Search results for: evidence based practice

Authors: Chiung-Hui Chen

Abstract:

Diagram and drawing are important ways to communicate and the reproduce of architectural design, Due to the development of information and communication technology, the professional thinking of architecture and interior design are also change rapidly. In development process of design, diagram always play very important role. This study is based on diagram theories, observe and record interaction between man and objects, objects and space, and space and time in a modern nuclear family. Construct a method for diagram to systematically and visualized describe the space plan of a modern nuclear family toward an intelligent design, to assist designer to retrieve information and review event pattern of past and present.

Keywords: Digital diagram, information model, context aware, data analysis.

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Authors: Garima Srivastava, R. K. Srivastava, R. C. Vaishya

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Decision Support System (DSS), a query-based system meant to help decision makers to use a variety of information for decision making, plays a very vital role in sustainable growth of any country. For this very purpose it is essential to analyze the educational system because education is the only way through which people can be made aware as to how to sustain our planet. The purpose of this paper is to prepare a decision support system for efficiency evaluation of education system with the help of Distributed Geographical Information System.

Keywords: Distributed GIS, Web GIS, Spatial Decision Support System, Bundelkhand Zone, Efficiency, Primary School Education.

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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: Y. Boutiche, N. Ramou, M. Ben Gharsallah

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This paper is devoted to present and discuss a model that allows a local segmentation by using statistical information of a given image. It is based on Chan-Vese model, curve evolution, partial differential equations and binary level sets method. The proposed model uses the piecewise constant approximation of Chan-Vese model to compute Signed Pressure Force (SPF) function, this one attracts the curve to the true object(s)-s boundaries. The implemented model is used to extract weld defects from weld radiographic images in the aim to calculate the perimeter and surfaces of those weld defects; encouraged resultants are obtained on synthetic and real radiographic images.

Keywords: Active contour, Chan-Vese Model, local segmentation, weld radiographic images.

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Authors: Manisha Dubey, Pankaj Gupta

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This paper presents a systematic approach for the design of power system stabilizer using genetic algorithm and investigates the robustness of the GA based PSS. The proposed approach employs GA search for optimal setting of PSS parameters. The performance of the proposed GPSS under small and large disturbances, loading conditions and system parameters is tested. The eigenvalue analysis and nonlinear simulation results show the effectiveness of the GPSS to damp out the system oscillations. It is found tat the dynamic performance with the GPSS shows improved results, over conventionally tuned PSS over a wide range of operating conditions.

Keywords: Genetic Algorithm, Genetic power system stabilizer, Power system stabilizer, Small signal stability

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Authors: J. I. Asnor, S. Rosnah, Z. W. H. Wan, H. A. B. Badrul

Abstract:

Pineapples can be classified using an index with seven levels of maturity based on the green and yellow color of the skin. As the pineapple ripens, the skin will change from pale green to a golden or yellowish color. The issues that occur in agriculture nowadays are to do with farmers being unable to distinguish between the indexes of pineapple maturity correctly and effectively. There are several reasons for why farmers cannot properly follow the guideline provide by Federal Agriculture Marketing Authority (FAMA) and one of reason is that due to manual inspection done by experts, there are no specific and universal guidelines to be adopted by farmers due to the different points of view of the experts when sorting the pineapples based on their knowledge and experience. Therefore, an automatic system will help farmers to identify pineapple maturity effectively and will become a universal indicator to farmers.

Keywords: Artificial Neural Network, Image Processing, Index of Maturity, Pineapple

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Authors: Réka Sárközi, Péter Iványi, Attila B. Széll

Abstract:

The aim of this paper is to present the adaptation of the dome construction tool for formex algebra to the parametric design software Grasshopper. Formex algebra is a mathematical system, primarily used for planning structural systems such like truss-grid domes and vaults, together with the programming language Formian. The goal of the research is to allow architects to plan truss-grid structures easily with parametric design tools based on the versatile formex algebra mathematical system. To produce regular structures, coordinate system transformations are used and the dome structures are defined in spherical coordinate system. Owing to the abilities of the parametric design software, it is possible to apply further modifications on the structures and gain special forms. The paper covers the basic dome types, and also additional dome-based structures using special coordinate-system solutions based on spherical coordinate systems. It also contains additional structural possibilities like making double layer grids in all geometry forms. The adaptation of formex algebra and the parametric workflow of Grasshopper together give the possibility of quick and easy design and optimization of special truss-grid domes.

Keywords: Parametric design, structural morphology, space structures, spherical coordinate system.

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Authors: Kyoung-il Do, Byung-seok Lee, Hee-guk Chae, Jeong-yun Seo Yong-seo Koo

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In this paper, a Silicon Controlled Rectifier (SCR)-based Electrostatic Discharge (ESD) protection circuit with high holding voltage and high robustness characteristics is proposed. Unlike conventional SCR, the proposed circuit has low trigger voltage and high holding voltage and provides effective ESD protection with latch-up immunity. In addition, the TCAD simulation results show that the proposed circuit has better electrical characteristics than the conventional SCR. A stack technology was used for voltage-specific applications. Consequentially, the proposed circuit has a trigger voltage of 17.60 V and a holding voltage of 3.64 V.

Keywords: ESD, SCR, latch-up, power clamp, holding voltage.

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Authors: Muhaned Zaidi, Ian Grout, Abu Khari bin A’ain

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In this paper, a two-stage op-amp design is considered using both Miller and negative Miller compensation techniques. The first op-amp design uses Miller compensation around the second amplification stage, whilst the second op-amp design uses negative Miller compensation around the first stage and Miller compensation around the second amplification stage. The aims of this work were to compare the gain and phase margins obtained using the different compensation techniques and identify the ability to choose either compensation technique based on a particular set of design requirements. The two op-amp designs created are based on the same two-stage rail-to-rail output CMOS op-amp architecture where the first stage of the op-amp consists of differential input and cascode circuits, and the second stage is a class AB amplifier. The op-amps have been designed using a 0.35mm CMOS fabrication process.

Keywords: Op-amp, rail-to-rail output, Miller compensation, negative Miller capacitance.

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Authors: N.H. Mvungi

Abstract:

This paper addresses control of commutation of switched reluctance (SR) motor without the use of a physical position detector. Rotor position detection schemes for SR motor based on magnetisation characteristics of the motor use normal excitation or applied current /voltage pulses. The resulting schemes are referred to as passive or active methods respectively. The research effort is in realizing an economical sensorless SR rotor position detector that is accurate, reliable and robust to suit a particular application. An effective and reliable means of generating commutation signals of an SR motor based on inductance profile of its stator windings determined using active probing technique is presented. The scheme has been validated online using a 4-phase 8/6 SR motor and an 8-bit processor.

Keywords: Position detection, rotor position, sensorless, switched reluctance, SR.

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Authors: M. Dezvarei, S. Morovati

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In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: Clonal algorithm, proton exchange membrane fuel cell, particle swarm optimization, real valued mutation.

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Authors: Achela K. Fernando, Xiujuan Zhang, Peter F. Kinley

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A feed-forward, back-propagation Artificial Neural Network (ANN) model has been used to forecast the occurrences of wastewater overflows in a combined sewerage reticulation system. This approach was tested to evaluate its applicability as a method alternative to the common practice of developing a complete conceptual, mathematical hydrological-hydraulic model for the sewerage system to enable such forecasts. The ANN approach obviates the need for a-priori understanding and representation of the underlying hydrological hydraulic phenomena in mathematical terms but enables learning the characteristics of a sewer overflow from the historical data. The performance of the standard feed-forward, back-propagation of error algorithm was enhanced by a modified data normalizing technique that enabled the ANN model to extrapolate into the territory that was unseen by the training data. The algorithm and the data normalizing method are presented along with the ANN model output results that indicate a good accuracy in the forecasted sewer overflow rates. However, it was revealed that the accurate forecasting of the overflow rates are heavily dependent on the availability of a real-time flow monitoring at the overflow structure to provide antecedent flow rate data. The ability of the ANN to forecast the overflow rates without the antecedent flow rates (as is the case with traditional conceptual reticulation models) was found to be quite poor.

Keywords: Artificial Neural Networks, Back-propagationlearning, Combined sewer overflows, Forecasting.

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Authors: D. S. A. Nanayakkara, K. J. P. G. Perera

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E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. TheAnalyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling TheAnalyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: Data clustering, data standardization, dimensionality reduction, human-computer interaction, user profiling.

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Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka

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This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.

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Authors: M. H. Korayem, K. Khoshhal, H. Aliakbarpour

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In this paper, a vision based system has been used for controlling an industrial 3P Cartesian robot. The vision system will recognize the target and control the robot by obtaining images from environment and processing them. At the first stage, images from environment are changed to a grayscale mode then it can diverse and identify objects and noises by using a threshold objects which are stored in different frames and then the main object will be recognized. This will control the robot to achieve the target. A vision system can be an appropriate tool for measuring errors of a robot in a situation where the experimental test is conducted for a 3P robot. Finally, the international standard ANSI/RIA R15.05-2 is used for evaluating the path-related characteristics of the robot. To evaluate the performance of the proposed method experimental test is carried out.

Keywords: Robot, Vision, Experiment, Standard.

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Authors: Sandeep Singh Gill, Rajeevan Chandel, Ashwani Chandel

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This paper presents a comparative study of Ant Colony and Genetic Algorithms for VLSI circuit bi-partitioning. Ant colony optimization is an optimization method based on behaviour of social insects [27] whereas Genetic algorithm is an evolutionary optimization technique based on Darwinian Theory of natural evolution and its concept of survival of the fittest [19]. Both the methods are stochastic in nature and have been successfully applied to solve many Non Polynomial hard problems. Results obtained show that Genetic algorithms out perform Ant Colony optimization technique when tested on the VLSI circuit bi-partitioning problem.

Keywords: Partitioning, genetic algorithm, ant colony optimization, non-polynomial hard, netlist, mutation.

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Authors: Boci J., Çabeli P., Shtylla T., Kumbe I.

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The development of the poultry industry in Albania is mainly based on the existence of intensive modern farms with huge capacities, which often are mixed with other forms. Colibacillosis is commonly displayed regardless of the type of breeding, delivering high mortality in poultry industry. The mechanisms with which pathogen enterobacters are able to cause the infection in poultry are not yet clear. The routine diagnose in the field, followed by isolation of E. coli and species of Salmonella genres in reference laboratories cannot lead in classification or full recognition of circulative strains in a territory, if it is not performed a differentiation among the present microorganisms in intensive farms and those in rural areas. In this study were isolated 1.496 strains of E. coli and 378 Salmonella spp. This study, presents distribution of poultry pathogenosity of E.coli and Salmonella spp., based on the usage of innovative diagnostic methods.

Keywords: poultry, E.coli, Salmonella spp., Enterobacter

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Authors: Ekesa B. Nakhauka, De Lange M., Macharia I., Garming H., Ouma E., Birachi E., Van Asten P., Van-Lauwe B., Blomme G.

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Impact of adopting products promoted by the Consortium for Improving Agriculture-based livelihoods in Central Africa (CIALCA) on food and nutrition security was tested. Multi-stage sampling was used to select 7 project mandate areas, 5 villages/mandate area (stratified into action, satellite and control sites) and 913 households. Structured questionnaires were administered; analysis of impact based on comparison between stratums, differences in means tested by ANOVA and significance of difference obtained by Tukey's HSD multiple rank tests. Perception of adequate food sufficiency received a higher rating in action and satellite sites compared to control sites reason being improved agricultural technologies. For >60% of households, worsened food security was due to climatic conditions. Although a higher proportion of households in action and satellite was meeting calorie RDIs in DRC and Burundi the difference was insignificant from control sites. 53% of respondents in control sites indicated a decrease in intake of protein rich foods, this was significantly higher than the proportion in the action (46%) and satellite (41%) sites.

Keywords: Food security, Farmer-households, Nutrition security

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Authors: Jindrich J. Melcher, Marcela Karmazínová

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The paper presents the brief information on particular results of experimental study focused to the problems of behavior of structural plated components made of fiber-cement-based materials and used in building constructions, exposed to atmospheric physical effects given by the weather changes in the summer period. Weather changes represented namely by temperature and rain cause also the changes of the temperature and moisture of the investigated structural components. This can affect their static behavior that means stresses and deformations, which have been monitored as the main outputs of tests performed. Experimental verification is based on the simulation of the influence of temperature and rain using the defined procedure of warming and water sprinkling with respect to the corresponding weather conditions during summer period in the South Moravian region at the Czech Republic, for which the application of these structural components is mainly planned. Two types of components have been tested: (i) glass-fiber-concrete panels used for building façades and (ii) fiber-cement slabs used mainly for claddings, but also as a part of floor structures or lost shuttering, and so on.

Keywords: Atmospheric physical effect, building component, experiment, fiber-cement, glass-fiber-concrete, simulation, static behavior, test, warming, water sprinkling, weather.

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Authors: Shonal Singh, Bibhya Sharma, Jito Vanualailai, Avinesh Prasad

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This paper considers the autonomous navigation problem of multiple n-link nonholonomic mobile manipulators within an obstacle-ridden environment. We present a set of nonlinear acceleration controllers, derived from the Lyapunov-based control scheme, which generates collision-free trajectories of the mobile manipulators from initial configurations to final configurations in a constrained environment cluttered with stationary solid objects of different shapes and sizes. We demonstrate the efficiency of the control scheme and the resulting acceleration controllers of the mobile manipulators with results through computer simulations of an interesting scenario.

Keywords: Artificial potential fields, kinodynamic constraints, Lyapunov-based control scheme, Lyapunov stability, minimum distance technique, nonholonomic manipulator.

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Authors: Dimitri Perrin, Heather J. Ruskin, Martin Crane

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We report on the development of a model to understand why the range of experience with respect to HIV infection is so diverse, especially with respect to the latency period. To investigate this, an agent-based approach is used to extract highlevel behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A network of independent matrices mimics the chain of lymph nodes. Dealing with massively multi-agent systems requires major computational effort. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach and, using the MPI library, are here implemented, tested and optimized. Our current focus is on the various implementations of the data transfer across the network. Three communications strategies are proposed and tested, showing that the most efficient approach is communication based on the natural lymph-network connectivity.

Keywords: HIV, Immune modelling, MPI, Parallelisation.

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Authors: Khairil Iskandar Othman, Zarina Bibi Ibrahim, Mohamed Suleiman

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A parallel block method based on Backward Differentiation Formulas (BDF) is developed for the parallel solution of stiff Ordinary Differential Equations (ODEs). Most common methods for solving stiff systems of ODEs are based on implicit formulae and solved using Newton iteration which requires repeated solution of systems of linear equations with coefficient matrix, I - hβJ . Here, J is the Jacobian matrix of the problem. In this paper, the matrix operations is paralleled in order to reduce the cost of the iterations. Numerical results are given to compare the speedup and efficiency of parallel algorithm and that of sequential algorithm.

Keywords: Backward Differentiation Formula, block, ordinarydifferential equations.

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Authors: Min Wang , Shuyuan Yang

Abstract:

The paper presents a method of designing ultrawide band (UWB) pulse array beamformer in the case of nearfield. Firstly the principle of space-time processing of UWB pulse array is discussed. The radical beampattern transform based on spherical coordinates is employed to solve the nearfield beamforming of UWB pulse array. The frequency invariant technology is considered for the frequency dependent beampattern of UWB pulse array. We use a multirate bank scheme of to implement the FI beamformer of UWB pulse array. By using multirate filters in each element channel, it can make the response of the UWB array to avoid distortion in the whole band. The simulation resultes are given to prove the efficiency and feasibility of this method.

Keywords: UWB pulse array, frequency invariant, multiratebank, nearfield beamformer, radical transform

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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Authors: Shameemraj M. Nadaf, Sipra Behera, Hemant K. Rath, Garima Mishra, Raja Mukhopadhyay, Sumanta Patro

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Microservices architecture has been widely embraced for rapid, frequent, and reliable delivery of complex applications. It enables organizations to evolve their technology stack in various domains. Today, the networking domain is flooded with plethora of devices and software solutions which address different functionalities ranging from elementary operations, viz., switching, routing, firewall etc., to complex analytics and insights based intelligent services. In this paper, we attempt to bring in the microservices based approach for agile and adaptive delivery of network services for any underlying networking technology. We discuss the life cycle management of each individual microservice and a distributed control approach with emphasis for dynamic provisioning, management, and orchestration in an automated fashion which can provide seamless operations in large scale networks. We have conducted validations of the system in lab testbed comprising of Traditional/Legacy and Software Defined Wireless Local Area networks.

Keywords: Microservices architecture, software defined wireless networks, traditional wireless networks, automation, orchestration, intelligent networks, network analytics, seamless management, single pane control, fine-grain control.

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Authors: Chandrakala Varatharajoo, Adelina Binti Asmawi, Nabeel Abdallah Mohammad Abedalaziz

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This study investigated the impact of inflectional and derivational morphemic analysis awareness on ESL secondary school students’ vocabulary learning strategy. The quasi-experimental study was conducted with 106 low proficiency secondary school students in two experimental groups (inflectional and derivational) and one control group. The students’ vocabulary acquisition was assessed through two measures: Morphemic Analysis Test and Vocabulary- Morphemic Test in the pretest and posttest before and after an intervention programme. Results of ANCOVA revealed that both the experimental groups achieved a significant score in Morphemic Analysis Test and Vocabulary-Morphemic Test. However, the inflectional group obtained a fairly higher score than the derivational group. Thus, the results indicated that ESL low proficiency secondary school students performed better on inflectional morphemic awareness as compared to derivatives. The results also showed that the awareness of inflectional morphology contributed more on the vocabulary acquisition. Importantly, learning inflectional morphology can help ESL low proficiency secondary school students to develop both morphemic awareness and vocabulary gain. Theoretically, these findings show that not all morphemes are equally useful to students for their language development. Practically, these findings indicate that morphological instruction should at least be included in remediation and instructional efforts with struggling learners across all grade levels, allowing them to focus on meaning within the word before they attempt the text in large for better comprehension. Also, by methodologically, by conducting individualized intervention and assessment this study provided fresh empirical evidence to support the existing literature on morphemic analysis awareness and vocabulary learning strategy. Thus, a major pedagogical implication of the study is that morphemic analysis awareness strategy is a definite boon for ESL secondary school students in learning English vocabulary.

Keywords: ESL, instruction, morphemic analysis, vocabulary.

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Authors: Nedeljko Cvejic, Artur Łoza, David Bull, Nishan Canagarajah

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In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.

Keywords: Fusion performance measures, image fusion, nonreferencequality measures, objective quality measures.

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Authors: M. K. Bhuyan

Abstract:

The use of human hand as a natural interface for humancomputer interaction (HCI) serves as the motivation for research in hand gesture recognition. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs), as used in MPEG-4, with each VOP corresponding to one semantically meaningful hand position. Next, the key VOPs are selected on the basis of the amount of change in hand shape – for a given key frame in the sequence the next key frame is the one in which the hand changes its shape significantly. Thus, an entire video clip is transformed into a small number of representative frames that are sufficient to represent a gesture sequence. Subsequently, we model a particular gesture as a sequence of key frames each bearing information about its duration. These constitute a finite state machine. For recognition, the states of the incoming gesture sequence are matched with the states of all different FSMs contained in the database of gesture vocabulary. The core idea of our proposed representation is that redundant frames of the gesture video sequence bear only the temporal information of a gesture and hence discarded for computational efficiency. Experimental results obtained demonstrate the effectiveness of our proposed scheme for key frame extraction, subsequent gesture summarization and finally gesture recognition.

Keywords: Hand gesture, MPEG-4, Hausdorff distance, finite state machine.

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Authors: Jihyung Kim, Taejin Kim, Sungho Park, Jun-Dong Cho

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In this paper, the problem of reducing switching activity in on-chip buses at the stage of high-level synthesis is considered, and a high-level low power bus binding based on dynamic bit reordering is proposed. Whereas conventional methods use a fixed bit ordering between variables within a bus, the proposed method switches a bit ordering dynamically to obtain a switching activity reduction. As a result, the proposed method finds a binding solution with a smaller value of total switching activity (TSA). Experimental result shows that the proposed method obtains a binding solution having 12.0-34.9% smaller TSA compared with the conventional methods.

Keywords: bit reordering, bus binding, low power, switching activity matrix

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Authors: Giseob Byun, Ji Yeon Cho, Bong Gyou Lee

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The purpose of this study is to analyze Green IT industry in major developed countries and to suggest overall directions for IT-Energy convergence industry. Recently, IT industry is pointed out as a problem such as environmental pollution, energy exhaustion, and high energy consumption. Therefore, Green IT gets focused which concerns as solution of these problems. However, since it is a beginning stage of this convergence area, there are only a few studies of IT-Energy convergence industry. According to this, this study examined the major developed countries in terms of institution arrangements, resources, markets and companies based on Van de Ven(1999)'s social system framework that shows relationship among key components of industrial infrastructure. Subsequently, the direction of the future study of convergence on IT and Energy industry is proposed.

Keywords: Green IT, Energy industry, Convergence, Social System Framework.

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