• Title/Summary/Keyword: 망 조정

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Adjustment of the Korean Secondary Level Net (우리나라 2등수준강의 조정)

  • 이석찬;조규전;이영진;이창경
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.6 no.2
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    • pp.1-9
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    • 1988
  • The main objective of the study is to execute the simultaneous adjustment of the secondary level net on the basis of the 1st order level net adjustment carried in 1987. Moreover, the basic raw field data obtained during last 21-years(’67~’87) is to be analyzed, corrected and edited in order to carry out a reasonable adjustment of the End order level net. As the result of the study, we obtained mean random error η=1.99$^{mm}$ /√km, mean systematic error ξ=2.09$^{mm}$ /√km, square root of the posterior reference variance $\sigma$$_{0}$ =9.12$^{mm}$ /√km and concluded that the accuracy obtained is good enough for the category of precision levelling.

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An Exploratory Study on Sales and Operations Planning as SCM Supporting Tool (공급망 관리 지원도구로서의 S&OP 운영에 관한 탐색적 연구)

  • Park, Seong Taek;Kim, Tae Ung;Kim, Mi Ryang
    • Journal of Digital Convergence
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    • v.19 no.2
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    • pp.93-103
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    • 2021
  • S&OP(Sales and Operations Planning) is an ongoing process of periodic planning, reviewing, and evaluation through the involvement of all key stakeholders. Within this process, performance is regularly reviewed and early warning signals are generated, so that the company can react quickly to changing market and operational environment. This paper presents a framework for effective S&OP for fair alignment, accountability, teamwork, visibility, and risk management. This framework focuses on supply chain information governance, level of information sharing through S&OP, role of S&OP as coordination mechanism, APS effectivesness as a planning tool and SCM performance. In addition, a brief case study on the operating characteristics of S&OP at three Korean firms is presented. Implications of the study finding are also provided. It will also make companies that are considering the introduction of S&OP aware of the importance of S&OP, which will provide practical guidelines for the introduction of S&OP.

Optimal Network Design for Enhancing the Precision of National Geodetic Network (국가 측지망의 정밀도 향상을 위한 최적 측지망 설계에 관한 연구)

  • Cho, Jae-Myoung;Yun, Hong-Sik;Wie, Gwang-Jae
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.6
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    • pp.587-594
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    • 2010
  • This paper describe the optimal design of geodetic network by analytical technique based on the quality criteria of network. We described an example of geodetic network design taking into account the precision, reliability and robustness that are the main criteria of network design. The main goal of this paper is to evaluate the criteria to design the geodetic network coinciding with the criteria of high precision(error ellipse, 2DRMS, CEP), reliability(internal and external reliability) and robustness(maximum shear strain, principal strain, dilatation). The network design parameters computed in this study show that precision and reliability has not much improved by about 2% and 3%, respectively, than the observed network, while robustness has much improved by about 3, 100%. It also shown that maximum errors of precision, reliability and robustness were reduced by 5%, 7% and 16,957%, respectively.

Efficient Multiple Multicast Algorithms in Wormhole - Routed Networks (웜홀 라우팅 망에서의 효율적인 다중 멀티캐스트 알고리즘)

  • Kim, Si-Gwan;Cho, Jung-Wan
    • Journal of KIISE:Computer Systems and Theory
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    • v.27 no.4
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    • pp.373-382
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    • 2000
  • The most important metric in wormhole-routed networks is the start-up latency. In this paper, we present new multicast algorithms that reduce node contention so that multiple multicast messages can be implemented with reduced latency. By exploiting available channels evenly as much as possible, these new algorithms show better performance than the existing multicast algorithms for wormhole 2D systems when multiple multicasts are involved. All algorithms presented are proven to be deadlock-free. A simulation study has been conducted that compares the performance of these multicast algorithms under various situations in a 2D mesh. We show that the overall performance of ours are up to 20% better than the previous studies. We observe that reducing the number of the generated multidestination messages closely related to shorter message latency. These proposed algorithms can be easily extended to 3D mesh systems.

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RNG-based Scatternet Formation Algorithm for Small-Scale Ad-Hoc Network (소규모 분산망을 위한 RNG 기반 스캐터넷 구성 알고리즘)

  • Cho, Chung-Ho
    • Journal of Internet Computing and Services
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    • v.8 no.4
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    • pp.17-29
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    • 2007
  • This paper addresses a RNG based scatternet topology formation, self-healing, and routing path optimization for small-scale distributed environment, which is called RNG-FHR(Scatternet Formation, self-Healing and self-Routing path optimization) algorithm. We evaluated the algorithm using ns-2 and extensible Bluetoothsimulator called blueware to show that RNG-FHR does not have superior performance, but is simpler and more practical than any other distributed algorithms from the point of depolying the network in the small-scale distributed dynamic environment due to the exchange of fewer messages and local control. As a result, we realized that even though RNG-FHR is unlikely to be possible for deploying in large-scale environment, it surely can be deployed for performance and practical implementation in small-scale environment.

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Generative Korean Inverse Text Normalization Model Combining a Bi-LSTM Auxiliary Model (Bi-LSTM 보조 신경망 모델을 결합한 생성형 한국어 Inverse Text Normalization 모델)

  • Jeongje Jo;Dongsu Shin;Kyeongbin Jo;Youngsub Han;Byoungki Jeon
    • Annual Conference on Human and Language Technology
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    • 2023.10a
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    • pp.716-721
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    • 2023
  • Inverse Text Normalization(ITN) 모델은 음성 인식(STT) 엔진의 중요한 후처리 영역 중 하나이며, STT 인식 결과의 가독성을 개선한다. 최근 ITN 모델에 심층신경망을 활용한 연구가 진행되고 있다. 심층 신경망을 사용하는 대부분의 선행연구는 문장 내 변환이 필요한 부분에 토큰 태깅을 진행하는 방식이다. 그러나 이는 Out-of-vocabulary(OOV) 이슈가 있으며, 학습 데이터 구축 시 토큰 단위의 섬세한 태깅 작업이 필요하다는 한계점이 존재한다. 더불어 선행 연구에서는 STT 인식 결과를 그대로 사용하는데, 이는 띄어쓰기가 중요한 한국어 ITN 처리에 변환 성능을 보장할 수 없다. 본 연구에서는 BART 기반 생성 모델로 생성형 ITN 모델을 구축하였고, Bi-LSTM 기반 보조 신경망 모델을 결합하여 STT 인식 결과에 대한 고유명사 처리, 띄어쓰기 교정 기능을 보완한 모델을 제안한다. 또한 보조 신경망을 통해 생성 모델 처리 여부를 판단하여 평균 추론 속도를 개선하였다. 실험을 통해 두 모델의 각 정량 성능 지표에서 우수한 성능을 확인하였고 결과적으로 본 연구에서 제안하는 두 모델의 결합된 방법론의 효과성을 제시하였다.

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Construction of the I-PD Control System by Multilayer Neural Network (다층 신경망에 의한 I-PD 제어계의 구성)

  • 고태언
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.1
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    • pp.74-79
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    • 2002
  • Many control techniques have been proposed in order to improve the control performance in discrete-time domain control system. In control system using these techniques, the response-characteristic of system is dependent on the gains of the controller. Specially, There is a need to readjust the gain of controller when the response of system is changed by disturbance or load fluctuation. In this paper, I-PD controller and pre-compensator are designed by multilayer neural network. The gains of I-PD controller and pre-compensator are adjusted automatically by back propagation algorithm when the response characteristic of system is changed under a condition. Applying this control technique to the position control system using a DC servo motor as a driver, the control performance of controller is verified by the results of experiment.

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Supply Chain Contract Model with Vague Demand Information (모호한 수요정보에서의 공급망 계약 모델)

  • Kim, Gi-Tae;Park, Jun-Cheul
    • The Journal of Information Systems
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    • v.21 no.2
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    • pp.181-196
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    • 2012
  • 본 논문은 고객의 수요정보에 대해 모호한 정보를 가진 공급자와 구매자 사이의 공급망 계약에 관한 것을 다루고 있는 것으로, 고객 수요에 대한 불확실성은 확률적 프로그래밍 모델에서 공식적으로 다루어져왔다. 확률적 프로그램의 한 가지 핵심적인 가정은 널리 알려져 있는바와 같이 수요에 대한 확률분포가 알려져 있다는 것이다. 그럼에도 불구하고 만약 수요에 대한 정보가 모호하거나 정확하지 않다면 수요에 대한 확률분포가 정확하지 않다는 점이다. 이런 상황에서 퍼지 이론은 수요정보를 나타내는데 유용하다고 할수 있다. 본 논문은 퍼지 랜덤수요변수들을 분산시스템의 공급망 계약에서 다루고 있다. 이 계약은 구매자의 주문량을 조정하는 옵션을 이용한다. 본 연구는 퍼지 랜덤 변수들을 GMIR(Graded Mean Integration Representation)을 이용하여, 알고리즘을 통해 구현함으로써 실증적 결과 값을 제시하고 미래 연구의 확장 가능성을 제시하고 있다.

A Natural Language Information Retrieval Model using Automatic Network and Two-level Document Ranking (자동 키워드망과 2단계 문서 순위 결정에 의한 자연어 정보검색 모델)

  • Kang, Hyun-Kyu;Park, Se-Young;Choi, Key-Sun
    • Annual Conference on Human and Language Technology
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    • 1995.10a
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    • pp.8-12
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    • 1995
  • 본 논문은 정보검색에서 사용자에게 순서화된 문서를 제시하기 이전에 1차로 검색된 문서들에 대하여 자동 키워드망과 2단계로 문서 순위 결정하는 모델에 대하여 논하였다. 자연어 검색을 위한 색인은 자동으로 구축된 키워드 색인으로 1차로 자연어 검색을 하고, 2차로 자동 키워드망을 이용한 순위재조정을 통해 검색효율의 향상에 관해 검색 효율을 평가하여 1차 검색 결과보다 최대 10.9%의 검색효율 향상을 보였다. 또한 문서 순위 조정 방법에 있어서 여러 가지 공식을 비교 분석하였으며 내용 검색을 반영하는 공식을 찾았다. 본 논문에서 제시한 2단계 순위 결정 방법은 리스트를 기반으로 하는 정보 검색의 분야에 적용되어 검색효율을 높일 수 있는 한가지 방법이 될 수 있을 것이다.

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Design of the Combined Direct and Indirect Adaptive Neural Controller Using Fuzzy Rule (퍼지규칙에 의한 직.간접 혼합 신경망 적응제어시스템의 설계)

  • 이순영;장순용
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.3
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    • pp.603-610
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    • 2000
  • In this paper, the direct and indirect adaptive controller are combined based on the Lyapunov synthesis approach. The Proposed controller is constructed from RBF Neural Network and weighting parameters are adjusted on-line according to some adaptation law. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. In the results, proposed controller has the main advantages of both the direct adaptive controller and the indirect adaptive controller. The effectiveness of the proposed control scheme is demonstrated through simulation results of control for one-link rigid robotics manipulator.

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