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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Gholami, M. | Gharehpetian, G.B. | Mohammadi, M.
Article Type: Research Article
Abstract: In this paper, a new method is presented, to assess the security of the power system. In this method, an intelligent hierarchical structure for classifiers is used, which requires fewer calculation efforts in comparison with direct methods. Therefore, it is suitable for real time applications. Also, the correlations among different scenarios of the power system are considered. Therefore, the results are more realistic. The proposed method is implemented on IEEE 39-Bus New England and IEEE 300-Bus networks and the results show the superiority of the proposed method over other ones, to assess the system static security.
Keywords: Static security assessment, decision tree, correlated data, real time applications
DOI: 10.3233/IFS-151566
Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2875-2880, 2015
Authors: Ali Khan, Sajid | Riaz, Naveed | Akram, Sheeraz | Latif, Shahzad
Article Type: Research Article
Abstract: Facial expressions classification is a fast growing research area. Lots of contribution has been made in this area by researchers from fields of computer science, computer vision, artificial intelligence and psychology. There are many applications that use facial expression classification to identify the behavior, emotion, feelings and opinion of a person. Facial expression classification is not a trivial task as there are many factors that need to be accounted like low quality of images, noise, and shape/color of image. In this article, we have proposed an efficient facial expression classification scheme. In the first step, we perform some pre-processing steps …like face detection and histogram equalization inorder to reduce the data dimenions and normalize the illumination effects. Then, an efficient feature extraction technique is used to extract the relevant face features. In the last step, we train and test Support Vector Machine (SVM) classifier to classify the facial expressions. Emirical results obtained using the JAFFE database suggest that the proposed technique produces impressive results by utilzing the best facial features. Show more
Keywords: Facial expression recognition, feature extraction, support vector machine, JAFFE database
DOI: 10.3233/IFS-151567
Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2881-2887, 2015
Authors: Jeyanthi, S. | Uma Maheswari, N. | Venkatesh, R.
Article Type: Research Article
Abstract: Automatic Fingerprint Recognition System (AFRS) is getting advanced as major distinct in the field of Biometrics. There are a number of difficult issues that need to be addressed in order to develop the scope for AFRS. In this regard designing challenges are non linear distortion, low quality image, segmentation, sensor noise, skin conditions, overlapping, inter class similarity, intra class variations and template aging. In crime scenes, the latent images can be merged with some background images or more number of fingerprint images from same person or different person can be overlapped. During investigation several possibilities are them to acquire damaged …or un separated fingerprint image. The suspected criminals can’t be identified and recognized using such kind of images. In forensics, the matching accuracy of latent is extremely critical even if it involves some degree of manual intervention by latent examiners including manual markup. An overlapped fingerprint image must be able to split for fingerprint identification and recognition. This paper developed an algorithm to separate overlapping latent images. The proposed AFRS analyzes and design a fingerprint recognition system for overlapped latent images. The planned work is to formulate with accurate and fast data retrieval using one-to-N fingerprint identification for overlapped images. Extensive experiments are performed on the SLF databases, NIST SD27, FVC DB1, DB2 databases and evaluate rank-1 identification rate. The results show that the proposed system can separate overlapped fingerprint more accurately and robustly and it consequently improve the fingerprint recognition accuracy of AFRS. Show more
Keywords: One-to-N fingerprint identification, latent image, overlapped fingerprint image, AFRS, forensics
DOI: 10.3233/IFS-151583
Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2889-2899, 2015
Article Type: Other
Citation: Journal of Intelligent & Fuzzy Systems, vol. 28, no. 6, pp. 2901-2913, 2015
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