• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.41-63
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• 2023

As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.8
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• pp.1157-1167
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• 2007

Internet communications have provoked new forms of online word-of-mouth(WOM) communication and it has become more powerful. At this point, this study analyses the effects of information characteristics(direction, consensus) of online WOM. Especially, quasi-experiment can systematically manipulate the direction and the consensus of online WOM information and it perceived the difference in the effects in this study. Female consumers who have purchased clothing at online shopping mall in past 6 months participated in the experiment by completing 4 type questionnaires(N=600). Data are analyzed using Cronbach's ${\alpha}$, t-test, one way ANOVA, two-way ANOVA, Duncan's multiple range test. The Results of this study are as follows: (1) The direction of online WOM information significantly influences consumer's reliability of information, attitude, and purchase intentions. These effects are more significant when negative WOM information than positive information and two-sided information was given. (2) Though there is the difference in reliability of information, the consensus of online WOM information does not have influences on consumer's attitude and purchase intentions. (3) Consumer's clothing involvement is related to WOM information searching. The highly involved consumer is more effected by online WOM information than the lowly one.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.651-658
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• 2011

An efficient modified $D^*$ lite algorithm is suggested, which can perform online path planning for mobile robots in dynamic indoor environment. Online path planning should plan and execute alternately in a short time, and hence it enables the robot avoid unknown dynamic obstacles which suddenly appear on robot's path. Based on $D^*$ Lite algorithm, we improved representation of edge cost, heuristic function, and priority queue management, to build a modified $D^*$ Lite algorithm. Performance of the proposed algorithm is revealed via extensive simulation study.

• Natural Product Sciences
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• v.17 no.3
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• pp.206-211
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• 2011

High-performance liquid chromatography coupled to an online $ABTS^+$-based assay (online HPLC-$ABTS^+$) system was used to determine the principal antioxidants in Cudrania tricuspidata fruits. Six prenylated isoflavonoids (1 - 6) were isolated from C. tricuspidata fruits according to the online HPLC-$ABTS^+$ system. The structures of isolated compounds, alpiniumisoflavone (1), 6,8-diprenylorobol (2), 6,8-diprenylgenistein (3), pomiferin (4), 4'-methylalpiniumisoflavone (5), and osajin (6) were identified by their retention time, UV spectra, ESI-MS, and NMR data. Among these compounds, 6,8-diprenylorobol (2) and pomiferin (4) reduced A2E photooxidation in a dose dependent manner.

• Journal of Information Processing Systems
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• v.6 no.1
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• pp.43-52
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• 2010

In the secure communication areas, three-party authenticated key exchange protocol is an important cryptographic technique. In this protocol, two clients will share a human-memorable password with a trusted server, in which two users can generate a secure session key. On the other hand the protocol should resist all types of password guessing attacks. Recently, STPKE' protocol has been proposed by Kim and Choi. An undetectable online password guessing attack on STPKE' protocol is presented in the current study. An alternative protocol to overcome undetectable online password guessing attacks is proposed. The results show that the proposed protocol can resist undetectable online password guessing attacks. Additionally, it achieves the same security level with reduced random numbers and without XOR operations. The computational efficiency is improved by $\approx$ 30% for problems of size $\approx$ 2048 bits. The proposed protocol is achieving better performance efficiency and withstands password guessing attacks. The results show that the proposed protocol is secure, efficient and practical.

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.4
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• pp.577-586
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• 2014

Purpose: This study investigates patterns of small group interaction and examines the influence among graduate nursing students of online collaborative learning strategies on small group interaction patterns, task performance and learning attitude in web-based team learning environments. Method: To analyze patterns of small group interaction, group discussion dialogues were reviewed by two instructors. Groups were divided into two categories depending on the type of feedback given (passive or active). For task performance, evaluation of learning processes and numbers of postings were examined. Learning attitude toward group study and coursework were measured via scales. Results: Explorative interactions were still low among graduate nursing students. Among the students given active feedback, considerable individual variability in interaction frequency was revealed and some students did not show any specific type of interaction pattern. Whether given active or passive feedback, groups exhibited no significant differences in terms of task performance and learning attitude. Also, frequent group interaction was significantly related to greater task performance. Conclusion: Active feedback strategies should be modified to improve task performance and learning attitude among graduate nursing students.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.83-92
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• 2022

With the digital transformation of the entire industry, software competency has become the core competency for the future talent. However, it is difficult to find researches related to the corporate education for improving employee's software capability. Therefore, this study tried to verify the relationship between factors affecting the learning performance of employees in online software education. For this purpose, a survey of 223 employees with online software education experience was analyzed using the SPSS PROCESS macro. As a result of analysis, perceived usefulness and self-regulated learning have been found to have a significant multiple mediating effect on learning performance by digital literacy and satisfaction. This suggests that not only learner factors but also the characteristics of education should be considered. The results of this study are expected to be helpful in designing effective online education programs.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.333-339
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• 2022

In this study, we study the effects of note-taking skills on students' academic performance, satisfaction, and concentration, and immersiveness when students are taking online classes. The Cornell note format was used for the note-taking skills. The survey result shows that note-taking skills in online class increase students' diligence, participation, and concentration. We find a strong positive correlation between the number of Cornell note submission and academic performance, and we show that the association between two is a statistically significant by using simple/multiple regression analysis. The multiple regression result shows that one unit increase in the Cornell note submission is associated with the increase in 0.253 midterm score on average. In addition, one unit increase in the Cornell note submission is associated with increase in 0.287 final exam score on average. Further, we conduct bootstrapping regression as a robustness test and show that the results are consistent with the simple/multiple regression results. These analyses show that Cornell note taking skills in online classes can be beneficial for students to improve the quality of their learning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1B
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• pp.17-21
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• 2007

In this paper, we propose new on-line processor management algorithms that manage heterogeneous multimedia services while maximizing energy efficiency. These online management mechanisms are combined in an integrated scheme for higher system performance and energy efficiency. The most important feature of our proposed scheme is its adaptability, flexibility and responsiveness to current network conditions. Simulation results clearly indicate the superior performance of our proposed scheme to strike the appropriate performance balance between contradictory requirements.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.2
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• pp.184-189
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• 2013

This paper proposes a method for improving the performance of a position sensorless control system for a slotless surface permanent magnet synchronous motor (SPMSM) in a very low-speed region. In position sensorless control based on a motor model, accurate motor parameters are required because parameter errors would affect position estimation accuracy. Therefore, online parameter identification is applied in the proposed system. The error between the reference voltage and the voltage applied to the motor is also affect position estimation accuracy and stability, thus it is compensated to ensure accuracy and stability of the sensorless control system. In this study, two voltage error compensation methods are used, and the effects of the compensation methods are discussed. The performance of the proposed sensorless control method is evaluated by experimental results.