• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.397-401
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• 2006

In this paper, we proposed a high precision location estimation algorithm using an enhanced decision scheme for RTLS and analyzed its performance in point of an average estimation error distance at 2D coordinates searching area, $300m\times300m$ and LOS propagation environments. Also the performance was compared with that of conventional TDOA algorithm according to the number of available reader and received sub-blink. From the results, we confirmed that the proposed location estimation algorithm using an enhanced decision scheme was able to improve an estimation accuracy even in boundary region of searching area. Moreover, effectively reduced an error distance in entire searching area so that increased the stability of location estimation in RTLS. Therefore, we verified that the proposed algorithm provided a more higher estimation accuracy and stability than conventional TDOA.

• Journal of Advanced Navigation Technology
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• v.10 no.4
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• pp.385-393
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• 2006

In this paper, we proposed a location estimation algorithm considering an extension of searching area in 2.45GHz band RTLS and analyzed its performance in terms of an average estimation error distance. The extendable searching area was assumed to be square of $300m{\times}300m$ and 2 dimensions. The arrangement shape of available readers was considered circle, rectangle, and shrinkage rectangle for extendable searching area. Also, we assumed that propagation path was LOS (Line-Of-Sight) environment, and analyzed the estimation error performance as a function of the number of received sub-blink considering an arrangement shape of available readers in searching area. From the results, compared with rectangle shape, circle shape showed the higher estimation accuracy. Also, we confirmed that the proposed location estimation algorithm provided high estimation accuracy in the shrinkage rectangle shape that was suitable for extension of searching area.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.29-48
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• 2014

The recent keyword advertising does not reflect the individual customer searching pattern because it is focused on each keyword at the aggregate level. The purpose of this research is to observe processes of customer searching patterns. To be specific, individual deal-proneness is mainly concerned. This study incorporates location as a control variable. This paper examines the relationship between customers' searching patterns and probability of purchase. A customer searching session, which is the collection of sequence of keyword queries, is utilized as the unit of analysis. The degree of deal-proneness is measured using customer behavior which is revealed by customer searching keywords in the session. Deal-proneness measuring function calculates the discount of deal prone keyword leverage in accordance with customer searching order. Location searching specificity function is also calculated by the same logic. The analyzed data is narrowed down to the customer query session which has more than two keyword queries. The number of the data is 218,305 by session, which is derived from Internet advertising agency's (COMAS) advertisement managing data and the travel business advertisement revenue data from advertiser's. As a research result, there are three types of the deal-prone customer. At first, there is an unconditional active deal-proneness customer. It is the customer who has lower deal-proneness which means that he/she utilizes deal-prone keywords in the last phase. He/she starts searching a keyword like general ones and then finally purchased appropriate products by utilizing deal-prone keywords in the last time. Those two types of customers have the similar rates of purchase. However, the last type of the customer has middle deal-proneness; who utilizes deal-prone keywords in the middle of the process. This type of a customer closely gets into the information by employing deal-prone keywords but he/she could not find out appropriate alternative then would modify other keywords to look for other alternatives. That is the reason why the purchase probability in this case would be decreased Also, this research confirmed that there is a loyalty effect using location searching specificity. The customer who has higher trip loyalty for specificity location responds to selected promotion rather than general promotion. So, this customer has a lower probability to purchase.

• Korean Management Science Review
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• v.29 no.1
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• pp.143-152
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• 2012

Location area planning (LAP) problem is to partition the cellular/mobile network into location areas with the objective of minimizing the total cost in location management. The minimum cost has two components namely location update cost and searching cost. Location update cost is incurred when the user changes itself from one location area to another in the network. The searching cost incurred when a call arrives, the search is done only in the location area to find the user. Hence, it is important to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking cost is a minimum. The complete mobile network is divided into location areas. Each location area consists of a group of cells. This partitioning problem is a difficult combinatorial optimization problem. In this paper, we use particle swarm optimization (PSO) to obtain the best/optimal group of cells for 16, 36, 49, and 64 cells network. Experimental studies illustrate that PSO is more efficient and surpasses those of precious studies for these benchmarking problems.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.785-786
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• 2008

In this paper, we propose a fast Motion Estimation (ME) algorithm for low computational complexity based on spatial correlations. The proposed algorithm uses the motion vector of neighboring blocks, to decide the location of initial searching point. The number of searching point decreases by changing the location of initial searching point. Experimental results show that the proposed algorithm reduces searching points about $7{\sim}13%$ and increases PSNR about $0.1{\sim}0.5$(dB) compared with conventional algorithm.

• Spatial Information Research
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• v.22 no.4
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• pp.21-38
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• 2014

Since users who search maps conduct their searching using the name they already know or is commonly called rather than formal name of a specific place, they tend to fail to find their destination. In addition, in typical web map service in terms of spatial searching of map. Location information of unintended place can be provided because when spatial searching is conducted with the vocabulary 'nearby' and 'in the vicinity', location exceeding 2 km from the current location is searched altogether as well. In this research, spatial range that human can perceive is calculated by extracting POI date with the usage of twitter data of SNS, constructing spatial relations with existing POI, which is already constructed. As a result, various place names acquired could be utilized as different names of existing POI data and it is expected that new POI data would contribute to select places for constructing POI data by utilizing to recognize places having lots of POI variation. Besides, we also expect efficient spatial searching be conducted using diverse spatial vocabulary which can be used in spatial searching and spatial range that human can perceive.

• Journal of the Korean Society for Library and Information Science
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• v.26
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• pp.167-185
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• 1994

The purpose of this study is to develop the optimal user/librarian interface in information searching. In order to achive the purpose, the 150 unskilled students as subjects have participated in the study. According to the change of the subjects' psychological information states by the access points within the library system, the subjects have been classified into the five types of model: the initial information state, the accepted identification information state, the bibliographic information state, the stack information state, and the location information state. Librarian's searching support is done for 10 minutes at the each access points. To develop the optimal user/librarian interface, the expected values of the models are calculated. The resultants are as follows: 1) The expected value of the initial information states model is 18.94: 2) The expected value of the accepted identification information model is 27.06: 3) The expected value of the bibliographic information state model is 27.06: 4) The expected value of the stack information state model is 22.38: 5) The expected value of the location information state model is 22.38. Those expected values are compared with each other. The model with the lowest expected value is chosen as the optimal user/librarian interface model. In the result, the user's initial information state model of the optimal user/librarian interface in information searching is developed. In order to search the information with the most effect, user must be interfaced with the librarian at his/her own initial information state.

• Journal of KSNVE
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• v.10 no.5
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• pp.783-791
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• 2000

This describes a study on the support location optimizations of the beams using the genetic algorithm and the sensitivity analysis. The genetic algorithm is a probabilistic method searching the optimum at several points simultaneously and requiring only the values of the object and constraint functions. It has therefore more chances to find the global solution and can be applied to the various problems. Nevertheless, it has such a shortcoming that it takes too many calculations, because it is ineffective in local search. While the traditional method using sensitivity analysis is of great advantage in searching the near optimum. thus the combination of the two techniques will make use of the individual advantages, that is, the superiority in global searching form the genetic algorithm and that in local searching form the sensitivity analysis. In this thesis, for the practical applications, the analysis is conducted by FEB ; and as the shapes of structures are taken as the design variation, it requires re-meshing for every analysis. So if it is not properly controlled, the result of the analysis is affected and the optimized solution amy not be the real one. the method is efficiently applied to the problems which the traditional methods are not working properly.

• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.228-233
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• 2010

In this paper, the iteration localization algorithm that NLOS signal is iteratively removed to get the exact location in the wireless sensor network is proposed. To evaluate the performance of the proposed algorithm, TDOA location estimation method is used, and readers are located on every 150m intervals with rectangular shape in $300m{\times}300m$ searching field. In that searching field, the error distance is analyzed according to increasing the number of iteration, sub-blink and the estimated sensor node locations which are located in the iteration range. From simulation results, the error distance is diminished according to increasing the number of the sub-blink and iteration with the proposed location estimation algorithm in NLOS environment. Therefore, to get more accurate location information in wireless sensor network in NLOS environments, the proposed location estimation algorithm removing NLOS signal effects through iteration scheme is suitable.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.547-557
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• 2016

Due to threats caused by social disasters, operating surveillance devices are essential for social safety. CCTV, infrared cameras and other surveillance equipment are used to observe threats. This research proposes a method for searching for the optimum location of surveillance sensors. A GA (Genetic Algorithm) was used, since this algorithm is one of the most reasonable and efficient methods for solving complex non-linear problems. The sensor specifications, a DEM (Digital Elevation Model) and VITD (Vector Product Interim Terrain Data) maps were used for input data. We designed a chromosome using the sensor pixel location, and used elitism selection and uniform crossover for searching final solution. A fitness function was derived by the number of detected pixels on the borderline and the sum of the detection probability in the surveillance zone. The results of a 5-sensor and a 10-sensor were compared and analyzed.