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2020 연구성과별 연구자 정보 (69 / 2428)

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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
A polyelectrolytic polyacetylene for quasi-solid state dye-sensitized solar cell applications Choi, Hyun-Kuk Choi, HK 1 Kyungpook Natl Univ, Sch Nano & Mat Sci & Engn, Sangju, South Korea ysgal@kiu.ac.kr;
A polyelectrolytic polyacetylene for quasi-solid state dye-sensitized solar cell applications Shin, Dong Jin Shin, DJ 2 Pusan Natl Univ, Grad Dept Chem Mat, Dept Chem Educ, Busan, South Korea ysgal@kiu.ac.kr;
A polyelectrolytic polyacetylene for quasi-solid state dye-sensitized solar cell applications Shin, Dong Jin Shin, DJ 2 Pusan Natl Univ, Busan, South Korea ysgal@kiu.ac.kr;
A polyelectrolytic polyacetylene for quasi-solid state dye-sensitized solar cell applications Jin, Sung-Ho Jin, SH 3 Pusan Natl Univ, Grad Dept Chem Mat, Dept Chem Educ, Busan, South Korea ysgal@kiu.ac.kr;
A polyelectrolytic polyacetylene for quasi-solid state dye-sensitized solar cell applications Jin, Sung-Ho Jin, SH 3 Pusan Natl Univ, Busan, South Korea ysgal@kiu.ac.kr;
A polyelectrolytic polyacetylene for quasi-solid state dye-sensitized solar cell applications Lim, Kwon Taek Lim, KT 4 Pukyong Natl Univ, Dept Display Engn, Busan, South Korea M-8855-2018 Lim, Kwon ysgal@kiu.ac.kr;
A polyelectrolytic polyacetylene for quasi-solid state dye-sensitized solar cell applications Jeong, Seung-Hwan Jeong, SH 5 Kyungil Univ, Dept Fire Safety, Gyongsan 38428, Gyeongsangbuk D, South Korea ysgal@kiu.ac.kr;
A polyelectrolytic polyacetylene for quasi-solid state dye-sensitized solar cell applications Gal, Yeong-Soon Gal, YS 6 교신저자 Kyungil Univ, Dept Fire Safety, Gyongsan 38428, Gyeongsangbuk D, South Korea ysgal@kiu.ac.kr;
A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer's disease Park, Jinhee Park, J 1 Korea Brain Res Inst, Dementia Res Grp, Daegu, South Korea mkcheon@kbri.re.kr;
A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer's disease Park, Jinhee Park, J 1 Kyungpook Natl Univ, Sch Elect Engn, Daegu, South Korea mkcheon@kbri.re.kr;
A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer's disease Kim, Hyerin Kim, H 2 Korea Brain Res Inst, Dementia Res Grp, Daegu, South Korea 0000-0003-4962-8272 Kim, Hyerin mkcheon@kbri.re.kr;
A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer's disease Kim, Jaekwang Kim, J 3 Korea Brain Res Inst, Dementia Res Grp, Daegu, South Korea 0000-0002-7312-4077 Kim, Jaekwang mkcheon@kbri.re.kr;
A practical application of generative adversarial networks for RNA-seq analysis to predict the molecular progress of Alzheimer's disease Cheon, Mookyung Cheon, M 4 교신저자 Korea Brain Res Inst, Dementia Res Grp, Daegu, South Korea AIE-0782-2022 Cheon, Mookyung 0000-0001-6777-6725 Cheon, Mookyung mkcheon@kbri.re.kr;
A Prediction Scheme in Spiking Neural Network (SNN) Hardware for Ultra-low Power Consumption Yang, Jeonggyu Yang, J 1 Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea jg.yang@knu.ac.kr;tsong@knu.ac.kr;
A Prediction Scheme in Spiking Neural Network (SNN) Hardware for Ultra-low Power Consumption Song, Taigon Song, T 2 교신저자 Kyungpook Natl Univ, Sch Elect & Elect Engn, Sch Elect Engn, Daegu 41566, South Korea jg.yang@knu.ac.kr;tsong@knu.ac.kr;
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