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Defect Detection Model Using Time Series Data Augmentation and Transformation

Computers, Materials & Continua 2024年第2期78卷 1713-1730页

作者： Gyu-Il Kim Hyun yoo Han-Jin Cho Kyungyong Chung Department of Computer Science Kyonggi UniversitySuwon-si16227Korea Contents Convergence Software Research Institue Kyonggi UniversitySuwon-si16227Korea Department of Energy IT Engineering Far East UniversityEumsung-gun27601Korea Division of AI Computer Science and Engineering Kyonggi UniversitySuwon-si16227Korea

Time-series data provide important information in many fields,and their processing and analysis have been the focus of much ***,detecting anomalies is very difficult due to data imbalance,temporal dependence,and ***,methodologies for data augmentation and conversion of time series data into images for analysis have been *** paper proposes a fault detection model that uses time series data augmentation and transformation to address the problems of data imbalance,temporal dependence,and robustness to *** method of data augmentation is set as the addition of *** involves adding Gaussian noise,with the noise level set to 0.002,to maximize the generalization performance of the *** addition,we use the Markov Transition Field(MTF)method to effectively visualize the dynamic transitions of the data while converting the time series data into *** enables the identification of patterns in time series data and assists in capturing the sequential dependencies of the *** anomaly detection,the PatchCore model is applied to show excellent performance,and the detected anomaly areas are represented as heat *** allows for the detection of anomalies,and by applying an anomaly map to the original image,it is possible to capture the areas where anomalies *** performance evaluation shows that both F1-score and Accuracy are high when time series data is converted to ***,when processed as images rather than as time series data,there was a significant reduction in both the size of the data and the training *** proposed method can provide an important springboard for research in the field of anomaly detection using time series ***,it helps solve problems such as analyzing complex patterns in data lightweight.

关键词： Defect detection time series deep learning data augmentation data transformation

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Interworking between Modbus and internet of things platform for industrial services

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Digital Communications and Networks 2024年第2期10卷 461-471页

作者： Sherzod Elamanov Hyeonseo Son Bob Flynn Seong Ki yoo Naqqash Dilshad Jaeseung Song Department of Convergence Engineering for Intelligent Drone Sejong UniversitySouth Korea SyncTechno Inc South Korea Exacta Global Smart Solutions USA Coventry University UK

In the era of rapid development of Internet of Things(IoT),numerous machine-to-machine technologies have been applied to the industrial *** to the divergence of IoT solutions,the industry is faced with a need to apply various technologies for automation and *** fact leads to a demand for an establishing interworking mechanism which would allow smooth interoperability between heterogeneous *** of the major protocols widely used today in industrial electronic devices is ***,data generated by Modbus devices cannot be understood by IoT applications using different protocols,so it should be applied in a couple with an IoT service layer ***2M,a global IoT standard,can play the role of interconnecting various protocols,as it provides flexible tools suitable for building an interworking framework for industrial ***,in this paper,we propose an interworking architecture between devices working on the Modbus protocol and an IoT platform implemented based on oneM2M *** the proposed architecture,we introduce the way to model Modbus data as oneM2M resources,rules to map them to each other,procedures required to establish interoperable communication,and optimization methods for this *** analyze our solution and provide an evaluation by implementing it based on a solar power management use *** results demonstrate that our model is feasible and can be applied to real case scenarios.

关键词： Internet of things Interoperability Interworking Modbus oneM2M

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Understanding acute kidney injury (AKI) in liver cirrhosis from the acute-on-chronic liver failure (ACLF) perspective

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Hepatobiliary Surgery and Nutrition 2024年第4期13卷 715-717页

作者： Jeong-Ju yoo Sang Gyune Kim Division of Gastroenterology and Hepatology Department of Internal MedicineSoonchunhyang University School of Medicine Bucheon HospitalBucheonKorea

In the field of hepatology,managing complications in patients with liver diseases is of paramount *** these,acute kidney injury(AKI)in patients with acute-on-chronic liver failure(ACLF)stands out due to its prevalence and significant impact on patient outcomes(1,2).AKI in ACLF differs substantially from AKI in simple liver cirrhosis in its clinical significance(3).AKI developed in ACLF is a manifestation of a multi-organ failure syndrome and is closely associated with a high mortality rate and severe complications.

关键词： Acute kidney injury(AKI) acute-on-chronic liver failure(ACLF) biomarker

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Spark plasma sintering of tungsten-based WTaVCr refractory high entropy alloys for nuclear fusion applications

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International Journal of Minerals,Metallurgy and Materials 2024年第1期31卷 146-154页

作者： Yongchul yoo Xiang Zhang Fei Wang Xin Chen Xing-Zhong Li Michael Nastasi Bai Cui Department of Mechanical&Materials Engineering University of Nebraska-LincolnLincolnNE 68588USA Nebraska Center for Materials and Nanoscience University of Nebraska-LincolnLincolnNE 68588USA Department of Nuclear Engineering Texas A&M UniversityCollege StationTX 77843USA

W-based WTaVCr refractory high entropy alloys (RHEA) may be novel and promising candidate materials for plasma facing components in the first wall and diverter in fusion reactors. This alloy has been developed by a powder metallurgy process combining mechanical alloying and spark plasma sintering (SPS). The SPSed samples contained two phases, in which the matrix is RHEA with a body-centered cubic structure, while the oxide phase was most likely Ta2VO6through a combined analysis of X-ray diffraction (XRD),energy-dispersive spectroscopy (EDS), and selected area electron diffraction (SAED). The higher oxygen affinity of Ta and V may explain the preferential formation of their oxide phases based on thermodynamic calculations. Electron backscatter diffraction (EBSD) revealed an average grain size of 6.2μm. WTaVCr RHEA showed a peak compressive strength of 2997 MPa at room temperature and much higher micro-and nano-hardness than W and other W-based RHEAs in the literature. Their high Rockwell hardness can be retained to at least 1000°C.

关键词： refractory high entropy alloy plasma-facing material fusion reactor spark plasma sintering

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Toward a Learnable Climate Model in the Artificial Intelligence Era

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Advances in Atmospheric Sciences 2024年第7期41卷 1281-1288页

作者： Gang HUANG Ya WANG yoo-Geun HAM Bin MU Weichen TAO Chaoyang XIE State key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Laboratory for Regional Oceanography and Numerical Modeling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China University of Chinese Academy of Sciences Beijing 100049China Department of Environmental Planning Graduate School of Environmental StudiesSeoul National UniversitySeoul 08826South Korea School of Software Engineering Tongji UniversityShanghai 200092China

Artificial intelligence(AI)models have significantly impacted various areas of the atmospheric sciences,reshaping our approach to climate-related *** this AI-driven transformation,the foundational role of physics in climate science has occasionally been *** perspective suggests that the future of climate modeling involves a synergistic partnership between AI and physics,rather than an“either/or”*** controversies around current physical inconsistencies in large AI models,we stress the critical need for detailed dynamic diagnostics and physical ***,we provide illustrative examples to guide future assessments and constraints for AI *** AI integration with numerical models,we argue that offline AI parameterization schemes may fall short of achieving global optimality,emphasizing the importance of constructing online ***,we highlight the significance of fostering a community culture and propose the OCR(Open,Comparable,Reproducible)*** a better community culture and a deep integration of physics and AI,we contend that developing a learnable climate model,balancing AI and physics,is an achievable goal.

关键词： artificial intelligence deep learning learnable climate model

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Predictive modeling of critical temperatures in magnesium compounds using transfer learning

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Journal of Magnesium and Alloys 2024年第4期12卷 1540-1553页

作者： Surjeet Kumar Russlan Jaafreh Subhajit Dutta Jung Hyeon yoo Santiago Pereznieto Kotiba Hamad Dae Ho yoon School of Advanced Materials Science&Engineering Sungkyunkwan University Suwon 16419Republic of Korea

This study presents a transfer learning approach for discovering potential Mg-based superconductors utilizing a comprehensive target ***,a large source dataset(Bandgap dataset)comprising approximately∼75k compounds is utilized for pretraining,followed by fine-tuning with a smaller Critical Temperature(T_(c))dataset containing∼300 ***,there is a significant improvement in the performance of the transfer learning model over the traditional deep learning(DL)model in predicting ***,the transfer learning model is applied to predict the properties of approximately 150k *** are validated computationally using density functional theory(DFT)calculations based on lattice dynamics-related ***,to demonstrate the extended predictive capability of the transfer learning model for new materials,a pool of virtual compounds derived from prototype crystal structures from the Materials Project(MP)database is generated.T_(c) predictions are obtained for∼3600 virtual compounds,which underwent screening for electroneutrality and thermodynamic *** Extra Trees-based model is trained to utilize E_(hull)values to obtain thermodynamically stable materials,employing a dataset containing Ehull values for approximately 150k materials for *** with Ehull values exceeding 5 meV/atom were filtered out,resulting in a refined list of potential Mg-based *** study showcases the effectiveness of transfer learning in predicting superconducting properties and highlights its potential for accelerating the discovery of Mg-based materials in the field of superconductivity.

关键词： Superconductivity Critical temperature Transfer learning Crystal structure features Thermodynamic stability

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Ag-GST/HfO_(x)-based unidirectional threshold switching selector with low leakage current and threshold voltage distribution for high-density cross-point arrays

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Rare Metals 2024年第1期43卷 280-288页

作者： Kyoung-Joung yoo Dae-Yun Kang Nahyun Kim Ho-Jin Lee Ta-Hyeong Kim Taeho Kim Tae Geun Kim School of Electrical Engineering Korea UniversitySeoul 02841Republic of Korea

The use of electrochemical-metallization-based volatile threshold switching selectors in cross-point arrays has been widely explored owing to their high on-off ratios and simple ***,these devices are unsuitable for cross-point architectures because of the difficulty in controlling the random filament formation that results in large fluctuations in the threshold voltage during *** this study,we investigated the unidirectional threshold transition characteristics associated with an Ag/GST/HfO_(x)/Pt-based bilayer selector and demonstrated the occurrence of a low leakage current(<1×10^(-11) A) and low distribution of the threshold voltage(Δ0.11 V).The bilayer structure could control the filament formation in the intermediate state through the insertion of an HfO_(x) tunneling *** stacking a bilayer selector with NiO_(x)based resistive random-access memory,the leakage and programming currents of the device could be significantly *** the crossbar array configuration,we performed equivalent circuit analysis of a one-selector oneresistor(1S1R) devices and estimated the optimal array size to demonstrate the applicability of the proposed *** maximum acceptable crossbar array size of the 1S1R device with the Ag/GST/HfO_(x)/Pt/Ti/NiO_(x)/Pt structure was 5.29×10^(14)(N^(2),N=2.3×10^(7)).

关键词： Selector device Tunneling barrier Threshold switching Sputtering 1S1R Cross-point array

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Cnoidal waves and their soliton limits in single mode fiber lasers

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Photonics Research 2024年第3期12卷 543-551页

作者： XIAO HU TUPEI CHEN SEONGWOO yoo DINGYUAN TANG Julong College Shenzhen Technology UniversityShenzhen 518118China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore

Cnoidal waves are a type of nonlinear periodic wave solutions of the nonlinear dynamic *** are well known in fluid dynamics,but it is not the case in *** this paper we show both experimentally and numerically that cnoidal waves could be formed in a fiber laser either in the net normal or net anomalous cavity dispersion regime,especially because,as the pump power is increased,the formed cnoidal waves could eventually evolve into a train of bright(in the net anomalous cavity dispersion regime)or dark(in the net normal cavity dispersion regime)*** simulations of the laser operation based on the extended nonlinear Schrödinger equation(NLSE)have well reproduced the experimental *** result not only explains why solitons can still be formed in a fiber laser even without mode locking but also suggests a new effective way of automatic stable periodic pulse train generation in lasers with a nonlinear cavity.

关键词： fiber pump mode

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Structural and electrochemical stabilization enabling high-energy P3-type Cr-based layered oxide cathode for K-ion batteries

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Carbon Energy 2024年第5期6卷 81-93页

作者： Wonseok Ko Seokjin Lee Hyunyoung Park Jungmin Kang Jinho Ahn Yongseok Lee Gwangeon Oh Jung-Keun yoo Jang-Yeon hwang Jongsoon Kim Department of Energy Science Sungkyunkwan UniversitySuwonRepublic of Korea SKKU Institute of Energy Science and Technology(SIEST) Sungkyunkwan UniversitySuwonRepublic of Korea Department of Energy Engineering Hanyang UniversitySeoulRepublic of Korea Carbon Composites Department Korea Institute of Materials Science(KIMS)ChangwonRepublic of Korea Department of Battery Engineering Hanyang UniversitySeoulRepublic of Korea

Layered-type transition metal(TM)oxides are considered as one of the most promising cathodes for K-ion batteries because of the large theoretical gravimetric capacity by low molar ***,they suffer from severe structural change by de/intercalation and diffusion of K^(+)ions with large ionic size,which results in not only much lower reversible capacity than the theoretical capacity but also poor power ***,it is important to enhance the structural stability of the layered-type TM oxides for outstanding electrochemical behaviors under the K-ion battery ***,it is investigated that the substitution of the appropriate Ti^(4+)contents enables a highly enlarged reversible capacity of P3-type KxCrO_(2) using combined studies of first-principles calculation and various *** the pristine P3-type KxCrO_(2) just exhibits the reversible capacity of∼120 mAh g^(−1) in the voltage range of 1.5-4.0 V(vs.K^(+)/K),the∼0.61 mol K^(+)corresponding to∼150 mAh g^(−1) can be reversible de/intercalated at the structure of P3-type K0.71[Cr_(0.75)Ti_(0.25)]O_(2) under the same ***,even at the high current density of 788 mA g^(−1),the specific capacity of P3-type K0.71[Cr_(0.75)Ti_(0.25)]O_(2) is∼120 mAh g^(−1),which is∼81 times larger than that of the pristine P3-type KxCrO_(2).It is believed that this research can provide an effective strategy to improve the electrochemical performances of the cathode materials suffered by severe structural change that occurred during charge/discharge under not only K-ion battery system but also other rechargeable battery systems.

关键词： cathodes first-principles calculations layered-type oxide materials potassium-ion batteries structural stabilization

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Porously Reduced 2-Dimensional Bi_(2)O_(2)CO_(3) Petals for Strain-Mediated Electrochemical CO_(2) Reduction to HCOOH

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Energy & Environmental Materials 2024年第1期7卷 215-221页

作者： Won Seok Cho Dae Myung Hong Wan Jae Dong Tae Hyung Lee Chul Jong yoo Donghwa Lee Ho Won Jang Jong-Lam Lee Department of Materials Science and Engineering Pohang University of Science and Technology(POSTECH)Pohang Gyungbuk 37673Korea Department of Materials Science and Engineering Research Institute of Advanced Materials Seoul National UniversitySeoul 08826Korea

Here we introduce bismuth-based catalysts for the efficient electrochemical reduction of CO_(2)to formic acid(HCOOH),which are composed of petal-shaped Bi_(2)O_(2)CO_(3)(BOC)that spontaneously formed from Bi thin film in aqueous carbonate solution at room *** the electrochemical reduction process,the BOC petals transform to reduced BOC(R-BOC)consisting of individual BOC and Bi *** mismatch between both domains induces biaxial strain at the *** functional theory calculations suggest that the tensile strain on the Bi domain stabilizes the*OCHO intermediate,reducing the thermodynamic barrier toward CO_(2)conversion to *** with the thermodynamic benefit and the unique nanoporous petal-shaped morphology,R-BOC petals have a superior Faradaic efficiency of 95.9%at-0.8 V_(RHE)for the electrochemical conversion of CO_(2)to *** work demonstrates that the spontaneously formed binary phases with desirable lattice strain can increase the activity of bismuth catalysts to the CO_(2)reduction reaction;such a strategy can be applicable in design of various electrocatalysts.

关键词： bismuth carbon dioxide reduction formic acid heterointerfaces strain

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