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A feasible route to produce 1.1 GPa ferritic-based low-Mn lightweight steels with ductility of 47%

Journal of Materials Science & Technology 2022年第22期117卷 225-237页

作者： Kwang Kyu Ko Hyo Ju Bae Eun Hye Park hyeon-uk jeong Hyoung Seok Park Jae Seok jeong Jung Gi Kim Hyokyung Sung Nokeun Park Jae Bok Seol Department of Materials Engineering and Convergence Technology Center for K-metalGyeongsang National University(GNU)Jinju 52828South Korea School of Materials Science and Engineering Yeungnam UniversityGyeongbuk 38541South Korea Materials Research Team R&D Hyundai MobisYongin 16891South Korea Materials Technology Development Team Doosan Heavy Industries&ConstructionChangwon 51711South Korea

High- and medium-Mn (H/M-Mn) base lightweight steels are a class of ultrastrong structural materials with high ductility compared to their low-Mn counterparts with low strength and poor ***, producing these H/M-Mn materials requires the advanced or high-tech manufacturing techniques, which can unavoidably provoke labor and cost concerns. Herein, we have developed a facilestrategy that circumvents the strength–ductility trade-off in low-Mn ferritic lightweight steels, by employing low-temperature tempering-induced partitioning (LTP). This LTP treatment affords a typical Fe-2.8Mn-5.7Al-0.3C (wt.%) steel with a heterogeneous size-distribution of metastable austenite embeddedin a ferrite matrix for partitioning more carbon into smaller austenite grains than into the larger austenite ones. This size-dependent partitioning results in slip plane spacing modification and lattice strain,which act through dislocation engineering. We ascribe the simultaneous improvement in strength andtotal elongation to both the size-dependent dislocation movement in austenite grains and the controlleddeformation-induced martensitic transformation. The low-carbon-partitioned large austenite grains increase the strength and ductility as a consequence of the combined martensitic transformation andhigh dislocation density-induced hardening and by interface strengthening. Additionally, high-carbonpartitioned small austenite grains enhance the strength and ductility by planar dislocation glide (inthe low strain regime) and by cross-slipping and delayed martensitic transformation (in the high strainregime). The concept of size-dependent dislocation engineering may provide different pathways for developing a wide range of heterogeneous-structured low-Mn lightweight steels, suggesting that LTP maybe desirable for broad industrial applications at an economic cost.

关键词： Low-Mn lightweight steel Carbon partitioning Metastable austenite Dislocation movement

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Anomaly Detection Using Data Rate of Change on Medical Data

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Computers, Materials & Continua 2024年第9期80卷 3903-3916页

作者： Kwang-Cheol Rim Young-Min Yoon Sung-uk Kim jeong-In Kim AI Convergence Research Institute Chosun UniversityGwangju61452Republic of Korea Interdisciplinary Program of Architectural Studies Chonnam UniversityGwangju61186Republic of Korea AINTCHAIN SOFT Co. Ltd.Mokpo-si58750Republic of Korea BK21 Human Resources Development Project Group Chosun UniversityGwangju61452Republic of Korea

The identification and mitigation of anomaly data,characterized by deviations from normal patterns or singularities,stand as critical endeavors in modern technological landscapes,spanning domains such as Non-Fungible Tokens(NFTs),cyber-security,and the burgeoning *** paper presents a novel proposal aimed at refining anomaly detection methodologies,with a particular focus on continuous data *** essence of the proposed approach lies in analyzing the rate of change within such data streams,leveraging this dynamic aspect to discern anomalies with heightened precision and *** empirical evaluation,our method demonstrates a marked improvement over existing techniques,showcasing more nuanced and sophisticated result ***,we envision a trajectory of continuous research and development,wherein iterative refinement and supplementation will tailor our approach to various anomaly detection scenarios,ensuring adaptability and robustness in real-world applications.

关键词： Anomaly data anomaly detection medical anomaly data cyber security rate of change

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Enhancement of porcine in vitro embryonic development through luteolin‑mediated activation of the Nrf2/Keap1 signaling pathway

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Journal of Animal Science and Biotechnology 2024年第2期15卷 600-613页

作者： Se-Been Jeon Pil-Soo jeong Min Ju Kim Hyo-Gu Kang Bong-Seok Song Sun-uk Kim Seong-Keun Cho Bo-Woong Sim Futuristic Animal Resource&Research Center(FARRC) Korea Research Institute of Bioscience and Biotechnology(KRIBB)Cheongju 28116Republic of Korea Department of Animal Science College of Natural Resources&Life SciencePusan National UniversityMiryang 50463Republic of Korea Department of Animal Science and Biotechnology College of Agriculture and Life ScienceChungnam National UniversityDaejeon 34134Republic of Korea Department of Functional Genomics University of Science and TechnologyDaejeon 34113Republic of Korea Department of Animal Science Life and Industry Convergence Research Institute(RICRI)College of Natural Resources&Life SciencePusan National UniversityMiryang 50463Republic of Korea

Background Oxidative stress,caused by an imbalance in the production and elimination of intracellular reactive oxygen species(ROS),has been recognized for its detrimental effects on mammalian embryonic ***(Lut)has been documented for its protective effects against oxidative stress in various ***,its specific role in embryonic development remains *** study aims to investigate the influence of Lut on porcine embryonic development and to elucidate the underlying *** After undergoing parthenogenetic activation(PA)or in vitro fertilization,embryos supplemented with 0.5μmol/L Lut displayed a significant enhancement in cleavage and blastocyst formation rates,with an increase in total cell numbers and a decrease in the apoptosis rate compared to the *** on D2 and D6 revealed that embryos with Lut supplementation had lower ROS levels and higher glutathione levels compared to the ***,Lut supplementation significantly augmented mitochondrial content and membrane ***,activation of the Nrf2/Keap1 signaling pathway was observed in embryos supplemented with Lut,leading to the upregulation of antioxidant-related gene transcription *** further validate the relationship between the Nrf2/Keap1 signaling pathway and effects of Lut in porcine embryonic development,we cultured PA embryos in a medium supplemented with brusatol,with or without the inclusion of *** positive effects of Lut on developmental competence were negated by brusatol *** Our findings indicate that Lut-mediated activation of the Nrf2/Keap1 signaling pathway contributes to the enhanced production of porcine embryos with high developmental competence,and offers insight into the mechanisms regulating early embryonic development.

关键词： Luteolin Mitochondrial function Nrf2/Keap1 signaling pathway Oxidative stress Porcine embryo development

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Perspectives of laparoscopic surgery for gastric cancer

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Chinese Journal of Cancer Research 2022年第5期34卷 533-538页

作者： jeong Ho Song Sang-uk Han Department of Surgery Ajou University School of MedicineSuwon 16499Republic of Korea

Gastrectomy is the main treatment option for gastric cancer patients. Laparoscopic approach has become popular as an alternative to open method during the last decades, and clinical trials have revealed safety and feasibility in the short-and long-term outcomes of laparoscopic gastrectomy. The aim of this review is to summarize the results of prospective clinical trials and propose future perspectives for laparoscopic gastrectomy.

关键词： Gastric cancer laparoscopic gastrectomy minimally-invasive surgery

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Self-supported VO_(2)on polydopamine-derived pyroprotein-based fibers for ultrastable and flexible aqueous zinc-ion batteries

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Carbon Energy 2024年第7期6卷 1-13页

作者： jeong Seok Yeon Sul Ki Park Shinik Kim Santosh VMohite Won Il Kim Gun Jang Hyun-Seok Jang Jiyoung Bae Sang Moon Lee Won GHong Byung Hoon Kim Yeonho Kim Ho Seok Park School of Chemical Engineering College of EngineeringSungkyunkwan UniversityGyeonggi-doRepublic of Korea Department of Engineering University of CambridgeCambridgeUK Department of Applied Chemistry Konkuk UniversityChungjuRepublic of Korea Department of Chemistry Ulsan National Institute of Science and Technology(UNIST)College of Natural SciencesUlsanRepublic of Korea Department of Physics Incheon National UniversityIncheonRepublic of Korea Intelligent Sensor Convergence Research Center Incheon National UniversityIncheonRepublic of Korea Institute of Basic Science Incheon National UniversityIncheonRepublic of Korea Division of Material Analysis and Research Korea Basic Science InstituteDaejeonRepublic of Korea

A conventional electrode composite for rechargeable zinc-ion batteries(ZIBs)includes a binder for strong adhesion between the electrode material and the current ***,the introduction of a binder leads to electrochemical inactivity and low electrical conductivity,resulting in the decay of the capacity and a low rate *** present a binder-and conducting agent-free VO_(2)composite electrode using in situ polymerization of dopamine on a flexible current collector of pyroprotein-based *** as-fabricated composite electrode was used as a substrate for the direct growth of VO_(2)as a self-supported form on polydopamine-derived pyroprotein-based fibers(pp-fibers@VO_(2)(B)).It has a high conductivity and flexible nature as a current collector and moderate binding without conventional binders and conducting agents for the VO_(2)(B)*** addition,their electrochemical mechanism was *** energy storage is induced by Zn^(2+)/H^(+)coinsertion during discharging,which can be confirmed by the lattice expansion,the formation of by-products including Zn_(x)(OTf)_(y)(OH)_(2x−y)·nH_(2)O,and the reduction of V^(4+)to V^(3+).Furthermore,the assembled Zn//pp-fibers@VO_(2)(B)pouch cells have excellent flexibility and stable electrochemical performance under various bending states,showing application possibilities for portable and wearable power sources.

关键词： aqueous battery binder free conducting agent‐free flexible electrode zinc‐ion battery

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Semi-Supervised Learning with Generative Adversarial Networks on Digital Signal Modulation Classification

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Computers, Materials & Continua 2018年第5期55卷 243-254页

作者： Ya Tu Yun Lin Jin Wang jeong-uk Kim College of Information and Communication Engineering Harbin Engineering UniversityHarbin 150001China School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha 410114China School of Information Engineering Yangzhou UniversityYangzhou 225009China Department of Energy Grid Sangmyung UniversitySeoulKorea

Deep Learning(DL)is such a powerful tool that we have seen tremendous success in areas such as Computer Vision,Speech Recognition,and Natural Language *** Automated Modulation Classification(AMC)is an important part in Cognitive Radio Networks,we try to explore its potential in solving signal modulation recognition *** cannot be overlooked that DL model is a complex model,thus making them prone to *** model requires many training data to combat with over-fitting,but adding high quality labels to training data manually is not always cheap and accessible,especially in real-time system,which may counter unprecedented data in ***-supervised Learning is a way to exploit unlabeled data effectively to reduce over-fitting in *** this paper,we extend Generative Adversarial Networks(GANs)to the semi-supervised learning will show it is a method can be used to create a more dataefficient classifier.

关键词： Deep Learning automated modulation classification semi-supervised learning generative adversarial networks

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Improved VGG Model for Road Traffic Sign Recognition

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Computers, Materials & Continua 2018年第10期57卷 11-24页

作者： Shuren Zhou Wenlong Liang Junguo Li jeong-uk Kim Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science&TechnologyChangsha410114China School of Computer&Communication Engineering Changsha University of Science&TechnologyChangsha410114China Department of Energy Grid Sangmyung UniversitySeoul110743Korea

Road traffic sign recognition is an important task in intelligent transportation *** neural networks(CNNs)have achieved a breakthrough in computer vision tasks and made great success in traffic sign *** this paper,it presents a road traffic sign recognition algorithm based on a convolutional neural *** natural scenes,traffic signs are disturbed by factors such as illumination,occlusion,missing and deformation,and the accuracy of recognition decreases,this paper proposes a model called Improved VGG(IVGG)inspired by VGG *** IVGG model includes 9 layers,compared with the original VGG model,it is added max-pooling operation and dropout operation after multiple convolutional layers,to catch the main features and save the training *** paper proposes the method which adds dropout and Batch Normalization(BN)operations after each fully-connected layer,to further accelerate the model convergence,and then it can get better classification *** uses the German Traffic Sign Recognition Benchmark(GTSRB)dataset in the *** IVGG model enhances the recognition rate of traffic signs and robustness by using the data augmentation and transfer learning,and the spent time is also reduced greatly.

关键词： Intelligent transportation traffic sign deep learning GTSRB data augmentation

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Abnormal Behavior Detection Using Deep-Learning-Based Video Data Structuring

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Intelligent Automation & Soft Computing 2023年第8期37卷 2371-2386页

作者： Min-jeong Kim Byeong-uk Jeon Hyun Yoo Kyungyong Chung Department of Computer Science Kyonggi UniversitySuwon-si16227Gyeonggi-doKorea Contents Convergence Software Research Institute Kyonggi UniversitySuwon-si16227Gyeonggi-doKorea Division of AI Computer Science and Engineering Kyonggi UniversitySuwon-si16227Gyeonggi-doKorea

With the increasing number of digital devices generating a vast amount of video data,the recognition of abnormal image patterns has become more ***,it is necessary to develop a method that achieves this task using object and behavior information within video *** methods for detecting abnormal behaviors only focus on simple motions,therefore they cannot determine the overall behavior occurring throughout a *** this study,an abnormal behavior detection method that uses deep learning(DL)-based video-data structuring is *** and motions are first extracted from continuous images by combining existing DL-based image analysis *** weight of the continuous data pattern is then analyzed through data structuring to classify the overall *** performance of the proposed method was evaluated using varying parameter settings,such as the size of the action clip and interval between action *** model achieved an accuracy of 0.9817,indicating excellent ***,we conclude that the proposed data structuring method is useful in detecting and classifying abnormal behaviors.

关键词： Deep learning object detection abnormal behavior recognition classification data structuring

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Usage patterns of emergency medical services in Korea: analysis of patient flow

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Chinese Medical Journal 2019年第3期132卷 259-268页

作者： Mira Oh Jae hyeon Lee Byoung uk Jeon Tae Oh jeong Tag Heo Sungmin Lee National Emergency Medical Center of National Medical Center Joong-guSeoulRepublic of Korea Department of Emergency medicine Chonbuk National University Medical SchoolDeokjin-guJeonjuRepublic of Korea Department of Emergency Medicine Chonnam National University Medical SchoolDong-guGwangjuRepublic of Korea

Background:This study used the National Emergency Department Information System (NEDIS) data to analyze the flow of emergency and critical emergency patients and to identify the patterns of emergency medical service usage in ***:The relevance index (RI) and commitment index (CI) were calculated from the 2016 NEDIS data. In this study, the number of clusters was determined using NbClust, and cluster analysis was used to analyze the usage patterns of emergency and critical emergency ***:The RI and CI were calculated using 8,389,766 cases of 214 districts. The results of the RI and CI suggested that there were 3 types of clusters among the emergency patients. In Cluster 1, 54 districts (25.2%) had low RI and high CI, and it was of outflow type. Cluster 2 was categorized as the influx-type in 58 districts (27.1%) irrespective of RI and low CI. Cluster 3 was categorized as the self-sufficient type found in 102 districts (47.7%), with high RI and high CI. The cluster analysis of the critical emergency patients was divided into 2 types. Cluster 1 was categorized as outflow type with high CI found in 129 districts (60.3%), while Cluster 2 was categorized as inflow type with low CI found in 85 districts (39.7%).Conclusions:This study elucidates the regional status of usage patterns of emergency and critical emergency patients in Korea. This study might serve as a basis for the establishment and selection of emergency medical service areas and vulnerable emergency medical service areas.

关键词： Clustering Commitment Index Emergency Department National Emergency Department Information System Relevance Index

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A TMA-Seq2seq Network for Multi-Factor Time Series Sea Surface Temperature Prediction

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Computers, Materials & Continua 2022年第10期73卷 51-67页

作者： Qi He Wenlong Li Zengzhou Hao Guohua Liu Dongmei Huang Wei Song Huifang Xu Fayez Alqahtani jeong-uk Kim Department of Information Technology Shanghai Ocean UniversityShanghai201306China State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou310012China College of Computer Dong Hua UniversityShanghai200051China College of Information Technology Shanghai Jian Qiao UniversityShanghai201306China Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh 12372Saudi Arabia Department of Electrical Engineering Sangmyung UniversitySouth KoreaKorea

Sea surface temperature (SST) is closely related to global climatechange, ocean ecosystem, and ocean disaster. Accurate prediction of SST isan urgent and challenging task. With a vast amount of ocean monitoring dataare continually collected, data-driven methods for SST time-series predictionshow promising results. However, they are limited by neglecting complexinteractions between SST and other ocean environmental factors, such as airtemperature and wind speed. This paper uses multi-factor time series SSTdata to propose a sequence-to-sequence network with two-module attention(TMA-Seq2seq) for long-term time series SST prediction. Specifically, TMASeq2seq is an LSTM-based encoder-decoder architecture facilitated by factorand temporal-attention modules and the input of multi-factor time series. Ittakes six-factor time series as the input, namely air temperature, air pressure,wind speed, wind direction, SST, and SST anomaly (SSTA). A factor attentionmodule is first designed to adaptively learn the effect of different factors onSST, followed by an encoder to extract factor-attention weighted features asfeature representations. And then, a temporal attention module is designedto adaptively select the hidden states of the encoder across all time steps tolearn more robust temporal relationships. The decoder follows the temporalattention module to decode the feature vector concatenated from the weightedfeatures and original input feature. Finally, we use a fully-connect layer tomap the feature into prediction results. With the two attention modules, ourmodel effectively improves the prediction accuracy of SST since it can notonly extract relevant factor features but also boost the long-term *** experiments on the datasets of China Coastal Sites (CCS) demonstrate that our proposed model outperforms other methods, reaching 98.29%in prediction accuracy (PACC) and 0.34 in root mean square error (RMSE).Moreover, SST prediction experiments in China’s East, South,

关键词： Sea surface temperature multi-factor attention long short-term memory

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