• Convergence Security Journal
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• v.23 no.5
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• pp.81-89
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• 2023

Kubernetes is a representative open-source software for container orchestration, playing a crucial role in monitoring and managing resources allocated to containers. As container environments become prevalent, security threats targeting containers continue to rise, with resource exhaustion attacks being a prominent example. These attacks involve distributing malicious crypto-mining software in containerized form to hijack computing resources, thereby affecting the operation of the host and other containers that share resources. Previous research has focused on detecting resource depletion attacks, so technology to respond when attacks occur is lacking. This paper proposes a reinforcement learning-based dynamic resource management framework for detecting and responding to resource exhaustion attacks and malicious containers running in Kubernetes environments. To achieve this, we define the environment's state, actions, and rewards from the perspective of responding to resource exhaustion attacks using reinforcement learning. It is expected that the proposed methodology will contribute to establishing a robust defense against resource exhaustion attacks in container environments

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.27-35
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• 2021

Automatic post editing is a research field that aims to automatically correct errors in machine translation results. This research is mainly being focus on high resource language pairs, such as English-German. Recent APE studies are mainly adopting transfer learning based research, where pre-training language models, or translation models generated through self-supervised learning methodologies are utilized. While translation based APE model shows superior performance in recent researches, as such researches are conducted on the high resource languages, the same perspective cannot be directly applied to the low resource languages. In this work, we apply two transfer learning strategies to Korean-English APE studies and show that transfer learning with translation model can significantly improves APE performance.

• Information and Communications Magazine
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• v.31 no.12
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• pp.81-88
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• 2014

본고에서는 교육내용 성취기준 링크드데이터 프로파일 설계 및 활용에 대해 소개한다. 성취기준은 학생들이 학습의 결과로 반드시 알아야 할 지식, 능력 및 태도를 구체적으로 명시한 것으로서 국가 교육과정의 중요한 요소로 인식되고 있다. 따라서 교수학습지원시스템은 성취기준 링크드데이터 프로파일을 기반으로 교육과정, 수럽계획, 학습자원, 평가 등을 연계할 수 있도록 구현되어야 한다.

• Annual Conference of KIPS
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• 2024.05a
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• pp.658-661
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• 2024

퍼블릭 클라우드 시장이 성장하면서 퍼블릭 클라우드에서 호스팅하는 컴퓨팅 자원으로 구축된 거대하고 복잡한 IT 시스템이 점차 많아지고 있다. 이러한 시스템의 증가는 서비스 장애 발생 확률을 높이므로, 장애 관리 및 선제 감지를 위한 퍼블릭 클라우드 자원의 이상 감지 연구에 대한 수요 또한 증가하고 있다. 그러나 연구에 활용할 수 있는 벤치마크 데이터셋이 없다는 점과, 실제 자원에서 추출할 수 있는 데이터는 레이블링이 되어 있지 않은 불균형 데이터라는 점 때문에 관련 연구가 부족한 상황이다. 이러한 문제를 해결하고자 본 논문은 비지도 방식의 표현 학습 기반 딥러닝 모델을 활용한 이상 감지 시스템을 제안한다. 시스템의 이상 감지 성능을 유지하고자 일정 주기마다 다수의 딥러닝 모델을 재학습하고 비교하여 최적의 모델로 업데이트 하는 방식을 고안하였다. 해당 시스템의 평가에는 실제 퍼블릭 클라우드 자원에서 발생한 메트릭 데이터가 활용됐으며, 그 결과 준수한 이상 감지 성능을 보인다는 것을 확인하였다.

• Digital Contents
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• no.5 s.144
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• pp.68-69
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• 2005

습자가 원하는 학습자원을 컴퓨터가 스스로 찾아내서 학습자에게 전달해주고, 더 나아가 새로운 지식까지 추론해서 제공해 줄 수는 없을까? 의미의 웹이라 불리고 있는 시멘틱 웹(Semantic Web)은 의미적으로 연결돼 있는 학습 정보를 컴퓨터가 의미를 이해해서 학습자가 원하는, 학습자 수준에 맞는 정보를 제공해주고 더 나아가 지식까지도 추론해서 학습자에게 가장 적합한 형태로 전달해 줄 수 있는 강력한 메커니즘으로 부각되고 있다. 이에 필자는 살이 있는 e러닝이 되기 위해서는 시멘틱 웹과의 통합이 필요하다고 생각해 2회에 걸쳐 시멘틱 웹과, 시멘틱 웹을 e러닝에 어떻게 적용할 것인지에 대해 진단해 보고자 한다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.2
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• pp.147-156
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• 2024

The sustainable management and enhancement of marine resources are becoming increasingly important issues worldwide. This study was conducted in response to these challenges, focusing on the development and performance comparison of fish detection and classification models as part of a deep learning-based technique for assessing the effectiveness of marine resource enhancement projects initiated by the Korea Fisheries Resources Agency. The aim was to select the optimal model by training various sizes of YOLOv8-Seg models on a fish image dataset and comparing each performance metric. The dataset used for model construction consisted of 36,749 images and label files of 12 different species of fish, with data diversity enhanced through the application of augmentation techniques during training. When training and validating five different YOLOv8-Seg models under identical conditions, the medium-sized YOLOv8m-Seg model showed high learning efficiency and excellent detection and classification performance, with the shortest training time of 13 h and 12 min, an of 0.933, and an inference speed of 9.6 ms. Considering the balance between each performance metric, this was deemed the most efficient model for meeting real-time processing requirements. The use of such real-time fish detection and classification models could enable effective surveys of marine resource enhancement projects, suggesting the need for ongoing performance improvements and further research.

• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.177-188
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• 2022

Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO₂ storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.1
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• pp.217-239
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• 2006

21st century is a knowledge and information society. Keeping pace with this global environment change. people demand various roles from a library First, they demand to play a role of an 'Information Connector' rather than a traditional role of a 'Book Container'. Second, they demand to be the place of the social integration for a solution to the information and learning gap and the place for a life-long learning for HRD(Human Resources Development) by the community unit. In addition, not only introducing a system of 'Deputy Prime Minister and Minister of Education & HRD' for national HRD and 'Five-Day Week' but the advent of 'an Aging Society' demand a change of a library. This study researches roles of a library inseparably related to such new paradigms in the life-long learning society as the knowledge. information, five-day week. aging and HRD, and shows the right direction of a library to pursue in the future.

• Annual Conference of KIPS
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• 2005.11a
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• pp.857-860
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• 2005

웹 기술 기반의 컨텐츠 개발 및 운영으로 다른 환경에서의 컨텐츠 활용을 토대로 교육자원의 정보들을 통합 운영할 수 있는 관리 중심체인 e-learning 시스템의 중요성과 필요성이 대두되고 있으며, 교육용 어플리케이션은 현재 표준화되지 않은 개발 프로세스를 기반하여 개발하고 있는 실정이다. 따라서, 교육 컨텐츠의 재사용을 높이기 위해 국제적 학습 표준인 SCORM (Sharable Content Object Reference Model)을 기반으로 하나의 플랫폼에 있어서 시스템 개발 중 다른 플랫폼으로의 재사용이 가능한 핵심자산을 이용하여 조립, 생산할 수 있는 방안으로 체계적인 교육자원을 개발하고 지원하기 위한 교수-학습지원 시스템 개발에 초점을 둔 연구가 요구된다. 따라서, 본 논문에서의 교육적 도메인으로 접근하여 MDA(Model Driven Architecture)상의 교수-학습지원 시스템을 정의한다. 또한 학습컨텐츠 표준 메타데이터를 이용하여 컨텐츠저장소에 관한 분석 및 설계를 하고 MDA 자동화 툴을 이용한 핵심자산을 통해 실제 교수자가 필요로하는 컨텐츠를 제공할 수 있는 교수-학습지원 시스템을 개발하고자 한다.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.4
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• pp.85-104
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• 2004

This study is supposed to the way to add and enlarge the elements related to educational domain in metadata of school library information system (DLS) by using the concept of learning object which the education information service agencies have adapted. This study is to propose the methods which can be accessed according to the units of learning content in order that they can be applied to the teaching and learning situations, and describe and index the total traits of interior data elements included in the information resources. Thus, the metadata of the existing DLS through the additional elements : , , and was made to access the information resources according to the teaching and learning situations and to accept the concept of interior learning units by means of the element.