• Title/Summary/Keyword: Hierarchical algorithm

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Semantic Access Path Generation in Web Information Management (웹 정보의 관리에 있어서 의미적 접근경로의 형성에 관한 연구)

  • Lee, Wookey
    • Journal of the Korea Society of Computer and Information
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    • v.8 no.2
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    • pp.51-56
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    • 2003
  • The structuring of Web information supports a strong user side viewpoint that a user wants his/her own needs on snooping a specific Web site. Not only the depth first algorithm or the breadth-first algorithm, but also the Web information is abstracted to a hierarchical structure. A prototype system is suggested in order to visualize and to represent a semantic significance. As a motivating example, the Web test site is suggested and analyzed with respect to several keywords. As a future research, the Web site model should be extended to the whole WWW and an accurate assessment function needs to be devised by which several suggested models should be evaluated.

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Hierrachical manner of motion parameters for sports video mosaicking (스포츠 동영상의 모자익을 위한 이동계수의 계층적 향상)

  • Lee, Jae-Cheol;Lee, Soo-Jong;Ko, Young-Hoon;Noh, Heung-Sik;Lee Wan-Ju
    • The Journal of Information Technology
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    • v.7 no.2
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    • pp.93-104
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    • 2004
  • Sports scene is characterized by large amount of global motion due to pan and zoom of camera motion, and includes many small objects moving independently. Some short period of sports games is thrilling to televiewers, and important to producers. At the same time that kinds of scenes exhibit exceptionally dynamic motions and it is very difficult to analyze the motions with conventional algorithms. In this thesis, several algorithms are proposed for global motion analysis on these dynamic scenes. It is shown that proposed algorithms worked well for motion compensation and panorama synthesis. When cascading the inter frame motions, accumulated errors are unavoidable. In order to minimize these errors, interpolation method of motion vectors is introduced. Affined transform or perspective projection transform is regarded as a square matrix, which can be factorized into small amount of motion vectors. To solve factorization problem, we preposed the adaptation of Newton Raphson method into vector and matrix form, which is also computationally efficient. Combining multi frame motion estimation and the corresponding interpolation in hierarchical manner enhancement algorithm of motion parameters is proposed, which is suitable for motion compensation and panorama synthesis. The proposed algorithms are suitable for special effect rendering for broadcast system, video indexing, tracking in complex scenes, and other fields requiring global motion estimation.

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A Study on the Development of Dynamic Models under Inter Port Competition (항만의 경쟁상황을 고려한 동적모형 개발에 관한 연구)

  • 여기태;이철영
    • Journal of the Korean Institute of Navigation
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    • v.23 no.1
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    • pp.75-84
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    • 1999
  • Although many studies on modelling of port competitive situation have been conducted, both theoretical frame and methodology are still very weak. In this study, therefore, a new algorithm called ESD (Extensional System Dynamics) for the evaluation of port competition was presented, and applied to simulate port systems in northeast asia. The detailed objectives of this paper are to develop Unit fort Model by using SD(System Dynamics) method; to develop Competitive Port Model by ESD method; to perform sensitivity analysis by altering parameters, and to propose port development strategies. For these the algorithm for the evaluation of part's competition was developed in two steps. Firstly, SD method was adopted to develop the Unit Port models, and secondly HFP(Hierarchical Fuzzy Process) method was introduced to expand previous SD method. The proposed models were then developed and applied to the five ports - Pusan, Kobe, Yokohama, Kaoshiung, Keelung - with real data on each ports, and several findings were derived. Firstly, the extraction of factors for Unit Port was accomplished by consultation of experts such as research worker, professor, research fellows related to harbor, and expert group, and finally, five factor groups - location, facility, service, cargo volumes, and port charge - were obtained. Secondly, system's structure consisting of feedback loop was found easily by location of representative and detailed factors on keyword network of STGB map. Using these keyword network, feedback loop was found. Thirdly, for the target year of 2003, the simulation for Pusan port revealed that liner's number would be increased from 829 ships to 1,450 ships and container cargo volumes increased from 4.56 million TEU to 7.74 million TEU. It also revealed that because of increased liners and container cargo volumes, length of berth should be expanded from 2,162m to 4,729m. This berth expansion was resulted in the decrease of congested ship's number from 97 to 11. It was also found that port's charge had a fluctuation. Results of simulation for Kobe, Yokohama, Kaoshiung, Keelung in northeast asia were also acquired. Finally, the inter port competition models developed by ESB method were used to simulate container cargo volumes for Pusan port. The results revealed that under competitive situation container cargo volume was smaller than non-competitive situation, which means Pusan port is lack of competitive power to other ports. Developed models in this study were then applied to estimate change of container cargo volumes in competitive relation by altering several parameters. And, the results were found to be very helpful for port mangers who are in charge of planning of port development.

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Recrystallization Topology : a Scale-free Power-law Network (재결정 위상 : 척도 없는 거듭제곱 법칙 망)

  • Park, Jae-Hyun
    • Journal of KIISE:Information Networking
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    • v.37 no.3
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    • pp.167-174
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    • 2010
  • Recently the distributed topology control algorithm for constructing the Recrystallization Topology in the unstructured peer-to-peer network was proposed. In this paper, we prove that such a hierarchical topology is a scale-free power-law network. We present a model of a construction process of the distributed protocol, and analyze it based on a mean-field approximation and the continuum theory, so that we show that the constructed Recrystallization Topology is a scale-free network. In the proposed model, all nodes are born with some initial attractiveness and the system incorporates the rewiring of some links at every time step. Some old links are removed with the anti-preferential probability, and some new links are added with preferential probability. In other words, according to the distributed algorithm, each node makes connections to the more-preferential nodes having higher hit-ratio than other nodes, while it disconnects the anti-preferential nodes having lesser hit-ratio. This gives a realistic description of the local processes forming the recrystallization topology in unstructured peer-to-peer network. We calculate analytically the degree distribution. The analytic result indicates that the constructed network is a scale-free network, of which the scaling exponent is 3.

Performance Comparison of Clustering using Discritization Algorithm (이산화 알고리즘을 이용한 계층적 클러스터링의 실험적 성능 평가)

  • Won, Jae Kang;Lee, Jeong Chan;Jung, Yong Gyu;Lee, Young Ho
    • Journal of Service Research and Studies
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    • v.3 no.2
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    • pp.53-60
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    • 2013
  • Datamining from the large data in the form of various techniques for obtaining information have been developed. In recent years one of the most sought areas of pattern recognition and machine learning method is created with most of existing learning algorithms based on categorical attributes to a rule or decision model. However, the real-world data, it may consist of numeric attributes in many cases. In addition it contains attributes with numerical values to the normal categorical attribute. In this case, therefore, it is required processes in order to use the data to learn an appropriate value for the type attribute. In this paper, the domain of the numeric attributes are divided into several segments using learning algorithm techniques of discritization. It is described Clustering with other data mining techniques. Large amount of first cluster with characteristics is similar records from the database into smaller groups that split multiple given finite patterns in the pattern space. It is close to each other of a set of patterns that together make up a bunch. Among the set without specifying a particular category in a given data by extracting a pattern. It will be described similar grouping of data clustering technique to classify the data.

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A study on vision system based on Generalized Hough Transform 2-D object recognition (Generalized Hough Transform을 이용한 이차원 물체인식 비젼 시스템 구현에 대한 연구)

  • Koo, Bon-Cheol;Park, Jin-Soo;Chien Sung-Il
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.1
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    • pp.67-78
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    • 1996
  • The purpose of this paper is object recognition even in the presence of occlusion by using generalized Hough transform(GHT). The GHT can be considered as a kind of model based object recognition algorithm and is executed in the following two stages. The first stage is to store the information of the model in the form of R-table (Reference table). The next stage is to identify the existence of the objects in the image by using the R-table. The improved GHT method is proposed for the practical vision system. First, in constructing the R-table, we extracted the partial arc from the portion of the whole object boundary, and this partial arc can be used for constructing the R-table. Also, clustering algorithm is employed for compensating an error arised by digitizing an object image. Second, an efficient method is introduced to avoid Ballard's use of 4-D array which is necessary for estimating position, orientation and scale change of an object. Only 2-D array is enough for recognizing an object. Especially, scale token method is introduced for calculating the scale change which is easily affected by camera zoom. The results of our test show that the improved hierarchical GHT method operates stably in the realistic vision situation, even in the case of object occlusion.

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Video Segmentation Method using Improved Adaptive Threshold Algorithm and Post-processing (개선된 적응적 임계값 결정 알고리즘과 후처리 기법을 적용한 동영상 분할 방법)

  • Won, In-Su;Lee, Jun-Woo;Lim, Dae-Kyu;Jeong, Dong-Seok
    • Journal of Korea Multimedia Society
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    • v.13 no.5
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    • pp.663-673
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    • 2010
  • As a tool used for video maintenance, Video segmentation divides videos in hierarchical and structural manner. This technique can be considered as a core technique that can be applied commonly for various applications such as indexing, abstraction or retrieval. Conventional video segmentation used adaptive threshold to split video by calculating difference between consecutive frames and threshold value in window with fixed size. In this case, if the time difference between occurrences of cuts is less than the size of a window or there is much difference in neighbor feature, accurate detection is impossible. In this paper, Improved Adaptive threshold algorithm which enables determination of window size according to video format and reacts sensitively on change in neighbor feature is proposed to solve the problems above. Post-Processing method for decrement in error caused by camera flash and fast movement of large objects is applied. Evaluation result showed that there is 3.7% improvement in performance of detection compared to conventional method. In case of application of this method on modified video, the result showed 95.5% of reproducibility. Therefore, the proposed method is more accurated compared to conventional method and having reproducibility even in case of various modification of videos, it is applicable in various area as a video maintenance tool.

Distributed Hierarchical Location Placement of Core Nodes in the OCBT Multicast Protocol (OCBT 멀티캐스트 프로토콜에서 core 노드의 분산 계층 위치 결정)

  • 황경호;조동호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.1A
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    • pp.90-95
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    • 2000
  • In the Ordered Core Based Tree(OCBT) protocol, a core location is the most important feature to affect the performance. In this paper, the location placement of multiple level cores is studied. The proposed algorithm isthat each node in the network evaluates a sum of shortest path costs from all the other nodes and the entirenetwork is divided into a hierarchy region to have 3-logical level(Small, Medium, Large). The node to have thelowest cost in each S-Region is decided to be a core node. Then, the core nodes in the each S-Region evaluatea sum of shortest path costs from all the other core nodes in the same M-Region. The core node to have thelowest cost is decided to be the upper level core node. Similarly the highest level core node is decided in theL-Region. The proposed algoritthm is compared with conventional two methods to put the core nodes in thenetwork One is the random method to put the core nodes randomly. The other is the center method to locatethe core node at the nearest node from the center of each S-Region and then to locate the highest level corenode at the nearest core node from the center of the entire network. Extensive simulations are performed in theview of mean tree cost and join latency. Simulation results show that the proposed algorithm has betterperformance than random method or center method.

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An Expanded Real-Time Scheduler Model for Supporting Aperiodic Task Servers (비주기적 태스크 서버들을 지원하기 위한 확장된 실시간 스케줄러 모델)

  • Shim, Jae-Hong;Kim, Yeong-Il;Choi, Hyung-Hee;Jung, Gi-Hyun;Yoo, Hae-Young
    • The KIPS Transactions:PartA
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    • v.8A no.1
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    • pp.16-26
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    • 2001
  • This paper proposes an extended scheduler model that is an extension of the existing model proposed already in [4, 5], which consists of upper layer task scheduler and lower layer scheduling framework. However, in order to support aperiodic task scheduling, the task scheduler has been divided into two parts, such as periodic task control component and aperiodic task control component. Thus, the proposed model can support various bandwidth-preserving servers that can service aperiodic tasks. The model distinctly separates a classic monolithic kernel scheduler into several kernel components according to their functionality. This enables system developers to implement a new scheduling algorithm or aperiodic task server independent of complex low kernel mechanism, and reconfigure the system at need. In Real-Time Linux [6], we implemented the proposed scheduling framework representative scheduling algorithms, and server bandwidth-preserving servers on purpose to test. Throughout these implementations, we confirmed that a new algorithm or server could be developed independently without updates of complex low kernel modules. In order to verify efficiency of the proposed model, we measured the performance of several aperiodic task servers. The results showed this the performance of model, which even consisted of two hierarchical components and several modules, didnt have such high run-time overhead, and could efficiently support reconfiguration and scheduler development.

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Efficient Feature Selection Based Near Real-Time Hybrid Intrusion Detection System (근 실시간 조건을 달성하기 위한 효과적 속성 선택 기법 기반의 고성능 하이브리드 침입 탐지 시스템)

  • Lee, Woosol;Oh, Sangyoon
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.12
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    • pp.471-480
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    • 2016
  • Recently, the damage of cyber attack toward infra-system, national defence and security system is gradually increasing. In this situation, military recognizes the importance of cyber warfare, and they establish a cyber system in preparation, regardless of the existence of threaten. Thus, the study of Intrusion Detection System(IDS) that plays an important role in network defence system is required. IDS is divided into misuse and anomaly detection methods. Recent studies attempt to combine those two methods to maximize advantagesand to minimize disadvantages both of misuse and anomaly. The combination is called Hybrid IDS. Previous studies would not be inappropriate for near real-time network environments because they have computational complexity problems. It leads to the need of the study considering the structure of IDS that have high detection rate and low computational cost. In this paper, we proposed a Hybrid IDS which combines C4.5 decision tree(misuse detection method) and Weighted K-means algorithm (anomaly detection method) hierarchically. It can detect malicious network packets effectively with low complexity by applying mutual information and genetic algorithm based efficient feature selection technique. Also we construct upgraded the the hierarchical structure of IDS reusing feature weights in anomaly detection section. It is validated that proposed Hybrid IDS ensures high detection accuracy (98.68%) and performance at experiment section.