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웬델 베리의『제이버 크로우』에 나타난 생태적 농업과 영농산업의 대비(對比)
이영현(Lee, Younghyun) 문학과환경학회 2013 문학과 환경 Vol.12 No.2
This paper aims to explore Wendell Berry’s ecological vision by comparing ecological agriculture and agribusiness revealed in his novel, Jayber Crow. The author embodies his ecological vision in the novel through the conflict between two farmers, Athey Keith and his son?in?law, Troy Chatham. In the ecological agriculture, such values as organic relations and interdependence between the members of a farm have been respected. Farming, whose aim is to feed and raise lives, degenerated into agribusiness, whose biggest concern is to maximize profit in the shortest time period. Troy insists on changing to modernized and mechanical ways of farming, as agribusinesses advertise. The businesses put commercial values ahead of everything, claiming that agricultural implements and chemicals like pesticides and herbicides will foster efficiency and enhance farm production. Traditional farms like Athey’s, how small they are, have been totally self-sufficient in food production, while Troy’s farm becomes more and more dependent on agribusinesses. The dominant?subordinate relationship aggravates Troy’s farm, which is typical of today’s mechanical farms. Troy ends up going bankrupt and cannot help selling “the Nest Egg”, though he and his wife, Mattie Keith, inherit a farm from Athey, her father. The comparison between traditional farming and agribusiness in the novel reveals Berry’s ecological vision which seeks sustainable ways of life for all the members of our ecological community.
NPU를 위한 효율적인 Fused Convolution 스케줄링 기법
이영현(Younghyun Lee),김혜준(Hyejun Kim),유용승(Yongseung Yu),조명진(Myeongjin Cho),서지원(Jiwon Seo),박영준(Yongjun Park) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.11
As the AI industry evolves, neural network processing units (NPUs) are being developed to deliver AI services faster and more efficiently. One of the most important challenges for these NPUs is task scheduling to minimize off-chip memory accesses, which incur significant performance overhead. In particular, convolutional layers can be fused with multiple layers to reduce the memory accesses, but it is difficult to find the optimal schedule due to the too large exploration space. In this paper, we propose an efficient schedule exploration algorithm to optimize the fusion of multiple convolutional layers in NPUs. The proposed algorithm organizes the fusion group exploration space in the form of a grid to explore the optimal schedule. Experimental results show that the fusion schedule explored by the proposed method reduces the latency by 7.7% and reduces the off-chip memory access by 15% compared to the baseline algorithm.
이영현(Younghyun Lee),정영만(Youngman Jeong),정찬세(Chanse Jeong),양순용(Soonyong Yang3) 한국자동차공학회 2013 한국자동차공학회 지부 학술대회 논문집 Vol.2013 No.4
This paper describes a production process of unmanned 3-wheel vehicle. We selected EV’s components and specification for the manufacturing of electric vehicles. and We made electric vehicle directly. Typical feature of our EV is method of motor drive. One motor is installed to rear wheel. we need to control at rear wheels. we measured steering angle, motor rpm. and We made program that control wheel operation dependent on vehicle speed and steering angle
이영현(Younghyun Lee),정찬세(Chanse Jeong),양순용(Soonyong Yang) 한국자동차공학회 2013 한국자동차공학회 지부 학술대회 논문집 Vol.2013 No.11
Fuel efficiency is one of the major issues in regard to energy and environment. As customers desire more comfortable vehicles, increase of accessory traction force is necessary. In this paper, according to the air conditioning compressor operate on fuel consumption for the study is described. Air-conditioning system of the vehicle increases fuel consumption by 30%. Injection time of the injector was measured. Potential was measured before and after the injector. Using an oscilloscope waveforms were measured. Impact on fuel consumption and air operation was writing about. Fuel injection air compressor operation showed that the more time that is.
이재명(Jaemyung Lee),이주성(Jusung Lee),이영현(Younghyun Lee),이준수(Jaemyung Lee) 대한전자공학회 2020 대한전자공학회 학술대회 Vol.2020 No.8
Instance segmentation-based approach using Mask R-CNN is currently one of the leading methods for the text localization task. Different from general object detection tasks, the aspect ratio of text instances is too high to apply Mask R-CNN as it is. To simply apply Mask R-CNN for text detection yields false positives due to overgeneralized receptive fields for bounding boxes. In this paper, we propose a modified Mask R-CNN architecture for text detection. We present a method to extract features containing word-level and character-level receptive fields simultaneously. Our approach shows consistent performance improvement on MLT 2017 and Incidental Scene Text. Moreover, our method surpasses most of prior state-of-the-art text localization methods appeared in recent computer vision conferences.