• Title/Summary/Keyword: engineering department

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Dual Address Electrodes for Fast Addressing Method of ac-PDP with High Xe% Working Gas

  • Lee, D.K.;Choi, J.H.;Choi, W.S.;Ok, J.W.;Kwon, B.S.;Lee, H.J.;Lee, H.J.;Kim, D.H.;Park, C.H.
    • 한국정보디스플레이학회:학술대회논문집
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    • 2005.07a
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    • pp.247-250
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    • 2005
  • In this paper, new address electrode having separated dual electrodes is suggested to reduce addressing time in ac PDP. It had been found that both the formative and jitter width of the suggested electrode are improved by $10{\sim}20$ % compared with the conventional one on IMID 04'. So we experiment other several kinds of the separated electrodes, and the change in discharge characteristics is analyzed by using a two-dimensional fluid simulation. The key feature of the suggested structure is that the distribution of Xe and Ne ion is controllable during the address periods without significant increases in the capacitive load of the address electrodes.

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A High Efficient Piezoelectric Windmill using Magnetic Force for Low Wind Speed in Wireless Sensor Networks

  • Yang, Chan Ho;Song, Yewon;Jhun, Jeongpil;Hwang, Won Seop;Hong, Seong Do;Woo, Sang Bum;Sung, Tae Hyun;Jeong, Sin Woo;Yoo, Hong Hee
    • Journal of the Korean Physical Society
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    • v.73 no.12
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    • pp.1889-1894
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    • 2018
  • An innovative small-scale piezoelectric energy harvester has been proposed to gather wind energy. A conventional horizontal-axis wind power generation has a low generating efficiency at low wind speed. To overcome this weakness, we designed a piezoelectric windmill optimized at low-speed wind. A piezoelectric device having high energy conversion efficiency is used in a small windmill. The maximum output power of the windmill was about 3.14 mW when wind speed was 1.94 m/s. Finally, the output power and the efficiency of the system were compared with a conventional wind power system. This work will be beneficial for the piezoelectric energy harvesting technology to be applied to the real world such as wireless sensor networks (WSN).

Electrical and magnetic properties of GaMnN with varying the concentrations of Mn and Mg

  • F.C. Yu;Kim, K.H.;Lee, K.J.;H.S. Kang;Kim, J.A.;Kim, D.J.;K.H. Baek;Kim, H.J.;Y.E. Ihm
    • Proceedings of the Materials Research Society of Korea Conference
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    • 2003.03a
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    • pp.109-109
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    • 2003
  • III- V ferromagnetic semiconductor has attracted great attention as a potential application for spintronics due to a successful demonstration of spin injection from ferromagnetic GaNnAs into semiconductor. GaMnN may be one of the possible candidates for room temperature operation. Samples were grown on sapphire (0001) substrate at $650^{\circ}C$ via molecular beam epitaxy with a single Precursor of (Et$_2$Ga(N$_3$)NH$_2$$CH_3$) and solid source of Mn at different Mn source temperature. The background pressure is low 10$^{-10}$ Torr and the samples growth pressure was 1.4 $\times$ 10$^{-6}$ Torr.

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Quality Estimation of Net Packaged Onions during Storage Periods using Machine Learning Techniques

  • Nandita Irsaulul, Nurhisna;Sang-Yeon, Kim;Seongmin, Park;Suk-Ju, Hong;Eungchan, Kim;Chang-Hyup, Lee;Sungjay, Kim;Jiwon, Ryu;Seungwoo, Roh;Daeyoung, Kim;Ghiseok, Kim
    • KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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    • v.28 no.3
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    • pp.237-244
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    • 2022
  • Onions are a significant crop in Korea, and cultivation is increasing every year along with high demand. Onions are planted in the fall and mainly harvested in June, the rainy season, therefore, physiological changes in onion bulbs during long-term storage might have happened. Onions are stored in cold room and at adequate relative humidity to avoid quality loss. In this study, bio-yield stress and weight loss were measured as the quality parameters of net packaged onions during 10 weeks of storage, and the storage environmental conditions are monitored using sensor networks systems. Quality estimation of net packaged onion during storage was performed using the storage environmental condition data through machine learning approaches. Among the suggested estimation models, support vector regression method showed the best accuracy for the quality estimation of net packaged onions.