• ETRI Journal
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• 제37권3호
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• pp.471-479
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• 2015

Traditional designs of cognitive radio (CR) focus on maximizing system throughput. In this paper, we study the joint overlay and underlay power allocation problem for orthogonal frequency-division multiple access-based CR. Instead of maximizing system throughput, we aim to maximize system energy efficiency (EE), measured by a "bit per Joule" metric, while maintaining the minimal rate requirement of a given CR system, under the total power constraint of a secondary user and interference constraints of primary users. The formulated energy-efficient power allocation (EEPA) problem is nonconvex; to make it solvable, we first transform the original problem into a convex optimization problem via fractional programming, and then the Lagrange dual decomposition method is used to solve the equivalent convex optimization problem. Finally, an optimal EEPA allocation scheme is proposed. Numerical results show that the proposed method can achieve better EE performance.

• 동력기계공학회지
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• 제16권2호
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• pp.54-59
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• 2012

In the present study, process optimization for thermal-sprayed Ni-based alloy coating has been performed using Taguchi method and analysis of variance(ANOVA). Ni-based alloy coatings were fabricated by flame spray process on steel substrate, and the hardness test and wear test were performed. Experiments were designed as per Taguchi's L9 orthogonal array and tests were conducted with different Oxygen gas flow, Acetylene gas flow, Powder feed rate and Spray distance. Multi response signal to noise ratio (MRSN) was calculated for the response variables and the optimum combination level of factors was obtained simultaneously using Taguchi's parametric design.

• 동력기계공학회지
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• 제17권6호
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• pp.108-114
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• 2013

This paper describes process optimization for thermal-sprayed Co-based self-flux alloy coating by Taguchi method. Co-based self-flux alloy coatings were fabricated according to $L_9(3^4)$ orthogonal array using flame spray process. Hardness test and wear test were performed, the results were analyzed by analysis of variance(ANOVA) considering a multi response signal to noise ratio(MRSN). From the results of ANOVA, the optimal combination of the flame spray parameters on Co-based self-flux alloy coating could be predicted. The calculated hardness and wear rate of the coatings by ANOVA were found to be close to that of confirmation experimental result.

• 대한조선학회논문집
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• 제43권6호
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• pp.693-699
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• 2006

This paper proposes a design optimization technique for ship RCS signature reductions using Taguchi method. The proposed technique comprises of i)evaluating initial RCS signatures, ii)defining critical areas which should be modified as design parameters, and threat factors which can't be controlled artificially as noise parameters, and finally iv)finding optimum parameters via analyzing signal to noise ratios for designated characteristics. We applied the technique to a model ship and found that it is suitable for radar stealth designs. In addition, the proposed technique is applicable to submarine designs against sonar threats.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4268-4289
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• 2020

Advanced traffic signal timing method plays very important role in reducing road congestion and air pollution. Reinforcement learning is considered as superior approach to build traffic light timing scheme by many recent studies. It fulfills real adaptive control by the means of taking real-time traffic information as state, and adjusting traffic light scheme as action. However, existing works behave inefficient in complex intersections and they are lack of feasibility because most of them adopt traffic light scheme whose phase sequence is flexible. To address these issues, a novel adaptive traffic signal timing scheme is proposed. It's based on actor-critic reinforcement learning algorithm, and advanced techniques proximal policy optimization and generalized advantage estimation are integrated. In particular, a new kind of reward function and a simplified form of state representation are carefully defined, and they facilitate to improve the learning efficiency and reduce the computational complexity, respectively. Meanwhile, a fixed phase sequence signal scheme is derived, and constraint on the variations of successive phase durations is introduced, which enhances its feasibility and robustness in field applications. The proposed scheme is verified through field-data-based experiments in both medium and high traffic density scenarios. Simulation results exhibit remarkable improvement in traffic performance as well as the learning efficiency comparing with the existing reinforcement learning-based methods such as 3DQN and DDQN.

• 한국멀티미디어학회논문지
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• 제8권11호
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• pp.1432-1438
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• 2005

심리음향모델을 기반으로 주파수영역에서 잡음을 형상화하여 오디오 신호에 부가하였을 때 부가된 잡음이 지각되지 않는 방법을 제안하였다. 신호의 마스킹 문턱값으로부터 지각되지 않는 잡음의 준위를 구하는 것은 심리음향모델에서 확산함수와 관련된 디컨버루션을 수반하는데 난제(ill-conditioned Problem)로 알려져 있다. 본 논문에서는 최적화 기법을 적용하여 잡음의 여기준위를 신호의 마스킹 준위에 일치시킴으로써 신호에 부가된 잡음이 청각적으로 지각되지 않는 한도 내에서 최대한의 잡음준위가 되도록 형상화하는 방법을 제시하고 실험적으로 그 타당성을 증명하였다.

• 한국군사과학기술학회지
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• 제26권2호
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• pp.122-128
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• 2023

The target must be located within the main-lobe of the antenna in order to measure the direction of the target by using sum-delta monopulse technique. The most common way if the target is located within the main-lobe is to compare the amplitude of the sum channel received signal with the delta channel received signal. However, in the case of the single-ring circular array antenna, it is difficult to apply the conventional method due to its structural limitation where antenna elements do not exist in the center of the array. In this paper, we proposed a novel method to identify whether a target is located within the main-lobe by appropriately adjusting the feeding amplitude of each element constituting the single-ring circular array antenna through the particle swarm optimization method. Simulation results showed that the proposed method can determine whether the target is located within the main-lobe of the single-ring circular array antenna.

• 융합신호처리학회논문지
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• 제9권2호
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• pp.129-134
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• 2008

본 논문에서는 적자생존 원리에 기반한 유전자 알고리즘을 이용하여 일차원 비선형 광자 결정 구조에 대해 분석하고, 광 트랜지스터로의 적용 가능성을 컴퓨터 시뮬레이션에 의해 증명한다. 이와 같은 형태의 최적 설계는 해석식이 필요한 steepest decent 최적 알고리즘과 달리 유전자 알고리즘은 탁월한 성능을 낼 수 있으며, 광 트랜지스터 뿐만 아니라 다른 광자 결정 광소자의 설계에 유용하게 적용될 수 있다. 또한, global minimum 최적해 부근에서 여러 가지의 해가 얻어지기 때문에 광 트랜지스터가 어떤 모양을 가져야 되는지 분석하는데 많은 도움을 주는 장점을 갖는다. 완전 광 필터 트랜지스터를 설계하기 위해 신경회로망 모델을 이용하여 초기 설계를 수행한 후, 유전자 알고리즘에 의해 최종적인 최적화 설계가 수행된다. 시뮬레이션으로부터 얻어진 일차원 광자 결정 트랜지스터의 스위칭 On/Off 비는 약 27dB 였다.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.258-265
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• 2021

High levels for noise and a loss of true signal make the quantitative interpretation of nuclear medicine (NM) images difficult. An application of profile optimization using a sigmoidal function in this study was used to acquire the NM images with high quality. And the images were acquired by using three kinds of reconstruction method using each same sinogram: a standard filtered back-projection (FBP), an iterative reconstruction (IR) technique, and the sigmoidal function profile optimization (SFPO). Comparison of image according to reconstruction method was performed to show a superiority of the SFPO for imaging. The images reconstructed by using the SFPO showed an average of 1.49 times and of 1.17 times better in contrast than the results obtained using the standard FBP and the IR technique, respectively. Higher signal to noise ratios were obtained as an average of 12.30 times and of 3.77 times than results obtained using the standard FBP and the IR technique, respectively. This study confirms that reconstruction with SFPO (vs FBP and vs IR) can lead to better lesion detectability and characterization with noise reduction. It can be developed for future reconstruction technique for the NM imaging.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 추계학술대회
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• pp.110-113
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• 2022

신호를 제어하는 방식은기존의 전통적인 수학적 방식을 이용한 최적화를 넘어 이제 인공지능이 본격적으로 활용되기 시작하는 단계까지 발전하였다. 이에 따라 인공지능을 적용하는 방안에 대해 다양한 연구들이 진행되고 있는데, 현행 연구에서는 주로 좋은 교통 상황에 대한 마땅한 고려 없이 간단히 지체도만을 고려하여 보상함수를 설정하는 방식을 주로 채택하고 있다. 그러나 이 경우 현실성이 떨어지는 신호 제어 방식을 인공지능이 학습할 가능성이 존재한다는 문제점을 지닐 뿐더러, 보상 함수에서 좋다고 평가하는 것이 실질적인 서비스 수준의 정의에 부합하지 않음을 확인할 수 있다. 따라서 본 연구에서는 기존의 보상함수 설정 사례를 분석하고, 개선 방향을 제시하고자 한다.