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Article
Development a 3-D Mathematical Model for Network Topology Based on Graph Theory*

Author: Dr. Laith Jasim Saud**
Journal: IRAQI JOURNAL OF COMPUTERS,COMMUNICATION AND CONTROL & SYSTEMS ENGINEERING المجلة العراقية لهندسة الحاسبات والاتصالات والسيطرة والنظم ISSN: 18119212 Year: 2012 Volume: 12 Issue: 2 Pages: 28-34
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

Abstract:Communication network efficiency depends upon many factors among which is the “Topology” which makes topology optimization an important issue to care for. One important thing in optimization problems is the formulation of objective functions. For the case of topology design it is not a straightforward matter to develop an efficient topology model as well as objective functions to be used in the optimization process. An effective unconventional approach is needed. This paper is concerned with enhancing the already existing set of formulas, relating topology and topology properties modeling and topology design objectives, by proposing a 3-dimension way of modeling that can serve network analysis, design, and optimization. The approach is based on graph theory. The proposed model and formulas can be easily programmed.


Article
COMPUTING NODES AND LINKS APPEARANCES ON GEODESICS IN NETWORKS TOPOLOGIES USING GRAPH THEORY
حساب عدد مرات ظھور العقد و الوصلات في المسارات الاقصر ضمن طوبولوجیات الشبكات باعتماد نظریة حالة الاشكال

Authors: Dr. Siddeeq Ameen Yousif * --- Dr. Laith Jasim Saud**
Journal: IRAQI JOURNAL OF COMPUTERS,COMMUNICATION AND CONTROL & SYSTEMS ENGINEERING المجلة العراقية لهندسة الحاسبات والاتصالات والسيطرة والنظم ISSN: 18119212 Year: 2012 Volume: 12 Issue: 1 Pages: 96-103
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

This paper proposes two important mathematical models related to network topologywhich helps in computing some of the efficiency or reliability factors of communicationnetwork as well as design purposes. Each of these models represents a topologyproperty. The first (second) of these models is used to compute the number ofappearances of any link (node) in the geodesics between nodes in a given networktopology, and so can be used to help in uniformly distributing the data flow throughlinks (nodes), as well as helping in measuring the degree of survivability of the networkin case of failure of some of its links (nodes). The two models have been developedusing “Graph Theory”, and so, giving the advantage of using the very wide range ofideas, tools, and theorems of this field in case of developing other network topologyformulas based on the two models proposed in this paper.

یقترح ھذا البحث نموذجین ریاضیین مھمین یخصان طوبولوجیة الشبكة. یساعد ھذین النموذجین في حساببعض عوامل الكفاءة و الاعتمادیة لشبكات الاتصال، كما یخدمان بعض اھداف التصمیم في الشبكات. ان كل منھذین النموذجین یمثل خاصیة من خصائص الطوبولوجیة. النموذج الاول (الثاني) من ھذین النموذجین یستخدملحساب عدد مرات ظھور أي و صَلة (عقدة) في المسارات الاقصر بین العقد ضمن طوبولوجیة شبكة ما، و بالتاليیمكن ان یستخدم في المساعدة في التوزیع المنتظم لانسیاب البیانات عبر الو صَلات ( العقد) و كذلك المساعدة فيقیاس درجة قدرة الشبكة على البقاء في حالة فشل بعض و صَلَاتھا (عقدھا) . لقد تم تطویر النموذجین باعتمادنظریة حالة الاشكال، و ھذا بدوره اعطى میزة امكانیة الاستفادة من المدى الواسع من الافكار و الادوات والنظریات التي یتیحھا ھذا الحقل المعرفي عند الحاجة لتطویر دوال اخرى ذات صلة بطوبولوجیة الشبكة اعتمادا على النموذجین المقترحین في ھذا البحث.


Article
A Cognitive Neural Linearization Model Design for Temperature Measurement System based on Optimization Algorithm

Author: Dr. Hayder Abd Dahad
Journal: IRAQI JOURNAL OF COMPUTERS,COMMUNICATION AND CONTROL & SYSTEMS ENGINEERING المجلة العراقية لهندسة الحاسبات والاتصالات والسيطرة والنظم ISSN: 18119212 Year: 2015 Volume: 15 Issue: 1 Pages: 61-71
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

Abstract – The main core of this paper is to design an experimental method for estimating of the nonlinearity, calibrating and testing of the different types of thermocouples temperature sensors (J, K, T, S and R) using multi-layer perceptron (MLP) neural network based on slice genetic (SG) optimization learning algorithm. Temperature sensor has a nonlinearity behavior nature in its output response but it requires a linear behavior output with accepts approximation in accuracy level, noise and measurement errors. Therefore, neural network topology is proposed with five main steps algorithm to reduce the effected noise and minimize the measured errors. Matlab simulation results and laboratory work (LabVIEW) validate the preciously of the proposed cognitive neural linearization algorithm in terms of calculating the temperature from the different types of thermocouples temperature sensors and minimizing the error between the actual temperature output and neural linearization temperature output as well as overcoming the problem of the over learning in the linearization model with the minimum number of fitness evaluation for the learning algorithm..

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