• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.47-54
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• 2017

Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

• Journal of the Ergonomics Society of Korea
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• v.36 no.3
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• pp.255-265
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• 2017

Objective: This study aims to survey visual search performance models to assess and predict individual's visual tasks in everyday life and industrial sites. Background: Visual search is one of the most frequently performed and critical activities in everyday life and works. Visual search performance models are needed when designing or assessing the visual tasks. Method: This study was mainly based on survey of literatures related to ergonomics relevant journals and web surfing. In the survey, the keywords of visual search, visual search performance, visual search model, etc. were used. Results: On the basis of the purposes, developing methods and results of the models, this study categorized visual search performance models into six groups: probability-based models, SATO models, visual lobe-based models, computer vision models, neutral network-based models and detection time models. Major models by the categories were presented with their advantages and disadvantages. More models adopted the accuracy among two factors of accuracy and speed characterizing visual tasks as dependent variables. Conclusion: This study reviewed and summarized various visual search performance models. Application: The results would be used as a reference or tool when assessing the visual tasks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.744-768
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• 2016

As various pieces of information can be provided through the web, schemes that provide search results optimized for individual users are required in consideration of user preference. Since the existing social search schemes use users' profiles, the accuracy of the search deteriorates. They also decrease the reliability of a search result because they do not consider a search time. Therefore, a new social search scheme that considers temporal information as well as popularities and user preferences is required. In this paper, we propose a new mobile social search scheme considering popularities and user preferences based on temporal information. Popularity is calculated by collecting the visiting records of users, while user preference is generated by the actual visiting information among the search results. In order to extract meaningful information from the search target objects that have multiple attributes, a skyline processing method is used, and rank is given to the search results by combining the user preference and the popularity with the skyline processing result. To show the superiority of the proposed scheme, we conduct performance evaluations of the existing scheme and the proposed scheme.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.214-221
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• 2010

The search-results clustering problem is defined as the automatic and on-line grouping of similar documents in search results returned from a search engine. In this paper, we propose a new search-results clustering algorithm specialized for a paper search service. Our system consists of two algorithmic phases: Category Hierarchy Generation System (CHGS) and Paper Clustering System (PCS). In CHGS, we first build up the category hierarchy, called the Field Thesaurus, for each research field using an existing research category hierarchy (KOSEF's research category hierarchy) and the keyword expansion of the field thesaurus by a word clustering method using the K-means algorithm. Then, in PCS, the proposed algorithm determines the category of each paper using top-down and bottom-up methods. The proposed system can be used in the application areas for retrieval services in a specialized field such as a paper search service.

• Journal of Advanced Navigation Technology
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• v.12 no.2
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• pp.146-153
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• 2008

Due to the extremely short pulse in the Ultra-Wideband (UWB) technology, the accurate synchronization acquisition method is very important for both high data-rate WPAN and low data-rate WPAN. In this paper, we propose the synchronization acquisition algorithm based on two-step signal search method to acquire the synchronization in the UWB multi-path channel. At the first step, the search window is divided by two and the window that has higher power is chosen as a next search window. This operation is repeated until the measure power of the search window is smaller than the threshold value. At the second step, we employ Linear Search algorithm to the search window obtained at the first step for fine search. The proposed algorithm is proved that the synchronization acquisition is faster than the parallel search algorithm and it shows good performance in environment of the SNR extreme changes by the simulation.

• The Journal of Korean Medicine
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• v.30 no.4
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• pp.47-58
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• 2009

Objectives: Several domestic search systems for research projects providing capabilities of searching and managing the research information based on metadata have been completed, although they cannot search projects for specific domains such as the Oriental Medicine field. Therefore, in this paper we propose an effective method for collecting and refining information of research projects in the oriental medicine field. We also design and implement a search management system based on the collected information. Methods: We chose three search elements and defined the collecting process for research projects. The collected information was refined to enhance the quality of results. Then, the search management system was implemented by Adobe Flex. Results: We were able to collect 1,688 research projects in the oriental medicine field. We also implemented the search management system, which provides the functionalities of search and management such as input, update, delete, spreadsheet import/export of R&D projects, user management and access control. Conclusions: The collected information and the search management system will be used in a project analysis system which will be constructed in the future. The project analysis system could help to analyze trends in oriental medicine research as well as construct a technical roadmap.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.9
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• pp.451-464
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• 2016

Nowadays, entity search such as Google Product Search and Yahoo Pipes has been in the spotlight. The entity search engines have been used to retrieve web pages relevant with a particular entity. However, if an entity (e.g., Chinatown movie) has various meanings (e.g., Chinatown movies, Chinatown restaurants, and Incheon Chinatown), then the accuracy of the search result will be decreased significantly. To address this problem, in this article, we propose a novel method that quantifies the importance of search queries and then offers the best query for the entity search, based on Frequent Pattern (FP)-Tree, considering the correlation between the entity relevance and the frequency of web pages. According to the experimental results presented in this paper, the proposed method (59% in the average precision) improved the accuracy five times, compared to the traditional query terms (less than 10% in the average precision).

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.112-114
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• 2011

On multimedia databases, in order to realize the fast access method, indexing methods for the multidimension data space are used. However, since it is a premise to use the Euclid distance as the distance measure, this method lacks in flexibility. On the other hand, there are metric indexing methods which require only to satisfy distance axiom. Since metric indexing methods can also apply for distance measures other than the Euclid distance, these methods have high flexibility. This paper proposes an improved method of VP-tree which is one of the metric indexing methods. VP-tree follows the node which suits the search range from a route node at searching. And distances between a query and all objects linked from the leaf node which finally arrived are computed, and it investigates whether each object is contained in the search range. However, search speed will become slow if the number of distance calculations in a leaf node increases. Therefore, we paid attention to the candidates selection method using the triangular inequality in a leaf node. As the improved methods, we propose a method to use the nearest neighbor object point for the query as the datum point of the triangular inequality. It becomes possible to make the search range smaller and to cut down the number of times of distance calculation by these improved methods. From evaluation experiments using 10,000 image data, it was found that our proposed method could cut 5%~12% of search time of the traditional method.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.3
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• pp.12-18
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• 1994

Optimization in the engineering design is to select the best of many possible design alternatives in a complex design space. In order to optimize, various optimization methods have been used. One major problem of traditional optimization methods is that they often result in local optima. Recently genetic algorithm based on the mechanics of natural selection and natural genetics is used in many application fields for optimization. Genetic algorithm is more powerful to local optima, but it requires more calculation time and has difficulties in finding exact optimum point in design variable with real data type generally. In this paper. hybrid method was developed by coupling genetic algorithm and traditional direct search method. The developed method finds out a region for global optimum using genetic algorithm, and is to search global optimum using direct search method based on results obtained from genetic algorithm. By using hybrid method, calculation time is reduced and search efficient for optimum point is increased.

• The Journal of the Acoustical Society of Korea
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• v.29 no.3
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• pp.155-164
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• 2010

This paper proposes a robust detection method for ship wake search using two wake sensors. A long trailing wake in the rear of a surface ship is generated along the track of surface ships. In this paper, we assume that the nearer the surface ship, the stronger wake strength is and a two-sensor based wake homing torpedo can sense for the wake strength. On this assumption we propose a simple wake detection and search method using information of wake strength. Experimental results using monte-carlo simulation demonstrate that the proposed method yields better performance in search time than previous method, which uses a single sensor. Our method is shown faster by about 45 seconds than previous method to achieve the same performance. Also, it can improve the detection performance of torpedo in the case of short wake length.