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| 1 | A Closure Study of Aerosol Hygroscopic Growth Factor during the 2006 Pearl River Delta Campaign显示文摘Measurements of aerosol physical, chemical and optical parameters were carried out in Guangzhou, China from 1 July to 31 July 2006 during the Pearl River Delta Campaign. The dry aerosol scattering coefficient was measured using an integrating nephelometer and the aerosol scattering coefficient for wet conditions was determined by subtracting the sum of the aerosol absorption coefficient, gas scattering coefficient and gas absorption coefficient from the atmospheric extinction coefficient. Following this, the aerosol hygroscopic growth factor, f(RH), was calculated as the ratio of wet and dry aerosol scattering coefficients. Measurements of size-resolved chemical composition, relative humidity (RH), and published functional relationships between particle chemical composition and water uptake were likewise used to find the aerosol scattering coe?cients in wet and dry conditions using Mie theory for internally- or externally-mixed particle species [(NH_4)_2SO_4, NH_4NO_3, NaCl, POM, EC and residue]. Closure was obtained by comparing the measured f(RH) values from the nephelometer and other in situ optical instruments with those computed from chemical composition and thermodynamics. Results show that the model can represent the observed f(RH) and is appropriate for use as a component in other higher-order models. | 刘新罡 张远航 温梦婷 王京丽 Jinsang JUNG 张士煜 胡敏 曾立民 Young Joon KIM | 2010 | Advances in Atmospheric Sciences2010，27，4： | 3 |
| 2 | Measurement of Atmospheric Formaldehyde and Monoaromatic Hydrocarbons using Differential Optical Absorption Spectroscopy during Winter and Summer Intensive Periods in Seoul, Korea显示文摘 | Chulkyu Lee Young Joon Kim Sang-Bum Hong Hanlim Lee Jinsang Jung Yeo-Jin Choi Jungeun Park Ki-Hyun Kim Jai-Hoon Lee Ki-Joon Chun Hyun-Ho Kim | 2005 | Water Air and Soil Pollution (-)2005，，1： | 1 |
| 3 | Aerosol chemistry and the effect of aerosol water content on visibility impairment and radiative forcing in Guangzhou during the 2006 Pearl River Delta campaign显示文摘 | Jinsang Jung Hanlim Lee Young J. Kim Xingang Liu Yuanhang Zhang Jianwei Gu Shaojia Fan | 2009 | Journal of Environmental Management2009，，11： | 1 |
| 4 | Multiple feature clustering for image sequence segmentation显示文摘 | Jinsang Kim Tom Chen | 2001 | Pattern Recognition Letters2001，，11： | 1 |
| 5 | Adenovirusmediated interleukin-12 gene transfer combined with cytosine deaminase followed by 5-fluorocytosine treatment exerts potent antitumor activity in Renca tumor-bearing mice显示文摘 | Kyung-Sun Hwang Won-Kyung Cho Jinsang Yoo etal | 2005 | BMC Cancer2005，5，： | 1 |
| 6 | Research on the hygroscopic properties of aerosols by measurement and modeling during CAREBeijing-2006显示文摘 | LIU Xingang ZHANG Yuanhang JUNG Jinsang | 2009 | Journal of Geophysical Research2009，114，2： | 1 |
| 7 | A Poly(p-phenyleneethynylene) with a highly emissive aggregated phase显示文摘 | Robert D Jinsang K Michelle R | 2000 | J Am Ghem Soc2000，122，： | 1 |
| 8 | Multiple Feature Clustering for Image Sequence Segmentation 显示文摘 | Jinsang K Tom C | 2001 | Pattern Recognition Letter2001，22，： | 1 |
| 9 | Influences of relative humidity and particle chemical composition on aerosol scattering properties during the 2006 PRD campaign显示文摘 | Xingang Liu Yafang Cheng Yuanhang Zhang Jinsang Jung Nobuo Sugimoto Shih-Yu Chang Young J. Kim Shaojia Fan Limin Zeng | 2007 | Atmospheric Environment2007，，7： | 1 |
| 10 | Aerosol chemistry and the effect of aerosol water content on visibility impairment and radiative forcing in Guangzhou during the 2006 Pearl River Delta campaign显示文摘 | Jinsang Jung Hanlim Lee Young J. Kim Xingang Liu Yuanhang Zhang Jianwei Gu Shaojia Fan | 2009 | Journal of Environmental Management2009，，11： | 1 |
| 11 | Chicken Swarm Optimization with Deep Learning Based Packaged Rooftop Units Fault Diagnosis Model显示文摘Rooftop units(RTUs)were commonly employed in small commercial buildings that represent that can frequently do not take the higher level maintenance that chillers receive.Fault detection and diagnosis(FDD)tools can be employed for RTU methods to ensure essential faults are addressed promptly.In this aspect,this article presents an Optimal Deep Belief Network based Fault Detection and Classification on Packaged Rooftop Units(ODBNFDC-PRTU)model.The ODBNFDC-PRTU technique considers fault diagnosis as amulti-class classification problem and is handled usingDL models.For fault diagnosis in RTUs,the ODBNFDC-PRTU model exploits the deep belief network(DBN)classification model,which identifies seven distinct types of faults.At the same time,the chicken swarm optimization(CSO)algorithm-based hyperparameter tuning technique is utilized for resolving the trial and error hyperparameter selection process,showing the novelty of the work.To illustrate the enhanced performance of the ODBNFDC-PRTU algorithm,a comprehensive set of simulations are applied.The comparison study described the improvement of the ODBNFDC-PRTU method over other recent FDD algorithms with maximum accuracy of 99.30%and TPR of 93.09%. | G.Anitha N.Supriya Fayadh Alenezi E.Laxmi Lydia Gyanendra Prasad Joshi Jinsang You | 2023 | Computer Systems Science & Engineering2023，47，10： | 0 |
| 12 | A Method for Detecting Non-Mask Wearers Based on Regression Analysis显示文摘A novel practical and universal method of mask-wearing detection has been proposed to prevent viral respiratory infections.The proposed method quickly and accurately detects mask and facial regions using welltrained You Only Look Once(YOLO)detector,then applies image coordinates of the detected bounding box(bbox).First,the data that is used to train our model is collected under various circumstances such as light disturbances,distances,time variations,and different climate conditions.It also contains various mask types to detect in general and universal application of the model.To detect mask-wearing status,it is important to detect facial and mask region accurately and we created our own dataset by taking picture of images.Furthermore,the Convolutional Neural Network(CNN)model is trained with both our own dataset and open dataset to detect under heavy foot-traffic(Indoors).To make the model robust and reliable in various environment and situations,we collected various sample data in different distances.And through the experiment,we found out that there is a particular gradient according to the mask-wearing status.The proposed method searches the point where the distance between the gradient for each state and the coordinate information of the detected object is the minimum.Then it carry out the classification of mask-wearing status of detected object.Lastly,we defined and classified three different mask-wearing states according to the mask’s position(With mask,Wear a mask around chin and Without mask).The gradient according to the mask-wearing status,is analyzed through linear regression.The regression interpretation is based on coordinate information of mask-wearing status and the sample data collected in simulated environment that considering distances between objects and the camera in the World Coordinate System.Through the experiments,we found out that linear regression analysis is more suitable than logistic regression analysis for classification of people wearing masks in general-purpose environments.And the proposed method,through linear regression analysis,classifies in a very concise way than the others. | Dokyung Hwang Hyeonmin Ro Naejoung Kwak Jinsang Hwang Dongju Kim | 2022 | Computers, Materials & Continua2022，，9： | 0 |
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