• Journal of Korean Library and Information Science Society
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• v.36 no.4
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• pp.115-132
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• 2005

Libraries' functions include not only being a treasure house for cultural heritage and cultural development but also comprehensive functions such as lifelong learning and human resources development. At the present time, the Ministry of Education and Human Resources Development(MOE) has legal infrastructure and leadership which can develop and manage the nation's overall human and intellectual resources unlike previous Ministry of Education. For library to evolve as a stronghold for developing human resources and lifelong education, library policies must be unified into MOE which can provide the needed leadership. With direct management of libraries by MOE, which is currently overseeing and coordinating the nation's human resources development policies, library policies can be implemented systematically, mutual cooperation between libraries will be easier, and the link between library policies and the national and regional human resources development policies can be made.

• Proceedings of the Korea Database Society Conference
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• 2010.06a
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• pp.99-107
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• 2010

BSC(Balanced Scorecard)는 재무적 성과지표의 한계를 지양하고 고객관점, 내부 프로세스 관점, 학습과 성장 관점, 재무 관점의 다양한 관점에서 성과측정시스템으로 상용 될 수 있을 뿐만 아니라 전략의 해석, 전략적 캐스케이딩(cascading), 전략적 자원분배, 전략적 학습도구를 위한 전략관리시스템으로 또한 의사소통도구로서 사용된다. 분 논문에서는 대학내의 학과들이 각각 개별적인 특성이 존재하고 학과의 제한된 자원과 역량하에서의 효율적인 운영과 이에 대한 조직적인 접근방법이 필요하기 때문에 학과조직에 BSC를 적용하는 방안을 모색하였다. 이러한 학과 BSC는 대학 전체 또는 그 상위조직의 BSC를 위한 토대로 이용될 수 있을 뿐만 아니라 교육에 관련한 다양한 인증 및 평가와 연계할 수 있을 것이다. 또한 본 논문에서는 최소한의 프로그래밍과 이해하기 용이한 수행규칙, 그리고 유연한 개정을 위하여 비즈니스 규칙(Business Rule)으로 이루어지는 BRMS(Business Rule Management System)로 학과 BSC를 설계할 수 있는 방안을 모색하였다.

• Annual Conference of KIPS
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• 2023.05a
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• pp.665-666
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• 2023

딥러닝은 인간이 탐지하기 어려운 데이터의 특징 및 패턴을 인지하고, 이들을 학습하여 데이터를 분류 및 예측할 수 있는 기술이다. 그러나 딥러닝 모델을 잘 학습시키기 위해서는 고품질의 대용량 데이터와 이들을 처리할 수 있는 방대한 컴퓨터 자원이 요구되는 것이 일반적이다. 따라서 소량의 데이터만이 존재하는 분야나 컴퓨터 자원이 한정되어 있는 상황에서는 딥러닝을 적용하기 어렵다. 본 논문에서는, 소량의 데이터로도 모델을 자신들의 태스크에 맞게 최적화시킬 수 있는 메타러닝에 대해 소개하고, 메타 러닝 기법들의 방향에 따른 Metric-Based, Model-Based 및 Optimization 기반 모델들에 대해 소개하고, 앞으로 나아가야 할 연구 방향에 대해 제시한다.

• Smart Media Journal
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• v.12 no.2
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• pp.66-75
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• 2023

Recently, the number of cloud web applications is increasing owing to the accelerated migration of enterprises and public sector information systems to the cloud. Traditional network attacks on cloud web applications are characterized by Denial of Service (DoS) attacks, which consume network resources with a large number of packets. However, HTTP DoS attacks, which consume application resources, are also increasing recently; as such, developing security technologies to prevent them is necessary. In particular, since low-bandwidth HTTP DoS attacks do not consume network resources, they are difficult to identify using traditional security solutions that monitor network metrics. In this paper, we propose a new detection model for detecting HTTP DoS attacks on cloud web applications by collecting the application metrics of web servers and learning them using machine learning. We collected 18 types of application metrics from an Apache web server and used five machine learning and two deep learning models to train the collected data. Further, we confirmed the superiority of the application metrics-based machine learning model by collecting and training 6 additional network metrics and comparing their performance with the proposed models. Among HTTP DoS attacks, we injected the RUDY and HULK attacks, which are low- and high-bandwidth attacks, respectively. As a result of detecting these two attacks using the proposed model, we found out that the F1 scores of the application metrics-based machine learning model were about 0.3 and 0.1 higher than that of the network metrics-based model, respectively.

• Journal of Korean Home Economics Education Association
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• v.16 no.4 s.34
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• pp.43-56
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• 2004

The purpose of this study was to develop the web-based practical problem-solving teaching plans for middle school home economics class. Five practical problems which were obesity, food waste, processed food, genetically-modified food, and imported food were selected based on the food, nutrition and diet of adolescent in middle school home economics syllabus. Web-based practical problem-solving teaching plans were consisted of 5 processes: 1)recognition of the practical problem, 2)gathering and evaluation of various information, 3)figure out the best way to tackle the practical problem, 4)put into behavioral practice, and 5)analyze the results of the behavioral practice. For the effective lesson, several supplemental materials, such as individual and group reports format. obesity test methods, animations. pictures, and modules were developed. Teaching plans including supplemental materials provided might be useful to middle school home economics teachers.

• Journal of Nutrition and Health
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• v.52 no.1
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• pp.90-103
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• 2019

Purpose: This study examined the relationship of the nutrition of rice and the positive evaluation of the rice-based meal with the food consumption habits, physical and emotional health status, and learning efficacy of 601 middle and high school students in Jeonju area. Methods: The participants were divided into two groups using cluster analysis in that the participants belonging to the upper groups had a center score of 46.86 (n = 348), while the people belonging to the lower group had a center score of 36.89 (n = 253). Statistical differences were tested for all the relationships between the physical and emotional health symptoms and learning efficacy between the groups at the ${\alpha}=0.05$ level. Results: Significant differences in the physical self-evaluated symptoms were observed in all five items in each cluster (p < 0.05). In the case of the emotional health status, nine out of 10 items showed significant differences between the groups. Similarly, significant differences in all five items in learning efficacy questionnaire were noted (p < 0.05). Positive attitudes of the parents toward having breakfast also showed significant differences among the groups. Conclusion: The nutrition of rice and a positive evaluation of the rice-based meals significantly affect the physical and emotional health status and learning efficacy of juveniles. These findings can be used as baseline information for promoting nutrition education, particularly rice-based breakfast.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.1-7
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• 2020

The demand on the underwater communications is extremely increasing in searching for underwater resources, marine expedition, or environmental researches, yet there are many problems with the wireless communications because of the characteristics of the underwater environments. Especially, with the underwater wireless networks, there happen inevitable delay time and spacial inequality due to the distances between the nodes. To solve these problems, this paper suggests a new solution based on ALOHA-Q. The suggested method use random NAV value. and Environments take reward through communications success or fail. After then, The environments setting NAV value from reward. This model minimizes usage of energy and computing resources under the underwater wireless networks, and learns and setting NAV values through intense learning. The results of the simulations show that NAV values can be environmentally adopted and select best value to the circumstances, so the problems which are unnecessary delay times and spacial inequality can be solved. Result of simulations, NAV time decreasing 17.5% compared with original NAV.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.69-78
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• 2023

With the rapid growth of artificial intelligence, the demand for semiconductors is enormously increasing everywhere. To ensure the manufacturing quality and quantity simultaneously, the importance of automatic defect detection during the packaging process has been re-visited by adapting various deep learning-based methodologies into automatic packaging defect inspection. Deep learning (DL) models require a large amount of data for training, but due to the nature of the semiconductor industry where security is important, sharing and labeling of relevant data is challenging, making it difficult for model training. In this study, we propose a new framework for securing sufficient data for DL models with fewer computing resources through a divide-and-conquer approach. The proposed method divides high-resolution images into pre-defined sub-regions and assigns conditional labels to each region, then trains individual sub-regions and boundaries with boundary loss inducing the globally coherent and seamless images. Afterwards, full-size image is reconstructed by combining divided sub-regions. The experimental results show that the images obtained through this research have high efficiency, consistency, quality, and generality.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.9-21
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• 2024

Deep learning has been developing rapidly in recent years, with many researchers working to utilize large language models in various domains. However, there are practical difficulties that developing and utilizing language models require massive data and high-performance computing resources. Therefore, in-context learning, which utilizes prompts to learn efficiently, has been introduced, but there needs to be clear criteria for effective prompts for learning. In this study, we propose a methodology for enhancing prompt-based learning performance by improving the PET technique, which is one of the contextual learning methods, to select PVPs that are similar to the context of existing data. To evaluate the performance of the proposed methodology, we conducted experiments with 30,100 restaurant review datasets collected from Yelp, an online business review platform. We found that the proposed methodology outperforms traditional PET in all aspects of accuracy, stability, and learning efficiency.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.931-938
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• 2006

It is important to operate an education resources which could be integrated to an system. But most of existing education information system was not developed with standardization. It is need the core education asset and reusable education service to make a good education system. Consequently, it is needed to use Sharable Content Object Reference Model(SCORM) based contents managing in order to reuse the contents of education. And it needs assembling and producing method with reusable core asset of education system to develop the application program for education. In this thesis, we study the Teaching-Learning supporting system to support systematic education resources. Teaching-Learning support system is developed of educational domain assess through development process based on Model Driven Architecture(MDA) and core asset on each stage. Application program of education is developed using MDA automatic tool through analyzing and designing for contents storage which is based on contents meta model. We finally can develop the application software of education with low cost and high productivity by raising the reusability of education contents and by using the core asset to the whole development process.