Search results for: Strategic performance assessment systems

Authors: Zhuomin Zou, Thijs Van Landeghem, Elke Gruyaert

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Using supplementary cementitious materials, such as ground granulated blast-furnace slag (GGBFS) and limestone to replace Portland cement (PC) is a promising method to reduce the carbon emissions from cement production. To efficiently use GGBFS and limestone, it is necessary to carefully select the particle size distribution (PSD) of the binders. This study investigated the effects of the PSD of binders on the performance of slag-limestone ternary cement. Based on the PSD parameters of the binders, three types of ternary cements with a similar overall PSD were designed, i.e., No.1 fine GGBFS, medium PC, and coarse limestone; No.2 fine limestone, medium PC, and coarse GGBFS; No.3. fine PC, medium GGBFS, and coarse limestone. The binder contents in the ternary cements were 50% PC, 40% slag, and 10% limestone. The mortar performance of the three ternary cements was investigated in terms of flow table value, strength at 28 days, carbonation resistance and non-steady state chloride migration resistance at 28 days. Results show that ternary cement with fine limestone (No.2) has the weakest performance among the three ternary cements. Ternary cements with fine slag (No.1) show an overall comparable performance to ternary cement with fine PC (No.3). Moreover, the chloride migration coefficient of ternary cements with fine slag (No.1) is significantly lower than the other two ternary cements.

Keywords: Limestone, particle size distribution, slag, ternary cement.

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Authors: Modreck Gomo

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The evolution of groundwater chemistry and its quality is largely controlled by hydrogeochemical processes and their understanding is therefore important for groundwater quality assessments and protection of the water resources. A study was conducted in Bloemfontein town of South Africa to assess and compare the groundwater chemistry and quality characteristics in an alluvial aquifer and single-plane fractured-rock aquifers. 9 groundwater samples were collected from monitoring boreholes drilled into the two aquifer systems during a once-off sampling exercise. Samples were collected through low-flow purging technique and analysed for major ions and trace elements. In order to describe the hydrochemical facies and identify dominant hydrogeochemical processes, the groundwater chemistry data are interpreted using stiff diagrams and principal component analysis (PCA), as complimentary tools. The fitness of the groundwater quality for domestic and irrigation uses is also assessed. Results show that the alluvial aquifer is characterised by a Na-HCO₃ hydrochemical facie while fractured-rock aquifer has a Ca-HCO₃ facie. The groundwater in both aquifers originally evolved from the dissolution of calcite rocks that are common on land surface environments. However the groundwater in the alluvial aquifer further goes through another evolution as driven by cation exchange process in which Na in the sediments exchanges with Ca²⁺ in the Ca-HCO₃ hydrochemical type to result in the Na-HCO₃ hydrochemical type. Despite the difference in the hydrogeochemical processes between the alluvial aquifer and single-plane fractured-rock aquifer, this did not influence the groundwater quality. The groundwater in the two aquifers is very hard as influenced by the elevated magnesium and calcium ions that evolve from dissolution of carbonate minerals which typically occurs in surface environments. Based on total dissolved levels (600-900 mg/L), groundwater quality of the two aquifer systems is classified to be of fair quality. The negative potential impacts of the groundwater quality for domestic uses are highlighted.

Keywords: Alluvial aquifer, fractured-rock aquifer, groundwater quality, hydrogeochemical processes.

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Authors: Sangsuree Vasupongayya

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Fair share objective has been included into the goaloriented parallel computer job scheduling policy recently. However, the previous work only presented the overall scheduling performance. Thus, the per-user performance of the policy is still lacking. In this work, the details of per-user fair share performance under the Tradeoff-fs(Tx:avgX) policy will be further evaluated. A basic fair share priority backfill policy namely RelShare(1d) is also studied. The performance of all policies is collected using an event-driven simulator with three real job traces as input. The experimental results show that the high demand users are usually benefited under most policies because their jobs are large or they have a lot of jobs. In the large job case, one job executed may result in over-share during that period. In the other case, the jobs may be backfilled for performances. However, the users with a mixture of jobs may suffer because if the smaller jobs are executing the priority of the remaining jobs from the same user will be lower. Further analysis does not show any significant impact of users with a lot of jobs or users with a large runtime approximation error.

Keywords: deviation, fair share, discrepancy search, priority scheduling.

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Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfil requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: Single classifier, machine learning, ensemble learning, multi-sensor target tracking.

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Authors: Chechen Liao, Chin Yi Yang

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Although several factors that affect learning to program have been identified over the years, there continues to be no indication of any consensus in understanding why some students learn to program easily and quickly while others have difficulty. Seldom have researchers considered the problem of how to help the students enhance the programming learning outcome. The research had been conducted at a high school in Taiwan. Students participating in the study consist of 330 tenth grade students enrolled in the Basic Computer Concepts course with the same instructor. Two types of training methods-instruction-oriented and exploration-oriented were conducted. The result of this research shows that the instruction-oriented training method has better learning performance than exploration-oriented training method.

Keywords: Learning performance, programming learning, TDD, training method.

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Authors: Cemil Turan, Mohammad Shukri Salman

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The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The proposed algorithm provided high performance even if the input signal is highly correlated. In this work, we investigate the performance of the proposed TD-LMS algorithm for a large number of filter tap which is also a critical issue for standard LMS algorithm. Additionally, the optimum value of the most important parameter is calculated for all experiments. Moreover, the convergence analysis of the proposed algorithm is provided. The performance of the proposed algorithm has been compared to different algorithms in a sparse system identification setting of different sparsity levels and different number of filter taps. Simulations have shown that the proposed algorithm has prominent performance compared to the other algorithms.

Keywords: Adaptive filtering, sparse system identification, VSSLMS algorithm, TD-LMS algorithm.

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Authors: Helia Barzegar Sedigh, Farzaneh Hamedi, Payam Ashtari

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There are some limitations in common structural systems, such as providing appropriate lateral stiffness, adequate ductility, and architectural openings at the same time. Consequently, the concept of T-Resisting Frame (TRF) has been introduced to overcome all these deficiencies. The configuration of TRF in this study is a Vertical Plate Girder (VPG) which is placed within the span and two Horizontal Plate Girders (HPGs) connect VPG to side columns at each story level by the use of rigid connections. System performance is improved by utilizing rigid connections in side columns base joint. Shear yield of HPGs causes energy dissipation in TRF; therefore, high plastic deformation in web of HPGs and VPG affects the ductility of system. Moreover, in order to prevent shear buckling in web of TRF’s members and appropriate criteria for placement of web stiffeners are applied. In this paper, an experimental study is conducted by applying cyclic loading and using finite element models and numerical studies such as push over method are assessed on shear and flexural yielding of HPGs. As a result, seismic parameters indicate adequate lateral stiffness, and high ductility factor of 6.73, and HPGs’ shear yielding achieved as a proof of TRF’s better performance.

Keywords: Experimental study, finite element model, flexural and shear yielding, T-resisting frame.

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Authors: S. M. Gupta, Vanita Aggarwal, Som Nath Sachdeva

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The work reported through this paper is an experimental work conducted on High Performance Concrete (HPC) with super plasticizer with the aim to develop some models suitable for prediction of compressive strength of HPC mixes. In this study, the effect of varying proportions of fly ash (0% to 50% @ 10% increment) on compressive strength of high performance concrete has been evaluated. The mix designs studied were M30, M40 and M50 to compare the effect of fly ash addition on the properties of these concrete mixes. In all eighteen concrete mixes that have been designed, three were conventional concretes for three grades under discussion and fifteen were HPC with fly ash with varying percentages of fly ash. The concrete mix designing has been done in accordance with Indian standard recommended guidelines. All the concrete mixes have been studied in terms of compressive strength at 7 days, 28 days, 90 days, and 365 days. All the materials used have been kept same throughout the study to get a perfect comparison of values of results. The models for compressive strength prediction have been developed using Linear Regression method (LR), Artificial Neural Network (ANN) and Leave-One-Out Validation (LOOV) methods.

Keywords: ANN, concrete mixes, compressive strength, fly ash, high performance concrete, linear regression, strength prediction models.

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

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This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. Crisp description for a concept usually cannot represent human knowledge completely and practically. In the proposed Learning Classifier System initial population is constructed as a random collection of HPR–trees (related production rules) and crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is suggested for the proposed system and based on Subsumption Matrix (SM), a suitable fitness function is proposed. Suitable genetic operators are proposed for the chosen chromosome representation method. For implementing reinforcement a suitable reward and punishment scheme is also proposed. Experimental results are presented to demonstrate the performance of the proposed system.

Keywords: Hierarchical Production Rule, Data Mining, Learning Classifier System, Fuzzy Subsumption Relation, Subsumption matrix, Reinforcement Learning.

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Authors: Amira Kheriji Abbes, Faouzi Bouani, Mekki Ksouri

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Model Predictive Control (MPC) is an established control technique in a wide range of process industries. The reason for this success is its ability to handle multivariable systems and systems having input, output or state constraints. Neverthless comparing to PID controller, the implementation of the MPC in miniaturized devices like Field Programmable Gate Arrays (FPGA) and microcontrollers has historically been very small scale due to its complexity in implementation and its computation time requirement. At the same time, such embedded technologies have become an enabler for future manufacturing enterprisers as well as a transformer of organizations and markets. In this work, we take advantage of these recent advances in this area in the deployment of one of the most studied and applied control technique in the industrial engineering. In this paper, we propose an efficient firmware for the implementation of constrained MPC in the performed STM32 microcontroller using interior point method. Indeed, performances study shows good execution speed and low computational burden. These results encourage to develop predictive control algorithms to be programmed in industrial standard processes. The PID anti windup controller was also implemented in the STM32 in order to make a performance comparison with the MPC. The main features of the proposed constrained MPC framework are illustrated through two examples.

Keywords: Embedded software, microcontroller, constrainedModel Predictive Control, interior point method, PID antiwindup, Keil tool, C/Cµ language.

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Authors: Seyedeh Belin Tavakoly Sany, H. Rosli, R. Majid, S. Aishah

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In this study, water monitoring was performed from Nov. 2012 to Oct. 2013 to assess water quality and evaluate the spatial and temporal distribution of physicochemical and biological variables in water. Water samples were collected from 10 coastal water stations of West Port. In the case of water-quality assessment, multi-metric indices and operational indicators have been proposed to classify the trophic status at different stations. The trophic level of West Port coastal water ranges from eutrophic to hypertrophic. Chl-a concentration was used to estimate the biological response of phytoplankton biomass and indicated eutrophic conditions in West Port and mesotrophic conditions at the control site. During the study period, no eutrophication events or secondary symptoms occurred, which may be related to hydrodynamic turbulence and water exchange, which prevent the development of eutrophic conditions in the West Port.

Keywords: Water quality, multi-metric indices, operational indicator, Malaysia, West Port.

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Authors: Liyana Zahid, Mohd Fareq Abd Malek, Ee Meng Cheng, Wei Wen Liu, Yeng Seng Lee, Muhammad Nadeem Iqbal, Fwen Hoon Wee, Farrah Salwani Abdullah

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One of the parameters that affect the performance of microwave absorbers is the shape of the absorbers. This paper shows the performance (reflection loss) of truncated pyramidal and truncated wedge microwave absorbers in the range frequency between 8.2 to 12.4 GHz (X-Band) in simulation. The material used is sugarcane bagasse (SCB) which is one of the new materials that used to fabricate the microwave absorber. The complex permittivity was measured using Agilent dielectric probe technique. The designs were simulated using CST Microwave Studio Software. The reflection losses between these two shapes were compared.

Keywords: Microwave Absorber, Reflection Loss, Sugarcane Bagasse (SCB), X- Band.

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Authors: Naveed Ur Rehman, Rehan Jamil, Irfan Jamil

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In this paper, we regard as a coded transmission over a frequency-selective channel. We plan to study analytically the convergence of the turbo-detector using a maximum a posteriori (MAP) equalizer and a MAP decoder. We demonstrate that the densities of the maximum likelihood (ML) exchanged during the iterations are e-symmetric and output-symmetric. Under the Gaussian approximation, this property allows to execute a one-dimensional scrutiny of the turbo-detector. By deriving the analytical terminology of the ML distributions under the Gaussian approximation, we confirm that the bit error rate (BER) performance of the turbo-detector converges to the BER performance of the coded additive white Gaussian noise (AWGN) channel at high signal to noise ratio (SNR), for any frequency selective channel.

Keywords: MAP, ML, SNR, Decoder, BER, Coded transmission.

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Authors: Aleksander Nawrat, Karol Jędrasiak, Artur Ryt, Dawid Sobel

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The goal of the article is to present a novel Multimedia Firearms Training System. The system was developed in order to compensate for major problems of existing shooting training systems. The designed and implemented solution can be characterized by five major advantages: algorithm for automatic geometric calibration, algorithm of photometric recalibration, firearms hit point detection using thermal imaging camera, IR laser spot tracking algorithm for after action review analysis, and implementation of ballistics equations. The combination of the abovementioned advantages in a single multimedia firearms training system creates a comprehensive solution for detecting and tracking of the target point usable for shooting training systems and improving intervention tactics of uniformed services. The introduced algorithms of geometric and photometric recalibration allow the use of economically viable commercially available projectors for systems that require long and intensive use without most of the negative impacts on color mapping of existing multi-projector multimedia shooting range systems. The article presents the results of the developed algorithms and their application in real training systems.

Keywords: Firearms shot detection, geometric recalibration, photometric recalibration, IR tracking algorithm, thermography, ballistics.

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Authors: N. D. Osman, M. S. Salikin, M. I. Saripan

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CT assessment of postoperative spine is challenging in the presence of metal streak artifacts that could deteriorate the quality of CT images. In this paper, we studied the influence of different acquisition parameters on the magnitude of metal streaking. A water-bath phantom was constructed with metal insertion similar with postoperative spine assessment. The phantom was scanned with different acquisition settings and acquired data were reconstructed using various reconstruction settings. Standardized ROIs were defined within streaking region for image analysis. The result shows increased kVp and mAs enhanced SNR values by reducing image noise. Sharper kernel enhanced image quality compared to smooth kernel, but produced more noise in the images with higher CT fluctuation. The noise between both kernels were significantly different (P <0.05) with increment of noise in the bone kernel images (mean difference = 54.78). The technical settings should be selected appropriately to attain the acceptable image quality with the best diagnostic value.

Keywords: Computed tomography, metal streak, noise, CT fluctuation.

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Authors: M.Paroncini, F.Corvaro, G.Nardini, S.Pistolesi

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The development of renewable energies - particularly energy from wind, water, solar power and biomass - is a central aim of the European Commission's energy policy. There are several reasons for this choice: renewable energies are sustainable, nonpolluting, widely available and clean. Increasing the share of renewable energy in the energy balance enhances sustainability. It also helps to improve the security of energy supply by reducing the Community's growing dependence on imported energy sources.In this paper it was studied the possibility to realize three photovoltaic systems in the Italian Natural Park “Gola della Rossa e di Frasassi". The first photovoltaic system is a grid-connected system for Services and Documentation Center of Castelletta with a nominal power of about 6 kWp. The second photovoltaic system is a grid-connected integrated system on the ticket office-s roof with a nominal power of about 4 kWp. The third project is set up by five grid-connected systems integrated on the roofs of the bungalows in Natural Park-s tourist camping with a nominal power of about 10 kWp. The electricity which is generated by all these plants is purchased according to the Italian program called “Conto Energia". Economical analysis and the amount of the avoided CO2 emissions are elaborated for these photovoltaic systems.

Keywords: CO2 emissions, conto energia, photovoltaic systems.

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Authors: Md. Ashikur Rahman Khan, M. M. Rahman

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In electrical discharge machining (EDM), a complete and clear theory has not yet been established. The developed theory (physical models) yields results far from reality due to the complexity of the physics. It is difficult to select proper parameter settings in order to achieve better EDM performance. However, modelling can solve this critical problem concerning the parameter settings. Therefore, the purpose of the present work is to develop mathematical model to predict performance characteristics of EDM on Ti-5Al-2.5Sn titanium alloy. Response surface method (RSM) and artificial neural network (ANN) are employed to develop the mathematical models. The developed models are verified through analysis of variance (ANOVA). The ANN models are trained, tested, and validated utilizing a set of data. It is found that the developed ANN and mathematical model can predict performance of EDM effectively. Thus, the model has found a precise tool that turns EDM process cost-effective and more efficient.

Keywords: Analysis of variance, artificial neural network, material removal rate, modelling, response surface method, surface finish.

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Authors: Marie Mikušová, Viktorie Janečková

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Measurement and the following evaluation of performance represent important part of management. The paper focuses on indicators as the basic elements of performance measurement system. It emphasizes a necessity of searching requirements for quality indicators so that they can become part of the useful system. It introduces standpoints for a systematic dividing of indicators so that they have as high as possible informative value of background sources for searching, analysis, designing and using of indicators. It draws attention to requirements for indicators' quality and at the same it deals with some dangers decreasing indicator's informative value. It submits a draft of questions that should be answered at the construction of indicator. It is obvious that particular indicators need to be defined exactly to stimulate the desired behavior in order to attain expected results. In the enclosure a concrete example of the defined indicator in the concrete conditions of a small firm is given. The authors of the paper pay attention to the fact that a quality indicator makes it possible to get to the basic causes of the problem and include the established facts into the company information system. At the same time they emphasize that developing of a quality indicator is a prerequisite for the utilization of the system of measurement in management.

Keywords: performance, measurement, firm, indicator

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Authors: Chen-Chien Hsu, Chun-Hui Gao

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In this paper, a PSO-based approach is proposed to derive a digital controller for redesigned digital systems having an interval plant based on resemblance of the extremal gain/phase margins. By combining the interval plant and a controller as an interval system, extremal GM/PM associated with the loop transfer function can be obtained. The design problem is then formulated as an optimization problem of an aggregated error function revealing the deviation on the extremal GM/PM between the redesigned digital system and its continuous counterpart, and subsequently optimized by a proposed PSO to obtain an optimal set of parameters for the digital controller. Computer simulations have shown that frequency responses of the redesigned digital system having an interval plant bare a better resemblance to its continuous-time counter part by the incorporation of a PSO-derived digital controller in comparison to those obtained using existing open-loop discretization methods.

Keywords: Digital redesign, Extremal systems, Particle swarm optimization, Uncertain interval systems

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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: Yassine Jadi, Lin Jie

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In order to serve the society in an electronic manner, many developing countries have launched tremendous e-government projects. The strategies of development and implementation e-government system have reached different levels, and to ensure consistency of development, the governments need to evaluate e-government performance. The United nation has design e-government development ranking index (EGDI) that rely on three indexes, Online service index (OSI), Telecommunication Infrastructure index (TII), and human capital index( HCI) which are not reflecting the interaction between a government and their citizens. Based on data envelopment analyses (DEA) technique, we are using E-participating index (EPI) as an output of government effort to evaluate the performance of e-government system. Therefore, the ranking index can be achieved in efficiency manner.

Keywords: E-government, DEA, efficiency measurement, EGDI.

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Authors: M. Staníčková

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The paper deals with an application of quantitative analysis – the Data Envelopment Analysis (DEA) method to performance evaluation of the European Union Member States, in the reference years 2000 and 2011. The main aim of the paper is to measure efficiency changes over the reference years and to analyze a level of productivity in individual countries based on DEA method and to classify the EU Member States to homogeneous units (clusters) according to efficiency results. The theoretical part is devoted to the fundamental basis of performance theory and the methodology of DEA. The empirical part is aimed at measuring degree of productivity and level of efficiency changes of evaluated countries by basic DEA model – CCR CRS model, and specialized DEA approach – the Malmquist Index measuring the change of technical efficiency and the movement of production possibility frontier. Here, DEA method becomes a suitable tool for setting a competitive/uncompetitive position of each country because there is not only one factor evaluated, but a set of different factors that determine the degree of economic development.

Keywords: CCR CRS model, cluster analysis, DEA method, efficiency, EU, Malmquist index, performance.

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Authors: Nedjima Mouhoubi, Souad Sassi Boudemagh

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In this paper, we will try to demonstrate the importance of the project approach in the urban to deal with uncertainty, the importance of the involvement of all stakeholders in the urban project process and that the absence of an actor can lead to project failure but also the importance of the urban project management. These points are handled through the following questions: Does the urban adhere to the theory of complexity? Does the project approach bring hope and solution to make urban planning "sustainable"? How converging visions of actors for the same project? Is the management of urban project the solution to support the urban project approach?

Keywords: Strategic planning, project, urban project stakeholders, management.

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Authors: L. A. Muhammad, M. S. Argungu

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Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

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Authors: M. E. Rahman, D. Sujan, V. Pakrashi, P. Fanning

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The predictability of masonry arch bridges and their behaviour is widely considered doubtful due to the lack of knowledge about the conditions of a given masonry arch bridge. The assessment methods for masonry arch bridges are MEXE, ARCHIE, RING and Frame Analysis Method. The material properties of the masonry and fill material are extremely difficult to determine accurately. Consequently, it is necessary to examine the effect of load dispersal angle through the fill material, the effect of variations in the stiffness of the masonry, the tensile strength of the masonry mortar continuum and the compressive strength of the masonry mortar continuum. It is also important to understand the effect of fill material on load dispersal angle to determine their influence on ratings. In this paper a series of parametric studies, to examine the sensitivity of assessment ratings to the various sets of input data required by the frame analysis method, are carried out.

Keywords: Arch Bridge, Frame Analyses Method, Masonry

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Authors: Yucel Ugurlu

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This paper explains a novel approach to human interactive e-learning systems using head posture images. Students- face and hair information are used to identify a human presence and estimate the gaze direction. We then define the human-computer interaction level and test the definition using ten students and seventy different posture images. The experimental results show that head posture images provide adequate information for increasing human-computer interaction in e-learning systems.

Keywords: E-learning, image segmentation, human-presence, gaze-direction, human-computer interaction, LabVIEW

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Authors: Osuagwu Justine Ugochukwu, Sazali Abd Wahab, Sunday Sunday Akpan

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Investigating the effects of transformational and transactional leadership styles on the performance of healthcare employees at the University Teaching Hospital (UNTH) in Enugu, Nigeria, was the goal of the research. The respondents were asked to fill out a structured questionnaire. The respondents were chosen using a straightforward random sampling technique and consisted of 370 health workers at the hospital. The result of the analysis revealed that transactional and transformational leadership style has a positive while ambidextrous leadership has a negative effect on healthcare workers' performance in UNTH, Enugu. Therefore, the management of public hospitals that have the capacity to change their top management approach to leadership styles will gain substantial support from their employees’ thereby increasing organizational commitment and performance among health workers. This will have remarkable social implications, one of which is a change in the work culture and attitude of medical personnel from the seemingly anti-community of patients to friendly engagement and treatment of patients leading to a harmonious coexistence among these individuals in society. Investigating ambidextrous leadership and the use of nonparametric analysis is unique and has brought knowledge to leadership literature.

Keywords: Workers’ performance, transformational leadership, transactional leadership, governance quality, ambidextrous leadership.

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Authors: Mohamed M. Saleh, Khalid S. Al-Hagla

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By taking advantage of computer-s processing power, an unlimited number of variations and parameters in both spatial and environmental can be provided while following the same set of rules and constraints. This paper focuses on using the tools of parametric urbanism towards a more responsive environmental and sustainable urban morphology. It presents an understanding to Parametric Urban Comfort Envelope (PUCE) as an interactive computational assessment urban model. In addition, it investigates the applicability potentials of this model to generate an optimized urban form to Borg El Arab city (a new Egyptian Community) concerning the human comfort values specially wind and solar envelopes. Finally, this paper utilizes its application outcomes -both visual and numerical- to extend the designer-s limitations by decrease the concern of controlling and manipulation of geometry, and increase the designer-s awareness about the various potentials of using the parametric tools to create relationships that generate multiple geometric alternatives.

Keywords: Assessment model, human comfort, parametric urbanism, sustainable urban morphology.

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Authors: Patcharin Saechan, Isares Dhuchakallaya

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Thermoacoustic refrigerator is a cooling device which uses the acoustic waves to produce the cooling effect. The aim of this paper is to explore the experimental and numerical feasibility of a standing-wave thermoacoustic refrigerator. The effects of the stack length, position of stack and operating frequency on the cooling performance are carried out. The circular pore stacks are tested under the atmospheric pressure. A low-cost loudspeaker is used as an acoustic driver. The results show that the location of stack installed in resonator tube has a greater effect on the cooling performance, than the stack length and operating frequency, respectively. The temperature difference across the ends of stack can be generated up to 13.7°C, and the temperature of cold-end is dropped down by 5.3°C from the ambient temperature.

Keywords: Cooling performance, Refrigerator, Standing-wave, Thermoacoustics.

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Authors: Mohsen Hayati, Yazdan Shirvany

Abstract:

In this paper, the application of neural networks to study the design of short-term load forecasting (STLF) Systems for Illam state located in west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STLF systems was used. Our study based on MLP was trained and tested using three years (2004-2006) data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STLF systems.

Keywords: Artificial neural networks, Forecasting, Multi-layer perceptron.

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