• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.62-66
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• 2017

In this paper, we present the development of communication and data processing strategy for the electromagnetic wave precipitation gauge system. The electromagnetic wave precipitation gauge system is a small system for deriving area rainfall rates within 1 km radius through dual polarization radar observation at 24GHz band. It is necessary to take consider for measurement of accurate precipitation under limited computing resources originating from small systems and to minimize the use of network for the unattended operation and remote management. To overcome computational resource limitations, we adopted the fuzzy logic for quality control to eliminate non-precipitation echoes and developed the method by weighted synthesis of various rain rate fields using multiple radar QPE formulas. Also we have designed variable data packets rules to minimize the network traffic.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.2
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• pp.102-110
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• 2015

The main source of noise in computed tomography (CT) images is a quantum noise, which results from statistical fluctuations of X-ray quanta reaching the detector. This paper proposes a neural network (NN) based hybrid filter for removing quantum noise. The proposed filter consists of bilateral filters (BFs), a single or multiple neural edge enhancer(s) (NEE), and a neural filter (NF) to combine them. The BFs take into account the difference in value from the neighbors, to preserve edges while smoothing. The NEE is used to clearly enhance the desired edges from noisy images. The NF acts like a fusion operator, and attempts to construct an enhanced output image. Several measurements are used to evaluate the image quality, like the root mean square error (RMSE), the improvement in signal to noise ratio (ISNR), the standard deviation ratio (MSR), and the contrast to noise ratio (CNR). Also, the modulation transfer function (MTF) is used as a means of determining how well the edge structure is preserved. In terms of all those measurements and means, the proposed filter shows better performance than the guided filter, and the nonlocal means (NLM) filter. In addition, there is no severe restriction to select the number of inputs for the fusion operator differently from the neuro-fuzzy system. Therefore, without concerning too much about the filter selection for fusion, one could apply the proposed hybrid filter to various images with different modalities, once the corresponding noise characteristics are explored.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.605-613
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• 2013

This research proposes a vibration pattern algorithm to implement the haptic joystick to control a mobile robot at the remote site without watching the navigation environment. When the user cannot watch the navigation environment of the mobile robot, the user may rely on the haptic joystick solely to avoid obstacles and to guide the mobile robot to the target. To generate vibration patterns, there is a vibration motor at the bottom of the joystick which is held by the user to control the motion direction of the mobile robot remotely. When the mobile robot approaches to an obstacle, a pattern of vibration is generated by the motor, and by feeling the vibration pattern which is determined by the relative position of the mobile robot to the obstacle, the user can move the joystick to avoid the collision to the obstacle for the mobile robot. To generate the vibration patterns to convey the relative location of the obstacle near the mobile robot to the user, Fuzzy interferences have been utilized. To measure the distance and location of the obstacle near the mobile robot, ultrasonic sensors with the ring structure have been adopted and they are attached at the front and back sides of the mobile robot. The precise location of the obstacle is obtained by fusing the multiple data from ultrasonic sensors. Effectiveness of the proposed algorithm has been verified through the real experiments and the results are demonstrated.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1642_1643
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• 2009

일반적으로, 퍼지 예측 시스템의 성능은 데이터의 특성과 퍼지 집합을 생성하기 위한 클러스터일 기법에 매우 의존적이다. 하지만, 예측을 위한 시계열 데이터들은 자연현상에 기인하는 강한 비선형적 특성을 가지고 있으므로 적합한 시스템을 구현하는 것에 많은 제약이 따른다. 따라서 본 논문에서는 시계열의 비선형적 특성을 적절히 취급하기 위하여, 그들로부터 생성 가능한 차분 데이터 중, 유효한 차분데이터를 이용하여 다중 모델 퍼지 예측 시스템을 구현함으로써, 보다 우수한 예측이 가능하도록 하였으며, 퍼지 시스템의 모델링에는 교차 상관분석기법에 따른 계층적 구조의 클러스터링 기법 (Hierarchical Cross-correlation and K-means Clustering Algorithms: HCKA)을 적용하여, 시스템을 위한 규칙기반의 적합성을 높일 수 있도록 하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.229-237
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• 2011

As smart phones have become widely adopted, they have brought about changes in individual lifestyles, as well as significant changes in the industry. As the mobile technology of smart phones has become associated with all areas of industry, it is not only accelerating innovation in other industries such as shopping, healthcare service, education, and finance, but is also creating new markets and business opportunities. The preparation of thorough security measures for smart phones is increasing in demand. While offering excellent mobility and convenience, smart phones can be exposed to a range of violation threats. In particular, it is necessary to make efforts to develop a security system that can preemptively cope with potential security threats in the banking service area, which requires a high level of reliability. This paper suggests a security reference model that is considered for the smart phone-based joint mobile banking development project being undertaken by the Bank of Korea in 2010. The purpose of this study is to make a security reference model for a reliable smart phone-based mobile financial service, by recognizing the specific security threats directed toward smart phones, and providing countermeasures to these security threats. The proposed mobile banking security reference model is useful in improving system security by systematically analyzing information security threats to the mobile financial service, and by presenting the guideline for the preparation of countermeasures.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.5-8
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• 2003

This paper presents a methodology to be able to select an appropriate RP system that suits the end use of a part. Evaluation factors used in process selection include major attributes such as accuracy, roughness, strength, elongation, part cost and build time that greatly affect the performance of RP systems. Crisp values such as accuracy and surface roughness are obtained with a new test part developed. The test part is designed with conjoint analysis to reflect users' preference. The part cost and build time that have approximate ranges due to cost and many variable parameters are presented by linguistic values that can be described with triangular fuzzy numbers. Based on the evaluation values obtained, an appropriate RP process for a specific part application is selected by using the modified TOPSIS(Technique of Order Preference by Similarity to Ideal Solution) method. It uses crisp data as well as linguistic variables, and each weight on the alternatives is assigned by using pair-wise comparison matrix. The ranking order helps the decision making of the selection of RP systems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.165-171
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• 2004

Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.3
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• pp.322-326
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• 2004

This paper describes a new iris recognition method based on a shift-invariant wavelet sub-images. For the feature representation, we first preprocess an iris image for the compensation of the variation of the iris and for the easy implementation of the wavelet transform. Then, we decompose the preprocessed iris image into multiple subband images using a shift-invariant wavelet transform. For feature representation, we select a set of subband images, which have rich information for the classification of various iris patterns and robust to noises. In order to reduce the size of the feature vector, we quantize. each pixel of subband images using the Lloyd-Max quantization method Each feature element is represented by one of quantization levels, and a set of these feature element is the feature vector. When the quantization is very coarse, the quantized level does not have much information about the image pixel value. Therefore, we define a new similarity measure based on mutual information between two features. With this similarity measure, the size of the feature vector can be reduced without much degradation of performance. Experimentally, we show that the proposed method produced superb performance in iris recognition.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.249-254
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• 2009

The today's decision making tasks in globalized business and manufacturing become more complex, and ill-defined, and typically multiaspect or multi-discipline due to many influencing factors. The requirement of obtaining fast and reliable decision solutions further complicates the task. Intelligent decision support system (DSS) currently exhibit wide spread applications in business and manufacturing because of its ability to treat ill-structuredness and vagueness associated with complex decision making problems. For multi-dimensional decision problems, generally an optimum single DSS can be developed. However, with an increasing number of influencing dimensions, increasing number of their factors and relationships, complexity of such a system exponentially grows. As a result, software development and maintenance of an optimum DSS becomes cumbersome and is often practically unfeasible for real situations. This paper presents a technically feasible approximation of an optimum DSS through decreasing its complexity by a modular structure. It consists of multiple DSSs, each of which contains the homogenous knowledge's, decision making tools and possibly expertise's pertaining to a certain decision making dimension. Simple, efficient and practical integration mechanism is introduced for integrating the individual DSSs within the proposed overall DSS architecture.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.198-204
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• 2007

In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.