• Structural Engineering and Mechanics
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• v.52 no.2
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• pp.351-368
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• 2014

This study presents a hunting search based optimum design algorithm for engineering optimization problems. Hunting search algorithm is an optimum design method inspired by group hunting of animals such as wolves, lions, and dolphins. Each of these hunters employs hunting in a different way. However, they are common in that all of them search for a prey in a group. Hunters encircle the prey and the ring of siege is tightened gradually until it is caught. Hunting search algorithm is employed for the automation of optimum design process, during which the design variables are selected for the minimum objective function value controlled by the design restrictions. Three different examples, namely welded beam, cellular beam and moment resisting steel frame are selected as numerical design problems and solved for the optimum solution. Each example differs in the following ways: Unlike welded beam design problem having continuous design variables, steel frame and cellular beam design problems include discrete design variables. Moreover, while the cellular beam is designed under the provisions of BS 5960, LRFD-AISC (Load and Resistant Factor Design-American Institute of Steel Construction) is considered for the formulation of moment resisting steel frame. Levy Flights is adapted to the simple hunting search algorithm for better search. For comparison, same design examples are also solved by using some other well-known search methods in the literature. Results reveal that hunting search shows good performance in finding optimum solutions for each design problem.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.1-8
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• 2008

With growing interest in location-based service (LBS), there is increasing necessity for nearest neighbor (NN) search through query while the user is moving. NN search in such a dynamic environment has been performed through the repeated applicaton of the NN method to the search segment, but this increases search cost because of unnecessary redundant calculation. We propose slabbed continuous nearest neighbor (Slabbed_CNN) search, which is a new method that searches CNN in the search segment while moving, Slabbed_CNN reduces calculation costs and provides faster services than existing CNN by reducing the search area and calculation cost of the existing CNN method through reducing the search segment using slabs.

• Journal of Korean Library and Information Science Society
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• v.40 no.4
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• pp.199-225
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• 2009

The purpose of this paper is to grow more interest and to forster research in full-texts retrieval of digitized books area through the review of Book Search Track and the analysis of research methods. First, this paper introduces the INEX tracks, the registration of INEX, the task process and the participating organizations. Second, to introduce the Book Search Track of all INEX tracks, this paper provides an overview of the test collection, the tasks, the task and submission guidelines and evaluation results of the Book Search Track's. Third, through paper review of the Book Search track that was lunched in 2007 as part of the INEX initiative, this paper presents the future research subject. This study expects that the readers are attracted by INEX tracks and full-texts retrieval of digitized books in korea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1527-1533
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• 2009

In this paper, we design directional search pattern using motion direction biased characteristics of MVP distribution, and proposes a direction applied cross diamond search method that adaptively change search pattern according to moving direction of search point. Proposed method predict motion vectors from neighbor macro blocks, and define initial motion direction by using predicted motion vectors. It improve search efficiency by using alternately proposed search pattern according to motion direction of BMP in search process. The simulation results show that proposed method is able to fast motion estimation compared with conventional cross diamond search, according as it reduce computational complexity that is required of motion estimation with $0.43%{\sim}1.76%$.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.6
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.533-543
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• 2012

We in this paper propose a semantic search system based on Korean medicine ontology. Semantic search augments search results and improves search accuracy by understanding which concept denotes terms which users is trying to find. Our semantic search system also provides these semantic search capabilities. Moreover, search scenarios which is meaningful in Korean medicine are designed and implemented by analyzing the semantics of Korean medicine ontology. Therefore, our system can help users find the useful search results with respect to Korean medicine by providing the more meaningful information as well as the connected information in ontology.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.4
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.9
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• pp.1378-1389
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• 2002

This study was to identify dimensions of subjective knowledge and to test the structural model of the effect of subjective knowledge on information search and evaluation rules for apparel products. A questionnaire was administered to 668 females living in Seoul, Taejon, and Cheongju, and the data were analysed by using LISREL 8. The results of this study were as follows: First, consumers' subjective knowledge regarding apparel products consisted of five factors; Style knowledge, Fashion Knowledge, Store Knowledge, Fabric/Management Knowledge, and Brand knowledge. Those factors were influenced by the experience related with apparel products. Second, the subjective knowledge influenced information searches. That is, internal search was significantly influenced by fashion knowledge and store knowledge, while external search was significantly influenced by fashion knowledge and fabric/management knowledge. Third, the subjective knowledge had indirect effects on evaluation rules via search activities (e.g., internal and external), suggesting that the internal search was mediated in relationship between subjective knowledge and compensatory rule, while the urtemal search was mediated in the relationship between subjective knowledge and noncompensatory rule. Therefore, this study implies that subjective knowledge plays an important role to explain consumers' decision making processes such as information search and evaluation.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.881-890
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• 2002

In this paper, by using agent technology, we proposes and implements the search system that supplies the result close to the user preference through the analysis of user preference. To offer better qualified information to user without redundant search results and unnecessary information of legacy search system. this system uses user's information and generates keywords and categories. Comparing user's favorite category with search result of legacy search system through the agent oriented search engine, it supplies only the result close to the user's category. At the same time, search result is saved into the databases according to each category to be used for search work later. As a result, the redundant information of search result was efficiently removed and the information close to the user's favorite category was obtained.

• Journal of Korean Library and Information Science Society
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• v.35 no.1
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• pp.303-317
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• 2004

The purpose of this study was to develop a framework for predicting searching performance through an understanding of how cognitive ability relates to searching process and outcome. Specifically, this study examined the relationship between spatial visualization, logical reasoning, integrative reasoning, and information searching process and outcome. Information searching process was assessed by seven search process indicators: (1) search command selection: (2) combination of search commands; (3) application of Boolean logic: (4) application of truncation; (5) use of limit search function; (6) number of search statements; and (7) number of search errors made. Searching outcome was assessed by the number of correct answers to search questions. Subjects first took three standardized cognitive tests that measured cognitive abilities, and performed online catalog searching in response to seven information search questions. The searches were logged using Lotus ScreenCam, and reviewed for the analysis. Factor analysis was used to find underlying structures of the seven search process variables. Multiple regression analysis was applied to examine the predictive power of three cognitive variables on three extracted factors, and search outcome. Results of the data analysis showed that individual differences in logical reasoning could predict information searching process and outcome.