• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1851-1859
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• 1998

We summarize the password-based authetication protocol K1P which was introduced in our easlier papers [1,2] and then propose three more extended protocols. These protocols preserve a design concept of K1P, i.e., security and efficiency, and canbe used for various purposes. They are a One-time key K1P, a Client public key K1P, and an Exponential key exchange K1P.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.89-98
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• 2007

For browsing, searching, and manipulating video documents, an indexing technique to describe video contents is required. Until now, the indexing process is mostly carried out by specialists who manually assign a few keywords to the video contents and thereby this work becomes an expensive and time consuming task. Therefore, automatic classification of video content is necessary. We propose a fully automatic and computationally efficient method for analysis and summarization of spots news video for 5 spots news video such as soccer, golf, baseball, basketball and volleyball. First of all, spots news videos are classified as anchor-person Shots, and the other shots are classified as news reports shots. Shot classification is based on image preprocessing and color features of the anchor-person shots. We then use the dominant color of the field and motion features for analysis of sports shots, Finally, sports shots are classified into five genre type. We achieved an overall average classification accuracy of 75% on sports news videos with 241 scenes. Therefore, the proposed method can be further used to search news video for individual sports news and sports highlights.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.202-215
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• 2022

The purpose of this study is to identify gamification techniques and characteristics of digital marketing based on the main information communication, learning, and play of the current consumer group, and to present effective gamification digital marketing plans for the MZ generation. The summary of the research process is as follows. First, the characteristics and definitions of MZ generation and gamification were described and the concept was clarified. Second, domestic and foreign gamification cases were compared and analyzed. Studies show that we should be wary of gamification digital marketing, which fails to reflect the characteristics of the fun-seeking MZ generation by failing to organically connect the mechanisms and structures of gamification, focusing only on visible elements, such as Point, Badge, and Leaderboard. In addition, customers who lose the fun of obtaining rewards and leave because they feel that the rewards (points, badges, leaderboards) they provide are worthless should be prevented.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.241-264
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• 2022

Bibliographic metadata can help researchers effectively utilize essential publications that they need and grasp academic trends of their own fields. With the manual creation of the metadata costly and time-consuming. it is nontrivial to effectively automatize the metadata construction using rule-based methods due to the immoderate variety of the article forms and styles according to publishers and academic societies. Therefore, this study proposes a two-step extraction process based on rules and deep neural networks for generating bibliographic metadata of scientific articlles to overcome the difficulties above. The extraction target areas in articles were identified by using a deep neural network-based model, and then the details in the areas were analyzed and sub-divided into relevant metadata elements. IThe proposed model also includes a model for generating reference summary information, which is able to separate the end of the text and the starting point of a reference, and to extract individual references by essential rule set, and to identify all the bibliographic items in each reference by a deep neural network. In addition, in order to confirm the possibility of a model that generates the bibliographic information of academic papers without pre- and post-processing, we conducted an in-depth comparative experiment with various settings and configurations. As a result of the experiment, the method proposed in this paper showed higher performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.469-478
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• 2010

This paper proposes the effective shape descriptor for 3D foot pose estimation. To reduce processing time, silhouette-based foot image database is built and meta information which involves the 3D pose of the foot is appended to the database. And we proposed a modified Centroid Contour Distance whose size of the feature space is small and performance of pose estimation is better than the others. In order to analyze performance of the descriptor, we evaluate time and spatial complexity with retrieval accuracy, and then compare with the previous methods. Experimental results show that the proposed descriptor is more effective than the previous methods on feature extraction time and pose estimation accuracy.

• Smart Media Journal
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• v.10 no.1
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• pp.39-46
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• 2021

This study is about a method of extracting a summary from a news article in consideration of the importance of each sentence constituting the article. We propose a method of calculating sentence importance by extracting the probabilities of topic sentence, similarity with article title and other sentences, and sentence position as characteristics that affect sentence importance. At this time, a hypothesis is established that the Topic Sentence will have a characteristic distinct from the general sentence, and a deep learning-based classification model is trained to obtain a topic sentence probability value for the input sentence. Also, using the pre-learned ELMo language model, the similarity between sentences is calculated based on the sentence vector value reflecting the context information and extracted as sentence characteristics. The topic sentence classification performance of the LSTM and BERT models was 93% accurate, 96.22% recall, and 89.5% precision, resulting in high analysis results. As a result of calculating the importance of each sentence by combining the extracted sentence characteristics, it was confirmed that the performance of extracting the topic sentence was improved by about 10% compared to the existing TextRank algorithm.

• 한국정보통신설비학회:학술대회논문집
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• 2002.08a
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• pp.156-167
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• 2002

디지털방송의 주요 특징은 고품질, 데이터방송, 다채널로 요약할 수 있다. 다채널화는 현재보다 채널수, 프로그램수의 급격한 증가로 이어지며 채널수 프로그램수의 증가는 시청자가 지금보다 원하는 프로그램을 찾는데 보다 많은 시간이 소요됨을 의미한다. 디지털 방송에서는 시청자의 프로그램 탐색을 돕는 전자프로그램 가이드(EPG : Electric Program Guide) 서비스를 제공하고 있으나 현재 EPG는 기존의 신문에서 제공하는 채널별 프로그램 가이드와 크게 기능이 다르지 않다. 이에 따라 최근 EPG는 주제별, 시간대별 방송프로그램 검색 외에 Agent의 개념을 도입하여 개인의 취향을 분석하는 EPG를 개인화에 대한 연구가 이루어 지고 있으며 더 나아가 정보를 자동으로 공지하는 방법에 대한 연구도 요구되어 진다. 본 연구에서는 사용자 취향에 적합한 프로그램 정보가 취득 되는 대로 별도 조작 없이 공지될 수 있는 ${\ulcorner}$자동공지 기반의 AP-EPG${\lrcorner}$ 에 대하여 제안하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.841-843
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• 2005

비디오 데이터 분석은 감시, 검색, 스포츠 경기 자동 요약 등 많은 분야에서 사용되는 기술이다. 그러나 감시 카메라나 스포츠 경기 비디오와 같이 사람의 영역이 저해상도인 환경에서는 포즈 추정, 모델과의 매칭이 어렵기 때문에 제스처 인식 연구는 많이 이루어지고 있지 못하다. 본 논문에서는 카메라가 Pan/Tilt/Zoom 동작을 하고 사람이 빠르게 움직이는 방송용 테니스 비디오에서, 사람을 추출하고, Curvature Scale Space를 기반으로 한 특징을 추출하여 학습된 포즈 모델과 매칭하는 방법과, 차원의 축소를 통해 일련의 포즈들을 학습된 제스처와 매칭하는 방법을 제안한다. 50개의 방송용 테니스 경기 비디오 장면에 대하여 서브 제스처 추출을 수행한 결과, 서브 포즈에 대하여 모델과 매칭이 잘 되고, 매칭이 되지 않는 포즈를 포함하는 시퀀스에 대해서도 강인한

• The KIPS Transactions:PartA
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• v.13A no.3 s.100
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• pp.205-210
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• 2006

To assist developing robust multithreaded software, we develop a thread monitoring system for multithreaded Java programs, which can trace or monitor running threads and synchronization. We design a monitoring system which has options to select interesting threads and synchronizations. Using this tool, programmers can monitor only interesting threads and synchronization in more details by selecting options. It also provides profile information after execution, which summarizes behavior of running threads and synchronizations during execution. We implement the system based on code inlining, and presents some experimental results.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.725-728
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• 2003

사용자의 감정에 관련된 정보를 처리하는 것은 인간과 컴퓨터와의 상호작용(HCI)에 있어서 매우 중요한 역할을 한다. 특히 비디오 데이터에 대한 사용자의 감정을 처리하는 것은 비디오 검색이나 요약본 구성에 매우 중요하다. 사용자의 감정을 처리하기 위해서는 감정에 관련된 특징들을 추출 및 측정하고 이를 기반으로 비디오 장면을 분류하는 것이 필요하다. 본 논문에서는 칼라 정보를 바탕으로 Fisher의 Linear Discriminant Analysis 방식 및 Mahalanobis Distance 측정을 이용하여 기본 감정의 분류 방식을 제안한다. 공포 감정의 경우 77.8%의 의미 있는 결과를 얻었다.