• The Korean Journal of Archival Studies
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• no.12
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• pp.37-80
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• 2005

Archival appraisal has been a significant field and demanding task in thoughts and practice about modern archive, in particular, because of insufficiency of resources for the preservation in comparison with the large scale of recorded information. Appraising records does naturally go with the selecting and acquiring them. In the field of appraisal, however, comprehensive accountability on appraisal is much more important than selection and acquisition. The purpose of this study is the proposition of the theoretic approach to the analysis of the factors concerning the archival appraisal. For this purpose, I would try not the actual practice of the archival appraisal but theoretical categories of archival appraisal decision. The archival Characteristic, Value, and Context will be proposed as theoretical categories for the analysis of archival appraisal decision. Firstly, Characteristic category makes it clear to identify the reliable and authentic records, and then, Value provides us with elucidation about the appraisers' recognition of values. Lastly, Context explains the priority of selection throughout creating, using, interrelationship, and social meaning of archives.

• Earthquakes and Structures
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• v.16 no.1
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• pp.29-39
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• 2019

A three-step screening process is presented in this article for selection of consistent earthquake records in which number of suitable ground motions is quickly screened and reduced to a handful number. Records that remain at the end of this screening process considerably reduce the dispersion of structural responses. Then, an effective method is presented for spectral matching and modification of the selected records. Dispersion of structural responses is explored using different statistical measures for each scaling procedure. It is shown that the Uniform Design Method, presented in this study for scaling of earthquake records, results in most cases in the least dispersion measure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.176-179
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• 2022

In this paper, we consider a sectorized wireless powered sensor network (WPSN), wherein sensor nodes are clustered based on sectors and transmit data to the cluster head (CH) using energy harvested from a hybrid access point. We construct a system model for this sectorized WPSN and find optimal coordinates of CH that maximize the achievable transmission rate of sensing data. To obtain the optimal CH with low overhead, we perform an asymptotic geometric analysis (GA). Simulation results show that the proposed GA-based CH selection method is close to the optimal performance exhibited by exhaustive search with a low feedback overhead.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.577-587
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• 2023

Conventional categorical data imputation techniques, such as mode imputation, often encounter issues related to overestimation. If the variable has too many categories, multinomial logistic regression imputation method may be impossible due to computational limitations. To rectify these limitations, we propose a two-stage imputation method. During the first stage, we utilize the Boruta variable selection method on the complete dataset to identify significant variables for the target categorical variable. Then, in the second stage, we use the important variables for the target categorical variable for logistic regression to impute missing data in binary variables, polytomous regression to impute missing data in categorical variables, and predictive mean matching to impute missing data in quantitative variables. Through analysis of both asymmetric and non-normal simulated and real data, we demonstrate that the two-stage imputation method outperforms imputation methods lacking variable selection, as evidenced by accuracy measures. During the analysis of real survey data, we also demonstrate that our suggested two-stage imputation method surpasses the current imputation approach in terms of accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.15-21
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• 2011

Cooperative diversity system can be applied to an ad-hoc network for reduction of the power consumption, for expansion of the communication range, and for improving the system performance. In a selection relay cooperative diversity system which selects the maximal SNR(Signal-to-noise ratio) relay for transmitting the source information, the selected strong relay transmits continuously under slow fading channel, consequently it reduces the network lifetime. To overcome this defect, recently the uniform power relay selection has been studied to expand the network life time. We apply the uniform power relay selection to a DOT(Double opportunistic transmit) cooperative system that select the transmit relays, of which the SNR of the transmit relays exceed both of the source-relay and the relay-destination threshold. And the performance of the system is analytically derived. The performance comparisons are made among SC(Selection combining), MRC(Maximal ratio combining), and uniform power relay selection of the cooperative diversity system. We noticed that the performance of the uniform power relay selection is inferior to that of others. It is interpreted that the uniform transmit opportunity to the selected relays for extension of the network lifetime degrades the performance.

• The Journal of Information Systems
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• v.26 no.3
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• pp.63-90
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• 2017

Purpose This study proposes a novel system trading model using case-based reasoning (CBR) based on absolute similarity threshold. The proposed model is designed to optimize the absolute similarity threshold, feature selection, and instance selection of CBR by using genetic algorithm (GA). With these mechanisms, it enables us to yield higher returns from stock market trading. Design/Methodology/Approach The proposed CBR model uses the absolute similarity threshold varying from 0 to 1, which serves as a criterion for selecting appropriate neighbors in the nearest neighbor (NN) algorithm. Since it determines the nearest neighbors on an absolute basis, it fails to select the appropriate neighbors from time to time. In system trading, it is interpreted as the signal of 'hold'. That is, the system trading model proposed in this study makes trading decisions such as 'buy' or 'sell' only if the model produces a clear signal for stock market prediction. Also, in order to improve the prediction accuracy and the rate of return, the proposed model adopts optimal feature selection and instance selection, which are known to be very effective in enhancing the performance of CBR. To validate the usefulness of the proposed model, we applied it to the index trading of KOSPI200 from 2009 to 2016. Findings Experimental results showed that the proposed model with optimal feature or instance selection could yield higher returns compared to the benchmark as well as the various comparison models (including logistic regression, multiple discriminant analysis, artificial neural network, support vector machine, and traditional CBR). In particular, the proposed model with optimal instance selection showed the best rate of return among all the models. This implies that the application of CBR with the absolute similarity threshold as well as the optimal instance selection may be effective in system trading from the perspective of returns.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.520-526
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• 2018

In this paper, considering the superposition transmission-based wireless cooperative multicast communication system (ST-CMS) with multiple relays and destinations, we propose a relay selection scheme to improve the data rate of multicast communication. In addition, we adopt the optimal power allocation coefficient for the superposition transmission to maximize the data rate of the proposed relay selection scheme. To propose the relay selection scheme, we derive an approximate expression for the data rate of the ST-CMS, and present the relay selection scheme using only partial channel state information based on the approximate expression. Moreover, we derive an approximate average data rate of the proposed relay selection scheme. Through numerical investigation, comparing the average data rates of the proposed relay selection scheme and the optimal relay selection scheme using full channel state information, we show that the proposed scheme provides extremely similar performance to the optimal scheme in the high signal-to-noise power ratio region.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.16-28
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• 2016

The study was conducted to compare and analyze the importance and performance of leisure destination selection attributes of persons who use recreational forests and rural tourism villages. This researcher investigated the use patterns of users to identify the ground for connection between recreational forest and rural tourism village, analyzed their recognition differences in physical selection attribute, program selection attribute, and service selection attribute in order for leisure destination selection, and conducted importance-performance analysis(IPA analysis) to draw a plan for connection. The main results and suggestions are presented as follows. First, recreational forests were visited by family users in order for rest and emotional cultivation and provided experience programs using simple public interest function of forest, whereas rural tourism villages were visited by family users, friends and co-workers, groups and club members to experience a variety of annual programs and understand regional cultures. It was found that it was necessary to connect natural forest with rural tourism village in order to meet the leisure needs of the people changed in diversified ways. Secondly, it was found that the connection between rural tourism village and recreational forest visited mainly for simple rest led to positive visit intention of users. It was expected that there will be various kinds of uses, including experience program participation, child education, and safe accommodations security. In other words, the connection between recreational forest and rural tourism village is an alternative to trigger actual demands and recreational forest activities with high quality. Thirdly, in the case of users of recreational forests, their performance of all selection attributes was lower than their importance of them. Therefore, overall improvements were needed. In particular, needed were the diversity, benefit, and promotion of programs, improvements in locality(themes), supply of lodges and convenient facilities, booking system, the purchase system of local special products, and professional skills of operators and managers. On contrary, the performance of program selection attribute of rural tourism village was high. Therefore, it was found that program attribute of rural tourism village was the main connection factor to activate recreational forest use. Fourthly, according to IPA analysis, the proper connections between loges, convenient facilities, and nearby touristattractions, which give high expectations and satisfaction to users, needed to remain. And it was required to make common efforts to accomplish the goal (income creation) of rural tourism village and improve booking system for visitors and performance of local special products sales opportunity. In addition, the essential factors to induce users' leisure destination selection were found to be maintenance of the use fee system of recreational forest, diversity of rural tourism village program, and retention of locality.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.2 s.161
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• pp.225-235
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• 2007

The purpose of this study is to grasp the character of consumers and the situation of domestic kidult fashion market. By grasping the distribution of kidult generation and the factors of product-selection based on products images, this research could be a substantial data to kidult associated company product planning and marketers. Subjects for this study were 213 Daegu women from 20 to 30 yearn of age who have high propensity to kidult. The statistical treatment of material used by SPSS 1.0 program consists of frequency analysis, factor analysis, multiple regression analysis, cluster analysis, and t-test. As a results, the characteristics of kidult consumers are classified as six factors. On image toward of kidult fashion goods, there was a significant difference 20 and 30 aged generation. According to fashion goods group, each group recognized on image of fashion products as follow: Group A is 'fancy', group B is 'childish', group C are 'familiarity', group D was recognized as 'fancy' and was identical to A on adjective expression, but was different A on recognition. All consumer characteristics of fun, character, girlish, nostalgia have a significant relation with the recurrence of products selection factor, and its order was character, girlish, nostalgia, and fun.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.19-33
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• 2001

Link weight analysis approach is suggested as a heuristic for selection of input nodes in artificial neural network for bankruptcy prediction. That is to analyze each input node\\\\`s link weight-absolute value of link weight between an input node and a hidden node in a well-trained neural network model. Prediction accuracy of three methods in this approach, -weak-linked-neurons elimination method, strong-linked-neurons selection method and integrated link weight model-is compared with that of decision tree and multivariate discrimination analysis. In result, the methods suggested in this study show higher accuracy than decision tree and multivariate discrimination analysis. Especially an integrated model has much higher accuracy than any individual models.