• 한국전자통신학회논문지
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• 제15권6호
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• pp.987-994
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• 2020

본 논문은 음향잡음감쇠기에서 CNN(: Convolutional Neural Network) 계층의 커널 사이즈가 성능에 미치는 영향을 위한 연구하였다 이 시스템은 기존의 적응필터를 이용하는 대신 신경망 적응예측필터를 이용한 심층학습 알고리즘으로 잡음감쇠 성능을 개선한다. 100-neuron, 16-filter CNN 필터와 오차 역전파(back propagation) 알고리즘을 이용하여 잡음이 포함된 단일입력 음성신호로부터 음성을 추정한다. 이는 음성신호가 갖는 유성음 구간에서의 준주기적 성질을 이용하는 것이다. 본 연구에서 커널 사이즈에 대한 잡음감쇠기의 성능을 검증하기 위하여 Tensorflow와 Keras 라이브러리를 사용한 시뮬레이션 프로그램을 작성하고 모의실험을 수행하였다. 모의실험 결과, 커널 사이즈가 16 정도일 때 평균자승오차(MSE: Mean Square Error) 및 평균절대값오차(MAE: Mean Absolute Error) 값이 가장 작은 것으로 나타났으며 사이즈가 이보다 더 작거나 커지면 MSE 및 MAE 값이 증가하는 것을 볼 수 있다. 이는 음성신호의 경우 커널 사이즈가 16 정도일 때 특성을 가장 잘 포집할 수 있음을 알 수 있다.

• 디지털융복합연구
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• 제19권6호
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• pp.233-238
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• 2021

블록체인 기술은 모든 거래를 축적하고 저장하며 모든 트랜잭션의 내용을 확인하기 위해 데이터 자체는 압축되지만 확장성이 제한된다. 또한 거래 유형별로 별도의 검증 알고리즘을 사용하기 때문에 거래 규모가 커질수록 검증 부담이 커진다. 기존 블록체인은 사양이 낮은 서버를 사용하여 블록 싱크가 되지 않기 때문에 네트워크에 참여할 수 없다. 이러한 문제로 인해 시간이 지날수록 블록체인 네트워크의 데이터 크기가 커지고 자원이 풍부한 사용자를 제외하고는 네트워크 참여가 불가능하다. 따라서 본 논문에서는 일반 동작 검증을 위한 영지식 증명 알고리즘을 연구함으로써 트랜잭션을 향상시켰다. 이 시스템에서는 일반 동작 검증이 가능한 영지식 회로 생성기 설계와 검증자 및 검증자의 최적화도 수행하였다. 그리고 키 생성을 최적화하기 위한 알고리즘을 개발하였다.

• 산업경영시스템학회지
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• 제44권2호
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• pp.58-65
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• 2021

Meta-heuristic algorithms have been developed to efficiently solve difficult problems and obtain a global optimal solution. A common feature mimics phenomenon occurring in nature and reliably improves the solution through repetition. And at the same time, the probability is used to deviate from the regional optimal solution and approach the global optimal solution. This study compares the algorithm created based on the above common points with existed SA and HS to show advantages in time and accuracy of results. Existing algorithms have problems of low accuracy, high memory, long runtime, and ignorance. In a two-variable polynomial, the existing algorithms show that the memory increases and the accuracy decrease. In order to improve the accuracy, the new algorithm increases the number of initial inputs and increases the efficiency of the search by introducing a direction using vectors. And, in order to solve the optimization problem, the results of the last experiment were learned to show the learning effect in the next experiment. The new algorithm found a solution in a short time under the experimental conditions of long iteration counts using a two-variable polynomial and showed high accuracy. And, it shows that the learning effect is effective in repeated experiments.

• 산업경영시스템학회지
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• 제44권2호
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• pp.24-35
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• 2021

Due to increasing awareness on the treatment of end-of-use/life products, disassembly has been a fast-growing research area of interest for many researchers over recent decades. This paper introduces a novel lot-sizing problem that has not been studied in the literature, which is the service-parts lot-sizing with disassembly option. The disassembly option implies that the demands of service parts can be fulfilled by newly manufactured parts, but also by disassembled parts. The disassembled parts are the ones recovered after the disassembly of end-of-use/life products. The objective of the considered problem is to maximize the total profit, i.e., the revenue of selling the service parts minus the total cost of the fixed setup, production, disassembly, inventory holding, and disposal over a planning horizon. This paper proves that the single-period version of the considered problem is NP-hard and suggests a heuristic by combining a simulated annealing algorithm and a linear-programming relaxation. Computational experiment results show that the heuristic generates near-optimal solutions within reasonable computation time, which implies that the heuristic is a viable optimization tool for the service parts inventory management. In addition, sensitivity analyses indicate that deciding an appropriate price of disassembled parts and an appropriate collection amount of EOLs are very important for sustainable service parts systems.

• 전자통신동향분석
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• 제36권1호
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• pp.54-63
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• 2021

Since the recent COVID-19 pandemic, countries have been strengthening trade protection for their security, and the importance of securing strategic materials, such as food, is drawing attention. In addition to the cultural aspects, the global preference for food produced in Korea is increasing because of the Korean Wave. Thus, the Korean food industry can be developed into a high-value-added export food industry. Currently, Korea has a low self-sufficiency rate for foodstuffs apart from rice. Korea also suffers from problems arising from population decline, aging, rapid climate change, and various animal and plant diseases. It is necessary to develop technologies that can overcome the production structures highly dependent on the outside world of food and foster them into export-type system industries. The global agricultural industry-related technologies are actively being modified via data accumulation, e.g., environmental data, production information, and distribution and consumption information in climate and production facilities, and by actively expanding the introduction of the latest information and communication technologies such as big data and artificial intelligence. However, long-term research and investment should precede the field of living organisms. Compared to other industries, it is necessary to overcome poor production and labor environment investment efficiency in the food industry with respect to the production cost, equipment postmanagement, development tailored to the eye level of field workers, and service models suitable for production facilities of various sizes. This paper discusses the flow of domestic and international technologies that form the core issues of the site centered on the 4th Industrial Revolution in the field of agriculture, livestock, and fisheries. It also explains the environmental awareness production technologies centered on sustainable intelligence platforms that link climate change responses, optimization of energy costs, and mass production for unmanned production, distribution, and consumption using the unstructured data obtained based on detection and growth measurement data.

• 한국정보통신학회논문지
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• 제25권4호
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• pp.565-571
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• 2021

본 논문은 레이더 시스템에 사용되는 상용칩의 주파수 선택적 IQ 불일치를 보상하는 기법을 제안하고, 성능 열화로 인하여 고성능 레이더 시스템에 적용이 어려웠던 상용칩의 사용이, 제안된 기법을 통하여 가능함을 성능 분석을 통하여 보였다. IQ 불일치 보상 성능의 극대화를 위하여 본 논문에서는 특잇값 분해를 통한 차원 축소 기법을 제안하고, 제안된 차원 축소 기법에 기반한 IQ 불일치 복소 보상 여파기의 설계를 위한 최적화 모델을 제안하였다. 제안된 보상 기법의 우수성을 입증하기 위하여 실제 상용칩에 기반한 IQ 불일치 측정 및 보상 시스템을 FPGA로 구현하였으며, 개발된 시스템을 통하여 논문에서 제안하는 방법의 성능을 검증하였다. 성능 검증 결과, 기존 방법과 비교하여 본 논문에서 제안하는 방법이 큰 복잡도 증가 없이 기존 방법의 성능을 뛰어넘는 우수한 성능을 보임을 확인하였다.

• 한국해양공학회지
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• 제35권4호
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• pp.273-286
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• 2021

In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

• 방사성폐기물학회지
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• 제19권4호
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• pp.459-467
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• 2021

In the majority of countries, the upper limit of buffer temperature in a repository is set to below 100℃ due to the possible illitization. This smectite-to-illite transformation is expected to be detrimental to the swelling functions of the buffer. However, if the upper limit is increased while preventing illitization, the disposal density and cost-effectiveness for the repository will dramatically increase. Thus, understanding the characteristics and creating a database related to the buffer under the elevated temperature conditions is crucial. In this study, a strategy to investigate the bentonite found in Korea under the elevated temperatures from a mineral transformation and radionuclides retardation perspective was proposed. Certain long-term hydrothermal reactions generated the bentonite samples that were utilized for the investigation of their mineral transformation and radionuclide retardation characteristics. The bentonite samples are expected to be studied using in-situ synchrotron-based X-Ray Diffraction (XRD) technique to determine the smectite-to-illite transformation. Simultaneously, the 'high-temperature and high-pressure mineral alteration measurement system' based on the Diamond Anvil Cell (DAC) will control and provide the elevated temperature and pressure conditions during the measurements. The kinetic models, including the Huang and Cuadros model, are expected to predict the time and manner in which the illitization will become detrimental to the performance and safety of the repository. The sorption reactions planned for the bentonite samples to evaluate the effects on retardation will provide the information required to expand the current knowledge of repository optimization.

• 산업경영시스템학회지
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• 제44권4호
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• pp.113-127
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• 2021

Topic modeling has been receiving much attention in academic disciplines in recent years. Topic modeling is one of the applications in machine learning and natural language processing. It is a statistical modeling procedure to discover topics in the collection of documents. Recently, there have been many attempts to find out topics in diverse fields of academic research. Although the first Department of Industrial Engineering (I.E.) was established in Hanyang university in 1958, Korean Institute of Industrial Engineers (KIIE) which is truly the most academic society was first founded to contribute to research for I.E. and promote industrial techniques in 1974. Korean Society of Industrial and Systems Engineering (KSIE) was established four years later. However, the research topics for KSIE journal have not been deeply examined up until now. Using topic modeling algorithms, we cautiously aim to detect the research topics of KSIE journal for the first half of the society history, from 1978 to 1999. We made use of titles and abstracts in research papers to find out topics in KSIE journal by conducting four algorithms, LSA, HDP, LDA, and LDA Mallet. Topic analysis results obtained by the algorithms were compared. We tried to show the whole procedure of topic analysis in detail for further practical use in future. We employed visualization techniques by using analysis result obtained from LDA. As a result of thorough analysis of topic modeling, eight major research topics were discovered including Production/Logistics/Inventory, Reliability, Quality, Probability/Statistics, Management Engineering/Industry, Engineering Economy, Human Factor/Safety/Computer/Information Technology, and Heuristics/Optimization.

• Journal of Ginseng Research
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• 제46권3호
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• pp.367-375
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• 2022

Background: Short-term hydroponic-cultured ginseng (sHCG), which is 1-year-old ginseng seedlings cultivated for 4 weeks in a hydroponic system, is a functional food item with several biological effects. However, the optimal extraction conditions for sHCG, and the bioactivity of its extracts, have not been evaluated. Methods: Chlorogenic acid (CGA) and ginsenoside contents were evaluated in sHCG, white ginseng (WG), and red ginseng (RG) using high-performance liquid chromatography. Response surface methodology (RSM) was used to optimize the extraction conditions (temperature and ethanol concentration) to maximize the yield of dry matter, CGA, and four ginsenosides (Re, Rg₁, Rb₁, and Rd) from sHCG. The optimal extraction conditions were applied to pilot-scale production of sHCG extracts. The expression levels of tumor necrosis factor (TNF)-α/interferon (IFN)-γ-induced thymic and activation-regulated chemokines (TARC/CCL17) were measured after treatment with sHCG, WG, and RG extracts, and the effects of their bioactive compounds (CGA and four ginsenosides) on human skin keratinocytes (HaCaTs) were evaluated. Results: CGA and four ginsenosides, which are bioactive compounds of sHCG, significantly inhibited TNF-α/IFN-γ-induced TARC/CCL17 expression. The optimal sHCG extraction conditions predicted by the RSM models were 80 ℃ and 60% ethanol (v/v). The sHCG extracts produced at the pilot scale under optimal conditions greatly alleviated TNF-α/IFN-γ-induced TARC/CCL17 production compared with WG and RG extracts. Conclusions: Pesticide-free sHCG extracts, which contain high levels of CGA and the ginsenosides Re, Rg₁, Rb₁, and Rd as bioactive compounds, may have therapeutic potential for atopic diseases.