• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.583-600
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• 2014

Social media is considered a valuable platform for gathering and analyzing the collective and subconscious opinions of people in Internet and mobile environments, where they express, explicitly and implicitly, their daily preferences for brands and products. Extracting and tracking the various attitudes and concerns that people express through social media could enable us to categorize brands and decipher individuals' cognitive decision-making structure in their choice of brands. We investigate the cognitive network structure of consumers by building an inter-category map through the mining of big data. In so doing, we create an improved online recommendation model. Building on economic sociology theory, we suggest a framework for revealing collective preference by analyzing the patterns of brand names that users frequently mention in the online public sphere. We expect that our study will be useful for those conducting theoretical research on digital marketing strategies and doing practical work on branding strategies.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.813-821
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• 2012

Environmental and public health concern for the emission of air pollutants from burn-up process in waste incineration plants located in the vicinity of living environment was increased during the past decade. The purpose of this study was to suggest of the simple and rapid method of priority setting model for the decision of full-scale public health assessment. This method was consists of total 5-step. Step 1 was "secure the satellite map" and we can use the satellite map which serves from the website such as NAVER Co. Step 2 was "drawing mesh on the map" for catch the point of occupation of environmental sensitivity facilities, and step 3 was "identification and sorting of the facilities", Step 4 was "setting of weight" using the "weighted linear combination (WLC) method". Finally, all facility was sorted by score. As a result, we can set a priority of 145 facilities based on 177 facilities which managed in local government. Facilities in Seoul metropolitan area was high rank in priority list. On the other side, Facilities located at the country or rural area was low rank because of low occupation of the house and the environmental sensitivity facilities such as kindergarten, elementary school, and hospital. In this study, we suggested simple and rapid method that using for screening procedure of public health assessment.

• Journal of Korean Society for Geospatial Information Science
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• v.2 no.2 s.4
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• pp.43-53
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• 1994

GSIS(geo-spatial information system), particularly when utilized in hazard management decision, is one of hazard analysis tool. Data of GSIS input from digitizing or scanning of map or aerial photos. This paper focuses upon the hazard prediction in GSIS and RS analysis to assess map, aerialphotos, satellite imagery and soil map. This study found computation of hazard area analysis. the results is formed as raster data model of quadtree. Authors knew more accurate results of overlay. This paper shows building up integrated data base as well as search of hazard area in aerial photographs.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.30-35
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• 2005

An automatic transmission pattern with the fixed standard shift map can provide comfortable shift to driver. However it may be a complain to provide shift by the same shift pattern for driver because the inclination of a driver may be various. Therefore, in this paper, we design the decision module, which can decide the driving style using input to decide the inclination of the driver and driving manner. The goal of this paper is to calibrate the shift map according to the inclination of the driver using the decided driving manner from the proposed module. As a result, the proposed intelligent automatic transmission system can provide a suitable shift point and time to the driver. To verify the performance of the proposed system, the real data that is obtained from the road test will be used.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.174-176
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• 2005

This treatise studies composing process that renew information mastered by interactive experience between environment and system via network among individuals. In the previous study map information regarding free space is learned by using of reinforced learning algorithm, which enable each individual to construct optimal action policy. Based on those action policy each individuals can obtain optimal path. Moreover decision process to distinguish best optimal path by comparing those in the network composed of each individuals is added. Also information about the finally chosen path is being updated. A self renewing method of each system information by sharing the each individual data via network is proposed Data enrichment by shilling the information of many maps not in the single map is tried Numerical simulation is conducted to confirm the propose concept. In order to prove its suitability experiment using micro-mouse by integrating and comparing the information between individuals is carried out in various types of map to reveal successful result.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.443-451
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• 2016

Globally, landslides triggered by natural or human activities have resulted in enormous damage to both property and life. Recent climatic changes and anthropogenic activities have increased the number of occurrence of these disasters. Despite many researches, there is no standard method that can produce reliable prediction. This article discusses the process of landslide susceptibility mapping using various methods in current literatures and applies the FR (Frequency Ratio) method to develop a susceptibility map for the 2015 earthquake region of Sindhupalchowk, Nepal. The complete mapping process describes importance of selection of area, and controlling factors, widespread techniques of modelling and accuracy assessment tools. The FR derived for various controlling factors available were calculated using pre- and post- earthquake landslide events in the study area and the ratio was used to develop susceptibility map. Understanding the process could help in better future application process and producing better accuracy results. And the resulting map is valuable for the local general and authorities for prevention and decision making tasks for landslide disasters.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.31-36
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• 2003

This paper proposes an acceleration method of PCA(Principal Component Analysis) based feature detection. The feature detection method makes decision whether the target feature is included in a given image, and if included, calculates the position and extent of the target feature. The position and scale of the target feature or face is not known previously, all the possible locations should be tested for various scales to detect the target. This is a search Problem in huge search space. This Paper proposes a fast face and feature detection method by reducing the search space using the multi-stage prediction map and contour Prediction map. A Proposed method compared to the existing whole search way, and it was able to reduce a computational complexity below 10％ by experiment.

• Korea Journal of Hospital Management
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• v.22 no.3
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• pp.105-117
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• 2017

This study was performed to provide medical service providers with useful information for their market competitiveness and decision making. It is regarding positioning map and repositioning map strategy to enforce market competitiveness through bench marking of a specific hospital which has been relatively underestimated in the market. With AHP and biplot analyses for this study, we could identify priority of properties that medical service consumers consider when they choose a university hospital and market competitiveness of alternative university hospitals. It is expected that the study of repositioning strategy to Strengthening Market Competitiveness will provide efficient problem solving method to allocation restricted resources by repositioning the specific university hospital through benchmarking with evaluation factors of the most market competitiveness university hospital. When Inje University Paik Hospital was benchmarked and repositioned, the share of Paik hospital increased and there was only 3.1% difference from Dongah Dong-A University Hospital, which occupied the first place in market competitiveness. Such the results of this study may suggestion management strategies to provide efficient problem solving methods when companies responding to rapidly changing management environments allocation restricted resources.

• Journal of Information Technology Services
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• v.20 no.1
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• pp.81-92
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• 2021

As the degree of economic development of society increases, the maintenance issues on the existing social overhead capital becomes essential. Accordingly, the adaptation of the concept of Level of service in highway maintenance is indispensable. It is also crucial to manage and perform the service level such as road assets to provide universal services to users. In this regards, the purpose of this study is to improve the maintenance service rating model and to focus on the assessment items and weights among the improvements. Particularly, in determining weights, an Analytic Hierarchy Process (AHP) is performed based on the survey response results. After then, this study conducts unsupervised neural network models such as Self-Organizing Map (SOM) and Davies-Bouldin (DB) Index to divide proper sub-groups and determine priorities. This paper identifies similar cases by grouping the results of the responses based on the similarity of the survey responses. This can effectively support decision making in general situations where many evaluation factors need to be considered at once, resulting in reasonable policy decisions. It is the process of using advanced technology to find optimized management methods for maintenance.

• Journal of the Semiconductor & Display Technology
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• v.23 no.4
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• pp.172-176
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• 2024

In modern applications such as virtual reality (VR), augmented reality (AR), and autonomous vehicles, the accuracy and reliability of Depth Maps play a critical role in enhancing user experience and optimizing system performance. These applications fundamentally rely on Depth Maps for visual information processing, interaction, and decision-making. While 360-degree cameras have emerged as an innovative solution, offering comprehensive visual coverage of the surrounding environment, current technologies face significant challenges in efficiently processing large volumes of data and generating precise Depth Maps. This study addresses the critical role of Depth Maps in VR, AR, and autonomous vehicles, proposing a novel hybrid depth estimation framework. The framework combines patch-based depth estimation with Vision Transformers (ViT) to enhance the accuracy and reliability of Depth Maps in 360-degree imaging applications. Patch-based depth estimation leverages Structure from Motion (SFM) to improve local spatial precision, while ViTs address distortions caused by wide field-of-view projections and learn global features. By integrating these approaches, the framework improves the accuracy and resolution of Depth Maps, enabling the generation of dense 3D point clouds for detailed spatial representation and reconstruction. This method overcomes challenges of computational complexity and accuracy, marking significant advancements in 360-degree imaging technology for immersive and autonomous systems.