• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.65-74
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• 2021

Digital image processing and retrieving have increasingly become very popular on the Internet and getting more attention from various multimedia fields. That results in additional privacy requirements placed on efficient image matching techniques in various applications. Hence, several searching methods have been developed when confidential images are used in image matching between pairs of security agencies, most of these search methods either limited by its cost or precision. This study proposes a secure and efficient method that preserves image privacy and confidentially between two communicating parties. To retrieve an image, feature vector is extracted from the given query image, and then the similarities with the stored database images features vector are calculated to retrieve the matched images based on an indexing scheme and matching strategy. We used a secure content-based image retrieval features detector algorithm called Speeded-Up Robust Features (SURF) algorithm over public cloud to extract the features and the Honey Encryption algorithm. The purpose of using the encrypted images database is to provide an accurate searching through encrypted documents without needing decryption. Progress in this area helps protect the privacy of sensitive data stored on the cloud. The experimental results (conducted on a well-known image-set) show that the performance of the proposed methodology achieved a noticeable enhancement level in terms of precision, recall, F-Measure, and execution time.

• Journal of Korean Library and Information Science Society
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• v.45 no.1
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• pp.125-147
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• 2014

The aim of this study is to develop and suggest a reading strategy to learn for integrating reading and writing. The reading and writing strategy could be divided in directed strategies related to the cognitive process and indirected strategies to carry out the process successfully. Therefore, its strategies are constructed of the indirected strategy corresponding with the instructional design model and the direct strategy containing specific action plans of the model's progressive stages. When considering the reading to learn could be run as a program in the school, in this study, the basic model of the indirected strategy is devised with four steps of 'preparing-designing-implementing-evaluating'. And the implementing stage of the read to learn combining reading and writing is consisted of six steps as 'selecting subjects-considering contents-searching-writing-correcting-publishing'. Also, proper indirected strategies such as graphic organization and checklists are suggested in order to assist reading and writing activities in the implementing stage.

• Journal of the Korea Convergence Society
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• v.8 no.6
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• pp.97-107
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• 2017

The purpose of this study was to investigate information source of the choice of select dental medical institution and the relationship between socioeconomic characteristics and information searching pattern. This study was conducted for residents adults and teens living in Gwangju and rural communities of Jellanam-do province including. The study shows that 61.0 % of the information of selecting dental medical institutes had been introduced by the acquaintance and the rest of the information(37.0%) had been gotten from the internet. The purpose of this study is to develop an information search method that can influence the choice of medical consumers in dental clinics, and to establish a new dental clinic management strategy based on this research. Plus, we want to develop an information search source that can have a convergence effect on the selection of medical consumers in dental medical institutions.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.11
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• pp.596-603
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• 2004

This paper proposes an expert system based on the pattern recognition method which can enhance the accuracy and effectiveness of real-time bus reconfiguration strategy for the transfer of faulted load when a main transformer fault occurs in the automated substation. The minimum distance classification method is adopted as the pattern recognition method of expert system. The training pattern set is designed MTr by MTr to minimize the searching time for target load pattern which is similar to the real-time load pattern. But the control pattern set, which is required to determine the corresponding bus reconfiguration strategy to these trained load pattern set is designed as one table by considering the efficiency of knowledge base design because its size is small. The training load pattern generator based on load level and the training load pattern generator based on load profile are designed, which are can reduce the size of each training pattern set from max L/sup (m+f)/ to the size of effective level. Here, L is the number of load level, m and f are the number of main transformers and the number of feeders. The one reduces the number of trained load pattern by setting the sawmiller patterns to a same pattern, the other reduces by considering only load pattern while the given period. And control pattern generator based on exhaustive search method with breadth-limit is designed, which generates the corresponding bus reconfiguration strategy to these trained load pattern set. The inference engine of the expert system and the substation database and knowledge base is implemented in MFC function of Visual C++ Finally, the performance and effectiveness of the proposed expert system is verified by comparing the best-first search solution and pattern recognition solution based on diversity event simulations for typical distribution substation.

• Journal of Korean Society of Rural Planning
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• v.18 no.3
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• pp.149-164
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• 2012

The purpose of the present study is to construct a rural development strategy from the nexus between spatial changes in specialized crops and suitable cultivation area of the crops. This paper pays particular attention to identify product life cycle of specialized crops in rural areas and estimate the impact of climate change on alterations in spatial distribution of the crops. In order to do so, first of all, this study applies multi-level model (Random coefficient model) to estimate the regional coefficient of five orchard crops. It utilizes the data 1995 to 2010 Korea Agricultural Census. Futhermore, it also adopts overlay analysis by ArcGIS to identify the development path of the crops and the relationship with climate change. Based on the results, it suggests a mechanism activating regional agriculture. The findings propose re-searching and relocating specialized regions of the crops. Especially, it proves each rural area can drive the new agricultural strategy to strengthen regional agriculture by estimating the relationship between development of specialized crops and suitable cultivation areas. For instance, shifting specialized crops in particular regions and enriching genetic or species varieties can be primary measures and it will contribute to improve the reliable base for income sources in the rural communities. This paper also offers specific policy implications regarding rural development plans in response to crops' life cycle and climate changes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.9
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• pp.1521-1526
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• 2007

This paper presents the application of Adaptive Evolutionary Algorithm (AEA) to search an optimal setting of overcurrent relay coordination to protect ring distribution systems. The AEA takes the merits of both a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner to use the global search capability of GA and the local search capability of ES. The overcurrent relay settings and coordination requirements are formulated into a set of constraint equations and an objective function is developed to manage the overcurrent relay settings by the Time Coordination Method. The domain of overcurrent relays coordination for the ring-fed distribution systems is a non-linear system with a lot of local optimum points and a highly constrained optimization problem. Thus conventional methods fail in searching for the global optimum. AEA is employed to search for the optimum relay settings with maximum satisfaction of coordination constraints. The simulation results show that the proposed method can optimize the overcurrent relay settings, reduce relay mis-coordinated operations, and find better optimal overcurrent relay settings than the present available methods.

• Journal of Korea Multimedia Society
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• v.2 no.1
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• pp.9-21
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• 1999

This paper presents the time-segmented storage structure in order to increment search performance and the two data migration strategies: migration by Time Granularity and migration by LST-GET. In the migration strategy by Time Granularity, we describe how to assign entity version to the past, current segment, and future segments. We also describe searching and moving processes for data validity at a granularity level. In the migration strategy by LST-GET, we describe how to computer the value of dividing criterion. We simulate the search performance of the proposed segmented storage structure in comparison with the conventional storage structure in comparison with the conventional storage structure in relational database system. Finally, extensive simulation studies are performed in order to compare the search performance of the migration strategies with the time-segmented storage structure.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.488-492
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• 2007

In this study, we investigated how to distinguish customer delivered value to re-purchasing in fierce B2C industry. To identify key managerial variables that could distinctively impact re-purchasing, we first identified customer value proposition as per the customer buying decision process. Next, core value propositions of choice efficiency and competitive price are defined to determine vendor satisfaction during the searching stage and purchasing stage. The trust level is also introduced in the sense of reflecting confirmation to guarantee after purchase security. Then, significant managerial variables to impact on core value propositions are extracted. The resulting structural model illustrated that search convenience and quality assurance affect the choice efficiency, and re-purchase intention is strongly explained by both the vendor satisfaction and trust level. The empirical testing results also support that transaction cost reduction is key determinant of shopping at the Internet shopping mall. Furthermore, trust level should be combined to induce re-purchasing in addition to transaction cost savings.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1261-1268
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• 2013

This study proposes a voltage and reactive coordinative control strategy with distributed generator (DG) in a distribution power system. The aim is to determine the optimum dispatch schedules for an on-load tap changer (OLTC), distributed generator settings and all shunt capacitor switching on the load and DG generation profile in a day. The proposed method minimizes the real power losses and improves the voltage profile using squared deviations of bus voltages. The results indicate that the proposed method reduces the real losses and voltage fluctuations and improve receiving power factor. This paper proposes coordinated voltage and reactive power control methods that adjust optimal control values of capacitor banks, OLTC, and the AVR of DGs by using a voltage sensitivity factor (VSF) and dynamic programming (DP) with branch-and-bound (B&B) method. To avoid the computational burden, we try to limit the possible states to 24 stages by using a flexible searching space at each stage. Finally, we will show the effectiveness of the proposed method by using operational cost of real power losses and voltage deviation factor as evaluation index for a whole day in a power system with distributed generators.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.213-224
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• 1998

Since the late 1980s, an Increasing number of neural network models have been studied in the areas of financial prediction and analysis. The purpose of this study is to Investigate the possibility of building a neural network model that is able to construct a profitable trading strategy in the Korean Stock Market. This study classifies stocks into the future market winners and losers from the publicly available accounting information and builds portfolios based on this information. The performances of the winner portfolios and the loser portfolios are compared with each other and against the market index. The empirical result of this research is consistent with the traditional fundamental analysis where it is claimed that the financial statements contain firm values that may not be fully reflected In stock prices without delay. Despite the supporting empirical evidence. It is somewhat Inconclusive as to whether or not the abnormal return in excess of market return is the result of the extra knowledge obtained in the neural network models derived from the historical accounting data. This research attempts to open another avenue using neural network models for searching for evidence against market efficiency where statistics and intuition have played a major role.