• Title/Summary/Keyword: 처리성능

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Extraction and Recognition of Concrete Slab Surface Cracks using ART2-based RBF Network (ART2 기반 RBF 네트워크를 이용한 콘크리트 슬래브 표면의 균열 추출 및 인식)

  • Kim, Kwang-Baek
    • Journal of Korea Multimedia Society
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    • v.10 no.8
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    • pp.1068-1077
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    • 2007
  • This paper proposes a method that extracts characteristics of cracks such as length, thickness and direction from a concrete slab surface image with image processing techniques. These techniques extract the cracks from the concrete surface image in variable conditions including bad image conditions) using the ART2-based RBF network to recognize the dominant directions -45 degree, 45 degree, horizontal and vertical) of the extracted cracks from the automatically calculated specifications like the lengths, directions and widths of the cracks. Our proposed extraction algorithms and analysis of the concrete cracks used a Robert operation to emphasize the cracks, and a Multiple operation to increase the difference in brightness between the cracks and background. After these treatments, the cracks can be extracted from the image by using an iterated binarization technique. Noise reduction techniques are used three separate times on this binarized image, and the specifications of the cracks are extracted form this noiseless image. The dominant directions can be recognized by using the ART2-based RBF network. In this method, the ART2 is used between the input layer and the middle layer to learn, and the Delta learning method is used between the middle layer and the output layer. The experiments using real concrete images showed that the cracks were effectively extracted, and the Proposed ART2-based RBF network effectively recognized the directions of the extracted cracks.

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Cycle Extendability of Torus Sub-Graphs in the Enhanced Pyramid Network (개선된 피라미드 네트워크에서 토러스 부그래프의 사이클 확장성)

  • Chang, Jung-Hwan
    • Journal of Korea Multimedia Society
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    • v.13 no.8
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    • pp.1183-1193
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    • 2010
  • The pyramid graph is well known in parallel processing as a interconnection network topology based on regular square mesh and tree architectures. The enhanced pyramid graph is an alternative architecture by exchanging mesh into the corresponding torus on the base for upgrading performance than the pyramid. In this paper, we adopt a strategy of classification into two disjoint groups of edges in regular square torus as a basic sub-graph constituting of each layer in the enhanced pyramid graph. Edge set in the torus graph is considered as two disjoint sub-sets called NPC(represents candidate edge for neighbor-parent) and SPC(represents candidate edge for shared-parent) whether the parents vertices adjacent to two end vertices of the corresponding edge have a relation of neighbor or sharing in the upper layer of the enhanced pyramid graph. In addition, we also introduce a notion of shrink graph to focus only on the NPC-edges by hiding SPC-edges within the shrunk super-vertex on the resulting shrink graph. In this paper, we analyze that the lower and upper bounds on the number of NPC-edges in a Hamiltonian cycle constructed on $2^n{\times}2^n$ torus is $2^{2n-2}$ and $3{\cdot}2^{2n-2}$ respectively. By expanding this result into the enhanced pyramid graph, we also prove that the maximum number of NPC-edges containable in a Hamiltonian cycle is $4^{n-1}$-2n+1 in the n-dimensional enhanced pyramid.

Improved Simple Boundary Following Algorithm (개선된 간단한 경계선 추적자 알고리즘)

  • Cheong, Cheol-Ho;Han, Tack-Don
    • Journal of KIISE:Software and Applications
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    • v.33 no.4
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    • pp.427-439
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    • 2006
  • The SBF (Simple Boundary Follower) is a boundary-following algorithm, and is used mainly for image recognition and presentation. The SBF is very popular because of its simplicity and efficiency in tracing the boundary of an object from an acquired binary image; however, it does have two drawbacks. First, the SBF cannot consistently process inner or inner-outer corners according to the follower's position and direction. Second, the SBF requires movement operations for the non-boundary pixels that are connected to boundary pixels. The MSBF (Modified Simple Boundary Follower) has a diagonal detour step for preventing inner-outer corner inconsistency, but is still inconsistent with inner-corners and still requires extra movement operations on non-boundary pixels. In this paper, we propose the ISBF (Improved Simple Boundary Follower), which solves the inconsistencies and reduces the extra operations. In addition, we have classified the tour maps by paths from a current boundary pixel to the next boundary pixel and have analyzed SBF, MSBF, and ISBF. We have determined that the ISBF has no inconsistency issues and reduces the overall number of operations.

Data Weight based Scheduling Scheme for Fair data collection in Sensor Networks with Mobile Sink (모바일 싱크 기반 무선 센서 네트워크에서 균등한 데이타 수집을 위한 데이타 가중치 기반 스케줄링 기법)

  • Jo, Young-Tae;Park, Chong-Myung;Lee, Joa-Hyoung;Jung, In-Bum
    • Journal of KIISE:Information Networking
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    • v.35 no.1
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    • pp.21-33
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    • 2008
  • The wireless sensor nodes near to the fixed sink node suffer from the quickly exhausted battery energy. To address this problem, the mobile sink node has been applied to distribute the energy consumption into all wireless sensor nodes. However, since the mobile sink node moves, the data collection scheduling scheme is necessary for the sink node to receive the data from all sensor nodes as fair as possible. The application fields of wireless sensor network need the real-time processing. If the uneven data collection occurs in the wireless sensor network, the real-time processing for the urgent events can not be satisfied. In this paper, a new method is proposed to support the lair data collection between all sensor nodes. The proposed method performs the scheduling algorithm based on the resident time of the sink node staying in a radius of communication range and the amount of data transferred already. In this paper, the proposed method and existing data collection scheduling schemes are evaluated in wireless sensor network with the mobile sink node. The result shows that the proposed method provides the best fairness among all data collection schemes.

A Efficient RSIP Address Translation Technique in Linux-based Intranet Environment (리눅스기반 인트라넷 환경에서 효율적인 RSIP주소 변환기법)

  • Lee, Youngtaek;Kim, Won;Jeon, Moon-Seok
    • Journal of the Korea Computer Industry Society
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    • v.5 no.1
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    • pp.39-48
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    • 2004
  • An IP address shortage problem is happening with a rapid propagation of the Internet and demands about a new IP address. Address translation technology as NAT is becoming use widely in order to solve these problems. NAT is an very useful If address translation technique that allows two connected networks to use different and incompatible IP address schemes. Rut it is difficult to use NAT particularly for applications that embeded IP addresses in data payloads or encrypted IP packet to guarantee End-to-End Security such as IPSec. In addition to rewiting the source/destination IP address in the packet, NAT must modify IP checksum every time, which could lead to considerablely performance decrease of the overall system in the process of address translation. RSIP is an alternative to solve these disadvantages and address shortage problems of NAT. Both NAT and RSIP divide networks into inside and outside addressing realms. NAT translates addresses between internal network and external network, but RSIP uses a borrowed external address for outside communications. RSIP server assigns a routable, public address to an RSIP client temporaily to communicate with public network outside the private network. In this paper, I will analyze NAT and RSIP gateway system, and then I will propose the Linux-based RSIP gateway for more efficient IP Address Translation in Intranet environments based on RSIP standard of IETF.

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Fault Location Estimation Algorithm in the Railway High Voltage Distribution Lines Using Flow Technique (반복계산법을 이용한 철도고압배전계통의 고장점표정 알고리즘)

  • Park, Kye-In;Chang, Sang-Hoon;Choi, Chang-Kyu
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.22 no.2
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    • pp.71-79
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    • 2008
  • High voltage distribution lines in the electric railway system placed according track with communication lines and signal equipments. Case of the over head lines is occurrence the many fault because lightning, rainstorm, damage from the sea wind and so on. According this fault caused protection device to wrong operation. One line ground fault that occurs most frequently in railway high voltage distribution lines and sort of faults is line short, three line ground breaking of a wire, and so on. For this reason we need precise maintenance for prevent of the faults. The most important is early detection and fast restoration in time of fault for a safety transit. In order to develop an advanced fault location device for 22.9[kV] distribution power network in electric railway system this paper deals with new fault locating algorithm using flow technique which enable to determine the location of the fault accurately. To demonstrate its superiorities, the case studies with the algorithm and the fault analysis using PSCAD/EMTDC (Power System Computer Aided Design/Electro Magnetic Transients DC Analysis Program) were carried out with the models of direct-grounded 22.9[kV] distribution network which is supposed to be the grounding method for electric railway system in Korea.

Hybrid Behavior Evolution Model Using Rule and Link Descriptors (규칙 구성자와 연결 구성자를 이용한 혼합형 행동 진화 모델)

  • Park, Sa Joon
    • Journal of Intelligence and Information Systems
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    • v.12 no.3
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    • pp.67-82
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    • 2006
  • We propose the HBEM(Hybrid Behavior Evolution Model) composed of rule classification and evolutionary neural network using rule descriptor and link descriptor for evolutionary behavior of virtual robots. In our model, two levels of the knowledge of behaviors were represented. In the upper level, the representation was improved using rule and link descriptors together. And then in the lower level, behavior knowledge was represented in form of bit string and learned adapting their chromosomes by the genetic operators. A virtual robot was composed by the learned chromosome which had the best fitness. The composed virtual robot perceives the surrounding situations and they were classifying the pattern through rules and processing the result in neural network and behaving. To evaluate our proposed model, we developed HBES(Hybrid Behavior Evolution System) and adapted the problem of gathering food of the virtual robots. In the results of testing our system, the learning time was fewer than the evolution neural network of the condition which was same. And then, to evaluate the effect improving the fitness by the rules we respectively measured the fitness adapted or not about the chromosomes where the learning was completed. In the results of evaluating, if the rules were not adapted the fitness was lowered. It showed that our proposed model was better in the learning performance and more regular than the evolutionary neural network in the behavior evolution of the virtual robots.

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Multi-stage News Classification System for Predicting Stock Price Changes (주식 가격 변동 예측을 위한 다단계 뉴스 분류시스템)

  • Paik, Woo-Jin;Kyung, Myoung-Hyoun;Min, Kyung-Soo;Oh, Hye-Ran;Lim, Cha-Mi;Shin, Moon-Sun
    • Journal of the Korean Society for information Management
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    • v.24 no.2
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    • pp.123-141
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    • 2007
  • It has been known that predicting stock price is very difficult due to a large number of known and unknown factors and their interactions, which could influence the stock price. However, we started with a simple assumption that good news about a particular company will likely to influence its stock price to go up and vice versa. This assumption was verified to be correct by manually analyzing how the stock prices change after the relevant news stories were released. This means that we will be able to predict the stock price change to a certain degree if there is a reliable method to classify news stories as either favorable or unfavorable toward the company mentioned in the news. To classify a large number of news stories consistently and rapidly, we developed and evaluated a natural language processing based multi-stage news classification system, which categorizes news stories into either good or bad. The evaluation result was promising as the automatic classification led to better than chance prediction of the stock price change.

Conceptual Design Analysis of Satellite Communication System for KASS (KASS 위성통신시스템 개념설계 분석)

  • Sin, Cheon Sig;You, Moonhee;Hyoung, Chang-Hee;Lee, Sanguk
    • Journal of Advanced Navigation Technology
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    • v.20 no.1
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    • pp.8-14
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    • 2016
  • High-level conceptual design analysis results of satellite communication system for Korea augmentation satellite system (KASS) satellite communication system, which is a part of KASS and consisted of KASS uplink Stations and two leased GEO is presented in this paper. We present major functions such as receiving correction and integrity message from central processing system, taking forward error correction for the message, modulating and up converting signal and conceptual design analysis for concepts for design process, GEO precise orbit determination for GEO ranging that is additional function, and clock steering for synchronization of clocks between GEO and GPS satellites. In addition to these, KASS requires 2.2 MHz for SBAS Augmentation service and 18.5 MHz for Geo-ranging service as minimum bandwidths as a results of service performance analysis of GEO ranging with respect to navigation payload(transponder) RF bandwidth is presented. These analysis results will be fed into KASS communication system design by carrying out final analysis after determining two GEOs and sites of KASS uplink stations.

Multi-layer Caching Scheme Considering Sub-graph Usage Patterns (서브 그래프의 사용 패턴을 고려한 다중 계층 캐싱 기법)

  • Yoo, Seunghun;Jeong, Jaeyun;Choi, Dojin;Park, Jaeyeol;Lim, Jongtae;Bok, Kyoungsoo;Yoo, Jaesoo
    • The Journal of the Korea Contents Association
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    • v.18 no.3
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    • pp.70-80
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    • 2018
  • Due to the recent development of social media and mobile devices, graph data have been using in various fields. In addition, caching techniques for reducing I/O costs in the process of large capacity graph data have been studied. In this paper, we propose a multi-layer caching scheme considering the connectivity of the graph, which is the characteristics of the graph topology, and the history of the past subgraph usage. The proposed scheme divides a cache into Used Data Cache and Prefetched Cache. The Used Data Cache maintains data by weights according to the frequently used sub-graph patterns. The Prefetched Cache maintains the neighbor data of the recently used data that are not used. In order to extract the graph patterns, their past history information is used. Since the frequently used sub-graphs have high probabilities to be reused, they are cached. It uses a strategy to replace new data with less likely data to be used if the memory is full. Through the performance evaluation, we prove that the proposed caching scheme is superior to the existing cache management scheme.