Search results for: optimization for learning and data analysis

Authors: Yutaka Takaoka, Mika Ohta, Aki Sugano, Tsuyoshi Oda, Eiichi Maeda, Sumiyo Hanaoka, Masako Matsuura

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Along with the increased morbidity of glaucoma or diabetic retinitis pigmentosa, etc., number of people with vision loss is also increasing in Japan. It is difficult for the visually impaired to learn and acquire braille because most of them are middle-aged. In addition, number of braille teachers are not sufficient and reducing in Japan, and this situation makes more difficult for the visually impaired. Therefore, we research and develop a Web-based e-learning program for tactile braille, that cooperate with braille display and voice assistance.

Keywords: Acquired visually impaired, Braille, e-learning, Tactile braille

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Authors: C. Xavier Mendieta, J. J McArthur

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Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: Building archetypes, data analysis, energy benchmarks, GHG emissions.

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Authors: Ajay Shekhar Pandey, D. Singh, S. K. Sinha

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A clustering based technique has been developed and implemented for Short Term Load Forecasting, in this article. Formulation has been done using Mean Absolute Percentage Error (MAPE) as an objective function. Data Matrix and cluster size are optimization variables. Model designed, uses two temperature variables. This is compared with six input Radial Basis Function Neural Network (RBFNN) and Fuzzy Inference Neural Network (FINN) for the data of the same system, for same time period. The fuzzy inference system has the network structure and the training procedure of a neural network which initially creates a rule base from existing historical load data. It is observed that the proposed clustering based model is giving better forecasting accuracy as compared to the other two methods. Test results also indicate that the RBFNN can forecast future loads with accuracy comparable to that of proposed method, where as the training time required in the case of FINN is much less.

Keywords: Load forecasting, clustering, fuzzy inference.

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Authors: M. Mokhtarzadeh, M. Taheri Qomi, M. Nikafrooz, A. Atashafrooz

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The purpose of the present study was to investigate the effectiveness of using motion graphics as a learning medium on training hearing aids maintenance skills to hearing-impaired children. The statistical population of this study consisted of all children with hearing loss in Ahvaz city, at age 4 to 7 years old. As the sample, 60, whom were selected by multistage random sampling, were randomly assigned to two groups; experimental (30 children) and control (30 children) groups. The research method was experimental and the design was pretest-posttest with the control group. The intervention consisted of a 2-minute motion graphics clip to train hearing aids maintenance skills. Data were collected using a 9-question researcher-made questionnaire. The data were analyzed by using one-way analysis of covariance. Results showed that the training of hearing aids maintenance skills with motion graphics was significantly effective for those children. The results of this study can be used by educators, teachers, professionals, and parents to train children with disabilities or normal students.

Keywords: Hearing-impaired children, hearing aids, hearing aids maintenance skill, and motion graphics.

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Authors: R. Satish, G. Raja Rao

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In this paper a hybrid distributed generation (DG) system connected to isolated load is studied. The DG system consisting of photo voltaic (PV) system, fuel cells, aqua electrolyzer, diesel engine generator and a battery energy storage system. The ambient temperature value of PV is taken as constant to make the output power of PV is directly proportional to the radiation and output power of other DG sources and frequency of the system is controlled by simple integral (I), proportional plus integral (PI), and proportional plus integral and derivative(PID) controllers. A maiden attempt is made to apply a more recent and powerful optimization technique named as bacterial foraging technique for optimization of controllers gains of the proposed hybrid DG system. The system responses with bacterial foraging based controllers are compared with that of classical method. Investigations reveal that bacterial foraging based controllers gives better responses than the classical method and also PID controller is best. Sensitivity analysis is carried out which demonstrates the robustness of the optimized gain values for system loading condition.

Keywords: Aqua electrolyzer, bacterial foraging, battery energy storage system, diesel engine generator, distributed generation, fuel cells, photo voltaic system.

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Authors: S. Habte, K. Ouazzane, P. Patel, S. Patel

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The dynamic and highly competitive nature of the consumer electronics retail industry means that businesses in this industry are experiencing different decision making challenges in relation to pricing, inventory control, consumer satisfaction and product offerings. To overcome the challenges facing retailers and create opportunities, we propose a generic data warehousing solution which can be applied to a wide range of consumer electronics retailers with a minimum configuration. The solution includes a dimensional data model, a template SQL script, a high level architectural descriptions, ETL tool developed using C#, a set of APIs, and data access tools. It has been successfully applied by ASK Outlets Ltd UK resulting in improved productivity and enhanced sales growth.

Keywords: Consumer electronics retail, dimensional data model, data analysis, generic data warehousing, reporting.

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Authors: SangWon Han, MuWook Pyeon, Sujung Moon, DaeKyo Seo

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Recently, technologies based on three-dimensional (3D) space information are being developed and quality of life is improving as a result. Research on real-time digital map (RDM) is being conducted now to provide 3D space information. RDM is a service that creates and supplies 3D space information in real time based on location/shape detection. Research subjects on RDM include the construction of 3D space information with matching image data, complementing the weaknesses of image acquisition using multi-source data, and data collection methods using big data. Using RDM will be effective for space analysis using 3D space information in a U-City and for other space information utilization technologies.

Keywords: RDM, multi-source data, big data, U-City.

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Authors: N. Chitanand

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Given the dynamic nature of the higher education landscape, induction programmes for new academics has become the norm nowadays to support academics negotiate these rough terrain. This study investigates an induction programme for new academics in a higher education institution to establish what difference it has made to participants. The findings revealed that the benefits ranged from creating safe spaces for collaboration and networking to fostering reflective practice and contributing to the scholarship of teaching and learning. The study also revealed that some of the intentions of the programme may not have been achieved, for example transformative learning. This led to questioning whether this intention is an appropriate one given the short duration of the programme and the long, drawn out process of transformation. It may be concluded that the academic induction programme in this study serves to sow the seeds for transformative learning through fostering critically reflective practice. Recommendations for further study could include long term impact of the programme on student learning and success, these being the core business of higher education. It is also recommended that in addition to an induction programme, the university invests in a mentoring programme for new staff and extend the support for academics in order to sustain critical reflection and which may contribute to transformative educational practice.

Keywords: Induction programme, reflective practice, scholarship of teaching, transformative learning.

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Authors: S. M. Anisuzzaman, Sariah Abang, Awang Bono, D. Krishnaiah, N. M. Ismail, G. B. Sandrison

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Wax and asphaltene are high molecular weighted compounds that contribute to the stability of crude oil at a dispersed state. Transportation of crude oil along pipelines from the oil rig to the refineries causes fluctuation of temperature which will lead to the coagulation of wax and flocculation of asphaltenes. This paper focuses on the prevention of wax and asphaltene precipitate deposition on the inner surface of the pipelines by using a wax inhibitor and an asphaltene dispersant. The novelty of this prevention method is the combination of three substances; a wax inhibitor dissolved in a wax inhibitor solvent and an asphaltene solvent, namely, ethylene-vinyl acetate (EVA) copolymer dissolved in methylcyclohexane (MCH) and toluene (TOL) to inhibit the precipitation and deposition of wax and asphaltene. The objective of this paper was to optimize the percentage composition of each component in this inhibitor which can maximize the viscosity reduction of crude oil. The optimization was divided into two stages which are the laboratory experimental stage in which the viscosity of crude oil samples containing inhibitor of different component compositions is tested at decreasing temperatures and the data optimization stage using response surface methodology (RSM) to design an optimizing model. The results of experiment proved that the combination of 50% EVA + 25% MCH + 25% TOL gave a maximum viscosity reduction of 67% while the RSM model proved that the combination of 57% EVA + 20.5% MCH + 22.5% TOL gave a maximum viscosity reduction of up to 61%.

Keywords: Asphaltene, ethylene-vinyl acetate, methylcyclohexane, toluene, wax.

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Authors: S.C. Swain, S. Panda, A.K. Mohanty, C. Ardil

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This paper presents the applications of computational intelligence techniques to economic load dispatch problems. The fuel cost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. In view of the above, both continuous and discontinuous fuel cost equations are considered in the present paper. First, genetic algorithm optimization technique is applied to a 6- generator 26-bus test system having continuous fuel cost equations. Results are compared to conventional quadratic programming method to show the superiority of the proposed computational intelligence technique. Further, a 10-generator system each with three fuel options distributed in three areas is considered and particle swarm optimization algorithm is employed to minimize the cost of generation. To show the superiority of the proposed approach, the results are compared with other published methods.

Keywords: Economic Load Dispatch, Continuous Fuel Cost, Quadratic Programming, Real-Coded Genetic Algorithm, Discontinuous Fuel Cost, Particle Swarm Optimization.

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Authors: Sunita Verma , Divya Tiwari, Ajay Verma

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Water samples were collected from river Pandu at six stations where human and animal activities were high. Composite samples were analyzed for dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD) , pH values during dry and wet seasons as well as the harmattan period. The total data points were used to establish relationships between the parameters and data were also subjected to statistical analysis and expressed as mean ± standard error of mean (SEM) at a level of significance of p<0.05. Regression analysis was carried out to establish relationships if any between studied parameters and relationships in form of scatter plots were obtained between DO/BOD, COD/DO, BOD/COD, COD/pH, BOD/pH and DO/pH. The high to moderate correlation coefficient observed, R2 ranged from 0.68 to 0.15 between these parameters.

Keywords: BOD, DO, COD, pH, Regression analysis.

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Authors: Daniele Losanno, Giorgio Serino

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This paper focuses on parametric analysis of reinforced concrete structures equipped with supplemental damping braces. Practitioners still luck sufficient data for current design of damper added structures and often reduce the real model to a pure damper braced structure even if this assumption is neither realistic nor conservative. In the present study, the damping brace is modelled as made by a linear supporting brace connected in series with the viscous/hysteretic damper. Deformation capacity of existing structures is usually not adequate to undergo the design earthquake. In spite of this, additional dampers could be introduced strongly limiting structural damage to acceptable values, or in some cases, reducing frame response to elastic behavior. This work is aimed at providing useful considerations for retrofit of existing buildings by means of supplemental damping braces. The study explicitly takes into consideration variability of (a) relative frame to supporting brace stiffness, (b) dampers’ coefficient (viscous coefficient or yielding force) and (c) non-linear frame behavior. Non-linear time history analysis has been run to account for both dampers’ behavior and non-linear plastic hinges modelled by Pivot hysteretic type. Parametric analysis based on previous studies on SDOF or MDOF linear frames provide reference values for nearly optimal damping systems design. With respect to bare frame configuration, seismic response of the damper-added frame is strongly improved, limiting deformations to acceptable values far below ultimate capacity. Results of the analysis also demonstrated the beneficial effect of stiffer supporting braces, thus highlighting inadequacy of simplified pure damper models. At the same time, the effect of variable damping coefficient and yielding force has to be treated as an optimization problem.

Keywords: Brace stiffness, dissipative braces, non-linear analysis, plastic hinges, reinforced concrete.

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Authors: Heesung Lee, Joonkyung Sung, Euntai Kim

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This paper proposes a method which reduces power consumption in single-error correcting, double error-detecting checker circuits that perform memory error correction code. Power is minimized with little or no impact on area and delay, using the degrees of freedom in selecting the parity check matrix of the error correcting codes. The genetic algorithm is employed to solve the non linear power optimization problem. The method is applied to two commonly used SEC-DED codes: standard Hamming and odd column weight Hsiao codes. Experiments were performed to show the performance of the proposed method.

Keywords: Error correcting codes, genetic algorithm, non-linearpower optimization, Hamming code, Hsiao code.

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Authors: Khin Fai Chen, Jee-Hou Ho, Eng Hwa Yap

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An Acoustic Micro-Energy Harvester (AMEH) is developed to convert wasted acoustical energy into useful electrical energy. AMEH is mathematically modeled using Lumped Element Modelling (LEM) and Euler-Bernoulli beam (EBB) modelling. An experiment is designed to validate the mathematical model and assess the feasibility of AMEH. Comparison of theoretical and experimental data on critical parameter value such as Mm, Cms, dm and Ceb showed the variances are within 1% to 6%, which is reasonably acceptable. Then, AMEH undergoes bandwidth tuning for performance optimization. The AMEH successfully produces 0.9V/(m/s^2) and 1.79μW/(m^2/s^4) at 60Hz and 400kΩ resistive load which only show variances about 7% compared to theoretical data. At 1g and 60Hz resonance frequency, the averaged power output is about 2.2mW which fulfilled a range of wireless sensors and communication peripherals power requirements. Finally, the design for AMEH is assessed, validated and deemed as a feasible design.

Keywords: Piezoelectric, acoustic, energy harvester, thermoacoustic.

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Authors: A. M. Fahim, G. Saake, A. M. Salem, F. A. Torkey, M. A. Ramadan

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Data clustering is an important data exploration technique with many applications in data mining. The k-means algorithm is well known for its efficiency in clustering large data sets. However, this algorithm is suitable for spherical shaped clusters of similar sizes and densities. The quality of the resulting clusters decreases when the data set contains spherical shaped with large variance in sizes. In this paper, we introduce a competent procedure to overcome this problem. The proposed method is based on shifting the center of the large cluster toward the small cluster, and recomputing the membership of small cluster points, the experimental results reveal that the proposed algorithm produces satisfactory results.

Keywords: K-Means, Data Clustering, Cluster Analysis.

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Authors: Mohd Afif Md Nasir, Faizal Amin NurYunus, Jamaluddin Hashim, Abd Samad Hassan Basari, A. Halim Sahelan

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The aim of this study is to identify the suitability of Virtual Learning Environment (VLE) in welding simulator application towards Computer-Based Training (CBT) in developing skills upon new students at the Advanced Technology Training Center (ADTEC) Batu Pahat, Johor, Malaysia and GIATMARA, Batu Pahat, Johor, Malaysia. The significance of the study is to create a computer-based skills development approach in welding technology among new students in ADTEC and GIATMARA as well as to cultivate the elements of general skills among them. This study is also important in elevating the number of individual knowledge workers (K-workers) working in manufacturing industry in order to achieve a national vision which is to be an industrial nation in the year of 2020. The design of the study is a survey type of research which using questionnaires as the instruments and some 136 students from ADTEC and GIATMARA were interviewed. Descriptive analysis is used to identify the frequency and mean values. The findings of the study show that the welding technology has developed skills in the students because of the application of VLE simulated at a high level and the respondents agreed that the skills could be embedded through the application of the VLE simulator. In summary, the VLE simulator is suitable in welding skills development training in terms of exposing new students with the relevant characteristics of welding skills and at the same time spurring the students’ interest towards learning more about the skills.

Keywords: Computer-Based Training (CBT), knowledge workers (K-workers), virtual learning environment, welding simulator, welding technology.

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Authors: Bhed Bahadur Bista, Danda B. Rawat

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In this paper, we investigate multihop polling and data gathering schemes in layered sensor networks in order to extend the life time of the networks. A network consists of three layers. The lowest layer contains sensors. The middle layer contains so called super nodes with higher computational power, energy supply and longer transmission range than sensor nodes. The top layer contains a sink node. A node in each layer controls a number of nodes in lower layer by polling mechanism to gather data. We will present four types of data gathering schemes: intermediate nodes do not queue data packet, queue single packet, queue multiple packets and aggregate data, to see which data gathering scheme is more energy efficient for multihop polling in layered sensor networks.

Keywords: layered sensor network, polling, data gatheringschemes.

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Authors: Nhat Linh Ho, Thanh-Phong Dao, Shyh-Chour Huang, Hieu Giang Le

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This paper presents a design and optimization for a compliant gripper. The gripper is constructed based on the concept of compliant mechanism with flexure hinge. A passive force regulation mechanism is presented to control the grasping force a micro-sized object instead of using a sensor force. The force regulation mechanism is designed using the planar springs. The gripper is expected to obtain a large range of displacement to handle various sized objects. First of all, the statics and dynamics of the gripper are investigated by using the finite element analysis in ANSYS software. And then, the design parameters of the gripper are optimized via Taguchi method. An orthogonal array L₉ is used to establish an experimental matrix. Subsequently, the signal to noise ratio is analyzed to find the optimal solution. Finally, the response surface methodology is employed to model the relationship between the design parameters and the output displacement of the gripper. The design of experiment method is then used to analyze the sensitivity so as to determine the effect of each parameter on the displacement. The results showed that the compliant gripper can move with a large displacement of 213.51 mm and the force regulation mechanism is expected to be used for high precision positioning systems.

Keywords: Flexure hinge, compliant mechanism, compliant gripper, force regulation mechanism, Taguchi method, response surface methodology, design of experiment.

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Authors: Eftah Bte. Moh @ Hj Abdullah, Izazol Binti Idris, Abd Aziz Bin Abd Shukor

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This study aimed to identify the alignment of understanding and assessment practices among secondary school teachers. The study was carried out using quantitative descriptive study. The sample consisted of 164 teachers who taught Form 1 and 2 from 11 secondary schools in the district of North Kinta, Perak, Malaysia. Data were obtained from 164 respondents who answered Expectation Alignment Understanding and Practices of School Assessment (PEKDAPS) questionnaire. The data were analysed using SPSS 17.0+. The Cronbach’s alpha value obtained through PEKDAPS questionnaire pilot study was 0.86. The results showed that teachers' performance in PEKDAPS based on the mean value was less than 3, which means that perfect alignment does not occur between the understanding and practices of school assessment. Two major PEKDAPS sub-constructs of articulation across grade and age and usability of the system were higher than the moderate alignment of the understanding and practices of school assessment (Min=2.0). The content focused of PEKDAPs sub-constructs which showed lower than the moderate alignment of the understanding and practices of school assessment (Min=2.0). Another two PEKDAPS subconstructs of transparency and fairness and the pedagogical implications showed moderate alignment (2.0). The implications of the study is that teachers need to fully understand the importance of alignment among components of assessment, learning and teaching and learning objectives as strategies to achieve quality assessment process.

Keywords: Alignment, assessment practices, School Based Assessment, understanding.

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Authors: M.I.S. Ismail, Z. Taha

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In this paper, the experimental design of using the Taguchi method is employed to optimize the processing parameters in the plasma arc surface hardening process. The processing parameters evaluated are arc current, scanning velocity and carbon content of steel. In addition, other significant effects such as the relation between processing parameters are also investigated. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the effects of these processing parameters. Through this study, not only the hardened depth increased and surface roughness improved, but also the parameters that significantly affect the hardening performance are identified. Experimental results are provided to verify the effectiveness of this approach.

Keywords: Plasma arc, hardened depth, surface roughness, Taguchi method, optimization.

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, Speech Emotion Recognition, longitudinal biomarker, machine learning.

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Authors: Yeliz Ekinci, Raife Merve Ön

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Nowadays, technological progress is one of the most important components of economic growth and the efficiency of R&D activities is particularly essential for countries. This study is an attempt to analyze the R&D efficiencies of EU countries. The indicators related to R&D efficiencies should be determined in advance in order to use DEA. For this reason a list of input and output indicators are derived from the literature review. Considering the data availability, a final list is given for the numerical analysis for future research.

Keywords: Data envelopment analysis, economic growth, EU Countries, R&D efficiency.

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Authors: Mohammadhosein Hasanbeig, Lacra Pavel

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In this paper, we study a distributed control algorithm for the problem of unknown area coverage by a network of robots. The coverage objective is to locate a set of targets in the area and to minimize the robots’ energy consumption. The robots have no prior knowledge about the location and also about the number of the targets in the area. One efficient approach that can be used to relax the robots’ lack of knowledge is to incorporate an auxiliary learning algorithm into the control scheme. A learning algorithm actually allows the robots to explore and study the unknown environment and to eventually overcome their lack of knowledge. The control algorithm itself is modeled based on game theory where the network of the robots use their collective information to play a non-cooperative potential game. The algorithm is tested via simulations to verify its performance and adaptability.

Keywords: Distributed control, game theory, multi-agent learning, reinforcement learning.

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Authors: R. Maier, S. Thalmann, A. Sandow

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Organizations face challenges supporting knowledge workers due to their particular requirements for an environment supportive of their self-guided learning activities which are important to increase their productivity and to develop creative solutions to non-routine problems. Face-to-face knowledge sharing remains crucial in spite of a large number of knowledge management instruments that aim at supporting a more impersonal transfer of knowledge. This paper first describes the main criteria for a conceptual and technical solution targeted at flexible management of office space that aims at assigning those knowledge workers to the same room that are most likely to thrive when being brought together thus enhancing their knowledge work productivity. The paper reflects on lessons learned from the implementation and operation of such a solution in a project-focused organization and derives several implications for future extensions that target to foster problem solving, informal learning and personal development.

Keywords: informal learning, knowledge work, officemanagement.

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Authors: Radek Malinský, Ivan Jelínek

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This article deals with the popularity of candidates for the president of the United States of America. The popularity is assessed according to public comments on the Web 2.0. Social networking, blogging and online forums (collectively Web 2.0) are for common Internet users the easiest way to share their personal opinions, thoughts, and ideas with the entire world. However, the web content diversity, variety of technologies and website structure differences, all of these make the Web 2.0 a network of heterogeneous data, where things are difficult to find for common users. The introductory part of the article describes methodology for gathering and processing data from Web 2.0. The next part of the article is focused on the evaluation and content analysis of obtained information, which write about presidential candidates.

Keywords: Sentiment Analysis, Web 2.0, Webometrics.

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Authors: Mohamed EL Boujnouni, Mohamed Jedra, Noureddine Zahid

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Support Vector Domain Description (SVDD) is one of the best-known one-class support vector learning methods, in which one tries the strategy of using balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. As all kernel-based learning algorithms its performance depends heavily on the proper choice of the kernel parameter. This paper proposes a new approach to select kernel's parameter based on maximizing the distance between both gravity centers of normal and abnormal classes, and at the same time minimizing the variance within each class. The performance of the proposed algorithm is evaluated on several benchmarks. The experimental results demonstrate the feasibility and the effectiveness of the presented method.

Keywords: Gravity centers, Kernel’s parameter, Support Vector Domain Description, Variance.

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Authors: Farhat Hajer, Khir Tahar, Cherni Rafik, Dakhli Radhouen, Ammar Ben Brahim

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This paper presents the energy and exergy optimization of a real gas turbine power plant performance of 100 MW of power, installed in the South East of Tunisia. A simulation code is established using the EES (Engineering Equation Solver) software. The parameters considered are those of the actual operating conditions of the gas turbine thermal power station under study. The results show that thermal and exergetic efficiency decreases with the increase of the ambient temperature. Air excess has an important effect on the thermal efficiency. The emission of NOx rises in the summer and decreases in the winter. The obtained rates of NOx are compared with measurements results.

Keywords: Efficiency, exergy, gas turbine, temperature.

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Authors: Ahmad T. Al-Taani, Noor Aldeen K. Al-Awad

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In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web-pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.

Keywords: Text classification, HTML, web pages, machine learning, fuzzy logic, Arabic web pages.

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Authors: Stuart Palmer, Dale Holt

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This paper presents a large scale, quantitative investigation of the impact of discipline differences on the student experience of using an online learning environment (OLE). Based on a representative sample of 2526 respondents, a number of significant differences in the mean rating by broad discipline area of the importance of, and satisfaction with, a range of elements of an OLE were found. Broadly speaking, the Arts and Science and Technology discipline areas reported the lowest importance and satisfaction ratings for the OLE, while the Health and Behavioural Sciences area was the most satisfied with the OLE. A number of specific, systematic discipline differences are reported and discussed. Compared to the observed significant differences in mean importance ratings, there were fewer significant differences in mean satisfaction ratings, and those that were observed were less systematic than for importance ratings.

Keywords: Discipline difference, learning management system, online learning environment, student evaluation.

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Authors: Mikel Niño, Roberto V. Zicari, Todor Ivanov, Kim Hee, Naveed Mushtaq, Marten Rosselli, Concha Sánchez-Ocaña, Karsten Tolle, José Miguel Blanco, Arantza Illarramendi, Jörg Besier, Harry Underwood

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One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or “common good”, covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to “classical” data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.

Keywords: Data-Driven projects, humanitarian operations, personal and sensitive data, social good, stakeholders analysis.

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