• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.190-192
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• 2005

PKI(Public Key Infrastructure)에서 인증서 상태 검증은 네트워크 환경에서의 거래에 신뢰성과 안전성 및 기밀성, 무결성 등의 서비스를 제공한다. 인증서 검증 방식은 CRL, OCSP, SCVP, DVCS 등이 있다. CRL은 시간이 지남에 따라 CRL의 크기가 증가하여 검증 시간이 지연되고 실시간 검증을 할 수 없는 단점을 가지고 있다. OCSP는 CRL을 이용하지 않고 거의 실시간에 가깝게 인증서를 검증하지만 서버의 부하 증가와 느린 검증 등의 단점을 가지고 있다. 분산 OCSP는 OCSP 서버를 분산시킨 후 CRL을 중복하여 보관하거나 분개하여 보관한 상태에서 검증하는 방식으로 대리검증에 따른 느린 검증과 CA의 부하부담 등의 단점을 가지고 있다. 본 논문에서는 제기된 단점들을 해결하여 빠른 검증과 부하 분산 효과를 얻을 수 있도록 분산된 OCSP 서버를 그룹으로 분류하고, 그룹 내의 각 서버에 인증서 폐지 정보를 중복 저장하여 부하분산, 빠른 검증, CRL을 Delta CRL 방식으로 OCSP 서버에 전송하여 네트워크 부하를 감소할 수 있도록 그룹 분산 OCSP 방식을 제안하고자 한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.133-139
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• 2002

For efficiently providing distributed services, distributed computing environments are specified the requirements of various services and distributed object platforms applied an object-oriented technology by TINA Consortium and OMG CORBA. Because applications are becoming large and distributing, their servicing and managing interfaces among objects are being complicated. In order to solve these defects, it is necessary to suggest a new object grouping model and specify object service/management requirements can be introduced under the object groups.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.157-168
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• 2005

Group key agreement protocols are designed to provide a group of parties securely communicating over a public network with a session key. The mobile computing architecture is asymmetric in the sense of computational capabilities of participants. That is, the protocol participants consist of the stationary server(application servers) with sufficient computational Power and a cluster of mobile devices(clients) with limited computational resources. It is desirable to minimize the amount of computation performed by each group member in a group involving low-power mobile devices such as smart cards or personal digital assistants(PDAs). Furthermore we are required to update the group key with low computational costs when the members need to be excluded from the group or multiple new members need to be brought into an existing group. In this paper, we propose a dynamic group key protocol which offers computational efficiency to the clients with low-power mobile devices. We compare the total communicative and computational costs of our protocol with others and prove its suity against a passive adversary in the random oracle model.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.635-642
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• 2003

The radical development of recent network technology provides the basic foundation which can establish a high speed and cheap cluster system. It is a general trend that conventional cluster systems are built as the system over a fixed level based on stabilized and high speed local networks. A multi-distributed web cluster group is a web cluster model which can obtain high performance, high efficiency and high availability through mutual cooperative works between effective job division and system nodes through parallel performance of a given work and shared memory of SC-Server with low price and low speed system nodes on networks. For this, multi-distributed web cluster group builds a sub-cluster group bound with single imaginary networks of multiple system nodes and uses the web distributed shared memory of system nodes for the effective data transmission within sub-cluster groups. Since the presented model uses a load balancing and parallel computing method of large-scale work required from users, it can maximize the processing efficiency.

• Journal of KIISE:Software and Applications
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• v.37 no.9
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• pp.659-668
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• 2010

Collaborative filtering systems grasp behaviors for a new user and need new information for the user in order to recommend interesting items to the user. For the purpose of acquiring the information the collaborative filtering systems learn behaviors for users based on the previous data and can obtain new information from the results. In this paper, we propose an inductive inference method to obtain new information for users and rank items by using the new information in the proposed method. The proposed method clusters users into groups by learning users through NMF among inductive machine learning methods and selects the group features from the groups by using chi-square. Then, the method classifies a new user into a group by using the bayesian probability model as one of inductive inference methods based on the rating values for the new user and the features of groups. Finally, the method decides the ranks of items by applying the Rocchio algorithm to items with the missing values.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8A
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• pp.702-711
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• 2011

This paper proposes a HAG(Hidden-Node-Aware Grouping) algorithm for IEEE 802.15.4 networks to enhance the performance by eliminating collisions resulted from the hidden node problem without adopting the RTS/CTS packet exchanges. To solve the hidden node problem, the HAG algorithm organizes nodes into disjoint transmission groups by dynamically allocating hidden nodes into separate groups which take turns in a round robin way for their transmission. For dynamic group adjustment, it periodically evaluates the presence of hidden nodes based on subordinate nodes' receipt reports. To accurately measure its behavior, this paper also builds an analytical model to estimate its throughput fluctuation over various network topologies. The mathematical model along with simulation results confirmed that the HAG technique gracefully degraded the throughput of IEEE 802.15.4 networks whereas the standard IEEE 802.15.4 networks suffer severe throughput fallout as hidden nodes become populated.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.39-47
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• 2021

The construction of high-quality input features through effective segmentation is essential for increasing the sentence comprehension of a language model. Improving the quality of them directly affects the performance of the downstream task. This paper comparatively studies the segmentation that effectively reflects the linguistic characteristics of Korean regarding word and sentence classification. The segmentation types are defined in four categories: eojeol, morpheme, syllable and subchar, and pre-training is carried out using the RoBERTa model structure. By dividing tasks into a sentence group and a word group, we analyze the tendency within a group and the difference between the groups. By the model with subchar-level segmentation showing higher performance than other strategies by maximal NSMC: +0.62%, KorNLI: +2.38%, KorSTS: +2.41% in sentence classification, and the model with syllable-level showing higher performance at maximum NER: +0.7%, SRL: +0.61% in word classification, the experimental results confirm the effectiveness of those schemes.

• The Korean Journal of Coaching Psychology
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• v.5 no.2
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• pp.1-24
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• 2021

This study is an experimental study to examine the effect of the 1:1 coaching and example ideas with the GROW model on the creativity of new product ideas. Participants were composed of 32 adults who did not know coaching and were not related to new product development-related industries, and the experiment was randomly assigned to 1:1 coaching group, example idea group, and control group. The ideas answered by the participants were evaluated by measuring novelty, appropriateness, and willingness to pay after the experiment, and 30 experimental data and 3 expert group evaluation data were used for the final analysis. As a result of the study, the 1:1 coaching using the GROW model had a significant effect on the creativity of new product ideas, and in particular, had a positive effect on novelty. The example idea group received the lowest score among the three groups, including the control group, in novelty and suitability, and was found to have a negative effect on idea creativity. Based on these results, implications and limitations for the use of coaching in the work or situation of presenting creative ideas were discussed, and suggestions for follow-up studies were made.

• Information and Communications Magazine
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• v.24 no.4
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• pp.67-75
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• 2007

본 고에서는 MPEG 3DGC(3D Graphics Compression)서브그룹에서 진행중인ISO/IEC 14496-16 AFX(Animation Framework extension)중 Animation과 관련된 동향에 대해 기술한다. 가상 공간에서의 bone-based, 모델과 같은 캐릭터 애니메이션의 표현과 압축, 소스 모델과 타겟 모델로 부터 일련의 연속적인 중간 모델들을 만들어서 부드러운 애니메이션이 가능하도록 하는 모핑 애니메이션, 키 프레임 애니메이션의 압축에 대해 살펴보고, 현재 진행중인 Frame-based Animation Compression 대해 살펴본다. 마지막으로, 이러한 압축 툴을 사용하여 압축한 3D 비트 스트림을 다중화(Multiplexing)하여 저장하는 m3d 데이터 포맷에 대해 살펴본다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.466-468
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• 2000

이 논문에서는 Helmholtz machine을 사용하여 데이터의 분포 추정을 함으로써 문서 분류기를 학습하는 방법 제안한다. Helmholtz machine 은 생성 모델과 인식 모델로 구성된 그래프 모델로서, 그래프 모델에서의 분포 추정을 보다 가능하게 하기 위한 근사 방법 중의 하나이다. Helmholtz machine에서의 각 입력 노드는 문서를 구성하는 하나의 단어에 대응하는 이진 노드이다. 입력 노드의 개수가 많아지면 그만큼 학습 시간이 증가하기 때문에, 학습 시간을 줄이면서 적정 수준의 성능을 유지하기 위해 자질 선정이 필요하다. 이러한 요구 사항을 충족시키기 위해 정보획득량(information gain)기준을 이용하였으며, 뉴스 그룹 데이터에 대해 그 성능을 측정하고 Naive Bayes를 이용한 것과 비교한다.