The pricing and hedging of complex derivative securities via Monte Carlo simulations of stochastic differential equations constitutes an intensive computational task. To achieve "real time" execution, as often required by financial institutions, one needs highly efficient implementations of the multi-point distributed random variables underlying the simulations. In this paper a fast and flexible dedicated hardware solution is proposed. A comparative performance analysis demonstrates that the hardware solution is bottleneck-free and flexible, and significantly increases the computational efficiency of the software solution.
{"title":"A multi-point distributed random variable accelerator for Monte Carlo simulation in finance","authors":"N. Liberati, F. Martini","doi":"10.1109/ISDA.2005.11","DOIUrl":"https://doi.org/10.1109/ISDA.2005.11","url":null,"abstract":"The pricing and hedging of complex derivative securities via Monte Carlo simulations of stochastic differential equations constitutes an intensive computational task. To achieve \"real time\" execution, as often required by financial institutions, one needs highly efficient implementations of the multi-point distributed random variables underlying the simulations. In this paper a fast and flexible dedicated hardware solution is proposed. A comparative performance analysis demonstrates that the hardware solution is bottleneck-free and flexible, and significantly increases the computational efficiency of the software solution.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122518202","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}
In this paper, a new functionality of early warning for an online stock trading system is presented. The warning functionality helps to focus traders' attention on specific situations on the stock market. The specific situations relate to the rare circumstances where a trader should be alerted by exceptional raises or drops of share prices, volatilities and market index changes. Usually, these alerts force a trader to make a decision either to buy or sell a share. To discover the warning rules and events, an evolution-based model is proposed. This model also introduces a new function that stores the experimental knowledge by keeping track of all historical alert events-solutions and actions taken by a trader. This model is composed of the three following components, which are integrated with each other: alert rules, pattern clustering and genetic engine. This approach has been tested on real data extracted from the Internet Bourse Expert System and Paris Stock Exchange.
{"title":"Early warning in online stock trading systems","authors":"Piotr Lipiński, J. Korczak","doi":"10.1109/ISDA.2005.42","DOIUrl":"https://doi.org/10.1109/ISDA.2005.42","url":null,"abstract":"In this paper, a new functionality of early warning for an online stock trading system is presented. The warning functionality helps to focus traders' attention on specific situations on the stock market. The specific situations relate to the rare circumstances where a trader should be alerted by exceptional raises or drops of share prices, volatilities and market index changes. Usually, these alerts force a trader to make a decision either to buy or sell a share. To discover the warning rules and events, an evolution-based model is proposed. This model also introduces a new function that stores the experimental knowledge by keeping track of all historical alert events-solutions and actions taken by a trader. This model is composed of the three following components, which are integrated with each other: alert rules, pattern clustering and genetic engine. This approach has been tested on real data extracted from the Internet Bourse Expert System and Paris Stock Exchange.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134253372","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}
As processors that are used in embedded systems become increasingly more powerful, a variety of functions, including multimedia, games and the proper system-operating function, are added to the systems. Despite the fact that embedded systems are becoming increasingly more powerful, system resources remain limited, and system functionalities are being developed in the form of applications running on the middleware such as virtual machines, or in the form of embedded systems' applications. An example of this is virtual machines (VM's) that are in the form of applications in embedded systems. This paper aims to design and implement a structured platform for MVM's (multi-VM's) that enables the middleware and system applications, such as the VM's to manage the system resources and easily share the common functions amongst them.
{"title":"Structured platform for multiple virtual machines","authors":"ChanSung Jung, Seman Oh","doi":"10.1109/ISDA.2005.86","DOIUrl":"https://doi.org/10.1109/ISDA.2005.86","url":null,"abstract":"As processors that are used in embedded systems become increasingly more powerful, a variety of functions, including multimedia, games and the proper system-operating function, are added to the systems. Despite the fact that embedded systems are becoming increasingly more powerful, system resources remain limited, and system functionalities are being developed in the form of applications running on the middleware such as virtual machines, or in the form of embedded systems' applications. An example of this is virtual machines (VM's) that are in the form of applications in embedded systems. This paper aims to design and implement a structured platform for MVM's (multi-VM's) that enables the middleware and system applications, such as the VM's to manage the system resources and easily share the common functions amongst them.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130368675","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}
Formal concept analysis (FCA) is a method for deriving conceptual structures out of data that are represented as objects with features. FCA discovers dependencies within the data based on the relation among objects and features. However, not every pair of objects and features defines a concept. Concept approximation is to find the best or closest concept(s) to approximate a pair of objects and features. Concept approximation is significant in that under the circumstances that we can not find a concept, using concept approximation will give the best or most possible solution. In this paper, we evaluate three approaches through experiments in the application of document retrieval. We provide analysis of these approaches and give our concluding remarks.
{"title":"Comparative evaluation on concept approximation approaches","authors":"J. Deogun, Liying Jiang","doi":"10.1109/ISDA.2005.35","DOIUrl":"https://doi.org/10.1109/ISDA.2005.35","url":null,"abstract":"Formal concept analysis (FCA) is a method for deriving conceptual structures out of data that are represented as objects with features. FCA discovers dependencies within the data based on the relation among objects and features. However, not every pair of objects and features defines a concept. Concept approximation is to find the best or closest concept(s) to approximate a pair of objects and features. Concept approximation is significant in that under the circumstances that we can not find a concept, using concept approximation will give the best or most possible solution. In this paper, we evaluate three approaches through experiments in the application of document retrieval. We provide analysis of these approaches and give our concluding remarks.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115510677","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}
Genetic algorithms (GAs) are very popular optimization tool, although efficient applications of GAs requires users have problem with setting their parameters and used genetic operators to obtain satisfactory solution in acceptable time. We propose an intelligent agent as a control mechanism for a group of cooperating genetic algorithms. A core of the system is a family of cooperating genetic algorithms. Manager, a kind of fuzzy expert system, is responsible for control of GAs to assure effectiveness of the search process. It requires providing knowledge concerning influence of some parameters of GAs on tempo and mode of evolution. Such knowledge in the form of fuzzy inference rules should be included into Manager. Analyser - the third part of the system, will gather knowledge concerning progress and actual state of a working system. This knowledge will be used in the form of facts to fire suitable rules. The simulation study of efficiency of developed system is presented and discussed.
{"title":"Managing of cooperative genetic algorithms by intelligent agent","authors":"H. Kwasnicka, Magdalena Gierusz","doi":"10.1109/ISDA.2005.61","DOIUrl":"https://doi.org/10.1109/ISDA.2005.61","url":null,"abstract":"Genetic algorithms (GAs) are very popular optimization tool, although efficient applications of GAs requires users have problem with setting their parameters and used genetic operators to obtain satisfactory solution in acceptable time. We propose an intelligent agent as a control mechanism for a group of cooperating genetic algorithms. A core of the system is a family of cooperating genetic algorithms. Manager, a kind of fuzzy expert system, is responsible for control of GAs to assure effectiveness of the search process. It requires providing knowledge concerning influence of some parameters of GAs on tempo and mode of evolution. Such knowledge in the form of fuzzy inference rules should be included into Manager. Analyser - the third part of the system, will gather knowledge concerning progress and actual state of a working system. This knowledge will be used in the form of facts to fire suitable rules. The simulation study of efficiency of developed system is presented and discussed.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"271 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122076650","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}
B. Berg, C. Tattersall, J. Janssen, F. Brouns, Hub Kurvers, R. Koper
Open and distance learning (ODL) gives learners freedom of time, place and pace of study, putting learner self-direction centre-stage. However, increased responsibility should not come at the price of over-burdening or abandonment of learners as they progress along their learning journey. This paper introduces an approach to recommending the sequencing of e-learning modules for distance learners based on self-organization theory. It describes an architecture which supports the recording, processing and presentation of collective learner behavior designed to create a feedback loop informing learners of successful paths towards the attainment of learning goals. The article includes initial results from a large-scale experiment designed to validate the approach.
{"title":"Swarm-based sequencing recommendations in e-learning","authors":"B. Berg, C. Tattersall, J. Janssen, F. Brouns, Hub Kurvers, R. Koper","doi":"10.1109/ISDA.2005.88","DOIUrl":"https://doi.org/10.1109/ISDA.2005.88","url":null,"abstract":"Open and distance learning (ODL) gives learners freedom of time, place and pace of study, putting learner self-direction centre-stage. However, increased responsibility should not come at the price of over-burdening or abandonment of learners as they progress along their learning journey. This paper introduces an approach to recommending the sequencing of e-learning modules for distance learners based on self-organization theory. It describes an architecture which supports the recording, processing and presentation of collective learner behavior designed to create a feedback loop informing learners of successful paths towards the attainment of learning goals. The article includes initial results from a large-scale experiment designed to validate the approach.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124248293","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}
Due to the wide deployment of sensor networks recently security in sensor networks has become a hot research topic. Popular ways to secure a sensor network are by including cryptographic techniques or by safeguarding sensitive information from unauthorized access/manipulation and by implementing efficient intrusion detection mechanisms. This paper proposes a novel ant colony based intrusion detection mechanism which could also keep track of the intruder trials. The IDEAS technique could work in conjunction with the conventional machine learning based intrusion detection techniques to secure the sensor networks. The algorithm is presented and illustrated by simulating a sensor network.
{"title":"IDEAS: intrusion detection based on emotional ants for sensors","authors":"S. Banerjee, C. Grosan, A. Abraham","doi":"10.1109/ISDA.2005.53","DOIUrl":"https://doi.org/10.1109/ISDA.2005.53","url":null,"abstract":"Due to the wide deployment of sensor networks recently security in sensor networks has become a hot research topic. Popular ways to secure a sensor network are by including cryptographic techniques or by safeguarding sensitive information from unauthorized access/manipulation and by implementing efficient intrusion detection mechanisms. This paper proposes a novel ant colony based intrusion detection mechanism which could also keep track of the intruder trials. The IDEAS technique could work in conjunction with the conventional machine learning based intrusion detection techniques to secure the sensor networks. The algorithm is presented and illustrated by simulating a sensor network.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126507299","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}
Crew grouping is an important problem and formulating a good solution always involves many challenges. For example, grouping soldiers intelligently to tank combat units, we should take into consideration the combined technical proficiency of the soldiers, the amount of military training, the units from which the soldiers come, their service age, personal background, etc. In this paper, we propose a hybrid fuzzy-genetic algorithm (FGA) approach to solve the crew grouping problem. Fuzzy logic based controllers are applied to fine-tune dynamically the crossover and mutation probability in the genetic algorithms, in an attempt to improve the algorithm performance. The FGA approach is compared with the standard genetic algorithm (SGA). Empirical results clearly demonstrates that while the SGA approach gives satisfactory solutions for the problem, the FGA method usually performs significantly better.
{"title":"Hybrid fuzzy-genetic algorithm approach for crew grouping","authors":"Hongbo Liu, Zhang Xu, A. Abraham","doi":"10.1109/ISDA.2005.51","DOIUrl":"https://doi.org/10.1109/ISDA.2005.51","url":null,"abstract":"Crew grouping is an important problem and formulating a good solution always involves many challenges. For example, grouping soldiers intelligently to tank combat units, we should take into consideration the combined technical proficiency of the soldiers, the amount of military training, the units from which the soldiers come, their service age, personal background, etc. In this paper, we propose a hybrid fuzzy-genetic algorithm (FGA) approach to solve the crew grouping problem. Fuzzy logic based controllers are applied to fine-tune dynamically the crossover and mutation probability in the genetic algorithms, in an attempt to improve the algorithm performance. The FGA approach is compared with the standard genetic algorithm (SGA). Empirical results clearly demonstrates that while the SGA approach gives satisfactory solutions for the problem, the FGA method usually performs significantly better.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130026461","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}
I. L. Ruiz, G. C. García, Manuel Urbano-Cuadrado, M. Gómez-Nieto
The recovery of information from large databases based on similarity approach supposes a high computational cost -when the process is carried out comparing each one of the records with the search pattern. If the database records store some data structure representing the information of the problem domain by means of a graph it is possible to classify these records using a hierarchical model which considers the structural basic elements of the graphs and diminishes the computational cost of the recovery process considerably. In this paper we propose a classification model based on structural elements (cycles and chains) for large and medium databases.
{"title":"New models for the clustering of large databases through a hierarchical paradigm","authors":"I. L. Ruiz, G. C. García, Manuel Urbano-Cuadrado, M. Gómez-Nieto","doi":"10.1109/ISDA.2005.72","DOIUrl":"https://doi.org/10.1109/ISDA.2005.72","url":null,"abstract":"The recovery of information from large databases based on similarity approach supposes a high computational cost -when the process is carried out comparing each one of the records with the search pattern. If the database records store some data structure representing the information of the problem domain by means of a graph it is possible to classify these records using a hierarchical model which considers the structural basic elements of the graphs and diminishes the computational cost of the recovery process considerably. In this paper we propose a classification model based on structural elements (cycles and chains) for large and medium databases.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129211069","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}
This paper extends the analysis of a statistical methodology for source detection and localization (SDL) in a network of randomly distributed wireless nodes equipped with homogeneous and omni-directional sensors. The investigations are focused on SDL with respect to the nearest sensor node and are based on the observed source (phenomenon) energy. In this framework, the SDL algorithms are viewed as classification problems which are solved using pattern recognition techniques. In the presented approach: (i) sensors are randomly distributed and little is known about their exact locations; and (ii) a self-calibrating mechanism is proposed for creating the dataset whose feature vectors constitute the reference points for sensor locations in the space of sensor readings. The performance of the proposed algorithms is evaluated through Monte Carlo simulations and is demonstrated to be robust in the presence of noise and changes in the propagation environments.
{"title":"Pattern recognition based detection and localization in a network of randomly distributed sensor nodes","authors":"H. Al-Hertani, J. Ilow","doi":"10.1109/ISDA.2005.77","DOIUrl":"https://doi.org/10.1109/ISDA.2005.77","url":null,"abstract":"This paper extends the analysis of a statistical methodology for source detection and localization (SDL) in a network of randomly distributed wireless nodes equipped with homogeneous and omni-directional sensors. The investigations are focused on SDL with respect to the nearest sensor node and are based on the observed source (phenomenon) energy. In this framework, the SDL algorithms are viewed as classification problems which are solved using pattern recognition techniques. In the presented approach: (i) sensors are randomly distributed and little is known about their exact locations; and (ii) a self-calibrating mechanism is proposed for creating the dataset whose feature vectors constitute the reference points for sensor locations in the space of sensor readings. The performance of the proposed algorithms is evaluated through Monte Carlo simulations and is demonstrated to be robust in the presence of noise and changes in the propagation environments.","PeriodicalId":345842,"journal":{"name":"5th International Conference on Intelligent Systems Design and Applications (ISDA'05)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128572227","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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