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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: Zaki, M. | Abulwafa, M.M.
Article Type: Research Article
Abstract: In this work, we present effective methods for detecting and representing invariant features of three dimensional (3-D) objects from single images. Our methods are independent of the viewpoint position, and can be used in the recognition process of 3-D objects. The invariant features are; shapes of the object surfaces, organization of the surfaces within the object, and the new feature which is shapes of privileged surfaces (PS) of the object. Also we explain the way these …features are represented and matched against stored model of the object. Our work is built around the knowledge based approach and depends on the fact that while it is true that the appearance of a 3-D object may change completely as it is viewed from different viewpoints, it is also true that many aspects of the object projection remain invariant over large ranges of viewpoints. This approach is different from the other approach that derives or calculates depth information and orientations of surfaces using more than one image of the object, or the approach that statistically detects and matchs the object features. The main contribution of our work is the introduction of privileged surface of 3-D object which plays an important role in the recognition process. Also we introduce heuristic methods for detecting shapes of surfaces, object organization, object & model representations and matching. The idea of matching privileged surfaces reduces the ambiguity that may arise due to limited visibility of the object surfaces (existence of hidden surfaces) when matching features of both the image and the model. Also matching privileged surfaces reduces the need of detecting and matching orientations of surfaces. This approach has been applied to 3-D objects which are bounded by planar surfaces. However, the work can be extended in a straightforward manner to support 3-D objects that are bounded by curved surfaces. Show more
Keywords: object recognition, vision system, image representation, model representation, matching techniques, privileged surface, surface shape, object organization
Citation: Journal of Intelligent & Fuzzy Systems, vol. 12, no. 2, pp. 79-95, 2002
Authors: Pinzolas, Miguel | Astrain, José J. | de Mendívil, José R. González | Villadangos, Jesús
Article Type: Research Article
Abstract: A neuro-fuzzy system for isolated hand-written digit recognition using a similarity fuzzy measure is presented. The system is composed of two main blocks: a first block that normalises the input and compares it with a set of fuzzy patterns, and a second block with a multilayer perceptron (MLP) to perform the definitive classification. The comparison with the fuzzy patterns is carried out via a fuzzy similarity measure that uses the Yager parametric norms and co-norms. Along …this work, several values of the parameter have been studied, in order to obtain the optimum. The simplicity of the method makes it extremely quick. Recognition accuracy of the method is about 90% single classification, and close to 97,5% classification scheme. Show more
Keywords: hand-written digit recognition, fuzzy systems, neural networks
Citation: Journal of Intelligent & Fuzzy Systems, vol. 12, no. 2, pp. 97-105, 2002
Authors: Jolly-Desodt, A.M. | Jolly, D. | Wawak, F.
Article Type: Research Article
Abstract: This paper presents a decision support system and its interface, both based on fuzzy and possibility theories, intended for man-machine systems and that has been realized for a teleoperation system. The kinds of assistance useful to the human operator in man-machine systems are first reviewed: this stresses the contribution of a decision support system in such an organization. The necessity to enclose a specific man-machine interface presenting that aid is showed. Then, the steps of the …decision support system design are investigated: due to the context of man machine systems, the efficiency of the Fuzzy and Possibility Theories to modelise the aid is obvious. Finally, the application realized dedicated to the teleoperation field is handled, but the strength of this system is its ability to apply to all man machine systems. Show more
Citation: Journal of Intelligent & Fuzzy Systems, vol. 12, no. 2, pp. 107-117, 2002
Authors: Wu, Q. | Sepehri, N. | He, S.
Article Type: Research Article
Abstract: This paper presents a novel application of multilayer neural networks for online control of a class of base-excited inverted pendulums. The pendulum has two degrees of rotational freedom and its base-point moves freely in three-dimensional space. The goal is to apply control torques to keep the pendulum in a desired orientation, in spite of disturbing base-point movement. Four three-layered neural networks are trained online to represent the inverse dynamics of the plant within a controller. The …conditions of training accuracy, to guarantee the stability of such a non-autonomous closed-loop system, are established using Lyapunov stability theory. The proposed neural controller is examined through simulations. Its performance is also compared with the performance of a Lyapunov controller from the most recent published work. It is shown that the proposed control scheme is simple in implementation in the sense that it does not require a mathematical model of the target pendulum or the measurement of the base-point movement. At the same time, it produces fast, yet well-damped responses with smooth control torques. The work presented here can benefit practical problems such as the study of stable locomotion of the human upper-body and bipedal robots. Show more
Citation: Journal of Intelligent & Fuzzy Systems, vol. 12, no. 2, pp. 119-131, 2002
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