IJARAI Volume 2 Issue 1

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Paper 1: CBR in the service of accident cases evaluating

Abstract: This paper introduces a research aiming at the development of a decision support system concerning the approval of automated railway transportation systems. The objective is to implement a valuation method for the degree of compliance of the automated transportation system in-group of safety standards by the analysis of the scenarios of accident. To reach this target, we envisaged an approach Rex (Return of experience) who draws the lessons of accidents / incidents lived and/or imagined by the experts of the analysis of security in the IFSTAAR. Our approach consists in offering a decision support in the side of the experts of the certification based on a reuse of the scenarios of accidents already validated historically on other approved transportation systems. This approach Rex is very useful since it provides to the experts a class of scenarios of accidents similar to the new case treated and getting closer to the context of new case. The Case-based reasoning is then exploited as a mode of reasoning by analogy allowing to choose and to recollect one under group of historical cases that can help in the resolution of the new case introduced by the experts. Process-Oriented Case-Based Reasoning (PO-CBR) is a growing application area in which CBR is used to address problems involving process data in a variety of specialized domains. PO-CBR systems often use structured cases. Our approach is characterized by a two-phased retrieval strategy. A first phase consists in retrieving a set of cases to be considered (a class of cases most similar to a problem to resolve). In a second phase, a more fine grained strategy is then applied to the pool of candidate cases already selected by the mean of similarity measures. This approach can enhance the process of retrieving cases compared to an exhaustive case-by-case comparison.

Author 1: Lassaâd Mejri
Author 2: Sofian Madi
Author 3: Henda Ben Ghézala

Keywords: componentSecurity of transport; Artificial Intelligence; Ontology; Case-Based Reasoning; Resolution scenario; Scenario of accident.

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Paper 2: Prediction Method for Time Series of Imagery Data in Eigen Space

Abstract: Prediction method for time series of imagery data on eigen space is proposed. Although the conventional prediction method is defined on the real world space and time domains, the proposed method is defined on eigen space. Prediction accuracy of the proposed method is supposed to be superior to the conventional methods. Through experiments with time series of satellite imagery data, validity of the proposed method is confirmed.

Author 1: Kohei Arai

Keywords: prediction method; eigen value decomposition; eigen space; time series analysis.

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Paper 3: Image Prediction Method with Nonlinear Control Lines Derived from Kriging Method with Extracted Feature Points Based on Morphing

Abstract: Method for image prediction with nonlinear control lines which are derived from extracted feature points from the previously acquired imagery data based on Kriging method and morphing method is proposed. Through comparisons between the proposed method and the conventional linear interpolation and widely used Cubic Spline interpolation methods, it is found that the proposed method is superior to the conventional methods in terms of prediction accuracy.

Author 1: Kohei Arai

Keywords: Kriging; morphing; image prediction; interpolation; image feature extraction.

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Paper 4: Method for object motion characteristic estimation based on wavelet Multi-Resolution Analysis: MRA

Abstract: Method for object motion characteristic estimation based on wavelet Multi-Resolution Analysis: MRA is proposed. With moving pictures, the motion characteristics, direction of translation, roll/pitch/yaw rotations can be estimated by MRA with an appropriate support length of the base function of wavelet. Through simulation study, method for determination of the appropriate support length of Daubechies base function is clarified. Also it is found that the proposed method for object motion characteristics estimation is validated.

Author 1: Kohei Arai

Keywords: object motion characteristic; MRA; wavelet.

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Paper 5: An interactive Tool for Writer Identification based on Offline Text Dependent Approach

Abstract: Writer identification is the process of identifying the writer of the document based on their handwriting. The growth of computational engineering, artificial intelligence and pattern recognition fields owes greatly to one of the highly challenged problem of handwriting identification. This paper proposes the computational intelligence technique to develop discriminative model for writer identification based on handwritten documents. Scanned images of handwritten documents are segmented into words and these words are further segmented into characters for word level and character level writer identification. A set of features are extracted from the segmented words and characters. Feature vectors are trained using support vector machine and obtained 94.27% accuracy for word level, 90.10% for character level. An interactive tool has been developed based on the word level writer identification model.

Author 1: Saranya K
Author 2: Vijaya MS

Keywords: Feature Extraction; Support Vector Machine; Training, Writer Identification.

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Paper 6: Multi-modal Person Localization And Emergency Detection Using The Kinect

Abstract: Person localization is of paramount importance in an ambient intelligence environment since it is the first step towards context-awareness. In this work, we present the development of a novel system for multi-modal person localization and emergency detection in an assistive ambient intelligence environment for the elderly. Our system is based on the depth sensor and microphone array of 2 Kinect devices. We use skeletal tracking conducted on the depth images and sound source localization conducted on the captured audio signal to estimate the location of a person. In conjunction with the location information, automatic speech recognition is used as a natural and intuitive means of communication in order to detect emergencies and accidents, such as falls. Our system attained high accuracy for both the localization and speech recognition tasks, verifying its effectiveness.

Author 1: Georgios Galatas
Author 2: Shahina Ferdous
Author 3: Fillia Makedon

Keywords: localization; multi-modal; Kinect; speech recognition; context-awareness; 3-D interaction

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