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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Khadija Attouri Majdi Mansouri Mansour Hajji Abdelmalek Kouadri Kais Bouzrara Hazem Nounou Institut Superieur des Sciences Appliques et de Technologie de Kasserine Kairouan University Tunisia The Department of Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Signals and Systems Laboratory Institute of Electrical and Electronics Engineering University M Hamed Bougara of Boumerdes Boumerdes Algeria The Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir Tunisia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The key idea behind this study is to integrate a moving window dynamic PCA (MW-DPCA) methodology for fault detection within the Tennessee Eastman process (TEP) into a low-computational power system, the Raspberry Pi 4 card, for real-time application. Indeed, the paramount importance of real-time fault detection (FD) in intricate industrial processes presents a critical challenge. Various data-driven techniques have been developed to ensure safety, maintain operational stability, and optimize productivity in such processes. Principal Component Analysis (PCA) is a fundamental data-driven technique that utilizes dimensionality reduction to extract the most informative features from high-dimensional data, simplifying analysis and potentially revealing underlying fault patterns. However, PCA primarily focuses on static relationships and may miss crucial temporal dynamics for fault identification. This is where dynamic PCA (DPCA) excels. By incorporating lagged values of variables, DPCA captures the temporal evolution of features, enabling a more comprehensive understanding of process behavior and improving the detection of faults involving dynamic changes. In order to address the stochastic measurements, a moving average filter tool is also employed. The results obtained and the successful realization of this implementation demonstrate the adaptability of the approach and pave the way for its seamless integration into practical industrial applications.

关键词： Fault detection Power system dynamics Power system stability Feature extraction electrical fault detection Real-time systems Stability analysis Robustness Safety Principal component analysis

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Fully Customizable, Low-Cost, Multi-Contact Nerve Cuffs for Spatially Selective Neuromodulation

Fully Customizable, Low-Cost, Multi-Contact Nerve Cuffs for ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Morgan Riley FNU Tala Katherine J. Johnson Benjamin C. Johnson Biomedical Engineering Doctoral Program Boise State University Boise ID USA Dept. of Electrical and Computer Engineering Boise State University Boise ID USA Office of Research Compliance Boise State University Boise ID USA

Selective neuromodulation of peripheral nerves is an emerging treatment for neurological diseases that are resistant to traditional drug therapy. While nerve cuffs with multichannel stimulation can be made by many varied methods, they usually require specialized microfabrication or additive manufacturing equipment. A truly low-cost and effective method of creating a custom cuff has not been accessible to researchers to prototype new methodologies and therapies in acute studies. Here, we present an inexpensive, highly repeatable method to create multi-contact nerve cuffs that require a simple postproduction PEDOT:PSS coating to improve the tissue/electrode interface. We demonstrate spatially selective neuromodulation with the proposed cuff design on the rat sciatic by preferentially activating the tibialis anterior (TA) and the lateral gastrocnemius (LG) in longitudinal and transverse stimulation patterns. This demonstrates that the proposed cuff fabrication method was not only effective for selective neuromodulation, but it is also significantly lower in cost, fully-customizable, and easily manufactured for future selective neuromodulation studies.

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SoC-Oriented Implementation of Machine Learning Based Breast Cancer Classification Algorithm

SoC-Oriented Implementation of Machine Learning Based Breast...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Abdelrahman Saeed Ayman Tawfik Hassan Mostafa Ahmed Hussein Khalil Electronics and Communications Engineering Department Cairo University Giza Egypt Department of Electrical and Computer Engineering Ajman University United Arab Emirates (UAE) University of Science and Technology Nanotechnology and Nanoelectronics Program Zewail City of Science and Technology Giza Egypt

Convolutional Neural Networks (CNN) have drawn the attention of researchers in the medical imaging field. Many researchers have exploited CNN for breast cancer detection. This study provides an Internet of Things (IoT) friendly implementation of CNN for breast cancer detection. To achieve faster time to Market, Deep-learning Processing Unit (DPU) on Field programmable Gate Array (FPGA) is adopted for the CNN hardware implementation. CNN inference on the proposed system achieves a 1.6x speed-up factor and 91.5% reduction in energy consumption compared to the conventional general-purpose multi-core Central Processing Unit (CPU).

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Real-Time Fault Detection and Diagnosis Method for Industrial Chemical Tennessee Eastman Process

Real-Time Fault Detection and Diagnosis Method for Industria...

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International Conference on Control, Decision and Information Technologies (CoDIT)

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The accurate detection and diagnosis of faults are critical for maintaining optimal operation and ensuring the reliability of industrial processes. Notably, the topic of online fault detection and diagnosis has recently presented a significant challenge. This work mainly deploys a neural network technique for the comprehensive detection and diagnosis of faults within the Tennessee Eastman Process (TEP) on a low-computational power system, the Raspberry Pi board. The devolved methodology showcases a remarkable level of accuracy (94.50%) in diagnosing the various TEP faults, affirming its robustness and effectiveness. To elevate the practical applicability of the proposed approach, a meticulous investigation into the implementation of the suggested approach on a Raspberry Pi 4 card was undertaken. The successful realization of this implementation not only highlights the adaptability of the approach but also paves the way for its seamless integration into practical industrial applications.

关键词： Accuracy Embedded systems Fault detection Neural networks electrical fault detection Real-time systems Robustness Power system reliability Information technology Chemicals

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Sentiment Analysis of Hashtag Activism on Social Media Twitter

Sentiment Analysis of Hashtag Activism on Social Media Twitt...

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computer Science, Information Technology and engineering (ICCoSITE), International Conference on

作者： Sidharta Sidharta Yaya Heryadi Lukas Lukas Wayan Suparta Yulyani Arifin Computer Science Department BINUS Graduated Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Currently, the performance of the police in Indonesia is often in the spotlight of the public with cases that occur, both on a national and regional scale, including personal experiences who also feel disappointed with the performance of the police. The cases, such as the rape of three children by a biological father in East Luwu, and the barrage of other cases that have occurred, in their handling have left the public disappointed, giving rise to the hashtag percumlaporpolisi on social media, especially on twitter. This hashtag became trending and was widely responded to by the public. Using free hashtag keywords, tweet data is collected using Twitter’s API for sentiment analysis. The datasets obtained from the crawling results is the latest data with a total of 100 datasets. This study applies the naïve bayes algorithm using textblob which aims to determine the value of polarity and subjectivity. From the results of the analysis carried out, the words that appear most often are useless police, police chief, and policeman. While the results of the sentiment analysis that has been carried out are 40 percent positive sentiment, 40 percent are neutral sentiment and 10 percent are negative sentiment from the hashtags used. From these results, according to the keywords used, the percentage of negative sentiment should be greater than positive and neutral sentiment. It is necessary to conduct a more in-depth study related to the model used in the next research.

关键词： computer science Sentiment analysis Pediatrics Law enforcement Social networking (online) Blogs Biology

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Gate Stack engineering in n-type (−201) $\upbeta-\text{Ga}_{2}\mathrm{O}_{3}$ Transistors

Gate Stack Engineering in n-type (−201) $\upbeta-\text{Ga}_...

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International Conference on Emerging Electronics (ICEE)

作者： Vishal Khandelwal Saravanan Yuvaraja Chuanju Wang Dhanu Chettri Xiaohang Li Advanced Semiconductor Laboratory Electrical and Computer Engineering Program CEMSE division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

A systematic study of Al 2 O 3 and SiO 2 / Al 2 O 3 dielectric on p-Ga2O3 is carried out including the effect of the forming gas annealing. Capacitance-voltage (C-V) curve of the Al 2 O 3 /Ga 2 O 3 gate stack shows a large hysteresis and sweep-to-sweep C-V shift compared to SiO 2 /Al 2 O 3 /Ga 2 O 3 case, which suggests SiO2 interlayer reduces the defect density in Al 2 O 3 /Ga 2 O 3 gate stack. In addition, forming gas annealing further suppresses the interface and border traps density in both Al 2 O 3 /Ga 2 O 3 and SiO 2 / Al 2 O 3 /Ga 2 O 3 gate stacks. A thin film transistor (TFT) with annealed SiO 2 / Al 2 O 3 dielectric has an on-off ratio of ~106, a subthreshold swing (SS) of ~ 0.75 V/decade, and a hysteresis width $(\mathrm{V}_{\text{Hy}})$ of~ 0.5 V compared to an on-off ratio of~105, a SS of ~1.2 V/decade, and a VHy of ~2 V in the controlled TFT with unannealed Al 2 O 3 dielectric. The increased on-off ratio by one order, reduced SS by > 400 mV/decade, and $\mathrm{V}_{\text{Hy}}$ by >1.5 V is attributed to decreased interface and border traps in annealed SiO 2 / Al 2 O 3 compared to unannealed Al 2 O 3 /Ga 2 O 3 gate stack. Interface trap density is calculated by $\mathbf{V}_{\text{Hy}}$ of the transistor, which showed a five-time reduction in annealed SiO 2 / Al 2 O 3 /Ga 2 O 3 compared to the unannealed A;2O3/Ga 2 O 3 gate stack. This study suggests that annealed SiO 2 / Al 2 O 3 dielectric stack is promising for $\boldsymbol{\upbeta}-\text{Ga}_2 \mathrm{O}_3$ transistors.

关键词： Silicon compounds Electron traps Annealing Capacitance-voltage characteristics Logic gates Dielectrics Thin film transistors

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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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Assessment of force control improvement induced by sinusoidal vibrotactile stimulation in dominant and non-dominant hands

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Research on Biomedical engineering 2021年第1期37卷 95-103页

作者： Germer, Carina Marconi Moreira, Luciana Sobral Elias, Leonardo Abdala Department of Electronics and Biomedical Engineering School of Electrical and Computer Engineering University of Campinas CampinasSP Brazil Neural Engineering Research Laboratory Center for Biomedical Engineering University of Campinas CampinasSP Brazil Cellular and Structural Biology Graduate Program Institute of Biology University of Campinas CampinasSP Brazil Faculty of Biological Sciences Center for Life Sciences Pontifical Catholic University of Campinas CampinasSP Brazil

Purpose: Vibrotactile stimulation has been shown to improve sensorimotor integration in the central nervous system, thereby enhancing motor performance in several conditions. Here we aim to address two questions: (1) Would lateral asymmetries yielding handedness influence the force control improvement induced by sinusoidal vibrotactile stimulation? (2) Does the force control improvement depend on finding an optimum stimulus intensity? Methods: Eleven participants performed a visually guided force-matching task, while different intensities of sinusoidal vibrations were applied to the index finger skin. Tasks consisted of abductions of the index fingers of dominant and non-dominant hands at 5% of their maximal voluntary contractions. The force coefficient of variation (CoV) in the condition without vibration was used as the reference (control) for later comparison with five vibration intensities. Also, force CoV in the control condition was compared with those obtained from the optimal vibration selected either from both hands or from a single hand (the one that started the experiment). Results: Despite the known sensory asymmetries in cortical and spinal circuits, handedness did not significantly influence the improvement of force control induced by sinusoidal vibrotactile stimulation during low-intensity contractions. Moreover, there was a significant reduction in force variability irrespective of the criteria used to select the vibration intensity. Conclusion: These findings add to the current knowledge on the effects of sinusoidal vibrotactile stimulation on force control and have potential implications for the development of wearable motor enhancer devices. © 2020, Sociedade Brasileira de Engenharia Biomedica.

关键词： Force control

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Sum-Rate Maximization for Intelligent Reflecting Surface Assisted MIMO SWIPT Systems

Sum-Rate Maximization for Intelligent Reflecting Surface Ass...

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Future Telecommunication Technologies (SOFTT), Symposium on

作者： H. J. Liong C. W. R. Chiong Lenin Gopal Filbert H. Juwono Department of Electrical and Computer Engineering Curtin University Malaysia Miri Sarawak Malaysia Department of Electrical and Electronic Engineering University of Southampton Malaysia Eko Galleria Nusajaya Johor Malaysia Computer Science Program University of Southampton Malaysia Eko Galleria Nusajaya Johor Malaysia

ISBN: (纸本)9781665455985

Intelligent reflecting surface (IRS) has recently stimulated an upsurge of research interest due to its capability of enhancing the spectral and energy efficiencies for future sixth generation (6G) wireless communication systems. This motivates the integration of IRS into simultaneous wireless information and power transfer (SWIPT) systems to improve the performance of energy harvesting and information de-coding. To unleash the full potential of IRS and achieve high sum-rate, the optimal joint transmitter precoding and reflective beamforming design is crucial yet challenging to solve. The issue has not been well investigated and the solution remains elusive. Hence, this research aims to jointly optimize the transmitter precoding and reflective beamforming matrices for IRS-assisted multi-user multiple-input multiple-output (MIMO) SWIPT systems under quality of service (QoS) constraints. Simulation results demonstrate the effectiveness of IRS in enhancing the system performance.

关键词： Wireless communication Transmitters Array signal processing Precoding System performance Simulation Quality of service

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Effect of laser irradiation on the tribological properties of RF-sputtered nickel oxide (NiO) thin films

arXiv

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arXiv 2023年

作者： Itapu, Srikanth Borra, Vamsi Li, Frank X. Cortes, Pedro Kumar, Mohit Hemanth Electrical and Computer Engineering Program College of STEM Rayen School of Engineering Youngstown State University YoungstownOH44555 United States Department of Electronics & Communication Engineering Alliance University Bengaluru562106 India Chemical Engineering Program College of STEM Rayen School of Engineering Youngstown State University YoungstownOH44555 United States Department of Mechanical Engineering Alliance University Bengaluru562106 India

The present work aims at investigating the effect of laser irradiation on the tribological properties of RF-sputtered NiO thin films deposited on industrial grade aluminum substrate. A semiconductor laser based on Nd:YAG operating at its 4th harmonic wavelength, λ = 266nm with varying laser fluence and spot size of about 5 µm is irradiated on the NiO film. The localized heating allows for smoothening of the NiO film along with contributions to the changes in the stoichiometry of NiO (reduction of excess oxygen). In particular, the effects of tuning laser fluence and the subsequent tribology tests pertaining to the coefficient of friction variations for tribological tests are discussed. © 2023, CC BY.

关键词： Tribology

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