• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.206-208
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• 2002

Distributed generation (DG) is predicted to play an increasing role in the electric power system of the near future. Distributed generation is by definition that is of limited size (roughly 10MW or less) and interconnected at the substation, distribution feeder or customer load levels. The effects of generation sources within a distribution network on the system losses are investigated in this paper. WLAV state estimation is performed with the composite distribution system containing DG. Simulations with test cases are performed and the results are presented, using IEEE34 bus radial distribution system.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.215-220
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• 2014

We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.375-375
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• 2000

Estimating software development effort remains a complex problem attracting considerable research attention. Improving the estimation techniques available to project managers would facilitate more effective control of time and budgets in software development as well as market. However, estimation is difficult because of its similarity to export judgment approaches and fur its potential as an expert assistant in support of human judgment. Especially, in software development for DCS (Distributed Control System), because of infrastructure software related to target-machines hardware and process characteristics should be considered, estimating software development effort is more complex. This paper suggests software development effort estimation technique using neural network. The methods considered are based on COCOMO and case-based projects. Estimation results applied to case-based project appeared to have value fur software development effort estimation models.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.4
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• pp.1-10
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• 2010

In this study, two estimation equations for preparing stream data for distributed storm runoff model were developed by analyzing the nonlinear relation between upstream flow-length and stream width, and between upstream flow-length and stream bed-slope. The equations for stream cell were tested in Chungjudam watershed (6,661 $km^2$) using KIMSTORM. Six storm events occurring between 2003 and 2008 were selected for the model calibration and verification before the test of equations. The average values of the Nash-Sutcliffe model efficiency (ME), the volume conservation index (VCI), the relative error of peak runoff rate (EQp), and the difference of time to peak runoff (DTp) were 0.929, 1.035, 0.037, and -0.406 hr for the calibrated four storm events and 0.956, 0.939, 0.055, and 0.729 hr for the two verified storm events respectively. The estimation equations were tested to the storm events, and compared the flood hydrograph. The test result showed that the estimation equation of stream width reduced the peak runoff and delaying the time to peak runoff, and the estimation equation of stream bed-slope showed the opposite results.

• Journal of Broadcast Engineering
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• v.15 no.1
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• pp.112-121
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• 2010

Distributed video coding is a coding paradigm that allows complexity to be shared between encoder and decoder, in contrast with conventional video coding. We propose that complexity balancing method of encoder/decoder by phase motion estimation algorithm. The encoder performs partial motion estimation. The result of the partial motion estimation is transferred to the decoder, and the decoder performs motion estimation within the narrow range. When the encoder can afford some complexity, complexity balancing is possible. The method proposed is able to know relativity between complexity balancing and coding efficiency. The coding efficiency increase rate by the encoder complexity increases is higher than that by the decoder complexity increases. The proposed method can control the complexity and coding efficiency according to devices' resources and channel conditions.

• Smart Structures and Systems
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• v.19 no.4
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• pp.383-391
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• 2017

In this paper, we investigate the impacts of network topology on the performance of a distributed estimation algorithm, namely combine-then-adaptive (CTA) diffusion LMS, based on the data with or without the assumptions of temporal and spatial independence with noisy links. The study covers different network models, including the regular, small-world, random and scale-free whose the performance is analyzed according to the mean stability, mean-square errors, communication cost (link density) and robustness. Simulation results show that the noisy links do not cause divergence in the networks. Also, among the networks, the scale free network (heterogeneous) has the best performance in the steady state of the mean square deviation (MSD) while the regular is the worst case. The robustness of the networks against the issues like node failure and noisier node conditions is discussed as well as providing some guidelines on the design of a network in real condition such that the qualities of estimations are optimized.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.6
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• pp.533-538
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• 2004

Recently, it is increasing the concern of distributed generations(DGs) that installed small power at a site near by the customer. In deregulation environment, not only distributed generation operation but also state estimation is the key function in distribution systems. This paper process to calculate the impact of distributed generation on a distribution feeder. WLAV state estimation is performed the distribution systems with DGs and bad data test including single, multiple, interacting. Simulations with test cases are performed and the results are presented, using IEEE 34 bus radial distribution systems

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.327-330
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• 2003

This paper proposes an estimation algorithm for the generating power of distributed generations(DG) interconnected with distribution networks. These days, DG are rapidly increasing and most of them are interconnected with distribution networks. The DG can supply power into the distribution network, which may make significant impact on fault current and the protection scheme of the interconnected distribution networks. Generally these influences of DG is proportioned as the distributed generator's power. Therefore, it is important to forecast the output power of distributed generator in PCC(point of common coupling). This paper presents the prediction method of DG's power by monitoring the current and phase difference.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.731-739
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• 2017

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low complexity video sampling. In DCVS schemes, motion estimation & motion compensation is employed at the decoder side, similarly to distributed video coding (DVC), for a low-complex encoder. However, since a simple BCS-SPL algorithm is applied to a residual arising from motion estimation and compensation in conventional MC-BCS-SPL (motion compensated block compressed sensing with smoothed projected Landweber) scheme, the reconstructed visual qualities are severly degraded in Wyner-Ziv (WZ) frames. Furthermore, the scheme takes lots of iteration to reconstruct WZ frames. In this paper, the conventional MC-BCS-SPL algorithm is improved to be operated in more effective way in WZ frames. That is, first, the proposed algorithm calculates a correlation coefficient between two reference key frames and, then, by selecting adaptively the reference frame, the residual reconstruction in pixel domain is performed to the conventional BCS-SPL scheme. Experimental results show that the proposed algorithm achieves significantly better visual qualities than conventional MC-BCS-SPL algorithm, while resulting in the significant reduction of the decoding time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.559-575
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• 2023

3D human pose estimation is widely applied in various fields, including action recognition, sports analysis, and human-computer interaction. 3D human pose estimation has achieved significant progress with the introduction of convolutional neural network (CNN). Recently, several researches have proposed the use of multiview approaches to avoid occlusions in single-view approaches. However, as the number of cameras increases, a 3D pose estimation system relying on a CNN may lack in computational resources. In addition, when a single host system uses multiple cameras, the data transition speed becomes inadequate owing to bandwidth limitations. To address this problem, we propose a distributed real-time 3D pose estimation framework based on asynchronous multiple cameras. The proposed framework comprises a central server and multiple edge devices. Each multiple-edge device estimates a 2D human pose from its view and sendsit to the central server. Subsequently, the central server synchronizes the received 2D human pose data based on the timestamps. Finally, the central server reconstructs a 3D human pose using geometrical triangulation. We demonstrate that the proposed framework increases the percentage of detected joints and successfully estimates 3D human poses in real-time.