• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3717-3723
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• 2022

For the first time, two-dimensional temporal behavior of the edge localized mode (ELM) filament is measured in the edge tokamak plasma with a multi-channel electrical probe array (MCEP). MCEP, which has 16 floating probes (4 × 4), is mounted at the far scrape-off layer (SOL) region in the KSTAR. An electron temperature and an ion flux are measured by sideband method (SBM), which can achieve two-dimensional measurements with high time resolution. Furthermore, temporal evolutions of the electron temperature and the ion flux are obtained during the ELM occurrence. In the H-mode period, short spikes from ELM bursts are observed in measured plasma parameters, and the trend is similar to that of typical Hα signal. Interestingly, when blob-like ELM filaments crash the probe, the heat flux is significantly higher in a local region of the probe array. The results show that our probe array using the SBM can measure the ELM behavior and the plasma parameters without the effect of the stray current caused by the huge device. This study can provide valuable data needed to understand the interaction between the SOL plasma and the plasma facing components (PFCs).

• Journal of Information Processing Systems
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• 제10권3호
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• pp.443-458
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• 2014

An extreme learning machine (ELM) is a recently proposed learning algorithm for a single-layer feed forward neural network. In this paper we studied the ensemble of ELM by using a bagging algorithm for facial expression recognition (FER). Facial expression analysis is widely used in the behavior interpretation of emotions, for cognitive science, and social interactions. This paper presents a method for FER based on the histogram of orientation gradient (HOG) features using an ELM ensemble. First, the HOG features were extracted from the face image by dividing it into a number of small cells. A bagging algorithm was then used to construct many different bags of training data and each of them was trained by using separate ELMs. To recognize the expression of the input face image, HOG features were fed to each trained ELM and the results were combined by using a majority voting scheme. The ELM ensemble using bagging improves the generalized capability of the network significantly. The two available datasets (JAFFE and CK+) of facial expressions were used to evaluate the performance of the proposed classification system. Even the performance of individual ELM was smaller and the ELM ensemble using a bagging algorithm improved the recognition performance significantly.

• Steel and Composite Structures
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• 제31권5호
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• pp.427-435
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• 2019

The estimation of moment and rotation in steel rack connections could be significantly helpful parameters for designers and constructors in the initial designing and construction phases. Accordingly, Extreme Learning Machine (ELM) has been optimized to estimate the moment and rotation in steel rack connection based on variable input characteristics as beam depth, column thickness, connector depth, moment and loading. The prediction and estimating of ELM has been juxtaposed with genetic programming (GP) and artificial neural networks (ANNs) methods. Test outcomes have indicated a surpass in accuracy predicting and the capability of generalization in ELM approach than GP or ANN. Therefore, the application of ELM has been basically promised as an alternative way to estimate the moment and rotation of steel rack connection. Further particulars are presented in details in results and discussion.

• 지식경영연구
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• 제14권4호
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• pp.1-17
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• 2013

As online communities proliferate, online news sites have received great attention in news media research. Although most of the online news sites provide contents for free, some have adopted the Pay-What-You-Want (PWYW) model by offering a voluntary payment option to the readers. In this study, we investigate the factors which influence subscribers' voluntary payment behavior on an online news site. Drawing upon both the Stimulus-Organism-Response (SOR) framework and the Elaboration Likelihood Model (ELM), we hypothesize that appreciation has a direct effect on the subscribers' voluntary payment behavior, whereas central factors (positive emotional content, cognitive content) and peripheral factors (news sharing, news article length) of the news articles have indirect impacts on voluntary payment behavior through the enhanced appreciation. Based on an empirical analysis of 172 news articles from the Korean online news site that adopted the PWYW pricing model (i.e., Ohmynews.com), we find that appreciation plays a critical role in voluntary payment behavior and that peripheral factors have significant impacts on appreciation. However, the impacts of central factors on appreciation are not found. By identifying influencing factors of subscribers' voluntary payment behavior on online news sites for the first time, this paper suggests a prospective alternative profit model for online news providers faced with fierce competition.

• Asia pacific journal of information systems
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• 제24권1호
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• pp.65-91
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• 2014

Our study adopted ELM (Elaboration Likelihood Model) to measure the impact of central and peripheral cues on e-healthcare website behavior and its consequence on perceived loyalty of users. While most of ELM studies did not elaborate the antecedent of both central and peripheral cues, we measured the antecedents of those information processing routes to clarify how technical and quality factors (i.e. information organization, security concern, and website attractiveness) develop the nature of either central or peripheral route. We found that information organization was the main antecedent of information quality presented on the website. Second, the results revealed that website security has a positive effect on website credibility. Third, we also found that website attractiveness was positively associated with website credibility. Fourth, consistent with elaboration likelihood model, the empirical findings suggested that information quality (central cue) and website credibility (peripheral cue) were strong predictors of behavior intention to use health website. Our findings also suggested that behavior intention to use health website significantly influenced perceived loyalty.

• 품질경영학회지
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• 제49권2호
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• pp.171-181
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• 2021

Purpose: This study aims to identify effective ways to induce water resources conservation for general water consumers. Methods: In order to find the core factors to motivate water saving behavior for general consumers, this study utilized the theory of reasoned action which is well known as one of the most frequently used theory in consumer's green behavior analysis. Results: Among six hypothesized relationships in the research model four were proved to be statistically significant. The relationship between attitude toward water savings and the water saving behavior was found to be significant but only through the behavioral intention. Conclusion: Consumers with positive attitude on water conservation will practice water saving behavior with behavioral intention. However, consumers only with high knowledge on water conservation naturally and habitually practice water saving behavior without recognizing the intention to save the water. Thus, both positive attitude on the water conservation and subjective norm must be satisfied since the two factors tend to lead to actual green behavior using different psychological routes.

• Asia pacific journal of information systems
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• 제18권3호
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• pp.147-165
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• 2008

IT education can be summarized as persuading the educatee to accept IT. The persuasion is made by delivering the messages for how-to-use and where-to-use to the educatee, which leads formulation of a belief structure for using IT. Therefore, message based persuasion theory, as well as IT acceptance theories such as technology acceptance model(TAM), would play a very important role for explaining IT education. According to elaboration likelihood model(ELM) that has been considered as one of the most influential persuasion theories, people change attitude or perception by two routes, central route and peripheral route. In central route, people would think critically about issue-related arguments in an informational message. In peripheral route, subjects rely on cues regarding the target behavior with less cognitive efforts. Moreover, such persuasion process is not a one-shot program but continuous repetition with feedbacks, which leads to changing a belief structure for using IT. An educatee would get more knowledge and experiences of using IT as following an education program, and be more dependent on a central route than a peripheral route. Such change would reformulate a belief structure which is different from the intial one. The objectives of this study are the following two: First, an identification of the relationship between ELM and belief structures for using IT. Especially, we analyze the effects of message interpretation through both of central and peripheral routes on perceived usefulness which is an important explaining variable in TAM and perceived use control which have perceived ease of use and perceived controllability as sub-dimensions. Second, a longitudinal analysis of the above effects. In other words, change of the relationship between interpretation of message delivered by IT education and beliefs of IT using is analyzed longitudinally. For achievement of our objectives, we suggest a research model, which is constructed as three-layered. While first layer has a dependent variable, use intention, second one has perceived usefulness and perceived use control that has two sub-concepts, perceived ease of use and perceived controllability. Finally, third one is related with two routes in ELM, source credibility and argument quality which are operationalization of peripheral route and central route respectively. By these variables, we suggest five hypotheses. In addition to relationship among variables, we suggest two additional hypotheses, moderation effects of time in the relationships between perceived usefulness and two routes. That is, source credibility's influence on perceived usefulness is decreased as time flows, and argument quality's influence is increased. For validation of it, our research model is tested empirically. With measurements which have been validated in the other studies, we survey students in an Excel class two times for longitudinal analysis. Data Analysis is done by partial least square(PLS), which is known as an appropriate approach for multi-group comparison analysis with a small sized sample as like this study. In result. all hypotheses are statistically supported. One of theoretical contributions in this study is an analysis of IT education based on ELM and TAM which are considered as important theories in psychology and IS theories respectively. A longitudinal analysis by comparison between two surveys based on PLS is also considered as a methodological contribution. In practice, finding the importance of peripheral route in early stage of IT education should be notable.

• 한국조경학회지
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• 제39권1호
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• pp.56-64
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• 2011

생태관광은 환경을 보존하고 지역주민의 복지를 유지하는 자연지역으로의 책임 있는 관광이라고 정의할 수 있으며, 지속가능한 관광을 위한 대안관광의 하나로 최근에 들어 생태관광에 대한 연구와 생태관광 활동이 활발해지고 있다. 본 연구는 정교화 가능성 모형(elaboration likelihood model: ELM, Petty and Cacioppo, 1986)이론을 바탕으로 생태관광활동에 참여하는 관광객은 높은 정교화 수준의 고관여 집단으로 이미 친환경 태도를 형성하고 있는 집단이며, 이들의 신념과 태도에 일치하는 생태관광활동 참여는 순환적으로 친환경 태도를 강화할 것으로 가설을 설정하였다. 이를 검증하기 위하여 2010년 9월에 람사르 등록 습지로 우리나라의 대표적인 생태관광지라 할 수 있는 우포늪 습지에서 방문객 183명을 대상으로 실증적으로 생태관광활동에 따른 관광환경태도의 변화를 논의하였다. 생태관광활동 참여 이전과 이후의 관광환경 태도의 변화는 '반환경적 행위동조 요인' > '추억 표상 요인' > '반환경적 일탈 요인'의 순으로 유의한 차이가 있는 것으로 나타났다. 이러한 결과는 생태관광활동 참여자는 관광활동 중에 생태관광 자원의 본질적 속성에 의한 영향과 다양한 환경교육 및 체험프로그램 등을 제공받음으로써 방문 전에 형성하고 있는 친환경적인 태도를 보다 정교하게 강화하는 것으로 이해할 수 있다. 또한, 본 연구의 조사대상지인 우포늪 생태관광지는 생태관광 개발 및 운영에 있어서 기본적으로 친환경 태도의 형성과 강화의 목적을 달성하고 있다고 평가할 수 있다. 특히, 요인별 변화에서 생태관광활동 참여가 양극단의 환경태도보다는 '반환경적 행위동조'라는 중간적 환경태도 변화에 더 크게 작용하는 것으로 나타났는데, 이는 생태관광활동 참여를 통하여 '반환경적 행위동조'태도를 친환경적으로 완화할 수 있다는 것으로 생태관광의 역할을 확인하는 중요한 결과이다.

• 패션비즈니스
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• 제20권6호
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• pp.32-51
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• 2016

KakaoTalk has become a reputed mobile social network and an inseparable part of people's lives by leading the mobile industry in South Korea. However, there is a lack of studies in academia regarding perception of the consumers and assessment toward the mobile marketing and services by KakaoTalk. Based on the theoretical orientation of Elaboration Likelihood Model (ELM: Petty & Cacioppo, 1986) and electronic service quality (E-S-QUAL: Parasuraman, Zeithaml, & Malhotra, 2005), this study investigates the effects of information sources (Charles & Richard, 1988), and examines the consumer perception toward the service quality of KakaoTalk. A total of 209 responses were collected, using a self-administered survey in Seoul and Gyeonggi province, South Korea from March 2015 to June 2015. A seven-point Likert scale survey was developed to measure the information sources (i.e., argument quality, post popularity, and post attractiveness), electronic service quality (i.e., efficiency, fulfillment, privacy, and system availability), attitude (i.e., usefulness, preference, and overall attitude), and behavioral intention (i.e., like intention, share intention, and purchase intention). This study reveals a consensus that an online environment is different from the traditional retail context in terms of information source and service quality. Specifically, the results indicate that argument quality greatly impacts the attitudes of the individuals and their behavioral intention toward mobile shopping via social media channel. The most powerful factor among E-S-QUAL is "efficiency." This dimension of service quality influences the customer perception of usefulness and preference as well as share and like intention toward mobile shopping on KakaoTalk.

• Steel and Composite Structures
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• 제34권5호
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.