• 한국공작기계학회논문집
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• 제18권2호
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• pp.178-186
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• 2009

Most of automotive plastic parts are injection molding products. Inspection of total product is impossible, because number of product to inspect is too many and various. Condition-based Monitoring was proposed to decrease cost and time for inspecting. In this research, a system that predicts quality of part at fabrication point of time, and confirms informations through the internet was developed. Cavity sensors were installed inside of mold, and gathered signals as measuring, and through this process Sensor-based Monitoring system can be observed manufacturing of a part. Monitoring system transmits signals to client through the internet, and finally developed system provides manufacturing informations and predictions of quality as web-based monitoring.

• 농약과학회지
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• 제5권4호
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• pp.27-32
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• 2001

17과일의 43가지 부위의 메탄을 추출물을 대상으로 5종의 주요 농업해충 및 4종의 저장물 해충에 대한 살충효과를 조사한 효과는 과일류의 종류 및 해충의 종류에 따라 커다란 차이를 보였다. 5,000 ppm 농도에서 80% 이상의 살충효과를 나타내는 10종의 시료를 2,500 ppm에서 살충효과를 검정하였다. 모과와 석류씨가 벼멸구, 포도씨가 복숭아혹진딧물, 유자, 자몽, 메론, 감, 사과, 복숭아, 포도씨가 배추좀나방, 모과씨가 담배거세미나방, 모과와 포도 추출물이 점박이응애에 대하여 80% 이상의 살충효과를 나타냈다. 4종의 저장물해충에 대한 살충효과는 50 ppm의 농도로 처리할 때 모과 및 포도 추출물이 쌀바구미, 모과, 유자, 감 및 포도 추출물이 팥바구미에 대하여 80% 이상의 살충효과를 나타냈다. 그러나 화랑곡나방와 궐련벌레에 대하여는 사용된 과일류의 추출물이 활성을 나타내지 않았다. 이상의 결과로부터 복숭아혹진딧물, 벼멸구, 배추좀나방 담배거세미나방 및 점박이응애에 높은 방제효과를 보인 상기과일류 추출물들은 농업해충 방제제로서 사용 가능성이 예상되었으며, 또한 쌀바구미와 팥바구미에 강한 살충효과를 보인 추출물은 저장물해충방제에 이용할 수 있을 것으로 기대된다.

• Industrial Engineering and Management Systems
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• 제10권1호
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• pp.34-42
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• 2011

Many companies open multiple projects simultaneously due to market trends, which results in a crowding out effect because of limited resources. R&D engineers become overloaded and scheduling of product development is delayed resulting in timing misses and lost sales leads. The company in this case study (Company A), often opens up many projects simultaneously in order to respond to market needs quickly. The engineers are overloaded and, of course, the schedule is delayed. In order to identify problems, Company A began using Dr. Goldratt's Thinking Processes (TP) during new product development (NPD). When the analysis phase of TP was completed, Company A's core problem was identified as "the quantity of kick-off projects." Consequently, new rules and conditions and procedures were proposed for the opening, suspending, stopping, and closing of projects. Finally, the "Future Reality Tree" ensured that the proposed rules, conditions and procedures were set up as an available solution approved for practical application by executives. After a one-year trial run, the results showed that the Project Duration Rate was reduced by 53%, the Project Closed Rate was increased by 140% and the Project on Time Rate was increased from 10% to 68%. The above results give significant evidence of the benefits of the proposed methodology.

• JSTS:Journal of Semiconductor Technology and Science
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• 제16권2호
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• pp.251-254
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• 2016

An energy-efficient object matching accelerator is proposed for mobile object recognition based on matching prediction scheme. Conventionally, vocabulary tree has been used to save the external memory bandwidth in object matching process but involved massive internal memory transactions to examine each object in a database. In this paper, a novel object matching accelerator is proposed based on matching predictions to reduce unnecessary internal memory transactions by mitigating non-target object examinations, thereby improving the energy-efficiency. Experimental results show a 26% reduction in power-delay product compared to the prior art.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
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• pp.229-232
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• 2000

각종 범용 컴퓨터 및 디지탈 신호처리에서 중요한 역할을 하는 16비트 정수형, 2의 보수 형태의 곱셈연산을 수행하기 위한 고속 승산기구조를 설계하고 시뮬레이션 하였다. 부분곱을 합하는 부분은 일반적으로 전체 곱셈기 처리 지연시간의 절반정도를 차지하므로 이 부분의 설계방법이 곱셈기의 궁극적인 속도향상에 직접적인 영향을 미친다. 부분곱의 개수를 줄이기 위하여 Booth encoder를 사용하였고, partial product(부분곱)의 덧셈시간을 줄이기 위하여 4:2 CSA(can save adder)와 3:2 CSA로 CSA tree를 구성 하였으며, 최종결과는 carry look- ahead tree로 얻어진다. Hyundai CMOS 0.35$\mu\textrm{m}$ 1-poly 4-metal 공정으로 layout하여 설계하였으며, 곱셈시간은 2.7ns(tipical case)이하로 측정되었다.

• Natural Product Sciences
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• 제19권3호
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• pp.263-268
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• 2013

The inhibitory effects of adipogenesis on ethyl acetate (EtOAc) fraction from leaves of the Tulip tree (TT) were evaluated. Exposure to TT EtOAc fraction (25~200 ${\mu}g/mL$) for a 72 hr incubation period did not significantly change cell viability. TT EtOAc fraction, with concentrations of 100 and 200 ${\mu}g/mL$, inhibited lipid accumulation in 3T3-L1 adipocytes in a dose dependent manner in adipogenesis. The expression of $PPAR{\gamma}$ and $C/EBP{\alpha}$, essential adipogenic markers, was significantly decreased when TT EtOAc fraction was added to cells for 8 days as compared with the untreated control group. These results suggest that TT EtOAc fraction might be a potential therapeutic agent as an effective, natural alternative material for obesity treatment.

• 정보처리학회논문지A
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• 제10A권6호
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• pp.671-676
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• 2003

본 논문에서는 고속 병렬 곱셈기에서 속도향상을 위해 부분 곱을 가산하는 과정에 구성되는 CSA(Carry Select Adder) 트리에 새로운 압축기를 적용한 새로운 첫 번째 부분 곱가산(First Partial Product Addition : FPA)를 제안하여 기존의 전가산기를 이용한 병렬가산기보다 부분곱을 계산하는 속도를 약 20% 개선할 수 있게 했다. 새로운 회로는 새로운 FPA 구조를 사용하여 최종 합 CLA 비트를 N/2로 줄인다. 2.5v 0.25um CMOS 기술을 이용하여 제작된 16${\times}$16 곱셈기는 5.14nS의 곱셈 고속을 얻었다. 이 곱셈기의 구조는 파이프라인 설계에 용이하며 고성능을 낸다.

• Nuclear Engineering and Technology
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• 제49권8호
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• pp.1575-1588
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• 2017

In order to develop a domestic research roadmap for severe accidents, a special committee was established by the Korean Nuclear Society. One of the subcommittees discussed the characteristics and the relevant technical issues in the stages of fission product release and physical forms of radionuclide release and transport. The group members developed a tree to identify fission product release phenomena by tracing failures of individual defense-in-depth barriers and added possible countermeasures against failure. For each elemental issue, they searched for technical problems by examining the phenomena, accident management actions, and regulatory aspects relevant to the mitigation features for containment, including mitigation strategies against containment bypass accidents. Regulatory concerns, including the source term and the acceptance criteria for radionuclide release, were also considered. They identified further research needs regarding important technical issues based on the degree of the current knowledge level in Korea and in foreign countries, looking at the significance and urgency of issues and the expected research period required to reach an advanced level of knowledge. As a result, the group identified the 12 most important and urgent issues, most of which were expected to require mid-term and long-term research periods.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.17-28
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• 2023

Today Agriculture segment is a significant supporter of Indian economy as it represents 18% of India's Gross Domestic Product (GDP) and it gives work to half of the nation's work power. Farming segment are required to satisfy the expanding need of food because of increasing populace. Therefore, to cater the ever-increasing needs of people of nation yield prediction is done at prior. The farmers are also benefited from yield prediction as it will assist the farmers to predict the yield of crop prior to cultivating. There are various parameters that affect the yield of crop like rainfall, temperature, fertilizers, ph level and other atmospheric conditions. Thus, considering these factors the yield of crop is thus hard to predict and becomes a challenging task. Thus, motivated this work as in this work dataset of different states producing different crops in different seasons is prepared; which was further pre-processed and there after machine learning techniques Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, Ridge Regression, Polynomial Regression, Linear Regression are applied and their results are compared using python programming.

• 융합정보논문지
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• 제7권1호
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• pp.55-60
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• 2017

사물인터넷 환경에서 인간의 개입 없는 지능화된 서비스를 위해서는 IoT 디바이스에서 생성되는 빅데이터로 부터 정상 패턴을 학습하고 이를 기반으로 불량, 오작동과 같은 이상 징후에 대해 예측하는 과정이 요구된다. 본 연구의 목적은 제품 공정의 다양한 기기에서 발생되는 빅데이터를 분석함으로써 제품 불량을 예측할 수 있는 기계 학습모델을 구현하는 것이다. 기계 학습 모델은 어느 정도 볼륨을 가진 기존 데이터를 기반으로 분석을 해야 하므로 빅데이터 분석도구 R을 사용하였으며, 제품 공정에서 수집된 데이터에는 제품에 대한 불량 여부가 포함되어 있으므로 지도 학습 모델을 활용하였다. 연구의 결과, 제품 불량에 영향을 주는 변수 및 변수 조건을 분류하였고, 의사결정 트리를 기반으로 제품의 불량 여부에 대한 예측 모델을 제시하였다. 또한, ROC Curve를 이용한 모델의 적합성 및 성능평가 분석에서 모델의 예측력은 상당히 높게 나타났다.