• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.351-358
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• 2005

Many methods have been developed and are in use for structural size optimization problems, In which the cross-sectional areas or sizing variables are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. This paper proposes an efficient optimization method for structures with discrete-sized variables based on the harmony search (HS) meta-heuristic algorithm. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary In this paper, a discrete search strategy using the HS algorithm is presented in detail and its effectiveness and robustness, as compared to current discrete optimization methods, are demonstrated through a standard truss example. The numerical results reveal that the proposed method is a powerful search and design optimization tool for structures with discrete-sized members, and may yield better solutions than those obtained using current method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2001.04a
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• pp.223-232
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• 2001

This paper describes Genetic Algorithm-Based Relay Search Method, RS-GA, which is developed in this study to search the multiple design variables in the design space. The RS-GA based on Simple-GA consists of some functions to search many variables from some wide variable space. It repeats a Simple-GA, that is the convergence process of the Simple-GA, which makes many time reiteration itself. From the results of the numerical studies, it was actually found that RS-GA can search all peak-variable from the 2D functions including 5 peaks. Finally, RS-GA applied for design-strengthening problems in composite plate girder bridges using the external prestressing technique is also verified.

• 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.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1724-1731
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• 2018

The conventional polynomial neural network (PNN) is a classical flexible neural structure and self-organizing network, however it is not free from the limitation of overfitting problem. In this study, we propose a space search-optimized polynomial neural network (ssPNN) structure to alleviate this problem. Ranking selection is realized by means of ranking selection-based performance index (RS_PI) which is combined with conventional performance index (PI) and coefficients based performance index (CPI) (viz. the sum of squared coefficient). Unlike the conventional PNN, L2-norm regularization method for estimating the polynomial coefficients is also used when designing the ssPNN. Furthermore, space search optimization (SSO) is exploited here to optimize the parameters of ssPNN (viz. the number of input variables, which variables will be selected as input variables, and the type of polynomial). Experimental results show that the proposed ranking selection-based polynomial neural network gives rise to better performance in comparison with the neuron fuzzy models reported in the literatures.

• Journal of Technology Innovation
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• v.25 no.3
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• pp.299-331
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• 2017

This research details firm knowledge search types based on the locus and features for Korean firms in the knowledge-based industry, and then analyzes differences in innovation performance according to the types from the view of a configurational approach. Existing research has mainly concentrated on establishing a relation between knowledge search and outcome variables. Consequently, firms have relatively insufficient understanding of how to systematize knowledge search. Hence, this research classifies knowledge search into four dimensions-external search breadth, external search depth, internal search breadth, and internal search depth-by the locus and features of search. Furthermore, the research draws actual types of knowledge search of firms and analyzes differences in innovation performance. The main result of the research is as follows. First, the research reasons out six clusters of firms which have a dissimilar knowledge search type. Each cluster shows differences while participating in every dimension of knowledge search or few dimensions. Second, as for innovation performance, each cluster shows different exploitative and exploratory innovation performance according to their knowledge search type. This research applies a configurational approach while existing research applied a reductionistic approach, thereby establishing the major contribution which enables us to study a phenomenon as it comes, not to analyze variables and relationships of variables. Lastly, the research suggests a future direction of research based on the result of this research.

• Journal of Families and Better Life
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• v.14 no.3
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• pp.91-108
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• 1996

The major purpose of this study was to find the influencing factors in explaining search patterns of product attributes in formation and to find if significant differences exist in search outcomes by search patterns. The data for this study were collected in a survey and the final sample consisted of 327 respondents purchased refrigerator 340 purchased bed. The important findings of this study are as follows: First the variables related to search cost-benefit play an important role in identifying search patterns for each of product attributers. The findings of this study provide some implications regarding consumer education programs and consumer information providing policies.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.1-31
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• 2009

This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.4
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• pp.536-548
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• 1994

The puprpose of this study were to investigate the conceptual framework of situational variables on clothing types, to find out the relationship between situational variables and personality characteristics, and to determine the effects of situational variables on clothing purchase types. A Questionnaire was developed based on the previous studies. Data was collected from 530 women living Pusan and analyzed by the factor analysis, person correlation, and discriminant analysis. The results of this study were as following; Communication situations and purchasing situations were found out to be different on clothing purchase types. In planning purchase, consumers were affected by printed and tele-communication information search and were affected by interpersonal information search in unplanning purchase. In impulseing purchase, consumers were affected by store information search. It was found out that consumers with high rational clothing involvements were affected by only the purchasing situations when they would buy clothing, but consumers with high emotional clothing involvements were affected by the communication situations as well as the purchase situations. Consumers with high self monitoring traits were not affected by the communication situations and mostly the purchasing situations. Results showed that the purchasing situation was the most significant variables in clothing purchase behavior, communication situating or purchasing situations were differently influenced on clothing purchase types.

• Journal of Information Technology Applications and Management
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• v.27 no.5
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• pp.23-33
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• 2020

As the 4G and 5G Internet technologies become more common and developed, an environment for uploading and watching videos is created and spread, in addition to simply uploading posts. Watching and sharing daily life among media contents called Vlog, are very common more than ever. This means that individual users could access Vlog easily and the situation could be new trend. Additionally, academic research about Volg is increasing. We analyzed three independent variables affecting a perceived enjoyment we set up the dependent variable. Information search, self-expression, and social need are set as independent variables and social interaction is set as the control variable. Information search and self-expression are significant effect to perceived enjoyment except social need. In particular, social interaction as a control variable has effect to all relationships.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.258-258
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• 2012

In frequency analyses of hydrological data, it is necessary for the interested variables to be homogenous and independent. However, recent evidences have shown that the occurrence of extreme hydro-meteorological events is influenced by large-scale climate variability, and the assumption of homogeneity does not generally hold anymore. Therefore, in order to associate the non-homogenous characteristics of hydro-meteorological variables, we propose the parameter estimation method of probability models using meta-heuristic algorithms, specifically harmony search. All the weather stations in South Korea were employed to demonstrate the performance of the proposed approaches. The results showed that the proposed parameter estimation method using harmony search is a comparativealternative for the probability distribution of the non-homogenous hydro-meteorological variables data.