• IE interfaces
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• v.18 no.1
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• pp.82-87
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• 2005

Most of virtual reality systems ask users to control 3D objects or to navigate 3D world using 3D controllers. To maximize the human performance in the control, the design of virtual reality system and its input and output devices should be optimized. In this study, an experiment was designed to investigate the effects of three resolution factors of a virtual reality system on the human performance. Six subjects conducted the experiment for the factors; two frame rates, three spatial resolutions, and three pictorial contents. The result showed that the greater the spatial resolution was, the higher the human performance was. For the temporal resolution, fixed frame rate at 18 Hz was better than the varied maximized frame rate. For the pictorial contents, the virtual space with orientation cues marked the greatest performance than the other two conditions; the virtual space without any orientation cue and the virtual space like real world. These results could be applied for the design of virtual reality systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.86-93
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• 2012

This paper presents a new approach to solve the pursuit problem based on a univector field method. In our proposed method, a set of eight agents works together instantaneously to find suitable moving directions and follow the univector field to pursue and capture a prey agent by surrounding it from eight directions in an infinite grid-world. In addition, a set of strategies is proposed to make the pursuit problem more realistic in the real world environment. This is a general approach, and it can be extended for an environment that contains static or moving obstacles. Experimental results show that our proposed algorithm is effective for the pursuit problem.

• Transactions on Electrical and Electronic Materials
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• v.11 no.3
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• pp.106-111
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• 2010

The convergence of significantly different and disparate technologies such as spintronics, carbon nano tube field effect transistors, photon and bio-responsive molecular switches, memristor and memristive systems and metamaterials, coupled with energy scavenging sources are gaining a renewed focus in the quest for new products. This paper will provide an insight into an anticipated technological revolution and will highlight a futuristic Roadmap to capture opportunities that are brought about as the results of formulation of new circuit components basically driven by emergence of nanoscale materials as part of System on System integration. Challenges as the result of new lumped components such as memristor, metamaterial-based lumped components and the like that will challenge the designers' comfort zone will also be discussed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.241-248
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• 2004

Recent paradigm in technology shifts from object-based technology to environment-based technology. Issue here is interaction among humans and the world around humans. The world we consider includes natural and artificial "space." Interactive technology, which explore holistic interactions based on "Mom (embodiment)," suggests a good starting point for exploring this issue. Soft engineering, "Mom," holistic interactions, tangible space, ubiquitous computing, science of emotion, and interactive media are key concepts in interactive technology. Interactive tangible media "iT_Media" is proposed to explore and synthesize these ideas. Interactive technology initiative (ITI) is an interdisciplinary research group to search for the proper technology and the proper way of implementing technology: "interactive technology" or "soft engineering." Some experimental activities conducted by ITI are presented in this paper.tal activities conducted by ITI are presented in this paper.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.44-51
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• 2003

Knowledge acquisition is a bottleneck in knowledge-based system implementation. Decision tree induction is a useful machine learning approach for extracting classification knowledge from a set of training examples. Many real-world data contain fuzziness due to observation error, uncertainty, subjective judgement, and so on. To cope with this problem of real-world data, there have been some works on fuzzy classification rule learning. This paper makes a survey for the kinds of fuzzy classification rules. In addition, it presents a fuzzy classification rule learning method based on decision tree induction, and shows some experiment results for the method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.263-267
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• 2005

Building classifiers for financial real-world classification problems is often plagued by severely overlapping and highly skewed class distribution. New performance measures such as receiver operating characteristic (ROC) curve and area under ROC curve (AUC) have been recently introduced in evaluating and building classifiers for those kind of problems. They are, however, in-effective to evaluation of classifier's discrimination performance in a particular class of the classification problems that interests lie in only a local operating range of the classifier, In this paper, a new method is proposed that enables us to directly improve classifier's discrimination performance at a desired local operating range by defining and optimizing a partial area under ROC curve or domain-specific curve, which is difficult to achieve with conventional classification accuracy based learning methods. The effectiveness of the proposed approach is demonstrated in terms of fraud detection capability in a real-world fraud detection problem compared with the MSE-based approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.108-112
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• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.3
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• pp.17-26
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• 2013

We have developed an ideal functionality for security requirement of functional encryption schemes. The functionality is needed when we want to show the security of a functional encryption scheme in universal composable (UC) framework. A functionality $F_{fe}$ was developed to represent ideal respond of a functional encryption scheme against any polynomial time active attacker. We show that UC security notion of functional encryption scheme $F_{fe}$ is as strong as fully secure functional encryption in an indistinguishable game with chosen cipher text attack. The proof used a method that showing for any environment algorithm, it can not distinguish ideal world where the attacker play with ideal functionality $F_{fe}$ and real world where the attacker play a fully secure functional encryption scheme.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.216-220
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• 2007

Camera calibration in machine vision is the process of determining the intrinsic camera parameters and the three-dimensional (3D) position and orientation of the camera frame relative to a certain world coordinate system. On the other hand, Takagi-Sugeno-Kang (TSK) fuzzy system is a very popular fuzzy system and approximates any nonlinear function to arbitrary accuracy with only a small number of fuzzy rules. It demonstrates not only nonlinear behavior but also transparent structure. In this paper, we present a novel and simple technique for camera calibration for machine vision using TSK fuzzy model. The proposed method divides the world into some regions according to camera view and uses the clustered 3D geometric knowledge. TSK fuzzy system is employed to estimate the camera parameters by combining partial information into complete 3D information. The experiments are performed to verify the proposed camera calibration.

• Advances in Energy Research
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• v.3 no.2
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• pp.71-80
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• 2015

This paper describes nuclear energy technologies for the solution of long term energy problem with better reliability. A short overview about nuclear energy applications are explained with a basic analysis of energy. Furthermore, industrial application, space application of nuclear systems and ship propulsion in nuclear energy application are demonstrated in more detail. This report also includes some examples of the experienced nuclear power plant to identify energy production. The general purpose of the article is to understand how efficiently nuclear systems generates energy, and solve the world's increasing energy demand in our century.