• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.106-108
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• 2014

본 논문에서는 노드의 로드밸런싱 속성을 이용하여 분산경로를 설정하는 L.T(Load Tolerance)알고리즘을 제안한다. 모바일 애드 혹 네트워크(Mobile Ad hoc Network)는 유동성을 가진 노드들로 구성된 네트워크로 토폴로지의 변화가 빈번하여, 기존 알고리즘에서는 라우팅 경로를 유지하기 위한 계층적 네트워크연구가 진행되어 왔다. 하지만 계층적 네트워크에서 특정 클러스터 헤드노드에게 로드밸런싱이 집중될 경우, 클러스터 헤드노드의 제한된 로드밸런싱을 초과되어 통신이 단절된다. 본 논문에서 제안한 알고리즘은 유효한 통신 반경 안에 존재하는 클러스터 헤드노드들의 로드밸런싱을 측정한다. 클러스터 헤드노드의 로드밸런싱이 높을 경우, 소속된 클러스터 멤버노드는 클러스터 헤드노들의 로드밸런싱과 동적속성을 분석하여 L.T 속성을 계산하며, 계산된 L.T 속성을 이용하여, 노드의 분산경로를 설정한다. 모의실험을 통해 클러스터 헤드노드의 로드 밸런싱이 높을 경우, 로드밸런싱이 낮은 분산 경로를 제공함에 따라 향상된 패킷 전송률을 보일 것으로 기대된다.

• Coupled systems mechanics
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• v.11 no.4
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• pp.297-313
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• 2022

The objective of this paper is to study the effect of frequency in a two-dimensional orthotropic thermoelastic rotating solid with fractional order heat transfer in generalized thermoelasticity with two-temperature due to inclined load. As an application the bounding surface is subjected to uniformly and linearly distributed loads (mechanical and thermal source). The problem is solved with the help of Fourier transform. Assuming the disturbances to be harmonically time dependent, the expressions for displacement components, stress components, conductive temperature and temperature change are derived in frequency domain. Numerical inversion technique has been used to determine the results in physical domain. The results are depicted graphically to show the effect of frequency on various components. Some particular cases are also discussed in the present research.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.274-279
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• 1998

The structural behaviors of a arch composed of flexible membrane are investigated. The membrane is considered as thin shell with internal pressure during FEM analysis by using ABAQUS. In the paper, a wind load and uniformly distributed vertical load are considered. As a vertical load, snow loads including applied over all and half of the structure are introduced. The ends of arch are fixed to the ground. Load-Deflections relationship, buckling mode of the structure are presented.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.161-168
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• 2024

As the size of big data models grows, distributed training is emerging as an essential element for large-scale machine learning tasks. In this paper, we propose ParamHub for distributed data training. During the training process, this agent utilizes the provided data to adjust various conditions of the model's parameters, such as the model structure, learning algorithm, hyperparameters, and bias, aiming to minimize the error between the model's predictions and the actual values. Furthermore, it operates autonomously, collecting and updating data in a distributed environment, thereby reducing the burden of load balancing that occurs in a centralized system. And Through communication between agents, resource management and learning processes can be coordinated, enabling efficient management of distributed data and resources. This approach enhances the scalability and stability of distributed machine learning systems while providing flexibility to be applied in various learning environments.

• Journal of Urban Science
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• v.11 no.2
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• pp.45-54
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• 2022

Recently, regulations on automobile exhaust gas emission are being strengthened. Accordingly, automobile exhaust gas emissions are expected to decrease and continue to decrease. On the other hand, many countries do not yet consider the emission of non-exhaust air pollutants from automobiles as important. Automobile non-exhaust substances are classified into three categories: tire dust emissions, brake wear emissions, and road scattering dust. In particular, in the case of tire dust, research results exist that pollutant emissions increase as the weight of a vehicle increases. Since the weight of trucks varies according to the load and the load along the axles is also different, it can be expected that the emission of PM10 from the tire dust will be different depending on the loading method. Therefore, this study was conducted on the amount of PM10 generated in tire dust considering the axle load of the truck according to the loading method. However, it was confirmed that the total amount of PM10 was less than that all loads are loaded in the front or rear when the load was evenly distributed in the front and rear of the cargo compartment. In particular, if the load is distributed evenly in the front and back of the cargo compartment and the load in the front part is divided into 2 to 6 and loaded, as the number of divided loading increases the amount of PM10 generated decreases. And when the load is divided into 6 pieces, the total amount of PM10 generated is 0.3952g, the minimum value. If the load is divided into 6 or more and loaded evenly, the total PM10 generated continuously increases and converges to about 0.3964g.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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• pp.224-229
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• 2014

This paper presents the novel voltage control method in power distribution system with distributed generators. The voltage in distribution systems is regulated by Under Load Tap Changer(ULTC) of substation and pole transformer of primary feeders. Recently, Step Voltage Regulator(SVR) is getting located at distribution feeders to regulate effectively voltage of primary feeders. But the effectiveness of SVR decreases due to independent operation between SVR and ULTC, and also the existing Line Drop Compensator(LDC) method considering the distributed generators may be not able to regulate the proper voltage in a permissible range. Thus, this paper presents a optimal voltage control algorithm of SVR by using the secondary voltage data of main transformer in substation.

• Transactions on Electrical and Electronic Materials
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• v.18 no.6
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• pp.350-358
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• 2017

Recently, owing to increased interest in low-carbon energy supplies, renewable energy sources such as photovoltaics and wind turbines in distribution networks have received considerable attention for generating clean and unlimited energy. The presence of energy storage systems (ESSs) in the promising field of active distribution networks (ADNs) would have direct impact on power system problems such as encountered in probabilistic distributed generation (DG) model studies. Hence, the optimal procedure is offered herein, in which the simultaneous placement of an ESS, photovoltaic-based DG, and wind turbine-based DG in an ADN is taken into account. The main goal of this paper is to maximize the net present value of the loss reduction benefit by considering the price of electricity for each load state. The proposed framework consists of a scenario tree method for covering the existing uncertainties in the distribution network's load demand as well as DG. The collected results verify the considerable effect of concurrent installation of probabilistic DG models and an ESS in defining the optimum site of DG and the ESS and they demonstrate that the optimum operation of an ESS in the ADN is consequently related to the highest value of the loss reduction benefit in long-term planning as well. The results obtained are encouraging.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.3
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• pp.954-972
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• 2012

Content Delivery Networks (CDN) server loads that fluctuant necessitate CDN to improve its service scalability especially when the peak load exceeds its service capacity. The peer assisted scheme is widely used in improving CDN scalability. However, CDN operators do not want to lose profit by overusing it, which may lead to the CDN resource utilization reduced. Therefore, improving CDN scalability moderately and guarantying CDN resource utilization maximized is necessary. However, when and how to use the peer-assisted scheme to achieve such improvement remains a great challenge. In this paper, we propose a new method called Dynamic Moderate Peer-assisted Method (DMPM), which uses time series analysis to predict and decide when and how many server loads needs to offload. A novel peer-assisted mechanism based on the prediction designed, which can maximize the profit of the CDN operators without influencing scalability. Extensive evaluations based on an actual CDN load traces have shown the effectiveness of DMPM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.1976-1997
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• 2016

This paper investigates the problem of co-tier interference mitigation for dynamic small- cell networks, in which the load of each small-cell varies with the number of active associated small-cell users (SUs). Due to the fact that most small-cell base stations (SBSs) are deployed in an ad-hoc manner, the problem of reducing co-tier interference caused by dynamic loads in a distributed fashion is quite challenging. First, we propose a new distributed channel allocation method for small-cells with dynamic loads and define a dynamic interference graph. Based on this approach, we formulate the problem as a dynamic interference graph game and prove that the game is a potential game and has at least one pure strategy Nash equilibrium (NE) point. Moreover, we show that the best pure strategy NE point minimizes the expectation of the aggregate dynamic co-tier interference in the small-cell network. A distributed dynamic learning algorithm is then designed to achieve NE of the game, in which each SBS is unaware of the probability distributions of its own and other SBSs' dynamic loads. Simulation results show that the proposed approach can mitigate dynamic co-tier interference effectively and significantly outperform random channel selection.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.225-234
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• 2015

Nowadays a Virtual Power Plant (VPP) represents an aggregation of distributed energy resource such as Distributed Generation (DG), Combined Heat and Power generation (CHP), Energy Storage Systems (ESS) and load in order to operate as a single power plant by using Information and Communication Technologies, ICT. The VPP has been developed and verified based on a single virtual plant platform which is connected with a number of various distributed energy resources. As the VPP's distributed energy resources increase, so does the number of data from distributed energy. Moreover, it is obviously inefficient in the aspects of technique and cost that a virtual plant platform operates in a centralized manner over widespread region. In this paper the concept of the large-scale VPP which can reduce a error probability of system's load and increase the robustness of data exchange among distributed energy resources will be proposed. In addition, it can directly control and supervise energy resource by making small size's virtual platform which can make a optimal resource scheduling to consider of variable and sensitive load in the large-scale VPP. It makes certain the result is verified by simulation.