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Submicron Memtransistors Made from Monocrystalline Molybdenum Disulfide

ACS Nano 2024年第9期18卷 6936-6945页

作者： Yang, Shu-Ting Yang, Tilo H. Liang, Bor-Wei Lo, Han-Chieh Chang, Wen-Hao Lin, Po-Yen Su, Ching-Yuan Lan, Yann-Wen Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei116 Taiwan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Taiwan Semiconductor Research Institute National Applied Research Laboratories Hsinchu300091 Taiwan Department of Physics National Taiwan Normal University Taipei116 Taiwan Institute of Cellular and Organismic Biology Academia Sinica Taipei115 Taiwan Graduate Institute of Energy Engineering National Central University Taoyuan320317 Taiwan

Multiterminal memtransistors made from two-dimensional (2D) materials have garnered increasing attention in the pursuit of low-power heterosynaptic neuromorphic circuits. However, existing 2D memtransistors tend to necessitate high set voltages (>1 V) or feature defective channels, posing concerns regarding material integrity and intrinsic properties. Herein, we present a monocrystalline monolayer MoS2 memtransistor designed for operation within submicron regimes. Under reverse drain bias sweeps, our experiments reveal memristive behavior within the device, further controllable through modulation of the gate terminal. This controllability facilitates the consistent manifestation of multistate memory effects. Notably, the memtransistor behavior becomes more significant as the channel length diminishes, particularly with channel lengths below 1.6 μm, showcasing an increase in the switching ratio alongside a decrease in the set voltage with the decreasing channel length. Our optimized memtransistor demonstrates the ability to exhibit individual resistance states spanning 5 orders of magnitude, with switching drain voltages of approximately 0.05 V. To elucidate these findings, we investigate hot carrier effects and their interplay with oxide traps within the HfO2 dielectric. This work highlights the importance of memtransisor behavior in highly scaled 2D transistors, particularly those featuring low contact resistances. This understanding holds the potential to tailor memory characteristics essential for the development of energy-efficient neuromorphic devices. © 2024 American Chemical Society.

关键词： Molybdenum disulfide

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Impact of Temporal Precision on Speech Synthesis Accuracy From Electrocorticographic Brain Signals

Impact of Temporal Precision on Speech Synthesis Accuracy Fr...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Rabbani, Qinwan Fifer, Matthew S. Crone, Nathan E. Moro-Velazquez, Laureano Department of Electrical and Computer Engineering Johns Hopkins University Baltimore United States Research and Exploratory Development Department Johns Hopkins University Applied Physics Laboratory Laurel United States Department of Neurology Johns Hopkins Hospital Baltimore United States

ISBN: (纸本)9798350368741

Accurately time-aligned spectral targets are essential for training electrocorticographic (ECoG) brain-computer interfaces (BCIs) intended for real-time speech output. This alignment is particularly challenging with "silent speech, " in which speech occurs without phonation, or in the extreme, without articulation. Crafting suitably precise targets for silent speech is complex and error-prone due to multiple sources of temporal imprecision. We investigated how these temporal inaccuracies impact deep neural network performance in synthesizing speech from a BCI clinical trial participant who retained some speech capability. By simulating silent speech conditions through distortions in known acoustic target timings, we observed significant performance degradations at both phonetic and syllabic timescales. Accuracy-based measures offered a more reliable assessment of intelligibility than traditional metrics like the short-time objective intelligibility index, which may overestimate performance in low-precision contexts. These results underscore the need for advanced alignment techniques with precise phonetic and syllabic guarantees for silent speech BCIs focused on providing immediate output. © 2025 IEEE.

关键词： brain-computer interface deep neural network electrocorticography speech synthesis temporal alignment

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ON NON-REFLECTIVE BOUNDARIES FOR OUTDOOR SOUND PROPAGATION USING THE DISCONTINUOUS GALERKIN METHOD 10

ON NON-REFLECTIVE BOUNDARIES FOR OUTDOOR SOUND PROPAGATION U...

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10th Convention of the European Acoustics Association, EAA 2023

作者： Feriani, Sophia Julia Engsig-Karup, Allan P. Pind, Finnur Cosnefroy, Matthias Jeong, Cheol-Ho Acoustic Technology Department of Electrical and Photonics Engineering Technical University of Denmark Denmark Scientific Computing Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Treble Technologies Hafnartorg Kalkofnsvegur 2 Reykjavík101 Iceland

ISBN: (纸本)9788888942674

In environmental acoustics, sound propagates in open air and can be mathematically modelled in terms of a semi-infinite domain. The calculations for accurate numerical solutions for outdoor acoustics are computationally heavy when the chosen computation domain is large enough to fulfil the Sommerfeld radiation condition. To lower the computational cost, the domain must therefore be truncated to not significantly impact the numerical solution inside the domain and allow outgoing acoustic waves to leave the domain undisturbed. Various radiation conditions (sometimes considering the wind) have been developed to achieve this goal such as the Perfectly Matched Layer method. The aim of this study is to compare the accuracy of different non-reflecting boundaries using the high-order nodal discontinuous Galerkin finite element method (DG-FEM) for the case of an acoustic pulse propagating in a static and moving medium in an unstructured mesh. For each boundary treatment, the tunable parameters of the methods are defined to balance accuracy and computational cost. © 2023 S.J. Feriani et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

关键词： Galerkin methods

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Tell What You Hear From What You See - Video to Audio Generation Through Text

arXiv

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arXiv 2024年

作者： Liu, Xiulong Su, Kun Shlizerman, Eli Department of Electrical & Computer Engineering University of Washington Seattle United States Department of Applied Mathematics University of Washington Seattle United States

The content of visual and audio scenes is multi-faceted such that a video stream can be paired with various audio streams and vice-versa. Thereby, in video-to-audio generation task, it is imperative to introduce steering approaches for controlling the generated audio. While Video-to-Audio generation is a well-established generative task, existing methods lack such controllability. In this work, we propose VATT, a multi-modal generative framework that takes a video and an optional text prompt as input, and generates audio and optional textual description (caption) of the audio. Such a framework has two unique advantages: i) Video-to-Audio generation process can be refined and controlled via text which complements the context of the visual information, and ii) The model can suggest what audio to generate for the video by generating audio captions. VATT consists of two key modules: VATT Converter, which is an LLM that has been fine-tuned for instructions and includes a projection layer that maps video features to the LLM vector space, and VATT Audio, a bi-directional transformer that generates audio tokens from visual frames and from optional text prompt using iterative parallel decoding. The audio tokens and the text prompt are used by a pretrained neural codec to convert them into a waveform. Our experiments show that when VATT is compared to existing video-to-audio generation methods in objective metrics, such as VGGSound audiovisual dataset, it achieves competitive performance when the audio caption is not provided. When the audio caption is provided as a prompt, VATT achieves even more refined performance (with lowest KLD score of 1.41). Furthermore, subjective studies asking participants to choose the most compatible generated audio for a given silent video, show that VATT Audio has been chosen on average as a preferred generated audio than the audio generated by existing methods. VATT enables controllable video-to-audio generation through text as well as suggest

关键词： Vector spaces

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Blind Equalization using a Variational Autoencoder with Second Order Volterra Channel Model

arXiv

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arXiv 2024年

作者： Nielsen, Søren Føns Zibar, Darko Schmidt, Mikkel N. The Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark The Department of Electrical and Photonics Engineering Technical University of Denmark Denmark

Existing communication hardware is being exerted to its limits to accommodate for the ever increasing internet usage globally. This leads to non-linear distortion in the communication link that requires non-linear equalization techniques to operate the link at a reasonable bit error rate. This paper addresses the challenge of blind non-linear equalization using a variational autoencoder (VAE) with a second-order Volterra channel model. The VAE framework’s costfunction, the evidence lower bound (ELBO), is derived for real-valued constellations and can be evaluated analytically without resorting to sampling techniques. We demonstrate the effectiveness of our approach through simulations on a synthetic Wiener-Hammerstein channel and a simulated intensity modulated direct detection (IM/DD) optical link. The results show significant improvements in equalization performance, compared to a VAE with linear channel assumptions, highlighting the importance of appropriate channel modeling in unsupervised VAE equalizer frameworks. © 2024, CC BY.

关键词： Optical links

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Advancing Text-to-Image Generation: A Comparative Study of StyleGAN-T and Stable Diffusion 3 under Neutrosophic Sets

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Neutrosophic Sets and Systems 2025年 85卷 784-800页

作者： Sadek, Mohamed G. Hassan, A.Y. Diab, Tamer O. Abdelhafeez, Ahmed Benha Engineering Faculty Egypt Electrical Engineering Department Benha Engineering Faculty Benha University 13511 Egypt Computer Science Department Faculty of Information Systems and Computer Science October 6th University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan

Recent advances in generative models have revolutionized the technology employed for image synthesis quite significantly, and two paradigms—GANs and diffusion-based models—are leading the pack of innovation. This paper outlines an extensive comparison and analysis of some of the best models across both paradigms, namely StyleGAN-T, DF-GAN, AttnGAN, and BigGAN on the GAN side and Stable Diffusion 3 (SD3), DALL·E 3, Midjourney v6, and Imagen 2 on the diffusion side. We systematically inspect the architectural design, training protocols, text-conditioning processes, and domain adaptability of each model, highlighting how they address text-to-image generation challenges differently. Through qualitative and quantitative measurements—such as FID, CLIP Score, human preference surveys, and compositional accuracy, the work reveals performance tradeoffs concerning speed, control, creativity, semantic alignment, and photorealism. We use the Neutrosophic Set model to select the best model based on these evaluation matrices. We have different scores for each model based on evaluation matrices. So, the neutrosophic set is used to overcome the uncertainty information. We use the COPRAS method to rank the models and select the best one based on the evaluation matrix weights. © 2025, University of New Mexico. All rights reserved.

关键词： Photointerpretation

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Hybrid Machine Learning Algorithms for Optimal Diagnosis of Heart Disease with Feature Analysis

Hybrid Machine Learning Algorithms for Optimal Diagnosis of ...

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2023 International Conference on Power, Instrumentation, Energy and Control, PIECON 2023

作者： Ahmad, Ghulab Nabi Fatima, Hira Shafiullah Haris, Mohammad Institute of Applied Sciences Mangalayatan University Aligarh India BRA K.C.T.C College Raxual Bihar University Department of Mathematics Muzaffarpur India Institute of Technology and Management Department of Computer Science and Engineering Aligarh India

ISBN: (纸本)9798350399769

Timely prediction of heart disease and its cause is the most challenging issue in medical science. This paper uses various machine learning algorithms such as Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Naive Bayes, K-Nearest Neighbourhood, and K-fold cross-validation are used to predict heart diseases. The system uses a K-fold cross-validation technique to enhance the accuracies of algorithms. The UCI Kaggle Cleveland heart disease datasets is used to analyse the performance of the models. It is found in the experiment that the training accuracy of K-Nearest Neighbour is 88.52%, and Recall is 93.30%. The Random Forest produced the highest and most comparable Receiver Operating Characteristics Curve accuracy. Moreover, the experimental results of the recommended techniques are compared with previous heart disease prediction studies, and it is found that among the suggested technique, the performance of K-Nearest Neighbour is best. The fundamental goal of this study is to design a novel and distinctive model-creation approach for resolving practical issues. © 2023 IEEE.

关键词： Adaptive boosting

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Evaluating the spike in the symptomatic proportion of SARS-CoV-2 in China in 2022 with variolation effects:a modeling analysis

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Infectious Disease Modelling 2024年第2期9卷 601-617页

作者： Salihu S.Musa Shi Zhao Ismail Abdulrashid Sania Qureshi Andrés Colubri Daihai He Department of Genomics and Computational Biology University of Massachusetts Chan Medical SchoolWorcesterMA01605USA Department of Applied Mathematics Hong Kong Polytechnic UniversityHong Kong SARChina Department of Mathematics Aliko Dangote University of Science and TechnologyKanoNigeria School of Public Health Tianjin Medical UniversityTianjin300070China School of Finance and Operations Management The University of Tulsa800 South Tucker Dr.TulsaOK74104USA Department of Basic Sciences and Related Studies Mehran University of Engineering and Tech.JamshoroPakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon

Despite most COVID-19 infections being asymptomatic,China's Mainland had a high increase in symptomatic cases at the end of *** this study,we examine China's sudden COVID-19 symptomatic surge using a conceptual SIR-based *** model considers the epidemiological characteristics of SARS-CoV-2,particularly variolation,from non-pharmaceutical intervention(facial masking and social distance),demography,and disease mortality in China's *** increase in symptomatic proportions in China may be attributable to(1)higher sensitivity and vulnerability during winter and(2)enhanced viral inhalation due to spikes in SARS-CoV-2 infections(high transmissibility).These two reasons could explain China's high symptomatic proportion of COVID-19 in December *** study,therefore,can serve as a decision-support tool to enhance SARS-CoV-2 prevention and control ***,we highlight that facemask-induced variolation could potentially reduces transmissibility rather than severity in infected ***,further investigation is required to understand the variolation effect on disease severity.

关键词： SARS-CoV-2 Epidemic Epidemiological modeling Reproduction number Variolation

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Climate Change-based Urban Geographical Regions Planning: Sustainable Application Using Artificial Intelligence

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Remote Sensing in Earth Systems Sciences 2024年第1期8卷 98-107页

作者： Begum, Khaja Shahini Ambala, Srinivas Kumar, Bathina Rajesh Yajid, Mohd Shukri Ab Muniyandy, Elangovan Haldar, Ritwik Department of English Koneru Lakshmaiah Education Foundation AP Vaddeswaram India Department of Computer Engineering Pimpri Chinchwad College of Engineering Pune India Management and Science University Selangor Shah Alam Malaysia Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602 105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Avadi 600 062 India

From the level of individual creatures to that of ecosystems, where all species are components of intricate webs of interactions in the natural world, climate change can have a cascade impact. Though their full promise for mitigating climate change is still unrealised, artificial intelligence and machine learning are revolutionising scientific fields. Despite making up a small percentage of the planet’s surface, the enormous population of urban areas has a huge impact on climate change. Nevertheless, our understanding of the consequences of urbanisation on ecosystems and the climate is still lacking. This research proposes a novel technique in urban geographical region planning and climate change detection using a machine learning model. Here, the input has been collected as urban region geographical region changes analysis with climate change dataset and processed for noise removal and normalisation. Then this image has been segmented using a region-based graph cut active contour neural network, and features have been extracted using a deep transfer convolutional Gaussian model. Experimental analysis has been carried out in terms of detection accuracy, random precision, AUC, F1-score, and recall. The proposed model attained detection accuracy of 97%, random precision of 94%, AUC of 96%, F1-score of 95%, and recall of 98%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Active contour Climate change detection Graph cut Machine learning Urban geographical region

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Analyzing the function of smart security in the context of the internet of things 3

Analyzing the function of smart security in the context of t...

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3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Naidu, K. Venkatagurunatham Pillai, Anchu Krishnan Rajaprabha, C.E. Sharma R, Rajesh Ul Islam, Atowar Khasimbee, Shaik Dr M.G.R Educational and Research Institute Dept. of Computer Science and Engineering Chennai India Xavier Institute of Engineering Applied Science and Humanities Maharashtra Mumbai India Hindusthan Institute of Technology Department of Computer Science and Engineering Coimbatore India Adama Science and Technology University School of Electrical Engineering and Computing Department of Computer Science and Engineering Nazareth1888 Ethiopia University of Science and Technology Meghalaya Department of Computer Science and Electronics Meghalaya Baridua793101 India Aditya College of Engineering Department of Computer Science and Engineering Andhra Pradesh Surampalem533437 India

ISBN: (纸本)9798350399264

Technology is getting better day by day and human beings are using the latest technology possible for their needs and safety. Many devices have been invented that use the internet and with this human safety issues are also taken care of up to a great extent. GPS tracking devices, SHE (Society Harnessing Equipment), AESHS (Advanced Electronic System for Human Safety), ILA Systems are one of the most useful applications and devices that are used for human safety. Human safety and especially the safety of girls have become an emerging and sensitive issue in the present world scenario. This article deals with the role of the Internet of Things in advancing smart security. The issues are taken care of with the help of these upgraded devices that are easily accessible from a remote location with an internet connection. © 2023 IEEE.

关键词： Internet of things

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