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Volume-6 Issue-4: Published on September 05, 2016
Volume-6 Issue-4: Published on September 05, 2016

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Volume-6 Issue-4, September 2016, ISSN: 2231-2307 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Vahid Nourani

Paper Title:

Comparative Investigation of Trial load and Finite Element Methods in Analysis of Arch Dams

Abstract: Because of important role of dams and dam construction in human life, in the present paper the method of analysis of an important kind of dam (arch dam) has been presented in two different scientific ways and their results have been compared. In the method presented herein, the dam has been divided into horizontal elements of arcs and vertical elements of cantilevers, and using compatibility of displacements and trial and error (trial load method) the share of cantilevers and arcs from applied loads on dam have been determined. Then another analysis has been performed using Finite Element Method (FEM) by indicating stiffness matrix using iso-parametric hexahedral elements with eight nodes. Using the available equations, the displacements of nodes have been calculated. Because of high volume of calculations, computer has been used and software has been prepared. The results of these two methods have been compared to each-other. The results show that the trial load method is a reliable method in spite of the fact that simplifying assumptions have been used in its theory. As a result, an arch dam can be easily analyzed by trial load method. Also, to get more accurate results, more complete methods are necessary to solve FEM equations.

 Arch dam, Trial load method, Finite Element Method, Arc analysis, Cantilever analysis.


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Deepali Bhadane, K. N. Pawar

Paper Title:

Feature Based Mosaicing of Images

Abstract:  Image Mosaicing is a process of assembling the multiple overlapping images of the identical scene into a larger image. The output of the image mosaic will be the union of two input images. Image - mosaicing algorithms are used for gaining a mosaiced image. In this paper we have described the feature based mosaicing of two images. Feature based image mosaicing is the combination of corner detection, corner matching, motion parameter estimation and image stitching .For corner detection there are various algorithms - HARRIS, SUSAN,CSS. This corner detection algorithm produces an efficient and informative output mosaiced image. After corner detection RANSAC algorithm is used for Homography. After that image warping and image blending is done. Importance of Image Mosaicing can be seen in the field of medical imaging, computer vision, data from satellite, military automatic target recognition. In this paper we compare result CSS, SUSAN, HARRIS.

 Image mosaicing, Feature Extraction, Image registration, corner detection using HARRIS,SUSAN,CSS algorithm, Homography using RANSAC, Image warping, Image Blending.


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Ali Abdulraheem Alwan

Paper Title:

A Framework and Prototype for Personal Digital Library System

Abstract:   Nowadays, Digital Libraries have an inescapable role on delivering information resources to their users and new trends in Digital Libraries are to change from the passive state of only providing information resources to their users to a more active state by enabling the users of Digital Library to collaborate and share knowledge with each other. This project addresses the situation of managing a personal library and converting it from manually supported system to digitally supported system, because the current system makes it hard to serve the user effectively. The main objective was to develop a digital library management system, with a search functionality to facilitate the search and management of library resources. In general, this project offers the following services to the user: (a) Identify the transaction movement for the books and other resources of the library; (b) Know the detailed information about the books and other resources of   the library; (c) The ability to have reports from different kind of view for books and other resources of the library; (d) the ability to add, delete, update, find, etc. for the most data in the system in an easy way; (e) Offer a kind of security for the system by allowing to use it by having a specific password. The designed model is employed to develop the concept of personal library and make its resources available to use, integrate and share among many users efficiently and effectively.

  Digital Library, Personal Digital Library, PDL.


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Peter. U.  Eze, Dawn. C. Walker, Ifeyinwa E. Achumba

Paper Title:

Constructive Initialization of a Genetic Algorithm for the Solution of a Highly Constrained Departmental Timetabling Problem

Abstract: The University or Departmental Timetabling Problem (UTP or DTP) is a scheduling problem ridden with numerous constraints. Each of the constraints has a complex effect on the ideal solution and their combined effect makes the problem harder to solve. As a solution to this problem, a genetic algorithm (GA) approach was augmented by a process of constructive initialisation and applied to an exemplar scheduling problem in the Department of Computer Science at the University of Sheffield. The problem entailed scheduling of timetabled slots for 33 modules across a range of taught programmes at various levels, delivered by 29 lecturers in 10 lecture theatres and 6 laboratories.  A total of eight hard constraints and four soft constraints were considered, for problems of five levels of increasing complexity. It was found that the synergistic solution satisfied all the hard constraints, achieved up to 75% optimisation of the soft constraints, and converged within 500 iterations or an average of 2.74 minutes. These results indicate that the GA, when combined with constructive initialization, will give efficient solution to the DTP problem with constrained variables.

Departmental Timetabling Problem, Constructive Initialization, Genetic Algorithm, Scheduling, Constraints


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Nguyen Trong Dung, Nguyen Chinh Cuong

Paper Title:

Influence of the Particle Size on the Microstructure and the Curie Temperature (TC) of Nano-Iron Particles Model

Abstract:  This paper studies the influence of the particle size (with the chosen sizes 2.122 nm; 2.49 nm; 2.884 nm; 3.128 nm; 3.254 nm; 4.07 nm; 4.68 nm; 4.978 nm; 5.3 nm; 6.602 nm; 7.774 nm; 8.392 nm) on the microstructure and the Curie temperature (Tc) of nano-iron particles model. The nano-iron particles were created by Molecular Dynamics Simulation method with the Pak-Doyama pair interaction potential and aperiodic boundary conditions which is called soft boundary or free boundary. The microstructure characteristics were analyzed through the radial distribution function (RDF), the energy and the coordination number. The Curie temperature (Tc) is the point at which materials switch from the ferromagnetic phase to the paramagnetic phase and it is determined through the Ising model. The study purpose of this paper is to determine the relationship between the particle size and the Curie temperature (Tc) of the model. The obtained results showed that there was specific influence of the particle size on the microstructure and the Curie temperature (Tc) of the nano-iron particles model: when the size of the nano-iron particles was increased from 2.122 nm to 2.49 nm; 2.884 nm; 3.128 nm; 3.254 nm; 4.07 nm; 4.68 nm; 4.978 nm; 5.3 nm; 6.602 nm; 7.774 nm; 8.392 nm, the phase transition temperature of the model increased from 8.9 K to 9.3 K; 9.5 K; 9.6 K; 9.7 K; 10 K; 10.1 K; 10.2 K; 10.3 K; 10.4 K; 10.5 K; 10.6 K respectively. The results have also been compared with the results from the theoretical – experimental model showing the significant influence of the particle size on the Curie temperature of the nano-iron particles model. In addition, the nano-iron particles model at different sizes had the different microstructure characteristics and different Curie temperatures.

Particle size, microstructure, Curie temperature (Tc), nano-iron particles model, Molecular Dynamics.


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B.  Sowmiya, S. Amal Raj

Paper Title:

Review of the Self-Organizing Map (SOM) Approach in the Field of Environmental Engineering

Abstract: In environmental engineering field, the use of artificial neural networks (ANNs) has received steadily increasing interest over the last decade or so. In ANN, self-organizing map (SOM) is an unsupervised learning method to analyze, cluster, and model various types of large databases. There is, however, still a notable lack of comprehensive literature review for SOM along with training and data handling procedures, and potential applicability. As a result the present paper, first explains the basic structure and algorithm of self-organizing map (SOM) and secondly, to review published applications with special importance on environmental engineering related problems in order to assess how well SOM can be used to solve a particular problem. Finally, concluded that self-organizing map (SOM) is a hopeful technique suitable to investigate, model, and rule environmental related problems. However, in recent years, self-organizing map (SOM) has displayed a steady increase in the number of applications in environmental engineering related problems due to the robustness of the method.

Linear and non- linear process, Artificial Neural Network, Self Organizing Map, Environmental Engineering, Review.


1.       Aguado D., Montoya, T., Borras, L., Seco, A., Ferrer, J.Using Self Organizing Maps and PCA analysis and interpreting data from a P- removal. Engineering apllication of Artificial intelligence. 2008.21.919-930.
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4.       ASCE Task Committee on application of Artificial Neural Networks in Hydrology,. Artificial neural networks in hydrology. II: hydrologic applications. Journal of Hydrologic Engineering. 2000b. 5 (2), 124-137.

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7.       Bowden, G.J., Maier, H.R., Dandy, G.C.,. Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river. Journal of Hydrology. 2005b. 301, 93-107.

8.       Dawson, C.W., Wilby, R.L.,. Hydrological modelling using artificial neural networks. Progress in Physical Geography. 2001. 25 (1), 80-108.

9.       Heikkinen, M., Hiltunen, T., Liukkonen, M., Kettunen, A., Kuivalainen, R., Hiltunen, Y.,. A modelling and optimization system for fluidized bed power plants. Expert Systems with Applications. 2009. 36, 10274-10279.

10.    Heikkinen, M., Kettunen, A., Niemitalo, E., Kuivalainen, R., Hiltunen, Y.,. SOM-based method for process state monitoring and optimization in fluidized bed energy plant. In: Duch, W., Kacprzyk, J., Oja, E., Zadro_zny, S. (Eds.), Lecture Notes in Computer Science. 3696. Springer-Verlag Berlin, Heidelber. 2005.  409 -414.

11.    Heikkinen, M., Poutiainen, H., Liukkonen, M., Heikkinen, T. & Hiltunen, Y.Subtraction analysis based on self-organizing maps for an industrial wastewater treatment process. Mathametica. Computation Simulation. 2011. 82. 450–459.

12.    Hilario Lopez Garcia, Ivan Machon Gonzalez. Self-organizing map and clustering for wastewater treatment monitoring. Engineering Applications of Artificial Intelligence. 2004. 17. 215–225.

13.    Kohonen, T., 2001. Self-Organizing Maps. Springer-Verlag, Berlin.

14.    Liukkonen, M., Heikkinen, M., Hälikkä, E., Kuivalainen, R., Hiltunen, Y.,. Emission analysis of a fluidized bed boiler by using self-organizing maps. In:Kolehmainen, M., Toivanen, P., Beliczynski, B. (Eds.), Lecture Notes in Computer Science 5495. Springer-Verlag, Berlin Heidelberg, 2009c. 119-129.

15.    Liukkonen, M., Heikkinen, M., Hiltunen, T., Hälikkä, E., Kuivalainen, R., Hiltunen, Y., 2009b. Modeling of process states by using artificial neural networks in a fluidized bed energy plant. In: Troch, I., Breitenecker, F. (Eds.), Proceedings of MATHMOD 09 VIENNA. Argesim Publishing House, Vienna,pp. 2008.397-402.

16.    M. Pavan, R. Todeschini. 2008. Scientific Data Ranking Methods: Theory and Applications, Elsevier, Amsterdam.

17.    M.Liukkonen, T. Hiltunen, E.Halikka, Y. Hiltunen. Modeling of the fluidized bed combustion process of NOx emission using SOM. An application to the diagnosis of process state. Environmenatl modeling and Software. 2011. 26, 605-614.

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20.    Maier, H.R., Dandy, G.C.,. Neural networks for the prediction and forecasting of water resources variables: a review of modeling issues and applications. Environmental Modelling and Software. 2000. 15, 101-124.

21.    Richard Olawoyin,Antonia Nieto, Robert Larry Grason, Frank Hardisty, Samuel Oyewole,. Application of Artificial Neural Networks and Self organizing Maps for the categorization of water, soil and sediment quality in Petrochemical regions.Expert system with applications. 2013. 40,3634-3648.

22.    Tsakovski, S., Simeonov, V., .Hasse diagram technique as exploratory tool in sediment pollution assessment, Journal of Chemometrics . 2011.25 (5) 254–261.

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26.    Yan An, Zhihong Zou, Ranran Li, Descriptive.Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map. International Journal of Environmental Research and Public Health. 2016.13(1).115.

27.    Young-Seuk Park , Yong-Su Kwon, Soon-Jin Hwang , Sangkyu Park.Characterizing effects of landscape and morphometric factors on water quality of reservoirs using a self-organizing map. Environmental modelling and software. 2014. 55. 214-221.





Hayfa Masghouni

Paper Title:

Comparison Between Algorithms of MRI Image Segmentation

Abstract: In this article, we present different algorithms of MRI image segmentation based on classification of pixels. First, we present FCM (Fuzzy C_Means) and its different extensions with a comparison between them, after we present GMM (Gaussian Mixture Model) and EM (Expectation Maximization) and its extensions with a comparison between them.

 FCM, EM, GMM, MRI image segmentation


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5.       Krinidis S, Chatzis V, "A Robust Fuzzy Local Information C-Means Clustering Algorithm,"IEEE Transactions on Image Processing 2010,19:1328-1337.

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16.    Adelino R. Ferreira da Silva, "Bayesian mixture models of variable dimension for image

17.    segmentation," Rua Dr. Bastos Goncalves, n. 5, 10A, 1600-898 Lisboa, Portugal,2008

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Majid Khan, Abdus Salam, Javed Iqbal, Syed Irfan Ullah

Paper Title:

Comparative Analysis of Automated Software Testing Tools

Abstract:  The most significant segments of software development is software testing. Automated software testing is an effective testing process that reduces the effort and cost of manual testing. However, it is difficult to select a suitable software testing tool from the huge list of freely available tools. The main contribution of this work is to conduct a comparative study of three readily available automated software testing tools such as QTP, Silk4j and Load Runner. The selected tools are evaluated and compared on the basis of their usability, maintenance and effectiveness. For this purpose we have taken an existing JAVA based applications to perform automated testing on these three tools. The results will assist testers to effectively select the best automated software testing tool for related applications.

significant segments, However, Automated software, QTP, JAVA based,


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15.    Alégroth, Emil, Robert Feldt, and Pirjo Kolström. "Maintenance of automated test suites in industry: An empirical study on Visual GUI Testing." Information and Software Technology 73 (2016): 66-80.

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Aditi Kacheria, Nidhi Shivakumar, Shreya Sawkar, Archana Gupta

Paper Title:

Loan Sanctioning Prediction System

Abstract: People operating in banks face lots of issues which involve approval of a loan. In the 21st century, people often rely on technology to tackle such issues. This paper proposes a loan sanctioning system which determines whether or not a loan should be given to a person, based on certain attributes. In spite of banks following stringent rules and regulations and conducting meticulous background checks while sanctioning a loan and keeping in mind the probability of the person's ability to return the loan, often such situations are faced where in, the person is unable to repay the loan that has been given to him. In this paper, the system that we propose for the bankers will help them predict the credible customers who have applied for loan, thereby improving the chances of their loans being repaid in time. This classification is done using Naïve Bayesian algorithm. In order to improve the classification accuracy, the quality of the data is improved before classifying it by using K-NN and Binning algorithms. This system uses these algorithms in order to yield a better efficiency so as to reduce the possibility of such a problem. The proposed system additionally facilitates self-confirmation regarding the same for the commoner.

 Binning, Data mining, K-NN, Naïve Bayesian.


1.       Nirmala Devi M.; Appavu S.; Swathi U.V., “An amalgam KNN to predict diabetes mellitus”, Emerging Trends in Computing, Communication and Nanotechnology
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4.       Sudhakar, K.; Manimekalai, Dr. M., "Study of Heart Disease Prediction using Data Mining", International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 1, ISSN: 2277 128X, pages 1157-1160, January 2014.

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6.       Dr. K. Usha Rani, “Analysis of Heart Diseases Dataset Using Neural Network Approach”, International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.1, No.5, September 2011.

7.       Karthika Jayprakash, Nidhi Kargathra, Pranay Jagtap, Suraj Shridhar and Archana Gupta, "Comparison of Classification Techniques for Heart Health Analysis System", International Journal of Computer Sciences and Engineering(IJCSE), Volume-04, Issue-02, E-ISSN: 2347-2693, pages 92-95, Feb. 2016.

8.       Ms. Neethu Baby, Mrs. Priyanka L.T., "Customer Classification And Prediction Based On Data Mining Technique", International Journal of Emerging Technology and Advanced Engineering (IJETAE), Volume 2, Issue 12, ISSN 2250-2459, ISO 9001:2008 Certified Journal, pages 314-318, December 2012.

9.       Rucha Shinde, Sandhya Arjun, Priyanka Patil, Prof. Jaishree Waghmare, "An Intelligent Heart Disease Prediction System Using K-Means Clustering and Naïve Bayes Algorithm",  International Journal of Computer Science and Information Technologies (IJCSIT), Vol. 6 (1), ISSN: 0975-9646, pages 637-639, 2015.

10.    L.Pandeeswari, K.Rajeswari, "K-Means Clustering and Naive Bayes Classifier For Categorization of Diabetes Patients",   International Journal of Innovative Science, Engineering & Technology (IJISET), Vol. 2 Issue 1, ISSN 2348 – 7968, pages 179-185, January 2015.

11.    Sivasree M S, Rekha Sunny T, "Loan Credibility Prediction System Based on Decision Tree Algorithm", International Journal of Engineering Research & Technology (IJERT), Vol. 4 Issue 09, ISSN: 2278-0181, pages 825-830, September-2015.






S. A. Asklany, Khaled Elhelow, M. Abd El-Wahab

Paper Title:

On using Adaptive Hybrid Intelligent Systems in PM10 Prediction

Abstract: A comparative study based on producing two intelligence systems applied to PM10 prediction was presented in this work. Adaptive Network –based Fuzzy Inference System (ANFIS) used in build a system has three weather elements as input variables (Wind Speed, Wind Direction and Temperature) and the PM10 as output variable for PM10 nowcast model. Another technique used ANFIS in prediction of chaotic time series to get 6 hours forecast for PM10 from the present data. For developing the models, thirteen years hourly data for Mansoria station coordinates 29° 300′ 0″ N, 45° 45′ 0″ E from 1995to 2007 has been used.  Different models employing a different training and testing data sets had been studied. The criteria of performance evaluation are calculated for estimating and comparing the performances of the two techniques.  The results show that the two presented models success tools in PM10 prediction with acceptable root mean square error (RMSE); the model built on using ANFIS for chaotic time series prediction has smaller error compared with the adaptive network fuzzy inference system.

  Air quality, artificial intelligence, pollution, ANFIS, soft computing


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Rana Kadhim Abdulnabi

Paper Title:

Using Spray Pyrolysis Technique to Prepare PBS Lead Sulfide Thin Films and Study Their Structural and Electrical Properties as Function of Thickness

Abstract:  Lead sulfide (PbS) thin films are prepared by "solution "from, lead acetate" pb (CH3COO)2  and Thiourea CS(NH2) using Spray Pyrolysis Technique (SPT) on glassy substrates at temperature of 200Cº with a variable thicknesses of 100, 200, 300 nm. The "structural properties are approved by X-Ray Refraction (XRR), which helped in displaying the films having a cubic structure such as NaCl The size of the crystal grains of PbS films are shown to be increased when increasing the thickness of PbS films. Roughness of the films was measured according to the Root Mean Square (RMS). This was achieved using Scanning Microscope (SM). With increasing film thickness to the mentioned values, results showed an increase with RMS, electrical conductivity of the PbS film to 0.0186*10­³, 0.4166*10-3 and 0.9090*10­³ (Ω.cm)­¹ and with charge-carrier concentration as well to 0.298*10¹¹, 1.1*1011, 12*10¹¹ cm− 3.الخلاصة: في هذا البحث تم تحضير اغشية كبريتيد الرصاص( PbS )  بأستخدام محلول من خلات الرصاص 2(CH3COO ) PbS والثايوريا  CS(NH2)  على قاعدة زجاجية بدرجة حرارة 200 Cͦ بطريقة الرش الكيميائي الحراري . تم دراسة الخصائص التركيبية عند اسماك متغيرة (100,200,300)   بأستخدام اشعة  X- Ray التي اوضحت الشكل البلوري للاغشية  وقد لاحظنا زيادة الحجم الحبيبي للاغشية بزيادة سمك الغشاء , كما تم قياس خشونة السطح للاغشية بأستخدام فحص STM. كما تم دراسة الخصائص الكهربائية ومنها التوصيلية الكهربائية  والتي قيمها 0.0186,0.4166,0.9090)*10ˉ³( Ω.cm)ˉ¹) وحاملات الشحن للاغشية والتي قيمها (0.298,1.1,12)*10¹¹ cmˉ³

 lead sulfide, chemical pyrolysis, thin film, semiconductor


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Surinder Kumar

Paper Title:

Module Allocation for Maximizing Reliability of Distributed Computing Systems using Genetic Algorithms

Abstract:   The problem of the module allocation in distributed computing system is to need to allocate a number of modules to different processors for execution. The paper deals with the problem of module allocation in heterogeneous distributed computing systems with the goal of maximizing the system reliability. We present a genetic algorithm to obtain the optimal solution for this problem. In the performance of the algorithm we consider more one parameter such as the number of modules, the number of processors, and module interaction density of applications. The experimental results illustrate the effectiveness of this algorithm over conventional algorithms.

 Distributed computing systems, Genetic algorithms, Module allocations and Maximizing reliability.


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Mohammed AbdALLA Adam Elmaleeh, Fadalalla Suleiman Mahmoud Gamer

Paper Title:

Implementation of FBG Mechanism for the Removal of Optical Signal Spreading

Abstract:    Single mode fiber has been used in long haul communications systems to increase the transmission capacity and to meet the increasing of demand for the communication services. Therefore, any type of the signal degradation effects should be strappingly minimized. The performance of a digital communication system is measured by probability of error per bit, which is referred to as the bit error rate (BER). Error occurs as a result of noise in the received signal, or due to pulse spreading into neighboring bits which result in symbol interference.  In this paper the optical signal degradation effects were studied. Initially the optical signal Eye diagram for an optical fiber of different lengths before applying compensation mechanism were obtained using OPTsys simulation tool.   The data rate of 20 - 40 Gbps is introduced to the system and examined using specified fiber lengths parameters. It is observed that the received signals were significantly degrade due to the signal degradation effects. Fiber Bragg Grating is implemented as spreading lessens mechanism and the optical amplifier (EDFA) is used to compensate the reduction of signal power when propagates through the fiber strand. The results obtained showed that the width of the pulse spreading significantly reduced from 0.43ps to 0.18ps, with BER of 8.825x10-10, Quality factor = 9.7 and total possible distance is found to be of 25 k.

Digital communication, FBG, BER, Optical Signal, Optical amplifier Bearings, Fast Fourier transform.


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