• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.454-458
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• 2008

This article describes an interference reduction scheme for Mobile WiMAX in an indoor environment. The feasibility of user deployed femtocells in the same frequency channel as an existing macro cell network is investigated. One of the important requirements for co-channel operation of femtocells such as auto-configuration and self optimization are discussed. In femtocell deployments, leakage of the pilot signal to the outside of a house can result of the higher number of mobility events caused by passing user of macrocell. This interference effect can be minimized by reducing the pilot power using proper scheme. This paper introduces existing auto-configuration method of power control and proposed interference reduction scheme using power control for Mobile WiMAX in an indoor environment.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.570-573
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• 2008

In spite of many experimental studies of low-power applied-field magnetoplasmadynamic(AFMPD) thrusters, thrust efficiencies of the past thrusters are very low. Hence, drastic improvement in thrust performance is required for AF-MPD thrusters to compete against other types of electric propulsion in a moderate power regime around 10 kW. For the optimization of AF-MPD thrusters, a numerical code for the flowfield simulation is now under development. A preliminary result shows that the code can deal with a complicated mixture of the induced and applied magnetic fields, which will lead to a combination of the self-field, swirl, Hall, as well as electrothermal accelerations.

• Investigative Magnetic Resonance Imaging
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• v.23 no.1
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• pp.17-25
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• 2019

We discuss recent advances in Gd-based $T_1$-weighted MR contrast agents for the mapping of cellular pH. The pH plays a critical role in various biological processes. During the past two decades, several MR contrast agents of strategic importance for pH-mapping have been developed. Some of these agents shed light on the pH fluctuation in the tumor microenvironment. A pH-responsive self-assembled contrast agent facilitates the visualization of tumor size as small as $3mm^3$. Optimization of various parameters is crucial for the development of pH-responsive contrast agents. In due course, the new contrast agents may provide significant insight into pH fluctuations in the human body.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.230-238
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• 2021

A sensor network is made up of many sensors deployed in different areas to be monitored. They communicate with each other through a wireless medium. The routing of collected data in the wireless network consumes most of the energy of the network. In the literature, several routing approaches have been proposed to conserve the energy at the sensor level and overcome the challenges inherent in its limitations. In this paper, we propose a new low-energy routing protocol for power grids sensors based on an unsupervised clustering approach. Our protocol equitably harnesses the energy of the selected cluster-head nodes and conserves the energy dissipated when routing the captured data at the Base Station (BS). The simulation results show that our protocol reduces the energy dissipation and prolongs the network lifetime.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2564-2569
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• 2021

The neutronic analysis of Helium Cooled Ceramic Reflector (HCCR) breeding blankets has been performed using the 3D Monte Carlo code MCNPX and ENDF nuclear data library. This study aims to reduce ⁶Li percentage in the breeder zones as much as possible ensuring tritium self-sufficiency. This work is devoted to investigating the effect of ⁶Li percentage on the HCCR breeding blanket's neutronic parameters, such as neutron flux and spectrum, Tritium Breeding Ratio (TBR), nuclear power density, and energy multiplication factor. In the ceramic breeders at the saturated thickness, increasing the enrichment of ⁶Li reduces its share in the tritium production. Therefore, ceramic breeders typically use lower enriched Li from 30% to 60%. The investigation of neutronic analysis in the suggested geometry shows that using 60% ⁶Li in Li₂TiO₃ can yield acceptable TBR and energy deposition results, which would be economically feasible.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.09a
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• pp.27-50
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• 2009

This paper describes an adaptive management approach for predicting, monitoring, and controlling ground movements associated with excavations in urban areas. Successful use of monitoring data to update performance predictions of supported excavations depends equally on reasonable numerical simulations of performance, the type of monitoring data used as observations, and the optimization techniques used to minimize the difference between predictions and observed performance. This paper summarizes each of these factors and emphasizes their inter-dependence. Numerical considerations are described, including the initial stress and boundary conditions, the importance of reasonable representation of the construction process, and factors affecting the selection of the constitutive model. Monitoring data that can be used in conjunction with current numerical capabilities are discussed, including laser scanning and webcams for developing an accurate record of construction activities, and automated and remote instrumentations to measure movements. Self-updating numerical models that have been successfully used to compute anticipated ground movements, update predictions of field observations and to learn from field observations are summarized. Applications of these techniques from case studies are presented to illustrate the capabilities of this approach.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.88-92
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• 2023

Lithium-ion batteries are actively used in various industrial sites such as field robots, drones, and electric vehicles due to their high energy efficiency, light weight, long life span, and low self-discharge rate. When using a lithium-ion battery in a field, it is important to accurately estimate the SoC (State of Charge) of batteries to prevent damage. In recent years, SoC estimation using data-based artificial neural networks has been in the spotlight, but it has been difficult to deploy in the embedded board environment at the actual site because the computation is heavy and complex. To solve this problem, neural network lightening technologies such as network pruning have recently attracted attention. When pruning a neural network, the performance varies depending on which layer and how much pruning is performed. In this paper, we introduce an optimized pruning technique by improving the existing pruning method, and perform a comparative experiment to analyze the results.

• Annual Conference of KIPS
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• 2011.11a
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• pp.523-526
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• 2011

셀룰러 네트워크에서 핸드오버는 사용자에게 끊김 없는 통신을 제공하기 위한 중요한 이슈 중에 하나이다. 그러나 커버리지가 작은 펨토셀이 급격하게 설치되면, 끊김 없는 통신의 지원은 더욱 어려워질 것이다. 이를 해결 하기 위해서는 단말이 시기 적절하게 핸드오버 할 수 있도록 지원해야 한다. 만약 핸드오버가 너무 이르거나 혹은 너무 늦게 수행되면, 사용자는 일시적으로 통신 단절인 RLF (Radio Link Failure)을 경험하게 된다. 핸드오버의 시기는 핸드오버 파라미터에 의해 결정될 수 있다. 본 논문에서는 RLF 을 최소화하고, eNB 가 네트워크 운용자의 도움 없이 최적화된 핸드오버 파라미터를 자가 구성할 수 있는 방법을 제안한다. 본 논문에서 제안한 방법은 기존의 방법에 비해 효과적으로 RLF 을 줄일 수 있음을 확인 할 수 있다.

• ETRI Journal
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• v.45 no.5
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• pp.811-821
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• 2023

We propose an adaptive unmanned aerial vehicle (UAV)-assisted object recognition algorithm for urban surveillance scenarios. For UAV-assisted surveillance, UAVs are equipped with learning-based object recognition models and can collect surveillance image data. However, owing to the limitations of UAVs regarding power and computational resources, adaptive control must be performed accordingly. Therefore, we introduce a self-adaptive control strategy to maximize the time-averaged recognition performance subject to stability through a formulation based on Lyapunov optimization. Results from performance evaluations on real-world data demonstrate that the proposed algorithm achieves the desired performance improvements.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3515-3524
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• 2023

A reinforcement learning framework is proposed for the control problem of outlet steam pressure of the once-through steam generator(OTSG) in this paper. The double-layer controller using Proximal Policy Optimization(PPO) algorithm is applied in the control structure of the OTSG. The PPO algorithm can train the neural networks continuously according to the process of interaction with the environment and then the trained controller can realize better control for the OTSG. Meanwhile, reinforcement learning has the characteristic of difficult application in real-world objects, this paper proposes an innovative pretraining method to solve this problem. The difficulty in the application of reinforcement learning lies in training. The optimal strategy of each step is summed up through trial and error, and the training cost is very high. In this paper, the LSTM model is adopted as the training environment for pretraining, which saves training time and improves efficiency. The experimental results show that this method can realize the self-adjustment of control parameters under various working conditions, and the control effect has the advantages of small overshoot, fast stabilization speed, and strong adaptive ability.