• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.327-346
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• 2019

The goal of hyperspectral pansharpening is to combine a hyperspectral image (HSI) with a panchromatic image (PANI) derived from the same scene to obtain a single fused image. In this paper, a new hyperspectral pansharpening approach using adaptive weighted regression and guided filter is proposed. First, the intensity information (INT) of the HSI is obtained by the adaptive weighted regression algorithm. Especially, the optimization formula is solved to obtain the closed solution to reduce the calculation amount. Then, the proposed method proposes a new way to obtain the sufficient spatial information from the PANI and INT by guided filtering. Finally, the fused HSI is obtained by adding the extracted spatial information to the interpolated HSI. Experimental results demonstrate that the proposed approach achieves better property in preserving the spectral information as well as enhancing the spatial detail compared with other excellent approaches in visual interpretation and objective fusion metrics.

• ETRI Journal
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• v.36 no.1
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• pp.171-174
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• 2014

In weighted bit-flipping-based algorithms for low-density parity-check (LDPC) codes, due to the existence of overconfident incorrectly received bits, the metric values of the corresponding bits will always be wrong in the decoding process. Since these bits cannot be flipped, decoding failure results. To solve this problem, an improved parallel weighted bit flipping algorithm is proposed. Specifically, a reliability-saturation strategy is adopted to increase the flipping probability of the overconfident incorrectly received bits. Simulation results show that the error floor of LDPC codes is greatly lowered.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.381-389
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• 2022

Detecting partially occluded objects is difficult due to the appearances and shapes of occluders are highly variable. These variabilities lead to challenges of localizing accurate bounding box or classifying objects with visible object parts. To address these problems, we propose a two-stage part-based attention approach for robust object detection under partial occlusion. First, our part attention network(PAN) captures the important object parts and then it is used to generate weighted object features. Based on the weighted features, the re-weighted object features are produced by our reinforced PAN(RPAN). Experiments are performed on our collected military vehicle dataset and synthetic occlusion dataset. Our method outperforms the baselines and demonstrates the robustness of detecting objects under partial occlusion.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.273-283
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• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.196-204
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• 2013

In this paper, a scheduling algorithm is proposed for military satellite networks to improve QoS(Quality of Service) based on WDRR(Weighted Deficit Round Robin) method. When the packet size that has been queued to be larger, the proposed scheme DWDRR(Dynamic WDRR) method give appropriate additional quantum using EWMA(Exponentially Weighted Moving Average). To demonstrate an usefulness of proposed algorithm using OPNET modeler that built the simulation environment, reliability and real-time availability of the proposed algorithm is analyzed. The simulation results show an availability of proposed scheme in terms of reduce queuing delay and packet drop rate compared and analyzed the existing algorithms WRR(Weighted Round Robin), DRR(Deficit Round Robin) and WDRR with DWDRR.

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.2
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• pp.101-107
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• 2009

In existing wireless ad-hoc networks, how to distribute network resources fairly between many users to optimize data transmission is an important research subject. However, in wireless mesh networks (WMNs), it is one of the research areas to avoid gateway bottleneck more than the fair network resource sharing. It is because WMN traffic are concentrated on the gateway connected to backhaul. To solve this problem, the paper proposes Weighted Fairness Time-sharing Access (WFTA). The proposed WFTA is a priority time scheduling scheme based on Weighted Fair Queuing (WFQ).

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.5
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• pp.31-43
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• 1996

In this paper, we analyze the delay characteristics of the multimdedia traffic in B-ISDN, and propose a weighted variable-size window estimator considering the QoS characteristics of the media and the variable delay characteristics of the networks, and present a delay estimator-based synchronization protocol for the efficient synchronization in ATM-based B-ISDN. The proposed estimator assigns a high weight value to recent cells arrived in the receiver, and suitably adjusts window size in order to efficiently adapt to delay variation by the prameter to detect the delay variation of the networks. The proposed synchronization protocol estimates end-to-end delay by the weighted variable-size window estimator, and dynamically schedules th evirtual channel of the transmitter to playout multimedia data on time in the receiver. Also, we evaluate the performance of the delay estimator, which is the most importnat functional element in our proposed synchronization protocol, by the simulation and analyze the results of the simulation.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.4
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• pp.219-226
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• 2019

One of the most widely studied protocols for tactical ad-hoc networks is Optimized Link State Routing Protocol (OLSR). As for OLSR research, most research work focus on reducing control traffic overhead and choosing relay point. In addition, because OLSR is mostly dependent on link detection and propagation, dynamic Hello timer become research challenges. However, different timer interval causes imbalance of link validity time by affecting link lifetime. To solve this problem, we propose a weighted topology graph model for constructing a robust network topology based on the link validity time. In order to calculate the link validity time, we use control message timer, which is set for each node. The simulation results show that the proposed mechanism is able to achieve high end-to-end reliability and low end-to-end delay in small networks.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.914-927
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• 2017

Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model-local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.1-6
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• 2009

Localization of nodes is a key technology for application of wireless sensor network. Having a GPS receiver on every sensor node is costly. In the past, several approaches, including range-based and range-free, have been proposed to calculate positions for randomly deployed sensor nodes. Most of them use some special nodes, called anchor nodes, which are assumed to know their own locations. Other sensors compute their locations based on the information provided by these anchor nodes. This paper uses a single mobile anchor node to move in the sensing field and broadcast its current position periodically. We provide a weighted centroid localization algorithm that uses coefficients, which are decided by the influence of mobile anchor node to unknown nodes, to prompt localization accuracy. We also suggest a criterion which is used to select mobile anchor node which involve in computing the position of nodes for improving localization accuracy. Weighted centroid localization algorithm is simple, and no communication is needed while locating. The localization accuracy of weighted centroid localization algorithm is better than maximum likelihood estimation which is used very often. It can be applied to many applications.