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2023 Workshop on Data science Techniques for Datasets on Mental and Neurodegenerative Disorders, DSTNDS 2023

作者： Yu, Jennifer Ali, Mai Zhu, Rui Edke, Parinita Goldenberg, Anna Department of Computer Science University of Toronto Toronto Canada Department of Electrical and Computer Engineering University of Toronto Toronto Canada Department of Laboratory Medicine and Pathobiology University of Toronto Toronto Canada Hospital for Sick Children Toronto Canada Vector Institute Toronto Canada

Maternal health is one of the main sustainable development goals of the World Health Organization (WHO). Changes associated with pregnancy can be reflected in the physiological, psychological and behavioral states of women. In this study, we investigated relationships between Adverse Childhood Experiences (ACEs) and mental health symptoms such as depression and anxiety over pregnancy and into the postpartum period, as well as quality of life. Further, we examined the interrelationship between mental health and physical health during and post pregnancy, finding that the effects during pre and postnatal periods tend to differ. We hope that our analysis lays potential groundwork for exploring more complex relationships between mental health symptoms and ACEs during and post pregnancy. © 2023 CEUR-WS. All rights reserved.

关键词： Behavioral research

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Cryptanalysis of DBST, a lightweight block cipher

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Frontiers of computer science 2024年第4期18卷 219-221页

作者： Sadegh SADEGHI Nasour BAGHERI Department of Mathematics Institute for Advanced Studies in Basic Sciences(IASBS)Zanjan 45137-66731Iran Research Center for Basic Sciences and Modern Technologies(RBST) Institute for Advanced Studies in Basic Sciences(IASBS)Zanjan 45137-66731Iran Electrical Engineering Department Shahid Rajaee Teacher Training UniversityTehran 16788-15811Iran School of Computer Science(SCS) Institute for Research in Fundamental Sciences(IPM)Tehran 19395-5531Iran

1 Introduction Conventional cryptographic primitives are not suitable for resource-constrained ***,numerous lightweight primitives have been proposed over the past decade,specifically tailored for such ***,such ciphers would not be used in a real-world application unless they were thoroughly tested for security against existing *** this direction,DBST[1]cipher has been recently proposed by Yan et *** balance security,cost,and efficiency,DBST has implemented a novel 4-branch generalized Feistel variant *** this structure,a 2-branch XOR operation has been incorporated in the middle section,establishing interconnections between all *** the other hand,by leveraging the bit-slice technique and subkeys,the algorithm introduces an innovative approach to constructing a dynamic S-box *** designers of DBST cipher have extensively investigated its resistance to known attacks such as linear and differential cryptanalysis,as well as impossible differential cryptanalysis,among *** them,the objective of differential cryptanalysis[2]is to identify high-probability characteristics in the plaintext that are transmitted to the ciphertext,known as distinguishers.

关键词： structure. primitive branch

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A Comprehensive Technique Based on Machine Learning for Device and Circuit Modeling of Gate-All-Around Nanosheet Transistors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 181-194页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering the Institute of Biomedical Engineering the Department of Electronics and Electrical Engineering the Institute of Pioneer Semiconductor Innovation and the Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

Machine learning (ML) is poised to play an important part in advancing the predicting capability in semiconductor device compact modeling domain. One major advantage of ML-based compact modeling is its ability to capture complex relationships and patterns in large datasets. Therefore, in this paper a novel design scheme based on dynamically adaptive neural network (DANN) is proposed to develop fast and accurate compact model (CM). This framework constitutes a powerful yet computationally efficient methodology and exhibits emergent dynamic behaviors. This paper demonstrates that the compact model based on ML can be designed to replicate the performance of conventional compact model for nanodevices. For this work, gate-all-around (GAA) nanosheet (NS) device characteristics are comprehensively analyzed for process variability sources using the proposed model. The device geometry parameters such as channel length, nanosheet width and nanosheet thickness are fed as input features to the DANN model. The adaptive neural network learns dynamically by updating weights of the model in accordance with the input features and achieves accurate neural weight convergence. The proposed model predicted the electrical characteristics of NS devices with less than 1% error rate. The model is also implemented and validated for the simulations of digital circuit designs such as inverter, and logic gates. ©;2023 The Authors.

关键词： Circuit simulation

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Degradation mechanism analysis of LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2) single crystal cathode materials through machine learning

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npj Computational Materials 2022年第1期8卷 2119-2127页

作者： Wuxin Sha Yaqing Guo Danpeng Cheng Qigao Han Ping Lou Minyuan Guan Shun Tang Xinfang Zhang Songfeng Lu Shijie Cheng Yuan-Cheng Cao School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhan430074China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430074China State Grid Huzhou Electric Power Supply Company Huzhou313000China School of Cyber Science&Engineering Huazhong University of Science and TechnologyWuhan430074China

LiNi_(0.5)Co_(0.2)Mn_(0.3)O_(2)(NCM523)has become one of the most popular cathode materials for current lithium-ion batteries due to its high-energy density and cost ***,the rapid capacity fading of NCM severely hinders its development and ***,the single crystal NCM523 materials under different degradation states are characterized using scanning transmission electron microscopy(STEM).Then we developed a neural network model with a two-sequential attention block to recognize the crystal structure and locate defects in STEM *** number of point defects in NCM523 is observed to experience a trend of increasing first and then decreasing in the degradation *** space between the transition metal columns shrinks obviously,inducing dramatic capacity *** analysis sheds light on the defect evolution and chemical transformation correlated with layered material *** also provides interesting hints for researchers to regenerate the electrochemical capacity and design better battery materials with longer life.

关键词： battery crystal analysis

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computer-Vision-Based Non-Contact Paste Concentration Measurement*

Computer-Vision-Based Non-Contact Paste Concentration Measur...

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2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Liang, Tailin Yuan, Zhaolin School of Computer Science and Engineering Beihang University State Key Laboratory of Software Development Environment Beijing China Research Institute of Advanced Manufacturing Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350378658

For monitoring the paste concentration, existing techniques, such as ultrasonic concentration meters and neutron meters, suffer from radiation hazards and low precision in high concentrations. This paper proposes a novel non-contact concentration measurement method based on deep learning. With the dataset collected by preparing the paste with different concentrations and taking photographs from the paste surface, a convolutional neural network is trained to extract the features from images and predict the concentration. The experiments indicate that the measurement accuracy is close to 88.79 % for the manual stirring paste dataset and 91.42 % for the automatic stirring paste dataset, which are sufficient in industrial applications. As a substitution of traditional concentration measurement instruments, the proposed vision-based concentration measurement method is non-contact and its accuracy is sufficient in industrial applications. © 2024 IEEE.

关键词： Radiation hazards

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Deep CNN Model for Multimodal Medical Image Denoising

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computers, Materials & Continua 2022年第11期73卷 3795-3814页

作者： Walid El-Shafai Amira A.Mahmoud Anas M.Ali El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

In the literature,numerous techniques have been employed to decrease noise in medical image modalities,including X-Ray(XR),Ultrasonic(Us),Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and Positron Emission Tomography(PET).These techniques are organized into two main classes:the Multiple Image(MI)and the Single Image(SI)*** the MI techniques,images usually obtained for the same area scanned from different points of view are used.A single image is used in the entire procedure in the SI *** denoising techniques can be carried out both in a transform or spatial *** paper is concerned with single-image noise reduction techniques because we deal with single medical *** most well-known spatial domain noise reduction techniques,including Gaussian filter,Kuan filter,Frost filter,Lee filter,Gabor filter,Median filter,Homomorphic filter,Speckle reducing anisotropic diffusion(SRAD),Nonlocal-Means(NL-Means),and Total Variation(TV),are ***,the transform domain noise reduction techniques,including wavelet-based and Curvelet-based techniques,and some hybridization techniques are ***,a deep(Convolutional Neural Network)CNN-based denoising model is proposed to eliminate Gaussian and Speckle noises in different medical image *** model utilizes the Batch Normalization(BN)and the ReLU as a basic *** a result,it attained a considerable improvement over the traditional *** previously mentioned techniques are evaluated and compared by calculating qualitative visual inspection and quantitative parameters like Peak Signal-to-Noise Ratio(PSNR),Correlation Coefficient(Cr),and system complexity to determine the optimum denoising algorithm to be applied *** on the quality metrics,it is demonstrated that the proposed deep CNN-based denoising model is efficient and has superior denoising performance over the traditionaldenoising techniques.

关键词： Image enhancement medical imaging speckle noise Gaussian noise denoising filters CNN denoising

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Fatigue crack propagation across grain boundary of Al-Cu-Mg bicrystal based on crystal plasticity XFEM and cohesive zone model

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Journal of Materials science & Technology 2022年第31期126卷 275-287页

作者： Qi Zhao Magd Abdel Wahab Yong Ling Zhiyi Liu School of Materials Science and Engineering Hubei University of Automotive TechnologyShiyan 442002China Faculty of Mechanical-Electrical and Computer Engineering School of Engineering and TechnologyVan Lang UniversityHo Chi Minh CityVietnam Soete Laboratory Faculty of Engineering and ArchitectureGhent UniversityTechnologiepark Zwijnaarde 903B-9052 ZwijnaardeBelgium School of Materials Science and Engineering Central South UniversityChangsha 410083China

In this paper,a methodology integrating crystal plasticity(CP),the eXtended finite element method(XFEM)and the cohesive zone model(CZM)is developed for an Al-Cu-Mg alloy to predict fatigue crack propagation(FCP)across grain boundary(GB)of Al-Cu-Mg alloy during stageІІ.One GB model is incor-porated into FCP constitutive law to describe grain interaction at GB.A bicrystal containing GB is built up to simulate FCP behavior through L participated *** features including GB characteristic,cumulative plastic strain(CPS)distribution and crystal slipping evidence can be *** numer-ical results are compared with published experimental data to check the accuracy of *** work demonstrates that the combination of CP containing GB constitutive laws,XFEM and CZM is a promising methodology in predicting twist angle-controlled crack deflection through GBs.

关键词： Grain boundary Twist angle Crystal plasticity Extended finite element method Fatigue crack propagation Cumulative plastic strain

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Subwavelength Fano Resonant Porous Silicon Metasurfaces for Sensing and Dynamic Structural Color

Subwavelength Fano Resonant Porous Silicon Metasurfaces for ...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Gafsi, Saddam Dos Santos, Estevao Marques Kravchenko, Ivan Ryckman, Judson D. Holcombe Department of Electrical and Computer Engineering Clemson University ClemsonSC29634 United States Center for Nanophase Materials Science Oak Ridge National Laboratory Oak RidgeTN37831 United States

ISBN: (纸本)9781957171395

We introduce the design, fabrication, and experimental investigation of subwavelength Fano resonant porous silicon metasurfaces functioning on the principle of guided mode resonance. These metasurfaces exhibit promise for dynamic structural coloration and sensing applications. CLEO 2024 © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Mesoporous materials

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Tuning the number of chiral edge channels in a fixed quantum anomalous Hall system

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Physical Review B 2024年第20期109卷 L201402-L201402页

作者： Peng Deng Yulei Han Peng Zhang Su Kong Chong Zhenhua Qiao Kang L. Wang Beijing Academy of Quantum Information Sciences Beijing 100193 China Department of Electrical and Computer Engineering University of California Los Angeles California 90095 USA Department of Physics Fuzhou University Fuzhou Fujian 350108 China International Center for Quantum Design of Functional Materials CAS Key Laboratory of Strongly-Coupled Quantum Matter Physics and Department of Physics University of Science and Technology of China Anhui 230026 China Hefei National Laboratory University of Science and Technology of China Hefei 230088 China

Quantum anomalous Hall (QAH) insulators exhibit chiral edge channels characterized by vanishing longitudinal conductance and quantized Hall conductance of Ce2/h, wherein the Chern number C is an integer equal to the number of the parallel chiral edge channels. These chiral edge channels conduct dissipationless transport in QAH insulators, making them pivotal for applications in low-consumption electronics and topological quantum computing. While the QAH effect with multiple chiral edge channels (i.e., C > 1) has been demonstrated in multilayers consisting of magnetic topological insulators and normal insulators, the channel number remains fixed for a given sample. Here, we unveil the tunability of the number of chiral edge channels within a single QAH insulator device. By tuning the magnetization of individual layers within the multilayer system, Chern insulating states with different Chern numbers are unveiled. The tunable Chern number was corroborated by our theoretical calculations. Furthermore, we conducted layer-dependent calculations to elucidate the contribution of the Chern number from different layers in the multilayer. Our findings demonstrate an extra degree of freedom in manipulating the chiral edge channels in QAH insulators. This tunability offers an extra dimension for the implementation of the QAH-based multichannel dissipationless transport.

关键词： Quantum anomalous Hall effect Quantum transport Topological insulators Molecular beam epitaxy

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Subwavelength Fano Resonant Porous Silicon Metasurfaces for Sensing and Dynamic Structural Color

Subwavelength Fano Resonant Porous Silicon Metasurfaces for ...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Porous materials

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