Pub Date : 2010-05-05DOI: 10.1109/INES.2010.5483825
P. Laczkó, B. Fehér, B. Benyó
BLAST, the most widely used bioinformatics search tool, is routinely used for tasks infeasible to run on commodity computer systems. Prefiltering appears to be a promising acceleration approach that conserves the behavior of the original program yet provides significant search speedup. We conceived and implemented one such prefilter system based on FPGA accelerator technology. Our results indicate that our system may prove to be a viable BLAST accelerator solution.
{"title":"FPGA-based BLAST prefiltering","authors":"P. Laczkó, B. Fehér, B. Benyó","doi":"10.1109/INES.2010.5483825","DOIUrl":"https://doi.org/10.1109/INES.2010.5483825","url":null,"abstract":"BLAST, the most widely used bioinformatics search tool, is routinely used for tasks infeasible to run on commodity computer systems. Prefiltering appears to be a promising acceleration approach that conserves the behavior of the original program yet provides significant search speedup. We conceived and implemented one such prefilter system based on FPGA accelerator technology. Our results indicate that our system may prove to be a viable BLAST accelerator solution.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121254830","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 : 2010-05-05DOI: 10.1109/INES.2010.5483839
J. F. Kotowski, E. Szlachcic, P. M. Wańtowski
In this paper, we propose a portfolio selection method based on a set of technical trading rules, which are optimized by a genetic algorithm. The aim of the research was to check if it is possible to obtain a set of trading rules deriving from technical indicators, which could be used to create a portfolio able to outperform standard portfolio models based upon Modern Portfolio Theory. On the contrary to the typical portfolio approach incorporating expected return and variance, presented method relies on market momentum analysis and stock timing using selected technical indicators.
{"title":"Portfolio selection based on technical trading rules optimized with a genetic algorithm","authors":"J. F. Kotowski, E. Szlachcic, P. M. Wańtowski","doi":"10.1109/INES.2010.5483839","DOIUrl":"https://doi.org/10.1109/INES.2010.5483839","url":null,"abstract":"In this paper, we propose a portfolio selection method based on a set of technical trading rules, which are optimized by a genetic algorithm. The aim of the research was to check if it is possible to obtain a set of trading rules deriving from technical indicators, which could be used to create a portfolio able to outperform standard portfolio models based upon Modern Portfolio Theory. On the contrary to the typical portfolio approach incorporating expected return and variance, presented method relies on market momentum analysis and stock timing using selected technical indicators.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123775659","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 : 2010-05-05DOI: 10.1109/INES.2010.5483832
Czeslaw Smutnicki
Approaches used to solve optimization tasks generated in problems of control, planning, designing and management have completely changed during recent years. Cases with unimodal, convex, differentiable scalar goal functions have disappeared from research labs, because a lot of satisfactory efficient methods were developed. On the battle square there have remained hard cases: multimodal, multi-criteria, non-differentiable, NP-hard, discrete, with huge dimensionality. These practical tasks, generated by industry and market, have caused serious troubles in seeking global optimum. Main reasons of these troubles are recognized as: huge cardinality of local extremes frequently with the exponential number of extremes; curse of dimensionality; NP-hardness; lack of differentiability. Unfortunately, known “classical” exact solution methods have considered as rather weak in so hard conditions of the work. From the beginning of eighties have been observed fast development of approximate methods, resistant to local extremes. In fact, practice of these methods antecede development of the suitable theory, which has been formed usually 10–15 years later than the time moment of creating the approach. That's why we observe now more than 20 different approaches inspired by Nature and more than 30 if we include parallel computing environments. The paper presents critical survey of methods, approaches and trends observed in modern optimization, focusing on nature-inspired techniques recommended for particularly hard problems. Applicability of the methods, depending the class of stated optimization task and classes of goal function, have been discussed. Numerical as well theoretical properties of these algorithms are shown. Newest our own very efficient proposals are also provided.
{"title":"New trends in optimization","authors":"Czeslaw Smutnicki","doi":"10.1109/INES.2010.5483832","DOIUrl":"https://doi.org/10.1109/INES.2010.5483832","url":null,"abstract":"Approaches used to solve optimization tasks generated in problems of control, planning, designing and management have completely changed during recent years. Cases with unimodal, convex, differentiable scalar goal functions have disappeared from research labs, because a lot of satisfactory efficient methods were developed. On the battle square there have remained hard cases: multimodal, multi-criteria, non-differentiable, NP-hard, discrete, with huge dimensionality. These practical tasks, generated by industry and market, have caused serious troubles in seeking global optimum. Main reasons of these troubles are recognized as: huge cardinality of local extremes frequently with the exponential number of extremes; curse of dimensionality; NP-hardness; lack of differentiability. Unfortunately, known “classical” exact solution methods have considered as rather weak in so hard conditions of the work. From the beginning of eighties have been observed fast development of approximate methods, resistant to local extremes. In fact, practice of these methods antecede development of the suitable theory, which has been formed usually 10–15 years later than the time moment of creating the approach. That's why we observe now more than 20 different approaches inspired by Nature and more than 30 if we include parallel computing environments. The paper presents critical survey of methods, approaches and trends observed in modern optimization, focusing on nature-inspired techniques recommended for particularly hard problems. Applicability of the methods, depending the class of stated optimization task and classes of goal function, have been discussed. Numerical as well theoretical properties of these algorithms are shown. Newest our own very efficient proposals are also provided.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126835294","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 : 2010-05-05DOI: 10.1109/INES.2010.5483840
M. Popa, A. Popa, H. Ciocarlie
Ad hoc network does not have an infrastructure, all the nodes have the same functionality and they act not only as sender or destination of a message but also as routers. The lack of infrastructure and the equality of the nodes are not always desirable. This paper proposes a layered architecture for ad hoc networks. It consists in a three layers structure. The first layer consists in a server connected to Internet, the second layer is made by partially mobile nodes connected to Internet and the third layer is made by totally mobile nodes found in the coverage area of different partially mobile nodes. An application was developed on the proposed architecture.
{"title":"A layered architecture for ad hoc networks of mobile embedded systems","authors":"M. Popa, A. Popa, H. Ciocarlie","doi":"10.1109/INES.2010.5483840","DOIUrl":"https://doi.org/10.1109/INES.2010.5483840","url":null,"abstract":"Ad hoc network does not have an infrastructure, all the nodes have the same functionality and they act not only as sender or destination of a message but also as routers. The lack of infrastructure and the equality of the nodes are not always desirable. This paper proposes a layered architecture for ad hoc networks. It consists in a three layers structure. The first layer consists in a server connected to Internet, the second layer is made by partially mobile nodes connected to Internet and the third layer is made by totally mobile nodes found in the coverage area of different partially mobile nodes. An application was developed on the proposed architecture.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122081108","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 : 2010-05-05DOI: 10.1109/INES.2010.5483866
K. Staniec, G. Debita
In the article it demonstrated that the neighbor-finding procedure in many nowadays wireless sensor networks bears a potential of generating an excessive radio interference. It is shown, based on Stojmenovič Minimum Spanning Tree algorithm, that the situation can be improved even in the worst case scenario of simultaneous transmission from all network nodes, by utilizing the directional antennas, taking the Signal-to-Noise and Interference ratio as a performance measure.
{"title":"Antenna beamwidth control for improving Signal-to-Noise ratio in wireless sensor networks","authors":"K. Staniec, G. Debita","doi":"10.1109/INES.2010.5483866","DOIUrl":"https://doi.org/10.1109/INES.2010.5483866","url":null,"abstract":"In the article it demonstrated that the neighbor-finding procedure in many nowadays wireless sensor networks bears a potential of generating an excessive radio interference. It is shown, based on Stojmenovič Minimum Spanning Tree algorithm, that the situation can be improved even in the worst case scenario of simultaneous transmission from all network nodes, by utilizing the directional antennas, taking the Signal-to-Noise and Interference ratio as a performance measure.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116317556","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 : 2010-05-05DOI: 10.1007/978-3-642-23229-9_18
V. Stoicu-Tivadar, L. Stoicu-Tivadar, S. Puscoci, D. Berian, V. Topac
{"title":"WebService-based solution for an intelligent telecare system","authors":"V. Stoicu-Tivadar, L. Stoicu-Tivadar, S. Puscoci, D. Berian, V. Topac","doi":"10.1007/978-3-642-23229-9_18","DOIUrl":"https://doi.org/10.1007/978-3-642-23229-9_18","url":null,"abstract":"","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130910214","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 : 2010-05-05DOI: 10.1109/INES.2010.5483856
A. Cichon, E. Szlachcic, J. F. Kotowski
In the paper an adapted version of the differential evolution algorithm has been created to solve a multi-objective optimization problem. Multi-objective Differential Evolution Algorithm using vector differences for perturbing the vector population with self adaptation is introduced. Through the combination of mutation strategies and self adaptation of crossover and differentiation constants the proposed MO algorithm performs better than the one with the simple DE scheme in terms of computation speed and quality of the generated multi-objective non-dominated solutions.
{"title":"Differential evolution for multi-objective optimization with self adaptation","authors":"A. Cichon, E. Szlachcic, J. F. Kotowski","doi":"10.1109/INES.2010.5483856","DOIUrl":"https://doi.org/10.1109/INES.2010.5483856","url":null,"abstract":"In the paper an adapted version of the differential evolution algorithm has been created to solve a multi-objective optimization problem. Multi-objective Differential Evolution Algorithm using vector differences for perturbing the vector population with self adaptation is introduced. Through the combination of mutation strategies and self adaptation of crossover and differentiation constants the proposed MO algorithm performs better than the one with the simple DE scheme in terms of computation speed and quality of the generated multi-objective non-dominated solutions.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116346247","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 : 2010-05-05DOI: 10.1109/INES.2010.5483844
P. Karch, I. Zolotová
This paper presents the possibility of deformation of the object contours using Graph cut method. The user interactively defines the contour of the object based on own requirements for segmentation. The procedure proposed in this article seeks global optimal solution Graph cut segmentation for local parts of the input image versus finding a global optimal solution for the whole input image in classical Graph cut segmentation. On the basis of local segmentation the contour of the object was deformed, which was defined by the user. The advantage of local processing in this process is rapid implementation of Graph cut segmentation even if the input resolution of the image is high. Higher speed is achieved by the local segmentation determined only on the vicinity of the route initialization contour and the segmentation is not performed on the entire input image. The size of the vicinity of the initialization contour which is taken into account by the processing of the image is determined interactively by the user. Terminals of the object and background in this procedure are determined automatically from initialization contours specified by the user. The paper presents the experimental results and comparison with the classical procedure using Graph cut segmentation.
{"title":"Interactive contour deformation of an object using Graph cut","authors":"P. Karch, I. Zolotová","doi":"10.1109/INES.2010.5483844","DOIUrl":"https://doi.org/10.1109/INES.2010.5483844","url":null,"abstract":"This paper presents the possibility of deformation of the object contours using Graph cut method. The user interactively defines the contour of the object based on own requirements for segmentation. The procedure proposed in this article seeks global optimal solution Graph cut segmentation for local parts of the input image versus finding a global optimal solution for the whole input image in classical Graph cut segmentation. On the basis of local segmentation the contour of the object was deformed, which was defined by the user. The advantage of local processing in this process is rapid implementation of Graph cut segmentation even if the input resolution of the image is high. Higher speed is achieved by the local segmentation determined only on the vicinity of the route initialization contour and the segmentation is not performed on the entire input image. The size of the vicinity of the initialization contour which is taken into account by the processing of the image is determined interactively by the user. Terminals of the object and background in this procedure are determined automatically from initialization contours specified by the user. The paper presents the experimental results and comparison with the classical procedure using Graph cut segmentation.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127373227","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 : 2010-05-05DOI: 10.1109/INES.2010.5483837
A. Kelemen, N. Kutasi, M. Imecs, I. Incze
The paper presents an online approach to the model-predictive control of the boost type PWM rectifier. The optimization is made on a horizon of one switching period for a cost function based on the instantaneous real and imaginary power errors. The control vectors are synthesized by space-vector modulation and are confined to the hexagonal area defined by the possible switching states of the three-phase bridge. The optimal control algorithm is developed in presence of the grid current limitation, introduced as a practical constraint.
{"title":"Constrained optimal direct power control of voltage-source PWM rectifiers","authors":"A. Kelemen, N. Kutasi, M. Imecs, I. Incze","doi":"10.1109/INES.2010.5483837","DOIUrl":"https://doi.org/10.1109/INES.2010.5483837","url":null,"abstract":"The paper presents an online approach to the model-predictive control of the boost type PWM rectifier. The optimization is made on a horizon of one switching period for a cost function based on the instantaneous real and imaginary power errors. The control vectors are synthesized by space-vector modulation and are confined to the hexagonal area defined by the possible switching states of the three-phase bridge. The optimal control algorithm is developed in presence of the grid current limitation, introduced as a practical constraint.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129985773","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 : 2010-05-05DOI: 10.1109/INES.2010.5483851
Florica Naghiu, D. Pescaru, Victor Gavrila, I. Jian, D. Curiac
Location estimation is an important part of a traffic surveillance system. Markov chain Monte Carlo methods based on particle filters have proved to be an effective solution in sensing error correction. We investigate in this paper the influence of particle filter parameters variation on sensing errors correction accuracy. Considered traffic surveillance system is based on a wireless sensor network. Several forms of probability density matrix and various methods for particle weight computation where considered, allowing us to find the dependencies between parameters. Finally, we use simulation to find optimal solutions in different traffic conditions.
{"title":"Influence of particle filter parameters on error correction accuracy in traffic surveillance using sensor networks","authors":"Florica Naghiu, D. Pescaru, Victor Gavrila, I. Jian, D. Curiac","doi":"10.1109/INES.2010.5483851","DOIUrl":"https://doi.org/10.1109/INES.2010.5483851","url":null,"abstract":"Location estimation is an important part of a traffic surveillance system. Markov chain Monte Carlo methods based on particle filters have proved to be an effective solution in sensing error correction. We investigate in this paper the influence of particle filter parameters variation on sensing errors correction accuracy. Considered traffic surveillance system is based on a wireless sensor network. Several forms of probability density matrix and various methods for particle weight computation where considered, allowing us to find the dependencies between parameters. Finally, we use simulation to find optimal solutions in different traffic conditions.","PeriodicalId":118326,"journal":{"name":"2010 IEEE 14th International Conference on Intelligent Engineering Systems","volume":"726 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122999600","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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