IJARAI Volume 1 Issue 6

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Paper 1: Human Gait Gender Classification in Spatial and Temporal Reasoning

Abstract: Biometrics technology already becomes one of many application needs for identification. Every organ in the human body might be used as an identification unit because they tend to be unique characteristics. Many researchers had their focus on human organ biometrics physical characteristics such as fingerprint, human face, palm print, eye iris, DNA, and even behavioral characteristics such as a way of talk, voice and gait walking. Human Gait as the recognition object is the famous biometrics system recently. One of the important advantage in this recognition compare to other is it does not require observed subject’s attention and assistance. This paper proposed Gender classification using Human Gait video data. There are many human gait datasets created within the last 10 years. Some databases that widely used are University of South Florida (USF) Gait Dataset, Chinese Academy of Sciences (CASIA) Gait Dataset, and Southampton University (SOTON) Gait Dataset. This paper classifies human gender in Spatial Temporal reasoning using CASIA Gait Database. Using Support Vector Machine as a Classifier, the classification result is 97.63% accuracy.

Author 1: Kohei Arai
Author 2: Rosa Andrie Asmara

Keywords: Gait Gender Classification; Gait Energy Motion; CASIA Gait Dataset.

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Paper 2: A Novel 9/7 Wavelet Filter banks For Texture Image Coding

Abstract: This paper proposes a novel 9/7 wavelet filter bank for texture image coding applications based on lifting a 5/3 filter to a 7/5 filter, and then to a 9/7 filter. Moreover, a one-dimensional optimization problem for the above 9/7 filter family is carried out according to the perfect reconstruction (PR) condition of wavelet transforms and wavelet properties. Finally, the optimal control parameter of the 9/7 filter family for image coding applications is determined by statistical analysis of compressibility tests applied on all the images in the Brodatz standard texture image database. Thus, a new 9/7 filter with only rational coefficients is determined. Compared to the design method of Cohen, Daubechies, and Feauveau, the design approach proposed in this paper is simpler and easier to implement. The experimental results show that the overall coding performances of the new 9/7 filter are superior to those of the CDF 9/7 filter banks in the JPEG2000 standard, with a maximum increase of 0.185315 dB at compression ratio 32:1. Therefore, this new 9/7 filter bank can be applied in image coding for texture images as the transform coding kernel.

Author 1: Songjun Zhang
Author 2: Guoan Yang
Author 3: Zhengxing Cheng
Author 4: Huub van de Wetering

Keywords: 9/7 wavelet filter banks; image coding; lifting scheme; texture image; Brodatz database.

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Paper 3: Mesopic Visual Performance of Cockpit’s Interior based on Artificial Neural Network

Abstract: The ambient light of cockpit is usually under mesopic vision, and it’s mainly related to the cockpit’s interior. In this paper, a SB model is come up to simplify the relationship between the mesopic luminous efficiency and the different photometric and colorimetric variables in the cockpit. Self-Organizing Map (SOM) network is demonstrated classifying and selecting samples. A Back-Propagation (BP) network can automatically learn the relationship between material characteristics and mesopic luminous efficiency. Comparing with the MOVE model, SB model can quickly calculate the mesopic luminous efficiency with certain accuracy.

Author 1: Dongdong WEI
Author 2: Gang SUN

Keywords: component; Mesopic Vision; Cockpit; Artificial Neural Network; BP; SOM.

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Paper 4: Visual Working Efficiency Analysis Method of Cockpit Based On ANN

Abstract: The Artificial Neural Networks method is applied on visual working efficiency of cockpit. A Self-Organizing Map (SOM) network is demonstrated selecting material with near properties. Then a Back-Propagation (BP) network automatically learns the relationship between input and output. After a set of training, the BP network is able to estimate material characteristics using knowledge and criteria learned before. Results indicate that trained network can give effective prediction for material.

Author 1: Yingchun CHEN
Author 2: Dongdong WEI
Author 3: Gang SUN

Keywords: component; Visual Working Efficiency; Artificial Neural Networks;Cockpit; BP; SOM.

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Paper 5: The Fault Location Method Research of Three-Layer Network System

Abstract: The fault location technology research of three-layer network system structure dynamic has important theoretic value and apparent engineering application value on exploring the fault detection and localization of the complex structure dynamic system. In this article, the method of failure propagation and adverse inference are adopted, the fault location algorithm of the three-layer structure dynamic network system is established on the basis of the concept of association matrix and the calculating method are proposed, and the simulation calculation confirmed the reliability of this paper. The results of the research can be used for the fault diagnosis of the hierarchical control system?testing of the engineering software and the analysis of the failure effects of layered network of all kinds and other different fields.

Author 1: Hu Shaolin
Author 2: Li ye
Author 3: Karl Meinke

Keywords: Three-layer network; fault propagation; fault location.

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