• 제목/요약/키워드: residual network

검색결과 462건 처리시간 0.023초

배수관망의 잔류염소 평활화를 위한 최적 재염소 처리 (Optimal Rechlorination for the Regulation of Chlorine Residuals in Water Distribution Systems)

  • 윤재흥;오정우;최영송
    • 상하수도학회지
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    • 제12권2호
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    • pp.90-98
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    • 1998
  • The optimal rechlorination in water distribution systems was investigated by incorporating optimization techniques into a numerical water quality model. For a hypothetical system that consists of 10 junctions including a storage tank and 12 links, the bulk ($k_b$) and pipe-wall ($k_w$) decay-rate constants of chlorine residual are assumed to be 2.0 1/day and 1.5 m/day, respectively. It was also assumed that the lower and upper limits of chlorine residual in the network are 0.2 mg/L and 0.6 mg/L. When the chlorine source is only the storage tank (without rechlorination), the high levels of chlorine residual appear near the storage tank to maintain the chlorine residuals above the lower limit over the junctions. On the other hand, the chlorine residuals in the network are distribute within the desirable range (0.2 - 0.6 mg/L) after the optimal rechlorination through five injection sites including the storage tank. In case of a real water distribution system that comprises 28 junctions including a clear well and 27 links, the bulk and pipe-wall decay-rate constants are 0.3 1/day and 0.2 m/day, respectively. Before rechlorination, the required chlorine residual at the clearwell is 5.1 mg/L to keep the chlorine residuals above the minimum level (0.6 mg/L) over the junctions. By the optimal rechlorination at five injection sites, the chlorine residuals are distributed within a desirable range of 0.6 mg/L through 2.0 mg/L, which can avoid the excess of chlorine residuals near the clear well. Consequently, total chlirine doses are decreased by 81% in the hypothetical distribution network and 69 % in the real distribution network for satisfying the minimum chlorine residuals.

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모바일 Deep Residual Network을 이용한 뎁스 영상 기반 1 인칭 시점 VR 손동작 인식 (Depth Image based Egocentric 3D Hand Pose Recognition for VR Using Mobile Deep Residual Network)

  • 박혜민;박나현;오지헌;이철우;최형우;김태성
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2019년도 추계학술발표대회
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    • pp.1137-1140
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    • 2019
  • 가상현실(Virtual Reality, VR), 증강현실(Augmented Reality, AR), 혼합현실(Mixed Reality, MR) 분야에 유용한 인간 컴퓨터 인터페이스 기술은 필수적이다. 특히 휴먼 손동작 인식 기술은 직관적인 상호작용을 가능하게 하여, 다양한 분야에서 편리한 컨트롤러로 사용할 수 있다. 본 연구에서는 뎁스 영상 기반의 1 인칭 시점 손동작 인식을 위하여 손동작 데이터베이스 생성 시스템을 구축하여, 손동작 인식기 학습에 필요한 1 인칭(Egocentric View Point) 데이터베이스를 촬영하여 제작한다. 그리고 모바일 Head Mounted Device(HMD) VR 을 위한 뎁스 영상 기반 1 인칭 시점 손동작 인식(Hand Pose Recognition, HPR) 딥러닝 Deep Residual Network 를 구현한다. 최종적으로, 안드로이드 모바일 디바이스에 학습된 Residual Network Regressor 를 이식하고 모바일 VR 에 실시간 손동작 인식 시스템을 구동하여, 모바일 VR 상 실시간 3D 손동작 인식을 가상 물체와의 상호작용을 통하여 확인 한다.

부분 최소 자승법과 잔차 보상기를 이용한 비선형 데이터 분류 (Non-linear Data Classification Using Partial Least Square and Residual Compensator)

  • 김경훈;김태영;최원호
    • 제어로봇시스템학회논문지
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    • 제10권2호
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    • pp.185-191
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    • 2004
  • Partial least squares(PLS) is one of multiplicate statistical process methods and has been developed in various algorithms with the characteristics of principal component analysis, dimensionality reduction, and analysis of the relationship between input variables and output variables. But it has been limited somewhat by their dependency on linear mathematics. The algorithm is proposed to classify for the non-linear data using PLS and the residual compensator(RC) based on radial basis function network (RBFN). It compensates for the error of the non-linear data using the RC based on RBFN. The experimental result is given to verify its efficiency compared with those of previous works.

Virtual Resource Allocation in Virtualized Small Cell Networks with Physical-Layer Network Coding Aided Self-Backhauls

  • Cheng, Yulun;Yang, Longxiang;Zhu, Hongbo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권8호
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    • pp.3841-3861
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    • 2017
  • Virtualized small cell network is a promising architecture which can realize efficient utilization of the network resource. However, conventional full duplex self-backhauls lead to residual self-interference, which limits the network performance. To handle this issue, this paper proposes a virtual resource allocation, in which the residual self-interference is fully exploited by employing a physical-layer network coding (PNC) aided self-backhaul scheme. We formulate the features of PNC as time slot and information rate constraints, and based on that, the virtual resource allocation is formulated as a mixed combinatorial optimization problem. To solve the problem efficiently, it is decomposed into two sub problems, and a two-phase iteration algorithm is developed accordingly. In the algorithm, the first sub problem is approximated and transferred into a convex problem by utilizing the upper bound of the PNC rate constraint. On the basis of that, the convexity of the second sub problem is also proved. Simulation results show the advantages of the proposed scheme over conventional solution in both the profits of self-backhauls and utility of the network resource.

수중음향 센서 네트워크에서 효율적인 저전력 군집화 기법 (An Energy-Efficient Clustering Scheme in Underwater Acoustic Sensor Networks)

  • 이재훈;서보민;조호신
    • 한국음향학회지
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    • 제33권5호
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    • pp.341-350
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    • 2014
  • 본 논문에서는 수중음향 센서 네트워크에서 자기 조직화 기법을 활용하는 에너지 효율적 클러스터링 기법을 제안한다. 제안 기법은 클러스터 헤드 선출에 각 노드의 배터리 잔여량 정보와 이웃 노드의 수를 고려하며, 클러스터 헤드의 배터리 잔여량이 특정 수준 이하로 떨어졌을 경우에만 클러스터 재구성을 수행함으로써 노드의 에너지 소모를 줄이고 네트워크 전체에 에너지 소모를 분산시켜 네트워크의 수명을 연장시킬 수 있다. 또한, 클러스터 헤드는 클러스터 멤버 노드로부터 수집한 데이터를 다중 홉 중계 방식으로 싱크 노드에 전송하여 에너지 소모를 줄인다. 컴퓨터 모의실험을 통해, 일정 시간 경과 후 전체 노드의 배터리 잔여량의 합, 생존 노드의 수, 네트워크 구성 단계에서의 에너지 소모량, 전체 노드의 에너지 소모 편차 등을 구하고 대표적 클러스터링 기법 중의 하나인 LEACH 기법과 비교 및 분석한다. 모의실험 결과, 제안 기법이 LEACH 기법에 비해 네트워크 운용 시간을 두 배 향상시킬 수 있으며, 전체 노드의 에너지 소모 편차 또한 감소시킴을 알 수 있다.

Performance Analysis of Low-Order Surface Methods for Compact Network RTK: Case Study

  • Song, Junesol;Park, Byungwoon;Kee, Changdon
    • Journal of Positioning, Navigation, and Timing
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    • 제4권1호
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    • pp.33-41
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    • 2015
  • Compact Network Real-Time Kinematic (RTK) is a method that combines compact RTK and network RTK, and it can effectively reduce the time and spatial de-correlation errors. A network RTK user receives multiple correction information generated from reference stations that constitute a network, calculates correction information that is appropriate for one's own position through a proper combination method, and uses the information for the estimation of the position. This combination method is classified depending on the method for modeling the GPS error elements included in correction information, and the user position accuracy is affected by the accuracy of this modeling. Among the GPS error elements included in correction information, tropospheric delay is generally eliminated using a tropospheric model, and a combination method is then applied. In the case of a tropospheric model, the estimation accuracy varies depending on the meteorological condition, and thus eliminating the tropospheric delay of correction information using a tropospheric model is limited to a certain extent. In this study, correction information modeling accuracy performances were compared focusing on the Low-Order Surface Model (LSM), which models the GPS error elements included in correction information using a low-order surface, and a modified LSM method that considers tropospheric delay characteristics depending on altitude. Both of the two methods model GPS error elements in relation to altitude, but the second method reflects the characteristics of actual tropospheric delay depending on altitude. In this study, the final residual errors of user measurements were compared and analyzed using the correction information generated by the various methods mentioned above. For the performance comparison and analysis, various GPS actual measurement data were collected. The results indicated that the modified LSM method that considers actual tropospheric characteristics showed improved performance in terms of user measurement residual error and position domain residual error.

에러율이 높은 무선 센서 네트워크의 수명을 연장시키기 위한 라우팅 기법 (A Routing Mechanism to Prolong the Lifetime of Error-Prone Wireless Sensor Networks)

  • 최재원;이광휘
    • 대한전자공학회논문지TC
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    • 제46권8호
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    • pp.43-49
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    • 2009
  • 본 논문에서는 에러율이 높은 무선 센서 네트워크의 수명을 연장시키기 위한 라우팅 알고리즘을 제안한다 제안하는 기법은 무선 링크의 품질을 기반으로 하여 패킷을 송수신한 이후의 잔여 에너지를 미리 추정하고, 그 때의 에너지가 가장 많이 남아 있을 것으로 예상되는 경로로 데이터를 전송한다. 제안하는 기법은 에러율을 고려하기 때문에 불필요한 재전송에 따른 에너지 소비를 줄이고 트래픽도 골고루 분산시킨다. 그리고 송수신 이후의 잔여 에너지양들 중에서 최소값이 가장 클 것으로 예상되는 경로를 선택함으로써 노드의 에너지 고갈을 최대한으로 지연시킨다. 다른 방식들에 비하여 제안하는 기법이 네트워크의 수명을 더욱 연장시킨다는 사실을 실험을 통하여 확인할 수 있었다.

합성곱 신경망을 이용한 선박의 잉여저항계수 추정 (Prediction of Residual Resistance Coefficient of Ships using Convolutional Neural Network)

  • 김유철;김광수;황승현;연성모
    • 대한조선학회논문집
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    • 제59권4호
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    • pp.243-250
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    • 2022
  • In the design stage of hull forms, a fast prediction method of resistance performance is needed. In these days, large test matrix of candidate hull forms is tested using Computational Fluid Dynamics (CFD) in order to choose the best hull form before the model test. This process requires large computing times and resources. If there is a fast and reliable prediction method for hull form performance, it can be used as the first filter before applying CFD. In this paper, we suggest the offset-based performance prediction method. The hull form geometry information is applied in the form of 2D offset (non-dimensionalized by breadth and draft), and it is studied using Convolutional Neural Network (CNN) and adapted to the model test results (Residual Resistance Coefficient; CR). Some additional variables which are not included in the offset data such as main dimensions are merged with the offset data in the process. The present model shows better performance comparing with the simple regression models.

Cavitation state identification of centrifugal pump based on CEEMD-DRSN

  • Cui Dai;Siyuan Hu;Yuhang Zhang;Zeyu Chen;Liang Dong
    • Nuclear Engineering and Technology
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    • 제55권4호
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    • pp.1507-1517
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    • 2023
  • Centrifugal pumps are a crucial part of nuclear power plants, and their dependable and safe operation is crucial to the security of the entire facility. Cavitation will cause the centrifugal pump to violently vibration with the large number of vacuoles generated, which not only affect the hydraulic performance of the centrifugal pump but also cause structural damage to the impeller, seriously affecting the operational safety of nuclear power plants. A closed cavitation test bench of a centrifugal pump is constructed, and a method for precisely identifying the cavitation state is proposed based on Complementary Ensemble Empirical Mode Decomposition (CEEMD) and Deep Residual Shrinkage Network (DRSN). First, we compared the cavitation sensitivity of pressure fluctuation, vibration, and liquid-borne noise and decomposed the liquid-borne noise by CEEMD to capture cavitation characteristics. The decomposition results are sent into a 12-layer deep residual shrinkage network (DRSN) for cavitation identification training. The results demonstrate that the liquid-borne noise signal is the most cavitation-sensitive signal, and the accuracy of CEEMD-DRSN to identify cavitation at different stages of centrifugal pumps arrives at 94.61%

Non-midway 광 위상 공액기를 갖는 분산 제어 전송 링크를 통한 WDM 채널의 왜곡 보상 (Compensation for the Distorted WDM Channels through the Dispersion-managed Optical Links with Non-midway Optical Phase Conjugator)

  • 이성렬
    • 한국항행학회논문지
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    • 제19권6호
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    • pp.595-600
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    • 2015
  • 전통적인 midway 광 위상 공액기 (OPC; optical phase conjugator)가 아닌 non-midway OPC를 분산 제어 (DM; dispersion-managed) 광전송 링크에 적용하여 파장 분할 다중 전송 (WDM; wavelength division multiplexed)을 위한 융통적인 네트워크의 구성 가능성을 분석하였다. 중계 구간의 수가 많을수록, 또한 중계 구간 당 잉여 분산 (RDPS; residual dispersion per span)이 클수록 non-midway OPC를 통한 유연한 링크의 구성 가능성이 커지는 것을 확인하였다. 아울러 OPC 이후의 후반 전송 구획을 구성하는 각 중계 구간의 RDPS를 OPC 이전의 전반 구획의 RDPS의 평균값으로 설정하는 링크 구조가 융통적 링크 구성에 더욱 유리하다는 것을 확인하였다.