• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.1-8
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• 2021

This study developed low-cost and high-efficiency pavement condition monitoring technology to produce the key information required for pavement management. A noise and artificial intelligence-based monitoring system was devised to compensate for the shortcomings of existing high-end equipment that relies on visual information and high-end sensors. From idea establishment to system development, functional definition, information flow, architecture design, and finally, on-site field evaluations were carried out. As a result, confidence in the high level of artificial intelligence evaluation was secured. In addition, hardware and software elements and well-organized guidelines on system utilization were developed. The on-site evaluation process confirmed that non-experts could easily and quickly investigate and visualized the data. The evaluation results could support the management works of road managers. Furthermore, it could improve the completeness of the technologies, such as prior discriminating techniques for external conditions that are not considered in AI learning, system simplification, and variable speed response techniques. This paper presents a new paradigm for pavement monitoring technology that has lasted since the 1960s.

• Management & Information Systems Review
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• v.31 no.2
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• pp.41-59
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• 2012

ERP is a new technique of process innovation. It indicates enterprise resource planning whose purpose is an integrated total management of enterprise resources. ERP can be also seen as one of the latest management systems that organically connects by using computers all business processes including marketing, production and delivery and control those processes on a real-time basis. Currently, however, it's not easy for local enterprises to have operators who will be in charge of ERP programs, even if they want to introduce the resource management system. This suggests that it's urgently needed to train such operators through ERP education at school. But in the field of education, actually, the lack of professional ERP instructors and less effective learning programs for industrial applications of ERP are obstacles to bringing up ERP workers who are competent as much as required by enterprises. In ERP, accounting is more important than any others. Accountants are assuming more and more roles in ERP. Thus, there's a rapidly increasing demand for experts in ERP accounting. This study examined previous researches and literature concerning ERP education, identified problems with current ERP education at college and proposed how to solve the problems. This study proposed the ways of improving ERP education at college as follows. First, a prerequisite learning of ERP, that is, educating the principle of accounting should be intensified to make students get a basic theoretical knowledge of ERP enough. Second, lots of different scenarios designed to try ERP programs in business should be created. In association, students should be educated to get a better understanding of incidents or events taken place in those scenarios and apply it to trying ERP for themselves. Third, as mentioned earlier, ERP is a system that integrates all enterprise resources such as marketing, procurement, personnel management, remuneration and production under the framework of accounting. It should be noted that under ERP, business activities are organically connected with accounting modules. More importantly, those modules should be recognized not individually, but as parts comprising a whole flow of accounting. This study has a limitation because it is a literature research that heavily relied on previous studies, publications and reports. This suggests the need to compare the efficiency of ERP education between before and after applying what this study proposed to improve that education. Also, it's needed to determine students' and professors' perceived effectiveness of current ERP education and compare and analyze the difference in that perception between the two groups.

• Journal of the Korea Convergence Society
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• v.7 no.4
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• pp.39-44
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• 2016

Due to the dazzling development of IT in this IT-oriented era, information delivering technology among objects, between objects and humans, and among humans has been actively performed. As information delivery technology has been actively performed, IoT became closely related to our daily lives and ubiquitous at any time and place. Therefore, IoT has become a part of our daily lives. CoAp, a web-based protocol, is mostly used in IoT environment. CoAp protocol is mostly used in the network where transmission speed is low along with the huge loss. Therefore, it is mostly used in IoT environment. However, there is a weakness on IoT that it is weak in security. If security issue occurs in IoT environment, there is a possibility for secret information of individuals or companies to be disclosed. If attackers infect the targeted device, and infected device accesses to the wireless frequently used in public areas, the relevant device sends arp spoofing to other devices in the network. Afterward, infected devices receive the packet sent by other devices in the network after occupying the packet flow in the internal network and send them to the designated hacker's server. This study suggests counter-attacks on this issues and a method of coping with them.

• Korean Journal of Construction Engineering and Management
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• v.25 no.1
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• pp.50-61
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• 2024

The market for compact houses is growing due to the demand for floor plans prioritizing user needs. However, clients often have difficulty communicating their spatial requirements to professionals including architects because they lack the means to provide evidence, such as spatial configurations or cost estimates. This research aims to create a framework that can translate sketched data-driven spatial requirements into 3D building components in BIM models to facilitate spatial understanding and provide building performance analysis to aid in budgeting in the early design phase. The research process includes developing a process model, implementing, and validating the framework. The process model describes the data flow within the framework and identifies the required functionality. Implementation involves creating systems and user interfaces to integrate various systems. The validation verifies that the framework can automatically convert sketched space requirements into walls, floors, and roofs in a BIM model. The framework can also automatically calculate material and energy costs based on the BIM model. The developed frame enables clients to efficiently create 3D building components based on the sketched data and facilitates users to understand the space and analyze the building performance through the created BIM models.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.

• Korean Association of Arts Management
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• no.53
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• pp.127-151
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• 2020

In this study, the announced in 2010 was used to identify the flow of social value expansion on the culture and art education and to provide the future direction. In the context of culture and art education, cultural diversity is an important agenda, and thus the case of cultural diversity program by the National Museum of Contemporary Art was analyzed to discuss the social role of culture and art education. To summarize the findings, it is a program of promoting understanding on the diversity of art in the same period and various identifies of the members of our society through the exhibition of «Artist of the Year», and it is a program on cultural diversity of understanding the diversity and identity of various members in our society through the contemporary artwork. Through theme-based approach, education on cultural diversity and cooperative learning were applied to develop the sense of community. Based on the core values of education on cultural diversity, the contents of the education program on performed total of 80 times on 14 programs in 2017-2019 were analyzed. As a result, the analysis showed 9 core values, and the core values of education on cultural diversity derived through the content analysis of the education program on were ① Engagement, ② Conversation, ③ Citizenship, ④ Coexistence, ⑤ Human Rights, ⑥ Difference, ⑦ Equality, ⑧ Cooperation, ⑨ Solidarity. As the space enhancing the cultural engagement, the art museum is a place for realizing the value on cultural diversity, so it has significance as the space that embraces both cultural diversity and culture and art education. In this sense, it was identified that the discussion on the cultural diversity and culture and art education was being expanded into the perspective of various groups and communities in our society through the core values of engagement, conversation, citizenship, coexistence, human rights, difference, equality, cooperation, solidarity and direction, which were provided by the analysis of the contents on the art museum education program on cultural diversity in the National Museum of Contemporary Art.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.6-7
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• 2021

Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.

• Journal of Science Education
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• v.47 no.2
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• pp.192-210
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• 2023

This study was intended to develop the plant molecular biology experimental program using Rapid-cycling Brassica rapa (RcBr) based on the teaching steps and teaching methods of the cognitive apprenticeship model and to determine its application effects. In order to improve a subject's cognitive function and expertise on molecular biology experiments, two themes composed of a total 8 class sessions were selected: 'Identification of DFR gene in purple RcBr and non-purple RcBr' and 'Identification of RcBr's genetic polymorphism site using the DNA profiling method'. Research subjects were 18 pre-service teaching majors in biology education of H University in Chungbuk, Korea. The effectiveness of the developed program was verified by analyzing the enhancement of 'cognitive function' related to the use of molecular biology knowledge and technology, and the enhancement of 'domain-general metacognitive abilities.' The effect of the developed program was also determined by analyzing the task flow diagram provided. The developed program was effective in improving the cognitive functions of the pre-service teachers on the use of knowledge and technology of molecular biology experiments. It was especially effective to improve the higher cognitive function of pre-service teachers who did not have the previous experience. The developed program also showed a significant improvement in the task of metacognitive knowledge and in the planning, checking, and evaluation of metacognitive regulation, which are sub-elements of domain-general metacognitive abilities. It was found that the developed program's self-test activity could help the pre-service teachers to improve their metacognitive regulation. Therefore, this developed program turned out to be helpful for pre-service teachers to develop core competencies needed for molecular biology experimental classes. If the teaching and learning materials of the developed program could be reconstructed and applied to in-service teachers or high school students, it would be expected to improve their metacognitive abilities.

• Proceedings of the KSPS conference
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• 2000.07a
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• pp.235-240
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• 2000

In the age of global communication, more human exchange is extended at the grass-roots level. In the old days, language policy and language planning was based on one nation-state with one language. But high waves of globalizaiton have allowed extended human flow of exchange beyond one's national border on a daily basis. Under such circumstances, homogeneity in Japan may not allow Japanese to speak and communicate only in Japanese and only with Japanese people. In Japan, an advisory report was made to the Ministry of Education in June 1996 about what education should be like in the 21st century. In this report, an introduction of English at public elementary schools was for the first time made. A basic policy of English instruction at the elementary school level was revealed. With this concept, English instruction is not required at the elementary school level but each school has their own choice of introducing English as their curriculum starting April 2002. As Baker, Colin (1996) indicates the age of three as being the threshold diving a child becoming bilingual naturally or by formal instruction. Threre is a movement towards making second language acquisition more naturalistic in an educational setting, developing communicative competence in a more or less formal way. From the lesson of the Canadian immersion success, Genesee (1987) stresses the importance of early language instruction. It is clear that from a psycho-linguistic perspective, most children acquire basic communication skills in their first language apparently effortlessly and without systematic and formal instruction during the first six or seven years of life. This innate capacity diminishes with age, thereby making language learning increasingly difficult. The author, being a returnee, experienced considerable difficulty acquiring L2, and especially achieving native-like competence. There will be many hurdles to conquer until Japanese students are able to reach at least a communicative level in English. It has been mentioned that English is not taught to clear the college entrance examination, but to communicate. However, Japanese college entrance examination still makes students focus more on the grammar-translation method. This is expected to shift to a more communication stressed approach. Japan does not have to aim at becoming an official bilingual country, but at least communicative English should be taught at every level in school Mito College is a small two-year co-ed college in Japan. Students at Mito College are basically notgood at English. It has only one department for business and economics, and English is required for all freshmen. It is necessary for me to make my classes enjoyable and attractive so that students can at least get motivated to learn English. My major target is communicative English so that students may be prepared to use English in various business settings. As an experiment to introduce more communicative English, the author has made the following syllabus design. This program aims at training students speak and enjoy English. 90-minute class (only 190-minute session per week is most common in Japanese colleges) is divided into two: The first half is to train students orally using Graded Direct Method. The latter half uses different materials each time so that students can learn and enjoy English culture and language simultaneously. There are no quizes or examinations in my one-academic year program. However, all students are required to make an original English poem by the end of the spring semester. 2-6 students work together in a group on one poem. Students coming to Mito College, Japan have one of the lowest English levels in all of Japan. However, an attached example of one poem made by a group shows that students can improve their creativity as long as they are kept encouraged. At the end of the fall semester, all students are then required individually to make a 3-minute original English speech. An example of that speech contest will be presented at the Convention in Seoul.