• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Journal of Korean Academy of Nursing
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• v.13 no.1
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• pp.7-21
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• 1983

For the flexible and rational distribution of limited existing health resources based on measurements of individual risk, the socalled Risk Approach is being proposed by the World Health Organization as a managerial tool in maternal and child health care program. This approach, in principle, puts us under the necessity of developing a technique by which we will be able to measure the degree of risk or to discriminate the future outcomes of pregnancy on the basis of prior information obtainable at prenatal care delivery settings. Numerous recent studies have focussed on the identification of relevant risk factors as the Prior infer mation and on defining the adverse outcomes of pregnancy to be dicriminated, and also have tried on how to develope scoring system of risk factors for the quantitative assessment of the factors as the determinant of pregnancy outcomes. Once the scoring system is established the technique of classifying the patients into with normal and with adverse outcomes will be easily de veloped. The scoring system should be developed to meet the following four basic requirements. 1) Easy to construct 2) Easy to use 3) To be theoretically sound 4) To be valid In searching for a feasible methodology which will meet these requirements, the author has attempted to apply the“Likelihood Method”, one of the well known principles in statistical analysis, to develop such scoring system according to the process as follows. Step 1. Classify the patients into four groups: Group $A_1$: With adverse outcomes on fetal (neonatal) side only. Group $A_2$: With adverse outcomes on maternal side only. Group $A_3$: With adverse outcome on both maternal and fetal (neonatal) sides. Group B: With normal outcomes. Step 2. Construct the marginal tabulation on the distribution of risk factors for each group. Step 3. For the calculation of risk score, take logarithmic transformation of relative proport-ions of the distribution and round them off to integers. Step 4. Test the validity of the score chart. h total of 2, 282 maternity records registered during the period of January 1, 1982-December 31, 1982 at Ewha Womans University Hospital were used for this study and the“Questionnaire for Maternity Record for Prenatal and Intrapartum High Risk Screening”developed by the Korean Institute for Population and Health was used to rearrange the information on the records into an easy analytic form. The findings of the study are summarized as follows. 1) The risk score chart constructed on the basis of“Likelihood Method”ispresented in Table 4 in the main text. 2) From the analysis of the risk score chart it was observed that a total of 24 risk factors could be identified as having significant predicting power for the discrimination of pregnancy outcomes into four groups as defined above. They are: (1) age (2) marital status (3) age at first pregnancy (4) medical insurance (5) number of pregnancies (6) history of Cesarean sections (7). number of living child (8) history of premature infants (9) history of over weighted new born (10) history of congenital anomalies (11) history of multiple pregnancies (12) history of abnormal presentation (13) history of obstetric abnormalities (14) past illness (15) hemoglobin level (16) blood pressure (17) heart status (18) general appearance (19) edema status (20) result of abdominal examination (21) cervix status (22) pelvis status (23) chief complaints (24) Reasons for examination 3) The validity of the score chart turned out to be as follows: a) Sensitivity: Group $A_1$: 0.75 Group $A_2$: 0.78 Group $A_3$: 0.92 All combined : 0.85 b) Specificity : 0.68 4) The diagnosabilities of the“score chart”for a set of hypothetical prevalence of adverse outcomes were calculated as follows (the sensitivity“for all combined”was used). Hypothetidal Prevalence : 5％ 10％ 20％ 30％ 40％ 50％ 60％ Diagnosability : 12% 23% 40% 53% 64% 75% 80%.

• Proceedings of the KOR-KST Conference
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• 1995.12a
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• pp.45-73
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• 1995

The current paper presents a system dynamics model which can generate the land use anq transportation system performance simultaneously is proposed. The model system consists of 7 submodels (population, migration of population, household, job growth-employment-land availability, housing development, travel demand, and traffic congestion level), and each of them is designed based on the causality functions and feedback loop structure between a large number of physical, socio-economic, and policy variables. The important advantages of the system dynamics model are as follows. First, the model can address the complex interactions between land use and transportation system performance dynamically. Therefore, it can be an effective tool for evaluating the time-by-time effect of a policy over time horizons. Secondly, the system dynamics model is not relied on the assumption of equilibrium state of urban systems as in conventional models since it determines the state of model components directly through dynamic system simulation. Thirdly, the system dynamics model is very flexible in reflecting new features, such as a policy, a new phenomenon which has not existed in the past, a special event, or a useful concept from other methodology, since it consists of a lots of separated equations. In Chapter I, II, and III, overall approach and structure of the model system are discussed with causal-loop diagrams and major equations. In Chapter V _, the performance of the developed model is applied to the analysis of the impact of highway capacity expansion on land use for the area of Montgomery County, MD. The year-by-year impacts of highway capacity expansion on congestion level and land use are analyzed with some possible scenarios for the highway capacity expansion. This is a first comprehensive attempt to use dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions. The model structure is not very elaborate mainly due to the problem of the availability of behavioral data, but the model performance results indicate that the proposed approach can be a promising one in dealing comprehensively with complicated urban land use/transportation system.

• The Mathematical Education
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• v.62 no.3
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• pp.435-455
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• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• Journal of Environmental Policy
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• v.13 no.1
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• pp.69-93
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• 2014

The aim of this research was to develop a climate change vulnerability index at the district level (Si, Gun, Gu) with respect to the health care sector in Korea. The climate change vulnerability index was esimated based on the four major causes of climate-related illnesses : vector, flood, heat waves, and air pollution/allergies. The vulnerability assessment framework consists of six layers, all of which are based on the IPCC vulnerability concepts (exposure, sensitivity, and adaptive capacity) and the pathway of direct and indirect impacts of climate change modulators on health. We collected proxy variables based on the conceptual framework of climate change vulnerability. Data were standardized using the min-max normalization method. We applied the analytic hierarchy process (AHP) weight and aggregated the variables using the non-compensatory multi-criteria approach. To verify the index, sensitivity analysis was conducted by using another aggregation method (geometric transformation method, which was applied to the index of multiple deprivation in the UK) and weight, calculated by the Budget Allocation method. The results showed that it would be possible to identify the vulnerable areas by applying the developed climate change vulnerability assessment index. The climate change vulnerability index could then be used as a valuable tool in setting climate change adaptation policies in the health care sector.

• Journal of the Korean Chemical Society
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• v.66 no.4
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• pp.305-322
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• 2022

In this study, a practice-based teacher education program was developed and applied to improve the TPACK of pre-service chemistry teachers. Also the program effect and obstacles were confirmed by measuring the development of TPACK. The participants of this study were 20 pre-service chemistry teachers of 3rd grade and 2 pre-service chemistry teachers of 4th grade who took chemistry education courses at K University located in Chungcheongbuk Province. The developed teacher education program consisted of four stages: preparation, rehearsal, practice, and reflection. The feedbacks from researchers and colleagues pre-service teachers were provided in preparation, rehearsal, and reflection stages. As a result of the study, the program of this study did not show an educational effect in the "constructive learning activities" of preservice teachers, but it was found to have an educational effect in "problem solving". In other words, in "constructive learning activity", most pre-service teachers were at 0 level before and after the program. The pre-service teachers designed the class to unilaterally provide technology to simply use it as a tool to explain subject content or revise misconceptions, and learners can passively acquire knowledge. However, in the case of "problem solving", the pre-service teachers who were at level 0 before the educational program changed to level 1. Before the program, the pre-service teachers designed classes to solve problems by memory without using technology, but after the program they planned classes that provides opportunities to approach and solve various problems through the technology presented by the teacher. However, there were not many pre-service teachers corresponding to level 2, which constitutes voluntary learning in which learners use technology to solve various problems while selecting and variously manipulating technology. In addition, as obstacles to the TPACK development of pre-service chemistry teachers, there were external factors such as lack of classroom support environment for TPACK implementation, lack of time for education planning, and inadequate technology competency. And there were internal factors such as perspectives of traditional education and negative attitude toward technology. In particular, the proportion of pre-service teachers who preceived inappropriate technical competency as an external obstacles of TPACK development was high. Therefore, it was necessary to develop an education program corresponding to type 2 or type 3 that enables TPACK development through TK for pre-service teachers.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.159-185
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• 2016

Planning a multi-day trip is a complex, yet time-consuming task. It usually starts with selecting a list of points of interest (POIs) worth visiting and then arranging them into an itinerary, taking into consideration various constraints and preferences. When choosing POIs to visit, one might ask friends to suggest them, search for information on the Web, or seek advice from travel agents; however, those options have their limitations. First, the knowledge of friends is limited to the places they have visited. Second, the tourism information on the internet may be vast, but at the same time, might cause one to invest a lot of time reading and filtering the information. Lastly, travel agents might be biased towards providers of certain travel products when suggesting itineraries. In recent years, many researchers have tried to deal with the huge amount of tourism information available on the internet. They explored the wisdom of the crowd through overwhelming images shared by people on social media sites. Furthermore, trip planning problems are usually formulated as 'Tourist Trip Design Problems', and are solved using various search algorithms with heuristics. Various recommendation systems with various techniques have been set up to cope with the overwhelming tourism information available on the internet. Prediction models of recommendation systems are typically built using a large dataset. However, sometimes such a dataset is not always available. For other models, especially those that require input from people, human computation has emerged as a powerful and inexpensive approach. This study proposes CYTRIP (Crowdsource Your TRIP), a multi-day trip itinerary planning system that draws on the collective intelligence of contributors in recommending POIs. In order to enable the crowd to collaboratively recommend POIs to users, CYTRIP provides a shared workspace. In the shared workspace, the crowd can recommend as many POIs to as many requesters as they can, and they can also vote on the POIs recommended by other people when they find them interesting. In CYTRIP, anyone can make a contribution by recommending POIs to requesters based on requesters' specified preferences. CYTRIP takes input on the recommended POIs to build a multi-day trip itinerary taking into account the user's preferences, the various time constraints, and the locations. The input then becomes a multi-day trip planning problem that is formulated in Planning Domain Definition Language 3 (PDDL3). A sequence of actions formulated in a domain file is used to achieve the goals in the planning problem, which are the recommended POIs to be visited. The multi-day trip planning problem is a highly constrained problem. Sometimes, it is not feasible to visit all the recommended POIs with the limited resources available, such as the time the user can spend. In order to cope with an unachievable goal that can result in no solution for the other goals, CYTRIP selects a set of feasible POIs prior to the planning process. The planning problem is created for the selected POIs and fed into the planner. The solution returned by the planner is then parsed into a multi-day trip itinerary and displayed to the user on a map. The proposed system is implemented as a web-based application built using PHP on a CodeIgniter Web Framework. In order to evaluate the proposed system, an online experiment was conducted. From the online experiment, results show that with the help of the contributors, CYTRIP can plan and generate a multi-day trip itinerary that is tailored to the users' preferences and bound by their constraints, such as location or time constraints. The contributors also find that CYTRIP is a useful tool for collecting POIs from the crowd and planning a multi-day trip.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.12
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• pp.803-812
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• 2014

This study assesses the strategy and performance of Eco-industrial Park (EIP) initiative implemented by Korea Industrial Complex Corporation (KICOX) with the support of Ministry of Trade, Industry and Energy (MOTIE), Korea since 2005 to 2013 and recommends future directions. After the concept of EIP based on industrial symbiosis (IS) is introduced, the background and implementation procedure of the EIP initiative are described. Then, economic and environmental achievement was assessed. During the project periods (2005-2013), 449 industrial symbiosis project were explored, among which 296 projects have been implemented. Among (Of these 296 projects,) them, 244 projects have been completed in which 118 projects have been commercialized which shows 48% commercialization rate of the completed projects. Through these commercialized projects, around 311.1 billion won/year of economic benefits and reduction of waste by-products of 828,113 tons/year, wastewater of 215,517 tons/year, reduction in energy consumption of 250,475 toe/year and GHG emission reduction of 1,107,189 $tCO_2/year$ were achieved. This results confirmed that EIP initiative based on industrial symbiosis can enhance eco-efficiency of industrial parks and harmonize economy and environment. However, there are obstacles like absence of interagency coordination and cooperation, laws and institutional barriers, increased demand for local governments, funding for project investment. Thus, to utilize EIP initiative as a strategic tool for competiveness and environmental management of industrial parks, it needs intergovernmental collaboration and interdisciplinary approach to lower barrier in implementation.

• Progress in Medical Physics
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• v.14 no.4
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• pp.211-217
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• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.