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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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IJARAI Vol. 5 Issue 10 (2016)

Open Access | | 6 papers

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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1

Image Retrieval Method Utilizing Texture Information Derived from Discrete Wavelet Transformation Together with Color Information

Author 1: Kohei Arai Author 2: Cahya Ragmad

Image retrieval method utilizing texture information which is derived from Discrete Wavelet Transformation: DWT together with color information is proposed. One of the specific features of the texture information extracted from portions of image is based on Dyadic wavelet transformation with forming texture feature vector by using energy derived from Gabor transform on 7 by 7 pixel neighbor of significant points. Using the Wang`s dataset, the proposed method is evaluated with retrieval success rate (precision and recall) as well as Euclidian distance between the image in concern (Query image) and the other images in the database of interest and is compared to the other method. As the result through the experiments, it is found that the DWT derived texture information is significantly effective in comparison to the color information.

Wavelet DWT local feature Color Texture CBIR
Abstract doi.org/10.14569/IJARAI.2016.051001 PDF
2

Pattern of Success Vs. Pattern of Failure: Adaptive Authentication Through Kolmogorov–Smirnov (K-S) Statistics

Author 1: Gahangir Hossain Author 2: Pradeep Palaniswamy Author 3: Rajab Challoo

Smartphones have become a basic necessity in lives of all human beings. Apart from the core functionality of communication, these become a medium for storage of sensitive personal information, financial data and official documents. Hence, there is an inevitable need to emphasize on securing access to such devices considering the nature of data being stored. In addition, accessibility and authentication methods need to secure, robust, and user-friendly. This paper discusses an adaptive authentication mechanism with a nonparametric classification approach, Kolmogorov–Smirnov (K-S) statistic, which is coupled with the use of lock pattern dynamics as a secure and user-friendly two-factor authentication method. The data used for experimental exploration were collected from a systematically programmed Android device to capture the temporal parameters when individuals drew lock patterns on the touch screen. Each user has his individualistic way of drawing the pattern, which is used as the key for identifying imposters from valid users.

Mobile user experience Biometrics Smart mobile devices Mobile identity management Mobile authentication Lock patterns Mean time value
Abstract doi.org/10.14569/IJARAI.2016.051002 PDF
3

Error Analysis of Line of Sight Estimation using Purkinje Images for Eye-based Human-Computer Interaction: HCI

Author 1: Kohei Arai

Error analysis of line of sight estimation using Purkinje images for eye-based Human-Computer Interaction: HCI is conducted. Double Purkinje images which are obtained by two points of light sources are used in the proposed method for eye rotation angle estimation. It aimed at the improvement of the eyeball rotation angle accuracy by simply presuming the value of the curvature radius of the cornea. This technique is a cancellation of the time of the calibration that is the problem of past glance presumption. By presuming the size of the radius of curvature of the cornea. As a result, the eyeball rotation angle presumption accuracy of about 0.98deg was obtained 0.57deg and horizontally in the vertical direction without doing the calibration.

Computer input just by sight Computer input by human eyes only Purkinje image
Abstract doi.org/10.14569/IJARAI.2016.051003 PDF
4

Method for Vigor Diagnosis of Tea Trees based on Nitrogen Content in Tealeaves Relating to NDVI

Author 1: Kohei Arai

Method for vigor diagnosis of tea trees based on nitrogen content in tealeaves relating to NDVI is proposed. In the proposed method, NIR camera images of tealeaves are used for estimation of nitrogen content in tealeaves. The nitrogen content is highly correlated to Theanine (amid acid) content in tealeaves. Theanine rich tealeaves taste good. Therefore, tealeaves quality can be estimated with NIR camera images. Also, leaf area of tealeaves is highly correlated to NIR reflectance of tealeaf surface. Therefore, not only tealeaf quality but also harvest mount can be estimated with NIR camera images. Experimental results shows the proposed method does work for estimation of appropriate tealeaves harvest timing with NIR camera images.

Tealeaves Nitrigen content Amino accid Leaf area NDVI
Abstract doi.org/10.14569/IJARAI.2016.051004 PDF
5

Flowcharting the Meaning of Logic Formulas

Author 1: Sabah Al-Fedaghi

In logic, representation of a domain (e.g., physical reality) comprises the things its expressions (formulas) refer to and their relationships. Recent research has examined the realm of nonsymbolic representations, especially diagrams. It is claimed that, in general, diagrams have advantages over linguistic descriptions. Current diagrammatic representations of logic formulas do not completely depict their underlying semantics, and they lack a basic static structure that incorporates elementary dynamic features, creating a conceptual gap that can lead to misinterpretation. This paper demonstrates a methodology for mapping the sense of a logic formula and producing diagrams that integrate linguistic conception, truth-values, and meaning and can be used in teaching, communication, and understanding, especially with students specializing in logic representation and reasoning.

knowledge representation logic formulas diagrammatic representation sense
Abstract doi.org/10.14569/IJARAI.2016.051005 PDF
6

Pursuit Reinforcement Competitive Learning: PRCL based Online Clustering with Learning Automata

Author 1: Kohei Arai

A new online clustering method based on not only reinforcement and competitive learning but also pursuit algorithm (Pursuit Reinforcement Competitive Learning: PRCL) as well as learning automata is proposed for reaching a relatively stable clustering solution in comparatively short time duration. UCI repository data which are widely used for evaluation of clustering performance in usual is used for a comparative study among the existing conventional online clustering methods of Reinforcement Guided Competitive Learning: RGCL, Sustained RGCL: SRGCL, Vector Quantization, and the proposed PRCL. The results show that the clustering accuracy of the proposed method is superior to the conventional methods. More importantly, it is found that the proposed PRCL is much faster than the conventional methods. The proposed method is then applied to the evacuation simulation study. It is found that the proposed method is much faster than the conventional method of vector quatization to find the most appropriate evacuation route. Due to the fact that the proposed PRCL method allows finding the most appropriate evacuation route, collisions among peoples who have to evacuate for the proposed method is much less than that of vector quatization.

Pursuit Reinforcement Guided Competitive Learning Reinforcement Guided Competitive Learning Sustained Reinforcement Guided Competitive Learning Vector Quantization Learning Automata
Abstract doi.org/10.14569/IJARAI.2016.051006 PDF
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