• Advanced Industrial SCIence
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• v.3 no.3
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• pp.29-35
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• 2024

This study aims to analyze the impact of economic indicators (economic growth rate, employment rate, inflation) on individuals' mental health, particularly the occurrence of depression, and to clarify the correlation between economic stability and mental health. Data on economic indicators and depression were collected from public data portals and national statistics, and then refined and analyzed using Python and Pandas. Data visualization was performed using Seaborn and Matplotlib. The results showed a strong correlation between economic instability and increased depression rates, with a tendency for the number of depression cases to rise during periods of inflation and declines in economic growth. Additionally, certain age groups and genders exhibited higher depression rates, with social isolation and economic difficulties identified as major contributing factors. This study contributes to mental health policy development, and further research considering various social factors is needed.

• Wind and Structures
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• v.39 no.4
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• pp.271-285
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• 2024

The multiple-fan wind tunnel is an important facility for reproducing target wind field. Existing control methods for the multiple-fan wind tunnel can generate wind speeds that satisfy the target statistical characteristics of a wind field (e.g., power spectrum). However, the frequency-domain features cannot well represent the nonstationary winds of extreme storms (e.g., downburst). Therefore, this study proposes a multiple-fan wind tunnel control scheme based on Deep Reinforcement Learning (DRL), which will completely transform into a data-driven closed-loop control problem, to reproduce the target wind field in the time domain. Specifically, the control scheme adopts the Deep Deterministic Policy Gradient (DDPG) paradigm in which the strong fitting ability of Deep Neural Networks (DNN) is utilized. It can establish the complex relationship between the target wind speed time series and the current control strategy in the DRL-agent. To address the fluid memory effect of the wind field, this study innovatively designs the system state and control reward to improve the reproduction performance based on historical data. To validate the performance of the model, we established a simplified flow field based on Navier Stokes equations to simulate a two-dimensional numerical multiple-fan wind tunnel environment. Using the strategy of DRL decision maker, we generated a wind speed time series with minor error from the target under low Reynolds number conditions. This is the first time that the AI methods have been used to generate target wind speed time series in a multiple-fan wind tunnel environment. The hyperparameters in the DDPG paradigm are analyzed to identify a set of optimal parameters. With these efforts, the trained DRL-agent can simultaneously reproduce the wind speed time series in multiple positions.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.163-174
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• 2020

The market for electric vehicles is growing due to the public's interest in the environment and the expansion of electric vehicle support projects in terms of government policy. This study surveyed 2,332 people in Jeju, one of the nation's representative areas of electric vehicles, and the higher the perceived value in terms of the total cost of automobile ownership for electric vehicles, the higher the intention to purchase electric vehicles. The higher the level of knowledge and attachment, the higher the intention to purchase electric vehicles. While many previous studies considered economic value mainly as price, the study was conducted to approach economic value in terms of total cost of ownership. Marketing practitioners also look for practical contributions in that they can propose price framing so that customers can judge the economic value of the electric vehicle as a strategic way to increase the intention to purchase the electric vehicle, rather than just the purchase price. can see. In addition, the same research should be conducted in various regions besides Jeju, so that the research results can be generalized.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.85-97
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• 2023

Seoul Boramae Park was opened on May 5, 1986, after the Republic of Korea Air Force Academy relocated to Cheongju City in 1985. This study aims to examine the birth and evolution of Seoul Boramae Park and diagnose the park's value being transformed from the former site of the Air Force Academy. Policy reports and newspaper data were analyzed as a research method, focusing on Seoul public records. The study results are as follows. First, Seoul Boramae Park is a large-scale park created before the policy for parks on relocated sites we enacted. Second, Seoul Boramae Park has historical value as an urban park where memories and traces of the Air Force Academy overlap. Third, Seou Boramae Park contributed to regional change by promoting the public value of parks created on the relocated sites with an urban planning method. Seoul Boramae Park has implications for Korean landscape history as a case of securing large green areas in Seoul and presenting its function and roles as a park created on a relocated site.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.171-193
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• 2018

LOD(Linked Open Data) cloud is a practical implementation of semantic web. We suggested a new method that provides identity links conveniently in LOD cloud. It also allows changes in LOD to be reflected to searching results without any omissions. LOD provides detail descriptions of entities to public in RDF triple form. RDF triple is composed of subject, predicates, and objects and presents detail description for an entity. Links in LOD cloud, named identity links, are realized by asserting entities of different RDF triples to be identical. Currently, the identity link is provided with creating a link triple explicitly in which associates its subject and object with source and target entities. Link triples are appended to LOD. With identity links, a knowledge achieves from an LOD can be expanded with different knowledge from different LODs. The goal of LOD cloud is providing opportunity of knowledge expansion to users. Appending link triples to LOD, however, has serious difficulties in discovering identity links between entities one by one notwithstanding the enormous scale of LOD. Newly added entities cannot be reflected to searching results until identity links heading for them are serialized and published to LOD cloud. Instead of creating enormous identity links, we propose LOD to prepare its own link policy. The link policy specifies a set of target LODs to link and constraints necessary to discover identity links to entities on target LODs. On searching, it becomes possible to access newly added entities and reflect them to searching results without any omissions by referencing the link policies. Link policy specifies a set of predicate pairs for discovering identity between associated entities in source and target LODs. For the link policy specification, we have suggested a set of vocabularies that conform to RDFS and OWL. Identity between entities is evaluated in accordance with a similarity of the source and the target entities' objects which have been associated with the predicates' pair in the link policy. We implemented a system "Change Acceptable In-Depth Searching System(CAIDS)". With CAIDS, user's searching request starts from depth_0 LOD, i.e. surface searching. Referencing the link policies of LODs, CAIDS proceeds in-depth searching, next LODs of next depths. To supplement identity links derived from the link policies, CAIDS uses explicit link triples as well. Following the identity links, CAIDS's in-depth searching progresses. Content of an entity obtained from depth_0 LOD expands with the contents of entities of other LODs which have been discovered to be identical to depth_0 LOD entity. Expanding content of depth_0 LOD entity without user's cognition of such other LODs is the implementation of knowledge expansion. It is the goal of LOD cloud. The more identity links in LOD cloud, the wider content expansions in LOD cloud. We have suggested a new way to create identity links abundantly and supply them to LOD cloud. Experiments on CAIDS performed against DBpedia LODs of Korea, France, Italy, Spain, and Portugal. They present that CAIDS provides appropriate expansion ratio and inclusion ratio as long as degree of similarity between source and target objects is 0.8 ~ 0.9. Expansion ratio, for each depth, depicts the ratio of the entities discovered at the depth to the entities of depth_0 LOD. For each depth, inclusion ratio illustrates the ratio of the entities discovered only with explicit links to the entities discovered only with link policies. In cases of similarity degrees with under 0.8, expansion becomes excessive and thus contents become distorted. Similarity degree of 0.8 ~ 0.9 provides appropriate amount of RDF triples searched as well. Experiments have evaluated confidence degree of contents which have been expanded in accordance with in-depth searching. Confidence degree of content is directly coupled with identity ratio of an entity, which means the degree of identity to the entity of depth_0 LOD. Identity ratio of an entity is obtained by multiplying source LOD's confidence and source entity's identity ratio. By tracing the identity links in advance, LOD's confidence is evaluated in accordance with the amount of identity links incoming to the entities in the LOD. While evaluating the identity ratio, concept of identity agreement, which means that multiple identity links head to a common entity, has been considered. With the identity agreement concept, experimental results present that identity ratio decreases as depth deepens, but rebounds as the depth deepens more. For each entity, as the number of identity links increases, identity ratio rebounds early and reaches at 1 finally. We found out that more than 8 identity links for each entity would lead users to give their confidence to the contents expanded. Link policy based in-depth searching method, we proposed, is expected to contribute to abundant identity links provisions to LOD cloud.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.107-127
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• 2022

Global challenges such as the corona pandemic, climate change and the war-on-tech ensure that the demand who the technologies of the future develops and monitors prominently for will be on the agenda. Development of, and applications in, agrifood, biotech, high-tech, medtech, quantum, AI and photonics are the basis of the future earning capacity of the Netherlands and contribute to solving societal challenges, close to home and worldwide. To be like the Netherlands and Europe a strategic position in the to obtain knowledge and innovation chain, and with it our autonomy in relation to from China and the United States insurance, clear choices are needed. Brainport Eindhoven: Building on Philips' knowledge base, there is create an innovative ecosystem where more than 7,000 companies in the High-tech Systems & Materials (HTSM) collaborate on new technologies, future earning potential and international value chains. Nearly 20,000 private R&D employees work in 5 regional high-end campuses and for companies such as ASML, NXP, DAF, Prodrive Technologies, Lightyear and many others. Brainport Eindhoven has a internationally leading position in the field of system engineering, semicon, micro and nanoelectronics, AI, integrated photonics and additive manufacturing. What is being developed in Brainport leads to the growth of the manufacturing industry far beyond the region thanks to chain cooperation between large companies and SMEs. South-Holland: The South Holland ecosystem includes companies as KPN, Shell, DSM and Janssen Pharmaceutical, large and innovative SMEs and leading educational and knowledge institutions that have more than Invest €3.3 billion in R&D. Bearing Cores are formed by the top campuses of Leiden and Delft, good for more than 40,000 innovative jobs, the port-industrial complex (logistics & energy), the manufacturing industry cluster on maritime and aerospace and the horticultural cluster in the Westland. South Holland trains thematically key technologies such as biotech, quantum technology and AI. Twente: The green, technological top region of Twente has a long tradition of collaboration in triple helix bandage. Technological innovations from Twente offer worldwide solutions for the large social issues. Work is in progress to key technologies such as AI, photonics, robotics and nanotechnology. New technology is applied in sectors such as medtech, the manufacturing industry, agriculture and circular value chains, such as textiles and construction. Being for Twente start-ups and SMEs of great importance to the jobs of tomorrow. Connect these companies technology from Twente with knowledge regions and OEMs, at home and abroad. Wageningen in FoodValley: Wageningen Campus is a global agri-food magnet for startups and corporates by the national accelerator StartLife and student incubator StartHub. FoodvalleyNL also connects with an ambitious 2030 programme, the versatile ecosystem regional, national and international - including through the WEF European food innovation hub. The campus offers guests and the 3,000 private R&D put in an interesting programming science, innovation and social dialogue around the challenges in agro production, food processing, biobased/circular, climate and biodiversity. The Netherlands succeeded in industrializing in logistics countries, but it is striving for sustainable growth by creating an innovative ecosystem through a regional industry-academic research model. In particular, the Brainport Cluster, centered on the high-tech industry, pursues regional innovation and is opening a new horizon for existing industry-academic models. Brainport is a state-of-the-art forward base that leads the innovation ecosystem of Dutch manufacturing. The history of ports in the Netherlands is transforming from a logistics-oriented port symbolized by Rotterdam into a "port of digital knowledge" centered on Brainport. On the basis of this, it can be seen that the industry-academic cluster model linking the central government's vision to create an innovative ecosystem and the specialized industry in the region serves as the biggest stepping stone. The Netherlands' innovation policy is expected to be more faithful to its role as Europe's "digital gateway" through regional development centered on the innovation cluster ecosystem and investment in job creation and new industries.

• The Journal of Korean Academic Society of Nursing Education
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• v.5 no.2
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• pp.177-190
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• 1999

This study has been conducted on the basis of the literature review of Nursing Education Research in China from 1990 through August 1998. Its purpose was to support the basic data of nursing education which is risen as major revolutionary of nursing in China and those for exchange of information between Korea-China nursing education. It is retrospective and descriptive research analyzing one hundred eighty articles published in The Journal of China Nursing. The results of the study were as follows. 1. Only 33.3% of the professors of Technical Nursing School who have played of major role of nursing education in China have carried out the study related to nursing education. Baccalaureate program professors have marked 22.2% of all studies, and diploma program professors have done 12.2% of all. Therefore, the professors of above the diploma program have done total 44.4%. It explains that the professors of baccalaureate and diploma programs have done more studies related to nursing education than those of Technical Nursing School. 2. In terms of the study design, most of the studies(38.8%) were case studies introducing the curriculum contents that were done at education institutions. And then, 28.5% were reviewing the articles, and 15.6% were descriptive studies. 3. In terms of the content of the study, 38.3% were relevant to education of Technical Nursing School, 15.0% were about baccalaureate education, and 10.4% is about diploma. 4. To analyze the specific contents of the studies ; a. In baccalaureate program, human resources (professor or teaching), course extension, lab, classes, teaching method, education philosophy, goal of education, evaluation method, and human resource development were included. b. In diploma program, teaching contents evaluation method, teaching method, and educational system were included c. In the technical school, there were qualification of professors , teaching method, evaluation method, opening the courses, teaching contents, goal of education and so on. d. Beyond these, there were practice guidance and appraisement, teaching method, and opening new courses which were not specially indicated as educational curriculum and score management as continuing education. What is above tell us that the study regarding development of university system has been progressed actively and widely. It has been for the effort of revolution which based on the China government force to reform of nursing education process during last 10 years. On the base of the result, we suggest the following questions and the alternatives. 1) Since most articles are case studies related to teaching methods and the others doesn't propose the research method. the study which is applied more exact research method is needed. 2) No study is regarding social change and health policy. Because University program, founded in 1983 is on the beginning point, the research about curriculum have to be taken as a top priority as well as to reflect social needs which are based on social changes and national health policy 3) Only one review article study tells nursing Human resource. To appear in large numbers in nursing manpower, avoid the present hospital nurses training system. Then, the study for manpower development which is able to accomplish in many fields has to be advanced. 4) Most studies did not have literature review processes, so it was impossible for researcher to know the past study tendency and there is no relation among studies as to same subject, the education about research method is needed.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.199-230
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• 2021

Innovative new products and services are being launched through the convergence between heterogeneous industries, and social interest and investment in convergence industries such as AI, big data-based future cars, and robots are continuously increasing. However, in the process of commercialization of convergence new products and services, there are many cases where they do not conform to the existing regulatory and legal system, which causes many difficulties in companies launching their products and services into the market. In response to these industrial changes, the current government is promoting the improvement of existing regulatory mechanisms applied to the relevant industry along with the expansion of investment in new industries. This study, in these convergence industry trends, aimed to analysis the existing regulatory system that is an obstacle to market entry of innovative new products and services in order to preemptively predict regulatory issues that will arise in emerging industries. In addition, it was intended to establish a regulatory impact analysis system to evaluate adequacy and prepare improvement measures. The flow of this study is divided into three parts. In the first part, previous studies on regulatory impact analysis and evaluation systems are investigated. This was used as basic data for the development direction of the regulatory impact framework, indicators and items. In the second regulatory impact analysis framework development part, indicators and items are developed based on the previously investigated data, and these are applied to each stage of the framework. In the last part, a case study was presented to solve the regulatory issues faced by actual companies by applying the developed regulatory impact analysis framework. The case study included the autonomous/electric vehicle industry and the Internet of Things (IoT) industry, because it is one of the emerging industries that the Korean government is most interested in recently, and is judged to be most relevant to the realization of an intelligent information society. Specifically, the regulatory impact analysis framework proposed in this study consists of a total of five steps. The first step is to identify the industrial size of the target products and services, related policies, and regulatory issues. In the second stage, regulatory issues are discovered through review of regulatory improvement items for each stage of commercialization (planning, production, commercialization). In the next step, factors related to regulatory compliance costs are derived and costs incurred for existing regulatory compliance are calculated. In the fourth stage, an alternative is prepared by gathering opinions of the relevant industry and experts in the field, and the necessity, validity, and adequacy of the alternative are reviewed. Finally, in the final stage, the adopted alternatives are formulated so that they can be applied to the legislation, and the alternatives are reviewed by legal experts. The implications of this study are summarized as follows. From a theoretical point of view, it is meaningful in that it clearly presents a series of procedures for regulatory impact analysis as a framework. Although previous studies mainly discussed the importance and necessity of regulatory impact analysis, this study presented a systematic framework in consideration of the various factors required for regulatory impact analysis suggested by prior studies. From a practical point of view, this study has significance in that it was applied to actual regulatory issues based on the regulatory impact analysis framework proposed above. The results of this study show that proposals related to regulatory issues were submitted to government departments and finally the current law was revised, suggesting that the framework proposed in this study can be an effective way to resolve regulatory issues. It is expected that the regulatory impact analysis framework proposed in this study will be a meaningful guideline for technology policy researchers and policy makers in the future.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.507-516
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• 2013

The purpose of this study is to identify physical activity levels of the basic livelihood security recipients elderly women, to investigate relation between cardiovascular disease risk factors and sacrcopenia based on the levels, and to develop physical activity programs for healthy life of the elderly. The subjects of this study were 134 old females with $71{\pm}6.67$ years old who used senior centers in K-gu. The authors used the International Physical Activity Questionnaire for investigating the physical activity levels of the elderly, measuring their physical activity levels for seven days on average and classifying them into two groups, the Low Physical Activity (n=77) and the Moderate Physical Activity (n=57) groups based on the levels. Blood pressure, waist measurement, TC, HDL-C, LDL-C, TG, Glucose, and atherogenic index (AI) were measured as the cardiovascular disease risk factors; percent body fat, appendicular skeletal muscle mass, total muscle mass, and skeletal muscle index were measured as factors related to sarcopenia. Independent samples t-Test was conducted to analyze differences on the two groups based on the physical activity levels, with ${\alpha}=.05$ the as significance level. According to the results, HDL (p=.017) were higher and AI (p=.007) was lower; percent body fat (p=.008) was lower, and ASM (p=.000), total muscle mass (p=.000), and SMI (p=.001) were higher. In conclusion, moderate intensity physical activities rather than low intensity ones may have positive effects on the cardiovascular disease risk factors and sarcopenia levels, and participation in regular physical activities with at least moderate intensity by various methods may be needed for prevention of illness and healthy life of the elderly.