• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Journal of Arbitration Studies
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• v.15 no.2
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• pp.3-35
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• 2005

The meaning of Online ADR lies in the prompt and economical resolution of disputes by applying the information/communication element (Internet) to existing ADR. However, if the promptness and economical efficiency are overemphasized, the fairness and appropriateness of dispute resolution may be compromised and consequently Online ADR will be belittled and criticized as second-class trials. In addition, as communication is mostly made using texts in Online ADR it is difficult to investigate cases and to create atmosphere and induce dynamic feelings, which are possible in the process of dispute resolution through face-to-face contact. Despite such difficulties, Online ADR is expanding its area not only in online but also in offline due to its advantages such as promptness, low expenses and improved resolution methods, and is expected to develop rapidly as the electronic government decided to adopt it in the future. Accordingly, the following points must be focused on for the continuous First, in the legal and institutional aspects for the development of Online ADR, it is necessary to establish a framework law on ADR. A framework law on ADR comprehending existing mediation and arbitration should be established and it must include contents of Online ADR, which utilizes electronic communication means. However, it is too early to establish a separate law for Online ADR because Online ADR must develop based on the theoretical system of ADR. Second, although Online ADR is expanding rapidly, it may take time to be settled as a tool of dispute resolution. As discussed earlier, additionally, if the amount of money in dispute is large or the dispute is complicated, Online ADR may have a negative effect on the resolution of the dispute. Thus, it is necessary to apply Online ADR to trifle cases or domestic cases in the early stage, accumulating experiences and correcting errors. Moreover, in order to settle numerous disputes effectively, Online ADR cases should be analyzed systematically and cases should be classified by type so that similar disputes may be settled automatically. What is more, these requirements should reflected in developing Online ADR system. Third, the application of Online ADR is being expanded to consumer disputes, domain name disputes, commercial disputes, legal disputes, etc., millions of cases are settled through Online ADR, and 115 Online ADR sites are in operation throughout the world. Thus Online ADR requires not temporary but continuous attention, and mediators and arbitrators participating in Online ADR should be more intensively educated on negotiation and information technologies. In particular, government-led research projects should be promoted to establish Online ADR model and these projects should be supported by comprehensive researches on mediation, arbitration and Online ADR. Fourth, what is most important in the continuous development and expansion of Online ADR is to secure confidence in Online ADR and advertise Online ADR to users. For this, incentives and rewards should be given to specialists such as lawyers when they participate in Online ADR as mediators and arbitrators in order to improve their expertise. What is more, from the early stage, the government and public institutions should have initiative in promoting Online ADR so that parties involved in disputes recognize the substantial contribution of Online ADR to dispute resolution. Lastly, dispute resolution through Online ADR is performed by organizations such as Korea Institute for Electronic Commerce and Korea Consumer Protection Board and partially by Korean Commercial Arbitration Board. Online ADR is expected to expand its area to commercial disputes in offline in the future. In response to this, Korean Commercial Arbitration Board, which is an organization for commercial dispute resolution, needs to be restructured.

• Korean journal of communication and information
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• v.61
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• pp.74-97
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• 2013

Asia is developing rapidly in 21st century. Human and material exchanges between Korea and Asian countries have greatly increased. Korea entered the multicultural society. It became important for Korean people to understand Asia more correctively. Korean media can play a key role for this. In this point, I analyzed 1786 news contents reported in 2011 by four Korean newspapers(Chosun Ilbo, Dong-A Ilbo, Hankyoreh newspaper, Kyungh Kyunghyang Daily News), to see differences of Asia and West news aspect and its reason, focusing on news topic, amount of news, news tone and foreign media sources. In amount of news, the percent of West(54.3%) was higher than that of Asia news(45.7%). In news tone, negative news were the most in Asia news, but the least in West news. Korean newspaper showed more positive attitude to West than Asia. 1786 news were classified into seven topics(morality and justice, politics, economics and science, society, diplomacy and national defense, human interest, people). In news amount of seven topics, Korean newspapers reported hard news like morality and justice more than soft news like human interest about Asia. However they reported many soft news about West besides hard news. In news topics and tone, hard news showed negative tone most and soft news showed neutral or positive tone most. As a result, Korean news showed the negative attitude to Asia and the positive to West. Among five main sources(media, government, private organization, individual and material), only media source affected the differences of news attitude to Asia and West. Asia media source took the more positive attitude to Asia than West. West media took the negative attitude to Asia most and the neutral attitude to West most. Korean newspapers used West media as main sources in the news of all areas except East Asia. As a result, Korean newspapers showed the West-centered-attitude and reported the negative news more than neutral and positive about Asia. It was suggested that Korean newspapers had better increase Asia news in diverse spheres by the direct reporting of the correspondent and the more use of Asia media through the internet.

• The Korean Journal of Elementary Counseling
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• v.11 no.2
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• pp.299-320
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• 2012

We have information through a variety of media such as language, pictures and internet. Since we get information through texts mostly, we can say that reading ability which enables a person to read a text and understand its meaning basically is the most essential for people to possess. Taking the advantage of the fact that a school is a place where learning and daily-life guidance can be made at the same time, we need to try encouraging students to involve in learning process and feel a sense of accomplishment by adding consultation between a teacher and a student or between a student and a student in Korean subject. This study selected two fifth grade classes of an elementary school of small and medium-sized city as an experimental group and a control group respectively and applied reading strategy program by using interaction of complementary lesson as the number of ten times during five weeks. It focused on making students interested in complementary class and encouraging them to become active participants. This study's goal is to see if the reading strategy program affects students' reading comprehension, metacognition and a sense of self-efficacy The results of the study are as in the following: first, the reading strategy program of complementary lesson is effective in students' reading comprehension and a range of factual understanding and sentimental understanding. Second, the reading strategy program of complementary lesson is effective in adjustment area as a subordinate factor of metacognition. Third, the reading strategy program of complementary lessonis effective in students' sense of self-efficacy. It is shown that experience of using new reading strategy and successful experience and help in peer-group members have a positive effects on a student's sense of self-efficacy. Forth, as the result of satisfaction evaluation over the program with the students' activity report and researchers' observation results, the study shows that the organization and operation of the program influences on students' effort and participation to reach the goal together positively. Through the results as above, we can say that the reading strategy program of complementary lesson have a positive effect on a student's reading comprehension, metacognition and a sense of self-efficacy.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Proceedings of the Korean DIstribution Association Conference
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• 2001.11b
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• pp.125-141
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• 2001

In this paper, the current problems of logistics industry in Korea and their possible solutions were discussed. With Korea Telecoms KT-Logis, the supplier and demander of logistics service would not have to invest large sum of money into their computer system. All they need is just a computer with internet connected. What KT-Logis influence on the logistics industry are the following; 1. Many logistics service supplier and demander can do the business on the web with one computer system. 2. This web based computer system does not only work on the office but also apply on the field worker such as delivery personnel or even the forwarder with mobile phone. 3. KT-Logis is an integrated system which cover the broad arrange of logistics management from truck management to customer relations management. 4. Finally, KT-Logis is web based systems which suits for current e-business and mobile environment. In future, more studies should be done to develop more progressive integrated logistics information systems with enterprise resource planning(ERP) and supply chain management(SCM).

• Geophysics and Geophysical Exploration
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• v.13 no.3
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• pp.268-276
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• 2010

Earthquake Hazard Mitigation Law was activated into force on March 2009. By the law, the obligation to monitor the effect of earthquake on the facilities was extended to many organizations such as gas company and local governments. Based on the estimation of National Emergency Management Agency (NEMA), the number of free-surface acceleration stations would be expanded to more than 400. The advent of internet protocol and the more simplified operation have allowed the quick and easy installation of seismic stations. In addition, the dynamic range of seismic instruments has been continuously improved enough to evaluate damage intensity and to alert alarm directly for earthquake hazard mitigation. For direct visualization of damage intensity and area, Real Time Intensity COlor Mapping (RTICOM) is explained in detail. RTICOM would be used to retrieve the essential information for damage evaluation, Peak Ground Acceleration (PGA). Destructive earthquake damage is usually due to surface waves which just follow S wave. The peak amplitude of surface wave would be pre-estimated from the amplitude and frequency content of first arrival P wave. Earthquake Early Warning (EEW) system is conventionally defined to estimate local magnitude from P wave. The status of EEW is reviewed and the application of EEW to Odesan earthquake is exampled with ShakeMap in order to make clear its appearance. In the sense of rapidity, the earthquake announcement of Korea Meteorological Agency (KMA) might be dramatically improved by the adaption of EEW. In order to realize hazard mitigation, EEW should be applied to the local crucial facilities such as nuclear power plants and fragile semi-conduct plant. The distributed EEW is introduced with the application example of Uljin earthquake. Not only Nation-wide but also locally distributed EEW applications, all relevant information is needed to be shared in real time. The plan of extension of Korea Integrated Seismic System (KISS) is briefly explained in order to future cooperation of data sharing and utilization.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.25-41
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• 2014

Recently, the number of social media users has increased rapidly because of the prevalence of smart devices. As a result, the amount of real-time data has been increasing exponentially, which, in turn, is generating more interest in using such data to create added value. For instance, several attempts are being made to analyze the relevant search keywords that are frequently used on new portal sites and the words that are regularly mentioned on various social media in order to identify social issues. The technique of "topic analysis" is employed in order to identify topics and themes from a large amount of text documents. As one of the most prevalent applications of topic analysis, the technique of issue tracking investigates changes in the social issues that are identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has two limitations. First, when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. This creates practical limitations in the form of significant time and cost burdens. Therefore, this traditional approach is difficult to apply in most applications that need to perform an analysis on the additional period. Second, the issue is not only generated and terminated constantly, but also one issue can sometimes be distributed into several issues or multiple issues can be integrated into one single issue. In other words, each issue is characterized by a life cycle that consists of the stages of creation, transition (merging and segmentation), and termination. The existing issue tracking methods do not address the connection and effect relationship between these issues. The purpose of this study is to overcome the two limitations of the existing issue tracking method, one being the limitation regarding the analysis method and the other being the limitation involving the lack of consideration of the changeability of the issues. Let us assume that we perform multiple topic analysis for each multiple period. Then it is essential to map issues of different periods in order to trace trend of issues. However, it is not easy to discover connection between issues of different periods because the issues derived for each period mutually contain heterogeneity. In this study, to overcome these limitations without having to analyze the entire period's documents simultaneously, the analysis can be performed independently for each period. In addition, we performed issue mapping to link the identified issues of each period. An integrated approach on each details period was presented, and the issue flow of the entire integrated period was depicted in this study. Thus, as the entire process of the issue life cycle, including the stages of creation, transition (merging and segmentation), and extinction, is identified and examined systematically, the changeability of the issues was analyzed in this study. The proposed methodology is highly efficient in terms of time and cost, as it sufficiently considered the changeability of the issues. Further, the results of this study can be used to adapt the methodology to a practical situation. By applying the proposed methodology to actual Internet news, the potential practical applications of the proposed methodology are analyzed. Consequently, the proposed methodology was able to extend the period of the analysis and it could follow the course of progress of each issue's life cycle. Further, this methodology can facilitate a clearer understanding of complex social phenomena using topic analysis.

• Archives of design research
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• v.18 no.1 s.59
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• pp.39-48
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• 2005

In the age of digital culture, TV broadcasting is exercising more influence as a information and communication medium compared to past. With the appearance of satellite broadcasting service in 2002, the broadcasting environment became a diversified field of local TV, cable TV, satellite, internet, etc. and created the time of multi-media and multi-channel. This ongoing change of broadcasting environment made the passive audience of the past, active image makers and new accepters, participants and users of communications, who know how to choose and use media as the active centerpiece, The active acceptor as the centerpiece of channel selections has become the center of the broadcasting, whereby they pick up and enjoy their favorite TV programs and came to remember the list of their favorite channels and zap them finally. In this point of spotting their favorite channels and improving the degree of recognition for the channels, the development of the noticeable brand for a particular program has made a great contribution. The aim of this study, therefore, is to recognize the factors, which are important in the habits of watching TV and to develop professional brands for TV broadcasting programs. The range of the survey for this study was home news programs and broadcasting stations abroad, which were on air from March to May in 2004. The focus of the survey was universal and professional news programs. Through this study, it was ascertained that, in the case of news, developing a brand for an anchor as well as for a professional brand of TV program could be an important element.