• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2007년도 하계학술대회 논문집 Vol.8
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• pp.174-175
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• 2007

A programmable metallization cell (PMC) memory structure with copper-saturated GeTe solid electrolyte films doped by nitrogen was prepared on a TiW bottom electrode by a co-sputtering technique at room temperature. The $Ge_{45}Te_{55}$ solid electrolyte films deposited with various $N_2$/Ar flow ratios showed an increase of crystallization temperature and especially, the electrolyte films deposited at $N_2$/Ar ratios above 30% showed a crystallization temperature above $400^{\circ}C$, resulting in surviving in a back-end process in semiconductor memory devices. The device with a 200 nm thick $Cu_{1-x}(Ge_{45}Te_{55})_x$ electrolyte switches at 1 V from an "off " state resistance, $R_{off}$, close to $10^5$ to an "on" resistance state, Ron, more than 20rders of magnitude lower for this programming current.

• 디지털산업정보학회논문지
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• 제14권4호
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• pp.79-85
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• 2018

This paper presents an implementation method of Long Term Evolution-Advanced (LTE-A) Physical Downlink Shared Channel (PDSCH) decoder using a general-purpose multicore Digital Signal Processor (DSP), TMS320C6670. Although the DSP provides some useful coprocessors such as turbo decoder, fast Fourier transformer, Viterbi Coprocessor, Bit Rate Coprocessor etc., it is specific to the base station platform implementation not the mobile terminal platform implementation. This paper shows an implementation method of the LTE-A PDSCH decoder using programmable DSP cores as well as the coprocessors of Fast Fourier Transformer and turbo decoder. First, it uses the coprocessor supported by the TMS320C6670, which can be used for PDSCH implementation. Second, we propose a core programming method using DSP optimization method for block diagram of PDSCH that can not use coprocessor. Through the implementation, we have verified a real-time decoding feasibility for the LTE-A downlink physical channel using test vectors which have been generated from LTE-A Reference Measurement Channel (RMC) Waveform R.6.

• International Journal of Naval Architecture and Ocean Engineering
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• 제12권1호
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• International journal of advanced smart convergence
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• 제11권2호
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• pp.22-29
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• 2022

In this paper, for the purpose of designing an real-time unmanned monitoring system, the YOLOv5s (small) object detection model was applied on the NVIDIA TX2^TM AI (Artificial Intelligence) edge computing platform in order to design the fundamental function of an unmanned monitoring system that can detect objects in real time. YOLOv5s was applied to the our real-time unmanned monitoring system based on the performance evaluation of object detection algorithms (for example, R-CNN, SSD, RetinaNet, and YOLOv5). In addition, the performance of the four YOLOv5 models (small, medium, large, and xlarge) was compared and evaluated. Furthermore, based on these results, the YOLOv5s model suitable for the design purpose of this paper was ported to the NVIDIA TX2^TM AI edge computing system and it was confirmed that it operates normally. The real-time unmanned monitoring system designed as a result of the research can be applied to various application fields such as an security or monitoring system. Future research is to apply NMS (Non-Maximum Suppression) modification, model reconstruction, and parallel processing programming techniques using CUDA (Compute Unified Device Architecture) for the improvement of object detection speed and performance.

• 유통과학연구
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• 제21권6호
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• pp.51-68
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• 2023

Purpose: This study aims to explore the impact of green products' claim skepticism on green purchase intention and further investigates the moderating role of environmental concern in the relationship. This study, by drawing the persuasion knowledge model expected that ambiguity avoidance penalizes less familiar brands than familiar brands. Further, the present study building on Hofstede's cultural dimension, specifically, uncertainty avoidance, undertook a scenario to understand any difference that exist between uncertainty avoidance cultural groups. This study also investigates gender differences in green claim skepticism and proclivity to purchase green products. Research design, data, and methodology: For analyzing the relationship relevant hypotheses were designed, and R-programming software was used. To test the hypotheses two independent sample t-test and regression analysis were carried out. Results: The results suggest that consumers' skepticism toward green claims influenced the intention to purchase eco-friendly products. The study finding also confirms the effect is moderated by environmental concern. Also, the findings of two scenarios reveal that consumers in high uncertainty avoidance culture exhibited a greater level of skepticism for green print advertising and green packaging claims when the brand in the advertising and packaging was unfamiliar than when it was familiar. Conclusions: To alter the negative effect of skepticism the consumer should believe the environmental claims are valid so that they can contribute to solving sustainability issues.

• 한국군사과학기술학회지
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• 제26권4호
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• pp.313-323
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• 2023

The wearable robot system is designed to assist human skeletal and muscular systems for enhancing user's abilities in various fields, including medical, industrial, and military. The military has an expanding need for wearable robots with the integration of surveillance/control systems and advanced equipment in unstructured battlefield environments. However, there is a lack of research on the design and mechanism of wearable robots, especially for power assist systems. This study proposes a lightweight wearable robot system that provides comfortable wear and muscle support effects in various movements for soldiers performing high-strength and endurance missions. The Power assist mechanism is described and verified, and the tasks that require power assist are analyzed. This study explain the system including its driving mechanism, control system, and mechanical design. Finally, the performance of the robot is verified through experiments and evaluations, demonstrating its effectiveness in muscle support.

• Steel and Composite Structures
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• 제50권4호
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• pp.443-458
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• 2024

The construction industry, one of the biggest producers of greenhouse emissions, is under a lot of pressure as a result of growing worries about how climate change may affect local communities. Geopolymer concrete (GPC) has emerged as a feasible choice for construction materials as a result of the environmental issues connected to the manufacture of cement. The findings of this study contribute to the development of machine learning methods for estimating the properties of eco-friendly concrete, which might be used in lieu of traditional concrete to reduce CO₂ emissions in the building industry. In the present work, the compressive strength (f_c) of GPC is calculated using random forests regression (RFR) methodology where natural zeolite (NZ) and silica fume (SF) replace ground granulated blast-furnace slag (GGBFS). From the literature, a thorough set of experimental experiments on GPC samples were compiled, totaling 254 data rows. The considered RFR integrated with artificial hummingbird optimization (AHA), black widow optimization algorithm (BWOA), and chimp optimization algorithm (ChOA), abbreviated as ARFR, BRFR, and CRFR. The outcomes obtained for RFR models demonstrated satisfactory performance across all evaluation metrics in the prediction procedure. For R² metric, the CRFR model gained 0.9988 and 0.9981 in the train and test data set higher than those for BRFR (0.9982 and 0.9969), followed by ARFR (0.9971 and 0.9956). Some other error and distribution metrics depicted a roughly 50% improvement for CRFR respect to ARFR.

• 한국산학기술학회논문지
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• 제21권8호
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• pp.557-562
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• 2020

코로나19로 인해서 비대면 강의환경에서 온라인 학습이 교육환경의 주요 학습기법으로 채택되고 있다. 온라인 학습패턴이 학업성적에 어떤 영향을 미치는지에 관한 연구가 부족하여, 본 연구에서는 학습자들의 온라인 동영상 학습횟수와 시간을 주요 요소로 두고, 매 학습에 대한 형성 평가와 함께 중간고사 기말고사를 바탕으로 학습효과의 상관관계를 분석하였다. 분석 대상은 대학에서 예체능 학부 학생들이 가장 어려워하는 교양 과목 중 컴퓨터 프로그래밍 교과목을 분석하였다. 실제 학생들의 사례를 분석한 결과 매주 실시한 형성 평가와 학습회수, 학습 시간과는 상관관계가 없는 것으로 나타났고, 중간고사와 기말고사와는 평소 학습회수(r=.39 p<0.05)와 학습 시간(r=.42 p<0.05)이 상관관계가 있는 것으로 나타났다. 강의 진행 과정에서 SMS 문자, 게시판, 메일 등의 요소는 모든 학생이 접하지 못하여 제외하였으므로, 앞으로는 좀 더 다양한 요인을 고려하여 비대면 강의환경에서의 학습자 패턴을 분석하고 연구한다면 학습자들의 요구와 학습효과를 향상할 수 있을 것이다.

• 한국항공우주학회지
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• 제41권9호
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• pp.681-688
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• 2013

불가피하게 급증하는 항공기 수요량에 따른 여러 가지 문제들을 해결하는 방안으로 항공기의 지연시간을 줄여, 공항의 수용력을 극대화하는 항공교통관리가 주목받고 있다. 본 논문은 공항주변 항공교통흐름을 원활히 하여 항공기 처리량을 최대화하는 항공기 스케줄링의 최적화를 목적으로 한다. 본 연구에서 개발한 스케줄링 기법은 스케줄링 문제를 수학적으로 모델링한 후, 혼합정수선형계획법과 유전자 알고리즘을 도입하여 항공기 지연시간을 최소로 하는 최적의 스케줄링을 제공한다. 최적화된 스케줄링과 실제 인천 공항에서의 항공기 스케줄링과 비교해 보았고, 그 결과 최적화된 스케줄링이 제공하는 항공기 처리량이 현재 인천 공항에서 처리하는 항공기보다 현저히 높다는 결과를 확인할 수 있었다. 본 연구에서 개발한 스케줄러는 향후 항공기의 포화 상태를 적절하게 대처하는데 큰 도움을 줄 것이라 예상되어진다.

• 한국농림기상학회지
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• 제20권2호
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• pp.228-232
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• 2018

기후변화 영향평가를 위하여 프로세스 작물모형이 많이 이용되고 있지만, FORTRAN, C++, Delphi, Java와 같은 컴퓨터 프로그래밍 언어로 만들어지기 때문에 농학자들이 작물 모형을 제작하는 것이 쉽지 않다. 배추 모형을 개발하기 위해 6 가지 온도 체계를 가진 토양-식물-대기 연구(SPAR) 실험 자료가 사용되었다. SPAR 챔버에서의 식물 재배 기간 동안 잎의 수, 잎의 면적, 식물의 생장률을 6 회 측정 하였다. 또한 휴대용 LI-6400 광합성 측정기를 이용하여 잎의 광합성을 측정 하였다. 잎 수준 광합성 예측은 Farquhar, von Caemmerer 및 Berry (FvCB) 모형을 적용 하였고, 수관의 광합성은 Sun/Shade 모형이 사용되었다. 이러한 전 과정은 BuildIt 이라는 Excel 추가기능이 포함된 엑셀 파일로 제작되었다. 개발된 모형으로 시간 단위의 기상 입력 자료를 사용하여 배추의 광합성, 생장률 및 기타 생리 변수의 변화를 모의할 수 있었으며, 측정된 배추의 건조 중량의 변화와 모형에서 예측된 동화량과는 비례적인 관계를 나타내었으나, 온도에 따라서 다르게 나타났다.