• 제어로봇시스템학회논문지
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• 제14권12호
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• pp.1278-1285
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• 2008

An optimization-based real-time joint angle extraction method of human elbow is proposed by processing the biomedical signal of surface EMG (electromyogram) measured at the center point of biceps brachii. The EMG signal is known as non-stationary (time-varying) signal, but we assume that it is quasi-stationary because a physical or physiological system has limitations in the rate at which it can change its characteristics. Based on the assumption, a pre-processing method to obtain pre-angle values from raw EMG signal is firstly suggested, and then an optimization method to minimize the error between the pre-angle and real joint angle is proposed in this paper. Finally, we suggest the experimental results showing the effectiveness of the proposed algorithm.

• 대한교통학회지
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• 제18권1호
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• pp.87-97
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• 2000

Signal optimization model is divided bandwidth-maximizing model and delay-minimizing model. Bandwidth-maximizing model express model formulation as MILP(Mixed Integer Linear Programming) and delay-minimizing model like TRANSYT-7F use "hill climbing" a1gorithm to optimize signal times. This study Proposed optimization model using genetic algorithm one of evolution algorithm breaking from existing optimization model This Proposed model were tested by several scenarios and evaluated through NETSIM with TRANSYT-7F\`s outputs. The result showed capability that can obtain superior solution.

• Nuclear Engineering and Technology
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• 제54권6호
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• pp.2221-2229
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• 2022

In this research, for improving the measurement performance of Prompt Gamma-ray Neutron Activation Analysis (PGNAA) set-up, a new optimization method for set-up design was proposed and investigated. At first, the calculation method for Signal-to-Noise Ratio (SNR) was proposed. Since the SNR could be calculated and quantified accurately, the SNR was chosen as the evaluation parameter in the new optimization method. For discussing the feasibility of the SNR optimization method, two kinds of PGNAA set-ups were designed in the MCNP code, based on the SNR optimization method and the previous signal optimization method, respectively. Meanwhile, the single element spectra analysis method was proposed, and the analysis effect of single element spectra as well as element sensitivity were used for comparing the measurement performance. Since the simulation results showed the better measurement performance of set-up designed by SNR optimization method, the experimental set-ups were built for the further testing, finally demonstrating the feasibility of the SNR optimization method for PGNAA setup design.

• 한국인터넷방송통신학회논문지
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• 제22권3호
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• pp.15-24
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• 2022

현재 교차로에서의 보행자 교통흐름이나 비동력차 교통흐름의 신호제어에 대한 연구는 비교적 적다. 교통 흐름 신호 제어의 최적화 방안을 연구하여 보행자, 비동력차, 자동차 등의 전체적인 교통 흐름을 조화롭게 통제할 수 있게 하는 것은 교차로의 정체 상황을 개선하는 데 중요한 의의가 있다. 교차로의 교통 최적화를 위해 본 논문은 채널화 최적화와 위상 설계의 두 가지 측면에서 출발하며, 교차로에서의 충돌점의 수를 공간적, 시간적 할당으로부터 각각 감소시킨다. 고전적인 신호 타이밍 방법을 이론적 기반으로하고, 교통 여행객의 안전과 시간 적 이익 보장을 목표로 교차로의 채널화 최적화 및 신호 제어 방안을 제안한다. 자동차, 비자동차, 보행자를 객체로 하는 교차로의 채널화 및 위상 설계방법에 대해 논의하고, 교차로의 채널화 최적화 개선 방안을 제안한다. 교차로 신호제어의 다목적 최적화 모델을 구축하였으며, NSGA-II 알고리즘을 기반으로 모델을 해결하였다.

• 제어로봇시스템학회논문지
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• 제7권10호
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• pp.819-826
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• 2001

Genetic algorithms are becoming more popular because of their relative simplicity and robustness. Genetic algorithms are global search techniques for nonlinear optimization. However, traditional genetic algorithms, though robust, are generally not the most successful optimization algorithm on any particular domain because they are poor at hill-climbing, whereas simulated annealing has the ability of probabilistic hill-climbing. Therefore, hybridizing a genetic algorithm with other algorithms can produce better performance than using the genetic algorithm or other algorithms independently. In this paper, we propose an efficient hybrid optimization algorithm named the adaptive random signal-based learning. Random signal-based learning is similar to the reinforcement learning of neural networks. This paper describes the application of genetic algorithms and simulated annealing to a random signal-based learning in order to generate the parameters and reinforcement signal of the random signal-based learning, respectively. The validity of the proposed algorithm is confirmed by applying it to two different examples.

• 한국도로학회논문집
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• 제17권5호
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• pp.93-103
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• 2015

PURPOSES : The purpose of this study is to present a linear programing optimization model for the design of lane-based lane-uses and signal timings for an isolated intersection. METHODS: For the optimization model, a set of constraints for lane-uses and signal settings are identified to ensure feasibility and safety of traffic flow. Three types of objective functions are introduced for optimizing lane-uses and signal operation, including 1) flow ratio minimization of a dual-ring signal control system, 2) cycle length minimization, and 3) capacity maximization. RESULTS : The three types of model were evaluated in terms of minimizing delay time. From the experimental results, the flow ratio minimization model proved to be more effective in reducing delay time than cycle length minimization and capacity maximization models and provided reasonable cycle lengths located between those of other two models. CONCLUSIONS : It was concluded that the flow ratio minimization objective function is the proper one to implement for lane-uses and signal settings optimization to reduce delay time for signalized intersections.

• 한국통신학회논문지
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• 제28권11C호
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• pp.1152-1160
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• 2003

본 논문에서는 다양한 해상도의 신호 입력을 지원하는 고품위급 모니터의 디지털 신호처리 회로를 제안한다. 기존의 디지털 회로에서 ADC(Analog to Digital Convertor)와 VDP(Video Display Processor)로부터 발생하는 내부 디지털 PLL(Phase-locked Loop)의 낮은 성능과 IC의 내부 편차문제, 모듈간의 상이한 전압 차이 때문에, 다양한 입력 신호에서 안정된 동기신호 처리를 할 수 없는 문제가 있었다. 이를 해결하기 위해서 다양한 해상도의 신호 입력으로부터 동기 신호들의 규칙성을 이용하여 동기 신호를 관리하면서 시스템의 간섭을 최소화하는 동기신호 최적화 기법을 제안하였다. 제안한 방법을 적용한 결과 다양한 해상도에서 안정적으로 동기신호를 처리함으로써 여러 모드의 입력신호에 대응할 수 있었다.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.377-384
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• 2023

The existence of abnormal breakpoint data leads to poor channel balance in wireless sensor networks (WSN). To enhance the communication quality of WSNs, a method for positioning abnormal breakpoint data in WSNs on the basis of signal reconstruction is studied. The WSN signal is collected using compressed sensing theory; the common part of the associated data set is mined by exchanging common information among the cluster head nodes, and the independent parts are updated within each cluster head node. To solve the non-convergence problem in the distributed computing, the approximate term is introduced into the optimization objective function to make the sub-optimization problem strictly convex. And the decompressed sensing signal reconstruction problem is addressed by the alternating direction multiplier method to realize the distributed signal reconstruction of WSNs. Based on the reconstructed WSN signal, the abnormal breakpoint data is located according to the characteristic information of the cross-power spectrum. The proposed method can accurately acquire and reconstruct the signal, reduce the bit error rate during signal transmission, and enhance the communication quality of the experimental object.

• 한국산업융합학회 논문집
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• 제4권1호
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• pp.41-49
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• 2001

This study developed signal optimization algorithm by analyzing vehicle arrival patterns. The major principle of signal optimization is dissipate all queueing vehicle in 1cycle and assign delay time uniformly for all approaches. For this, this study used optimal green time and surplus green time. Optimal green time calculated by estimated traffic volume from vehicle arrival model. Surplus green time defined as the gap of optimal green time and queue dissipated time. And alternative cycle has minimum surplus green time was selected as the optimal cycle. Finally, total delay and average delay per vehicle can be calculated by using queueing theory.

• Journal of Microbiology and Biotechnology
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• 제29권2호
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• pp.304-310
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• 2019

Interleukin-21 is a common ${\gamma}$-chain cytokine that controls the immune responses of B cells, T cells, and natural killer cells. Targeting IL-21 to strengthen the immune system is promising for the development of vaccines as well as anti-infection and anti-tumor therapies. However, the practical application of IL-21 is limited by the high production cost. In this study, we improved IL-21 production by codon optimization and selection of appropriate signal peptide in CHO-K1 cells. Codon-optimized or non-optimized human IL-21 was stably transfected into CHO-K1 cells. IL-21 expression was 10-fold higher for codon-optimized than non-optimized IL-21. We fused five different signal peptides to codon-optimized mature IL-21 and evaluated their effect on IL-21 production. The best result (a 3-fold increase) was obtained using a signal peptide derived from human azurocidin. Furthermore, codon-optimized IL-21 containing the azurocidin signal peptide promoted $IFN-{\gamma}$ secretion and STAT3 phosphorylation in NK-92 cells similar to codon-optimized IL-21 containing original signal peptide. Collectively, these results indicate that codon optimization and azurocidin signal peptides provide an efficient approach for the high-level production of IL-21 as a biopharmaceutical.