• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.107-117
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• 2011

The appearance of Web has brought an substantial revolution to all fields of society such knowledge management and business transaction as well as traditional information retrieval. In this paper, we propose an EFASIT(Extended Fuzzy AHP and SImilarity Technology) model considering the emotion analysis. And we combine the Extended Fuzzy AHP Method(EFAM) with SImilarity Technology(SIT) based on the domain corpus information in order to efficiently retrieve the document on the Web. The proposed the EFASIT model can generate the more definite rule according to integration of fuzzy knowledge of various decision-maker, and can give a help to decision-making, and confirms through the experiment.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.21-41
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• 2010

This paper proposes a system that can serve users with appropriate search results through real time filtering, and implemented adaptive user profiling based personalized information retrieval system(PIRS) using users' implicit feedbacks in order to deal with the problem of existing search systems such as Google or MSN that does not satisfy various user' personal search needs. One of the reasons that existing search systems hard to satisfy various user' personal needs is that it is not easy to recognize users' search intentions because of the uncertainty of search intentions. The uncertainty of search intentions means that users may want to different search results using the same query. For example, when a user inputs "java" query, the user may want to be retrieved "java" results as a computer programming language, a coffee of java, or a island of Indonesia. In other words, this uncertainty is due to ambiguity of search queries. Moreover, if the number of the used words for a query is fewer, this uncertainty will be more increased. Real-time filtering for search results returns only those results that belong to user-selected domain for a given query. Although it looks similar to a general directory search, it is different in that the search is executed for all web documents rather than sites, and each document in the search results is classified into the given domain in real time. By applying information filtering using real time directory classifying technology for search results to personalization, the number of delivering results to users is effectively decreased, and the satisfaction for the results is improved. In this paper, a user preference profile has a hierarchical structure, and consists of domains, used queries, and selected documents. Because the hierarchy structure of user preference profile can apply the context when users perfomed search, the structure is able to deal with the uncertainty of user intentions, when search is carried out, the intention may differ according to the context such as time or place for the same query. Furthermore, this structure is able to more effectively track web documents search behaviors of a user for each domain, and timely recognize the changes of user intentions. An IP address of each device was used to identify each user, and the user preference profile is continuously updated based on the observed user behaviors for search results. Also, we measured user satisfaction for search results by observing the user behaviors for the selected search result. Our proposed system automatically recognizes user preferences by using implicit feedbacks from users such as staying time on the selected search result and the exit condition from the page, and dynamically updates their preferences. Whenever search is performed by a user, our system finds the user preference profile for the given IP address, and if the file is not exist then a new user preference profile is created in the server, otherwise the file is updated with the transmitted information. If the file is not exist in the server, the system provides Google' results to users, and the reflection value is increased/decreased whenever user search. We carried out some experiments to evaluate the performance of adaptive user preference profile technique and real time filtering, and the results are satisfactory. According to our experimental results, participants are satisfied with average 4.7 documents in the top 10 search list by using adaptive user preference profile technique with real time filtering, and this result shows that our method outperforms Google's by 23.2%.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.388-398
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• 2004

This paper focuses on the reduction method of message traffic occurred when multiple participants collaborate in the distributed virtual environment. It is referred to as filtering method of update message to minimize data traffic exchanged in the virtual environment, and it is the essential process to improve the scalability of the virtual environment. Spatial partitioning method, a popular filtering technique, divides the whole environment into smaller sub-parts in order to make it small the regions to be maintained consistently. However, it is less flexible and adaptable because the information of area of interest must be configured before simulation. In this paper, the concept of dynamic area of interest is proposed, which is highly adaptable by applying dynamic environmental elements to AOI management. It uses multiple layering and multiple consistency algorithms for dynamic management, and makes it possible to consume system resource efficiently. For performance evaluation, experiments are performed with virtual avatars, measuring message traffic. Finally, the proposed model could be applied to the AOI management systems which accommodate massive users like MMORPG, or virtual communities.

• The KIPS Transactions:PartA
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• v.14A no.1 s.105
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• pp.47-54
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• 2007

In this paper we present a translation lookaside buffer (TLB) system with low power consumption for imbedded processors. The proposed TLB is constructed as multiple banks, each with an associated block buffer and a corresponding comparator. Either the block buffer or the main bank is selectively accessed on the basis of two bits in the block buffer (tag buffer). Dynamic power savings are achieved by reducing the number of entries accessed in parallel, as a result of using the tag buffer as a filtering mechanism. The performance overhead of the proposed TLB is negligible compared with other hierarchical TLB structures. For example, the two-cycle overhead of the proposed TLB is only about 1%, as compared with 5% overhead for a filter (micro)-TLB and 14% overhead for a same structure without continuos accessing distinction algorithm. We show that the average hit ratios of the block buffers and the main banks of the proposed TLB are 95% and 5% respectively. Dynamic power is reduced by about 95% with respect to with a fully associative TLB, 90% with respect to a filter-TLB, and 40% relative to a same structure without continuos accessing distinction algorithm.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1087-1101
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• 2020

Various security devices are used to protect internal networks and valuable information from rapidly evolving cyber attacks. Firewall, which is the most commonly used security device, tries to prevent malicious attacks based on a text-based filtering rule (i.e., access control policy), by allowing or blocking access to communicate between inside and outside environments. However, in order to protect a valuable internal network from large networks, it has no choice but to increase the number of access control policy. Moreover, the text-based policy requires time-consuming and labor cost to analyze various types of vulnerabilities in firewall. To solve these problems, this paper proposes a 3D-based hierarchical visualization method, for intuitive analysis and management of access control policy. In particular, by providing a drill-down user interface through hierarchical architecture, Can support the access policy analysis for not only comprehensive understanding of large-scale networks, but also sophisticated investigation of anomalies. Finally, we implement the proposed system architecture's to verify the practicality and validity of the hierarchical visualization methodology, and then attempt to identify the applicability of firewall data analysis in the real-world network environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1B
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• pp.39-45
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• 2006

In this paper, existing technology that uses broadcasting and multicasting IP addrsses at the wireless access network, based on Internet as a core network, is upgraded. By employing broadcasting service request by receivers, convergence of multicasting and broadcasting, and lower level filtering of broadcast data, the load and traffic of network, server, base station, and receiver is substantially reduced. The technology proposed in this paper could be useful for general broadcasting services, and especially optimum for LBS and Telematics services.

• Annual Conference of KIPS
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• 2002.11a
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• pp.767-770
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• 2002

영상 검색의 수행 방법으로 사람의 시각 시스템의 특성을 기반으로 웨이블릿 변환의 고주파수 에너지와 형태학적 필터링을 이용하여 분할된 객체의 효과적인 특징 추출을 통한 계층적인 검색 시스템을 제안한다. 영상 고유의 특징을 얻기 위해 객체의 형태 정보와 질감(texture) 방향성 및 칼라 정보를 이용한다. 본 논문에서는 객체의 형태 정보의 추출을 위하여 사용자의 질의(query)영상에서 객체의 윤곽선의 편각차분 변동율에 의한 형태 특징 벡터를 추출하고 GLCM (Gray Level Co-occurrence Matrix)의 Contrast를 질감 특징으로 추출한다. 이들 두 특징을 이용하여 1차 분류 과정을 거치고 2차 검사에서는 보다 정확한 검색을 수행하기 위하여 1차로 분류된 후보영상들에 대하여 세부 정보인 칼라 정보를 기반으로 유사도를 측정함으로써 유사한 칼라와 형태를 가지는 영상뿐만 아니라 칼라가 다른 유사한 영상에도 효율적인 검색 성능을 보였다.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.529-542
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• 2000

Recent years, the use of multimedia information is rapidly increasing, and the video media is the most rising one than any others, and this field Integrates all the media into a single data stream. Though the availability of digital video is raised largely, it is very difficult for users to make the effective video access, due to its length and unstructured video format. Thus, the minimal interaction of users and the explicit definition of video structure is a key requirement in the lately developing image and video management systems. This paper defines the terms and hierarchical video structure, and presents the system, which construct the clustering-based video hierarchy, which facilitate users by browsing the summary and do a random access to the video content. Instead of using a single feature and domain-specific thresholds, we use multiple features that have complementary relationship for each other and clustering-based methods that use normalization so as to interact with users minimally. The stage of shot boundary detection extracts multiple features, performs the adaptive filtering process for each features to enhance the performance by eliminating the false factors, and does k-means clustering with two classes. The shot list of a result after the proposed procedure is represented as the video hierarchy by the intelligent unsupervised clustering technique. We experimented the static and the dynamic movie videos that represent characteristics of various video types. In the result of shot boundary detection, we had almost more than 95% good performance, and had also rood result in the video hierarchy.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.217-226
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• 2005

In today's cyberworld, network performance is affected not only by an increased demand for legitimate content request, but also by an increase in malicious activity. In this Paper, we research that network performance was affected by an increase in malicious Hacker who make DoS Attack, DDoS Attack, SYN Flooding, IP Spoofing, etc. in using TCP/IP. We suggest that Packet filtering in Network Level, Gateway Level, Application Level against to Protect by Hacker's attack. Also, we suggest that content distribution in Web Server approaches to mitigate Hacker's activity using Cache Sever, Mirror Sever, CDN. These suggests are going to use useful Protection methode of Hacker's attack.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.433-438
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• 2019

This paper proposes a method of improving deep learning based numbers and characters recognition performance on parts of drawing through image preprocessing. The proposed character recognition system consists of image preprocessing and 7 layer deep learning model. Mathematical morphological filtering is used as preprocessing to remove the lines and shapes which causes false recognition of numbers and characters on parts drawing. Further.. Further, the used deep learning model is a 7 layer deep learning model instead of VGG-16 model. As a result of the proposed OCR method, the recognition rate of characters is 92.57% and the precision is 92.82%.