• 제어로봇시스템학회논문지
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• 제20권12호
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• pp.1225-1230
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• 2014

This paper investigates the group average-consensus and group formation-consensus problems for first-order multi-agent systems. The control protocol for group consensus is designed by considering the positive adjacency elements. Since each intra-group Laplacian matrix cannot be satisfied with the in-degree balance because of the positive adjacency elements between groups, we decompose the Laplacian matrix into an intra-group Laplacian matrix and an inter-group Laplacian matrix. Moreover, average matrices are used in the control protocol to analyze the stability of multi-agent systems with a fixed and undirected communication topology. Using the graph theory and the Lyapunov functional, stability analysis is performed for group average-consensus and group formation-consensus, respectively. Finally, some simulation results are presented to validate the effectiveness of the proposed control protocol for group consensus.

• 융합신호처리학회논문지
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• 제14권4호
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• pp.243-248
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• 2013

무선 센서 네트워크에서 동적 시스템에 대한 consensus 알고리듬은 센서 네트워크의 데이터 융합을 위해 신축적인 알고리듬을 적용할 수 있다. 본 논문은 분산 센서 데이터 기반의 평균적인 consensus 특성을 이용하여 n개의 센서 계측치들의 평균을 추적하기 위해 센서 네트워크의 노드들로 구성되는 하나의 분산 데이터 융합 필터를 구현하였다. 본 consensus 필터는 센서 네트워크에서 분산 칼만 필터링에 의한 구조로 데이터 융합의 문제를 해결한다. consensus 필터의 최적 수렴특성, 잡음 전파의 감소 및 빠른 입력신호들의 추적 능력을 보여준다. 필터링 처리 결과를 확인하기 위해 지그비 통신을 이용하여 각 센서의 출력신호와 필터링 처리 결과 및 각 센서의 개별적 신호들을 통합하고 consensus 필터링 처리 결과를 보였다.

• 대기
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• 제21권2호
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• pp.209-220
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• 2011

A new consensus algorithm for the prediction of tropical cyclone track has been developed. Conventional consensus is a simple average of a few fixed models that showed the good performance in track prediction for the past few years. Meanwhile, the consensus in this study is a weighted average of a few models that may change for every individual forecast time. The models are selected as follows. The first step is to find the analogous past tropical cyclone tracks to the current track. The next step is to evaluate the model performances for those past tracks. Finally, we take the weighted average of the selected models. More weight is given to the higher performance model. This new algorithm has been named as DYTRAP (DYnamic data-base Typhoon tRAck Prediction) in the sense that the data base is used to find the analogous past tracks and the effective models for every individual track prediction case. DYTRAP has been applied to all 2009 tropical cyclone track prediction. The results outperforms those of all models as well as all the official forecasts of the typhoon centers. In order to prove the real usefulness of DYTRAP, it is necessary to apply the DYTRAP system to the real time prediction because the forecast in typhoon centers usually uses 6-hour or 12-hour-old model guidances.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2299-2318
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• 2019

Location-aware networks are of great importance for both civil lives and military applications. Methods based on line-of-sight (LOS) measurements suffer sever performance loss in harsh environments such as indoor scenarios, where sensors can receive both LOS and non-line-of-sight (NLOS) measurements. In this paper, we propose a data association (DA) process based on the expectation maximization (EM) algorithm, which enables us to exploit multipath components (MPCs). By setting the mapping relationship between the measurements and scatters as a latent variable, coefficients of the Gaussian mixture model are estimated. Moreover, considering the misalignment of sensor position, we propose a space-alternating generalized expectation maximization (SAGE)-based algorithms to jointly update the target localization and sensor position information. A two dimensional (2-D) circularly symmetric Gaussian distribution is employed to approximate the probability density function of the sensor's position uncertainty via the minimization of the Kullback-Leibler divergence (KLD), which enables us to calculate the expectation step with low computational complexity. Moreover, a distributed implementation is derived based on the average consensus method to improve the scalability of the proposed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms can perform close to the Monte Carlo-based method with much lower communication overhead and computational complexity.

• 센서학회지
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• 제28권5호
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• pp.277-283
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• 2019

In this paper, we propose a distributed fusion estimation for sensor networks using a receding horizon strategy. Communication channels were modelled as Markov jump systems, and a posterior probability distribution for communication channel characteristics was calculated and incorporated into the filter to allow distributed fusion estimation to handle path loss observation situations automatically. To implement distributed fusion estimation, a Kalman-Consensus filter was then used to obtain the average consensus, based on the estimates of sensors randomly distributed across sensor networks. The advantages of the proposed algorithms were then verified using a large-scale sensor network example.

• 한국컴퓨터정보학회논문지
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• 제27권4호
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• pp.27-36
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• 2022

본 논문에서는 이러한 어류 가공 현장의 문제점을 개선하기 위해서 AI 머신 비전을 이용한 어류의 목표 중량 절단 예측기법을 제안한다. 제안하는 방법은 먼저 입력된 물고기의 평면도와 정면도를 촬영하여 이미지기반의 전처리를 수행한다. 그런 다음 RANSAC(RANdom SAMmple Consensus)를 사용하여 어류의 윤곽선을 추출한 다음 3D 모델링을 사용하여 물고기의 3D 외부 정보를 추출한다. 이어서 추출된 3차원 특징 정보와 측정된 중량 정보를 머신러닝하여 목표 중량에 대한 절단 지점을 예측하기 위한 신경망 모델을 생성한다. 마지막으로 제안기법을 통해 예측된 절단 지점으로 직접 절단한 뒤 그 중량을 측정하였다. 그리고 측정된 무게를 목표 무게와 비교하여 MAE(Mean Absolute Error) 와 MRE(Mean Relative Error)와 같은 평가 방법을 사용해 성능을 평가하였다. 그 결과, 목표 중량과 비교해 3% 이내의 평균 오차율을 달성하였다. 제안된 기법은 향후 자동화 시스템과 연계되어 수산업 발전에 크게 기여할 것으로 전망한다.

• ETRI Journal
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• 제46권4호
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• pp.648-659
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• 2024

Author verification is challenging because of the diversity in writing styles. We propose an enhanced handwriting verification method that combines handcrafted and automatically extracted features. The method uses a genetic algorithm to reduce the dimensionality of the feature set. We consider offline Bangla handwriting content and evaluate the proposed method using handcrafted features with a simple logistic regression, radial basis function network, and sequential minimal optimization as well as automatically extracted features using a convolutional neural network. The handcrafted features outperform the automatically extracted ones, achieving an average verification accuracy of 94.54% for 100 writers. The handcrafted features include Radon transform, histogram of oriented gradients, local phase quantization, and local binary patterns from interwriter and intrawriter content. The genetic algorithm reduces the feature dimensionality and selects salient features using a support vector machine. The top five experimental results are obtained from the optimal feature set selected using a consensus strategy. Comparisons with other methods and features confirm the satisfactory results.

• 한국유기농업학회지
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• 제31권3호
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• pp.167-189
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• 2023

Korea has become the highest nitrogen balance (228 kg/ha) among 34 OECD member countries, and has the stigma of being a 'Nutrient overload country' as of 2019. Accordingly, research on the derivation and utilization of nutrient balance indicators and the 'regional nutrient management system' are being promoted to improve Korea's nutrient balance. It is necessary to support these policies and studies, form a public consensus on improving the nutrient balance, and evaluate the function of the public benefit. This paper aims to estimate the public benefit value of improving the nutrient balance based on an analysis of consumers' willingness to pay and recognition of Korea's nutrient excess for 600 consumers nationwide. As results, 21.2% of the respondents said they were aware of excessive nutrients in Korea, and 76.7% of the respondents said they were aware of the need for nutrient management. The average amount of intention to pay for the improvement of three pollution (soil, water quality, and air) that can occur due to a nutrient overload was ￦2,321.1 for soil pollution improvement, ￦2,391.2 for water pollution improvement, and ￦2,377.9 for air pollution improvement. The average willingness to pay for the three pollution reduction was ￦6,002.3. These results are expected to be used to form a public consensus on the balance of payments and to establish measures to enhance public interest values in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권4호
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• pp.547-559
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• 2010

As web-based online communities are rapidly growing, the agents in the communities need to know their measurable belief of trust for safe and successful interactions. In this paper, we propose a computational model of trust resulting from available feedbacks in online communities. The notion of trust can be defined as an aggregation of consensus given a set of past interactions. The average trust of an agent further represents the center of gravity of the distribution of its trustworthiness and untrustworthiness. Furthermore, we precisely describe the relationships among reputation, trust and average trust through concrete examples showing their computations. We apply our trust model to online social networks in order to show how trust mechanisms are involved in the rational purchasing decision-making of buyers and sellers, and we summarize our simulation results.

• Asia pacific journal of information systems
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• 제9권1호
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• pp.143-163
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• 1999

This study investigates the effect of group size on group performance, here the quality of group decision, Four effects are proposed and tested in a field experimental setting : (1) the relationship between the group size and the distribution of individual's problem-solving ability ; (2) the change of the group decision quality as group size increases ; (3) the relationship between the group decision quality and the quality of the best/worst member as group size increases ; (4) the relationship between the group decision quality and the average quality of individuals in the group as group size increases. Data showed that contrary to the exiting results, group decision quality was not improved with the group size. Rather, it showed a little tendency that group decision quality was worsened with the group size. Data also showed that consensus-oriented group decision making process produced the compromised output. Thus, group decision quality was not better than the average group members'. The opinion of the best member was not accepted. The implications of the findings are discussed for the development of a Korean GSS.