IJARAI Volume 1 Issue 4

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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Paper 1: Security Assessment of Software Design using Neural Network

Abstract: Security flaws in software applications today has been attributed mostly to design flaws. With limited budget and time to release software into the market, many developers often consider security as an afterthought. Previous research shows that integrating security into software applications at a later stage of software development lifecycle (SDLC) has been found to be more costly than when it is integrated during the early stages. To assist in the integration of security early in the SDLC stages, a new approach for assessing security during the design phase by neural network is investigated in this paper. Our findings show that by training a back propagation neural network to identify attack patterns, possible attacks can be identified from design scenarios presented to it. The result of performance of the neural network is presented in this paper.

Author 1: A Adebiyi
Author 2: Johnnes Arreymbi
Author 3: Chris Imafidon

Keywords: Neural Networks; Software security; Attack Patterns.

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Paper 2: The Need for a New Data Processing Interface for Digital Forensic Examination

Abstract: Digital forensic science provides tools, techniques and scientifically proven methods that can be used to acquire and analyze digital evidence. There is a need for law enforcement agencies, government and private organisations to invest in the advancement and development of digital forensic technologies. Such an investment could potentially allow new forensic techniques to be developed more frequently. This research identifies techniques that can facilitates the process of digital forensic investigation, therefore allowing digital investigators to utilize less time and fewer resources. In this paper, we identify the Visual Basic Integrated Development Environment as an environment that provides set of rich features which are likely to be required for developing tools that can assist digital investigators during digital forensic investigation. Establishing a user friendly interface and identifying structures and consistent processes for digital forensic investigation has been a major component of this research.

Author 1: Inikpi O ADEMU
Author 2: Dr Chris O. IMAFIDON

Keywords: autonomous coding; intellisense; visual sudio; integrated development environment; relational reconstruction; data processing.

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Paper 3: Intelligent Agent based Flight Search and Booking System

Abstract: The world globalization is widely used, and there are several definitions that may fit this one word. However the reality remains that globalization has impacted and is impacting each individual on this planet. It is defined to be greater movement of people, goods, capital and ideas due to increased economic integration, which in turn is propelled, by increased trade and investment. It is like moving towards living in a borderless world. With the reality of globalization, the travel industry has benefited significantly. It could be said that globalization is benefiting from the flight industry. Regardless of the way one looks at it, more persons are traveling each day and are exploring several places that were distant places on a map. Equally, technology has been growing at an increasingly rapid pace and is being utilized by several persons all over the world. With the combination of globalization and the increase in technology and the frequency in travel there is a need to provide an intelligent application that is capable to meeting the needs of travelers that utilize mobile phones all over. It is a solution that fits in perfectly to a user’s busy lifestyle, offers ease of use and enough intelligence that makes a user’s experience worthwhile. Having recognized this need, the Agent based Mobile Airline Search and Booking System is been developed that is built to work on the Android to perform Airline Search and booking using Biometric. The system also possess agent learning capability to perform the search of Airlines based on some previous search pattern .The development been carried out using JADE-LEAP Agent development kit on Android.

Author 1: Floyd Garvey
Author 2: Suresh Sankaranarayanan

Keywords: Agents; Biometric; JADE-LEAP; Android.

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Paper 4: Imputation And Classification Of Missing Data Using Least Square Support Vector Machines – A New Approach In Dementia Diagnosis

Abstract: This paper presents a comparison of different data imputation approaches used in filling missing data and proposes a combined approach to estimate accurately missing attribute values in a patient database. The present study suggests a more robust technique that is likely to supply a value closer to the one that is missing for effective classification and diagnosis. Initially data is clustered and z-score method is used to select possible values of an instance with missing attribute values. Then multiple imputation method using LSSVM (Least Squares Support Vector Machine) is applied to select the most appropriate values for the missing attributes. Five imputed datasets have been used to demonstrate the performance of the proposed method. Experimental results show that our method outperforms conventional methods of multiple imputation and mean substitution. Moreover, the proposed method CZLSSVM (Clustered Z-score Least Square Support Vector Machine) has been evaluated in two classification problems for incomplete data. The efficacy of the imputation methods have been evaluated using LSSVM classifier. Experimental results indicate that accuracy of the classification is increases with CZLSSVM in the case of missing attribute value estimation. It is found that CZLSSVM outperforms other data imputation approaches like decision tree, rough sets and artificial neural networks, K-NN (K-Nearest Neighbour) and SVM. Further it is observed that CZLSSVM yields 95 per cent accuracy and prediction capability than other methods included and tested in the study.

Author 1: T R Sivapriya
Author 2: A.R.Nadira Banu Kamal
Author 3: V.Thavavel

Keywords: Lease Square Support Vector Machine; z-score; Classification; KNN; Support Vector Machine.

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Paper 5: A Proposed Hybrid Technique for Recognizing Arabic Characters

Abstract: Optical character recognition systems improve human-machine interaction and are urgently required for many governmental and commercial departments. A considerable progress in the recognition techniques of Latin and Chinese characters has been achieved. By contrast, Arabic Optical Character Recognition (AOCR) is still lagging although the interest and research in this area is becoming more intensive than before. This is because the Arabic is a cursive language, written from right to left, each character has two to four different forms according to its position in the word, and most characters are associated with complementary parts above, below, or inside the character. The process of Arabic character recognition passes through several stages; the most serious and error-prone of which are segmentation, and feature extraction & classification. This research focuses on the feature extraction and classification stage, being as important as the segmentation stage. Features can be classified into two categories; Local features, which are usually geometric, and Global features, which are either topological or statistical. Four approaches related to the statistical category are to be investigated, namely: Moment Invariants, Gray Level Co-occurrence Matrix, Run Length Matrix, and Statistical Properties of Intensity Histogram. The paper aims at fusing the features of these methods to get the most representative feature vector that maximizes the recognition rate.

Author 1: S F Bahgat
Author 2: S.Ghomiemy
Author 3: S. Aljahdali
Author 4: M. Alotaibi

Keywords: Optical Character Recognition; Feature Extraction; Dimensionality Reduction; Principal Component Analysis; Feature Fusion.

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Paper 6: Automatic Melakarta Raaga Identification Syste: Carnatic Music

Abstract: It is through experience one could as certain that the classifier in the arsenal or machine learning technique is the Nearest Neighbour Classifier. Automatic melakarta raaga identification system is achieved by identifying the nearest neighbours to a query example and using those neighbours to determine the class of the query. This approach to classification is of particular importance today because issues of poor run-time performance are not such a problem these days with the computational power that is available. This paper presents an overview of techniques for Nearest Neighbour classification focusing on; mechanisms for finding distance between neighbours using Cosine Distance, Earth Movers Distance and formulas are used to identify nearest neighbours, algorithm for classification in training and testing for identifying Melakarta raagas in Carnatic music. From the derived results it is concluded that Earth Movers Distance is producing better results than Cosine Distance measure.

Author 1: B Tarakeswara Rao
Author 2: Sivakoteswararao Chinnam
Author 3: P Lakshmi Kanth
Author 4: M.Gargi

Keywords: Music; Melakarta Raaga; Cosine Distance; Earth Movers Distance; K-NN;

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