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Fuzzy Cluster Based Diagnosis System for Classifying Computer Viruses (컴퓨터 바이러스 분류를 위한 퍼지 클러스터 기반 진단시스템)

  • Rhee, Hyun-Sook
    • The KIPS Transactions:PartB
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    • v.14B no.1 s.111
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    • pp.59-64
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    • 2007
  • In these days, malicious codes have become reality and evolved significantly to become one of the greatest threats to the modern society where important information is stored, processed, and accessed through the internet and the computers. Computer virus is a common type of malicious codes. The standard techniques in anti-virus industry is still based on signatures matching. The detection mechanism searches for a signature pattern that identifies a particular virus or stain of viruses. Though more accurate in detecting known viruses, the technique falls short for detecting new or unknown viruses for which no identifying patterns present. To cope with this problem, anti-virus software has to incorporate the learning mechanism and heuristic. In this paper, we propose a fuzzy diagnosis system(FDS) using fuzzy c-means algorithm(FCM) for the cluster analysis and a decision status measure for giving a diagnosis. We compare proposed system FDS to three well known classifiers-KNN, RF, SVM. Experimental results show that the proposed approach can detect unknown viruses effectively.

Improvement of Character-net via Detection of Conversation Participant (대화 참여자 결정을 통한 Character-net의 개선)

  • Kim, Won-Taek;Park, Seung-Bo;Jo, Geun-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.10
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    • pp.241-249
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    • 2009
  • Recently, a number of researches related to video annotation and representation have been proposed to analyze video for searching and abstraction. In this paper, we have presented a method to provide the picture elements of conversational participants in video and the enhanced representation of the characters using those elements, collectively called Character-net. Because conversational participants are decided as characters detected in a script holding time, the previous Character-net suffers serious limitation that some listeners could not be detected as the participants. The participants who complete the story in video are very important factor to understand the context of the conversation. The picture elements for detecting the conversational participants consist of six elements as follows: subtitle, scene, the order of appearance, characters' eyes, patterns, and lip motion. In this paper, we present how to use those elements for detecting conversational participants and how to improve the representation of the Character-net. We can detect the conversational participants accurately when the proposed elements combine together and satisfy the special conditions. The experimental evaluation shows that the proposed method brings significant advantages in terms of both improving the detection of the conversational participants and enhancing the representation of Character-net.

A Method to utilize Inner and Outer SNS Method for Analyzing Preferences (선호도 분석을 위한 내·외부 SNS 활용기법)

  • Park, Sung-Hoon;Kim, Jindeog
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.12
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    • pp.2871-2877
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    • 2015
  • Shopping patterns are changing with the emergence of SNS. Recently, it is also interested in providing the information based on the users' needs. Generally, the provided information is obtained from the history of users' simple browsing. Best selling hot item list is also provided in order to reflect the preferences of public users. However, the provided information is irrelevant to an individual preference. In this paper, we propose a method to utilize inner and outer SNS for analyzing public preferences about goods which are interested by individual users. The inner analyzing module collects and analyzes the preferences of community members about two goods designated by individual users. The outer analyzing module supports to analyze public preferences by using the tweeter SNS. The results of implementation show that it is possible to recommend goods based on the individual users' preferences unlike the existing shopping mall.

A Comparative Study of Genetic Algorithm and Mathematical Programming Technique applied in Design Optimization of Geodesic Dome (지오데식 돔의 설계최적화에서 유전알고리즘과 수학적계획법의 비교연구)

  • Lee, Sang-Jin;Lee, Hyeon-Jin
    • Proceeding of KASS Symposium
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    • 2008.05a
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    • pp.101-106
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    • 2008
  • This paper describes a comparative study of genetic algorithm and mathematical programming technique applied in the design optimization of geodesic dome. In particular, the genetic algorithm adopted in this study uses the so-called re-birthing technique together with the standard GA operations such as fitness, selection, crossover and mutation to accelerate the searching process. The finite difference method is used to calculate the design sensitivity required in mathematical programming techniques and three different techniques such as sequential linear programming (SLP), sequential quadratic programming(SQP) and modified feasible direction method(MFDM) are consistently used in the design optimization of geodesic dome. The optimum member sizes of geodesic dome against several external loads is evaluated by the codes $ISADO-GA{\alpha}$ and ISADO-OPT. From a numerical example, we found that both optimization techniques such as GA and mathematical programming technique are very effective to calculate the optimum member sizes of three dimensional discrete structures and it can provide a very useful information on the existing structural system and it also has a great potential to produce new structural system for large spatial structures.

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A Modified Sum-Product Algorithm for Error Floor Reduction in LDPC Codes (저밀도 패리티 검사부호에서 오류마루 감소를 위한 수정 합-곱 알고리즘)

  • Yu, Seog-Kun;Kang, Seog-Geun;Joo, Eon-Kyeong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.5C
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    • pp.423-431
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    • 2010
  • In this paper, a modified sum-product algorithm to correct bit errors captured within the trapping sets, which are produced in decoding of low-density parity-check (LDPC) codes, is proposed. Unlike the original sum-product algorithm, the proposed decoding method consists of two stages. Whether the main cause of decoding failure is the trapping sets or not is determined at the first stage. And the bit errors within the trapping sets are corrected at the second stage. In the modified algorithm, the set of failed check nodes and the transition patterns of hard-decision bits are exploited to search variable nodes in the trapping sets. After inverting information of the variable nodes, the sum-product algorithm is carried out to correct the bit errors. As a result of simulation, the proposed algorithm shows continuously improved error performance with increase in the signal-to-noise ratio. It is, therefore, considered that the modified sum-product algorithm significantly reduces or possibly eliminates the error floor in LDPC codes.

Analysis of Posting Preferences and Prediction of Update Probability on Blogs (블로그에서 포스팅 성향 분석과 갱신 가능성 예측)

  • Lee, Bum-Suk;Hwang, Byung-Yeon
    • Journal of KIISE:Databases
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    • v.37 no.5
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    • pp.258-266
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    • 2010
  • In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.

Fast Join Mechanism that considers the switching of the tree in Overlay Multicast (오버레이 멀티캐스팅에서 트리의 스위칭을 고려한 빠른 멤버 가입 방안에 관한 연구)

  • Cho, Sung-Yean;Rho, Kyung-Taeg;Park, Myong-Soon
    • The KIPS Transactions:PartC
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    • v.10C no.5
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    • pp.625-634
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    • 2003
  • More than a decade after its initial proposal, deployment of IP Multicast has been limited due to the problem of traffic control in multicast routing, multicast address allocation in global internet, reliable multicast transport techniques etc. Lately, according to increase of multicast application service such as internet broadcast, real time security information service etc., overlay multicast is developed as a new internet multicast technology. In this paper, we describe an overlay multicast protocol and propose fast join mechanism that considers switching of the tree. To find a potential parent, an existing search algorithm descends the tree from the root by one level at a time, and it causes long joining latency. Also, it is try to select the nearest node as a potential parent. However, it can't select the nearest node by the degree limit of the node. As a result, the generated tree has low efficiency. To reduce long joining latency and improve the efficiency of the tree, we propose searching two levels of the tree at a time. This method forwards joining request message to own children node. So, at ordinary times, there is no overhead to keep the tree. But the joining request came, the increasing number of searching messages will reduce a long joining latency. Also searching more nodes will be helpful to construct more efficient trees. In order to evaluate the performance of our fast join mechanism, we measure the metrics such as the search latency and the number of searched node and the number of switching by the number of members and degree limit. The simulation results show that the performance of our mechanism is superior to that of the existing mechanism.

Design of an Intellectual Smart Mirror Appication helping Face Makeup (얼굴 메이크업을 도와주는 지능형 스마트 거울 앱의설계)

  • Oh, Sun Jin;Lee, Yoon Suk
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.5
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    • pp.497-502
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    • 2022
  • Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

Index-based Searching on Timestamped Event Sequences (타임스탬프를 갖는 이벤트 시퀀스의 인덱스 기반 검색)

  • 박상현;원정임;윤지희;김상욱
    • Journal of KIISE:Databases
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    • v.31 no.5
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    • pp.468-478
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    • 2004
  • It is essential in various application areas of data mining and bioinformatics to effectively retrieve the occurrences of interesting patterns from sequence databases. For example, let's consider a network event management system that records the types and timestamp values of events occurred in a specific network component(ex. router). The typical query to find out the temporal casual relationships among the network events is as fellows: 'Find all occurrences of CiscoDCDLinkUp that are fellowed by MLMStatusUP that are subsequently followed by TCPConnectionClose, under the constraint that the interval between the first two events is not larger than 20 seconds, and the interval between the first and third events is not larger than 40 secondsTCPConnectionClose. This paper proposes an indexing method that enables to efficiently answer such a query. Unlike the previous methods that rely on inefficient sequential scan methods or data structures not easily supported by DBMSs, the proposed method uses a multi-dimensional spatial index, which is proven to be efficient both in storage and search, to find the answers quickly without false dismissals. Given a sliding window W, the input to a multi-dimensional spatial index is a n-dimensional vector whose i-th element is the interval between the first event of W and the first occurrence of the event type Ei in W. Here, n is the number of event types that can be occurred in the system of interest. The problem of‘dimensionality curse’may happen when n is large. Therefore, we use the dimension selection or event type grouping to avoid this problem. The experimental results reveal that our proposed technique can be a few orders of magnitude faster than the sequential scan and ISO-Depth index methods.hods.

Implementation of the Passenger Positioning Systems using Beacon (Beacon을 활용한 선박 탑승자 위치확인 시스템의 구현)

  • Jeong, Seon-Jae;Yim, Jae-Hong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.1
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    • pp.153-160
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    • 2016
  • In this paper, we propose a system that tracks the position of the passengers and sailors using a Bluetooth-based Beacon in the ship. The position of the tracking passengers, sometimes fatal emergencies of the rescue team, such as the sinking of the ship is utilized in order to efficiently and quickly rescue the passengers, and the collected data can be utilized additionally by grasping the flow of human traffic patterns. The system proposed in this paper, install MAC data acquisition called AP (Access Point) for each cabin, and in the installed AP retrieves Tag of the information provided to the passenger and collected. A Tag has only its own MAC Address to the privacy, no user information is not collected. All data communication by sending and receiving MAC Address was only to ensure anonymity.