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Digital Vision Based Concrete Compressive Strength Evaluating Model Using Deep Convolutional Neural Network

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Computers, Materials & Continua 2019年第9期61卷 911-928页

作者： Hyun Kyu Shin Yong Han Ahn sang hyo lee Ha Young Kim Architectural Engineering Hanyang UniversityERICAAnsan-si15588Korea School of Architecture and Architectural Engineering Hanyang UniversityERICAAnsan-si15588Korea Division of Architecture and Civil Engineering Kangwon National UniversitySamcheok-si25913Korea Graduate School of Information Yonsei UniversitySeoul-si03722Korea.

Compressive strength of concrete is a significant factor to assess building structure health and ***,various methods have been developed to evaluate the compressive strength of concrete ***,previous methods have several challenges in costly,time-consuming,and *** address these drawbacks,this paper proposed a digital vision based concrete compressive strength evaluating model using deep convolutional neural network(DCNN).The proposed model presented an alternative approach to evaluating the concrete strength and contributed to improving efficiency and *** model was developed with 4,000 digital images and 61,996 images extracted from video recordings collected from concrete *** experimental results indicated a root mean square error(RMSE)value of 3.56(MPa),demonstrating a strong feasibility that the proposed model can be utilized to predict the concrete strength with digital images of their surfaces and advantages to overcome the previous *** experiment contributed to provide the basis that could be extended to future research with image analysis technique and artificial neural network in the diagnosis of concrete building structures.

关键词： Concrete compressive strength deep learning deep convolutional neural network image-based evaluation building maintenance and management

Defect-Detection Model for Underground Parking Lots Using Image Object-Detection Method

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Computers, Materials & Continua 2021年第3期66卷 2493-2507页

作者： Hyun Kyu Shin Si Woon lee Goo Pyo Hong lee Sael sang hyo lee Ha Young Kim Architectural Engineering Hanyang UniversityERICAAnsan15588Korea Department of Artificial Intelligence Ajou UniversitySuwon16499Korea Division of Architecture and Civil Engineering Kangwon National UniversitySamcheok25913Korea Division of Smart Convergence Engineering Hanyang UniversityERICAAnsan15588Korea Graduate School of Information Yonsei UniversitySeoul03722Korea

The demand for defect diagnoses is gradually gaining ground owing to the growing necessity to implement safe inspection methods to ensure the durability and quality of ***,conventional manpower-based inspection methods not only incur considerable cost and time,but also cause frequent disputes regarding defects owing to poor ***,the demand for an effective and efficient defect-diagnosis model for concrete structures is imminent,as the reduction in maintenance costs is significant from a long-term ***,this paper proposes a deep learning-based image objectidentification method to detect the defects of paint peeling,leakage peeling,and leakage traces that mostly occur in underground parking lots made of concrete *** deep learning-based object-detection method can replace conventional visual inspection methods.A faster region-based convolutional neural network(R-CNN)model was used with a training dataset of 6,281 images that utilized a region proposal network to objectively localize the regions of interest and detect the surface *** defects were classified according to their type,and the learning of each exclusive model was ensured through test sets obtained from real underground parking *** a result,average precision scores of 37.76%,36.42%,and 61.29%were obtained for paint peeling,leakage peeling,and leakage trace defects,***,this study verified the performance of the faster RCNN-based defect-detection algorithm along with its applicability to underground parking lots.

关键词： Faster R-CNN deep learning defect detection concrete structures

Development of large acceptance multi-purpose spectrometer in Korea for symmetry energy

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Nuclear Science and Techniques 2018年第12期29卷 6-14页

作者： Byungsik Hong Jung Keun Ahn Gyeonghwan Bak Jamin Jo Minho Kim Eun Joo Kim Young Jin Kim Young Jun Kim Minjung Kweon Hanseul lee hyo sang lee Jong-Won lee Jung Woo lee Kyong Sei lee Byul Moon Dong Ho Moon Benard Mulilo Jaebeom Park Min sang Ryu Hyunha Shim LAMPS Collaboration Department of Physics Korea University Seoul 02841Republic of Korea Department of Physics Chonnam National UniversityGwangju 61186 Republic of Korea Division of Science Education Chonbuk National UniversityJeonju 54896 Republic of Korea Rare Isotope Science Project Institute for Basic ScienceDaejeon 34047 Republic of Korea Department of Physics Inha University Incheon 22212Republic of Korea

The Rare Isotope Accelerator complex for ONline experiments(RAON) is a new radioactive ion beam accelerator facility under construction in Korea. The large acceptance multi-purpose spectrometer(LAMPS) is one of the experimental devices for nuclear physics at RAON. It focuses on the nuclear symmetry energy at supra-saturation densities. The LAMPS Collaboration has developed and constructed various detector elements, including a time projection chamber(TPC) and a forward neutron detector array. From the positron beam test, the drift velocity of the secondary electrons in the TPC is 5:3±0:2 cm/ls with P10 gas mixture, and the position resolution for pads with dimensions of 4×15 mm^2 is in the range of$ 0.6–0.8 mm, depending on the beam position. From the neutron beam test, the energy resolution of the prototype neutron detector module is determined to be 3.4%, and theposition resolution is estimated to be better than 5.28 *** present, the construction of the LAMPS neutron detector system is in progress.

关键词：分光计精力用途朝鲜对称开发核物理学合作发展

Optimal three-dimensional impact time guidance with seeker’s field-of-view constraint

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Chinese Journal of Aeronautics 2021年第2期34卷 240-251页

作者： Shaoming HE Chang-Hun lee hyo-sang SHIN Antonios TSOURDOS School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Department of Aerospace Engineering Korea Advanced Institute of Science and TechnologyDaejeon 34141Republic of Korea School of Aerospace Transport and ManufacturingCranfield UniversityCranfiehMK43 OALUnited Kingdom

This paper proposes a new three-dimensional optimal guidance law for impact time control with seeker’s Field-of-View(FOV) constraint to intercept a stationary target. The proposed guidance law is devised in conjunction with the concept of biased Proportional Navigation Guidance(PNG). The guidance law developed leverages a nonlinear function to ensure the boundedness of velocity lead angle to cater to the seeker’s FOV limit. It is proven that the impact time error is nullified in a finite-time under the proposed method. Additionally, the optimality of the biased command is theoretically analyzed. Numerical simulations confirm the superiority of the proposed method and validate the analytic findings.

关键词： Applied optimal control Field-of-view constraint Impact time control Missile guidance Optimal error dynamics

Site-selective oral delivery of therapeutic antibodies to the inflamed colon via a folic acid-grafted organic/inorganic hy brid nanocomposite system

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Acta Pharmaceutica Sinica B 2022年第11期12卷 4249-4261页

作者： sang Hoon lee Jae Geun Song hyo-Kyung Han College of Pharmacy Dongguk University-SeoulGoyang 10326South Korea

This study aimed to develop a pH-responsive folic acid-grafted organic/inorganic hybrid nanocomposite system for site-selective oral delivery of therapeutic antibodies. A folic acid-grafted aminoclay(FA-AC) was prepared via an in situ sol-gel method. Then, a drug-loaded nanocomplex was prepared via the electrostatic interaction of FA-AC with infliximab(IFX), a model antibody, and coated with Eudragit? S100(EFA-AC-IFX). FA-AC exhibited favorable profiles as a drug carrier including low cytotoxicity, good target selectivity, and capability to form a nanocomplex with negatively charged macromolecules. A pH-responsive FA-AC-based nanocomplex containing IFX(EFA-AC-IFX) was also obtained in a narrow size distribution with high entrapment efficiency(>87%). The conformational stability of IFX entrapped in EFA-AC-IFX was well maintained in the presence of proteolytic enzymes. EFA-ACIFX exhibited pH-dependent drug release, minimizing premature drug release in gastric conditions and the upper intestine. Accordingly, oral administration of EFA-AC-IFX to colitis-induced mice was effective in alleviating the progression of ulcerative colitis, while oral IFX solution had no efficacy. These results suggest that a pH-responsive FA-AC-based nanocomposite system can be a new platform for the site-selective oral delivery of therapeutic antibodies.

关键词： Infliximab Aminoclay Colonic delivery:TNF-x Infammation Folate rceptor Anibody Nanocomposite

^18F-FDG PET/CT显像能否鉴别诊断特发性肺纤维化患者的孤立性肺结节?

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中华核医学与分子影像杂志 2018年第12期38卷 840-840页

作者：唐军(译) Suk Hyun lee Changhwan Sung hyo sang lee Hee-young Yoon Soo-Jong Kim Jungsu S.Oh Jin Woo Song Mi Young Kim Jin-Sook Ryu 上海交通大学医学院附属苏州九龙医院核医学科 215021 Department of Nuclear Medicine Asan Medical Center University of Ulsan College of MedicineSeoul South Korea

目的特发性肺纤维化(IPF)患者的肺癌发生率高,患者肺功能差,易发生气胸,因此对CT发现的孤立性肺结节(SPN)不宜采用侵入性诊断方法,否则可能导致严重的不良后果。^18F-脱氧葡萄糖(FDG)PET/CT可用于非IPF患者SPN的良恶性鉴别,但在IPF患者... 详细信息

目的特发性肺纤维化(IPF)患者的肺癌发生率高,患者肺功能差,易发生气胸,因此对CT发现的孤立性肺结节(SPN)不宜采用侵入性诊断方法,否则可能导致严重的不良后果。^18F-脱氧葡萄糖(FDG)PET/CT可用于非IPF患者SPN的良恶性鉴别,但在IPF患者中的诊断准确性尚无研究。因此该研究拟调查^18F-FDGPET/CT是否能鉴别诊断IPF患者的SPN。方法回顾性分析来自该院的55例IPF患者[男54例、女1例,年龄(67.8±7.6)岁],患者SPN大小为8~30(18.5±5.7)mm,所有患者在2004年4月至2016年3月间行胸部CT和^18F-FDGPET/CT显像。对SPN的^18F-FDG摄取行视觉分析和半定量分析,图像结果与最终病理诊断(n=52)或影像学随访(n=3)结果进行比较。结果最终诊断结果表明,41个(75%)SPNs为恶性(21个鳞状细胞癌、9个腺癌、5个小细胞癌、4个混合类型癌、1个大细胞神经内分泌癌和1个肉瘤样癌),14个(25%)为良性。视觉分析PET/CT图像诊断SPN为恶性病变的灵敏度、特异性、阳性预测值(PPV)和阴性预测值(NPV)分别为98%、86%、95%和92%。使用最大标准摄取值(SUVmax)为2.0行半定量分析诊断的灵敏度、特异性、PPV和NPV分别为95%、93%、98%和87%。结论^18F-FDGPET/CT可用于IPF患者SPN的良恶性鉴别,如其用于非IPF患者一样。

关键词： ^18F-FDG 正电子发射断层显像术肺癌孤立性肺结节特发性肺纤维化

PGLYRP1 protein as a novel mediator of cellular dialogue in neuroinflammation

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Neural Regeneration Research 2025年第7期20卷 1993-1994页

作者： Anup Bhusal Won-Ha lee Kyoungho Suk Department of Pharmacology School of MedicineKyungpook National UniversityDaeguRepublic of Korea BK21 Plus KNU Biomedical Convergence Program Department of Biomedical ScienceSchool of MedicineKyungpook National UniversityDaeguRepublic of Korea School of Life Sciences BK21 plus KNU Creative BioResearch GroupKyungpook National UniversityDaeguRepublic of Korea Brain Science and Engineering Institute Kyungpook National UniversityDaeguRepublic of Korea

Neuroinflammation has been identified as a crucial element in several neurological disorders. Glial cells play a critical role in directing neuroinflammation, both in deleterious and beneficial ways.

关键词： inflammation considerably

Single-cell and spatial omics:exploring hypothalamic heterogeneity

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Neural Regeneration Research 2025年第6期20卷 1525-1540页

作者： Muhammad Junaid Eun Jeong lee Su Bin Lim Department of Biochemistry&Molecular Biology Ajou University School of MedicineSuwonSouth Korea Department of Biomedical Sciences Graduate School of Ajou UniversitySuwonSouth Korea Department of Brain Science Ajou University School of MedicineSuwonSouth Korea

Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.

关键词： cellular diversity hypothalamus multi-omics single-cell transcriptomics spatial transcriptomics

Optimization of an Artificial Intelligence Database and Camera Installation for Recognition of Risky Passenger Behavior in Railway Vehicles

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Computers, Materials & Continua 2025年第1期82卷 1277-1293页

作者： Min-kyeong Kim Yeong Geol lee Won-Hee Park Su-hwan Yun Tae-Soon Kwon Duckhee lee Railroad Test&Certification Division Korea Railroad Research Institute(KRRI)Cheoldo BangmulgwanroUiwang-si16105Republic of Korea Railroad Safety Division Korea Railroad Research Institute(KRRI)Cheoldo BangmulgwanroUiwang-si16105Republic of Korea

Urban railways are vital means of public transportation in *** than 30%of metropolitan residents use the railways,and this proportion is expected to *** enhance safety,the government has mandated the installation of closed-circuit televisions in all carriages by ***,cameras still monitored *** address this limitation,we developed a dataset of risk factors and a smart detection system that enables an immediate response to any abnormal behavior and intensive monitoring *** created an innovative learning dataset that takes into account seven unique risk factors specific to Korean railway *** data collection was conducted across the Shinbundang Line of the Incheon Transportation Corporation,and the Ui-Shinseol *** observed several behavioral characteristics and assigned unique annotations to *** also considered carriage *** performance was evaluated by camera placement and *** the camera installation plan was *** dataset will find immediate applications in domestic railway *** artificial intelligence algorithms will be verified shortly.

关键词： AI railway vehicle risk factor smart detection AI training data