IJARAI Volume 4 Issue 9

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: Case-based Reasoning with Input Text Processing to Diagnose Mood [Affective] Disorders

Abstract: Case-Based Reasoning is one of the methods used in expert systems. Calculation of similarity degree among the cases has always been an important aspect in CBR as the system will attempt to identify cases with the highest of similarity degree in a case-base to provide solutions for new problems. In this research, a CBR model with input text processing for diagnosing mood [affective] disorder is developed. It correlates with the increased tendency of mood disorder in accordance with the dynamics of the economic and political situation. Calculation of similarity degree among the cases is one of the main focuses in this research. This study proposed a new method to calculate similarity degree between cases, Modified-Tversky. The analysis performed to assess the method used in measuring case similarity reveals that the Modified-Tversky Method surpasses the other methods. In the all tests conducted, the results of case similarity measures using the Modified-Tversky method is greater than or equal to the calculations performed using the Jaccard dan Tversky methods. The test results also provide an average level of performance in processing text input is 89.3 %.

Author 1: Sri Mulyana
Author 2: Sri Hartati
Author 3: Retantyo Wardoyo
Author 4: Edi Winarko

Keywords: Case-Based Reasoning; mood disorder; case similarity; Jaccard Method; Tversky Method; Modified-Tversky Method

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Paper 2: Instruments and Criteria for Research and Analysis of the Internet Visibility of Bulgarian Judicial Institutions WEB-Space*

Abstract: e-Justice has been under discussion at European level since 2007. The article describes some tools and displays objective criteria for evaluating the WEB-pages of judicial institutions in Bulgaria. A methodology is offered in order to improve the organization and functioning of the judicial institutions. It is used to conduct experimental tests for analysis and assessment of the main characteristics of the Bulgaria courts’ WEB-sites. The results provide grounds for findings and recommendations leading to improved communication and the presence of these institutions in the WEB.

Author 1: Nayden Valkov Nenkov
Author 2: Mariana Mateeva Petrova

Keywords: judicial institution; WEB-page; SEO (search engine optimization); evaluation criteria; court

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Paper 3: A Directional Audible Sound System using Ultrasonic Transducers

Abstract: In general the audible sound has the characteristics of spreading, however the ultrasound is directional. This study used amplitude-modulating technique for an array of 8 ultrasonic transducers to produce directional audible sound beam. In this study sound field distribution for the directional audible sound beam has been investigated. The effect of different weightings varied with different frequency for the transducers on the directivity of the sound beam has also been evaluated. An H (infinity) optimization method was used to calculate the optimal weightings of the transducers for better directivity of the sound beam. Different optimal weightings also added to the carrier and sideband frequencies to control the difference frequency’s beamwidth and sidelobe amplitude. The results showed that the beam width can be controlled and good directivity of the sound beam can be obtained by using the H_8 optimization method.

Author 1: Wen-Kung Tseng

Keywords: ultrasound; amplitude-modulating; directional audible sound beam; weightings; H_8 optimization method

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Paper 4: System for Human Detection in Image Based on Intel Galileo

Abstract: The aim of this paper is a comparative analysis of methods for motion detection and human recognition in the image. Authors propose the own solution following the comparative analysis of current approaches. Then authors design and implement hardware and software solution for motion detection in the video with human recognition in the picture. The development board Intel Galileo serves as the basis for hardware implementation. Authors implement own software solution for motion detection and human recognition in the image, resulting in the evaluation of proposed implementation.

Author 1: Rastislav Eštók
Author 2: Ondrej Kainz
Author 3: Miroslav Michalko
Author 4: František Jakab

Keywords: image processing; Intel Galileo; motion detection; object recognition

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Paper 5: System for EKG Monitoring

Abstract: In this paper the system for the electrocardiogram (EKG) monitoring based on the of Arduino microcontroller is presented. Detailed description of the electrocardiogram itself serves as a ground for building the proposed hardware and software solution. The software implementation is in a form of both, Matlab environment, and own application. Final output enables retrieval of the actual data in real time and further and provide the rudimentary diagnosis. Utilization of such device is for self home diagnosis of arrhythmia.

Author 1: Jakub Ševcík
Author 2: Ondrej Kainz
Author 3: Peter Fecilak
Author 4: František Jakab

Keywords: Arduino; arrhythmia; C sharp; cardiovascular diseases; diagnosis; electrocardiogram; heart; Matlab

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Paper 6: Automatic Recognition of Human Parasite Cysts on Microscopic Stools Images using Principal Component Analysis and Probabilistic Neural Network

Abstract: Parasites live in a host and get its food from or at the expensive of that host. Cysts represent a form of resistance and spread of parasites. The manual diagnosis of microscopic stools images is time-consuming and depends on the human expert. In this paper, we propose an automatic recognition system that can be used to identify various intestinal parasite cysts from their microscopic digital images. We employ image pixel feature to train the probabilistic neural networks (PNN). Probabilistic neural networks are suitable for classification problems. The main novelty is the use of features vectors extracted directly from the image pixel. For this goal, microscopic images are previously segmented to separate the parasite image from the background. The extracted parasite is then resized to 12x12 image features vector. For dimensionality reduction, the principal component analysis basis projection has been used. 12x12 extracted features were orthogonalized into two principal components variables that consist the input vector of the PNN. The PNN is trained using 540 microscopic images of the parasite. The proposed approach was tested successfully on 540 samples of protozoan cysts obtained from 9 kinds of intestinal parasites.

Author 1: Beaudelaire Saha Tchinda
Author 2: Daniel Tchiotsop
Author 3: René Tchinda
Author 4: Didier WOLF
Author 5: Michel NOUBOM

Keywords: Human Parasite Cysts; Microscopic image; Segmentation; Parasite extraction; feature extraction; Principal component analysis; probabilistic neural Network; Parasite Recognition

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