Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798370
S. Karmakar, M. Kowar, P. Guhathakurta
Attempt to recognize pattern of meteorological parameters over the smaller scale geographical region (district) artificial neural network models have been developed. 54 years data for 1951-2004 have been used, of which the first 41 years (1951-1991) of data are used for training the network and data for the period 1991-2004 are used independently for validation. We have found that the mean absolute deviation (% of mean) between actual and predicted values of the each model is less than and half of the standard deviation (% of mean) in the independent period (1991-2004). The performances of these models in pattern recognition and prediction have been found to be extremely good. The models are developed and their evaluations have been presented in this paper.
{"title":"Development of Artificial Neural Network Models for Long-Range Meteorological Parameters Pattern Recognition over the Smaller Scale Geographical Region-District","authors":"S. Karmakar, M. Kowar, P. Guhathakurta","doi":"10.1109/ICIINFS.2008.4798370","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798370","url":null,"abstract":"Attempt to recognize pattern of meteorological parameters over the smaller scale geographical region (district) artificial neural network models have been developed. 54 years data for 1951-2004 have been used, of which the first 41 years (1951-1991) of data are used for training the network and data for the period 1991-2004 are used independently for validation. We have found that the mean absolute deviation (% of mean) between actual and predicted values of the each model is less than and half of the standard deviation (% of mean) in the independent period (1991-2004). The performances of these models in pattern recognition and prediction have been found to be extremely good. The models are developed and their evaluations have been presented in this paper.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115223785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798351
Sajal Kumar Das, B. Nath
When data objects that are the subject of analysis using machine learning techniques are described by a large number of feature (i.e. the data is high dimension) it is often beneficial to reduce the dimension of the data. dimensionality reduction (DR) can be beneficial not only reasons of computational efficiency but also because it can improve the accuracy of the analysis. Now we have tried to introduce a novel transform to achieve dimensionality reduction. This paper summarizes survey on feature selection and extraction from high-dimensionality data sets using genetic algorithm. The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, to obtain the accuracy and saves the computation time and simplifies the result. We are trying to develop GA-based approach utilizing a feedback linkage between feature evaluation and association rule. That is we carry out feature selection simultaneously with association rule mining, through "genetic learning and evolution.
{"title":"Dimesionality Reduction using Association Rule Mining","authors":"Sajal Kumar Das, B. Nath","doi":"10.1109/ICIINFS.2008.4798351","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798351","url":null,"abstract":"When data objects that are the subject of analysis using machine learning techniques are described by a large number of feature (i.e. the data is high dimension) it is often beneficial to reduce the dimension of the data. dimensionality reduction (DR) can be beneficial not only reasons of computational efficiency but also because it can improve the accuracy of the analysis. Now we have tried to introduce a novel transform to achieve dimensionality reduction. This paper summarizes survey on feature selection and extraction from high-dimensionality data sets using genetic algorithm. The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, to obtain the accuracy and saves the computation time and simplifies the result. We are trying to develop GA-based approach utilizing a feedback linkage between feature evaluation and association rule. That is we carry out feature selection simultaneously with association rule mining, through \"genetic learning and evolution.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"15 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120821014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798487
K. K. Mohan, A. K. Verma, A. Srividya, G. V. Rao, R. Gedela
In a competitive business landscape, large organizations such as insurance companies and banks are under high pressure to innovate, improvise and distinguish their products and services while continuing to reduce the time-to market for new product introductions. Generating a single view of the customer is vital from different perspectives of the systems developer over a period of time because of the existence of disconnected systems within an enterprise. Therefore, to increase revenues and cost optimization, it is important to build enterprise systems more closely with the business requirements by reusing the existing systems. While building distributed based applications, it is important to take into account the proven processes like Rational Unified Process (RUP) to mitigate risks and increase the reliability of systems. Experiences in developing applications in Java Enterprise Edition (JEE) with customized RUP have been presented in this paper. RUP is adopted into an onsite-offshore development model along with ISO 9001 and SEICMM Level 5 standards. This paper provides an RUP approach to achieve increased reliability with higher productivity and lower defect density along with competitiveness through cost effective custom software solutions. Quantitative software reliability prediction is done using Generalized Stochastic Petri Nets, based on the RUP implemented prototype obtained from the PoC of a financial application prior to the actual implementation of the application development.
{"title":"Early Quantitative Software Reliability Prediction Using Petri-nets","authors":"K. K. Mohan, A. K. Verma, A. Srividya, G. V. Rao, R. Gedela","doi":"10.1109/ICIINFS.2008.4798487","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798487","url":null,"abstract":"In a competitive business landscape, large organizations such as insurance companies and banks are under high pressure to innovate, improvise and distinguish their products and services while continuing to reduce the time-to market for new product introductions. Generating a single view of the customer is vital from different perspectives of the systems developer over a period of time because of the existence of disconnected systems within an enterprise. Therefore, to increase revenues and cost optimization, it is important to build enterprise systems more closely with the business requirements by reusing the existing systems. While building distributed based applications, it is important to take into account the proven processes like Rational Unified Process (RUP) to mitigate risks and increase the reliability of systems. Experiences in developing applications in Java Enterprise Edition (JEE) with customized RUP have been presented in this paper. RUP is adopted into an onsite-offshore development model along with ISO 9001 and SEICMM Level 5 standards. This paper provides an RUP approach to achieve increased reliability with higher productivity and lower defect density along with competitiveness through cost effective custom software solutions. Quantitative software reliability prediction is done using Generalized Stochastic Petri Nets, based on the RUP implemented prototype obtained from the PoC of a financial application prior to the actual implementation of the application development.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125868016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798355
M. Kowsalya, K. K. Ray, D. Kothari, Abhishek Kumar, Aurav Ghai
The relative positions of the bus voltage phasors in the voltage space of a system depend on the characteristics of and the power flow in, the transmission network. When the voltage space of the system is examined with respect to the "centroid" of the system voltage space, it is possible to identify the loadability of buses and rank them accordingly. A technique based on concepts applied to equilibrium analysis of rigid bodies is developed to determine the centroid voltage of the system voltage space and centroid voltage of the generator voltage space. The relative positions of the bus voltage phasors with respect to the centroid voltage of the system voltage space and centroid voltage of the generator voltage space are used to identify and compute a voltage stability index for the load buses in the system. The developed index [C2] is optimized using particle swarm optimization (PSO) and differential evolution algorithm (DE). The algorithm minimizes the voltage stability index of all the load buses to improve the static voltage stability margin.
{"title":"A Fast Technique of Voltage Stability Analysis and Optimization in the Grid Network","authors":"M. Kowsalya, K. K. Ray, D. Kothari, Abhishek Kumar, Aurav Ghai","doi":"10.1109/ICIINFS.2008.4798355","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798355","url":null,"abstract":"The relative positions of the bus voltage phasors in the voltage space of a system depend on the characteristics of and the power flow in, the transmission network. When the voltage space of the system is examined with respect to the \"centroid\" of the system voltage space, it is possible to identify the loadability of buses and rank them accordingly. A technique based on concepts applied to equilibrium analysis of rigid bodies is developed to determine the centroid voltage of the system voltage space and centroid voltage of the generator voltage space. The relative positions of the bus voltage phasors with respect to the centroid voltage of the system voltage space and centroid voltage of the generator voltage space are used to identify and compute a voltage stability index for the load buses in the system. The developed index [C2] is optimized using particle swarm optimization (PSO) and differential evolution algorithm (DE). The algorithm minimizes the voltage stability index of all the load buses to improve the static voltage stability margin.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125504204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798474
R. Singh, S. Goswami
This paper addresses the effect of load models on nodal pricing and revenue generation of distributed generation (DG) in distribution network. Most of the literatures dealing with DGs have assumed loads as constant in their analyses. Since the loads are voltage and frequency sensitive, analysis assuming constant loads will give inaccurate and misleading results. Under deregulation locational pricing of power is popular in the context of transmission system. It is relevant to study the applicability of the pricing strategies in distribution system having distributed generation. It is shown that DG resources obtain more revenue under nodal pricing. It is further established that load models can significantly change the nodal prices and revenue of DG, and presence of DG improves voltage profile all around in the distribution network. The effectiveness of this work is verified through simulation results on a rural radial distribution system under time varying loading condition.
{"title":"Evaluation of Nodal Prices and Revenue of Distributed Generation in Distribution Network Including Load Model","authors":"R. Singh, S. Goswami","doi":"10.1109/ICIINFS.2008.4798474","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798474","url":null,"abstract":"This paper addresses the effect of load models on nodal pricing and revenue generation of distributed generation (DG) in distribution network. Most of the literatures dealing with DGs have assumed loads as constant in their analyses. Since the loads are voltage and frequency sensitive, analysis assuming constant loads will give inaccurate and misleading results. Under deregulation locational pricing of power is popular in the context of transmission system. It is relevant to study the applicability of the pricing strategies in distribution system having distributed generation. It is shown that DG resources obtain more revenue under nodal pricing. It is further established that load models can significantly change the nodal prices and revenue of DG, and presence of DG improves voltage profile all around in the distribution network. The effectiveness of this work is verified through simulation results on a rural radial distribution system under time varying loading condition.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122699423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798380
Pravinkumar D. Patel, Miteshkumar N. Priyadrshi, V. Patel
A DC-DC converter of 10 KW capacity for converting 144 V DC voltage available as a battery supply to 600 V DC for battery backup drive is presented in this paper. The converter uses full bridge inverter - transformer -rectifier scheme to provide galvanic isolation between input and output and uses IGBTs to switch at 6 KHZ. The simulation results are shown and discussed. In this paper, a phase shifted control scheme is compared with conventional control scheme applied to an isolated dc-dc converter configuration with full-bridge inverter at the primary side and a fast recovery rectification method at the secondary side of the transformers. The proposed scheme is illustrated and experimentally verified by a 600 V, 10 kW prototype.
{"title":"Design and Implementation of Isolated High Power DC/DC Boost Converter Using DSP","authors":"Pravinkumar D. Patel, Miteshkumar N. Priyadrshi, V. Patel","doi":"10.1109/ICIINFS.2008.4798380","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798380","url":null,"abstract":"A DC-DC converter of 10 KW capacity for converting 144 V DC voltage available as a battery supply to 600 V DC for battery backup drive is presented in this paper. The converter uses full bridge inverter - transformer -rectifier scheme to provide galvanic isolation between input and output and uses IGBTs to switch at 6 KHZ. The simulation results are shown and discussed. In this paper, a phase shifted control scheme is compared with conventional control scheme applied to an isolated dc-dc converter configuration with full-bridge inverter at the primary side and a fast recovery rectification method at the secondary side of the transformers. The proposed scheme is illustrated and experimentally verified by a 600 V, 10 kW prototype.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122637190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798358
P. Shrivasthava, P. Vundavilli, D. K. Pratihar
During locomotion, one of various important tasks, a biped robot has to perform is the identification of 3D environment. The present work addresses the problem of offline 3D reconstruction of the environment using a stereo-vision system. The developed stereo-vision system works based on the concept of an epipolar geometry. The mathematical model that interpolates 3D position of a point with the help of an observed 2D point by two cameras, has been utilized to extract and virtually reproduce the environment, such as a staircase, a sloping surface and a ditch surface. The extracted information from the vision module may be used to plan the path of the biped robot in the said environment.
{"title":"An Approach for 3D Reconstruction of Environment Using Stereo-Vision System","authors":"P. Shrivasthava, P. Vundavilli, D. K. Pratihar","doi":"10.1109/ICIINFS.2008.4798358","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798358","url":null,"abstract":"During locomotion, one of various important tasks, a biped robot has to perform is the identification of 3D environment. The present work addresses the problem of offline 3D reconstruction of the environment using a stereo-vision system. The developed stereo-vision system works based on the concept of an epipolar geometry. The mathematical model that interpolates 3D position of a point with the help of an observed 2D point by two cameras, has been utilized to extract and virtually reproduce the environment, such as a staircase, a sloping surface and a ditch surface. The extracted information from the vision module may be used to plan the path of the biped robot in the said environment.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121894592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798356
A. Aloisio, P. Branchini
The VME64x standard defines a double edge source synchronous block transfer (2eSST) capable to sustain a data transfer rate up to 320 MByte/s on the VMEbus. This level of performance is achieved by double edge clocking a 64-bit bus with bursts of data strobe pulses. The switching activity of such a wide bus on a shared backplane challenges the signal integrity and the data transfer reliability. The bus-invert is a well known coding technique developed to lower the peak power dissipation in I/O busses by decreasing their switching activity. In this paper we discuss how the bus-invert coding can be applied to improve the 2eSST performance. The hardware overheads introduced by the encoding algorithm is discussed in the view of deployments in low-latency, real-time applications.
{"title":"Synchronous VME64x Block Transfers with Bus-Invert Coding For Low Noise, Low Power Performance","authors":"A. Aloisio, P. Branchini","doi":"10.1109/ICIINFS.2008.4798356","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798356","url":null,"abstract":"The VME64x standard defines a double edge source synchronous block transfer (2eSST) capable to sustain a data transfer rate up to 320 MByte/s on the VMEbus. This level of performance is achieved by double edge clocking a 64-bit bus with bursts of data strobe pulses. The switching activity of such a wide bus on a shared backplane challenges the signal integrity and the data transfer reliability. The bus-invert is a well known coding technique developed to lower the peak power dissipation in I/O busses by decreasing their switching activity. In this paper we discuss how the bus-invert coding can be applied to improve the 2eSST performance. The hardware overheads introduced by the encoding algorithm is discussed in the view of deployments in low-latency, real-time applications.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122116358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798433
M. L. Prasad, M. Roy, C. K. Roy
Ferroresonance is a nonlinear oscillatory phenomenon, which occurs in capacitively coupled transformers under certain conditions in a power system. The magnetizing branch of the transformer at no-load is modeled by nonlinear equation. The coupling capacitances are treated as parameters and different numerical simulations of ferroresonance are performed. The power spectral density and phase plane analyses are conducted on ferroresonance over-voltage generated across transformer to identify the modes of ferroresonance.
{"title":"Analysis of Ferroresonant Oscillations in a Nonlinear Circuit","authors":"M. L. Prasad, M. Roy, C. K. Roy","doi":"10.1109/ICIINFS.2008.4798433","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798433","url":null,"abstract":"Ferroresonance is a nonlinear oscillatory phenomenon, which occurs in capacitively coupled transformers under certain conditions in a power system. The magnetizing branch of the transformer at no-load is modeled by nonlinear equation. The coupling capacitances are treated as parameters and different numerical simulations of ferroresonance are performed. The power spectral density and phase plane analyses are conducted on ferroresonance over-voltage generated across transformer to identify the modes of ferroresonance.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128314880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-12-01DOI: 10.1109/ICIINFS.2008.4798444
B. Sreejith, A. K. Verma, A. Srividya
Rolling element bearings are critical mechanical components in rotating machinery. Fault detection and diagnosis in the early stages of damage is necessary to prevent their malfunctioning and failure during operation. Vibration monitoring is the most widely used and cost-effective monitoring technique to detect, locate and distinguish faults in rolling element bearings. This paper presents an algorithm using feed forward neural network for automated diagnosis of localized faults in rolling element bearings. Normal negative log-likelihood value and kurtosis value extracted from time-domain vibration signals are used as input features for the neural network. Trained neural networks are able to classify different states of the bearing with 100% accuracy. The proposed procedure requires only a few input features, resulting in simple preprocessing and faster training. Effectiveness of the proposed method is illustrated using the bearing vibration data obtained experimentally.
{"title":"Fault diagnosis of rolling element bearing using time-domain features and neural networks","authors":"B. Sreejith, A. K. Verma, A. Srividya","doi":"10.1109/ICIINFS.2008.4798444","DOIUrl":"https://doi.org/10.1109/ICIINFS.2008.4798444","url":null,"abstract":"Rolling element bearings are critical mechanical components in rotating machinery. Fault detection and diagnosis in the early stages of damage is necessary to prevent their malfunctioning and failure during operation. Vibration monitoring is the most widely used and cost-effective monitoring technique to detect, locate and distinguish faults in rolling element bearings. This paper presents an algorithm using feed forward neural network for automated diagnosis of localized faults in rolling element bearings. Normal negative log-likelihood value and kurtosis value extracted from time-domain vibration signals are used as input features for the neural network. Trained neural networks are able to classify different states of the bearing with 100% accuracy. The proposed procedure requires only a few input features, resulting in simple preprocessing and faster training. Effectiveness of the proposed method is illustrated using the bearing vibration data obtained experimentally.","PeriodicalId":429889,"journal":{"name":"2008 IEEE Region 10 and the Third international Conference on Industrial and Information Systems","volume":"45 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113987425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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