• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.614-617
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• 2003

Recently the demand of constructing high-rised building grows larger. So it becomes more important to make an exact plan of a tower cranes which has an important position in high-rised building construction. Nevertheless businessmen of construction sites only depend on a great store of experience without a clear process of locating tower cranes. The object of this study is to set up the process model for locating tower cranes. The study went off through a study of related documents, an interview with some experts and a visiting of job sites. In result the study suggests a process model which has four steps of considering an establishing, disjointing, a radius of working, easy working. Case study was examined to estimate the feasibility and applicability of the proposed model. As a result, the model is proven to be a method to locate tower cranes quickly and cleary, and to operate properly as a decision-making tool.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.8
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• pp.663-673
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• 2013

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalization of LBS is the accurate estimating position for mobile object. Focusing on IMU deployed in smart phone, we develop a hybrid positioning estimation framework with a combination of WPS. The developed approaches can strengthen the advantages of independent indoor applicability of IMU. The estimation of IMU is efficiently compensated by radio fingerprint based Wi-Fi Positioning System. We put a focus especially on the hybrid algorithmic framework. Compared on the existing approaches of WPS or IMU, we achieve the comparable higher performance on both of average error of estimation and deviation of errors. Furthermore test-bed based on smart phone platform is practically developed and all data have been harvested from the actual measurement of test indoor area. This can approve the practical usefulness of proposed framework.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.649-656
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• 2012

The Global Positioning System (GPS) is widely utilized for commercial and military applications to estimate the location of the user or object. The GPS suffers from various intentional or unintentional interferers and it requires estimating the accurate angle-of-arrival (AOA) of the GPS signal to suppress interference signals and to efficiently detect GPS data. Since the power of GPS signal is very low comparing with the noise and interference signals, it is extremely difficult to estimate GPS AOA before despreading. Although AOA of GPS signal is usually estimated after despreading, it requires choosing the GPS AOA among results of AOA estimation because they include AOAs of interference and GPS signals when existing high-power interferers. In this paper, we propose the efficient choosing algorithm of the GPS signal among the estimated AOAs. The proposed algorithm compares the estimated results before despreading and after despreading for choosing AOA of GPS signal. Computer simulation examples are presented to illustrate the performance of the proposed algorithm.

• The KIPS Transactions:PartD
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• v.12D no.2 s.98
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• pp.289-302
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• 2005

The mobile agent has very various performance according to the element of communication number of times between hosts, quantity of transmission data agent's size, network state etc. specially, migration method is caused much effect in whole performance of distributed system. Most existing migration methods have simplicity structure that it moves doing to accumulate continuously result after achieving task by visiting host in the fixed order. Therefore, in case there are situation such as fault, obstacle, and service absence etc. This can be inefficient due to mobile agent increased network required time. In this paper, we design and implementation Multicast Migration Model for minimizing network required time by solving this problems. Multicast Migration Model includes components such as mobile agent including call module and naming agent, which provides object replication information and distributed server's location transparence. And we evaluate and compare with existing migration method applying prototype system to verify implemented migration model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.34-40
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• 2008

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.1
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• pp.73-81
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• 2010

In recent years, there have been diverse researches and utilizations of creating geo-spatial information with high resolution satellite images. However thematic maps made with middle or low resolution satellite images have low location accuracy and precision of thematic information. This study set out to propose a method of making a precision thematic map with high resolution satellite images by examining the conversion from the conventional method based on middle or low resolution satellite images to the automatic method based on high resolution satellite images of GSD 1m or lower, extracting thematic information of middle or large scale of 1/5,000 or lower, and analyzing its accuracy. Seven classification classes were categorized according to the object-oriented classification in order to automatically extract thematic information with high resolution satellite images. And the classification results were compared and analyzed with the old middle scale land cover map and 1/1000 digital map.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.549-557
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• 2012

Spatial phenomena such as environment pollution, disease and the risk of spreading information need a rapid initial response to perceive spread event. Moving data perceive spread event through real-time processing and analysis. To process and analysis the event, spatial-temporal complex event processing is used. Previous spatialtemporal complex event processing is possible basis spatial operator but insufficient apply to design spatialtemporal complex event processing to perceive spatial phenomena of high complexity. This study proposed hierarchical spatio-temporal CEP design which will efficiently manage the fast growing incoming sensor data. The implementation of the proposed design is evaluated with GPS location data of moving vehicles which are used as the incoming data stream for identifying spatial events. The spatial component of existing CEP software engine has been extended during the implementation phase to broaden the capabilities of processing spatio-temporal events.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.236-247
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• 2010

Recently, mean shift tracking algorithms have been proposed which use the information of color histogram together with some spatial information provided by the kernel. In spite of their fast speed, the algorithms are suffer from an inherent instability problem which is due to the use of an isotropic kernel for spatiality and the use of the Bhattacharyya coefficient as a similarity function. In this paper, we analyze how the kernel and the Bhattacharyya coefficient can arouse the instability problem. Based on the analysis, we propose a novel tracking scheme that uses a new representation of the location of the target which is constrained by the color, the area, and the spatiality information of the target in a more stable way than the mean shift algorithm. With this representation, the target localization in the next frame can be achieved by one step computation, which makes the tracking stable, even in difficult situations such as low-rate-frame environment, and partial occlusion.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.425-430
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• 2015

This paper is a study to improve the classification efficiency of rotating objects by using deep neural networks to which a deep learning algorithm was applied. For the classification experiment of rotating objects, COIL-20 is used as data and total 3 types of classifiers are compared and analyzed. 3 types of classifiers used in the study include PCA classifier to derive a feature value while reducing the dimension of data by using Principal Component Analysis and classify by using euclidean distance, MLP classifier of the way of reducing the error energy by using error back-propagation algorithm and finally, deep learning applied DBN classifier of the way of increasing the probability of observing learning data through pre-training and reducing the error energy through fine-tuning. In order to identify the structure-specific error rate of the deep neural networks, the experiment is carried out while changing the number of hidden layers and number of hidden neurons. The classifier using DBN showed the lowest error rate. Its structure of deep neural networks with 2 hidden layers showed a high recognition rate by moving parameters to a location helpful for recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7B
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• pp.586-594
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• 2012

The drastic growth of mobile communication and spreading of smart phone make the significant attention on Location Based Service. The one of most important things for vitalization of LBS is the accurate estimating position for mobile object. Focusing on AP's probabilistic position estimation, we develop an AP distribution map and new pattern matching algorithm for position estimation. The developed approaches can strengthen the advantages of Radio fingerprint based Wi-Fi Positioning System, especiall on the algorithms and data handling. Compared on the existing approaches of fingerprint pattern matching algorithm, we achieve the comparable higher performance on both of average error of estimation and deviation of errors. Furthermore all fingerprint data have been harvested from the actual measurement of radio fingerprint of Seoul, Kangnam area. This can approve the practical usefulness of proposed methodology.