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5th International Conference on Trends in Computational and Cognitive engineering, TCCE 2023

作者： Singh, Pushpendra Sarkar, Jhimli Dey, Parama Sarkar, Sounak Pattanaya, Anindya Nag, Sudipa Pramanik, Sudeshna Sahoo, Pathik Saxena, Komal Krishnanda, Soami Daya Dutta, Tanusree Ghosh, Subrata Bandyopadhyay, Anirban NIMS 1-2-1 Sengen Ibaraki Tsukuba3050047 Japan Department Electronics and Electrical Communication Engineering IIT Kharagpur West Bengal Kharagpur721302 India Department of Biosciences and Bioengineering Indian Institute of Technology Guwahati Assam781039 India Organizational Behavior and Human Resource Management Indian Institute of Management Ranchi834008 India Amity School of Applied Science Amity University Rajasthan Kant Kalwar NH-11C Jaipur Delhi Highway Rajasthan Jaipur303007 India Microwave Physics Laboratory Department of Physics and Computer Science Dayalbag Educational Institute Uttar Pradesh Agra282005 India Chemical Science and Technology Division CSIR-North East Institute of Science and Technology NEIST Assam Jorhat785006 India Uttar Pradesh Ghaziabad201002 India

ISBN: (纸本)9789819719228

The conventional EEG machine measures brain signal frequencies between 1 and 300 Hz on the scalp. By utilizing Fourier transform (FFT), it generates a 2D frequency profile. Our innovative EEG, known as Dodecanogram (DDG), operates in two modes. In the first mode, it detects a wide range of frequencies from 6 THz to 1 milliHz, creating a brain scan based on resonance. In the second mode, it uses picosecond pulses to capture potential surges, measuring their duration, intensity, and phase variation, revealing brain activity patterns. Both modes work simultaneously in the DDG device. To minimize environmental interference, we use interconnected DDG devices on eight human brains. The detected results from DDG show that DDG is a fundamental technology for understanding various mental states. Potential applications include neuro-disease diagnosis and exploring treatments involving electrical and electromagnetic pulses. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electromagnetic pulse

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Carrier confinement and alloy disorder exacerbate Auger-Meitner recombination in AlGaN ultraviolet light-emitting diodes

arXiv

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arXiv 2024年

作者： Pant, Nick Bushick, Kyle McAllister, Andrew Lee, Woncheol Van de Walle, Chris G. Kioupakis, Emmanouil Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Materials Science & Engineering University of Michigan Ann ArborMI48109 United States Department of Electrical Engineering & Computer Science University of Michigan Ann ArborMI48109 United States Materials Department University of California Santa BarbaraCA93106 United States

The quantum efficiency of AlGaN ultraviolet light-emitting diodes (LEDs) declines (droops) at increasing operating powers due to Auger-Meitner recombination (AMR). Using first-principles density-functional theory, we show that indirect AMR mediated by electron-phonon coupling and alloy disorder can induce bulk C coefficients as large as ∼10-31 cm6/s. Furthermore, we find that the confinement of carriers by polarization fields within quantum wells severely relaxes crystal-momentum conservation, which exacerbates the rate of AMR over radiative recombination by an order of magnitude relative to the bulk. This results in a striking decrease in quantum efficiency at high power. Suppressing polarization fields and jointly increasing the well width would greatly mitigate AMR and efficiency droop. Copyright © 2024, The Authors. All rights reserved.

关键词： Aluminum gallium nitride

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A Detailed Analysis of Qualitative and Quantitative Factors in Realization of 6G Communication

A Detailed Analysis of Qualitative and Quantitative Factors ...

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International Conference on Internet of Things: Systems, Management and Security

作者： Mohammad Alja’Afreh Ali Karime Sahel Alouneh Abdulmotaleb El Saddik Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) UAE School of Electrical Engineering and Computer Science University of Ottawa Canada Department of Electrical and Computer Engineering The Royal Military College of Canada Canada Cybersecurity Program College of Engineering AL AIN University UAE Computer Engineering Department German Jordanian University

Undoubtedly, the world has so far faced a pandemic which is reshaping daily lives and business activities. Even at current endemic stages, special focus on maintaining physical distancing norms for curbing the expeditious spread of the disease, many institutions, individuals and industries rely on communications networks or telecoms for ensuring service consistency to avoid complete termination of their business operations and other activities. This has put enormous pressure on mobile networks and communication systems thereby making the technology experts to think more about introducing rapid speed, vast coverage and high connectivity networks. The extensive application of fresh communication networks and enabling technologies have impelled the advent of 6G communication networks. As 6G is still in its inception phase, its complete realization requires a proper and high understanding of diverse quantitative and qualitative factors supporting its deployment. From this standpoint, this survey article intends to deeply explore 6G networks, their significance and prerequisites. This paper provides a succinct theoretical background of 6G technology, and reviews the diverse enabling technologies and existing works undertaken on core technologies. It explores the prevailing gaps in research for providing readers to gain information regarding challenges in perfect 6G network realization and implementation thus paving the road for a successful 6G vision.

关键词： 6G mobile communication Systematics Pandemics Roads Telecommunications Communication networks Security

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Exploring 3D Reconstruction with Drone Images: Advances and Challenges in Urban Environments

Exploring 3D Reconstruction with Drone Images: Advances and ...

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Annual Conference of Industrial Electronics Society

作者： Thiago João Miranda Baldivieso Taise Grazielle Da Silva Batista Fabio Suim Chagas Luiz Carlos Pacheco Rodrigues Velho Paulo Fernando Ferreira Rosa Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil State Institute of the Environment Inea/RJ Rio de Janeiro Brazil Department of Science and Industry Systems University of South-Eastern Norway Kongsberg Norway Department of Computer Graphics Institute for Pure and Applied Mathematics Rio de Janeiro Brazil Electrical Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, starting with image acquisition, followed by the application of specific photogrammetry software—both commercial and open-source—and concluding with a qualitative evaluation of the results.

关键词： Industrial electronics Three-dimensional displays Urban areas Aircraft Image reconstruction Photogrammetry Drones

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Electro-Polymerization Process with Double-Sided Electrodes for Supercapacitors

Electro-Polymerization Process with Double-Sided Electrodes ...

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International Flexible Electronics Technology Conference (IFETC)

作者： Nandu Koripally Lulu Yao Naresh Eedugurala Jason D. Azoulay Tse Nga Ng Department of Electrical and Computer Engineering University of California San Diego La Jolla CA USA Materials Science Engineering Program University of California San Diego La Jolla CA USA Chemisty Department Georgia Institute of Technology Atlanta GA USA

Supercapacitors are known for longer cycle life and faster charging rate compared to batteries. However, the energy density of supercapacitors requires improvement to expand their application space. To raise the energy density of redox supercapacitors, this work demonstrates electro-polymerization on both sides of electrodes to increase material loading, reduce overall device mass, and consequently increase the capacitance, power, and energy density of supercapacitors. We achieved an energy density of 1823 mWh kg -1 and a power density of 16.5 W kg -1 with a wide potential window of 3 V.

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AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min Taiwan International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei11529 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu30013 Taiwan National Chengchi University Department of Computer Science Taipei11605 Taiwan National Tsing Hua University Department of Electrical Engineering Institute of Communications Engineering Hsinchu300044 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei11529 Taiwan

The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intelligence-generated fake videos only utilize visual modality or audio modality. While some methods exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multimodal datasets of deepfake videos involving acoustic and visual manipulations, and are mostly based on convolutional neural networks with low detection accuracy. Considering that human cognition instinctively integrates multisensory information including audio and visual cues to perceive and interpret content and the success of transformer in various fields, this study introduces the audio-visual transformer-based ensemble network (AVTENet). This innovative framework tackles the complexities of deepfake technology by integrating both acoustic and visual manipulations to enhance the accuracy of video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multimodal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that the proposed model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. We also compare AVTENet against humans in detecting video forgery. The results show that AVTENet significantly outperforms humans. © 2016 IEEE.

关键词： audio-visual AVTENet Deepfake detection

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Deep and shallow data science for multi-scale optical neuroscience

arXiv

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arXiv 2024年

作者： Mishne, Gal Charles, Adam Halıcıoğlu Data Science Institute Department of Electrical and Computer Engineering the Neurosciences Graduate Program UC San Diego 9500 Gilman Drive La Jolla CA92093 United States Department of Biomedical Engineering Kavli Neuroscience Discovery Institute Center for Imaging Science Department of Neuroscience Mathematical Institute for Data Science Johns Hopkins University BaltimoreMD21287 United States

Optical imaging of the brain has expanded dramatically in the past two decades. New optics, indicators, and experimental paradigms are now enabling in-vivo imaging from the synaptic to the cortex-wide scales. To match the resulting flood of data across scales, computational methods are continuously being developed to meet the need of extracting biologically relevant information. In this pursuit, challenges arise in some domains (e.g., SNR and resolution limits in micron-scale data) that require specialized algorithms. These algorithms can, for example, make use of state-of-the-art machine learning to maximally learn the details of a given scale to optimize the processing pipeline. In contrast, other methods, however, such as graph signal processing, seek to abstract away from some of the details that are scale-specific to provide solutions to specific sub-problems common across scales of neuroimaging. Here we discuss limitations and tradeoffs in algorithmic design with the goal of identifying how data quality and variability can hamper algorithm use and dissemination. © 2024, CC BY.

关键词： Neuroimaging

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Study of ASIC Readout Used for Detectors in an MR Compatible, RF-Penetrable TOF-PET Insert

Study of ASIC Readout Used for Detectors in an MR Compatible...

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IEEE Symposium on Nuclear science (NSS/MIC)

作者： Qian Dong Salar Sajedi Ilaria Sacco Peter Fischer Craig S. Levin Departments of Electrical Engineering and Radiology Stanford University Stanford CA USA Departments of Radiology Stanford University Stanford CA USA Department of Computer Science Heidelberg University Baden-Württemberg Germany Department of Radiology Electrical Engineering Bioengineering and Physics Stanford University Molecular Imaging Program at Stanford (MIPS) Stanford CA USA

Developing positron emission tomography (PET) systems with high channel number has driven the need for application-specific integrated circuits (ASICs) owing to their compactness, multi-channel readout capability, and excellent time and energy resolution performance. They can also be quite flexible by employing field-programmable gate arrays (FPGAs) in the readout circuit. In particular, the ASIC+FPGA approach provides a high performance and compact solution for TOF-PET applications. ASICs serve functions of extracting time and energy information from analog SiPM signals, and an FPGA is employed for other application-specific requirements like on-board chip configuration, communication with data acquisition (DAQ) systems, and system monitoring. Based on this foundation, we developed TOF-capable detector modules for our second generation RF-penetrable PET insert. During our previous experiments, we found that different trigger and readout methods lead to different noise pattern and intensity in MR environment, and also have different singles count loss ratio. This paper aims to study and compare different readout configurations for our MR-compatible detectors. We studied four trigger and readout methods: hit-standard, frequent-standard, hit-bypass, and frequent-bypass, and compared their singles count loss ratios with both theoretical models and experimental results. For all four methods, the theoretical results matched the experimental results well. The two methods which used bypass mode performed better than those using the standard mode approach. With the most optimized trigger and readout method (hit-bypass), we achieved 1.2% singles count loss ratio at a 20 kcps count rate per channel.

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Inkwell: Design and Validation of a Low-Cost Open Electricity-Free 3D Printed Device for Automated Thin Smearing of Whole Blood

arXiv

引用

arXiv 2023年

作者： Nowak, Jerome Kothari, Anesta Li, Hongquan Pannu, Jaspreet Algazi, Dani Prakash, Manu Department of Mechanical Engineering United States Department of Bioengineering United States Department of Electrical Engineering United States Department of Medicine United States Department of Computer Science United States United States Woods Institute of the Environment United States Center for Innovation in Global Health United States Stanford University StanfordCA United States

Microscopy plays a crucial role in hematology and diagnosis of infectious diseases worldwide. For malaria alone, more than 200 million slides are read by manual microscopists every year. High quality thin blood smears are essential for subsequent microscopy examinations including malaria microscopy, but are hard to make in field settings. Current manual smearing methods lack consistency and often do not provide a uniformly dense mono-layer of red blood cells, even when prepared by trained experts. Existing devices for assisting in making thin smears are available but are limited by cost or complexity for wider use. Here we present Inkwell, a portable mechanical device capable of making high quality thin blood smears in field settings. Inkwell is simple, low-cost, does not use electricity, and requires minimal training prior to use. By utilizing passive dissipative dynamics of a spiral spring coupled to an air dashpot with a tunable valve - we demonstrate a highly tunable mechanism for constant velocity smears at prescribed angle. Inkwell is capable of producing high quality blood smears of tunable cell density with more than 12 million individually distinguishable red blood cells on a single slide. The current design, which exploits precision manufacturing of a 17 cents plastic syringe and a spring, can be printed on a standard 3D printer with overall unit cost of less than a few dollars in large quantities. We further present usability tests to confirm performance over 10,000 unit cycle operations with no degradation in quality of the smear and demonstrate ease of use with minimal training. Inkwell enhances the broader toolbox of open innovations in diagnostics for providing high quality medical care in low and medium resource settings. Combined with rise of 3D printing, Inkwell presents an alternative to traditional centralized manufacturing and opens up distributed manufacturing of medical diagnostics in global context. © 2023, CC BY.

关键词： 3D printing

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A Novel Resource Allocation in Software-Defined Networks for IoT Application

A Novel Resource Allocation in Software-Defined Networks for...

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International Conference on Software, Telecommunications and computer Networks (SoftCOM)

作者： Alexandre Ladeira de Sousa Ogobuchi Daniel OKey Renata Lopes Rosa Muhammad Saadi Demostenes Zegarra Rodriguez Department of Computer Science Federal University of Lavras Lavras Minas Gerais Brazil Graduate Program in Information Engineering Federal University of ABC Santo Andre Sao Paulo Brazil Department of Electrical Enginnering University of Central Punjab Punjab Pakistan Computer Science Department Federal University of Lavras Lavras Minas Gerais Brazil

The rapid proliferation of Internet of Things (IoT) devices has posed significant challenges for network resource allocation and management. In this paper, we propose a novel methodology for efficient resource allocation in Software-Defined Networks (SDNs) to meet the unique requirements of IoT applications. Our approach leverages the flexibility and programmability of SDN to dynamically allocate network resources based on the specific needs of IoT devices. Our proposal combines reinforcement learning with dynamic resource allocation, demonstrating its effectiveness in optimizing resource allocation and enhancing network performance. The results highlight the potential of our approach to addressing the resource challenges in SDN-based IoT environments. The proposed method obtains results superior to 30% of throughput in comparison to a traditional resource allocation in SDN to IoT applications.

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