• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.35-46
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• 2023

A model test is performed to measure the sloshing impact pressure in the liquid tank. A preprocessing is performed to learn the model test results applied with various environmental conditions. In this study, we propose a method for generating data similar to the total pressure data using Generative Adversarial Networks. In addition, after approximating the generated result to the three parameter Weibull distribution, the difference of the three parameters was compared through the RMSE and SMAPE calculation results. As a result, the distribution of the generated data showed similar results to the total pressure data distribution.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.169-169
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• 2023

Most distributed water is not used effectively due to water loss occurring in pipe networks. These water losses are caused by leakage, typically due to high water pressure to ensure adequate water supply. High water pressure can cause the pipe to burst or develop leaks over time, particularly in an aging network. In order to reduce the amount of leakage and ensure proper water distribution, it is important to apply pressure management. Pressure management aims to maintain a steady and uniform pressure level throughout the network, which can be achieved through various operational schemes. The schemes include: (1) installing a variable speed pump (VSP), (2) introducing district metered area (DMA), and (3) operating pressure-reducing valves (PRV). Applying these approaches requires consideration of various hydraulic, economic, and environmental aspects. Due to the different functions of these approaches and related components, an all-together optimization of these schemes is a complicated task. In order to reduce the optimization complexity, this study recommends a sequential optimization method. With three network operation schemes considered (i.e., VSP, DMA, and PRV), the method explores all the possible combinations of pressure management paths. Through sequential optimization, the best pressure management path can be determined using a multiple-criteria decision analysis (MCDA) to weigh in factors of cost savings, investment, pressure uniformity, and CO₂ emissions. Additionally, the contribution of each scheme to pressure management was also described in the application results.

• ETRI Journal
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• v.30 no.3
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• pp.483-485
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• 2008

A micro-sensor network is comprised of a large number of small sensors with limited memory capacity. Current key-establishment schemes for symmetric encryption require too much memory for micro-sensor networks on a large scale. In this paper, we propose a memory-efficient hypercube key establishment scheme that only requires logarithmic memory overhead.

• The KIPS Transactions:PartC
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• v.16C no.6
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• pp.707-716
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• 2009

Wireless Sensor Networks are consisted of sensor nodes that communicated with each other to transmit information. Because sensor nodes have physically many limits, wireless sensor networks are hard to adopt for traditional networks. Transmissions are consumed most energy of sensor nodes. That's why energy-efficient transmission techniques and QoS support techniques for different kind of data are most important in wireless sensor networks. The thesis proposes the agent based framework for energy distribution and QoS in wireless sensor networks. Agents have its own behavior policy by means of a gene, which is optimized by genetic operations. Agents behavior to distribute energy consumption over sensor nodes. Simulation results show that the enhanced framework extends the lifetime of sensor nodes. Successful transmission ratios of emergency data and non emergency data are increased by 27% and 14%, respectively. Also, the results demonstrate that Qos of networks are improved.

• Journal of Drive and Control
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• v.17 no.1
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• pp.13-20
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• 2020

Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

• Journal of Communications and Networks
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• v.12 no.2
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• pp.181-190
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• 2010

A multitude of overlay network designs for resilient routing, multicasting, quality of service, content distribution, storage, and object location have been proposed. Overlay networks offer several attractive features, including ease of deployment, flexibility, adaptivity, and an infrastructure for collaboration among hosts. In this paper, we explore cooperation among co-existing, possibly heterogeneous, overlay networks. We discuss a spectrum of cooperative forwarding and information sharing services, and investigate the associated scalability, heterogeneity, and security problems. Motivated by these services, we design Synergy, a utility-based overlay internetworking architecture that fosters overlay cooperation. Our architecture promotes fair peering relationships to achieve synergism. Results from Internet experiments with cooperative forwarding overlays indicate that our Synergy prototype improves delay, throughput, and loss performance, while maintaining the autonomy and heterogeneity of individual overlay networks.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.93-109
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• 1994

Even though sojourn time distributions are essential information in analyzing queueing networks, there are few methods to compute them accurately in non-product form queueing networks. In this study, we model the location process of a typical customer as a GMPH semi-Markov chain and develop computationally useful formula for the transition function and the first-passage time distribution in the GMPH semi-Markov chain. We use the formula to develop an effcient method for approximating sojourn time distributions in the non-product form queueing networks under quite general situation. We demonstrate its validity through numerical examples.

• Knowledge Management Research
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• v.12 no.2
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• pp.69-80
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• 2011

This paper reports on a structural view of a knowledge network comprised of clubs and organisationsexpressly concerned with cultural activities in a regional Australian city. Social network analysis showed an uneven distribution of power, influence, and prominence in the network. The network structure consisted of two modules of vertices clustered around particular categories of creative arts and these modules were linked most frequently by several organisations acting as communication hubs and boundary spanners. The implications of the findings include 'network weaving' for improving the network structure and developing a systemic approach for exploring the structures of social action that form community-based knowledge networks.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.1-6
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• 2019

Recently, big data and artificial intelligence (AI) based on communication systems have become one of the hottest issues in the technology sector, and methods of analyzing big data using AI approaches are now considered essential. This paper presents diverse paradigms to subjects which deal with diverse research areas, such as image segmentation, fingerprint matching, human tracking techniques, malware distribution networks, methods of intrusion detection, digital image watermarking, wireless sensor networks, probabilistic neural networks, query processing of encrypted data, the semantic web, decision-making, software engineering, and so on.

• Journal of applied mathematics & informatics
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• v.40 no.3_4
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• pp.515-530
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• 2022

A factor graph and belief propagation can be used for finding stochastic values of link weights in biological networks. However it is not easy to follow the process of use and so we presented the process with a toy network of three nodes in our prior work. We extend this work more generally and present numerical example for a network of 100 nodes.