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Correction: Reliable high work-function molybdenum dioxide synthesis via template-effect-utilizing atomic layer deposition for next-generation electrode applications

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Journal of Materials Chemistry C 2022年第36期10卷 13268-13269页

作者： Ye Won Kim Ae Jin Lee Dong Hee Han Dae Cheol Lee Ji Hyeon Hwang Youngjin Kim Songyi Moon Taewon Youn Minyung Lee Woojin Jeon Department of Advanced Materials Engineering for Information and Electronics and Integrated Education Program for Frontier Science & Technology (BK21 Four) Kyung Hee University Yongin Gyeonggi 17104 Korea SK Hynix Inc. Icheon Gyeonggi 17336 Korea

Correction for ‘Reliable high work-function molybdenum dioxide synthesis via template-effect-utilizing atomic layer deposition for next-generation electrode applications’ by Ye Won Kim et al., J. Mater. Chem. C, 202...

Correction for ‘Reliable high work-function molybdenum dioxide synthesis via template-effect-utilizing atomic layer deposition for next-generation electrode applications’ by Ye Won Kim et al., J. Mater. Chem. C, 2022, https://***/10.1039/d2tc02104h.

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A Bayesian Optimization Framework for Analog Circuits Optimization 15

A Bayesian Optimization Framework for Analog Circuits Optimi...

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15th International Conference on Computer engineering and Systems, ICCES 2020

作者： Abdelaal, Shady A. Hussein, Ahmed Mostafa, Hassan Cairo University Electronics and Communications Engineering Department Giza12613 Egypt University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza12578 Egypt

ISBN: (纸本)9780738105598

The growing complexity of analog circuits poses challenging constraints on analog simulation tools. Simulation based optimization approaches have gained a lot of interest to cut down the analog circuit design time and complexity. One of these approaches is the Bayesian optimization (BO) approach, which represents the analog circuit as a black box function, and incorporates optimization goal and constraints aiming to reach the optimum design parameters with the least possible simulation iterations. In this paper, a BO approach for automated sizing of analog circuits is discussed. The proposed approach uses Gaussian Process (GP) as a surrogate model and utilizes SOBOL sampling. The proposed algorithm is validated on a two-stage op amp benchmark circuit and compared to the literature work. © 2020 IEEE.

关键词： Analog circuits

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engineering Andreev Bound States for Thermal Sensing in Proximity Josephson Junctions

arXiv

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arXiv 2025年

作者： Jung, Woochan Arnault, Ethan G. Huang, Bevin Park, Jinho Jang, Seong Watanabe, Kenji Taniguchi, Takashi Englund, Dirk Fong, Kin Chung Lee, Gil-Ho Physics Department Pohang University of Science and Technology Pohang37673 Korea Republic of Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States Intelligence Community Postdoctoral Research Fellowship Program Massachusetts Institute of Technology CambridgeMA02139 United States Department of Mechanical Engineering Columbia University New YorkNY10027 United States Research Center for Functional Materials National Institute for Materials Science Tsukuba Japan International Center for Materials Nanoarchitectonics National Institute for Materials Science Tsukuba Japan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Department of Physics Northeastern University BostonMA02115 United States Quantum Materials and Sensing Institute BurlingtonMA01803 United States

The thermal response of proximity Josephson junctions (JJs) is governed by the temperature (T)- dependent occupation of Andreev bound states (ABS), making them promising candidates for sensitive thermal detection. In this study, we systematically engineer ABS to enhance the thermal sensitivity of critical current (lc) of proximity JJs, quantified as |dlc/dT/| for threshold readout scheme and |dlc/***−1| for inductive readout scheme. Using a gate-tunable graphene-based JJ platform, we explore the impact of key parameters—including channel length, transparency, carrier density, and superconducting material—on the thermal response. Our results reveal that the proximity-induced superconducting gap plays a crucial role in optimizing thermal sensitivity. Notably, we see a maximum |dlc/***−1| value of 0.6 K−1 at low temperatures with titanium-based graphene JJs. By demonstrating a systematic approach to engineering ABS in proximity JJs, this work establishes a versatile framework for optimizing thermal sensors and advancing the study of ABS-mediated transport. © 2025, CC BY.

关键词： Superconducting materials

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Mathematical modelling and optimization of parameters for Al-Si-Fe aluminum alloy reinforced by Al 2 O 3 and graphite particles using Taguchi method

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Materials Today: Proceedings 2021年 44卷 979-986页

作者： Robale Dinsa Daba Devendra Kumar Sinha Habtamu Beri Satyam Shivam Gautam Gulam Mohammed Sayeed Ahmed Ram Sewak Singh Program of Mechanical Design and Manufacturing Engineering School of Mechanical Chemical and Materials Engineering ASTU ADAMA Ethiopia Department of Mechanical Engineering North Eastern Regional Institute of Science and Technology Itanagar India Department of Electronics and Communication School of Electrical Engineering and Computing ASTU ADAMA Ethiopia

In the present scenario the aluminum and its alloys are preferred due to requirement of lightweight high strength material. The present research article interrogates experimentally the study of actual density and porosity using powder metallurgy method. The experimental design is done using Taguchi L 16 orthogonal array. Actual density and porosity has been analyzed based on ‘smaller is best’ basis. Actual density and porosity are calculated using Archimedes principle. The leverage of four levels and five process parameters such as weight percentage of Al 2 O 3 , weight percentage of graphite, compaction pressure, compaction time and milling time are considered. Results reveal that Al 2 O 3 weight percentage has the highest leverage on density followed by compaction time and graphite weight percentage.

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Shaping Integrity: Why Generative Artificial Intelligence Does Not Have to Undermine Education

arXiv

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arXiv 2024年

作者： Tan, Myles Joshua Toledo Maravilla, Nicholle Mae Amor Tan Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL32611 United States Department of Epidemiology College of Public Health & Health Professions College of Medicine University of Florida GainesvilleFL32610 United States Biology Program College of Arts and Sciences University of St. La Salle Negros Occidental Bacolod City6100 Philippines Department of Natural Sciences College of Arts and Sciences University of St. La Salle Negros Occidental Bacolod City6100 Philippines Department of Chemical Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City6100 Philippines Department of Electronics Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City6100 Philippines Yo-Vivo Corporation Negros Occidental Bacolod City6100 Philippines

This paper examines the role of generative artificial intelligence (GAI) inpromoting academic integrity within educational settings. It explores how AIcan be ethically integrated into classrooms to enhance learning experiences,foster intrinsic motivation, and support voluntary behavior change amongstudents. By analyzing established ethical frameworks and educational theoriessuch as deontological ethics, consequentialism, constructivist learning, andSelf-Determination Theory (SDT), the paper argues that GAI, when usedresponsibly, can enhance digital literacy, encourage genuine knowledgeconstruction, and uphold ethical standards in education. This researchhighlights the potential of GAI to create enriching, personalized learningenvironments that prepare students to navigate the complexities of the modernworld ethically and effectively. © 2024, CC BY-NC-SA.

关键词： Contrastive Learning

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FPGA Utilized Implementation of Epileptic Seizure Detection System Based on Wearable Devices using Dynamic Partial Reconfiguration

FPGA Utilized Implementation of Epileptic Seizure Detection ...

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Japan-Egypt International Conference on electronics, Communications and Computers (JEC-ECC)

作者： Mohamed Fawzy Ahmed Hussien Hassan Mostafa Siemens Digital Industries Software Cairo Egypt Electronics and Electrical Communications Engineering Department Cairo University Giza Egypt Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology October Gardens 6th of October University of Science and technology Giza Egypt

ISBN: (纸本)9781665464642

Unplanned seizures are caused by a disorder in the central nervous system known as epilepsy. Although significant advancements have been made in the realm of non-EEG wearable devices, there is still much room for improvement in the field of EEG-based seizure detection and prediction using ML. The management of epilepsy has a lot of promise to be aided by non-invasive wearable technology. The suggested study intends to design and implement a support vector machine (SVM) classification-based epileptic seizure detection system based on various wearable devices. The proposed technique for detecting seizures accomplishes According to data for seizure detection, our system consistently achieves a sensitivity of 100% and an accuracy of 97%. High level MATLAB model creation is part of the design cycle. Despite the fact that high performance cannot be achieved with just one signal. Although a high performance detection system cannot achieve the requisite sensitivity and accuracy with a single signal, we presented various combining techniques. RTL modelling, design optimization, FPGA implementation, and functional verification are all included in the implementation cycle. The capacity of the FPGA’s partial dynamic reconfiguration is suggested for implementation in order to make better use of the available resources. Comparing the proposed implementation to relevant earlier work, it demonstrated improved utilization.

关键词： Support vector machines Training Performance evaluation Sensitivity Wearable computers Epilepsy Feature extraction

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Eye-Zheimer: A Deep Transfer Learning Approach of Dementia Detection and Classification from NeuroImaging 7

Eye-Zheimer: A Deep Transfer Learning Approach of Dementia D...

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7th IEEE International Conference on engineering Technologies and Applied Sciences, ICETAS 2020

作者： Alon, Helcy D. Ligayo, Michael Angelo D. Misola, Maribel A. Sandoval, Allan A. Fontanilla, Marites V. Technological Institute of the Philippines Graduate Program Manila Philippines Quezon City University Department of Electronics Engineering Quezon City Philippines FEU Institute of Technology Department of Computer Engineering Manila Philippines St. Paul University Department of Information Technology Quezon City Philippines

ISBN: (纸本)9780738105048

Dementia is a common term for memory loss, speech, problem-solving, and other cognitive skills that are serious enough to interfere with everyday life, and Alzheimer's is the leading cause of dementia. Alzheimer's disease is presumed to develop 20 years or more before symptoms occur, with degenerative changes that are unapparent to the person affected. The deep learning approach for early detection and Alzheimer's disease classification has recently gained significant attention. This study proposed disease detection trained by utilizing the YOLO v3 algorithm that aims to detect Alzheimer's disease based solely on Magnetic Resonance Imaging (MRI). Pascal VOC format and LabelImg tool are used for annotating the datasets, categorizing the image as non-demented and mild-demented. Model 4 was used in the system having 98.617% training accuracy, 98.8207% validation accuracy, and mAP of 96.17%. To test the accuracy of the used model, images of MRI scans are presented and it recorded 80% testing accuracy. © 2020 IEEE.

关键词： Object detection

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Unveiling Multivariate EEG Features: A Novel Approach to Enhancing ADHD Diagnosis Through Visual and Auditory Attention Tests

Unveiling Multivariate EEG Features: A Novel Approach to Enh...

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International Conference on Fuzzy Theory and it's Applications (iFUZZY)

作者： Zuo-Cian Fan Ro-Wei Lin Ching-Shu Tsai Wen-Jiun Chou Chia-Jung Li Zih-Jun Huang Bin-Yu Shih Liang-Jen Wang Li-Wei Ko Department of Biological Science & Technology Center for Intelligent Drug Systems and Smart Bio-Devices (IDS2B) College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu Taiwan International Ph.D. Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Child and Adolescent Psychiatry Kaohsiung Chang Gung Memorial Hospit Department of Electronics and Electrical Engineering Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

We sought to revolutionize the classification of Attention-Deficit/Hyperactivity Disorder (ADHD) by pioneering an innovative approach that seamlessly integrated auditory and visual tests with electroencephalogram (EEG) coherence analysis, forming the foundation for our Support Vector Machine (SVM) models. Our primary objective was to achieve precise differentiation between individuals with ADHD and those without, aiming to reshape the landscape of ADHD diagnosis and early intervention. We constructed an SVM model based on CATA coherence, incorporating a carefully selected set of 180 features, and another grounded in CPT coherence with 70 features. Astonishingly, our exploration uncovered that a model incorporating CATA's coherence and Power Spectral Density (PSD) as features achieved an astounding accuracy rate of 97.7%, using only half the number of features. This revelation hints at untapped potential for multivariate advancements in the realm of ADHD classification. The landscape of ADHD diagnosis and intervention is perpetually evolving, most notably with the FDA's approval of game therapy for ADHD. Leveraging the transformative power of our findings, we envision the development of user-friendly game therapies for in-home use, empowering both clinicians and parents alike. This marks a paradigm shift in the realm of ADHD intervention, offering objective, data-driven tools for the early management of ADHD. Gamified therapy not only enhances accessibility but also fosters engagement and compliance, all of which are pivotal in the long-term care of individuals with ADHD. In summary, our study represents a significant advancement in our comprehension and classification of ADHD. By fusing auditory and visual tests with EEG coherence analysis, fortified by state-of-the-art machine learning techniques, we have achieved an unprecedented level of accuracy in identifying individuals with ADHD. Our findings, aligned with the FDA-approved game therapy, offer a glimpse into a

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Reduction of interface defects in gate-recessed GaN HEMTs by neutral beam etching

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Materials Today Advances 2024年 23卷

作者： Yu, Chia Hao Chiang, Wei Hsiang Chen, Yi-Ho Samukawa, Seiji Wuu, Dong Sing Chung, Chin-Han Hsiao, Ching-Lien Horng, Ray Hua Institute of Electronics National Yang Ming Chiao Tung University Department of Materials Science and Engineering National Chung Hsing University Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Institute of Comunications Engineering National Yang Ming Chiao Tung University Department of Applied Materials and Optoelectronic Engineering National Chi Nan University International College of Semiconductor Technology National Yang Ming Chiao Tung University Thin Film Physics Division Department of Physics Chemistry and Biology (IFM) Linköping University

This study investigates and compares the impact of different etching techniques on the fabrication of GaN high electron mobility transistors (HEMTs) between the inductively coupled plasma reactive ion etching (ICP-RIE) and the neutral beam etching (NBE) for the gate recess. By conducting direct current analysis, it was found that devices manufactured using the NBE exhibited superior electrical performance as compared with those produced using the ICP-RIE. These enhanced electrical characteristics include a transconductance of up to 100.4 mS/mm, a threshold voltage (V_th) of −2.3 V, an on/off current ratio of 1.1 × 10⁹, a subthreshold swing (S.S.) of 99.63 mV/dec, and a remarkably low gate leakage current. Additionally, we noted varying degrees of hysteresis in the I–V characteristics were related to process disparities possibly leading to interface defects. Multi-frequency capacitance-voltage (C–V) measurements were used to identify the interface defects at the oxide/AlGaN interface of the gate. The results revealed that devices fabricated using the NBE exhibited a lower interface defect density as compared with those fabricated using the ICP-RIE, thereby elucidating the reduced hysteresis observed in the I–V characteristics. These findings indicated the significant advantages of the NBE process in the fabrication of GaN HEMTs. © 2024 The Authors

关键词： GaN HEMTs Gate recess Interface defects Multi-frequency C–V Neutral beam etching

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Can Personalized Medicine Coexist with Health Equity? Examining the Cost Barrier and Ethical Implications

arXiv

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arXiv 2024年

作者： Francisco, Kishi Kobe Yee Apuhin, Andrane Estelle Carnicer Tan, Myles Joshua Toledo Byers, Mickael Cavanaugh Maravilla, Nicholle Mae Amor Tan Karim, Hezerul Abdul AlDahoul, Nouar Biology Program College of Arts and Science University of St. La Salle Negros Occidental Bacolod City Philippines Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Department of Epidemiology College of Public Health & Health Professions College of Medicine University of Florida GainesvilleFL United States Department of Natural Sciences College of Arts and Science University of St. La Salle Negros Occidental Bacolod City Philippines Department of Chemical Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City Philippines Department of Electronics Engineering College of Engineering and Technology University of St. La Salle Negros Occidental Bacolod City Philippines Yo-Vivo Corporation Negros Occidental Bacolod City Philippines Department of Civil and Coastal Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL United States Faculty of Engineering Multimedia University Selangor Cyberjaya Malaysia Department of Computer Science Division of Science New York University Abu Dhabi Saadiyat Marina District Abu Dhabi United Arab Emirates

Personalized medicine (PM) promises to transform healthcare by providingtreatments tailored to individual genetic, environmental, and lifestylefactors. However, its high costs and infrastructure demands raise concernsabout exacerbating health disparities, especially between high-income countries(HICs) and low- and middle-income countries (LMICs). While HICs benefit fromadvanced PM applications through AI and genomics, LMICs often lack theresources necessary to adopt these innovations, leading to a wideninghealthcare divide. This paper explores the financial and ethical challenges ofPM implementation, with a focus on ensuring equitable access. It proposesstrategies for global collaboration, infrastructure development, and ethicalframeworks to support LMICs in adopting PM, aiming to prevent furtherdisparities in healthcare accessibility and outcomes. © 2024, CC BY.

关键词： Personalized medicine

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