Search results for: Selection of students
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2334

Search results for: Selection of students

834 Collaborative Education Practice in a Data Structure E-Learning Course

Authors: Gang Chen, Ruimin Shen

Abstract:

This paper presented a collaborative education model, which consists four parts: collaborative teaching, collaborative working, collaborative training and interaction. Supported by an e-learning platform, collaborative education was practiced in a data structure e-learning course. Data collected shows that most of students accept collaborative education. This paper goes one step attempting to determine which aspects appear to be most important or helpful in collaborative education.

Keywords: Collaborative work, education, data structures.

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833 Observations about the Principal Components Analysis and Data Clustering Techniques in the Study of Medical Data

Authors: Cristina G. Dascâlu, Corina Dima Cozma, Elena Carmen Cotrutz

Abstract:

The medical data statistical analysis often requires the using of some special techniques, because of the particularities of these data. The principal components analysis and the data clustering are two statistical methods for data mining very useful in the medical field, the first one as a method to decrease the number of studied parameters, and the second one as a method to analyze the connections between diagnosis and the data about the patient-s condition. In this paper we investigate the implications obtained from a specific data analysis technique: the data clustering preceded by a selection of the most relevant parameters, made using the principal components analysis. Our assumption was that, using the principal components analysis before data clustering - in order to select and to classify only the most relevant parameters – the accuracy of clustering is improved, but the practical results showed the opposite fact: the clustering accuracy decreases, with a percentage approximately equal with the percentage of information loss reported by the principal components analysis.

Keywords: Data clustering, medical data, principal components analysis.

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832 Biological Soil Conservation Planning by Spatial Multi-Criteria Evaluation Techniques (Case Study: Bonkuh Watershed in Iran)

Authors: Ali Akbar Jamali

Abstract:

This paper discusses site selection process for biological soil conservation planning. It was supported by a valuefocused approach and spatial multi-criteria evaluation techniques. A first set of spatial criteria was used to design a number of potential sites. Next, a new set of spatial and non-spatial criteria was employed, including the natural factors and the financial costs, together with the degree of suitability for the Bonkuh watershed to biological soil conservation planning and to recommend the most acceptable program. The whole process was facilitated by a new software tool that supports spatial multiple criteria evaluation, or SMCE in GIS software (ILWIS). The application of this tool, combined with a continual feedback by the public attentions, has provided an effective methodology to solve complex decisional problem in biological soil conservation planning.

Keywords: GIS, Biological soil conservation planning, Spatial multi-criteria evaluation, Iran

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831 Feedstock Effects on Selecting the Appropriate Coil Configuration for Cracking Furnaces

Authors: Ramin Karimzadeh, Nazi Rahimi, Mohammad Ghashghaee

Abstract:

In the present research, steam cracking of two types of feedstocks i.e., naphtha and ethane is simulated for Pyrocrack1-1 and 2/2 coil configurations considering two key parameters of coil outlet temperature (COT) and coil capacity using a radical based kinetic model. The computer model is confirmed using the industrial data obtained from Amirkabir Petrochemical Complex. The results are in good agreement with performance data for naphtha cracking in a wide range of severity (0.4-0.7), and for ethane cracking on various conversions (50-70). It was found that Pyrocrack2-2 coil type is an appropriate choice for steam cracking of ethane at reasonable ethylene yield while resulting in much lower tube wall temperature while Pyrocrack1-1 coil type is a proper selection for liquid feedstocks i.e. naphtha. It can be used for cracking of liquid feedstocks at optimal ethylene yield whereas not exceeding the allowable maximum tube temperature.

Keywords: Coil configuration, Ethane, Naphtha, Steamcracking.

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830 Academic Motivation Maintenance for Students While Solving Mathematical Problems in the Middle School

Authors: M. Rodionov, Z. Dedovets

Abstract:

The level and type of student academic motivation are the key factors in their development and determine the effectiveness of their education. Improving motivation is very important with regard to courses on middle school mathematics. This article examines the general position regarding the practice of academic motivation. It also examines the particular features of mathematical problem solving in a school setting.

Keywords: Teaching strategy, mathematics, motivation, student.

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829 Forecasting Models for Steel Demand Uncertainty Using Bayesian Methods

Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

Abstract:

 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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828 One-Class Support Vector Machine for Sentiment Analysis of Movie Review Documents

Authors: Chothmal, Basant Agarwal

Abstract:

Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: Feature selection methods, Machine learning, NB, One-class SVM, Sentiment Analysis, Support Vector Machine.

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827 The Maximum Likelihood Method of Random Coefficient Dynamic Regression Model

Authors: Autcha Araveeporn

Abstract:

The Random Coefficient Dynamic Regression (RCDR) model is to developed from Random Coefficient Autoregressive (RCA) model and Autoregressive (AR) model. The RCDR model is considered by adding exogenous variables to RCA model. In this paper, the concept of the Maximum Likelihood (ML) method is used to estimate the parameter of RCDR(1,1) model. Simulation results have shown the AIC and BIC criterion to compare the performance of the the RCDR(1,1) model. The variables as the stationary and weakly stationary data are good estimates where the exogenous variables are weakly stationary. However, the model selection indicated that variables are nonstationarity data based on the stationary data of the exogenous variables.

Keywords: Autoregressive, Maximum Likelihood Method, Nonstationarity, Random Coefficient Dynamic Regression, Stationary.

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826 Computationally Efficient Adaptive Rate Sampling and Adaptive Resolution Analysis

Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

Abstract:

Mostly the real life signals are time varying in nature. For proper characterization of such signals, time-frequency representation is required. The STFT (short-time Fourier transform) is a classical tool used for this purpose. The limitation of the STFT is its fixed time-frequency resolution. Thus, an enhanced version of the STFT, which is based on the cross-level sampling, is devised. It can adapt the sampling frequency and the window function length by following the input signal local variations. Therefore, it provides an adaptive resolution time-frequency representation of the input. The computational complexity of the proposed STFT is deduced and compared to the classical one. The results show a significant gain of the computational efficiency and hence of the processing power. The processing error of the proposed technique is also discussed.

Keywords: Level Crossing Sampling, Activity Selection, Adaptive Resolution Analysis, Computational Complexity

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825 Forecasting Direct Normal Irradiation at Djibouti Using Artificial Neural Network

Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

Abstract:

In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: Artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt.

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824 A New Heuristic Approach for Optimal Network Reconfiguration in Distribution Systems

Authors: R. Srinivasa Rao, S. V. L. Narasimham

Abstract:

This paper presents a novel approach for optimal reconfiguration of radial distribution systems. Optimal reconfiguration involves the selection of the best set of branches to be opened, one each from each loop, such that the resulting radial distribution system gets the desired performance. In this paper an algorithm is proposed based on simple heuristic rules and identified an effective switch status configuration of distribution system for the minimum loss reduction. This proposed algorithm consists of two parts; one is to determine the best switching combinations in all loops with minimum computational effort and the other is simple optimum power loss calculation of the best switching combination found in part one by load flows. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on 33-bus system. The results show that the performance of the proposed method is better than that of the other methods.

Keywords: Distribution system, network reconfiguration, powerloss reduction, radial network, heuristic technique.

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823 Decision-Making Tool for Planning the Construction of Infrastructure Projects

Authors: R. Monib, C. I. Goodier, A. Gibb

Abstract:

The aim of this paper is to investigate the key drivers in planning the construction phase for infrastructure projects to reduce project delays. To achieve this aim, the research conducted three case studies using semi-structured and unstructured interviews (n = 59). The results conclude that a lack of modularization awareness is among the key factors attributed to project delays. The current emotive and ill-informed approach to decision-making, coupled with the lack of knowledge regarding appropriate construction method selection, prevents the potential benefits of modularization being fully realized. To assist with decision-making for the best construction method, the research presents project management tools to help decision makers to choose the most appropriate construction approach through optimizing the use of modularization in engineering and construction (EC). A decision-making checklist is presented in this paper. This checklist tool assists the project team in determining the best construction method, taking into consideration the module type.

Keywords: Infrastructure, modularization, decision support, planning.

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822 An Experimental Comparison of Unsupervised Learning Techniques for Face Recognition

Authors: Dinesh Kumar, C.S. Rai, Shakti Kumar

Abstract:

Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal Component Analysis (PCA), Self Organizing Maps (SOM) and Independent Component Analysis (ICA) are the three techniques among many others as proposed by different researchers for Face Recognition, known as the unsupervised techniques. This paper proposes integration of the two techniques, SOM and PCA, for dimensionality reduction and feature selection. Simulation results show that, though, the individual techniques SOM and PCA itself give excellent performance but the combination of these two can also be utilized for face recognition. Experimental results also indicate that for the given face database and the classifier used, SOM performs better as compared to other unsupervised learning techniques. A comparison of two proposed methodologies of SOM, Local and Global processing, shows the superiority of the later but at the cost of more computational time.

Keywords: Face Recognition, Principal Component Analysis, Self Organizing Maps, Independent Component Analysis

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821 Automatically Generated and Marked E-Learning Exercises for Logistics Cost Accounting

Authors: Markus Siepermann, Christoph Siepermann

Abstract:

This paper presents the concept and realisation of an e-learning tool that provides predefined or automatically generated exercises concerning logistics cost accounting. Students may practise where and whenever they like to via the Internet. Their solutions are marked automatically by the tool while considering consecutive faults and without any intervention of lecturers.

Keywords: Automatic marking, e-learning environment, onlinepracticing, randomly-generated exercises.

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820 E-Learning Platform with SPICE Web Service

Authors: A. Braeken, L. Sterckx, A. Touhafi, Y. Verbelen

Abstract:

When studying electronics, hands-on experience is considered to be very valuable for a better understanding of the concepts of electricity and electronics. Students lacking sufficient time in the lab are often put at disadvantage. A way to overcome this, is by using interactive multimedia in a virtual environment. Instead of proposing another new ad-hoc simulator for e-learning, we propose in this paper an e-learning platform integrating the SPICE simulator as a web service. This enables to make use of all the functions of the de-facto standard simulator SPICE inelectronics when developing new simulations.

Keywords: E-learning, SPICE, virtual experiments, web service.

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819 Combustion and Emission Characteristics in a Can-type Combustion Chamber

Authors: Selvakuma Kumaresh, Man Young Kim

Abstract:

Combustion phenomenon will be accomplished effectively by the development of low emission combustor. One of the significant factors influencing the entire Combustion process is the mixing between a swirling angular jet (Primary Air) and the non-swirling inner jet (fuel). To study this fundamental flow, the chamber had to be designed in such a manner that the combustion process to sustain itself in a continuous manner and the temperature of the products is sufficiently below the maximum working temperature in the turbine. This study is used to develop the effective combustion with low unburned combustion products by adopting the concept of high swirl flow and motility of holes in the secondary chamber. The proper selection of a swirler is needed to reduce emission which can be concluded from the emission of Nox and CO2. The capture of CO2 is necessary to mitigate CO2 emissions from natural gas. Thus the suppression of unburned gases is a meaningful objective for the development of high performance combustor without affecting turbine blade temperature.

Keywords: Combustion, Emission, Can-type Combustion Chamber, CFD, Motility of Holes, Swirl Flow.

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818 Enhanced Performance of Fading Dispersive Channel Using Dynamic Frequency Hopping(DFH)

Authors: Walid M. Saad

Abstract:

techniques are examined to overcome the performance degradation caused by the channel dispersion using slow frequency hopping (SFH) with dynamic frequency hopping (DFH) pattern adaptation. In DFH systems, the frequency slots are selected by continuous quality monitoring of all frequencies available in a system and modification of hopping patterns for each individual link based on replacing slots which its signal to interference ratio (SIR) measurement is below a required threshold. Simulation results will show the improvements in BER obtained by DFH in comparison with matched frequency hopping (MFH), random frequency hopping (RFH) and multi-carrier code division multiple access (MC-CDMA) in multipath slowly fading dispersive channels using a generalized bandpass two-path transfer function model, and will show the improvement obtained according to the threshold selection.

Keywords: code division multiple access (CDMA), dynamic channel allocation (DCA), dynamic channel assignment, frequency hopping, matched frequency hopping (MFH).

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817 Epistemological Functions of Emotions and Their Relevance to the Formation of Citizens and Scientists

Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

Abstract:

Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional mechanisms. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the so-called content-bearing function: it argues that emotions provide the material reasoning that is subsequently transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. This paper argues that science education must start from the presence of certain emotions in the learner if we want to form citizens with a scientific or cultural future.

Keywords: Epistemic emotions, science education, formation of citizens and scientists, epistemic functions of emotions.

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816 Online Learning Activities Kit on Plants in Thai Literature in Compliance with the School Botanical Garden of Plant Genetic Conservation Project under the Royal Initiative of Her Royal Highness Princess Maha Chakri Sirindhorn

Authors: Pornpapatsorn Princhankol, Kannika Udnunkarn

Abstract:

This research was aimed to develop and determine the quality of online learning activities kit as well as to examine the learning achievement of students and their satisfaction towards the kit through authentic assessment. The tools in this research contained online learning activities kit on plant in Thai literature in compliance with the School Botanical Garden of Plant Genetic Conservation Project under the Royal Initiative of Her Royal Highness Princess Maha Chakri Sirindhorn, the assessment form, the learning achievement test, the satisfaction form and the authentic assessment form. The population consisted of 40 students in the second range of primary years (Prathomsuksa 4 to 6) at Ban Khao Rak School, Suratthani Province, Thailand. The research results showed that the content quality of the developed online learning activities kit as assessed by the experts was 4.70 on average or at very high level. The pre-test and post-test comparison was made to examine the learning achievement and it revealed that the post-test score was higher than the pre-test score with statistical significance at the .01 level. The satisfaction of the sampling group towards the online learning activities kit was 4.74 or at the highest level. The authentic assessment showed an average of 1.69 or at good level. Therefore, the online learning activities kit on plant in Thai literature in compliance with the School Botanical Garden of Plant Genetic Conservation Project under the Royal Initiative of Her Royal Highness Princess Maha Chakri Sirindhorn could be used in real classroom situations.

Keywords: Online learning activities kit, Plants in Thai literature, School Botanical garden

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815 A Novel Method for the Characterization of Synchronization and Coupling in Multichannel EEG and ECoG

Authors: Manfred Hartmann, Andreas Graef, Hannes Perko, Christoph Baumgartner, Tilmann Kluge

Abstract:

In this paper we introduce a novel method for the characterization of synchronziation and coupling effects in multivariate time series that can be used for the analysis of EEG or ECoG signals recorded during epileptic seizures. The method allows to visualize the spatio-temporal evolution of synchronization and coupling effects that are characteristic for epileptic seizures. Similar to other methods proposed for this purpose our method is based on a regression analysis. However, a more general definition of the regression together with an effective channel selection procedure allows to use the method even for time series that are highly correlated, which is commonly the case in EEG/ECoG recordings with large numbers of electrodes. The method was experimentally tested on ECoG recordings of epileptic seizures from patients with temporal lobe epilepsies. A comparision with the results from a independent visual inspection by clinical experts showed an excellent agreement with the patterns obtained with the proposed method.

Keywords: EEG, epilepsy, regression analysis, seizurepropagation.

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814 Inductive Grammar, Student-Centered Reading, and Interactive Poetry: The Effects of Teaching English with Fun in Schools of Two Villages in Lebanon

Authors: Talar Agopian

Abstract:

Teaching English as a Second Language (ESL) is a common practice in many Lebanese schools. However, ESL teaching is done in traditional ways. Methods such as constructivism are seldom used, especially in villages. Here lies the significance of this research which joins constructivism and Piaget’s theory of cognitive development in ESL classes in Lebanese villages. The purpose of the present study is to explore the effects of applying constructivist student-centered strategies in teaching grammar, reading comprehension, and poetry on students in elementary ESL classes in two villages in Lebanon, Zefta in South Lebanon and Boqaata in Mount Lebanon. 20 English teachers participated in a training titled “Teaching English with Fun”, which focused on strategies that create a student-centered class where active learning takes place and there is increased learner engagement and autonomy. The training covered three main areas in teaching English: grammar, reading comprehension, and poetry. After participating in the training, the teachers applied the new strategies and methods in their ESL classes. The methodology comprised two phases: in phase one, practice-based research was conducted as the teachers attended the training and applied the constructivist strategies in their respective ESL classes. Phase two included the reflections of the teachers on the effects of the application of constructivist strategies. The results revealed the educational benefits of constructivist student-centered strategies; the students of teachers who applied these strategies showed improved engagement, positive attitudes towards poetry, increased motivation, and a better sense of autonomy. Future research is required in applying constructivist methods in the areas of writing, spelling, and vocabulary in ESL classrooms of Lebanese villages.

Keywords: Active learning, constructivism, learner engagement, student-centered strategies.

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813 A Dual Fitness Function Genetic Algorithm: Application on Deterministic Identical Machine Scheduling

Authors: Saleem Z. Ramadan, Gürsel A. Süer

Abstract:

In this paper a genetic algorithm (GA) with dual-fitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machine scheduling using simulated data. The results obtained from the proposed GA were compared with classical GA and integer programming (IP). Results showed that dual-fitness function GA outperformed the classical single-fitness function GA with statistical significance for large problems and was competitive to IP, particularly when large size problems were used.

Keywords: Machine scheduling, Genetic algorithms, Due dates, Number of tardy jobs, Number of early jobs, Integer programming, Dual Fitness functions.

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812 Experimental Measurements of Evacuated Enclosure Thermal Insulation Effectiveness for Vacuum Flat Plate Solar Thermal Collectors

Authors: Paul Henshall, Philip Eames, Roger Moss, Stan Shire, Farid Arya, Trevor Hyde

Abstract:

Encapsulating the absorber of a flat plate solar thermal collector in vacuum by an enclosure that can be evacuated can result in a significant increase in collector performance and achievable operating temperatures. This is a result of the thermal insulation effectiveness of the vacuum layer surrounding the absorber, as less heat is lost during collector operation. This work describes experimental thermal insulation characterization tests of prototype vacuum flat plate solar thermal collectors that demonstrate the improvement in absorber heat loss coefficients. Furthermore, this work describes the selection and sizing of a getter, suitable for maintaining the vacuum inside the enclosure for the lifetime of the collector, which can be activated at low temperatures.

Keywords: Vacuum, thermal, flat-plate solar collector.

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811 A Genetic and Simulated Annealing Based Algorithms for Solving the Flow Assignment Problem in Computer Networks

Authors: Tarek M. Mahmoud

Abstract:

Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.

Keywords: Genetic Algorithms, Flow Assignment, Routing, Computer network, Simulated Annealing.

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810 Effective Software-Based Solution for Processing Mass Downstream Data in Interactive Push VOD System

Authors: Ni Hong, Wu Guobin, Wu Gang, Pan Liang

Abstract:

Interactive push VOD system is a new kind of system that incorporates push technology and interactive technique. It can push movies to users at high speeds at off-peak hours for optimal network usage so as to save bandwidth. This paper presents effective software-based solution for processing mass downstream data at terminals of interactive push VOD system, where the service can download movie according to a viewer-s selection. The downstream data is divided into two catalogs: (1) the carousel data delivered according to DSM-CC protocol; (2) IP data delivered according to Euro-DOCSIS protocol. In order to accelerate download speed and reduce data loss rate at terminals, this software strategy introduces caching, multi-thread and resuming mechanisms. The experiments demonstrate advantages of the software-based solution.

Keywords: DSM-CC, data carousel, Euro-DOCSIS, push VOD.

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809 An Algorithm for Determining the Arrival Behavior of a Secondary User to a Base Station in Cognitive Radio Networks

Authors: Danilo López, Edwin Rivas, Leyla López

Abstract:

This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.

Keywords: Cognitive radio, MLPNN, base station, prediction, best effort, real time.

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808 DC-to-DC Converters for Low-Voltage High-Power Renewable Energy Systems

Authors: Abdar Ali, Rizwan Ullah, Zahid Ullah

Abstract:

This paper focuses on the study of DC-to-DC converters, which are suitable for low-voltage high-power applications. The output voltages generated by renewable energy sources such as photovoltaic arrays and fuel cell stacks are generally low and required to be increased to high voltage levels. Development of DC-to-DC converters, which provide high step-up voltage conversion ratios with high efficiencies and low voltage stresses, is one of the main issues in the development of renewable energy systems. A procedure for three converters−conventional DC-to-DC converter, interleaved boost converter, and isolated flyback based converter, is illustrated for a given set of specifications. The selection among the converters for the given application is based on the voltage conversion ratio, efficiency, and voltage stresses.

Keywords: Flyback converter, interleaved boost, photovoltaic array, fuel cell, switch stress, voltage conversion ratio, renewable energy.

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807 Dissolved Oxygen Prediction Using Support Vector Machine

Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

Abstract:

In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, Water Temperature, and Conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: Dissolved oxygen, Water quality, predication DO, Support Vector Machine.

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806 Feature Extraction for Surface Classification – An Approach with Wavelets

Authors: Smriti H. Bhandari, S. M. Deshpande

Abstract:

Surface metrology with image processing is a challenging task having wide applications in industry. Surface roughness can be evaluated using texture classification approach. Important aspect here is appropriate selection of features that characterize the surface. We propose an effective combination of features for multi-scale and multi-directional analysis of engineering surfaces. The features include standard deviation, kurtosis and the Canny edge detector. We apply the method by analyzing the surfaces with Discrete Wavelet Transform (DWT) and Dual-Tree Complex Wavelet Transform (DT-CWT). We used Canberra distance metric for similarity comparison between the surface classes. Our database includes the surface textures manufactured by three machining processes namely Milling, Casting and Shaping. The comparative study shows that DT-CWT outperforms DWT giving correct classification performance of 91.27% with Canberra distance metric.

Keywords: Dual-tree complex wavelet transform, surface metrology, surface roughness, texture classification.

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805 Structural Analysis of Username Segment in E-Mail Addresses of Engineering Institutes of Gujarat State of India

Authors: Jatinderkumar R. Saini

Abstract:

E-mail has become a key mechanism of electronic communication. This is true for professional organizations that like to communicate with their subjects online and are slowly shifting to paper-less office. The current paper focuses specifically on academic institutions offering Engineering course in Gujarat state and attempts for textual analysis of the usernames of the institutional e-mail addresses. We found that the institutions tend to design the username segment of their e-mail addresses by choosing words or combination of words from specific categories. The paper also highlights the use of special characters, digits and random words in designing the usernames. On the sidelines, the paper lists the style of employing department names and designations for the design process. To the best of our knowledge, this is the first formal attempt to analyze the selection of words employed for designing username segment of e-mail addresses of engineering institutions.

Keywords: E-mail address, Institute, Engineering, Username.

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