• 콘크리트학회논문집
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• 제18권1호
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• pp.13-19
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• 2006

본 연구는 기존연구에서 개발된 저수축 고성능 콘크리트의 기초적 물성과 공시체 단면크기 변화 및 철근구속에 따른 수축특성에 대하여 검토한 것이다. 굳지 않은 콘크리트의 특성으로, 팽창재와 수축저감제를 사용한 최적배합의 경우 콘트롤에 비해 유동성이 저하하여 SP제 사용량이 증가하였고, 공기량은 증가하여 AE제 사용량이 감소하였다. 또한, 최적배합 콘크리트의 압축 및 인장강도는 콘트롤과 비교하여 다소 크게 나타났다. 공시체크기에 따른 수축특성으로, 건조수축 길이변화율은 공시체 단면치수가 클수록 적게 발생하였으며, 자기수축은 공시체 크기변화, 측정방법별에 따라 큰 영향이 없는 것으로 나타났다. 철근구속에 따른 수축특성으로, 철근구속 공시체에서의 철근변형은 철근비가 증가할수록 감소하였고, 자기수축응력은 증가하였으며, 배합별에 따라서는 최적배합의 경우 콘트롤과 비교하여 70% 정도로 크게 저감되게 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권2호
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• pp.579-603
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• 2018

In this paper we propose a QoS-enhanced intelligent stochastic optimal fair real-time packet scheduler, QUEST, for 4G LTE traffic in routers. The objective of this research is to maximize the system QoS subject to the constraint that the processor utilization is kept nearly at 100 percent. The QUEST has following unique advantages. First, it solves the challenging problem of starvation for low priority process - buffered streaming video and TCP based; second, it solves the major bottleneck of the scheduler Earliest Deadline First's failure at heavy loads. Finally, QUEST offers the benefit of arbitrarily pre-programming the process utilization ratio.Three classes of multimedia 4G LTE QCI traffic, conversational voice, live streaming video, buffered streaming video and TCP based applications have been considered. We analyse two most important QoS metrics, packet loss rate (PLR) and mean waiting time. All claims are supported by discrete event and Monte Carlo simulations. The simulation results show that the QUEST scheduler outperforms current state-of-the-art benchmark schedulers. The proposed scheduler offers 37 percent improvement in PLR and 23 percent improvement in mean waiting time over the best competing current scheduler Accuracy-aware EDF.

• 한국멀티미디어학회논문지
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• 제23권2호
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• pp.135-145
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• 2020

Recently, deep-learning based methods for low-light image enhancement accomplish great success through supervised learning. However, they still suffer from the lack of sufficient training data due to difficulty of obtaining a large amount of low-/normal-light image pairs in real environments. In this paper, we propose an unsupervised learning approach for single low-light image enhancement using the bright channel prior (BCP), which gives the constraint that the brightest pixel in a small patch is likely to be close to 1. With this prior, pseudo ground-truth is first generated to establish an unsupervised loss function. The proposed enhancement network is then trained using the proposed unsupervised loss function. To the best of our knowledge, this is the first attempt that performs a low-light image enhancement through unsupervised learning. In addition, we introduce a self-attention map for preserving image details and naturalness in the enhanced result. We validate the proposed method on various public datasets, demonstrating that our method achieves competitive performance over state-of-the-arts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권9호
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• pp.2154-2172
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• 2013

A centralized cognitive radio (CR) network is proposed and its system capacity is studied. The CR network is designed with power control and multi-user scheduling schemes to support best-effort traffics under peak interference power constraints. We provide an analytical framework to quantify its system capacity, taking into account various key factors such as interference constraints, density of primary users, cell radius, the number of CR users, and propagations effects. Furthermore, closed-form formulas are derived for its capacities when only path loss is considered in the channel model. Semi-analytical expressions for the capacities are also given when more realistic channel models that include path loss, shadowing, and small-scale fading are used. The accuracy of the proposed analytical framework is validated by Monte Carlo simulations. Illustrated with a practical example, the provided analytical framework is shown to be useful for the strategic planning of centralized CR networks.

• Journal of information and communication convergence engineering
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• 제16권2호
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• pp.130-134
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• 2018

Wireless capsule endoscopy (WCE) is considered as recent technology for the detection cancer cells in the human digestive system. WCE sends the captured information from inside the body to a sensor on the skin surface through a wireless medium. In WCE, the design of low-power consumption devices is a challenging topic. In the Shannon-Nyquist sampling theorem, the number of samples should be at least twice the highest transmission frequency to reconstruct precise signals. The number of samples is proportional to the power consumption in wireless communication. This paper proposes compressive sensing as a method to reduce power consumption in WCE, by means of a trade-off between samples and reconstruction accuracy. The proposed scheme is validated under channel constraints, expressed as the realistic human body path loss. The results show that the proposed scheme achieves a significant reduction in WCE power consumption and achieves a faster computation time with low signal error reconstruction.

• 인터넷정보학회논문지
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• 제4권5호
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• pp.61-68
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• 2003

본 논문에서는 PRMA의 구조를 사용하여 ABR 형태의 데이터 서비스를 수행할 수 있는 알고리즘을 도입하므로서 그 개념을 확장하고, 채널의 이용효율을 극대화하도록 설계된 무선 MAC 알고리즘인 APRMA를 제안한다. 기존의 PRMA에서는 랜덤 데이터를 전송하고자 하는 단말들은 슬롯을 예약한 수 없다. 즉, 슬롯의 예약은 시간 지연에 엄격한 음성에만 국한된다. 그러나 데이터들도 요구하는 서비스 품질을 만족시켜주어야 하며, 이를 위해 데이터에 대해서도 예약을 가능하게 하므로서 채널의 처리율도 높일 수 있다. 따라서, APRMA에서는 초기에는 최소한의 대역만을 할당해주며, 잉여의 대역이 존재하면 계속 그 전송율을 높여나갈 수 있게 하므로서 채널의 이용율을 높이고, 음성과 같은 상대적으로 우선순위가 높은 서비스 요청에 대해서도 동시에 그 서비스 품질을 만족시킬 수 있다.

• 한국초전도ㆍ저온공학회논문지
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• 제15권2호
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• pp.34-38
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• 2013

AC Losses for face to face stacks of four identical coated conductors (CCs) were numerically calculated using the H-formulation combined with the E-J power law and the Kim model. The motive sample was the face to face stack of four 2 mm-wide CC tapes with 2 ${\mu}m$ thick superconducting layer of which the critical current density, $J_c$, was $2.16{\times}10^6A/cm^2$ on IBAD-MgO template, which was suggested for the mitigation of ac loss as a round shaped wire by Korea Electrotechnology Research Institute. For the calculation the cross section of the stack was simply modeled as vertically aligned 4 rectangles of superconducting (SC) layers with $E=E_o(J(x,y,t)/J_c(B))^n$ in x-y plane where $E_o$ was $10^{-6}$ V/cm, $J_c$(B) was the field dependence of current density and n was 21. The field dependence of the critical current of the sample measured in four-probe method was employed for $J_c$(B) in the equation. The model was implemented in the finite element method program by commercial software. The ac loss properties for the stacks were compared with those of single 4 cm-wide SC layers with the same critical current density or the same critical current. The constraint for the simulation was imposed in two different ways that the total current of the stack obtained by integrating J(x,y,t) over the cross sections was the same as that of the applied transport current: one is that one fourth of the external current was enforced to flow through each SC. In this case, the ac loss values for the stacks were lower than those of single wide SC layer. This mitigation of the loss is attributed to the reduction of the normal component of the magnetic field near the SC layers due to the strong expulsion of the magnetic field by the enforced transport current. On the contrary, for the other case of no such enforcement, the ac loss values were greater than those of single 4cm-wide SC layer and. In this case, the phase difference of the current flowing through the inner and the outer SC layers of the stack was observed as the transport current was increased, which was a cause of the abrupt increase of ac loss for higher transport current.

• 대한전기학회논문지
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• 제40권6호
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• pp.551-561
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• 1991

The probabilistic generation simulation plays a key role in power system expansion and operational planning especially for the calculation of expected energy, loss of load probaility and unserved energy expected. However, it is crucial to develop a probabilistic generation simulation algorithm which gives sufficiently precise results within a reasonable computation time. In a previous paper, we have proposed an efficent method using Fast Hartley Transform in convolution process for considering the thermal and nuclear units. In this paper, a method considering the scheduling of pumped-storage plants and hydro plants with energy constraint is proposed. The method also adopts FHT techniques. We improve the model to include multi-state and multi-block generation. The method has been applied for a real size model system.

• ETRI Journal
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• 제30권2호
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• pp.216-226
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• 2008

This paper proposes a novel transport network architecture for the next generation network (NGN) based on the optical burst switching technology. The proposed architecture aims to provide efficient delivery of various types of network traffic by satisfying their quality-of-service constraints. To this end, we have developed a soft-state bandwidth reservation mechanism, which enables NGN transport nodes to dynamically reserve bandwidth needed for active data burst flows. The performance of the proposed mechanism is evaluated by means of numerical analysis and NS2 simulation. Our results show that the packet delay is kept within the constraint for each traffic flow and the burst loss rate is remarkably improved.

• 소음진동
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• 제8권6호
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• pp.1113-1120
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• 1998

For an analysis of some Helmholtz resonators, it is likely to be more appropriate to consider acoustic field within cavity than just the 1-DOF analogous model. However, a design method that considers increased parameters than the lumped model. is not a trivial process due to the trade-off effect among the parameters. In this paper. the genetic algorithm. one of the optimization technique that rapidly converges to global fittest solution and robust convergence. is applied to the design process of Helmholtz resonators. Results show that the genetic algorithm can be successfully and efficiently used to find the resonant frequencies for both lumped model and distributed model.