector regression (SVR) can help to improve the approximation performance. Most of researches are concerned with the incorporation of knowledge in form of numerical relationships. Little work, however, has been done to incorporate the prior knowledge on the structural relationships among the variables (referred as to Structural Prior Knowledge, SPK). This paper explores the incorporation of SPK in SVR by constructing appropriate admissible support vector kernel (SV kernel) based on the properties of reproducing kernel (R.K). Three-levels specifications of SPK are studies with the corresponding sub-levels of prior knowledge that can be considered for the method. These include Hierarchical SPK (HSPK), Interactional SPK (ISPK) consisting of independence, global and local interaction, Functional SPK (FSPK) composed of exterior-FSPK and interior-FSPK. A convenient tool for describing the SPK, namely Description Matrix of SPK is introduced. Subsequently, a new SVR, namely Motivated Support Vector Regression (MSVR) whose structure is motivated in part by SPK, is proposed. Synthetic examples show that it is possible to incorporate a wide variety of SPK and helpful to improve the approximation performance in complex cases. The benefits of MSVR are finally shown on a real-life military application, Air-toground battle simulation, which shows great potential for MSVR to the complex military applications.

Keywords: admissible support vector kernel, reproducing kernel, structural prior knowledge, motivated support vector regression

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