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Carbon Energy 2024年第3期6卷 36-52页

作者： Dae-Ho Son ha kyung Park Dae-Hwan Kim Jin-kyu Kang Shi-Joon Sung Dae-Kue hwang Jaebaek Lee Dong-Hwan Jeon Yunae Cho William Jo Taeseon Lee JunHo Kim Sang-Hoon Nam Kee-Jeong Yang Division of Energy Technology DGISTDaeguRepublic of Korea Research Center for Thin Film Solar Cells DGISTDaeguRepublic of Korea Department of Physics Ewha Womans UniversitySeoulRepublic of Korea Department of Physics Incheon National UniversityIncheonRepublic of Korea Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMassachusettsUSA

Cu2ZnSn(S,Se)4(CZTSSe)solar cells have resource distribution and economic *** main cause of their low efficiency is carrier loss resulting from recombination of photo-generated electron and *** overcome this,it is important to understand their electron-hole behavior *** determine the carrier separation characteristics,we measured the surface potential and the local current in terms of the absorber *** elemental variation in the intragrains(IGs)and at the grain boundaries(GBs)caused a band edge shift and bandgap(Eg)*** the absorber surface and subsurface,an upward Ec and Ev band bending structure was observed at the GBs,and the carrier separation was *** the absorber center,both upward Ec and Ev and downward Ec-upward Ev band bending structures were observed at the GBs,and the carrier separation was *** improve the carrier separation and suppress carrier recombination,an upward Ec and Ev band bending structure at the GBs is desirable.

关键词： carrier separation CZTSSe flexible solar cell local current surface potential

Hemophagocytic lymphohistiocytosis triggered by relapsing polychondritis:A case report

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World Journal of Orthopedics 2024年第8期15卷 813-819页

作者： Mi-Ran han Jeong-Hwan hwang Seungah Cha So-Yeon Jeon kyu Yun Jang Namsu Kim Chang-Hoon Lee Department of Internal Medicine Jeonbuk National University Medical SchoolJeonju 54907South Korea Department of Pathology Jeonbuk National University Medical SchoolJeonju 54907South Korea Department of Laboratory Medicine Jeonbuk National University Medical SchoolJeonju 54907South Korea

BACKGROUND Hemophagocytic lymphohistiocytosis(HLH)is a rare,life-threatening disorder caused by abnormal histiocytes and T cell *** adults,it is predominantly associated with infections,cancers,and autoimmune *** polychondritis(RP),another rare disease,is diagnosed based on symptoms without specific tests,featuring cartilage inflammation characterized by swelling,redness,and pain,rarely inducing *** SUMMARY A 74-year-old woman visited the emergency room with a fever of 38.6℃.Blood tests,cultures,and imaging were performed to evaluate *** showed increased fluorescent antinuclear antibody levels and mild cytopenia,with no other specific *** revealed lymph node enlargement was observed;however,biopsy results were *** re-evaluation of the physical exam,inflammatory signs suggestive of RP were observed in the ears and nose,prompting a tissue biopsy for ***,persistent fever accompanied by cytopenia prompted a bone marrow examination,revealing hemophagocytic *** finding no significant results in blood culture,viral markers,and tissue examination of enlarged lymph nodes,HLH was diagnosed by *** involved methylprednisolone followed by *** two months,bone marrow examination confirmed resolution of hemophagocytosis,with normalization of hyperferritinemia and *** Thorough physical examination enabled diagnosis and treatment of HLH trig gered by RP in patients presenting with fever of unknown origin.

关键词： Hemophagocytic lymphohistiocytosis Relapsing polychondritis Autoimmune disease Fever of unknown origin Steroid Case report

Apolipoprotein A-I binding protein-mediated neuroprotection in glaucomatous neuroinflammation and neurodegeneration

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Neural Regeneration Research 2025年第5期20卷 1414-1415页

作者： Sinwoo hwang Seunghwan Choi Soo-Ho Choi Keun-Young Kim Yury I.Miller Won-kyu Ju hamilton Glaucoma Center and Shiley Eye Institute The Viterbi Family Department of OphthalmologyUniversity of California San DiegoLa JollaCAUSA Department of Medicine University of California San DiegoLa JollaCAUSA National Center for Microscopy and Imaging Research Department of NeurosciencesUniversity of California San DiegoLa JollaCAUSA

Glaucoma is a multifactorial eye disorder that can cause vision loss and irreversible blindness,affecting individ uals aged 40 to 80 yea rs *** to the aging population,it is expected that the number of people affected by glaucoma will surpass 111 million by 2040 as the disease becomes more *** primarily contributes to optic nerve axon loss and the progressive degeneration of retinal ganglion cells (RGCs),subsequently leading to vision impairment.

关键词： irreversible pass primarily

Convolutional Neural Network-Based Regression for Predicting the Chloride Ion Diffusion Coefficient of Concrete

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Computers, Materials & Continua 2022年第3期70卷 5059-5071页

作者： Hyun kyu Shin ha Young Kim Sang Hyo Lee Architectural Engineering Hanyang University ERICAAnsan15588Korea Graduate School of Information Yonsei UniversitySeoul03722Korea Division of Smart Convergence Engineering Hanyang University ERICAAnsan15588Korea

The durability performance of reinforced concrete(RC)building structures is significantly affected by the corrosion of the steel reinforcement due to chloride penetration,thus,the chloride ion diffusion coefficient should be investigated through experiments or theoretical equations to assess the durability of an RC *** study aims to predict the chloride ion diffusion coefficient of concrete,a heterogeneous material.A convolutional neural network(CNN)-based regression model that learns the condition of the concrete surface through deep learning,is developed to efficiently obtain the chloride ion diffusion *** the model implementation to determine the chloride ion diffusion coefficient,concrete mixes with w/c ratios of 0.33,0.40,0.46,0.50,0.62,and 0.68,are cured for 28 days;subsequently,the surface image data of the specimens are ***,the proposed model predicts the chloride ion diffusion coefficient using the concrete surface image data and exhibits an error of approximately 1.5E−12 m^(2)/*** results suggest the applicability of proposed model to the field of facility maintenance for estimating the chloride ion diffusion coefficient of concrete using images.

关键词： Chloride ion diffusion coefficient convolutional neural network deep learning

Management of symptomatic cervical facet cyst with cervical interlaminar epidural block: A case report

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World Journal of Clinical Cases 2022年第32期10卷 11936-11941页

作者： Seong Min hwang Min kyu Lee Saeyoung Kim Department of Anesthesiology and Pain Medicine School of MedicineKyungpook National UniversityDaegu 41944South Korea

BACKGROUND Symptomatic cervical facet cysts are relatively rare compared to those in the lumbar *** cysts are usually located in the 7th cervical and 1st thoracic vertebral(C7/T1)area,and surgical excision is performed in most ***,facet cysts are associated with degenerative conditions,and elderly patients are often ineligible for surgical *** interlaminar epidural block has been used in patients with cervical radiating symptoms and achieved good ***,cervical interlaminar epidural block may be the first-choice treatment for symptomatic cervical facet *** SUMMARY A 70-year-old man complained of a tingling sensation in the left hand,focused on the 4th and 5th fingers,for 1 year,and posterior neck pain for over 5 *** patient’s numeric rating scale(NRS)score was 5/*** patient was diagnosed with symptomatic cervical facet cyst at the left C7/T1 facet *** cervical interlaminar epidural block at the C7/T1 level with 20 mg triamcinolone and 5 mL of 0.5%lidocaine was *** patient's symptoms improved immediately after the block,with an NRS score of 3 *** 3 mo,his left posterior neck pain and tingling along the left 8th cervical dermatome were relieved,with an NRS score of *** A cervical interlaminar epidural block is a good alternative for managing symptomatic cervical facet cysts.

关键词： Cervical vertebrae Cysts Epidural Injections Neck pain Therapeutics Zygapophyseal joint Case report

Effect of Al addition on corrosion behavior of high-purity Mg in terms of processing history

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Journal of Magnesium and Alloys 2023年第3期11卷 851-868页

作者： Sang kyu Woo Byeong-Chan Suh ha Sik Kim Chang Dong Yim Helmholtz Zentrum Hereon Max-Planck-Straße 1Geesthacht D-21502Germany Korea Institute of Materials Science 797 Changwondae-roSeongsan-guChangwonGyeongnam 51508Republic of Korea University of Science and Technology 217 Gajeong-roYuseong-guDaejeon 34113Republic of Korea

In this study,the effects of Al addition on the corrosion behavior of pure Mg with controlled impurity contents were systematically analyzed according to the processing *** results revealed that the corrosion behavior of high-purity Mg-Al alloys is strongly related to changes in the microstructure,including theβphase and Al-Mn or Al-Fe phases,and the protectiveness of the surface film according to the Al content and processing *** the as-cast alloys,the corrosion rate increased due to the increase ofβphase as the Al content increased,but in the as-extruded alloys,the corrosion rate,which was high due to intermetallic compounds caused by impurities in the low Al alloy,decreased as the Al content increased,and then increased *** is due to the combined effect of the increase of theβphase and decrease of the impurity effect,and the increase of the dissolved Al *** results suggest that it is necessary to analyze the effect of alloying elements on the corrosion behavior of pure Mg with information concerning the impurity content and processing history.

关键词： Mg High purity Mg-Al alloys Processing history Micro-galvanic Surface film

A Deep Learning Approach for Detecting Covid-19 Using the Chest X-Ray Images

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Computers, Materials & Continua 2023年第1期74卷 751-768页

作者： Fatemeh Sadeghi Omid Rostami Myung-kyu Yi Seong Oun hwang Department of Industrial Engineering Sharif University of TechnologyTehran14588-89694Iran Department of Industrial Engineering University of HoustonHoustonTX77204USA Department of Computer Engineering Gachon UniversitySeongnam13120Korea

Real-time detection of Covid-19 has definitely been the most widely-used world-wide classification problem since the start of the pandemic from 2020 until *** the meantime,airspace opacities spreads related to lung have been of the most challenging problems in this area.A common approach to do on that score has been using chest X-ray images to better diagnose positive Covid-19 *** to most other classification problems,machine learning-based approaches have been the first/most-used candidates in this *** schemes based on machine/deep learning have been proposed in recent years though increasing the performance and accuracy of the system has still remained an open *** this paper,we develop a novel deep learning architecture to better classify the Covid-19 X-ray *** do so,we first propose a novel multi-habitat migration artificial bee colony(MHMABC)algorithm to improve the exploitation/exploration of artificial bee colony(ABC)*** that,we optimally train the fully connected by using the proposed MHMABC algorithm to obtain better accuracy and convergence rate while reducing the execution *** experiment results on Covid-19 X-ray image dataset show that the proposed deep architecture has a great performance in different important optimization ***,it will be shown that the MHMABC algorithm outperforms the state-of-the-art algorithms by evaluating its performance using some wellknown benchmark datasets.

关键词： ChestX-ray image processing evolutionary deep learning covid-19

Nanoconfinement effect of nanoporous carbon electrodes for ionic liquid-based aluminum metal anode

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Journal of Energy Chemistry 2022年第11期31卷 121-127,I0005页

作者： Juhee Yoon Seongbak Moon Son ha Hyung-kyu Lim Hyoung-Joon Jin Young Soo Yun Program in Environmental and Polymer Engineering Inha UniversityIncheon 22212South Korea Department of Polymer Science and Engineering Inha UniversityIncheon 22212South Korea KU-KIST Graduate School of Converging Science and Technology Korea UniversitySeoul 02841South Korea Division of Chemical Engineering and Bioengineering Kangwon National UniversityGangwon-do 24341South Korea Department of Integrative Energy Engineering Korea UniversitySeoul 02841South Korea

Rechargeable aluminum batteries(RABs),which use earth-abundant and high-volumetric-capacity metal anodes(8040 m Ah cm-3),have great potential as next-generation power sources because they use cheaper resources to deliver higher energies,compared to current lithium ion ***,the mechanism of charge delivery in the newly developed,ionic liquid-based electrolytic system for RABs differs from that in conventional organic ***,targeted research efforts are required to address the large overpotentials and cycling decay encountered in the ionic liquid-based electrolytic *** this study,a nanoporous carbon(NPC)electrode with well-developed nanopores is used to develop a high-performance aluminum *** negatively charged nanopores can provide quenched dynamics of electrolyte molecules in the aluminum deposition process,resulting in an increased collision *** fast chemical equilibrium of anionic species induced by the facilitated anionic collisions leads to more favorable reduction reactions that form aluminum *** nanoconfinement effect causes separated nucleation and growth of aluminum nanoparticles in the multiple confined nanopores,leading to higher coulombic efficiencies and more stable cycling performance compared with macroporous carbon black and 2D stainless steel electrodes.

关键词： Nanoconfinement effect Nanoporous carbon Ionic liquid electrolyte Metal anode Aluminum batteries Multivalent batteries

Efficient Gauss-Seidel Precoding with Parallel Calculation in Massive MIMO Systems

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Computers, Materials & Continua 2022年第1期70卷 491-504页

作者： Hyun-Sun hwang Jae-Hyun Ro Chan-Yeob Park Young-Hwan You Hyoung-kyu Song Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Department of Computer Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

A number of requirements for 5G mobile communication are satisfied by adopting multiple input multiple output(MIMO)*** inter user interference(IUI)which is an inevitable problem in MIMO systems becomes controllable when the precoding scheme is *** this paper,the horizontal Gauss-Seidel(HGS)method is proposed as precoding scheme in massive MIMO *** massive MIMO systems,the exact inversion of channel matrix is impractical due to the severe computational ***,the conventionalGauss-Seidel(GS)method is used to approximate the inversion of channel *** GS has good performance by using previous calculation results as ***,the required time for obtaining the precoding symbols is too long due to the sequential process of ***,the HGS with parallel calculation is proposed in this paper to reduce the required *** rows of channel matrix are eliminated for parallel calculation *** addition,HGSuses the ordered channelmatrix to prevent performance degradation which is occurred by parallel *** HGS with proper number of parallelly computed symbols has better performance and reduced required time compared to the traditional GS.

关键词： Massive MIMO GS matrix inversion linear precoding

Improved MIMO Signal Detection Based on DNN in MIMO-OFDM System

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Computers, Materials & Continua 2022年第2期70卷 3625-3636页

作者： Jae-Hyun Ro Jong-Gyu ha Woon-Sang Lee Young-Hwan You Hyoung-kyu Song Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

This paper proposes the multiple-input multiple-output(MIMO)detection scheme by using the deep neural network(DNN)based ensemble machine learning for higher error performance in wireless communication *** the MIMO detection based on the ensemble machine learning,all learning models for the DNN are generated in offline and the detection is performed in online by using already learned *** the offline learning,the received signals and channel coefficients are set to input data,and the labels which correspond to transmit symbols are set to output *** the online learning,the perfectly learned models are used for signal detection where the models have fixed bias and *** performance improvement,the proposed scheme uses the majority vote and the maximum probability as the methods of the model combinations for obtaining diversity gains at the MIMO *** simulation results show that the proposed scheme has improved symbol error rate(SER)performance without additional receive antennas.

关键词： MIMO DNN ensemble machine learning ML