Search results for: and Performance Evaluation.

Authors: S. M. Thahab, H. Abu Hassan, Z. Hassan

Abstract:

The InAlGaN alloy has only recently began receiving serious attention into its growth and application. High quality InGaN films have led to the development of light emitting diodes (LEDs) and blue laser diodes (LDs). The quaternary InAlGaN however, represents a more versatile material since the bandgap and lattice constant can be independently varied. We report an ultraviolet (UV) quaternary InAlGaN multi-quantum wells (MQWs) LD study by using the simulation program of Integrated System Engineering (ISE TCAD). Advanced physical models of semiconductor properties were used in order to obtain an optimized structure. The device performance which is affected by piezoelectric and thermal effects was studied via drift-diffusion model for carrier transport, optical gain and loss. The optical performance of the UV LD with different numbers of quantum wells was numerically investigated. The main peak of the emission wavelength for double quantum wells (DQWs) was shifted from 358 to 355.8 nm when the forward current was increased. Preliminary simulated results indicated that better output performance and lower threshold current could be obtained when the quantum number is four, with output power of 130 mW and threshold current of 140 mA.

Keywords: Nitride semiconductors, InAlGaN quaternary, UVLD, numerical simulation.

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Authors: A. Sivakumar, K. Srinivasan

Abstract:

The main objective of the study is focused in producing slag based geopolymer concrete obtained with the addition of alkali activator. Test results indicated that the reaction of silicates in slag is based on the reaction potential of sodium hydroxide and the formation of alumino-silicates. The study also comprises on the evaluation of the efficiency of polymer reaction in terms of the strength gain properties for different geopolymer mixtures. Geopolymer mixture proportions were designed for different binder to total aggregate ratio (0.3 & 0.45) and fine to coarse aggregate ratio (0.4 & 0.8). Geopolymer concrete specimens casted with normal curing conditions reported a maximum 28 days compressive strength of 54.75 MPa. The addition of glued steel fibres at 1.0% Vf in geopolymer concrete showed reasonable improvements on the compressive strength, split tensile strength and flexural properties of different geopolymer mixtures. Further, comparative assessment was made for different geopolymer mixtures and the reinforcing effects of steel fibres were investigated in different concrete matrix.

Keywords: Accelerators, Alkali activators, Geopolymer, Hot air oven curing, Polypropylene fibres, Slag, Steam curing, Steel fibres.

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Authors: Junting Xiang, Jörg Uwe Schlüter, Fei Duan

Abstract:

The miniaturization of gas turbines promises many advantages. Miniature gas turbines can be used for local power generation or the propulsion of small aircraft, such as UAV and MAV. However, experience shows that the miniaturization of conventional gas turbines, which are optimized at their current large size, leads to a substantial loss of efficiency and performance at smaller scales. This may be due to a number of factors, such as the Reynolds-number effect, the increased heat transfer, and manufacturing tolerances. In the present work, we focus on computational investigations of the Reynolds number effect and the wall heat transfer on the performance of axial compressor during its size change. The NASA stage 35 compressor is selected as the configuration in this study and computational fluid dynamics (CFD) is used to carry out the miniaturization process and simulations. We perform parameter studies on the effect of Reynolds number and wall thermal conditions. Our results indicate a decrease of efficiency, if the compressor is miniaturized based on its original geometry due to the increase of viscous effects. The increased heat transfer through wall has only a small effect and will actually benefit compressor performance based on our study.

Keywords: Axial compressor, CFD, heat transfer, miniature gas turbines, Reynolds number.

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Authors: Abu Qudeiri Jaber, Yamamoto Hidehiko Rizauddin Ramli

Abstract:

To create a solution for a specific problem in machine learning, the solution is constructed from the data or by use a search method. Genetic algorithms are a model of machine learning that can be used to find nearest optimal solution. While the great advantage of genetic algorithms is the fact that they find a solution through evolution, this is also the biggest disadvantage. Evolution is inductive, in nature life does not evolve towards a good solution but it evolves away from bad circumstances. This can cause a species to evolve into an evolutionary dead end. In order to reduce the effect of this disadvantage we propose a new a learning tool (criteria) which can be included into the genetic algorithms generations to compare the previous population and the current population and then decide whether is effective to continue with the previous population or the current population, the proposed learning tool is called as Keeping Efficient Population (KEP). We applied a GA based on KEP to the production line layout problem, as a result KEP keep the evaluation direction increases and stops any deviation in the evaluation.

Keywords: Genetic algorithms, Layout problem, Machinelearning, Production system.

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Authors: J. Rizk, M. H. Nagrial

Abstract:

The paper aims to show that implementing different types of reflectors in solar energy systems, will dramatically improve energy production by means of concentrating and intensifying more sunlight onto a solar cell. The Solar Intensifier unit is designed to increase efficiency and performance of a set of solar panels. The unit was fabricated and tested. The experimental results show good improvement in the performance of the solar energy system.

Keywords: Renewable Energy, Power optimization, Solar Energy.

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Authors: Zainul Huda, Muhammad Hani Ajani

Abstract:

The design, manufacture, and operation of thin-walled pressure vessels must be based on maximum safe operating pressure and an adequate factor of safety (FoS). This research paper first reports experimental evaluation of longitudinal and hoops stresses based on working pressure as well as maximum pressure; and then includes a critical study of factor of safety (FoS) in the design of a glass fiber pressure vessel. Experimental work involved the use of measuring instruments and the readings from pressure gauges. Design calculations involved the computations of design stress and FoS; the latter was based on breaking strength of 55 MPa for the glass fiber (pressure-vessel material). The experimentally determined FoS value has been critically compared with the general FoS allowed in the design of glass fiber pressure vessels.

Keywords: Thin-walled pressure vessel, hoop stress, longitudinal stress, factor of safety (FoS), fiberglass.

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Authors: Mahmoud Miri, Soleiman Maramaee

Abstract:

Because of architectural condition and structure application, sometimes mass source and stiffness source are not coincidence, and the structure is irregular. The structure is also might be asymmetric as an asymmetric bracing in plan which leads to unbalance distribution of stiffness or because of unbalance distribution of the mass. Both condition lead to eccentricity and torsion in the structure. The deficiency of ordinary code to evaluate the performance of steel structures against earthquake has been caused designing based on performance level or capacity spectrum be used. By using the mentioned methods it is possible to design a structure that its behavior against different earthquakes be predictive. In this article 5- story buildings with different percentage of asymmetric which is because of stiffness changes have been designed. The static and dynamic nonlinear analysis under three acceleration recording has been done. Finally performance level of the structure has been evaluated.

Keywords: Seismic analysis, torsion, asymmetric, irregular building, stiffness source.

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Authors: M. Moslehpour, S. Khorsandi

Abstract:

As transition to widespread use of IPv6 addresses has gained momentum, it has been shown to be vulnerable to certain security attacks such as those targeting Neighbor Discovery Protocol (NDP) which provides the address resolution functionality in IPv6. To protect this protocol, Secure Neighbor Discovery (SEND) is introduced. This protocol uses Cryptographically Generated Address (CGA) and asymmetric cryptography as a defense against threats on integrity and identity of NDP. Although SEND protects NDP against attacks, it is computationally intensive due to Hash2 condition in CGA. To improve the CGA computation speed, we parallelized CGA generation process and used the available resources in a trusted network. Furthermore, we focused on the influence of the existence of malicious nodes on the overall load of un-malicious ones in the network. According to the evaluation results, malicious nodes have adverse impacts on the average CGA generation time and on the average number of tries. We utilized a Trust Management that is capable of detecting and isolating the malicious node to remove possible incentives for malicious behavior. We have demonstrated the effectiveness of the Trust Management System in detecting the malicious nodes and hence improving the overall system performance.

Keywords: NDP, SEND, CGA, modifier, malicious node.

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Authors: Farideh Alizadeh

Abstract:

This article is investigating Boria which is a kind of common performance in Malaysia. Boria has been known as Boria and Borea and both are correct, but Boria is more common. Boria is a folk performance unique to Penang. This theatre style reached Penang in the mid-19th century and is believed to be derived from the Shia Islamic Passion play performed during the Muslim month of Muharram to commemorate the martyrs of Kerbela. These days in Malaysia (especially Penang) Boria mentions to a choral street performance performed annually by a number of groups composed mostly of Sunni Malaysian. Boria are performed for entertainment and often include an annual singing competition. The size, membership, themes and movements of each Boria troupe may vary from year to year. Similarly, the themes and contents of the Boria performed by the different troupes also changes each year and can have a comical, political or satirical notion. It is common to most groups during the first ten days of Muharram Boria generally is done.

Keywords: Boria, ritual, Passion play, theatre

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Authors: Roshan Dharshana Yapa, Koichi Harada

Abstract:

Breast skin-line estimation and breast segmentation is an important pre-process in mammogram image processing and computer-aided diagnosis of breast cancer. Limiting the area to be processed into a specific target region in an image would increase the accuracy and efficiency of processing algorithms. In this paper we are presenting a new algorithm for estimating skin-line and breast segmentation using fast marching algorithm. Fast marching is a partial-differential equation based numerical technique to track evolution of interfaces. We have introduced some modifications to the traditional fast marching method, specifically to improve the accuracy of skin-line estimation and breast tissue segmentation. Proposed modifications ensure that the evolving front stops near the desired boundary. We have evaluated the performance of the algorithm by using 100 mammogram images taken from mini-MIAS database. The results obtained from the experimental evaluation indicate that this algorithm explains 98.6% of the ground truth breast region and accuracy of the segmentation is 99.1%. Also this algorithm is capable of partially-extracting nipple when it is available in the profile.

Keywords: Mammogram, fast marching method, mathematical morphology.

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Authors: Chul Ho Han, Kyoung Hoon Kim

Abstract:

This paper carries out a performance analysis based on the first and second laws of thermodynamics for heat recovery vapor generator (HRVG) of ammonia-water mixture when the heat source is low-temperature energy in the form of sensible heat. In the analysis, effects of the ammonia mass concentration and mass flow ratio of the binary mixture are investigated on the system performance including the effectiveness of heat transfer, entropy generation, and exergy efficiency. The results show that the ammonia concentration and the mass flow ratio of the mixture have significant effects on the system performance of HRVG.

Keywords: Entropy, exergy, ammonia-water mixture, heat exchanger.

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Authors: Raif Parlakkaya, Ahmet Diken, Erkan Kara

Abstract:

This paper examines the relationship between corporate governance rating and stock prices of 26 Turkish firms listed in Turkish stock exchange (Borsa Istanbul) by using panel data analysis over five-year period. The paper also investigates the stock performance of firms with governance rating with regards to the market portfolio (i.e. BIST 100 Index) both prior and after governance scoring began. The empirical results show that there is no relation between corporate governance rating and stock prices when using panel data for annual variation in both rating score and stock prices. Further analysis indicates surprising results that while the selected firms outperform the market significantly prior to rating, the same performance does not continue afterwards.

Keywords: Corporate governance, stock price, performance, panel data analysis.

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Authors: M. Zerikat, S. Chekroun

Abstract:

This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.

Keywords: Electric drive, Induction motor, speed control, Adaptive control, neural network, High Performance.

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Authors: Kyoko Ito, Shinya Furuta, Daisuke Kamihigashi, Kimi Ueda, Hirotake Ishii, Hiroshi Shimoda, Fumiaki Obayashi, Kazuhiro Taniguchi

Abstract:

In order to improve intellectual concentration, few studies have verified the effect of indoor airflow among the thermal environment conditions, and the differences of the season in effects have not been studied. In this study, in order to investigate the influence of the airflow in winter on the intellectual concentration, an evaluation experiment was conducted. In the previous study, an effective airflow in summer was proposed and the improvement of intellectual concentration by evaluation experiment was confirmed. Therefore, an airflow profile in winter was proposed with reference to the airflow profile in summer. The airflows are a combination of a simulative airflow and mild airflow. An experiment has been conducted to investigate the influence of a room airflow in winter on intellectual concentration. As a result of comparison with no airflow condition, no significant difference was found. Based on the results, it is a future task to ask preliminary preference in advance and to establish a mechanism that can provide controllable airflow for each individual, taking into account the preference for airflow to be different for each individual.

Keywords: Intellectual concentration, airflow, winter, experiment.

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Authors: Jun Seok Kim, Cheong-Sool Park, Jun-Geol Baek, Sung-Shick Kim

Abstract:

Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.

Keywords: Control chart pattern recognition, Multi-resolution wavelet analysis, Bi-directional Kohonen network, Back-propagation network, Feature extraction.

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Authors: Ifeyinwa E. Achumba, Djamel Azzi, Rinat Khusainov

Abstract:

There are three approaches to complete Bayesian Network (BN) model construction: total expert-centred, total datacentred, and semi data-centred. These three approaches constitute the basis of the empirical investigation undertaken and reported in this paper. The objective is to determine, amongst these three approaches, which is the optimal approach for the construction of a BN-based model for the performance assessment of students- laboratory work in a virtual electronic laboratory environment. BN models were constructed using all three approaches, with respect to the focus domain, and compared using a set of optimality criteria. In addition, the impact of the size and source of the training, on the performance of total data-centred and semi data-centred models was investigated. The results of the investigation provide additional insight for BN model constructors and contribute to literature providing supportive evidence for the conceptual feasibility and efficiency of structure and parameter learning from data. In addition, the results highlight other interesting themes.

Keywords: Bayesian networks, model construction, parameterlearning, structure learning, performance index, model comparison.

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Authors: Metehan Makinacı

Abstract:

The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.

Keywords: Computer-aided diagnosis, support vector machines, Gauss-Markov random fields, texture classification.

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Authors: Changho Han, Jaemin Lee, Li Hua, Seokkwon Jeong

Abstract:

Design of membership function ranges in fuzzy logic control (FLC) is presented for robust control of a variable speed refrigeration system (VSRS). The criterion values of the membership function ranges can be carried out from the static experimental data, and two different values are offered to compare control performance. Some simulations and real experiments for the VSRS were conducted to verify the validity of the designed membership functions. The experimental results showed good agreement with the simulation results, and the error change rate and its sampling time strongly affected the control performance at transient state of the VSRS.

Keywords: Variable speed refrigeration system, Fuzzy logic control, membership function range, control performance.

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Authors: Houda Abadlia, Nadia Smairi, Khaled Ghedira

Abstract:

Multiobjective Particle Swarm Optimization (MOPSO) has shown an effective performance for solving test functions and real-world optimization problems. However, this method has a premature convergence problem, which may lead to lack of diversity. In order to improve its performance, this paper presents a hybrid approach which embedded the MOPSO into the island model and integrated a local search technique, Variable Neighborhood Search, to enhance the diversity into the swarm. Experiments on two series of test functions have shown the effectiveness of the proposed approach. A comparison with other evolutionary algorithms shows that the proposed approach presented a good performance in solving multiobjective optimization problems.

Keywords: Particle swarm optimization, migration, variable neighborhood search, multiobjective optimization.

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Authors: Chee Peng Lim, Wei Yee Goh

Abstract:

In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.

Keywords: AdaBoost, Elman network, neural network ensemble, time series regression.

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Authors: Young Kwon Yang, In Sung Kang, Jung Ha Hwang, Jin Chul Park

Abstract:

The present study is a foundational study for performance improvements on isolation wards to prevent proliferation of secondary infection of infectious diseases such as SARS, H1N1, and MERS inside hospitals. Accordingly, the present study conducted an analysis of the effect of sealing mechanisms and filling of openings on ensuring air tightness performance in isolation wards as well as simulation on air currents in improved isolation wards. The study method is as follows. First, previous studies on aerial infection type and mechanism were reviewed, and the review results were utilized as basic data of analysis on simulation of air current. Second, national and international legislations and regulations in relation to isolation wards as well as case studies on developed nations were investigated in order to identify the problems in isolation wards in Korea and improvement plans. Third, construction and facility plans were compared and analyzed between general and isolation wards focusing on large general hospitals in Korea, thereby conducting comparison and analysis on the performance and effects of air-tightness of general and isolation wards through CFD simulations. The study results showed that isolation wards had better air-tightness performance than that of general wards.

Keywords: AII Room, air-borne infection, CFD, computational fluid dynamics.

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Authors: M.M. Al Emran Hasan, M.Ektesabi, A.Kapoor

Abstract:

Recently electric vehicles are becoming popular as an alternative of conventional fossil fuel vehicles. Conventional Internal Combustion Engine (ICE) vehicle uses fossil fuel which contributing a major part of overall carbon emission in the environment. Carbon and other green house gas emission are responsible for global warming and resulting climate change. It becomes vital to evaluate performance of vehicle based on emission. In this paper an effort has been made to depict the picture of emission caused by vehicle and scenario of Australia has taken into account. Effort has been made to compare the fossil based vehicle with electric vehicle in phases. The study also evaluates advancement in electric vehicle technology, required infrastructure for sustainability and future scope of developments. This paper also includes the evaluation of electric vehicle concept for pollution control and sustainable transport systems in future. This study can be a benchmark for development of electric vehicle as low carbon emission alternative for the cities of tomorrow.

Keywords: Electric Vehicle, Fossil Fuel, Internal CombustionEngine, Green House Gas, In wheel motor, Smart grid

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Authors: Patrick O. Bobbie, Prince S. Attrams

Abstract:

In recent times, the rapid change in new technologies has spurred up the way and manner records are handled in educational institutions. Also, there is a need for reliable access and ease-of use to these records, resulting in increased productivity in organizations. In academic institutions, such benefits help in quality assessments, institutional performance, and assessments of teaching and evaluation methods. Students in educational institutions benefit the most when advanced technologies are deployed in accessing records. This research paper discusses the use of biometric technologies coupled with smartcard technologies to provide a unique way of identifying students and matching their data to financial records to grant them access to restricted areas such as examination halls. The system developed in this paper, has an identity verification component as part of its main functionalities. A systematic software development cycle of analysis, design, coding, testing and support was used. The system provides a secured way of verifying student’s identity and real time verification of financial records. An advanced prototype version of the system has been developed for testing purposes.

Keywords: Biometrics, fingerprints, identity-verification, smartcards.

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Authors: A. Bouabid, B. Bielenberg, S. Ainane, N. Pasha

Abstract:

In this paper, a team of faculty members of the Petroleum Institute in Abu Dhabi, UAE representing six different courses across General Engineering (ENGR), Communication (COMM), and Design (STPS) worked together to establish a clear developmental progression of learning outcomes and performance indicators for targeted knowledge, areas of competency, and skills for the first three semesters of the Bachelor of Sciences in Engineering curriculum. The sequences of courses studied in this project were ENGR/COMM, COMM/STPS, and ENGR/STPS. For each course’s nine areas of knowledge, competency, and skills, the research team reviewed the existing learning outcomes and related performance indicators with a focus on identifying linkages across disciplines as well as within the courses of a discipline. The team reviewed existing performance indicators for developmental progression from semester to semester for same discipline related courses (vertical alignment) and for different discipline courses within the same semester (horizontal alignment). The results of this work have led to recommendations for modifications of the initial indicators when incoherence was identified, and/or for new indicators based on best practices (identified through literature searches) when gaps were identified. It also led to recommendations for modifications of the level of emphasis within each course to ensure developmental progression. The exercise has led to a revised Sequence Performance Indicator Mapping for the knowledge, skills, and competencies across the six core courses.

Keywords: Curriculum alignment, horizontal and vertical progression, performance indicators, skill level.

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Authors: Yah-Ling Hung

Abstract:

eHealth is undoubtedly emerging as a promising vehicle to provide information for individual self-care management. However, the accessing ability, reading strategies and navigating behavior between higher literacy users and lower literacy users are significantly different. Yet, ways to tailor audiences’ health literacy and develop appropriate eHealth to feed their need become a big challenge. The purpose of this study is to compare the educational effectiveness of eHealth to deliver health knowledge between higher literacy users and lower literacy users, thus establishing useful design strategies of eHealth for users with different level of health literacy. The study was implemented in four stages, the first of which developed a website as the testing media to introduce health care knowledge relating to children’s allergy. Secondly, a reliability and validity test was conducted to make sure that all of the questions in the questionnaire were good indicators. Thirdly, a pre-post knowledge test was conducted with 66 participants, 33 users with higher literacy and 33 users with lower literacy respectively. Finally, a usability evaluation survey was undertaken to explore the criteria used by users with different levels of health literacy to evaluate eHealth. The results demonstrated that the eHealth Intervention in both groups had a positive outcome. There was no significant difference between the effectiveness of eHealth intervention between users with higher literacy and users with lower literacy. However, the average mean of lower literacy group was marginally higher than the average mean of higher literacy group. The findings also showed that the criteria used to evaluate eHealth could be analyzed in terms of the quality of information, appearance, appeal and interaction, but the users with lower literacy have different evaluation criteria from those with higher literacy. This is an interdisciplinary research which proposes the sequential key steps that incorporate the planning, developing and accessing issues that need to be considered when designing eHealth for patients with varying degrees of health literacy.

Keywords: eHealth, health intervention, health literacy, usability evaluation.

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Authors: K. Saravanan, R. Anita

Abstract:

Flexible AC Transmission Systems (FACTS) is granting a new group of advanced power electronic devices emerging for enhancement of the power system performance. Unified Power Flow Controller (UPFC) is a recent version of FACTS devices for power system applications. The back-up energy supply system incorporated with UPFC is providing a complete control of real and reactive power at the same time and hence is competent to improve the performance of an electrical power system. In this article, backup energy supply unit such as superconducting magnetic energy storage (SMES) is integrated with UPFC. In addition, comparative exploration of UPFC–battery, UPFC–UC and UPFC–SMES performance is evaluated through the vibrant simulation by using MATLAB/Simulink software.

Keywords: Power system, FACTS, UPFC, DC-DC chopper, battery, UC, SMES.

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Authors: Ly. Benbahouche

Abstract:

Currently, several soft switching topologies have been studied to achieve high power switching efficiency, reduced cost, improved reliability and reduced parasites. It is well known that improvement in power electronics systems always depend on advanced in power devices. The IGBT has been successfully used in a variety of switching applications such as motor drives and appliance control because of its superior characteristics.

The aim of this paper is focuses on simulation and explication of the internal dynamics of IGBTs behaviour under the most popular soft switching schemas that is Zero Current Switching (ZCS) environments.

The main purpose of this paper is to point out some mechanisms relating to current tail during the turn-off and examination of the response at turn-off with variation of temperature, inductance L, snubber capacitors Cs, and bus voltage in order to achieve an improved understanding of internal carrier dynamics. It is shown that the snubber capacitor, the inductance and even the temperature controls the magnitude and extent of the tail current, hence the turn-off time (switching speed of the device).

Moreover, it has also been demonstrated that the ZCS switching can be utilized efficiently to improve and reduce the power losses as well as the turn-off time. Furthermore, the turn-off loss in ZCS was found to depend on the time of switching of the device.

Keywords: PT-IGBT, ZCS, turn-off losses, dV/dt.

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Authors: Milan Paudel, Fook Fah Yap, Anil K. Bastola

Abstract:

The difficulties in riding small wheel bicycles and their lesser stability have been perceived for a long time. Although small wheel bicycles are designed using the similar approach and guidelines that have worked well for big wheel bicycles, the performance of the big wheelers and the smaller wheelers are markedly different. Since both the big wheelers and small wheelers have same fundamental geometry, most blame the small wheel for this discrepancy in the performance. This paper reviews existing guidelines for bicycle design, especially the front steering geometry for the bicycle, and provides a systematic and quantitative analysis of different wheel sized bicycles. A validated mathematical model has been used as a tool to assess the dynamic performance of the bicycles in term of their self-stability. The results obtained were found to corroborate the subjective perception of cyclists for small wheel bicycles. The current approach for small wheel bicycle design requires higher speed to be self-stable. However, it was found that increasing the headtube angle and selecting a proper trail could improve the dynamic performance of small wheel bicycles. A range of parameters for front steering geometry has been identified for small wheel bicycles that have comparable stability as big wheel bicycles. Interestingly, most of the identified geometries are found to be beyond the ISO recommended range and seem to counter the current approach of small wheel bicycle design. Therefore, it was successfully shown that the guidelines for big wheelers do not translate directly to small wheelers, but careful selection of the front geometry could make small wheel bicycles as stable as big wheel bicycles.

Keywords: Big wheel bicycle, design approach, ISO requirements, small wheel bicycle, stability and performance.

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Authors: M. Ben Slimene, M.-S. Ouali

Abstract:

Asset management of urban infrastructures faces a multitude of challenges that need to be overcome to obtain a reliable measurement of performances. Predicting the performance of slowly aging systems is one of those challenges, which helps the asset manager to investigate specific failure modes and to undertake the appropriate maintenance and rehabilitation interventions to avoid catastrophic failures as well as to optimize the maintenance costs. This article presents a methodology for modeling the deterioration of slowly degrading assets based on an operating history. It consists of extracting degradation profiles by grouping together assets that exhibit similar degradation sequences using an unsupervised classification technique derived from artificial intelligence. The obtained clusters are used to build the performance prediction models. This methodology is applied to a sample of a stormwater drainage culvert dataset.

Keywords: Artificial intelligence, clustering, culvert, regression model, slow degradation.

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Authors: Ibrahim Gomaa, Hoda M. O. Mokhtar

Abstract:

Although most of the existing skyline queries algorithms focused basically on querying static points through static databases; with the expanding number of sensors, wireless communications and mobile applications, the demand for continuous skyline queries has increased. Unlike traditional skyline queries which only consider static attributes, continuous skyline queries include dynamic attributes, as well as the static ones. However, as skyline queries computation is based on checking the domination of skyline points over all dimensions, considering both the static and dynamic attributes without separation is required. In this paper, we present an efficient algorithm for computing continuous skyline queries without discriminating between static and dynamic attributes. Our algorithm in brief proceeds as follows: First, it excludes the points which will not be in the initial skyline result; this pruning phase reduces the required number of comparisons. Second, the association between the spatial positions of data points is examined; this phase gives an idea of where changes in the result might occur and consequently enables us to efficiently update the skyline result (continuous update) rather than computing the skyline from scratch. Finally, experimental evaluation is provided which demonstrates the accuracy, performance and efficiency of our algorithm over other existing approaches.

Keywords: Continuous query processing, dynamic database, moving object, skyline queries.

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