Search results for: real decisions
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2558

Search results for: real decisions

1148 On Measuring the Reusability Proneness of Mobile Applications

Authors: Fathi Taibi

Abstract:

The abnormal increase in the number of applications available for download in Android markets is a good indication that they are being reused. However, little is known about their real reusability potential. A considerable amount of these applications is reported as having a poor quality or being malicious. Hence, in this paper, an approach to measure the reusability potential of classes in Android applications is proposed. The approach is not meant specifically for this particular type of applications. Rather, it is intended for Object-Oriented (OO) software systems in general and aims also to provide means to discard the classes of low quality and defect prone applications from being reused directly through inheritance and instantiation. An empirical investigation is conducted to measure and rank the reusability potential of the classes of randomly selected Android applications. The results obtained are thoroughly analyzed in order to understand the extent of this potential and the factors influencing it.

Keywords: Reusability, Software Quality Factors, Software Metrics, Empirical Investigation, Object-Oriented Software, Android Applications.

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1147 Forecasting US Dollar/Euro Exchange Rate with Genetic Fuzzy Predictor

Authors: R. Mechgoug, A. Titaouine

Abstract:

Fuzzy systems have been successfully used for exchange rate forecasting. However, fuzzy system is very confusing and complex to be designed by an expert, as there is a large set of parameters (fuzzy knowledge base) that must be selected, it is not a simple task to select the appropriate fuzzy knowledge base for an exchange rate forecasting. The researchers often look the effect of fuzzy knowledge base on the performances of fuzzy system forecasting. This paper proposes a genetic fuzzy predictor to forecast the future value of daily US Dollar/Euro exchange rate time’s series. A range of methodologies based on a set of fuzzy predictor’s which allow the forecasting of the same time series, but with a different fuzzy partition. Each fuzzy predictor is built from two stages, where each stage is performed by a real genetic algorithm.

Keywords: Foreign exchange rate, time series forecasting, Fuzzy System, and Genetic Algorithm.

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1146 Avoiding Pin Ball Routing Problem in Network Mobility Hand-Off Management

Authors: M. Dinakaran, P. Balasubramanie

Abstract:

With the demand of mobility by users, wireless technologies have become the hotspot developing arena. Internet Engineering Task Force (IETF) working group has developed Mobile IP to support node mobility. The concept of node mobility indicates that in spite of the movement of the node, it is still connected to the internet and all the data transactions are preserved. It provides location-independent access to Internet. After the incorporation of host mobility, network mobility has undergone intense research. There are several intricacies faced in the real world implementation of network mobility significantly the problem of nested networks and their consequences. This article is concerned regarding a problem of nested network called pinball route problem and proposes a solution to eliminate the above problem. The proposed mechanism is implemented using NS2 simulation tool and it is found that the proposed mechanism efficiently reduces the overload caused by the pinball route problem.

Keywords: Mobile IP, Pinball routing problem, NEMO

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1145 An Optimization of Orbital Transfer for Spacecrafts with Finite-thrust Based on Legendre Pseudospectral Method

Authors: Yanan Yang, Zhigang Wang, Xiang Chen

Abstract:

This paper presents the use of Legendre pseudospectral method for the optimization of finite-thrust orbital transfer for spacecrafts. In order to get an accurate solution, the System-s dynamics equations were normalized through a dimensionless method. The Legendre pseudospectral method is based on interpolating functions on Legendre-Gauss-Lobatto (LGL) quadrature nodes. This is used to transform the optimal control problem into a constrained parameter optimization problem. The developed novel optimization algorithm can be used to solve similar optimization problems of spacecraft finite-thrust orbital transfer. The results of a numerical simulation verified the validity of the proposed optimization method. The simulation results reveal that pseudospectral optimization method is a promising method for real-time trajectory optimization and provides good accuracy and fast convergence.

Keywords: Finite-thrust, Orbital transfer, Legendre pseudospectral method

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1144 MONARC: A Case Study on Simulation Analysis for LHC Activities

Authors: Ciprian Dobre

Abstract:

The scale, complexity and worldwide geographical spread of the LHC computing and data analysis problems are unprecedented in scientific research. The complexity of processing and accessing this data is increased substantially by the size and global span of the major experiments, combined with the limited wide area network bandwidth available. We present the latest generation of the MONARC (MOdels of Networked Analysis at Regional Centers) simulation framework, as a design and modeling tool for large scale distributed systems applied to HEP experiments. We present simulation experiments designed to evaluate the capabilities of the current real-world distributed infrastructure to support existing physics analysis processes and the means by which the experiments bands together to meet the technical challenges posed by the storage, access and computing requirements of LHC data analysis within the CMS experiment.

Keywords: Modeling and simulation, evaluation, large scale distributed systems, LHC experiments, CMS.

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1143 Machine Learning Methods for Environmental Monitoring and Flood Protection

Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer

Abstract:

More and more natural disasters are happening every year: floods, earthquakes, volcanic eruptions, etc. In order to reduce the risk of possible damages, governments all around the world are investing into development of Early Warning Systems (EWS) for environmental applications. The most important task of the EWS is identification of the onset of critical situations affecting environment and population, early enough to inform the authorities and general public. This paper describes an approach for monitoring of flood protections systems based on machine learning methods. An Artificial Intelligence (AI) component has been developed for detection of abnormal dike behaviour. The AI module has been integrated into an EWS platform of the UrbanFlood project (EU Seventh Framework Programme) and validated on real-time measurements from the sensors installed in a dike.

Keywords: Early Warning System, intelligent environmentalmonitoring, machine learning, flood protection.

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1142 Multi-objective Optimisation of Composite Laminates under Heat and Moisture Effects using a Hybrid Neuro-GA Algorithm

Authors: M. R. Ghasemi, A. Ehsani

Abstract:

In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.

Keywords: Composite Laminates, GA, Multi-objectiveOptimisation, Neural Networks, RBFNN.

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1141 Decision Algorithm for Smart Airbag Deployment Safety Issues

Authors: Aini Hussain, M A Hannan, Azah Mohamed, Hilmi Sanusi, Burhanuddin Yeop Majlis

Abstract:

Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.

Keywords: Crash severity analysis, occupant size classification, smart airbag, vehicle safety system.

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1140 Estimating the Costs of Conservation in Multiple Output Agricultural Setting

Authors: T. Chaiechi, N. Stoeckl

Abstract:

Scarcity of resources for biodiversity conservation gives rise to the need of strategic investment with priorities given to the cost of conservation. While the literature provides abundant methodological options for biodiversity conservation; estimating true cost of conservation remains abstract and simplistic, without recognising dynamic nature of the cost. Some recent works demonstrate the prominence of economic theory to inform biodiversity decisions, particularly on the costs and benefits of biodiversity however, the integration of the concept of true cost into biodiversity actions and planning are very slow to come by, and specially on a farm level. Conservation planning studies often use area as a proxy for costs neglecting different land values as well as protected areas. These literature consider only heterogeneous benefits while land costs are considered homogenous. Analysis with the assumption of cost homogeneity results in biased estimation; since not only it doesn’t address the true total cost of biodiversity actions and plans, but also it fails to screen out lands that are more (or less) expensive and/or difficult (or more suitable) for biodiversity conservation purposes, hindering validity and comparability of the results. Economies of scope” is one of the other most neglected aspects in conservation literature. The concept of economies of scope introduces the existence of cost complementarities within a multiple output production system and it suggests a lower cost during the concurrent production of multiple outputs by a given farm. If there are, indeed, economies of scope then simplistic representation of costs will tend to overestimate the true cost of conservation leading to suboptimal outcomes. The aim of this paper, therefore, is to provide first road review of the various theoretical ways in which economies of scope are likely to occur of how they might occur in conservation. Consequently, the paper addresses gaps that have to be filled in future analysis.

Keywords: Cost, biodiversity conservation, Multi-output production systems, Empirical techniques.

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1139 A Descriptive Study of Self-Compassion in Polytechnic Students in Indonesia

Authors: Emma Dwi Ariyani, Dini Hadiani

Abstract:

This article reports the descriptive analysis of self-compassion in polytechnic students. It has been long believed that self-compassion can improve students’ motivation in completing their studies. This research was conducted with the aim to see the degree of self-compassion in polytechnic students in Indonesia by using Neff's Self-Compassion Scale (short form) measurement tool consisting of 12 items. The research method used was descriptive study with survey technique on 255 students. The results showed that 78% of students had low self-compassion and 22% had high self-compassion. This revealed that polytechnic students still criticize themselves harshly, make a poor judgment and bad self-appraisal, and they also cannot accept their imperfection and consider it as a self-judgment. The students also tend to think that they are the only ones that experience failure and suffering. This can lead to a sense of isolation (self-isolation). Furthermore, the students are often too concerned with aspects that are not liked both in themselves and in life (over-identification). Improving the students’ level of self-compassion can be done by building an educational climate that not only criticizes the students but provides feedback as well. This should focus on the students’ real behavior rather than the students’ general character.

Keywords: Descriptive study, polytechnic students, Indonesia, self-compassion.

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1138 Mobile to Server Face Recognition: A System Overview

Authors: Nurulhuda Ismail, Mas Idayu Md. Sabri

Abstract:

This paper presents a system overview of Mobile to Server Face Recognition, which is a face recognition application developed specifically for mobile phones. Images taken from mobile phone cameras lack of quality due to the low resolution of the cameras. Thus, a prototype is developed to experiment the chosen method. However, this paper shows a result of system backbone without the face recognition functionality. The result demonstrated in this paper indicates that the interaction between mobile phones and server is successfully working. The result shown before the database is completely ready. The system testing is currently going on using real images and a mock-up database to test the functionality of the face recognition algorithm used in this system. An overview of the whole system including screenshots and system flow-chart are presented in this paper. This paper also presents the inspiration or motivation and the justification in developing this system.

Keywords: Mobile to server, face recognition, system overview.

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1137 A Scenario Oriented Supplier Selection by Considering a Multi Tier Supplier Network

Authors: Mohammad Najafi Nobar, Bahareh Pourmehr, Mehdi Hajimirarab

Abstract:

One of the main processes of supply chain management is supplier selection process which its accurate implementation can dramatically increase company competitiveness. In presented article model developed based on the features of second tiers suppliers and four scenarios are predicted in order to help the decision maker (DM) in making up his/her mind. In addition two tiers of suppliers have been considered as a chain of suppliers. Then the proposed approach is solved by a method combined of concepts of fuzzy set theory (FST) and linear programming (LP) which has been nourished by real data extracted from an engineering design and supplying parts company. At the end results reveal the high importance of considering second tier suppliers features as criteria for selecting the best supplier.

Keywords: Supply Chain Management (SCM), SupplierSelection, Second Tier Supplier, Scenario Planning, Green Factor, Linear Programming, Fuzzy Set Theory

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1136 Musculoskeletal Pain, Work Characteristics and Presenteeism among Hotel Employees

Authors: Ruey-Yu Chen, Yao-Tsung Chang, Ching-Ying Yeh, Yu-Ting Huang

Abstract:

Musculoskeletal problems in the hotel sector have been little studied. The aim of this study was to examine relationships of musculoskeletal pain and work characteristics with presenteeism, i.e., feeling sick but going to work anyway. Data of a self-reported questionnaire were collected from 1,101 employees, who joined the study on a voluntary basis from four hotels in northern Taiwan. The results showed that respondents who were female, were younger, had a higher educational level, and worked in the real-service department had higher presenteeism. There were significant positive associations between presenteeism and heavy loads, frequent beatings or hits of hard objects, improper bench height, employees’ lower limb and lower back pain. Our study results imply that knowledge of work characteristics and employees' musculoskeletal problems could be advantageously used to reduce presenteeism in the workplace.

Keywords: Musculoskeletal pain, absenteeism, presenteeism, hotel employees.

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1135 Main Bearing Stiffness Investigation

Authors: B. Bellakhdhar, A. Dogui, J.L. Ligier

Abstract:

Simplified coupled engine block-crankshaft models based on beam theory provide an efficient substitute to engine simulation in the design process. These models require accurate definition of the main bearing stiffness. In this paper, an investigation of this stiffness is presented. The clearance effect is studied using a smooth bearing model. It is manifested for low shaft displacement. The hydrodynamic assessment model shows that the oil film has no stiffness for low loads and it is infinitely rigid for important loads. The deformation stiffness is determined using a suitable finite elements model based on real CADs. As a result, a main bearing behaviour law is proposed. This behaviour law takes into account the clearance, the hydrodynamic sustention and the deformation stiffness. It ensures properly the transition from the configuration low rigidity to the configuration high rigidity.

Keywords: Clearance, deformation stiffness, main bearing behaviour law, oil film stiffness

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1134 Multi-Level Pulse Width Modulation to Boost the Power Efficiency of Switching Amplifiers for Analog Signals with Very High Crest Factor

Authors: Jan Doutreloigne

Abstract:

The main goal of this paper is to develop a switching amplifier with optimized power efficiency for analog signals with a very high crest factor such as audio or DSL signals. Theoretical calculations show that a switching amplifier architecture based on multi-level pulse width modulation outperforms all other types of linear or switching amplifiers in that respect. Simulations on a 2 W multi-level switching audio amplifier, designed in a 50 V 0.35 mm IC technology, confirm its superior performance in terms of power efficiency. A real silicon implementation of this audio amplifier design is currently underway to provide experimental validation.

Keywords: Audio amplifier, multi-level switching amplifier, power efficiency, pulse width modulation, PWM, self-oscillating amplifier.

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1133 Virtual Training, Human-Computer and Software Interactions, and Social-Based Embodiness

Authors: Philippe Fauquet-Alekhine

Abstract:

For professions of high risk industries, simulation training has always been thought in terms of high degree of fidelity regarding the real operational situation. Due to the recent progress, this way of training is changing, modifying the human-computer and software interactions: the interactions between trainees during simulation training session tend to become virtual, transforming the social-based embodiness (the way subjects integrate social skills for interpersonal relationship with co-workers). On the basis of the analysis of eight different profession trainings, a categorization of interactions has help to produce an analytical tool, the social interactions table. This tool may be very valuable to point out the changes of social interactions when the training sessions are skipping from a high fidelity simulator to a virtual simulator. In this case, it helps the designers of professional training to analyze and to assess the consequences of the potential lack the social-based embodiness.

Keywords: Interface, interaction, simulator, virtual training.

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1132 Parallel Discrete Fourier Transform for Fast FIR Filtering Based on Overlapped-save Block Structure

Authors: Ying-Wen Bai, Ju-Maw Chen

Abstract:

To successfully provide a fast FIR filter with FTT algorithms, overlapped-save algorithms can be used to lower the computational complexity and achieve the desired real-time processing. As the length of the input block increases in order to improve the efficiency, a larger volume of zero padding will greatly increase the computation length of the FFT. In this paper, we use the overlapped block digital filtering to construct a parallel structure. As long as the down-sampling (or up-sampling) factor is an exact multiple lengths of the impulse response of a FIR filter, we can process the input block by using a parallel structure and thus achieve a low-complex fast FIR filter with overlapped-save algorithms. With a long filter length, the performance and the throughput of the digital filtering system will also be greatly enhanced.

Keywords: FIR Filter, Overlapped-save Algorithm, ParallelStructure

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1131 Statistical Wavelet Features, PCA, and SVM Based Approach for EEG Signals Classification

Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

Abstract:

The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the supportvectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: Discrete Wavelet Transform, Electroencephalogram, Pattern Recognition, Principal Component Analysis, Support Vector Machine.

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1130 Proposing Problem-Based Learning as an Effective Pedagogical Technique for Social Work Education

Authors: Christine K. Fulmer

Abstract:

Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.

Keywords: Constructivist theoretical approach, experiential learning, pedagogy, problem-based learning, social work education.

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1129 Various Advanced Statistical Analyses of Index Values Extracted from Outdoor Agricultural Workers Motion Data

Authors: Shinji Kawakura, Ryosuke Shibasaki

Abstract:

We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.

Keywords: Advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis.

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1128 A Study on the Effect of Variation of the Cross-sectional Area of Spiral Volute Casing for Centrifugal Pump

Authors: Hyun Bae Jin, Myung Jin Kim, Wui Jun Chung

Abstract:

The impeller and the casing are the key components of a centrifugal pump. Although there have been many studies on the impeller and the volute casing of centrifugal pump, further study of the volute casing to improve the performance of centrifugal pumps is needed. In this paper, the effect of cross-sectional area on the performance of volute casing was investigated using a commercial CFD code. The performance characteristics, not only at the off-design point but also for a full type model are required these days. So we conducted numerical analysis for all operating points by using complete geometry through transient analysis. Transient analysis on the complete geometry of a real product has the advantage of simulating realistic flow. The results of this study show the variation of a performance curve by modifying the above-mentioned design parameter.

Keywords: Centrifugal Pump, Volute Casing, Cross-Section area, CFD

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1127 Theoretical Background of Dividend Taxation

Authors: Margareta Ilkova, Petr Teply

Abstract:

The article deals with dividends and their distribution from investors from a theoretical point of view. Some studies try to analyzed the reaction of the market on the dividend announcement and found out the change of dividend policy is associated with abnormal returns around the dividend announcement date. Another researches directly questioned the investors about their dividend preference and beliefs. Investors want the dividend from many reasons (e.g. some of them explain the dividend preference by the existence of transaction cost; investors prefer the dividend today, because there is less risky; the managers have private information about the firm). The most controversial theory of dividend policy was developed by Modigliani and Miller (1961) who demonstrated that in the perfect and complete capital markets the dividend policy is irrelevant and the value of the company is independent of its payout policy. Nevertheless, in the real world the capital markets are imperfect, because of asymmetric information, transaction costs, incomplete contracting possibilities and taxes.

Keywords: dividend distribution, taxation, payout policy, investor, Modigliani and Miller theorem

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1126 Power System Security Assessment using Binary SVM Based Pattern Recognition

Authors: S Kalyani, K Shanti Swarup

Abstract:

Power System Security is a major concern in real time operation. Conventional method of security evaluation consists of performing continuous load flow and transient stability studies by simulation program. This is highly time consuming and infeasible for on-line application. Pattern Recognition (PR) is a promising tool for on-line security evaluation. This paper proposes a Support Vector Machine (SVM) based binary classification for static and transient security evaluation. The proposed SVM based PR approach is implemented on New England 39 Bus and IEEE 57 Bus systems. The simulation results of SVM classifier is compared with the other classifier algorithms like Method of Least Squares (MLS), Multi- Layer Perceptron (MLP) and Linear Discriminant Analysis (LDA) classifiers.

Keywords: Static Security, Transient Security, Pattern Recognition, Classifier, Support Vector Machine.

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1125 General Process Control for Intelligent Systems

Authors: Radovan Holubek, Matus Vlasek, Peter Kostal

Abstract:

Development of intelligent assembly cell conception includes new solution kind of how to create structures of automated and flexible assembly system. The current trend of the final product quality increasing is affected by time analysis of the entire manufacturing process. The primary requirement of manufacturing is to produce as many products as soon as possible, at the lowest possible cost, but of course with the highest quality. Such requirements may be satisfied only if all the elements entering and affecting the production cycle are in a fully functional condition. These elements consist of sensory equipment and intelligent control elements that are essential for building intelligent manufacturing systems. Intelligent behavior of the system as the control system will repose on monitoring of important parameters of the system in the real time. Intelligent manufacturing system itself should be a system that can flexibly respond to changes in entering and exiting the process in interaction with the surroundings.

Keywords: Control system, intelligent manufacturing / assemble systems, manufacturing, monitoring process.

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1124 Intelligent Rescheduling Trains for Air Pollution Management

Authors: Kainat Affrin, P. Reshma, G. Narendra Kumar

Abstract:

Optimization of timetable is the need of the day for the rescheduling and routing of trains in real time. Trains are scheduled in parallel with the road transport vehicles to the same destination. As the number of trains is restricted due to single track, customers usually opt for road transport to use frequently. The air pollution increases as the density of vehicles on road transport is increased. Use of an alternate mode of transport like train helps in reducing air-pollution. This paper mainly aims at attracting the passengers to Train transport by proper rescheduling of trains using hybrid of stop-skip algorithm and iterative convex programming algorithm. Rescheduling of train bi-directionally is achieved on a single track with dynamic dual time and varying stops. Introduction of more trains attract customers to use rail transport frequently, thereby decreasing the pollution. The results are simulated using Network Simulator (NS-2).

Keywords: Air pollution, routing protocol, network simulator, rescheduling.

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1123 MITAutomatic ECG Beat Tachycardia Detection Using Artificial Neural Network

Authors: R. Amandi, A. Shahbazi, A. Mohebi, M. Bazargan, Y. Jaberi, P. Emadi, A. Valizade

Abstract:

The application of Neural Network for disease diagnosis has made great progress and is widely used by physicians. An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which was the great motivation towards our study. In our work, tachycardia features obtained are used for the training and testing of a Neural Network. In this study we are using Fuzzy Probabilistic Neural Networks as an automatic technique for ECG signal analysis. As every real signal recorded by the equipment can have different artifacts, we needed to do some preprocessing steps before feeding it to our system. Wavelet transform is used for extracting the morphological parameters of the ECG signal. The outcome of the approach for the variety of arrhythmias shows the represented approach is superior than prior presented algorithms with an average accuracy of about %95 for more than 7 tachy arrhythmias.

Keywords: Fuzzy Logic, Probabilistic Neural Network, Tachycardia, Wavelet Transform.

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1122 Content Based Sampling over Transactional Data Streams

Authors: Mansour Tarafdar, Mohammad Saniee Abade

Abstract:

This paper investigates the problem of sampling from transactional data streams. We introduce CFISDS as a content based sampling algorithm that works on a landmark window model of data streams and preserve more informed sample in sample space. This algorithm that work based on closed frequent itemset mining tasks, first initiate a concept lattice using initial data, then update lattice structure using an incremental mechanism.Incremental mechanism insert, update and delete nodes in/from concept lattice in batch manner. Presented algorithm extracts the final samples on demand of user. Experimental results show the accuracy of CFISDS on synthetic and real datasets, despite on CFISDS algorithm is not faster than exist sampling algorithms such as Z and DSS.

Keywords: Sampling, data streams, closed frequent item set mining.

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1121 Effect of Variable viscosity on Convective Heat Transfer along an Inclined Plate Embedded in Porous Medium with an Applied Magnetic Field

Authors: N.S. Tomer, Phool Singh, Manoj Kumar

Abstract:

The flow and heat transfer characteristics for natural convection along an inclined plate in a saturated porous medium with an applied magnetic field have been studied. The fluid viscosity has been assumed to be an inverse function of temperature. Assuming temperature vary as a power function of distance. The transformed ordinary differential equations have solved by numerical integration using Runge-Kutta method. The velocity and temperature profile components on the plate are computed and discussed in detail for various values of the variable viscosity parameter, inclination angle, magnetic field parameter, and real constant (λ). The results have also been interpreted with the aid of tables and graphs. The numerical values of Nusselt number have been calculated for the mentioned parameters.

Keywords: Heat Transfer, Magnetic Field, Porosity, Viscosity

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1120 Online Collaborative Learning System Using Speech Technology

Authors: Sid-Ahmed. Selouani, Tang-Ho Lê, Chadia Moghrabi, Benoit Lanteigne, Jean Roy

Abstract:

A Web-based learning tool, the Learn IN Context (LINC) system, designed and being used in some institution-s courses in mixed-mode learning, is presented in this paper. This mode combines face-to-face and distance approaches to education. LINC can achieve both collaborative and competitive learning. In order to provide both learners and tutors with a more natural way to interact with e-learning applications, a conversational interface has been included in LINC. Hence, the components and essential features of LINC+, the voice enhanced version of LINC, are described. We report evaluation experiments of LINC/LINC+ in a real use context of a computer programming course taught at the Université de Moncton (Canada). The findings show that when the learning material is delivered in the form of a collaborative and voice-enabled presentation, the majority of learners seem to be satisfied with this new media, and confirm that it does not negatively affect their cognitive load.

Keywords: E-leaning, Knowledge Network, Speech recognition, Speech synthesis.

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1119 Networked Radar System to Increase Safety of Urban Railroad Crossing

Authors: S. Saponara, L. Fanucci, R. Cassettari, P. Ruggiero, M. Righetto

Abstract:

The paper presents an innovative networked radar system for detection of obstacles in a railway level crossing scenario. This Monitoring System (MS) is able to detect moving or still obstacles within the railway level crossing area automatically, avoiding the need of human presence for surveillance. The MS is also connected to the National Railway Information and Signaling System to communicate in real-time the level crossing status. The architecture is compliant with the highest Safety Integrity Level (SIL4) of the CENELEC standard. The number of radar sensors used is configurable at set-up time and depends on how large the level crossing area can be. At least two sensors are expected and up four can be used for larger areas. The whole processing chain that elaborates the output sensor signals, as well as the communication interface, is fully-digital, was designed in VHDL code and implemented onto a Xilinx Virtex 6.

Keywords: Radar for safe mobility, railroad crossing, railway, transport safety.

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