IJARAI Volume 1 Issue 2

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Paper 1: A Fuzzy Approach to Classify Learning Disability

Abstract: The endeavor of this work is to support the special education community in their quest to be with the mainstream. The initial segment of the paper gives an exhaustive study of the different mechanisms of diagnosing learning disability. After diagnosis of learning disability the further classification of learning disability that is dyslexia, dysgraphia or dyscalculia are fuzzy. Hence the paper proposes a model based on Fuzzy Expert System which enables the classification of learning disability into its various types. This expert system facilitates in simulating conditions which are otherwise imprecisely defined.

Author 1: Pooja Manghirmalani
Author 2: Darshana More
Author 3: Kavita Jain

Keywords: Learning Disability, Dyslexia, Dysgraphia, Dyscalculia, Diagnosis, Classification, Fuzzy Expert System.

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Paper 2: A New Machine Learning Approach to Deblurring License Plate Using K-Means Clustering Method

Abstract: Vehicle license plate recognition (LPR) is one of the important fields in Intelligent Transportation Systems (ITS). LPR systems aim to locate, segment and recognize the license plate from captured car image. Despite the great progress of LPR system in the last decade, there are still many problems to solve to reach a robust LPR system adapted to different environment and condition. The current license plate recognition systems will not effectively work well for blurred plate image. In this paper, to overcome the blurring problem a new machine learning approach to Deblurring License Plate using the K-Means clustering method have proposed. Experimental results demonstrate the effectiveness of the K-Means clustering as a feature selection method for license plate images.

Author 1: Sanaz Aliyan
Author 2: Ali Broumandnia

Keywords: license plate recognition; K-Means clustering; deblurring; machine learning.

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Paper 3: Experimental Validation for CRFNFP Algorithm

Abstract: In 2010,we proposed CRFNFP[1] algorithm to enhance long-range terrain perception for outdoor robots through the integration of both appearance features and spatial contexts. And our preliminary simulation results indicated the superiority of CRFNFP over other existing approaches in terms of accuracy, robustness and adaptability to dynamic unstructured outdoor environments. In this paper, we further study on the comparison experiments for navigation behaviors of robotic systems with different scene perception algorithms in real outdoor scenes. We implemented 3 robotic systems and repeated the running jobs under various conditions. We also defined 3 creterion to facilitate comparison for all systems: Obstacle Response Distance (ORD), Time to Finish Job (TFJ), Distance of the Whole Run (DWR). The comparative experiments indicate that, the CRFNFP-based navigating system outperforms traditional local-map-based navigating systems in terms of all criterion. And the results also show that the CRFNFP algorithm does enhance the long-range perception for mobile robots and helps planning more efficient paths for the navigation.

Author 1: Wang Mingjun
Author 2: Yi Xinhua
Author 3: Wang Xuefeng
Author 4: Tu Jun

Keywords: autonomous nagivation; stereo vision; machine learning; conditional random fields; scene analysis.

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Paper 4: A Framework for automatic generation of answers to conceptual questions in Frequently Asked Question (FAQ) based Question Answering System

Abstract: Question Answering System [QAS] generates answer to various questions imposed by users. The QAS uses documents or knowledge base for extracting the answers to factoid questions and conceptual questions. Use of Frequently Asked Question (FAQ) base gives a satisfying results to QAS, but the limitation with FAQ base system is in the preparation of Question and Answer set as most of the questions are not predetermined.QAS using FAQ base fails if no semantically related questions are found in base, corresponding to the input question. This demands an automatic answering system as backup, which generates answer especially to conceptual questions. The work presented here gives a framework for automatic generation of answers to conceptual question especially “what”, “why” and “how” type for frequently asked based, Question Answering System and in terms gradually builds up the FAQ base.

Author 1: Saurabh Pal
Author 2: Sudipta Bhattacharya
Author 3: Indrani Datta
Author 4: Arindam Chakravorty
Author 5:

Keywords: Question Answering System, Frequently Asked Question, Frequently Asked Question base, knowledge Base, semantic net, semantic frame, tagging.

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Paper 5: Sensor Location Problems As Test Problems Of Nonsmooth Optimization And Test Results Of A Few Nonsmooth Optimization Solvers

Abstract: In this paper we address and advocate the sensor location problems and advocate them as test problems of nonsmooth optimization. These problems have easy-to-understand practical meaning and importance, easy to be even randomly generated, and the solutions can be displayed visually on a 2-dimensional plane. For testing some nonsmooth optimization solvers, we present a very simple sensor location problem of two sensors for four objects with the optimal solutions known by theoretical analysis. We tested several immediately ready-to-use optimization solvers on this problem and found that optimization solvers MATLAB’s ga() and VicSolver’s UNsolver can solve the problem, while some other optimization solvers like Excel solver, Dr Frank Vanden Berghen’s CONDOR, R’s optim(), and MATLAB’s fminunc() cannot solve the problem.

Author 1: Fuchun Huang

Keywords: sensor location problems; mathematical programming; nonsmooth optimization solver; test problems.

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Paper 6: The Role Of Technology and Innovation In The Framework Of The Information Society

Abstract: The literature on the information society indicates that it is a still-developing field of research. It can be explained by the lack of consensus on basic definitions and research methods. There are also different judgments on the importance and the significance of the information society. Some social scientists write about a change of era, others emphasize parallelism with the past. There are some authors who expect that the information society will solve the problems of social inequalities, poverty and unemployment, while others blame it on the widening social gap between the information haves and have-nots. Various models of the information society have been developed so far and they are so different from country to country that it would be rather unwise to look for a single, all-encompassing definition. In our time a number of profound socio-economic changes are underway. Almost every field of our life is affected by the different phenomena of globalization, beside the growing role of the individual; another important characteristic of this process is the development of an organizing principle based on the free creation, distribution, access and use of knowledge and information. The 1990s and the 21st century is undoubtedly characterized by the world of the information society (as a form of the post-industrial society), which represents a different quality compared to the previous ones. The application of these theories and schools on ICT is problematic in many respects. First, as we stated above, there is not a single, widely used paradigm which has synthesized the various schools and theories dealing with technology and society. Second, these fragmented approaches do not have a fully-fledged mode of application to the relationship of ICT and (information) society. Third, SCOT, ANT, the evolutionary- or the systems approach to the history of technology – when dealing with information society – does not take into account the results of approaches (such as information science or information systems literature or social informatics, information management and knowledge management, communication and media studies) studying the very essence of the information age: information, communication and knowledge. The list of unnoticed or partially incorporated sciences, which focuses on the role of ICT in human information processing and other cognitive activities, is much longer

Author 1: Peter Sasvari

Keywords: Information society; Social Construction of Technology; Actor-Network-Theory.

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Paper 7: Neural Network Based Hausa Language Speech Recognition

Abstract: Speech recognition is a key element of diverse applications in communication systems, medical transcription systems, security systems etc. However, there has been very little research in the domain of speech processing for African languages, thus, the need to extend the frontier of research in order to port in, the diverse applications based on speech recognition. Hausa language is an important indigenous lingua franca in west and central Africa, spoken as a first or second language by about fifty million people. Speech recognition of Hausa Language is presented in this paper. A pattern recognition neural network was used for developing the system.

Author 1: Matthew K Luka
Author 2: Ibikunle A. Frank
Author 3: Gregory Onwodi

Keywords: Artificial neural network, Hausa language, pattern recognition, Speech recognition, speech processing

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Paper 8: Improving Performance Analysis Of Routing Efficiency In Wireless Sensor Networks Using Greedy Algorithm

Abstract: The void problem causing the routing failure is the main challenge of the greedy routing in the wireless sensor networks. The current research work still can not fully deal with the void problem since the excessive control overheads should be consumed so as to guarantee the delivery of packets. In this paper the solution to the void problem is taken up as the issue. This situation which exists in the currently existing greedy routing algorithms in wireless sensor networks. The GAR protocol is a new protocol proposed here to guarantee the delivery of packets and excessive consumption of control overheads is resolved.

Author 1: VUDA SREENIVASARAO
Author 2: CHANDRA SRINIVAS POTLURI
Author 3: SREEDEVI KADIYALA
Author 4: Capt. GENETU YOHANNES

Keywords: Greedy routing, void problem, localized algorithm, wireless sensor network.

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Paper 9: Automated Marble Plate Classification System Based On Different Neural Network Input Training Sets And PLC Implementation

Abstract: The process of sorting marble plates according to their surface texture is an important task in the automated marble plate production. Nowadays some inspection systems in marble industry that automate the classification tasks are too expensive and are compatible only with specific technological equipment in the plant. In this paper a new approach to the design of an Automated Marble Plate Classification System (AMPCS),based on different neural network input training sets is proposed, aiming at high classification accuracy using simple processing and application of only standard devices. It is based on training a classification MLP neural network with three different input training sets: extracted texture histograms, Discrete Cosine and Wavelet Transform over the histograms. The algorithm is implemented in a PLC for real-time operation. The performance of the system is assessed with each one of the input training sets. The experimental test results regarding classification accuracy and quick operation are represented and discussed.

Author 1: Irina Topalova

Keywords: Automated classification; DCT; DWT; Neural network; PLC

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Paper 10: Analysis, Design and Implementation of Human Fingerprint Patterns System “Towards Age & Gender Determination, Ridge Thickness To Valley Thickness Ratio (RTVTR) & Ridge Count On Gender Detection

Abstract: The aim of this research is to analyze humans fingerprint texture in order to determine their Age & Gender, and correlation of RTVTR and Ridge Count on gender detection. The study is to analyze the effectiveness of physical biometrics (thumbprint) in order to determine age and gender in humans. An application system was designed to capture the finger prints of sampled population through a fingerprint scanner device interfaced to the computer system via Universal Serial Bus (USB), and stored in Microsoft SQL Server database, while back-propagation neural network will be used to train the stored fingerprint. The specific Objectives of this research are to: Use fingerprint sensor to collect different individual fingerprint, alongside their age and gender, Formulate a model and develop a fingerprint based identification system to determine age and gender of individuals and evaluate the developed system.

Author 1: E O Omidiora
Author 2: O. Ojo
Author 3: N.A. Yekini
Author 4: T.O. Tubi

Keywords: Age, Gender, Fingerprint, Ridges Count, RTVTR

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