• 한국노년학
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• v.27 no.2
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• pp.335-343
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• 2007

The purpose of this study was to identify the relationships among the perceived health status, activities of daily living, and depression for the elderly at home. The subjects of this study were 403 elderly over 60 years at home. The data were collected through personal interviews using structured questionnaires. The data were analyzed by descriptive statistics and Pearson correlation, using the SPSS 12.0 program. The results of this study were as follows. 1) It was seen that the degree of perceived health status is poor in 62.3%. 2) They could lead an independent daily living in 58.1%. 3) It was seen that contraction of depression was 43.8%. 4) There was a significant relationship among ADL and perceived health status, ADL and depression. However, there was no significant relationship among perceived health status and depression. Based upon above findings, this study give useful information for elderly health policy and intervention program.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.111-119
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• 2019

The existing smart grid device authentication system is concentrated on DCU, meter reading FEP and MDMS, and the authentication system for smart meters is not established. Although some cryptographic chips have been developed at present, it is difficult to complete the PKI authentication scheme because it is at the low level of simple encryption. Unlike existing power grids, smart grids are based on open two-way communication, increasing the risk of accidents as information security vulnerabilities increase. However, PKI is difficult to apply to smart meters, and there is a possibility of accidents such as system shutdown by sending manipulated packets and sending false information to the operating system. Issuing an existing PKI certificate to smart meters with high hardware constraints makes authentication and certificate renewal difficult, so an ultra-lightweight password authentication protocol that can operate even on the poor performance of smart meters (such as non-IP networks, processors, memory, and storage space) was designed and implemented. As a result of the experiment, lightweight cryptographic authentication protocol was able to be executed quickly in the Cortex-M3 environment, and it is expected that it will help to prepare a more secure authentication system in the smart grid industry.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.251-265
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• 2023

The purpose of this study is to deduce key indicators in evaluating the pedestrian environment for the elderly in Busan, which has entered an aging society, and to propose policy improvement measures. The key indicators were selected based on prior research and surveys, and the effectiveness of those indicators were measured through evaluations conducted on three places which have the highest proportion of the elderly population in Busan. The summaries of analysis are as follow. First, the three places are hillslide residential areas, and areas of activity that the elderly have were very narrow due to the restrictions on their movement caused by slope. Second, the areas were filled with a number of illegally parked vehicles. And the degree of segregation of pedestrian and vehicle and the level of safety were very low. Third, the streets with steep slopes of the target site force the elderly to move vertically, and for this reason, the elderly are expressing difficulties in outdoor activities. Fourth, it was found that the target site lacked a space for relaxation during outdoor activities. The poor walking environment not only limit the essential and social activities of the elderly, but also adversely affects the health and quality of life of the elderly. In order to maintain the health of the elderly and improve the quality of life, actions should be taken to improve the walking factors that affect the movement and external activities of the elderly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.157-172
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• 2024

Autonomous driving technology, when commercialized, has the potential to improve the safety, mobility, and environmental performance of transportation networks. However, safe autonomous driving may be hindered by poor sensor performance and limitations in long-distance detection. Therefore, cooperative autonomous driving that can supplement information collected from surrounding vehicles and infrastructure is essential. In addition, since HDVs, AVs, and CAVs have different ranges of perceivable information and different response protocols, countermeasures are needed for mixed traffic that occur during the transition period of autonomous driving technology. There is a lack of research on traffic flow optimization that considers the penetration rate of autonomous vehicles and the different characteristics of each road segment. The objective of this study is to develop weights based on safety, operational, and environmental factors for each infrastructure control use case and autonomous vehicle MPR. To develop an integrated evaluation index, infra-guidance AHP and hybrid AHP weights were combined. Based on the results of this study, it can be used to give right of way to each vehicle to optimize mixed traffic.

• Information Systems Review
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• v.22 no.1
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• pp.147-165
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• 2020

The sharing economy service is now spreading in various fields such as accommodation, cars and bicycles. In particular, bicycle-sharing service have become very popular around the world, and since September 2015, Seoul has been providing a bicycle-sharing service called 'Ttareungi'. However, the number of bicycles is unbalanced among rental stations continuously according to the user's bicycle use. In order to solve these problems, we employed social network analysis using Ttareungi data in Seoul, Korea. We analyzed degree centrality, closeness centrality, betweenness centrality and k-core. As a result, the degree centrality was found to be closely linked with bus or subway transfer center. Closeness centrality was found to be in an unbalanced departure and arrival frequency or poor public transport proximity. Betweenness centrality means where the frequency of departure and arrival occurs frequently. Finally, the k-core analysis showed that Mapo-gu was the most important group by time zone. Therefore, the results of this study may contribute to the planning of relocation and additional installation of bike rental station in Seoul.

• Journal of Korean Library and Information Science Society
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• v.55 no.1
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• pp.99-122
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• 2024

The purpose of this study is to analyze domestic academic library development plans, check whether key components are reflected, and seek ways to improve the establishment of academic library development plans. To this end, a rubric evaluation technique derived from research related to evaluation of foreign universities and libraries was used. The libraries of the top 15 domestic universities were selected by referring to the QS World University Evaluation and THE World University Evaluation as the subjects of the study, and how much the core components of the development plan were reflected were evaluated. The results of the study are as follows. First, as a result of evaluating the university library development plan, most of the contents of 'purpose', 'goal', and 'action plan' were reflected, but vulnerabilities were found in 'mission' and 'vision'. Second, some private academic libraries were moving toward strategic planning at the level of advanced countries, including all of the core components. Third, although most academic libraries specified 'purpose', it showed limitations due to perfunctory description and connection. In the comprehensive evaluation, out of the highest score of 15, 12 were good and 3 were poor, indicating that the development plans of domestic academic libraries were generally at a 'good' level. As an improvement measure, it was suggested to form a task force for development plan establishment, to disclose and promote development plans, and to strengthen education on development plans for librarians.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.3
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• pp.14-29
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• 2024

As a part of domestic and international 'Time-Urban Planning,' the concept of 'n-minute city' is being discussed. However, relevant research in this area remains insufficient. Particularly in South Korea, studies focusing on n-minute cities based on accessibility are notably lacking. Therefore, this study aims to investigate Changwon City, dividing it into urban and non-urban areas. For each of the eight different aspects of 'Living SOC', we analyze accessibility and propose fundamental directions for creating n-minute cities in Changwon. The data are collected at a 100×100m cell level, including population and the location of SOC facilities. The road network data are also constructed, and the network analysis method of QGIS employed to measure accessibility to each facility. The results indicate that in urban areas, the average travel time to Living SOC is approximately 12 minutes. However, even within urban areas, locations on the outskirts take around 16 minutes, showing some variation compared to the city center. Non-urban areas have an average travel time of about 18 minutes, indicating poor accessibility. Additionally, there is significant variability in travel time to facilities depending on the specific cell in non-urban areas, necessitating targeted solutions. Considering the ongoing population decline in South Korea, achieving n-minute cities requires not only reconsidering customized facility supply and placement based on regional characteristics but also fundamentally restructuring urban spaces through strategies such as compact cities to optimize land use.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.131-150
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• 2015

Omission of noun phrases for obligatory cases is a common phenomenon in sentences of Korean and Japanese, which is not observed in English. When an argument of a predicate can be filled with a noun phrase co-referential with the title, the argument is more easily omitted in Encyclopedia texts. The omitted noun phrase is called a zero anaphor or zero pronoun. Encyclopedias like Wikipedia are major source for information extraction by intelligent application systems such as information retrieval and question answering systems. However, omission of noun phrases makes the quality of information extraction poor. This paper deals with the problem of developing a system that can restore omitted noun phrases in encyclopedia documents. The problem that our system deals with is almost similar to zero anaphora resolution which is one of the important problems in natural language processing. A noun phrase existing in the text that can be used for restoration is called an antecedent. An antecedent must be co-referential with the zero anaphor. While the candidates for the antecedent are only noun phrases in the same text in case of zero anaphora resolution, the title is also a candidate in our problem. In our system, the first stage is in charge of detecting the zero anaphor. In the second stage, antecedent search is carried out by considering the candidates. If antecedent search fails, an attempt made, in the third stage, to use the title as the antecedent. The main characteristic of our system is to make use of a structural SVM for finding the antecedent. The noun phrases in the text that appear before the position of zero anaphor comprise the search space. The main technique used in the methods proposed in previous research works is to perform binary classification for all the noun phrases in the search space. The noun phrase classified to be an antecedent with highest confidence is selected as the antecedent. However, we propose in this paper that antecedent search is viewed as the problem of assigning the antecedent indicator labels to a sequence of noun phrases. In other words, sequence labeling is employed in antecedent search in the text. We are the first to suggest this idea. To perform sequence labeling, we suggest to use a structural SVM which receives a sequence of noun phrases as input and returns the sequence of labels as output. An output label takes one of two values: one indicating that the corresponding noun phrase is the antecedent and the other indicating that it is not. The structural SVM we used is based on the modified Pegasos algorithm which exploits a subgradient descent methodology used for optimization problems. To train and test our system we selected a set of Wikipedia texts and constructed the annotated corpus in which gold-standard answers are provided such as zero anaphors and their possible antecedents. Training examples are prepared using the annotated corpus and used to train the SVMs and test the system. For zero anaphor detection, sentences are parsed by a syntactic analyzer and subject or object cases omitted are identified. Thus performance of our system is dependent on that of the syntactic analyzer, which is a limitation of our system. When an antecedent is not found in the text, our system tries to use the title to restore the zero anaphor. This is based on binary classification using the regular SVM. The experiment showed that our system's performance is F1 = 68.58%. This means that state-of-the-art system can be developed with our technique. It is expected that future work that enables the system to utilize semantic information can lead to a significant performance improvement.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.127-147
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• 2020

The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.