{"title":"Training Feed-Forward Neural Networks Using a Parallel Genetic Algorithm with the Best Must Survive Strategy","authors":"Ali Kattan, R. Abdullah, R. A. Salam","doi":"10.1109/ISMS.2010.29","DOIUrl":"https://doi.org/10.1109/ISMS.2010.29","url":null,"abstract":"Feed-Forward Artificial Neural Networks (FFANN) can be trained using Genetic Algorithm (GA). GA offers a stochastic global optimization technique that might suffer from two major shortcomings: slow convergence time and impractical data representation. The effect of these shortcomings is more considerable in case of larger FFANN with larger dataset. Using a non-binary real-coded data representation we offer an enhancement to the generational GA used for the training of FFANN. Such enhancement would come in two fold: The first being a new strategy to process the strings of the population by allowing the fittest string to survive unchanged to the next population depending on its age. The second is to speed up fitness computation time through the utilization of known parallel processing techniques used for matrix multiplication. The implementation was carried on master-slaves architecture of commodity computers connected via Ethernet. Using a well-known benchmarking dataset, results show that our proposed technique is superior to the standard in terms of both the overall convergence time and processing time.","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133948630","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}
{"title":"A Time-Varying System Control Using Implicit Flatness: Case of an Inverted Pendulum","authors":"Chafik Maghzaoui, A. Mansour, H. Jerbi","doi":"10.1109/ISMS.2010.58","DOIUrl":"https://doi.org/10.1109/ISMS.2010.58","url":null,"abstract":"This paper focuses on a fundamental problem related to a characterization of differentially flat nonlinear system in implicit representation. The implicit differential flatness control is a central property for flat nonlinear systems, when the differential equations structure is complex. In this case the state variables and the input control cannot be explicitly expressed as functions of the components of the flat output and a finite number of their derivative. The purpose of this paper is investigated by the study of a tracking problem for a time-varying system which is obtained via the linearization of a nonlinear model around the desired trajectory. The performance study of the developed method is discussed on a non minimum phase model of an inverted pendulum.","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130001499","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}
{"title":"A Fast Affine Projection Algorithm Based on Matching Pursuit in Adaptive Noise Cancellation for Speech Enhancement","authors":"Sayed A. Hadei, N. Sonbolestan","doi":"10.1109/ISMS.2010.45","DOIUrl":"https://doi.org/10.1109/ISMS.2010.45","url":null,"abstract":"In many application of noise cancellation, the changes in signal characteristics could be quite fast. This requires the utilization of adaptive algorithms, which converge rapidly. Least Mean Squares (LMS) adaptive filters have been used in a wide range of signal processing application. The Recursive Least Squares (RLS) algorithm has established itself as the \"ultimate\" adaptive filtering algorithm in the sense that it is the adaptive filter exhibiting the best convergence behavior. Unfortunately, practical implementations of the algorithm are often associated with high computational complexity and/or poor numerical properties. Recently adaptive filtering was presented that was based on Matching Pursuits, have a nice tradeoff between complexity and the convergence speed. This paper describes a new approach for noise cancellation in speech enhancement using the new adaptive filtering algorithm named fast affine projection algorithm (FAPA). The simulation results demonstrate the good performance of the FAPA in attenuating the noise.","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117278711","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}
{"title":"Sequential Modeling of D_st Dynamics with SEEk Trained Recurrent Neural Networks","authors":"Lahcen Ouarbya, D. Mirikitani","doi":"10.1109/ISMS.2010.17","DOIUrl":"https://doi.org/10.1109/ISMS.2010.17","url":null,"abstract":"A sequential framework for modeling magnetospheric plasma interactions with a SEEK trained recurrent neural network is proposed. An overview of the state-space modeling framework is provided, along with a review of previous Kalman trained neural models. The proposed algorithm is described and is evaluated against an EKF trained RNN and a gradient based model. The exogenous inputs to the RNNs consist of three parameters, Bz, B^2, and (By)^2, where B, Bz, and By represent the magnitude, the southward and azimuthal components of the interplanetary magnetic field (IMF) respectively. It was found that the SEEK trained recurrent neural network outperforms other neural time series models trained with the Extended Kalman Filter, and gradient descent learning. The numerical simulations suggest that the SEEK filter provides superior tracking capabilities than the EKF, resulting in accurate forecast of the Dst index.","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117283769","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}
P. Lecca, Alida Palmisano, Adaoha Elizabeth Ihekwaba
{"title":"Correlation-Based Network Inference and Modelling in Systems Biology: The NF-kappa B Signalling Network Case Study","authors":"P. Lecca, Alida Palmisano, Adaoha Elizabeth Ihekwaba","doi":"10.1109/ISMS.2010.41","DOIUrl":"https://doi.org/10.1109/ISMS.2010.41","url":null,"abstract":"It is currently attracting the interest of theoretical biologists, biochemicists and experimentalists to attempt to deduce the structure of biochemical networks \"ab initio\" from routinely available experimental data. The recent advances in systems biology have been driven by the methods that generate in vivo time-course data characterizing biochemical network interactions. Such data can be used for inferring a model structure and its parameters in order to examine the dynamic behavior of biological processes on a systemic level. We present here a new correlation-based approach to network inference, whose most attractive feature is that information can be extracted from the observed data with little a priori knowledge of the underlying mechanisms. Our method introduces a new correlation metric based on a Voronoi tessellation of the variable space and infers correlations among stationary time series data of reactant concentrations. These correlations can be used to reveal dependencies between variables, as well as connectivity between species. The method has been applied to a real case study: the binding kinetics of the enzyme inhibitor kappa B kinase to its substrate inhibitor kappa B alpha, whose interaction is an integral part of the transduction of signals in the NF-kappa B signalling pathway.","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132667725","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}
Saleh M. Altowaijri, Rashid Mehmood, John G. Williams
{"title":"A Quantitative Model of Grid Systems Performance in Healthcare Organisations","authors":"Saleh M. Altowaijri, Rashid Mehmood, John G. Williams","doi":"10.1109/ISMS.2010.84","DOIUrl":"https://doi.org/10.1109/ISMS.2010.84","url":null,"abstract":"Future healthcare systems and organisations demand huge computational resources, and the ability for the applications to interact and communicate with each other within and across organisational boundaries. Examples of healthcare applications include medical imaging and processing, electronic health records, epidemiology and other higher-level analysis of healthcare data. Grid Computing has the potential to provide solutions to many of the challenges in healthcare systems, including the deployment path and business models. This paper presents a quantitative, Markovian, performance model to evaluate the suitability of computational Grids for pervasive deployment of medical applications in healthcare organisations. For a range and mix of medical applications, we compute steady state probability distributions of the respective Markov models and analyse the system performance using the results. This study is a step forward to quantitatively demonstrate the potential of computational Grids for their use in healthcare organisations.","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"301 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116328921","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}
{"title":"Randomness Modeling in Supply Chain Simulation","authors":"Galina Merkuryeva, O. Vecherinska","doi":"10.1109/ISMS.2010.34","DOIUrl":"https://doi.org/10.1109/ISMS.2010.34","url":null,"abstract":"Stochastic simulation models utilize probability distributions to represent a multitude of randomly occurring events. Theoretical distributions are commonly used to model the randomness of a real process because they help to smooth data irregularities that may exist due to the values missed during the data collection phase. These distributions can be selected either by fitting a distribution to the data collected, or based on the known properties of the process being modelled. The incompatibility between specific characteristics of the theoretical distribution and assumptions of simulation and mathematical calculus present an actual problem in supply chains. The paper is based on the analysis of mentioned contradictions. Different approaches to deal with theoretical probability distributions in supply chains are described in the paper.","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128495782","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}
{"title":"Nonparametric Driveline Identification and Control","authors":"A. Abass, S. Zhao, A. Shenton","doi":"10.1109/ISMS.2010.52","DOIUrl":"https://doi.org/10.1109/ISMS.2010.52","url":null,"abstract":"A nonparametric identification and control approach to active driveline control is investigated. A nonlinear model incorporating nonlinear clutch characteristics and driveline backlash is developed. An approach using short time Fourier transforms for nonparametric frequency response identification and smoothing is presented. The identification method is used to identify a driveline model both with and without backlash present. Two nonparametric controller design techniques are employed. A parameter space method is used to design a PI controller and an analytic-optimisation mixed sensitivity H∞ method to design a high order controller for the cases with and without backlash. The controllers designed for the system without backlash proved unstable when applied to the system with it present. In contrast, both the PI controller and the higher order controller from the new technique give good control of the fully nonlinear driveline. The new approach should be directly applicable to experimentally produced time series data, which potentially allows a systematic controller calibration without the need for extensive in-vehicle tuning.","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129364401","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}
{"title":"Invited Paper: Profiling Intelligent Systems Applications in Fraud Detection and Prevention: Survey of Research Articles","authors":"Mirjana Pejić-Bach","doi":"10.1109/ISMS.2010.26","DOIUrl":"https://doi.org/10.1109/ISMS.2010.26","url":null,"abstract":"This paper surveys intelligent systems (IS) applications using a literature review and classification of articles from 1956 to 2009 with a keyword index and article abstract in order to explore how IS applications in the field of fraud detection and prevention have developed during this period. Based on the scope of 36 articles found from Web of science (SSCI, SCI and A&HCI) database, this paper surveys and classifies IS applications in the fraud detection and prevention using the following three categories of intelligent systems: neural networks, fuzzy ISs, and computational intelligence. Following applications areas were detected and described: telecommunications, insurance, auditing, medical care, credit card transactions, e-business, bid pricing and identity verification.","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"309 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116760206","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}
{"title":"Usability Evaluation of Web Office Applications in Collaborative Writing","authors":"M. A. Khan, N. Israr, Sher Hassan","doi":"10.1109/isms.2010.37","DOIUrl":"https://doi.org/10.1109/isms.2010.37","url":null,"abstract":"Usability evaluation of collaborative writing system for education usage is essential to improve its functionality. In this paper, the usability of web office (ThinkFree doc) is tested using mix research approach. Usability evaluation is performed via the think aloud protocol. A questionnaire was designed for quantitative survey. The questionnaire was completed by users who have been using Thinkfree doc for educational collaborative work. Interviews were conducted with the selected participants for results validation. During usability evaluation process, positive and negative effects regarding software’s usage were recorded. The results revealed that the overall systems response is very slow. The software needs to improve its processing speed in order to make it more efficient for future use. The system also needs to improve overall functionality (for example collaborative work, synchronization, uploading and track changes) to provide accurate and complete results","PeriodicalId":434315,"journal":{"name":"2010 International Conference on Intelligent Systems, Modelling and Simulation","volume":"2007 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130630452","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}