• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.6
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• pp.967-978
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• 2016

This study examines consumers' multi-channel choices in the search phase and purchasing phase stage according to price sensitivity and product characteristics in order to propose a multichannel strategy. For the research, one-way ANOVA, t-test, clustering analysis, and crosstabs are used for the descriptive analysis of 317 surveys on men and women conducted in 2014. The findings are as follows. First, consumers that both experience goods and search goods rely on surrounding advice as well as a search channel regardless of price sensitivity. Second, channel selection differs by price sensitivity when it comes to purchasing phase. Consumers with high price sensitivity tend to purchase from online channels; however, consumers with low price sensitivity tend to purchase from off line channels in cases of search goods. Meanwhile, cases of experience goods have no meaningful result. Third, consumers are divided into 3 groups by the tendency of channel selection. In case of experience goods, search channel choice is aligned with purchasing channel; however, search channel choice is not aligned with purchasing channel in search goods. This study provides clear information on fashion consumers' behavior on multi-channel choices compared to ones for search goods consumers on strategic strategies for fashion companies.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.8
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• pp.33-39
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• 2005

The maximum output torque and power developed by the machine is ultimately depended on the allowable inverter current rating and maximum voltage which the inverter can supply to the machine. Therefore, considering the limited voltage and current capacities, it is desirable to consider a control method which yields the best possible torque per ampere. In this paper, we propose fuzzy neural network(FNN) controller that combines a fuzzy control and the neural network for high performance control of induction motor drive. This controller composes antecedence of the fuzzy rules and consequence by a clustering method and a multi-layer neural networks. This controller is compounding of advantages that robust control of a fuzzy control and high-adaptive control of the neural networks. Also, this paper is proposed control of maximum torque per ampere(MTPA) of induction moor. This strategy is reposed which is simple in structure and has the honest goal of minimizing the stator current magnitude for given load torque. The performance of the proposed induction motor drive with maximum torque control using FNN controller is verified by analysis results at dynamic operation conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2313-2326
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• 2018

The method of operating a game could determine the psychological distance between the player and the game character, and thus, in the Virtual Reality, players' control methodologies are important to enhance their immersion. This study has the objective of examining the difference in games according to the method of operation based on the player's movements. This study researched the effect of the method of operating movement conforming to the movement of the character and the physical operation of the body on forming game experiences for the player. The result of performing an experiment increased reality for the game player through a controller in the shape of the actual control, to increase focus in the game. As so, game play through movements, including actual movements by the player displayed to enhance game satisfaction. In the part of media remediation field, Game can be defined as media which has their own unique hypermediacy. Especially, in the motion based game, players' movement mediates players and the game, therefore, players' movement could make players' experience augmented or immediate in accordance with the characteristics of movements. Even though sports and dances genres of motion-based games are common, RPG or adventure genres are rare. It can be explained that the characteristics of the action have been explained in the immediacy. In a game of fantasy, which is difficult to experience in real-life situations, the nature of the player's motion can increase the immersion of the game, which can contribute to utilization of players' motion and experience design in the various genres and suggestion of grounds theory. In addition, through this study, it is able to design motion-based games of various genres.

• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.2
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• pp.175-185
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• 2021

Purpose: The aim of this study was to identify core keywords and topic groups in the 'Gestational diabetes mellitus (GDM) and Breastfeeding' field of research for better understanding research trends in the past 20 years. Methods: This was a text-mining and topic modeling study composed of four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building a co-occurrence matrix, and 4) analyzing network features and clustering topic groups. Results: A total of 635 papers published between 2001 and 2020 were found in databases (Web of Science, CINAHL, RISS, DBPIA, RISS, KISS). Among them, 3,639 words extracted from 366 articles selected according to the conditions were analyzed by text network analysis and topic modeling. The most important keywords were 'exposure', 'fetus', 'hypoglycemia', 'prevention' and 'program'. Six topic groups were identified through topic modeling. The main topics of the study were 'cardiovascular disease' and 'obesity'. Through the topic modeling analysis, six themes were derived: 'cardiovascular disease', 'obesity', 'complication prevention strategy', 'support of breastfeeding', 'educational program' and 'management of GDM'. Conclusion: This study showed that over the past 20 years many studies have been conducted on complications such as cardiovascular diseases and obesity related to gestational diabetes and breastfeeding. In order to prevent complications of gestational diabetes and promote breastfeeding, various nursing interventions, including gestational diabetes management and educational programs for GDM pregnancies, should be developed in nursing fields.

• Journal of The Korean Association For Science Education
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• v.36 no.6
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• pp.935-946
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• 2016

This study aims to explore cognitive biases relating the core competences of science and instructional strategy in reducing the level of cognitive biases. The literature review method was used to explore cognitive biases and science education experts discussed the relevance of cognitive biases to science education. Twenty nine cognitive biases were categorized into five groups (limiting rational causal inference, limiting diverse information search, limiting self-regulated learning, limiting self-directed decision making, and category-limited thinking). The cognitive biases in limiting rational causal inference group are teleological thinking, availability heuristic, illusory correlation, and clustering illusion. The cognitive biases in limiting diverse information search group are selective perception, experimenter bias, confirmation bias, mere thought effect, attentional bias, belief bias, pragmatic fallacy, functional fixedness, and framing effect. The cognitive biases in limiting self-regulated learning group are overconfidence bias, better-than-average bias, planning fallacy, fundamental attribution error, Dunning-Kruger effect, hindsight bias, and blind-spot bias. The cognitive biases in limiting self-directed decision-making group are acquiescence effect, bandwagon effect, group-think, appeal to authority bias, and information bias. Lastly, the cognitive biases in category-limited thinking group are psychological essentialism, stereotyping, anthropomorphism, and outgroup homogeneity bias. The instructional strategy to reduce the level of cognitive biases is disused based on the psychological characters of cognitive biases reviewed in this study and related science education methods.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.4
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• pp.131-141
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• 2012

The miracle of Korean economic development is the benchmarking for the developing countries. Among them, the STP of Science and technology area is very important case they tring to learn from Deadeok, Korea. Ecuador and Kazakhstan have the huge natural resources and they have interested in the model of Daedeok STP. This paper study about their needs and Daedeok's capability, and effective implementing factors. This paper suggest a six one based on the Daedeok Innopolis experiences for the successful local STP. First, most important thing is human resource development strategy for the knowledge and technology transfer. Second, the construction of Engineering Center for the collaboration of industry and academy is needed. This is important to have a bargaining power to the appropriate technology transfer. Third, they need a hardware and software infrastructure to the technology commercialization. It include a incubator, manager, and complimentary asset. Fourth, they have to connect with market closely for the venture creation and growth. Fifth, the clustering is realized by the STP construction. Lastly, leadership is critical factor to the absorptive capacity.

• Journal of KIISE:Information Networking
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• v.32 no.6
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• pp.659-667
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• 2005

A Mobile Ad Hoc Network(MANET) is a multi hop wireless network with no prepared base stations or centralized administrations, where flocks of peer systems gather and compose a network. Each node operates as a normal end system in public networks. In addition to it, a MANET node is required to work as a router to forward traffic from a source or intermediate node to others. Each node operates as a normal end system in public networks, and further a MANET node work as a router to forward traffic from a source or intermediate node to the next node via routing path. Applications of MANET are extensively wide, such as battle field or any unwired place; however, these are exposed to critical problems related to network management, node's capability, and security because of frequent and dynamic changes in network topology, absence of centralized controls, restricted usage on network resources, and vulnerability oi mobile nodes which results from the special MANET's character, shared wireless media. These problems induce MANET to be weak from security attacks from eavesdropping to DoS. To guarantee secure authentication is the main part of security service In MANET because networks without secure authentication are exposed to exterior attacks. In this paper, a multistage authentication strategy based on CGSR is proposed to guarantee that only genuine and veritable nodes participate in communications. The proposed authentication model is composed of key manager, cluster head and common nodes. The cluster head is elected from secure nodes, and key manager is elected from cluster heads. The cluster head will verify other common nodes within its cluster range in MANET. Especially, ID of each node is used on communication, which allows digital signature and blocks non repudiation. For performance evaluation, attacks against node authentication are analyzed. Based on security parameters, strategies to resolve these attacks are drawn up.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.319-329
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• 2021

This study aims to investigate Korean fashion-related research trends and knowledge structures on digital transformation through information-based approaches. Accordingly, we first identified the current status of the relevant research in Korean academic literature by year and journal; subsequently, we derived key research topics through network analysis, and then analyzed major research trends and knowledge structures by time. From 2010 to 2020, we collected 159 studies published on Korean academic platforms, cleansed data through Python 3.7, and measured centrality and network implementation through NodeXL 1.0.1. The results are as follows: first, related research has been actively conducted since 2016, mainly concentrated in clothing and art areas. Second, the online platform, AR/VR, appeared as the most frequently mentioned topic, and consumer psychological analysis, marketing strategy suggestion, and case analysis were used as the main research methods. Through clustering, major research contents for each sub-major of clothing were derived. Third, major subject by period was considered, which has, over time, changed from consumer-centered research to strategy suggestion, and design development research of platforms or services. This study contributes to enhancing insight into the fashion field on digital transformation, and can be used as a basic research to design research on related topics.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.417-423
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• 2017

To provide a ecological restoration strategy considering genetic diversity of Abies koreana in Mt. Jiri, the genetic diversity and the genetic differentiation among sub-populations such as Banyabong, Byeoksoryeong, and Cheonwangbong were investigated. The average number of alleles (A) was 7.8, the average number of effective alleles ($A_e$) was 4.9, observed heterozygosity ($H_o$) was 0.578, and expected heterozygosity ($H_e$) was 0.672, respectively. The level of genetic diversity within sub-populations ($H_e=0.672$) was lower than those of both population ($H_e=0.778$) and species ($H_e=0.759$) level. However, the level of genetic diversity was high compared those of Genus Abies. Genetic differentiation was 0.014 from F-statistics ($F_{ST}$) and was 0.004 from AMOVA analysis (${\Phi}_{ST}$). There was no almost genetic differentiation among sub-populations in Mt. Jiri from bayesian clustering. Therefore, If the seeds are sampled sufficiently by selecting the parameters from three sub-populations, it is possible that we could obtain genetically appropriate materials for ecological restoration.