• Journal of Creative Information Culture
• /
• v.5 no.3
• /
• pp.215-223
• /
• 2019

The wave of the information age gradually accelerates, and fusion analysis solutions that can utilize these knowledge data according to accumulation of various forms of big data such as large capacity texts, sounds, movies and the like are increasing, Reduction in the cost of storing data accordingly, development of social network service (SNS), etc. resulted in quantitative qualitative expansion of data. Such a situation makes possible utilization of data which was not trying to be existing, and the potential value and influence of the data are increasing. Research is being actively made to present future-oriented education systems by applying these fusion analysis systems to the improvement of the educational system. In this research, we conducted a big data analysis on Twitter, analyzed the natural language of the data and frequency analysis of the word, quantitative measure of how domestic windows education problems and outcomes were done in it as a solution.

• The Journal of the Korea Contents Association
• /
• v.14 no.5
• /
• pp.107-116
• /
• 2014

The purpose of this study is to verify the applicability of concept mapping in the process of planning social welfare program based on community network. Concept mapping is a kind of decision-making method that structuralized complex ideas and presented visually. Already, concept mapping is widely utilized in counseling, nursing and public health area to plan and evaluation their program and service. For recent, effectiveness of concept mapping has been reported. Concept mapping is a effective decision-making method that they recognize outcome gap between service provider and client, reach the outcome's consensus in counseling and nursing, medical area. In this study, we conceptualized 3rd year outcomes of Community Impact Project that was supported from Busan Chest using concept mapping. This CI project intervenes children and youth who lives in Buk-gu, Busan. Concept mapping has six stages-preparation, collecting ideas, structuring statements, representing statement, interpreting the results of the analysis, applying the results. We followed these steps. The participants were working at social welfare organizations, total 11 persons. We obtained 60 statements and analyzed using multidimensional scaling. we collected 5 clusters, cluster 1 'awareness and attitude change of children and youth', cluster 2 'social system change of children and youth', cluster 3 'friendly community formation', cluster 4 'community people change', cluster 5 'service provider change'. As a result, among total 5 clusters formed, 'awareness and attitude change of children and youth' came to the strongest outcomes. When concept mapping was applied to the program planning, the consensus of the opinion came easily in the decision-making process, and the participants were empowered. In addition, clear conceptualization on each element of the program planning was made.

• Journal of Digital Convergence
• /
• v.17 no.12
• /
• pp.509-521
• /
• 2019

The purpose of this study is to examine the patterns of the keywords in journals in the field of Cognitive Behavioral Therapy (CBT) to identify the knowledge structure of CBT studies in Korea. To compare CBT studies from Korea and abroad, 234 articles (2008-2019) published on "Cognitive Behavior Therapy in Korea" and 2,316 articles (1977-2019) published on "Cognitive Therapy and Research" were collected. The data were analyzed using NetMiner 4.3. The co-word analysis was done by calculating the cosine similarity matrix of major keywords, followed by visualizing the network. The results of this study identified the main interests of Korean CBT scholars, and categorized the knowledge structure of CBT in Korea into 9 research areas: "scale validation"; "perfectionism and entrapment"; "cognitive, emotional, and relationship characteristics of schizophrenic patients"; "cognitive characteristics and treatment of borderline personality disorder and depression/bipolar disorder patients"; "adaptation and psychological health"; "cognitive characteristics and treatment of patients with social anxiety disorder"; "causes and co-morbidities of depression"; "acceptance and commitment therapy"; and "understanding and the treatment of binge eating disorder patients." This study is meaningful in that it has reviewed the accumulated knowledge in the CBT field in Korea for the past 11 years, and suggests future tasks for development to improve the standards of CBT practice.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.12
• /
• pp.151-158
• /
• 2021

Internet of Things (IoT) technology, which provides services by connecting various objects in the real world and objects in the virtual world based on the Internet, is emerging as a technology that enables a hyper-connected society in the era of the 4th industrial revolution. Since IoT technology is a convergence technology that encompasses devices, networks, platforms, and services, various studies are being conducted. Among these studies, studies on measures that can measure service quality provided by IoT software are still insufficient. IoT software has hardware parts of the Internet of Things, technologies based on them, features of embedded software, and network features. These features are used as elements defining IoT software quality measurement metrics. However, these features are considered in the metrics related to IoT software quality measurement so far. Therefore, this paper presents a metric for reusability measurement among various quality factors of IoT software in consideration of these factors. In particular, since IoT software is used through IoT devices, services in IoT software must be designed to be changed, replaced, or expanded, and metrics that can measure this are very necessary. In this paper, we propose three metrics: changeability, replaceability, and scalability that can measure and evaluate the reusability of IoT software services were presented, and the metrics presented through case studies were verified. It is expected that the service quality verification of IoT software will be carried out through the metrics presented in this paper, thereby contributing to the improvement of users' service satisfaction.

• Korean Journal of Ecology and Environment
• /
• v.54 no.2
• /
• pp.130-141
• /
• 2021

By reviewing previous literature, we analyzed the food sources of 20 out of 29 endangered fish species from freshwater ecosystems in South Korea. A total of 19 studies reported that food sources of 20 endangered fish species included 20 phyla, 31 classes, 58 orders, 116 families, and 154 genera. Arthropod, insecta, diptera, and chironomidae were the most fed animal food sources according to different resolution of taxa index on phylum, class, order and family. Similarity, bacillariophyta, bacillariophyceae, naviculales, and cymbellaceae were the most fed abundant plant sources. A larger number of fish species were reliant on animal food sources than plant food sources. 18 of the endangered fish preyed on arthropods, whereas only 6 species consumed bacillariophyta. To characterize the feeding groups of the 20 fish species, a hierarchical clustering analysis and non-metric multidimensional scaling analysis were conducted. The fish species were divided into two groups: 1) insectivores and 2) planktivores. A network analysis, which associated the link between endangered fishes and food sources, also revealed the same two groups. The highest hub score of food sources was for macroinvertebrates, including diptera (0.47), ephemeroptera (0.42), and trichoptera (0.38), based on the network analysis. Niche breadth was used to calculate the diversity of the food sources. Phoxinus phoxinus (0.57) showed thehighest food source diversity among the fish species, whereas Iksookimia pacifica (0.01) showed the lowest. This study will be utilized for the conservation and restoration of the endangered fish species.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.52 no.1
• /
• pp.59-70
• /
• 2024

As urbanization progresses, the demand for parks and green space is increasing. Park green spaces in the city are important spaces in the city because they are recognized as spaces where people can freely engage in outdoor activities. The park service area is a measure that shows the extent to which services are provided based on distance. In this process, the concept of accessibility plays an important role, and walking, in particular, as the most basic means of transportation for people and has a great influence on the use of parks. However, the current park service area analysis focuses on discovering underprivileged areas, so detailed evaluation of beneficiary areas is insufficient. This study seeks to evaluate park service areas based on the pedestrian accessibility and the pedestrian network. Park services are services that occur when users directly visit the park, and accessibility is expected to be reflected in terms of usability. To quantify the pedestrian network, this study used space syntax to analyze pedestrian accessibility based on integration values. The integration values are an indicators that quantify the level of accessibility of the pedestrian network, and in this study, the higher the integration value, the higher the possibility of park use. The results of the study are as follows. First, Bundang-gu's park service area accounts for 43%, and includes most sections with high pedestrian accessibility, but some sections with good pedestrian accessibility are excluded. This can be seen as a phenomenon that occurs when residential areas and commercial and business areas are given priority during the urban planning process, and then park and green areas are selected. Second, based on Bundang-gu, the park service area and pedestrian accessibility within the park service area were classified by neighborhood unit. Differences appear for each individual neighborhood unit, and it is expected that the availability of the park will vary accordingly. In addition, even in areas created during the same urban planning process, there were differences in the evaluation of park service areas according to pedestrian accessibility. Using this, it is possible to evaluate individual neighborhood units that can be reflected in living area plans, and it can be used as a useful indicator in park and green space policies that reflect this in the future.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.101-123
• /
• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of Intelligence and Information Systems
• /
• v.22 no.2
• /
• pp.81-96
• /
• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.2
• /
• pp.93-98
• /
• 2016

For accurate precipitation forecasts the choice of weather factors and prediction method is very important. Recently, machine learning has been widely used for forecasting precipitation, and artificial neural network, one of machine learning techniques, showed good performance. In this paper, we suggest a new method for forecasting precipitation using DBN, one of deep learning techniques. DBN has an advantage that initial weights are set by unsupervised learning, so this compensates for the defects of artificial neural networks. We used past precipitation, temperature, and the parameters of the sun and moon's motion as features for forecasting precipitation. The dataset consists of observation data which had been measured for 40 years from AWS in Seoul. Experiments were based on 8-fold cross validation. As a result of estimation, we got probabilities of test dataset, so threshold was used for the decision of precipitation. CSI and Bias were used for indicating the precision of precipitation. Our experimental results showed that DBN performed better than MLP.

• Journal of the Korean Society for Library and Information Science
• /
• v.34 no.2
• /
• pp.21-45
• /
• 2000

The purpose of this study is to develop a new curriculum for the department of library and information science of junior college. For this purpose, First, a literature study was done along with interviews with assistant librarians, second, a questionnaries survey was conducted among professors, library administrators and assistant librarians, and the survey data were analyzed by SAS packages. Results obtained by this study are as follows; 1) Work scope of assistant librarians will be consisted of conventional library works and automated library works. And it is anticipated that the library will be transformed into an electronic library in the futrue. 2) Curriculum of department library and information science of junior college is gradually changing focused on conventional subjects toward automation and computer oriented subjects. 3) Curriculum of department of library and information science of junior college should be focused on the workshop oriented education and electronic library related subjects such as electronic library workshop, information system, data fare theory information system information network workshop.