• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.390-395
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• 2012

This paper describes an implementation of automatic mutual localization of swarm robots using a particle filter. Each robot determines the location of the other robots using wireless sensors. The measured data will be used for determination of the movement method of the robot itself. It also affects the other robots' self-arrangement into formations such as circles and lines. We discuss the problem of a circle formation enclosing a target that moves. This method is the solution for enclosing an invader in a circle formation based on mutual localization of the multi-robot without infrastructure. We use trilateration, which does require knowing the value of the coordinates of the reference points. Therefore, specifying the enclosure point based on the number of robots and their relative positions in the coordinate system. A particle filter is used to improve the accuracy of the robot's location. The particle filter is operates better for mutual location of robots than any other estimation algorithms. Through the experiments, we show that the proposed scheme is stable and works well in real environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.298-303
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• 2010

robots determine the location of the other robot using wireless sensors. Use it to decide how to move his. And go to any location, will make shape of column and line, circle. In this paper, we discuss problem in circle formation enclosing target which moves. It is method about enclosed invader in circle formation based on mutual localization of swarm robot without infrastructure. Therefore, use trilateration that do not need to know the value of the coordinates of reference points. So, Specify enclosed point for the number of robots base on between the relative position of the robot in the coordinate system. And particle filter is proposed to improve the accuracy of the location.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.438-449
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• 2005

In this paper, we describes the information-theoretic approaches to sensor selection and sensor placement in sensor net­works for target localization and tracking. We have developed a sensor selection heuristic to activate the most informative candidate sensor for collaborative target localization and tracking. The fusion of the observation by the selected sensor with the prior target location distribution yields nearly the greatest reduction of the entropy of the expected posterior target location distribution. Our sensor selection heuristic is computationally less complex and thus more suitable to sensor networks with moderate computing power than the mutual information sensor selection criteria. We have also developed a method to compute the posterior target location distribution with the minimum entropy that could be achieved by the fusion of observations of the sensor network with a given deployment geometry. We have found that the covariance matrix of the posterior target location distribution with the minimum entropy is consistent with the Cramer-Rao lower bound (CRB) of the target location estimate. Using the minimum entropy of the posterior target location distribution, we have characterized the effect of the sensor placement geometry on the localization accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1493-1504
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• 2010

The localization service which provides the location information of mobile user, is one of important service provided by sensor network. Many methods to obtain the location information of mobile user have been proposed. However, these methods were developed for only one mobile user so that it is hard to extend for multiple mobile users. If multiple mobile users start the localization process concurrently, there could be interference of beacon or ultrasound that each mobile user transmits. In the paper, we propose LME, the localization technique for multiple mobile nodes in mobile wireless sensor networks. In LME, collision of localization between sensor nodes is prevented by forcing the mobile node to get the permission of localization from anchor nodes. For this, we use CTS packet type for localization initiation by mobile node and RTS packet type for localization grant by anchor node. NTS packet type is uevento reject localization by anchor node for interference avoidance.nghe experimental result shows that the number of interference between nodes are increased in proportion to the number of mobile nodes and LME provides efficient localization.

• Composites Research
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• v.29 no.1
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• pp.1-6
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• 2016

Low-speed impact was localized on a stiffened composite structure, using 4 FBG sensors with 100 kHz-sampling rate interrogator and devised localization algorithm. The composite specimen consists of a main spar and several stringers, and the overall size of the specimen's surface is about $0.8{\times}1.2m$. Pre-stored reference data for 247 grid locations and 36 stiffener locations are gathered and used as comparison target for a random impact signal. The proposed algorithm uses the normalized cross-correlation method to compare the similarities of the two signals; the correlation results for each sensor's signal are multiplied by others, enabling mutual compensation. 20 verification points were successfully localized with a maximum error of 43.4 mm and an average error of 17.0 mm. For the same experimental setup, the performance of the proposed method is evaluated by reducing the number of sensors. It is revealed that the mutual compensation between the sensors is most effective in the case of a two sensor combination. For the sensor combination of FBG #1 and #2, the maximum localization error was 42.5 mm, with average error of 17.4 mm.

• Journal of the Economic Geographical Society of Korea
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• v.6 no.1
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• pp.99-117
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• 2003

Major proposes of this study are to analyze Korean Shipbuilding's production network and cooperation between related firms and to understand their spatial features. The Geographical study about networks has focused on automobiles, electronics or communications industries. That's because those industries have distinctive spatial features thanks to the full growth of subcontract structures. The labor-centered, capital-centered shipbuilding industry, differently from other manufacturing industries, has production networks where outside trades are common. Today internet based communication is being reinforced and the flexibility of purchase circumstances is being positively proceeded. The central axes of the production network of Sumsung shipbuilding are internationally Europe and Asian area, nationally Busan and Gyeongnam province and Seoul Metropolitan areas, locally inside subcontracting firms. And In order to construct mutual trust with cooperation firms, Sumsung shipbuilding is trying to reinforce two-way cooperation relation through 'SungJoHoi' organized with outside subcontracting firms and 'inside cooperation firms conference'. In conclusion, Sumsung shipbuilding is trying to strengthen the competitiveness of shipbuilding industry, spatially by setting up the network through globalization-localization and functionally by constructing the partnership production network for mutual communication.

• Journal of Navigation and Port Research
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• v.27 no.2
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• pp.145-153
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• 2003

The presence-feeling enhancement method of a Virtual Reality (VR) simulator is proposed in this paper. The method is to increase realistic human feeling by mutual synergy effect between stereoscopic image and three-dimensional (3D) sound. In order to test the influence of mutual synergy effect, subject assessment with five university students is carried out using VR ship simulator having PC monitor and LCD shutter glasses. It I found that the averaged scale value of image naturalness is increased by 0.5 from $I_{nat}$=3.1 to 3.6 when blending stereoscopic images with 3D sound, and the averaged score value of sound localization is increased by 10% from $A_{SL}$ = 70~75% to $A_{SL}$ = 80~85% when blending 3D sound with stereoscopic image. In conclusion, the results show that the proposed method is able to increase the presence feeling in the VR simulator.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2243-2250
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• 2014

In wireless sensor networks(WSNs), geographical routing algorithms can enhance the network capacity. However, in real WSNs, it is difficult for each node to know its physical location accurately. Especially, indoor environments contain various obstacles such as concrete wall, furniture which cause non-line-of-sight(NLOS) conditions. To solve the problem, we propose location error compensation algorithm by using two difference topology constructions. First topology is based on mobile node's location which is obtained from anchor nodes. Second topology is based on mutual distance from neighbor nodes. The proposed algorithm efficiently detects and corrects the location errors and significantly enhances the network performance of geographic routing in the presence of location errors.

• BMB Reports
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• v.46 no.6
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• pp.289-294
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• 2013

To maintain cellular homeostasis against the demands of the extracellular environment, a precise regulation of kinases and phosphatases is essential. In cell cycle regulation mechanisms, activation of the cyclin-dependent kinase (CDK1) and cyclin B complex (CDK1:cyclin B) causes a remarkable change in protein phosphorylation. Activation of CDK1:cyclin B is regulated by two auto-amplification loops-CDK1:cyclin B activates Cdc25, its own activating phosphatase, and inhibits Wee1, its own inhibiting kinase. Recent biological evidence has revealed that the inhibition of its counteracting phosphatase activity also occurs, and it is parallel to CDK1:cyclin B activation during mitosis. Phosphatase regulation of mitotic kinases and their substrates is essential to ensure that the progression of the cell cycle is ordered. Outlining how the mutual control of kinases and phosphatases governs the localization and timing of cell division will give us a new understanding about cell cycle regulation.

• Computers and Concrete
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• v.32 no.6
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• pp.615-623
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• 2023

Crack detection is an essential method to ensure the safety of dam concrete structures. Low-quality crack images of dam concrete structures limit the application of neural network methods in crack detection. This research proposes a modified attentional mechanism model to reduce the disturbance caused by uneven light, shadow, and water spots in crack images. Also, the focal loss function solves the small ratio of crack information. The dataset collects from the network, laboratory and actual inspection dataset of dam concrete structures. This research proposes a novel method for crack detection of dam concrete structures based on the U-Net neural network, namely AF-UNet. A mutual comparison of OTSU, Canny, region growing, DeepLab V3+, SegFormer, U-Net, and AF-UNet (proposed) verified the detection accuracy. A binocular camera detects cracks in the experimental scene. The smallest measurement width of the system is 0.27 mm. The potential goal is to achieve real-time detection and localization of cracks in dam concrete structures.