• Journal of the Korean housing association
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• v.21 no.3
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• pp.115-124
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• 2010

The environment which has been destroyed for the national growth since 1960's would seem to offer infinite resources to human, but now, the existence of human being is threatened by the development thoughtless for the environment. The World Powers have concentrated on green growth with eco-friendly resource since the end of 20th century. Korea suggested that the vision was the low carbon for green growth in 2008. It is necessary to supply Long-Life Housing in the green technology in terms of the sustainable housing development based on various life style, life cycle of the residences, the restrain remodeling and redevelopment in construction. This study is aim to establish the development of maintenance process to make continuous inhabitation of Long-Life Housing that has the separated SI for maintenance, durability, variability and remodeling. The maintenance for Long-Life Housing is very important to have more than 50~70 years the long term of life cycle in comparison with Housing. Also, the roles of manager and user are important parts in Long-Life Housing. The present maintenance for Housing is shift and repair works by the routine maintenance and demage. However, The maintenance for Long-Life Housing should consider movement and flexibility. In addition, Long-Life Housing requires the proper process of maintenance because it is different from Housing in housing concept, design and constructions stage. Therefore this study shows the efficient maintenance process for Long-Life Housing.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.30-39
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• 2012

An effective drowsy driver detection system is needed, because the probability of accident is high for drowsy driving and its severity is high at the time of accident. However, the drowsy driver detection system that uses bio-signals or vision is difficult to be utilized due to high cost. Thus, this paper proposes a drowsy driver detection algorithm by using steering angle sensor, which is attached to the most of vehicles at no additional cost, and vehicle information such as brake switch, throttle position signal, and vehicle speed. The proposed algorithm is based on jerk criterion, which is one of drowsy driver's steering patterns. In this paper, threshold value of each variable is presented and the proposed algorithm is evaluated by using acquired vehicle data from hardware in the loop simulation (HILS) through CAN communication and MATLAB program.

• Journal of IKEEE
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• v.14 no.3
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• pp.224-231
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• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.

• Spatial Information Research
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• v.21 no.5
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• pp.63-72
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• 2013

This paper analyzed the flood propagation characteristics of each flood elevation due to failure of embankment in Muju Namdae Stream using recursive call algorithm. A flood propagation order by the flood elevation was estimated by setting destruction point at Beonggu and Chasan small dam through recursive call algorithm and then, the number of grids of each flood propagation order and accumulated inundation area were calculated. Based on the flood propagation order and the grid size of DEM, flood propagation time could be predicted each flood elevation. As a result, the study could identify the process of flood propagation through distribution characteristic of the flood propagation order obtained from recursive call algorithm, and could provide basic data for protection from flood disaster by selecting the flood vulnerable area through the gradient pattern of the graph for accumulated inundation area each flood propagation order. In addition, the prediction of the flood propagation time for each flood water level using this algorithm helped provide valuable information to calculate the evacuation path and time during the flood season by predicting the flood propagation time of each flood water level.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.79-88
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• 1999

In this paper we address the tracking method which tracks only target object in image sequence including moving object. We use a contour tracking algorithm based on intensity and motion boundaries. The motion of the moving object contour in the image is assumed to be well describable by an affine motion model with a translation, a change in scale and a rotation. The moving object contour is represented by B-spline, the position and motion of which is estimated along the image sequence. we use pattern recognition to identify target object. In order to use linear Kalman Filters we decompose the estimation process into two filters. One is estimating the affine motion parameters and the other the shape of moving object contour. In some experiments with dial plate we show that this method enables us to obtain the robust motion estimates and tracking trajectories even in case of including obstructive object.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.66-73
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• 2006

Safety is the most important for all traffic management and control technology. This paper focuses on developing a flexible, reliable and real-time processing algorithm which is able to generate signal for the entering vehicle at the joining road through a camera and image processing technique. The images obtained from the camera located beside and upon the road can be used for traffic surveillance, the vehicle's travel speed measurement, predicted arriving time in joining area between main road and joining road. And the proposed algorithm displays the confluence safety signal with red, blue and yellow color sign. The three methods are used to detect the vehicle which is driving in setted detecting area. The first method is the gray scale normalized correlation algorithm, and the second is the edge magnitude ratio changing algorithm, and the third is the average intensity changing algorithm The real-time prototype confluence safety signal generation algorithm is implemented on stored digital image sequences of real traffic state and a program with good experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.322-327
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• 2007

Researchers in the field of psychology used Electroencephalographic (EEG) to record activities of human brain lot many years. As technology develope, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study emotion recognition method which uses one of physiological signals and gestures in the existing research. In this paper, we use together physiological signals and gestures for emotion recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both physiological signals and gestures gets high recognition rates better than using physiological signals or gestures. Both physiological signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on a reinforcement learning.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.569-580
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• 2008

Web services are the current most promising technology for service oriented architecture(SOA) implementations. However, in spite of the large scale acceptance of web services, they have been relegated to internal integration projects, and the grand vision of virtual enterprises where partners can be integrated on demand is yet to be realized. The main reason is that the current standards of web services are not very suitable for the dynamic web service discovery and integration. In this paper, we present a novel SemanticBPEL solution that merges the benefit of WS-BPEL, with the advantage of OWL-S for building a semi-automatic web service composition system. In particular, this work proposes a multi-phase search method for solving dynamic discovery and integration problems of web services. The proposed method is compared with the existing keyword based retrieval method. These comparisons show that our approach outperforms the existing method.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.95-102
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• 2013

The paradigm of SW industry has been rapidly changing into mobile and cloud technology environment. Research model based on PEST-SWOT analysis was employed to derive internal and external factors connected with PEST factors through analyzing the current status and problems of SW HRD system in Korea. Survey was conducted by 20 experts who are involved in SW companies, university, and R&D research institute using AHP(Analytic Hierarchy Process) model. The empirical result showed that SW fusion HRD, creativity-oriented university education in the field of software, global education and exchange, and revitalization of SW venture ecosystem are derived as policy visions of SW HRD for smart industry ecosystem. Another findings are that SW fusion HRD, revitalization of SW venture ecosystem, Job Creation through revitalization of SW start-up, Creation of coexistence between SW large enterprises and SMEs, creativity-oriented university education in the field of software, and global education and exchange are presented in order in terms of the importance of policy priority.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.219-230
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• 2017

This paper proposes a vehicle to road tracking algorithm based on vision sensor by using EKF(Extended Kalman Filter). The lateral offset, heading angle, and curvature which are obtained from vehicle to road tracking might be used as inputs to steering controller of LKAS(Lane Keeping Assist System) or for the warning decision logic of LDWS(Lane Departure Warning System). To the end, in this paper, the yaw rate, steering angle, and vehicle speed as well as lane raw points together with considering of vehicle lateral dynamics are utilized to improve the exactness and convergence of the vehicle to road tracking. The proposed algorithm has been tested at a proving ground that consists of straight and curve sections and compared with GPS datum using DGPS-RTK equipment to show the feasibility of the proposed algorithm.