• Title/Summary/Keyword: Path Combining

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A Hybrid Approach Combining Data Envelopment Analysis and Machine Learning to Evaluate the Efficiency of System Integration Projects (SI 프로젝트의 효율성 평가를 위해 자료포괄분석과 기계학습을 결합한 하이브리드 분석)

  • Hong, Han-Kuk;Ha, Sung-Ho;Park, Sang-Chan
    • Asia pacific journal of information systems
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    • v.10 no.1
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    • pp.19-35
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    • 2000
  • Data Envelopment Analysis(DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

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Joint Routing and Channel Assignment in Multi-rate Wireless Mesh Networks

  • Liu, Jiping;Shi, Wenxiao;Wu, Pengxia
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.5
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    • pp.2362-2378
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    • 2017
  • To mitigate the performance degradation caused by performance anomaly, a number of channel assignment algorithms have been proposed for multi-rate wireless mesh networks. However, network conditions have not been fully considered for routing process in these algorithms. In this paper, a joint scheme called Multi-rate Dijkstra's Shortest path - Rate Separated (MDSRS) is proposed, combining routing metrics and channel assignment algorithm. In MDSRS, the routing metric are determined through the synthesized deliberations of link costs and rate matches; then the rate separated channel assignment is operated based on the determined routing metric. In this way, the competitions between high and low rate links are avoided, and performance anomaly problem is settled, and the network capacity is efficiently improved. Theoretical analysis and NS-3 simulation results indicate that, the proposed MDSRS can significantly improve the network throughput, and decrease the average end-to-end delay as well as packet loss probability. Performance improvements could be achieved even in the heavy load network conditions.

Fast Pattern Classification with the Multi-layer Cellular Nonlinear Networks (CNN) (다층 셀룰라 비선형 회로망(CNN)을 이용한 고속 패턴 분류)

  • 오태완;이혜정;손홍락;김형석
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.9
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    • pp.540-546
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    • 2003
  • A fast pattern classification algorithm with Cellular Nonlinear Network-based dynamic programming is proposed. The Cellular Nonlinear Networks is an analog parallel processing architecture and the dynamic programing is an efficient computation algorithm for optimization problem. Combining merits of these two technologies, fast pattern classification with optimization is formed. On such CNN-based dynamic programming, if exemplars and test patterns are presented as the goals and the start positions, respectively, the optimal paths from test patterns to their closest exemplars are found. Such paths are utilized as aggregating keys for the classification. The algorithm is similar to the conventional neural network-based method in the use of the exemplar patterns but quite different in the use of the most likely path finding of the dynamic programming. The pattern classification is performed well regardless of degree of the nonlinearity in class borders.

Extraction of Simplified Boundary In Binary Image (이진 영상에서의 단순화된 윤곽선 추출 방법)

  • 김성영
    • Journal of the Korea Society of Computer and Information
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    • v.4 no.4
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    • pp.34-39
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    • 1999
  • In this paper, boundary extraction algorithm is suggested by removing boundary noises efficiently and simplifying object shape in binary image. To remove boundary noises, $2{times}2$ mask boundary extraction algorithm is modified . Proposed method is designed to generate a symmetric path for the parasitic branch noise and to analysis traced features on end point of noise. It can extract more simplified object boundary but preserve original object shape by combining white background color extraction result with foreground extraction result. The usefulness of the proposed method was proved through experiments with various binary images.

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Hybrid approach combining Data Envelopment Analysis and Machine Learning to Evaluate the Efficiency of System Integration Projects (SI 프로젝트의 효율성 평가를 위해 자료포괄분석과 기계학습을 결합한 하이브리드 분석)

  • Hong Han-Kuk;Kim Jong-Weon;Seo Bo-Ra
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 2006.05a
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    • pp.77-88
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    • 2006
  • Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

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Co-Simulation for Systematic and Statistical Correction of Multi-Digital-to-Analog-Convertor Systems

  • Park, Youngcheol;Yoon, Hoijin
    • Journal of electromagnetic engineering and science
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    • v.17 no.1
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    • pp.39-43
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    • 2017
  • In this paper, a systematic and statistical calibration technique was implemented to calibrate a high-speed signal converting system containing multiple digital-to-analog converters (DACs). The systematic error (especially the imbalance between DACs) in the current combining network of the multi-DAC system was modeled and corrected by calculating the path coefficients for individual DACs with wideband reference signals. Furthermore, by applying a Kalman filter to suppress noise from quantization and clock jitter, accurate coefficients with minimum noise were identified. For correcting an arbitrary waveform generator with two DACs, a co-simulation platform was implemented to estimate the system degradation and its corrected performance. Simulation results showed that after correction with 4.8 Gbps QAM signal, the signal-to-noise-ratio improved by approximately 4.5 dB and the error-vector-magnitude improved from 4.1% to 1.12% over 0.96 GHz bandwidth.

A Multi Upper Bound Access Control Model with Inheritance Attributes

  • Kim, Seok-Woo
    • Journal of Electrical Engineering and information Science
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    • v.2 no.6
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    • pp.162-166
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    • 1997
  • A message server have two basic functionalities, a server role for processing the processing the user environment as well as an entity role for transferring message to other entity in message system environment. The user who is going to send and receive his important information really wants to keep his own security requests. To satisfy this requirement, message server must be enforced by two seperated security policies- one for message processing security policy under department's computer working environment, the other for send/receive security policy under message system's communication path environment. Proposed access control model gurantees the user's security request by combining constrained server access control and message system access control with multi upper bound properties which come from inheritance attributes of originating user security contexts.

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A Proposal on Waterfront Development Reflecting the Sense of Place of Pusan South Harbor Area (부산남항의 장소적 특성을 고려한 워터프런트 개발방향)

  • 조용수;조은석
    • Journal of Korean Port Research
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    • v.14 no.4
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    • pp.407-418
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    • 2000
  • Although there are a lot of primary factors to be able to make characters and identities in Pusan South Harbor, Badly Planned development prevented enhancing the sense of place in urban waterfront. The point in the waterfront development is how to secure amenities based on indentity and orientation; node, landmark, edge, path, district. This study aims at developing waterfront area of Pusan South Harbor and attempting to establish an identity through studying characteristics of ‘places’ in Pusan South Harbor. The place consists of two elements; orientation and identity, which can be explained the environmental totality, ‘character’ and ‘space’ respectively. The urban waterfront has strong characteristics which consists of land area, water area, and transit zone combining two areas. The place of Pusan South Harbor is analysed those four elements. We proposed objectives and criteria which can be used in enhancing the sense of this place.

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constraints Identification in Time-varying Obstacle Avoidance for Mechanical Manipulators (기계적 매니퓰 레이터의 시변 물체 회피에서의 제약조건인식)

  • Lee, Bum-Hee;Ko, Myoung-Sam;Ha, In-Joong
    • Proceedings of the KIEE Conference
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    • 1987.07a
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    • pp.230-233
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    • 1987
  • This paper addresses the identification of various constraints in time-varying obstacle avoidance for mechanical manipulators. The manipulator constraints include the smoothness constraint and torque constraint, while the environmental constraints include a motion priority, a traveling time constraint, a path constraint, and a collision constraint. The inherent difficulties in combining these constraints are discussed with a suggestion for the purpose of time-varying obstacle avoidance.

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Intention-Oriented Itinerary Recommendation Through Bridging Physical Trajectories and Online Social Networks

  • Meng, Xiangxu;Lin, Xinye;Wang, Xiaodong;Zhou, Xingming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.12
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    • pp.3197-3218
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    • 2012
  • Compared with traditional itinerary planning, intention-oriented itinerary recommendations can provide more flexible activity planning without requiring the user's predetermined destinations and is especially helpful for those in unfamiliar environments. The rank and classification of points of interest (POI) from location-based social networks (LBSN) are used to indicate different user intentions. The mining of vehicles' physical trajectories can provide exact civil traffic information for path planning. This paper proposes a POI category-based itinerary recommendation framework combining physical trajectories with LBSN. Specifically, a Voronoi graph-based GPS trajectory analysis method is utilized to build traffic information networks, and an ant colony algorithm for multi-object optimization is implemented to locate the most appropriate itineraries. We conduct experiments on datasets from the Foursquare and GeoLife projects. A test of users' satisfaction with the recommended items is also performed. Our results show that the satisfaction level reaches an average of 80%.