@article { author = {Ahmed, Hatem and B. El-Sisi, A. and A. Mostafa, K. and I. Mahmoud, Imbaby}, title = {Implementation of a Real-Time Simulator for Dynamic Systems}, journal = {IJCI. International Journal of Computers and Information}, volume = {1}, number = {1}, pages = {2-10}, year = {2007}, publisher = {Minufiya University; Faculty of Computers and Information}, issn = {1687-7853}, eissn = {2735-3257}, doi = {10.21608/ijci.2007.33725}, abstract = {Real-time systems refer to systems that have real-time requirements for interacting with a human operator or otheragents with similar timescales. An efficient simulation of real-time systems requires a model that is accurate enough toaccomplish the simulation objective and is computationally efficient. In this paper a real time modeling system for dynamic systems will be studied. Normally, Real time modeling can be classified into hardware and software systems, but this work focuses on the software techniques and systems. Finally a demonstration example for real time simulator has been simulated for complex dynamic system, namely a small nuclear fusion device (Egyptor Tokamak). The obtained results agree well with published work. Such simulator can be considered an imperative requirement for predicative control tasks.}, keywords = {}, url = {https://ijci.journals.ekb.eg/article_33725.html}, eprint = {https://ijci.journals.ekb.eg/article_33725_cd2f411130069c44e5c6005ec642de37.pdf} } @article { author = {El-Sherbiny, Mahmoud}, title = {A Combined Particle Swarm Optimization Algorithm Based on the Previous Global Best and the Global Best Positions}, journal = {IJCI. International Journal of Computers and Information}, volume = {1}, number = {1}, pages = {11-22}, year = {2007}, publisher = {Minufiya University; Faculty of Computers and Information}, issn = {1687-7853}, eissn = {2735-3257}, doi = {10.21608/ijci.2007.33929}, abstract = {This paper introduces a combined algorithm to particle swarm based optimization and discusses the results of experimentally comparing the performances of its three versions with the performance of the particle swarm optimizer. In the combined algorithm, each particle flies and is attracted toward a new position according to its previous best position and the point resulted from the combination of the previous global best position and the global best position. The variants of the combined algorithm and the particle swarm optimizer are tested using a set of multimodal functions commonly used as benchmark optimization problems in evolutionary computation. Results indicate that the algorithm is highly competitive and can be considered as a viable alternative to solve the optimization problems.}, keywords = {Particle Swarm Optimization,Convergence,Evolutionary computation}, url = {https://ijci.journals.ekb.eg/article_33929.html}, eprint = {https://ijci.journals.ekb.eg/article_33929_b26dcd8fe157921b83b37e4f2108b5b0.pdf} } @article { author = {Torkey, F. and Ahmed, Hatem and Ismail, Nabil and Elkholy, Warda}, title = {Modeling of Updating Moving Object Database Using Timed Petri net Model}, journal = {IJCI. International Journal of Computers and Information}, volume = {1}, number = {1}, pages = {23-34}, year = {2007}, publisher = {Minufiya University; Faculty of Computers and Information}, issn = {1687-7853}, eissn = {2735-3257}, doi = {10.21608/ijci.2007.33930}, abstract = {Tracking moving objects is one of the most common requirements for many location-based applications. The location of amoving object changes continuously but the database location of the moving object cannot update continuously. Modelingof such moving object database should be considered to facilitate study of the performance and design parameters. Suchstudy is essential for selecting the optimal solution in order to minimize the implementation of the overhead cost. Locationupdating strategy for such type of database is the most important criteria. This paper proposed a timed Petri net modelbased on one of the most common updating strategies, namely the distance updating strategy. In addition, a method forestimating the time needed to update Moving Object Database (MOD) using the concept of the minimum cycle time in timed Petri nets is presented. This time is the main criterion, which can be used to study the overhead communication cost for MOD. A typical numerical example is given to demonstrate the advantages of proposed modeling technique.}, keywords = {Updating moving object database,Deterministic timed Petri net,Deviation update policy and tracking moving object database}, url = {https://ijci.journals.ekb.eg/article_33930.html}, eprint = {https://ijci.journals.ekb.eg/article_33930_eed3a0919018433a53d462122cd8dd80.pdf} } @article { author = {Zaher, Hegazy and Abd El- Wahed, W. and El-Sherbiny, Mahmoud and Matloub, Haidy}, title = {An Intelligent Decision Support System for Faculty Evaluation}, journal = {IJCI. International Journal of Computers and Information}, volume = {1}, number = {1}, pages = {35-49}, year = {2007}, publisher = {Minufiya University; Faculty of Computers and Information}, issn = {1687-7853}, eissn = {2735-3257}, doi = {10.21608/ijci.2007.33931}, abstract = {This paper presents an intelligent decision support system (IDSSFPE) for faculty performance evaluation. The requirements of the faculty decision makers are identified through the analysis and the design of the IDSSFPE. Three models based of the IDSSFPE are illustrated. Such models are: i) The performance measurement model based on data envelopment analysis (DEA), ii) Number of applicants estimation model, and iii) Applicants classification model based on artificial neural network (ANN).}, keywords = {Faculty performance,Intelligence decision support system,artificial neural network}, url = {https://ijci.journals.ekb.eg/article_33931.html}, eprint = {https://ijci.journals.ekb.eg/article_33931_6c9a64d2967924202ec6612c208a9905.pdf} } @article { author = {Hussain, Reda and Abd El-wahed, W. and Torkey, F.}, title = {A Hybrid Intelligent System for Arabic Handwritten Number Recognition}, journal = {IJCI. International Journal of Computers and Information}, volume = {1}, number = {1}, pages = {50-60}, year = {2007}, publisher = {Minufiya University; Faculty of Computers and Information}, issn = {1687-7853}, eissn = {2735-3257}, doi = {10.21608/ijci.2007.33932}, abstract = {This paper shows how developments in the area of neural network combined with genetic algorithms can be used in thehandwritten digit recognition. In this work, two approaches to the design of a feed-forward neural network that model thehandwritten recognition system are discussed. The first approach focuses on constructing the network by using a trail-and error method the second approach is responsible for determining the appreciate parameters of the neural network and itslearning algorithm by the mean of genetic algorithms. Results show that using genetic algorithm for selecting the nearoptimal parameters of the neural network, is improving classification performance on handwritten digits.}, keywords = {Neural Networks,Genetic Algorithms,Handwritten numeral recognition}, url = {https://ijci.journals.ekb.eg/article_33932.html}, eprint = {https://ijci.journals.ekb.eg/article_33932_838f494cd6328bc0cf5459b784e8daa3.pdf} }