• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.141-148
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• 2020

Automatic term extraction is to recognize domain-specific terms given a collection of domain-specific text. Previous term extraction methods operate effectively in unsupervised manners which include extracting candidate terms, and assigning importance scores to candidate terms. Regarding the calculation of term importance scores, the study focuses on utilizing sets of inner and outer terms of a candidate term. For a candidate term, its inner terms are shorter terms which belong to the candidate term as components, and its outer terms are longer terms which include the candidate term as their component. This work presents various functions that compute, for a candidate term, term strength from either set of its inner or outer terms. In addition, a scoring method of a term importance is devised based on C-value score and the term strength values obtained from the sets of inner and outer terms. Experimental evaluations using GENIA and ACL RD-TEC 2.0 datasets compare and analyze the effectiveness of the proposed term extraction methods for English. The proposed method performed better than the baseline method by up to 1% and 3% respectively for GENIA and ACL datasets.

• Korean Journal of Community Nutrition
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• v.16 no.5
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• pp.602-612
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• 2011

The purpose of this study was to evaluate importance and performance of dietitian's task at long term care hospitals foodservices in the Busan Kyongnam area. The research was performed through using questionnaires and conducted from June 11 to July 16, 2010 for 186 dietitians at 141 long-term care hospitals. Seventy-two percent of hospitals had two dietitians and 69% of them had a dietitian's office. Fifty-two percent of dietitians has worked for less than 2 years at long term care hospital, and 37.1% of them worked additional tasks. Seventy-three percent of hospitals conducted a therapeutic diet program and the therapeutic diets frequently provided were diabetic diet > tube feeding diet > dysphasia diet > sodium controlled diet. Mean score for the importance (4.36/5.00) and performance (3.91/5.00) of dietitian's tasks were significantly different (p < 0.001). The importance and performance grid showed that the purchase-inspection management and sanitation-safety management were high scores to the importance and performance (doing great area), menu-foodservice management and cooking-working management were low scores to the importance and high scores to the importance (overdone area), and nutrition management was low scores to the importance and performance (low priority). Forty-three percent of dietitians agreed with the needs for role separation between foodservice dietitian and clinical dietitian.

• The Korean Journal of Health Service Management
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• v.9 no.3
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• pp.95-106
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• 2015

Objectives : The purpose of this study was to identify levels of turnover intention of nurses in long-term care hospitals, and to explore influential factors on turnover intention. Methods : Data were collected with a structured questionnaires from 165 nurses. The data were analyzed with SPSS/WIN 21.0. Results : First, the average score for the practice environment cognition, job satisfaction, reward importance, and turnover intention were $3.14{\pm}0.21$, $3.18{\pm}0.32$, $4.02{\pm}0.53$, and $3.29{\pm}0.67$, respectively. Second, there were significant differences in the turnover intention according to the average monthly wage, total clinical career, present clinical career, work form, average monthly night shift and turnover experience. Third, the significant predictors of turnover intention were monthly salary, practice environment cognition, reward importance, monthly night shift and type of work explaining 67.0%. of the variance. Conclusions : It is necessary to conduct continuous and systematic research and to find ways that can prevent the resignation of nurses and improve cognition in the practice environment in long-term hospitals nurses.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.466-475
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• 2017

The purpose of this study was to investigate the status of infection control in long term care hospitals. Data were gathered from 156 long term care hospitals that received certification evaluation from May 1, 2016 to July 31, 2016. We used a questionnaire consisting of 85 items regarding the status and perceived importance of infection control. The data were analyzed using the SPSS / WIN 21.0 program. All of the hospitals have infection control regulations, 80.4% of them have an infection control committee and 86.0% of them employ an ICP(infection control practitioner) who holds this position in addition to another. Hand hygiene showed the highest score at 4.47 in the perceived importance of infection control. Employee education and compliance with the validity period of sterilized products showed the highest frequency and perceived importance among the infection control activities. The above results show that almost all of the long term care hospitals have infection control regulations, but that these regulations are not properly implemented, because of the lack of applicable regulations on the policy level. Therefore, it is necessary to develop infection monitoring standards and infection control guidelines for long term care hospitals and provide the infection control practitioners with training in how to apply them.

• The Plant Pathology Journal
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• v.38 no.4
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• pp.395-402
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• 2022

To predict rice blast, many machine learning methods have been proposed. As the quality and quantity of input data are essential for machine learning techniques, this study develops three artificial neural network (ANN)-based rice blast prediction models by combining two ANN models, the feed-forward neural network (FFNN) and long short-term memory, with diverse input datasets, and compares their performance. The Blast_Weathe long short-term memory r_FFNN model had the highest recall score (66.3%) for rice blast prediction. This model requires two types of input data: blast occurrence data for the last 3 years and weather data (daily maximum temperature, relative humidity, and precipitation) between January and July of the prediction year. This study showed that the performance of an ANN-based disease prediction model was improved by applying suitable machine learning techniques together with the optimization of hyperparameter tuning involving input data. Moreover, we highlight the importance of the systematic collection of long-term disease data.

• Journal of Korean society of Dental Hygiene
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• v.19 no.3
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• pp.399-408
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• 2019

Objectives: In this study, by a professional who provides medical services by gauging the level of personality recognition among dental hygienists, the basic data is provided to suggest the need for personality education in dental hygienists' education. Methods: A questionnaire survey was conducted with the members attending conservative education in 2018, and the results of the analysis of the total of 348 members were as follows. Results: The average age of the participants was 31.6 years, and their average career duration was 9.4 years. The total personality score was 3.74 points. The highest score was 4.10 points for conscience, and the lowest score was 2.98 points for habit. In terms of differences between general characteristics and personality domains, the personality perception score was statistically significantly higher for hygienists who were married than for those with a higher education level and working at a higher hospital level. There was a statistically significant positive correlation between the personality domains and the highest competence domain (r=0.790) in relation to total personality. The higher the competency, the higher the total score. Conclusions: Personality is not a part of being formed in the short term. It should be recognized that it is important to recognize the importance of personality in the dental hygiene education curriculum and to provide opportunities to develop personality through systematic programs.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.3-16
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• 2024

The government announced the Housing Welfare Roadmap (November 2017), to expand the supply of public rental housing by reconstructing aged long-term public rental complexes. Also, remodeling projects for complexes with low business feasibility of reconstruction projects are recognized as an alternative to supplying public rental housing in urban area. This study analyzed influence factors by dividing them into project feasibility, architectural plan, urban & residential environment plan, and legal system groups in order to establish a plan for long-term public rental housing remodeling project. Futhermore, this work conducted the principal component analysis to get the principal component factors among the influence factors of each group, and the weight analysis to calculate weighting of them. In addition, major influence factors were derived by calculating the relative importance score (RIS) of each factor. Lastly this paper validated the major influence factors and applicability of the procedure to select 3 complexes that can be reviewed for remolding project among 33 long-term public rental housing complexes located in Seoul. The results of this study are expected to be useful when establishing a remodeling project plan for long-term public rental housing.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.17 no.1
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• pp.73-81
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• 2010

Purpose: This study was done to identify the intensive care unit nurses' knowledge of and compliance with the standard precautions (universal precaution) as stated in infection control guidelines. Method: From September 14 to September 28, 2006, data were collected via a questionnaire survey from 189 Intensive Care Unit nurses working at three university branch hospitals and one general hospital in Gyeonggi province. Results: The mean knowledge score was 18.8/20.0 (93.9%). The mean compliance score was 3.4/4.0 (85.8%). Two factors influencing compliance were perception of the standard precautions and experience of needle stick injuries over the past year (p<.05). Two factors influencing knowledge were support of co-workers in the use of protective devices and the availability of hand-washing device or waterless alcohol gel (p<.05). Conclusion: In order to improve knowledge and compliance with standard precautions, all factors of importance for knowledge and compliance must be taken into consideration in the clinical work place and in education.

• Archives of Plastic Surgery
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• v.43 no.6
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• pp.512-517
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• 2016

Background Studies of the ear-molding technique have emphasized the importance of initiating molding early to achieve the best results. In the present study, we describe the immediate effects and long-term outcomes of this technique, focusing on children who were older than the ideal age of treatment initiation. Methods Patients who visited our institution from July 2014 to November 2015 were included. Medical charts were reviewed to collect data on demographics, the duration of treatment, the types of deformities, and the manner of recognition of the deformity and referral to our institution. Parents were surveyed to assess the degree of improvement, the level of procedural discomfort at the end of treatment, any changes in the shape of the molded auricle, and overall satisfaction 12 months after their last follow-up visits. Results A review of 28 ears in 18 patients was conducted, including the following types of deformities: constricted ear (64.2%), Stahl ear (21.4%), prominent ear (7.1%), and cryptotia (7.1%). The average score for the degree of improvement, rated on a 5-point scale (1, very poor; 5, excellent), was 3.5 at the end of treatment, with a score of 2.6 for procedural discomfort (1, very mild; 5, very severe). After 12 months, the shapes of all ears were well maintained. The average overall satisfaction score was 3.6 (1, very dissatisfied; 5, very satisfied). Conclusions We had reasonable outcomes in older patients. After 1 year of follow-up, these outcomes were well maintained. Patients past the ideal age at presentation can still be candidates for the molding technique.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.