• Korean Journal of Cognitive Science
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• v.13 no.3
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• pp.47-60
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• 2002

The study investigated the effects of types of presentation and cognitive load on multimedia learning. In experiment 1, subject were 90 elementary school students. The subject were assigned in three conditions: Narration and Text (NT) condition, Animation and Narration(AN) condition, Animation and Text(AT) condition. The result showed that AN condition improved the learning performances in comparison with AT condition, NT condition. Experiment 2 was administrated to 87 undergraduate students. They were participated in three conditions, also. The conditions were Animation and Text (AT) condition, Animation and Narration (AN) condition, Animation, Narration and Text (ANT) condition. the results showed that AN condition was greater in AT, ANT condition. The results from a series of these experiments imply that varying the types of presentation of identical learning materials had influences on the performances. Multimedia presentation(animation and verbal conditions) improved the learning performances in comparison with monomedia presentation(verbal condition), and the advantage was raised when learners were provided the learning material in the multimodal and multimedia environment(AN condition). Also, it came out that redundant text identical to narration disrupted learning when learners were in the picture (either animation or illustration) and narration conditions. Likewise, also for adults, performances were improved in the multimodal conditions and redundant text identical to narration was not helpful for learning. These results are evidences for the dual-coding theory and the cognitive load theory.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.47-65
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• 2021

This study aims to identify specific topics, trends, and structural characteristics of scholarly communication research, based on 1,435 articles published from 1970 to 2018 in the Scopus database through Latent Dirichlet Allocation topic modeling, serial analysis, and network analysis. Topic modeling, time series analysis, and network analysis were used to analyze specific topics, trends, and structures, respectively. The results were summarized into three sets as follows. First, the specific topics of scholarly communication research were nineteen in number, including research resource management and research data, and their research proportion is even. Second, as a result of the time series analysis, there are three upward trending topics: Topic 6: Open Access Publishing, Topic 7: Green Open Access, Topic 19: Informal Communication, and two downward trending topics: Topic 11: Researcher Network and Topic 12: Electronic Journal. Third, the network analysis results indicated that high mean profile association topics were related to the institution, and topics with high triangle betweenness centrality, such as Topic 14: Research Resource Management, shared the citation context. Also, through cluster analysis using parallel nearest neighbor clustering, six clusters connected with different concepts were identified.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Research in Mathematical Education
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• v.15 no.2
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• pp.127-140
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• 2011

"Statistical literacy" is important to be an effective citizen ([Gal, I. (2005). Towards "probability literacy" for all citizens: Building blocks and instructional dilemmas. In: G. A. Jones (Ed.), Exploring probability in school: Challenges for teaching and learning (pp. 39-63). New York: Springer]). Probability and statistics has been connected with real context and can be used to stimulate students' creative abilities. This study aims at identifying the extent that textbooks in three countries include experimental probability concepts and non-routine, open-ended, application and contextual problems. How well textbooks reflect real application situations is important in the sense that students can employ probability concepts when solving real world problems. Results showed that three textbook series did not mention experimental probability. Furthermore, all of text-books had more routine, close-ended, knowing, and non-contextual problems.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.11
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• pp.1009-1014
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• 2007

A detailed study on aged sleeves for old transmission lines was carried out to clarify the deterioration of sleeves and the condition of installation. A lot of removed aged sleeves from transmission lines were investigated. Many biased installed cases and corrosion of steel sleeve part were found. These defects can cause a serious accident such as blackout during operating. The temperature distribution within sleeve of ACSR conductor was precisely measured and examined, conducted as part of series of studies on large currents in transmission lines. According to measurements of the conductor temperature near a joint(sleeve and clamp), the electrical resistance of joint is lower than that of the same length conductor. The detailed results were presented in the text.

• Asia Marketing Journal
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• v.21 no.3
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• pp.65-82
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• 2019

This study examines the relationship between social media advertisement and customer interest in the context of luxury brands. Further, this study investigates the effective ways to utilize visual types (pictorial advertisement and video advertisement) and contents types (website link and hash-tag) in social media advertising by proposing a time-series model to estimate the long-term effect of social media advertising on social search. We find that the pictorial advertisements are more effective than video advertisements, which provides a different result from previous existing research. In addition, advertisements using hashtags are more effective than web links due to efficiency of the search feature. Finally, since the number of brand fans also have a positive effect on advertising interest, it is essential to utilize social media advertising for the enhancement of customers' interests. Confirming that the effectiveness of social media advertising varies depending on how the visual contents and text are presented, this research can help marketing managers to assess predicted outcomes of using various methods of social media advertising.

• The Journal of Information Systems
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• v.31 no.1
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• pp.289-304
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• 2022

Purpose The development of the network and mobile industries has induced companies to invest in information systems, leading a new industrial revolution. The Journal of Information Systems, which developed the information system field into a theoretical and practical study in the 1990s, retains a 30-year history of information systems. This study aims to identify academic values and research trends of JIS by analyzing the trends. Design/methodology/approach This study aims to analyze the trend of JIS by compounding various methods, named as TLS mining analysis. TLS mining analysis consists of a series of analysis including Term Frequency-Inverse Document Frequency (TF-IDF) weight model, Latent Dirichlet Allocation (LDA) topic modeling, and a text mining with Semantic Network Analysis. Firstly, keywords are extracted from the research data using the TF-IDF weight model, and after that, topic modeling is performed using the Latent Dirichlet Allocation (LDA) algorithm to identify issue keywords. Findings The current study used the summery service of the published research paper provided by Korea Citation Index to analyze JIS. 714 papers that were published from 2002 to 2012 were divided into two periods: 2002-2011 and 2012-2021. In the first period (2002-2011), the research trend in the information system field had focused on E-business strategies as most of the companies adopted online business models. In the second period (2012-2021), data-based information technology and new industrial revolution technologies such as artificial intelligence, SNS, and mobile had been the main research issues in the information system field. In addition, keywords for improving the JIS citation index were presented.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.47 no.6
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• pp.411-426
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• 2021

Combining different procedures to reduce the number of surgical sessions and patient discomfort in implant placement and sinus floor elevation has been recommended, and evidence supports good outcomes. The aim of this study was to review the results of clinical studies on sinus floor elevation through extraction sockets and simultaneous immediate posterior implant placement. An electronic search was carried out in PubMed, Scopus, and Web of Science to find English articles published in or before August 2020. A manual search was also performed. Titles, abstracts, and the full-text of the retrieved articles were studied. Thirteen studies met our eligibility criteria: 6 retrospective case series, 3 case reports, 2 prospective cohort case-series, 1 prospective case series, and 1 randomized controlled trial. Overall, 306 implants were placed; 2 studies reported implant survival rates of 91.7% and 98.57%. The others either did not report the survival rate or reported 100% survival. Sinus floor elevation through a fresh extraction socket and simultaneous immediate implant placement appears to be a predictable modality with a high success rate. However, proper case selection and the expertise of the clinician play fundamental roles in the success of such complex procedures.

• Management & Information Systems Review
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• v.22
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• pp.25-59
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• 2007

These days, a lot of information and knowledge is being produced and accumulated constantly, which makes it difficult for a person to get the exact information or knowledge in simple way that he or she wants to get. It is also true in college and university. A lot of data is increasing so fast that a student cannot achieve his or her goal in learning with the text. This means that it is necessary to bring a change in the way of teaching and learning from only simple lectures. So in this treatise, we try to develop the method of the introduction and operation of center for teaching and learning. In order to accomplish the purposes, this research has examined the questionare and domestic colleges and universities.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.461-468
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• 2001

Large-scale distributed applications based on Internet and client/server applications have to deal with series of problems such as load balancing, unpredictable communication delays, partial errors, and networking failures. Therefore, sophisticated applications such as teleconferencing, video-on-demand, and concurrent software engineering require an abstracted communication. In this paper, we present our design, implementation and performance analysis of group communication using the CORBA ORB, JAVA RMI, Socket based on distributed computing. We anticipate our study may apply to the various field of applications such as fault-tolerant client/server system, groupware, scalable text retrieval system, and financial information systems.