• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.264-272
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• 1998

This paper proposes a fault detection and recovery mechanism for a fault-tolerant Mini-MAP system, and provides detailed techniques for its implementation. This paper considers the fault-tolerant Mini-MAP system which has dual layer structure from the LLC sublayer down to the physical layer to cope with the faults of those layers. For a good fault detection, a redundant and hierarchical fault supervision architecture is proposed and its implementation technique for a stable detection operation is provided. Information for the fault location is provided from data reported with a fault detection and obtained by an additional network diagnosis. The faults are recovered by the stand-by sparing method applied for a dual network composed of two equivalent networks. A network switch mechanism is proposed to achieve a reliable and stable network function. A fault-tolerant Mini-MAP system is implemented by applying the proposed fault detection and recovery mechanism.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.5
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• pp.115-121
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• 1996

Recently, the Z-Map model has been used widely to represent the three dimensional geometric shape and to achieve the cross-section and point evaluation of the shape. In this paper, the CNC cutting planning and simulation modules for product with three dimensional geometric shape are realized based on the Z-Map model. The realized system has the various capabilities related to the automatic generation of tool path for the rough and finish cutting processes, the automatic elimination of overcut, the automatic generation of CNC program for a machining center and the cutting simulation. Especially, the overcut-free tool path is obtained by using the CL Z-Map models which are composed of the offset surfaces of the geometric shape of product.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3302-3307
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• 2009

The objective of the present study lies in providing the method to construct the precision population-statistical map for statistical demographics making full advantage of GIS and the national census data in an attempt to improve accuracy and reliability of population estimation applicable for a variety of location analysis. More specifically, it adopts the multiple regression analysis by segmented land use type(biotope) taking into account that the land use diversified as residence, commercial and office areas has the close connectivity and interdependence with population. Based on the analyzed result above, the study finalizes the modeling to construct demographic map with higher precision by prioritizing the population density by weight value and then re-distributing the population according to jurisdictional dong's and types of use for the land. The study consequently is expected to be conducive to improving precision and reliability rather than the existing method for population estimation widely acceptable thus far.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.909-914
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• 2011

In these days, according to the enhancement of the mobile communication technologies, location based services using the location and movements are vitalized. In this paper, we develop a private vehicle tracking system for garbage truck operation management using GPS and CDMA communication and Open map interface. The terminal equipment attached in vehicle receives the GPS signals and detect the position data including time, longitude, latitude, and altitude. And the terminal sends these data to the server PC through CDMA cellular network in fixed period. The server saves these data into database to process in map server program with which we can view real-time trace of moving vehicle. We apply our system to public garbage truck managing operation and we can increase operation efficiency by examine real-time working and moving path and by present reasonable operation rout.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3030-3038
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• 2023

Nowadays, mobile robots have been used to search for uncontrolled radioactive source in indoor environments to avoid radiation exposure for technicians. However, in the indoor environments, especially in the presence of obstacles, how to make the robots with limited sensing capabilities automatically search for the radioactive source remains a major challenge. Also, the source search efficiency of robots needs to be further improved to meet practical scenarios such as limited exploration time. This paper proposes an automatic source search strategy, abbreviated as ACA: the location of source is estimated by a convolutional neural network (CNN), and the path is planned by the A-star algorithm. First, the search area is represented as an occupancy grid map. Then, the radiation dose distribution of the radioactive source in the occupancy grid map is obtained by Monte Carlo (MC) method simulation, and multiple sets of radiation data are collected through the eight neighborhood self-avoiding random walk (ENSAW) algorithm as the radiation data set. Further, the radiation data set is fed into the designed CNN architecture to train the network model in advance. When the searcher enters the search area where the radioactive source exists, the location of source is estimated by the network model and the search path is planned by the A-star algorithm, and this process is iterated continuously until the searcher reaches the location of radioactive source. The experimental results show that the average number of radiometric measurements and the average number of moving steps of the ACA algorithm are only 2.1% and 33.2% of those of the gradient search (GS) algorithm in the indoor environment without obstacles. In the indoor environment shielded by concrete walls, the GS algorithm fails to search for the source, while the ACA algorithm successfully searches for the source with fewer moving steps and sparse radiometric data.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.49-56
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• 2023

This study proposed a damage location estimation method for automated image-based port infrastructure inspection. Memory efficiency was improved by calculating the homography matrix using feature detection technology and outlier removal technology, without going through the 3D modeling process and storing only damage information. To develop an algorithm specialized for port infrastructure, the algorithm was optimized through ground-truth coordinate pairs created using images of port infrastructure. The location errors obtained by applying this to the sample and concrete wall were (X: 6.5cm, Y: 1.3cm) and (X: 12.7cm, Y: 6.4cm), respectively. In addition, by applying the algorithm to the concrete wall and displaying it in the form of an exterior damage map, the possibility of field application was demonstrated.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.181-186
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• 2017

Child crimes such as child abduction and lost children(MIA) have long been pointed out as social problems. However, there are few ways to solve these problems. According to MIA statistics, about 3,000 babies are lost each year. This paper presents a study on prevention of lost children ratio using mobile LBS in order to reduce the incidence of lost children ratio in dense space. First, we input the personal information of the child and the contact information of the parent. Second, we use the Google Maps API to get the location (parent's location, child's location) information. Third, the personal information of the child and the parent is indicated in the obtained location information. In future research, based on SNS, we will carry out research on sending child location information and parent location information via SMS. It is expected that the prevention system of lost child using LBS and SNS will make a great contribution to reduce the lost children ratio in the ubiquitous society.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1121-1135
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• 2005

This paper proposes a moving object extraction method using the contrast map and salient points. In order to make the contrast map, we generate three-feature maps such as luminance map, color map and directional map and extract salient points from an image. By using these features, we can decide the Attention Window(AW) location easily The purpose of the AW is to remove the useless regions in the image such as background as well as to reduce the amount of image processing. To create the exact location and flexible size of the AW, we use motion feature instead of pre-assumptions or heuristic parameters. After determining of the AW, we find the difference of edge to inner area from the AW. Then, we can extract horizontal candidate region and vortical candidate region. After finding both horizontal and vertical candidates, intersection regions through logical AND operation are further processed by morphological operations. The proposed algorithm has been applied to many video sequences which have static background like surveillance type of video sequences. The moving object was quite well segmented with accurate boundaries.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.2
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• pp.281-286
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• 2017

SNS is a platformwhere users build a social relationship and share opinions and informations. To do these, it supports a text, an image and a video data. As it is possible to exploit the location data of a smart device, SNS tries to use the location data. However,since SNS does not support the coordinate data, it provides the restricted function sharing the image map instead of the vector map. In this paper, we propose a chatting systemsharing pathsto support the coordinate data on a classical SNS. On the proposed system, it is possible for usersjoined in a roomto watch a vector map of same area and exchange texts. If a user builds a path on the map, the system propagates the coordinate data of the generated path and the other users joined in the room watch the path immediately. The implemented chatting systemhasthe benefit to share the information related a map between users using coordinate data.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.249-257
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• 2017

This paper proposes a method to segment urban scenes semantically based on location prior information. Since major scene elements in urban environments such as roads, buildings, and vehicles are often located at specific locations, using the location prior information of these elements can improve the segmentation performance. The location priors are defined in special 2D coordinates, referred to as road-normal coordinates, which are perpendicular to the orientation of the road. With the help of depth information to each element, all the possible pixels in the image are projected into these coordinates and the learned prior information is applied to those pixels. The proposed location prior can be modeled by defining a unary potential of a conditional random field (CRF) as a sum of two sub-potentials: an appearance feature-based potential and a location potential. The proposed method was validated using publicly available KITTI dataset, which has urban images and corresponding 3D depth measurements.