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| 1 | A high-speed CMOS image sensor with column-parallel two step single-slope ADCs显示文摘 | Lira Seunghyun Lee Jeonghwan Dongsoo Kim | 2009 | IEEE Transactions on Electron Devices2009，56，3： | 1 |
| 2 | A high-speed CMOS image sensor with column-parallel two- step single-slope ADCs显示文摘 | Lim Seunghyun Lee Jeonghwan Kim Dongsoo | 2009 | IEEE Transactions on Electron Devices2009，56，3： | 1 |
| 3 | Pilot-scale temperate-climate treatment of domestic wastewater with a staged anaerobic fluidized membrane bioreactor (SAF-MBR)显示文摘 | SHIN Chungheon MCCARTY Perry L KIM Jeonghwan | 2014 | Bioresource Technology2014，59，： | 1 |
| 4 | A high-speed CMOS image sensor with column- parallel two-step single-slope ADCs显示文摘 | Lim Seunghyun Lee Jeonghwan Kim Dongsoo | 2009 | IEEE Transac tions on Electron Device2009，56，3： | 1 |
| 5 | Effect of ozone dosage and hydrodynamic conditions on the permeate flux in a hybrid ozonation–ceramic ultrafiltration system treating natural waters显示文摘 | Jeonghwan Kim Simon H.R. Davies Melissa J. Baumann Volodymyr V. Tarabara Susan J. Masten | 2007 | Journal of Membrane Science2007，，1： | 1 |
| 6 | Effect of ozone dosage and hydrodynamic conditions on the permeate flux in a hybrid ozonation–ceramic ultrafiltration system treating natural waters显示文摘 | Jeonghwan Kim Simon H.R. Davies Melissa J. Baumann Volodymyr V. Tarabara Susan J. Masten | 2007 | Journal of Membrane Science2007，，1： | 1 |
| 7 | The use of nanoparticles in polymeric and ceramic membrane structures: Review of manufacturing procedures and performance improvement for water treatment显示文摘 | Jeonghwan Kim Bart Van der Bruggen | 2010 | Environmental Pollution2010，，7： | 1 |
| 8 | A high-speed CMOS image sensor with column-parallel two-step single-slope ADCs显示文摘 | Lim Seunghyun Lee Jeonghwan Kim Dongsoo | | 0，，03： | 1 |
| 9 | Production of taxoland taxanesinTaxusbrevifolia cell cultures: effect of sugar 显示文摘 | Kim Jin Hoon Yun Jeonghwan Hwang Yngsoon | 1995 | Biotechnology1995，17，1： | 1 |
| 10 | Recurrent Autoencoder Ensembles for Brake Operating Unit Anomaly Detection on Metro Vehicles显示文摘The anomaly detection of the brake operating unit (BOU) in thebrake systems on metro vehicle is critical for the safety and reliability ofthe trains. On the other hand, current periodic inspection and maintenanceare unable to detect anomalies in an early stage. Also, building an accurateand stable system for detecting anomalies is extremely difficult. Therefore,we present an efficient model that use an ensemble of recurrent autoencodersto accurately detect the BOU abnormalities of metro trains. This is the firstproposal to employ an ensemble deep learning technique to detect BOUabnormalities in metro train braking systems. One of the anomalous caseson metro vehicles is the case when the air cylinder (AC) pressures are less thanthe brake cylinder (BC) pressures in certain parts where the brake pressuresincrease before coming to a halt. Hence, in this work, we first extract the dataof BC and AC pressures. Then, the extracted data of BC and AC pressuresare divided into multiple subsequences that are used as an input for bothbi-directional long short-term memory (biLSTM) and bi-directional gatedrecurrent unit (biGRU) autoencoders. The biLSTM and biGRU autoencodersare trained using training dataset that only contains normal subsequences. Fordetecting abnormalities from test dataset which consists of abnormal subsequences, the mean absolute errors (MAEs) between original subsequences andreconstructed subsequences from both biLSTM and biGRU autoencoders arecalculated. As an ensemble step, the total error is calculated by averaging twoMAEs from biLSTM and biGRU autoencoders. The subsequence with totalerror greater than a pre-defined threshold value is considered an abnormality.We carried out the experiments using the BOU dataset on metro vehiclesin South Korea. Experimental results demonstrate that the ensemble modelshows better performance than other autoencoder-based models, which showsthe effectiveness of our ensemble model for detecting BOU anomalies onmetro trains. | Jaeyong Kang Chul-Su Kim Jeong Won Kang Jeonghwan Gwak | 2022 | Computers, Materials & Continua2022，，10： | 0 |
| 11 | Greywater reuse as a key enabler for improving urban wastewater management显示文摘Sustainable water management is essential to guaranteeing access to safe water and addressing the challenges posed by climate change,urbanization,and population growth.In a typical household,greywater,which includes everything but toilet waste,constitutes 50e80%of daily wastewater generation and is characterized by low organic strength and high volume.This can be an issue for large urban wastewater treatment plants designed for high-strength operations.Segregation of greywater at the source for decentralized wastewater treatment is therefore necessary for its proper management using separate treatment strategies.Greywater reuse may thus lead to increased resilience and adaptability of local water systems,reduction in transport costs,and achievement of fit-for-purpose reuse.After covering greywater characteristics,we present an overview of existing and upcoming technologies for greywater treatment.Biological treatment technologies,such as nature-based technologies,biofilm technologies,and membrane bioreactors(MBR),conjugate with physicochemical treatment methods,such as membrane filtration,sorption and ion exchange technologies,and ultraviolet(UV)disinfection,may be able to produce treated water within the allowable parameters for reuse.We also provide a novel way to tackle challenges like the demographic variance of greywater quality,lack of a legal framework for greywater management,monitoring and control systems,and the consumer perspective on greywater reuse.Finally,benefits,such as the potential water and energy savings and sustainable future of greywater reuse in an urban context,are discussed. | Arjen Van de Walle Minseok Kim Md Kawser Alam Xiaofei Wang Di Wu Smruti Ranjan Dash Korneel Rabaey Jeonghwan Kim | 2023 | Environmental Science and Ecotechnology2023，，4： | 0 |
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