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K-최근방 이웃 방법을 사용한 장면 분류 시스템의 문턱값 접근을 통한 실제 환경에서의 성능 향상 방법
백승렬(SeungRyul Baek),유창동(Chang. D. Yoo) 대한전자공학회 2010 대한전자공학회 학술대회 Vol.2010 No.6
An Input image is blocked into several blocks and features are extracted from these blocks. Blocks are classified by K-NN classifier using training data with predefined labels, and the most frequently selected block label becomes the label of the image. K-NN based scene classification system is not perfect in a practical situation because there are lots of ambiguous images which even a man cannot tell (indoor from outdoor), (city from landscape), (sunset from mountain&forest), (forest from mountain). Thresholding approach is added to explicitly say that ambiguity exists, and this image has ambiguous label. This increases performance and completeness of previous K-NN based scene classification system.
The Economic Value of Residential Electricity Consumption in Seoul
Seung-Hoon Yoo,Seungryul Lee 한국에너지학회 2012 에너지공학 Vol.21 No.1
Electricity is the basic building block of economic development, and constitutes one of the vital infra-structural inputs in socio-economic development. The demand for electricity has been increasing due to extensive urbanization, industrialization, and a rise in the standard of living, as is the case with residential electricity consumption. This paper attempts to estimate the consumer surplus and the economic value of the residential consumption of electricity in Seoul to assist in decision-making in electricity management. The estimated consumer surplus represents the value of the area under the demand curve, above the actual price that is paid for residential electricity consumption. The estimated annual consumer surplus and economic value for the year 2005 amount to 2,144.7 and 3,727.4 billion won, respectively. The estimates per kWh were 184.9 and 316.0 won, respectively, which imply that the consumer surplus and the economic value of residential electricity consumption significantly outweigh the average price of electricity in 2005 of 91.1 won per kWh.
The Characteristics of Single Stripe Surface Dielectric Barrier Discharge with Solid Powder
Yong Ho Jung,Seungryul Yoo,Dong Chan Seok 한국진공학회(ASCT) 2020 Applied Science and Convergence Technology Vol.29 No.3
Surface dielectric barrier discharge (SDBD) plasma was generated with alumina powder on an SDBD electrode. Because of the higher dielectric constant of solid powder, a higher electric field is applied in the pores created by the powder particles. Depending on the powder particle sizes and gas species, the power consumption and total capacitance of the powder SDBD have characteristic trends. As the powder particle size decreases, the total volume of the discharge channels and consumed power at a given applied voltage decreased for helium (He) gas discharge; however, the opposite was observed for sulfur hexafluoride (SF6) gas discharge at atmospheric pressure. The consumed power decreased from 82.19 to 74.5 W with powder diameter decrement (no powder, 1, 0.1, and 0.01 mm) for He gas discharge at 10 kV and 1 kHz square voltage. However, for the SF6 gas discharge, the power increased from 17.86 to 49.07 W with 16 kV and 1 kHz square voltage. Therefore, the results of this study provide information regarding the characteristics of SDBD plasmas with porous dielectric media.
은닉 마르코프 모델의 최대 마진 훈련을 이용한 음성 감정 인식
윤성락(Sungrack Yun),이동훈(Donghoon Lee),백승렬(Seungryul Baek),박상혁(Sanghyuk Park),장달원(Dalwon Jang),유창동(Chag D. Yoo) 대한전자공학회 2010 대한전자공학회 학술대회 Vol.2010 No.6
In this paper, we propose a max-margin learning algorithm of hidden Markov model for speech emotion recognition. A max-margin learning leads to a good generalization ability on testing data even with small number of training data which may lead to an over-fitting. In the experiment, we observed that the proposed learning algorithm outperforms the learning criteria such as the maximum likelihood and maximum mutual information.