• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.95-115
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• 2022

The purpose of this study is to transform the sub-categorization terms of the National Science and Technology Standards Classification System into technical keywords by applying a machine learning algorithm. For this purpose, AttentionMeSH was used as a learning algorithm suitable for topic word recommendation. For source data, four-year research status files from 2017 to 2020, refined by the Korea Institute of Science and Technology Planning and Evaluation, were used. For learning, four attributes that well express the research content were used: task name, research goal, research abstract, and expected effect. As a result, it was confirmed that the result of MiF 0.6377 was derived when the threshold was 0.5. In order to utilize machine learning in actual work in the future and to secure technical keywords, it is expected that it will be necessary to establish a term management system and secure data of various attributes.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.87-93
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• 2016

In the current information-based society, information and communication technology(ICT) is very important for an individual, a society, and a nation. Especially, for a nation, ICT-related industries are forming an important part of a nation's economy. Also, unlike other industries, ICT-related industries do not require various infrastructures, and have an advantage of being developed with a few talented persons in a short period of time. In this sense, identification and education of gifted children in IT become an essential task of a nation's future. In the past, selection of the gifted children was based on paper tests. However, paper tests incurred various side effects such as private education. Since 2013, observation-recommendation system instead of paper tests has been fully adopted. The purpose of this paper is to analyze the validity of observation-recommendation admission system of the gifted children in IT. For this research purpose, the gifted children in gifted science education center attached in a university at Seoul become the focus of the samples. Their entrance score ranking and graduation record raking are compared for analysis of validity of admission system. After statistical analysis, there is a meaningful correlation between entrance score ranking and graduation record ranking for the gifted children in IT. It means that the higher entrance score ranking, the higher graduation record ranking. The analysis results are expected to be valuable baseline data for deciding usefulness of observation-recommendation admission system.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.1
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• pp.151-159
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• 2024

Purpose : This study was conducted to investigate correlation between patient satisfaction and rehabilitation motivation in a physical therapy environment. Methods : This study conducted a survey on musculoskeletal and neurological patients receiving rehabilitation treatment at a hospital. The subjects of the study were patients who were currently receiving rehabilitation treatment, either hospitalized or outpatient. 234 people were collected. A questionnaire was consisted of a total of 55 questions, including 27 questions about motivation for rehabilitation, 14 questions about physical therapy service environment, and 14 questions about patient satisfaction and intention to revisit. The detailed items in rehabilitation motivation consisted of 8 questions about task-oriented motivation, 7 questions about change-oriented motivation, 4 questions about obligatory motivation, 4 questions about external motivation, and 4 questions about intrinsic motivation, and in the physical therapy service environment, 4 questions about facility service and therapist service. , 6 questions, 4 questions about services used, 3 questions about friendliness, 4 questions about professionalism, 3 questions about treatment satisfaction, and 2 questions each about repeat visit and recommendation. Results : Facility service (r=.21) was highly correlated for task-oriented motivation, therapist service (r=.22) for change-oriented motivation, therapist service (r=.31) for mandatory motivation, therapist service (r=.19) for external motivation, and facility service (r=.56) for internal motivation. Revisit for task-oriented motivation (r=.47) is kind to change-oriented motives (r=-.13) was highly correlated with kindness (r=.19) for mandatory motives, recommendation (r=.14) for external motives, and expertise (r=.52) for internal motives. There was a high correlation between professionalism (r=.61) for facility services and kindness (r=.53) for therapist services, and revisit (r=.40) for service use. Conclusion : According to the results of this study, it was found that there was a correlation between patient satisfaction and rehabilitation motivation in a physical therapy environment.

• Management & Information Systems Review
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• v.36 no.4
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• pp.129-148
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• 2017

Conventional exhibition management information systems recommend tourist attractions that are close to the place in which an exhibition is held. Some recommended attractions by the location-based recommendation could be meaningless when nothing is related to the exhibition's topic. Our goal is to recommend attractions that are related to the content presented in the exhibition, which can be coined as content-based recommendation. Even though human exhibition curators can do this, the quality is limited to their manual task and knowledge. We propose an automatic way of discovering attractions relevant to an exhibition of interests. Language resources are incorporated to discover attractions that are more meaningful. Because a typical single machine is unable to deal with such large-scale language resources efficiently, we implemented the algorithm on top of Apache Spark, which is a well-known distributed computing framework. As a user interface prototype, a web-based system is implemented that provides users with a list of relevant attractions when users are browsing exhibition information, available at http://bike.snu.ac.kr/WARP. We carried out a case study based on Korean Tourism Organization Linked Open Data with Korean Wikipedia as a language resource. Experimental results are demonstrated to show the efficiency and effectiveness of the proposed system. The effectiveness was evaluated against well-known exhibitions. It is expected that the proposed approach will contribute to the development of both exhibition and tourist industries by motivating exhibition visitors to become active tourists.

• Journal of Gifted/Talented Education
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• v.25 no.6
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• pp.817-836
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• 2015

This research focuses on the development of gifted child behavior checklist which feasibly has application on the nation-wide gifted children observation-recommendation method. Corresponding measure has significance as it reflects actual observations of teachers teaching gifted children first-hand and involves measure of importance regarding each characteristic. An open survey on gifted children behavior characteristics lists and specific behavior patterns has been acquired from teachers in gifted education, and the checklist was developed through expert group review, pre-test, and confirmatory factor analysis process. The former checklists have shown several difficulties on application of observation-recommendation on the field due to behaviors that can't be observed in school, less important behaviors, and collide and duplicate behaviors etc. With regard to such problems, problematic clauses were removed based on the observation probability and importance of the behaviors. Ultimately, total of 32 behavior characteristic checklist consisting of ten sub factors(logical thinking, high achievement, originality, perfectionism, creative problem solving, curiosity, task commitment, conversation ability, creativity, passion) and two to three questions on each factor had been drawn. Through internal consistency test and item-total score correlation, each item of the measure has been analyzed to be consistently evaluating corresponding variables. In addition, the result of confirmatory factor analysis showed every item to be weighed appropriately on its sub-factor, strongly suggesting its feasibility on observation-recommendation of elementary gifted children as an appropriate checklist.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.119-124
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• 2016

According to the expansion of smartphone penetration and development of wearable device, personal context information can be easily collected. To use this information, the context aware recommender system has been actively studied. The key issue in this field is how to deal with the context information, as users are influenced by different contexts while rating items. But measuring the similarity among contexts is not a trivial task. To solve this problem, we propose context aware post-filtering to apply the context compensation. To be specific, we calculate the compensation for different context information by measuring their average. After reflecting the compensation of the rating data, the mechanism recommends the items to the user. Based on the item recommendation list, we recover the rating score considering the context information. To verify the effectiveness of the proposed method, we use the real movie rating dataset. Experimental evaluation shows that our proposed method outperforms several state-of-the-art approaches.

• Tuberculosis and Respiratory Diseases
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• v.79 no.3
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• pp.121-126
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• 2016

Lung function reportedly declines with age and that this decline is accelerated during disease progression. However, a recent study showed that the decline might peak in the mild and moderate stage. The prognosis of chronic obstructive pulmonary disease (COPD) can be improved if the disease is diagnosed in its early stages, prior to the peak of decline in lung function. This article reviews recent studies on early COPD and the possibility of applying the U.S. Preventive Services Task Force recommendation 2008 and 2015 for early detection of COPD in Korea.

• Journal of Dairy Science and Biotechnology
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• v.19 no.1
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• pp.30-38
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• 2001

The most important task in Korean dairy industry is to keep the seasonal and annual balance of raw milk supply and demand. Too much surplus milk supply which causes dumping sale of market milk makes dairy industries get in trouble of management, and eventually affects to farmers and consumers economically. As balancing of supply and demand is so important in the fee economic market system, the adaption of the quota system of milk production and seasonal price differentiation has been recommended very often as a method of controlling the milk supply and demand. However, this recommendation did not go through successfully due to the strong objection of dairy farmers. Recently, the voice of consumer's requirement for safer and more hygienic, and high protein, low fat level dairy product is getting stronger. By knowledge of this kind changes, quality improvement in nutrients and hygiene is the most positive way to expand the volume of milk consumption. To meet the consumer's demand, therefore, it is necessary to revise the level of milk fat content and the hygienic grading system for the payment system of raw milk.

• Ocean Systems Engineering
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• v.7 no.4
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• pp.319-328
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• 2017

Higher prediction efficacy is a very challenging task in any field of engineering. Due to global warming, there is a considerable increase in the global sea level. Through this work, an attempt has been made to find the sea level variability due to climate change impact at Haldia Port, India. Different statistical downscaling techniques are available and through this paper authors are intending to compare and illustrate the performances of three regression models. The models: Wavelet Neural Network (WNN), Minimax Probability Machine Regression (MPMR), Feed-Forward Neural Network (FFNN) are used for projecting the sea level variability due to climate change at Haldia Port, India. Model performance indices like PI, RMSE, NSE, MAPE, RSR etc were evaluated to get a clear picture on the model accuracy. All the indices are pointing towards the outperformance of WNN in projecting the sea level variability. The findings suggest a strong recommendation for ensembled models especially wavelet decomposed neural network to improve projecting efficiency in any time series modeling.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.931-956
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• 2019

Documents contain information that can be used for various applications, such as question answering (QA) system, information retrieval (IR) system, and recommendation system. To use the information, it is necessary to develop a method of extracting such information from the documents written in a form of natural language. There are several kinds of the information (e.g., temporal information, spatial information, semantic role information), where different kinds of information will be extracted with different methods. In this paper, the existing studies about the methods of extracting the temporal information are reported and several related issues are discussed. The issues are about the task boundary of the temporal information extraction, the history of the annotation languages and shared tasks, the research issues, the applications using the temporal information, and evaluation metrics. Although the history of the tasks of temporal information extraction is not long, there have been many studies that tried various methods. This paper gives which approach is known to be the better way of extracting a particular part of the temporal information, and also provides a future research direction.