• Journal of Navigation and Port Research
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• v.47 no.3
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• pp.128-133
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• 2023

In order for Aids to Navigation to provide sustainable services to users, it is possible when there is no Aids to Navigation accident. If an Aids to Navigation accident occurs, the manager should efficiently manage it to prevent the same accident. However, the current Aids to Navigation accident management only specifies the cause and type of the accident. There are no separate guidelines. Thus, the accident is recorded differently depending on the manager. Therefore, this study attempted to redefine Aids to Navigation accident. To this end, Aids to Navigation accidents that have occurred over the past 23 years (year 2000 to years 2022), IALA's Aids to Navigation information standard, S-201, and categories of accidents (traffic accidents and marine accidents) were analyzed. Causes of Aids to Navigation accidents were divided into internal and external causes. Accidents were divided into three types: Light tower accident, buoy accident, and equipment accident. By further subdividing primary items, the cause of accident was reestablished into 7 items such as mooring and bad weather and 11 items such as Light tower damage, buoy loss, and equipment breakdown. These research results can be used as basic data to provide future Aids to Navigation accident statistics.

• 한국노년학
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• v.31 no.4
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• pp.871-884
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• 2011

Standard Long-term care(LTC) Utilization Plan is a kind of care plan, which aims to help beneficiaries and their family choose services to meet their care needs. The objective of this study is to determine the relationships among family caregivers' perceived quality, overall satisfaction and utilization in Standard LTC Utilization Plan. Data were gathered from family caregivers with beneficiaries who have used community service in long-term care insurance system. A national cross-sectional descriptive survey was conducted in December 2008, using proportionate quota sampling. Finally, 351 family caregivers completed questionnaires which included demographic characteristics, perceived quality(9 items), overall satisfaction(1 item) and utilization(2 items). Path analysis was conducted to find a causal relationship. This study shows firstly, the quality of Standard LTC Utilization Plan was categorized into three dimensions, that is, assessment of care needs, recommended care plan, and management of monthly benefits. Secondly, reliability and validity of quality items were satisfied. Finally, in the effect of perceived quality and satisfaction for utilization, assessment of care needs(indirect effect, path coefficients=0.077) and overall satisfaction(total effect, path coefficients=0.324) were statistically significant. The findings of this study would be helpful in developing the strategies, which is needed to improve the role of Standard LTC Utilization Plan.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.51-67
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• 2009

Developing an agile recommender system for nomadic users has been regarded as a promising application in mobile and ubiquitous settings. To increase the quality of personalized recommendation in terms of accuracy and elapsed time, estimating future context of the user in a correct way is highly crucial. Traditionally, time series analysis and Makovian process have been adopted for such forecasting. However, these methods are not adequate in predicting context data, only because most of context data are represented as nominal scale. To resolve these limitations, the alignment-prediction algorithm has been suggested for context prediction, especially for future context from the low-level context. Recently, an ontological approach has been proposed for guided context prediction without context history. However, due to variety of context information, acquiring sufficient context prediction knowledge a priori is not easy in most of service domains. Hence, the purpose of this paper is to propose a novel context prediction methodology, which does not require a priori knowledge, and to increase accuracy and decrease elapsed time for service response. To do so, we have newly developed pattern-based context prediction approach. First of ail, a set of individual rules is derived from each context attribute using context history. Then a pattern consisted of results from reasoning individual rules, is developed for pattern learning. If at least one context property matches, say R, then regard the pattern as right. If the pattern is new, add right pattern, set the value of mismatched properties = 0, freq = 1 and w(R, 1). Otherwise, increase the frequency of the matched right pattern by 1 and then set w(R,freq). After finishing training, if the frequency is greater than a threshold value, then save the right pattern in knowledge base. On the other hand, if at least one context property matches, say W, then regard the pattern as wrong. If the pattern is new, modify the result into wrong answer, add right pattern, and set frequency to 1 and w(W, 1). Or, increase the matched wrong pattern's frequency by 1 and then set w(W, freq). After finishing training, if the frequency value is greater than a threshold level, then save the wrong pattern on the knowledge basis. Then, context prediction is performed with combinatorial rules as follows: first, identify current context. Second, find matched patterns from right patterns. If there is no pattern matched, then find a matching pattern from wrong patterns. If a matching pattern is not found, then choose one context property whose predictability is higher than that of any other properties. To show the feasibility of the methodology proposed in this paper, we collected actual context history from the travelers who had visited the largest amusement park in Korea. As a result, 400 context records were collected in 2009. Then we randomly selected 70% of the records as training data. The rest were selected as testing data. To examine the performance of the methodology, prediction accuracy and elapsed time were chosen as measures. We compared the performance with case-based reasoning and voting methods. Through a simulation test, we conclude that our methodology is clearly better than CBR and voting methods in terms of accuracy and elapsed time. This shows that the methodology is relatively valid and scalable. As a second round of the experiment, we compared a full model to a partial model. A full model indicates that right and wrong patterns are used for reasoning the future context. On the other hand, a partial model means that the reasoning is performed only with right patterns, which is generally adopted in the legacy alignment-prediction method. It turned out that a full model is better than a partial model in terms of the accuracy while partial model is better when considering elapsed time. As a last experiment, we took into our consideration potential privacy problems that might arise among the users. To mediate such concern, we excluded such context properties as date of tour and user profiles such as gender and age. The outcome shows that preserving privacy is endurable. Contributions of this paper are as follows: First, academically, we have improved sequential matching methods to predict accuracy and service time by considering individual rules of each context property and learning from wrong patterns. Second, the proposed method is found to be quite effective for privacy preserving applications, which are frequently required by B2C context-aware services; the privacy preserving system applying the proposed method successfully can also decrease elapsed time. Hence, the method is very practical in establishing privacy preserving context-aware services. Our future research issues taking into account some limitations in this paper can be summarized as follows. First, user acceptance or usability will be tested with actual users in order to prove the value of the prototype system. Second, we will apply the proposed method to more general application domains as this paper focused on tourism in amusement park.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.101-123
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• 2012

Currently, Social Media, it has widely a renown keyword and its related social trends and businesses have been fastly applied into various contexts. Social media has become an important research area for scholars interested in online technologies and cyber space and their social impacts. Social media is not only including web-based services but also mobile-based application services that allow people to share various style information and knowledge through online connection. Social media users have tendency to common identity- and bond-attachment through interactions such as 'thumbs up', 'reply note', 'forwarding', which may have driven from various factors and may result in delivering information, sharing knowledge, and specific experiences et al. Even further, almost of all social media sites provide and connect unknown strangers depending on shared interests, political views, or enjoyable activities, and other stuffs incorporating the creation of contents, which provides benefits to users. As fast developing digital devices including smartphone, tablet PC, internet based blogging, and photo and video clips, scholars desperately have began to study regarding diverse issues connecting human beings' motivations and the behavioral results which may be articulated by the format of antecedents as well as consequences related to contents that people create via social media. Social media such as Facebook, Twitter, or Cyworld users are more and more getting close each other and build up their relationships by a different style. In this sense, people use social media as tools for maintain pre-existing network, creating new people socially, and at the same time, explicitly find some business opportunities using personal and unlimited public networks. In terms of theory in explaining this phenomenon, social capital is a concept that describes the benefits one receives from one's relationship with others. Thereby, social media use is closely related to the form and connected of people, which is a bridge that can be able to achieve informational benefits of a heterogeneous network of people and common identity- and bonding-attachment which emphasizes emotional benefits from community members or friend group. Social capital would be resources accumulated through the relationships among people, which can be considered as an investment in social relations with expected returns and may achieve benefits from the greater access to and use of resources embedded in social networks. Social media using for their social capital has vastly been adopted in a cyber world, however, there has been little explaining the phenomenon theoretically how people may take advantages or opportunities through interaction among people, why people may interactively give willingness to help or their answers. The individual consciously express themselves in an online space, so called, common identity- or bonding-attachments. Common-identity attachment is the focus of the weak ties, which are loose connections between individuals who may provide useful information or new perspectives for one another but typically not emotional support, whereas common-bonding attachment is explained that between individuals in tightly-knit, emotionally close relationship such as family and close friends. The common identify- and bonding-attachment are mainly studying on-offline setting, which individual convey an impression to others that are expressed to own interest to others. Thus, individuals expect to meet other people and are trying to behave self-presentation engaging in opposite partners accordingly. As developing social media, individuals are motivated to disclose self-disclosures of open and honest using diverse cues such as verbal and nonverbal and pictorial and video files to their friends as well as passing strangers. Social media context, common identity- and bond-attachment for self-presentation seems different compared with face-to-face context. In the realm of social media, social users look for self-impression by posting text messages, pictures, video files. Under the digital environments, people interact to work, shop, learn, entertain, and be played. Social media provides increasingly the kinds of intention and behavior in online. Typically, identity and bond social capital through self-presentation is the intentional and tangible component of identity. At social media, people try to engage in others via a desired impression, which can maintain through performing coherent and complementary communications including displaying signs, symbols, brands made of digital stuffs(information, interest, pictures, etc,). In marketing area, consumers traditionally show common-identity as they select clothes, hairstyles, automobiles, logos, and so on, to impress others in any given context in a shopping mall or opera. To examine these social capital and attachment, we combined a social capital theory with an attachment theory into our research model. Our research model focuses on the common identity- and bond-attachment how they are formulated through social capitals: cognitive capital, structural capital, relational capital, and individual characteristics. Thus, we examined that individual online kindness, self-rated expertise, and social relation influence to build common identity- and bond-attachment, and the attachment effects make an impact on both the willingness to help, however, common bond seems not to show directly impact on information sharing. As a result, we discover that the social capital and attachment theories are mainly applicable to the context of social media and usage in the individual networks. We collected sample data of 256 who are using social media such as Facebook, Twitter, and Cyworld and analyzed the suggested hypotheses through the Structural Equation Model by AMOS. This study analyzes the direct and indirect relationship between the social network service usage and outcomes. Antecedents of kindness, confidence of knowledge, social relations are significantly affected to the mediators common identity-and bond attachments, however, interestingly, network externality does not impact, which we assumed that a size of network was a negative because group members would not significantly contribute if the members do not intend to actively interact with each other. The mediating variables had a positive effect on toward willingness to help. Further, common identity attachment has stronger significant on shared information.

• Korean Journal of Environment and Ecology
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• v.36 no.3
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• pp.318-326
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• 2022

The Convention on Biodiversity (CBD) recommends that 17% of the land be designated as a protected area to counter global environmental problems. Korea also realized a need to designate protected areas according to the international level and explain the significance of designating protected areas. Accordingly, studies on ecosystem services are required. In Korea, the protected areas are designated as national parks, provincial parks, and county parks by hierarchy under the Natural Parks Act. However, as priority was on political and administrative aspects, research on ecosystem service value evaluation and habitat management were concentrated in national parks, and provincial and county parks were relatively neglected. Therefore, more studies on provincial and county parks are necessary. In this study, habitat quality for Gajisan Provincial Park, where there were few studies on habitat management and ecosystem service valuation, was evaluated using the InVEST Habitat Quality model among the InVEST models. The analysis results were compared with 16 mountainous national parks. The results showed that the habitat quality value of Gajisan Provincial Park was 0.83, higher than that of the surrounding areas. The analysis of habitat quality in three districts showed 0,84 for the Tongdosa and Naewonsa districts and 0.83 for the Seoknamsa district. By use district, the nature conservation district, the natural environment district, the cultural heritage district, and the park village district had the highest habitat quality value in that order. Compared with the existing habitat quality analysis results of national parks, Gajisan Provincial Park showed naturalness at the level of Mudeungsan National Park. These results can be used as objective data for establishing policies and management plans to preserve biodiversity and promote ecosystem services in provincial parks.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.97-115
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• 2008

Introduction The e-government is concerned with using Internet and Web technologies to exchange information and services with citizens, businesses and other related organizations, and it centers on three functions, namely informational, interactive, and transactional [UN, 2001]. Many developed countries like the U.S. have been actively involved in e-government projects, since they enable both more effective public services for citizens and more efficient internal operations. Korea is among these leading countries that are planning to leverage computer and communication technologies to provide for integration of work processes and information as well as convenient access to information and services. For this reason, evaluating e-government projects is becoming a crucial issue for both researchers and policy-makers. However, most research to date has primarily focused on a model of success of an e-government system designed for citizens, overlooking internal systems specifically created for employees working in a public organization. This paper is intended to propose a model to measure the success of a Web-based information system designed for use by internal users at Chungwadae, the executive branch of Korea's central government. The paper is also aimed at applying the model to the assessment of the present system being used at Chungwadae in comparison with the preceding system. Evaluating an e-Government System The most widely cited model of information systems success today is that of DeLone and McLean[1992, 2003, 2004]. The original model states that the success of an information system can be measured using six dimensions, including system quality, information quality, use, user satisfaction, individual impact, and organizational impact. Although the ultimate success of an information system may be reflected in the impact that the system has upon individuals as well as an organization, aspects of using the system such as system use and user satisfaction can play an important role in determining the system success, because the system would be a sheer failure if users don't like and use the system. As a response to criticisms given by numerous researchers, the authors adapted their model to fit the emerging Web-based environment. The revised model[DeLone and McLean, 2003] they offered included an additional quality dimension, namely service quality, and combined individual and organizational impacts into net benefits which can also influence user satisfaction. The e-government system success model can be built around this updated model. Our model incorporates information quality, system quality, and service quality as in the DeLone and McLean model. However, the 'system use' dimension has been replaced by perceived usefulness, as suggested by Seddon[1998]. In addition, because the e-government systems that this paper focuses on are internal public systems used in government agencies, the 'net benefits' dimension has been replaced by perceived work efficiency. Based on the proposed model, a total of nine hypotheses have been formulated which we tested using an empirical analysis. Methods A questionnaire form has been created with items that are designed to examine the relationships among the variables in the model. The questionnaire has been handed over, in person, to 65 members of Chungwadae staff who are now actively using the E-Support System, the present information system created to support internal work at Chungwadae. We made arrangements to meet with each individual who agreed to participate in our survey, and helped to fill out the survey form with explanations. Of the 65 copies that were delivered, only 33 were returned, and 30 responses of these have been adopted for our analysis, since three were not valid. The extremely small sample size was due to the limited number of staff members who had adequate experience required of this study. Results We gathered data from the questionnaire survey and analyzed them using a regression analysis to test the hypotheses. As shown in the table below, the results indicated that all three dimensions of an information system’s quality are positively related to user satisfaction. However, information quality and system quality were found to be positively related to perceived usefulness, while service quality was not. In addition, perceived usefulness is not positively related to user satisfaction, implying that a user may find a system useful, but may not be satisfied with it. Finally, user satisfaction and perceived usefulness both are positively related to perceived work efficiency. This suggests that workers' positive experience with the system is important to guarantee favorable work efficiency. Conclusions We conclude that the proposed model proved useful in measuring the success of an internal information system used by a government agency. To demonstrate the applicability and usefulness of the model in the paper, we applied the model to the assessment of the present internal system used at Chungwadae in comparison with the preceding system. The results showed that the present system outperforms the preceding one in a statistically significant way. Future research will have to focus on applying the model to Korea's governmental agencies other than Chungwadae and examine whether it proves applicable in different types of governmental organizations.

• 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.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.83-105
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• 2016

Measuring an individual's subjective wellbeing in an accurate, unobtrusive, and cost-effective manner is a core success factor of the wellbeing support system, which is a type of medical IT service. However, measurements with a self-report questionnaire and wearable sensors are cost-intensive and obtrusive when the wellbeing support system should be running in real-time, despite being very accurate. Recently, reasoning the state of subjective wellbeing with conventional sentiment analysis and unstructured data has been proposed as an alternative to resolve the drawbacks of the self-report questionnaire and wearable sensors. However, this approach does not consider contextual polarity, which results in lower measurement accuracy. Moreover, there is no sentimental word net or ontology for the subjective wellbeing area. Hence, this paper proposes a method to extract keywords and their contextual polarity representing the subjective wellbeing state from the unstructured text in online websites in order to improve the reasoning accuracy of the sentiment analysis. The proposed method is as follows. First, a set of general sentimental words is proposed. SentiWordNet was adopted; this is the most widely used dictionary and contains about 100,000 words such as nouns, verbs, adjectives, and adverbs with polarities from -1.0 (extremely negative) to 1.0 (extremely positive). Second, corpora on subjective wellbeing (SWB corpora) were obtained by crawling online text. A survey was conducted to prepare a learning dataset that includes an individual's opinion and the level of self-report wellness, such as stress and depression. The participants were asked to respond with their feelings about online news on two topics. Next, three data sources were extracted from the SWB corpora: demographic information, psychographic information, and the structural characteristics of the text (e.g., the number of words used in the text, simple statistics on the special characters used). These were considered to adjust the level of a specific SWB. Finally, a set of reasoning rules was generated for each wellbeing factor to estimate the SWB of an individual based on the text written by the individual. The experimental results suggested that using contextual polarity for each SWB factor (e.g., stress, depression) significantly improved the estimation accuracy compared to conventional sentiment analysis methods incorporating SentiWordNet. Even though literature is available on Korean sentiment analysis, such studies only used only a limited set of sentimental words. Due to the small number of words, many sentences are overlooked and ignored when estimating the level of sentiment. However, the proposed method can identify multiple sentiment-neutral words as sentiment words in the context of a specific SWB factor. The results also suggest that a specific type of senti-word dictionary containing contextual polarity needs to be constructed along with a dictionary based on common sense such as SenticNet. These efforts will enrich and enlarge the application area of sentic computing. The study is helpful to practitioners and managers of wellness services in that a couple of characteristics of unstructured text have been identified for improving SWB. Consistent with the literature, the results showed that the gender and age affect the SWB state when the individual is exposed to an identical queue from the online text. In addition, the length of the textual response and usage pattern of special characters were found to indicate the individual's SWB. These imply that better SWB measurement should involve collecting the textual structure and the individual's demographic conditions. In the future, the proposed method should be improved by automated identification of the contextual polarity in order to enlarge the vocabulary in a cost-effective manner.

• Journal of Physiology & Pathology in Korean Medicine
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• v.25 no.5
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• pp.765-772
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• 2011

Knowledge which is represented by formal logic are widely used in many domains such like artificial intelligence, information retrieval, e-commerce and so on. And for medical field, medical documentary records retrieval, information systems in hospitals, medical data sharing, remote treatment and expert systems need knowledge representation technology. To retrieve information intellectually and provide advanced information services, systematically controlled mechanism is needed to represent and share knowledge. Importantly, medical expert's knowledge should be represented in a form that is understandable to computers and also to humans to be applied to the medical information system supporting decision making. And it should have a suitable and efficient structure for its own purposes including reasoning, extendability of knowledge, management of data, accuracy of expressions, diversity, and so on. we call it ontology which can be processed with machines. We can use the ontology to represent traditional medicine knowledge in structured and systematic way with visualization, then also it can also be used education materials. Hence, the authors developed an Shanghanlun ontology by way of showing an example, so that we suggested a methodology for ontology development and also a model to structure the traditional medical knowledge. And this result can be used for student to learn Shanghanlun by graphical representation of it's knowledge. We analyzed the text of Shanghanlun to construct relational database including it's original text, symptoms and herb formulars. And then we classified the terms following some criterion, confirmed the structure of the ontology to describe semantic relations between the terms, especially we developed the ontology considering visual representation. The ontology developed in this study provides database showing fomulas, herbs, symptoms, the name of diseases and the text written in Shanghanlun. It's easy to retrieve contents by their semantic relations so that it is convenient to search knowledge of Shanghanlun and to learn it. It can display the related concepts by searching terms and provides expanded information with a simple click. It has some limitations such as standardization problems, short coverage of pattern(證), and error in chinese characters input. But we believe this research can be used for basic foundation to make traditional medicine more structural and systematic, to develop application softwares, and also to applied it in Shanghanlun educations.