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Synergizing Deep Belief Networks and Multi-Layer Perceptrons for Advanced Facial Expression Identification: A Leap in Deep Learning Applications 9

Synergizing Deep Belief Networks and Multi-Layer Perceptrons...

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9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Sharada, K. Anandhan, K. Jeevanandam, Prabahar Mohanavel, V. Naik, B. Ravi Kannan, Sathish Department of Computer Science And Engineering Visakhapatnam India Gitam University Department of Computer Science And Engineering Bengaluru India Park College of Engineering And Technology Department of Mechanical Engineering Coimbatore Kaniyur641659 India Bharath Institute of Higher Education And Research Centre For Materials Engineering And Regenerative Medicine Tamil Nadu Chennai600073 India Chandigarh University Department of Mechanical Engineering Punjab Mohali140413 India St. Martin's Engineering College Department of Mechanical Engineering Telangana Secunderabad India Saveetha Institute of Medical And Techinical Sciences Saveetha School of Engineering Department of Vlsi Microelectronics Tamilnadu Chennai602105 India

ISBN: (纸本)9798350394474

Deep learning, a relatively recent breakthrough in machine learning, has ignited immense interest and applications across diverse fields, including but not limited to signal processing, computer vision and pattern recognition. Within this realm, deep belief networks (DBNs) stand out for their remarkable capacity for unsupervised feature learning. In our research, we introduce an innovative deep learning-based approach for the task of facial expression identification. This approach involves the integration of DBNs with a multi-layer perceptron (MLP), thereby leveraging the complementary strengths of these two neural network architectures. DBNs excel in autonomously extracting meaningful features from raw data, making them invaluable for tasks where feature engineering can be a bottleneck. On the other hand, MLPs are renowned for their ability to perform complex classification tasks effectively. The unsupervised feature learning capabilities of DBNs and the classification ability of MLPs are combined in one single framework. The experimental findings we obtained show that the suggested strategy outperforms other contemporary classification strategies. MLP, sparse representation, nearest subspace, Closest neighbor, and support vector machine were some of the other categorization methods we compared ours to. Our combined method achieved superior results in both scenarios, demonstrating its promise as a reliable and efficient approach to face emotion recognition. In especially for human emotion analysis and computer vision tasks, this study offers a major step forward in the realm of deep learning applications. © 2024 IEEE.

关键词： Multilayer neural networks

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Design and Development of a Touch Free Smart Home Controlling System Based on Virtual Reality (VR) Technology

Design and Development of a Touch Free Smart Home Controllin...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Devi, S. Rukmani Raghi, K.R. Priya, S. Geetha Sathi, G. Kumar, Sarva Naveen Dinesh, M. Saveetha College of Liberal Arts and Sciences Simats Deemed to Be University Department of Computer Science Tamil Nadu Chennai India St.Joseph's College of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India R.M.D. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Tamil Nadu Chennai India Mlr Institute of Technology Department of Electronics and Communication Engineering Hyderabad India Saveetha University Department of Vlsi Microelectronics Tamil Nadu Chennai India

ISBN: (纸本)9798350375237

The Touch-Free Smart Home Controlling System based on Virtual Reality (VR) Technology represents an innovative approach to home automation, leveraging the immersive capabilities of VR to provide users with seamless and intuitive control over their smart home environment without the need for physical touch. This system integrates VR headsets with motion sensors, depth cameras, and gesture recognition technology to enable users to navigate and interact with a virtual representation of their home environment. Smart home devices such as lights, thermostats, door locks, and entertainment systems are interconnected and controlled through the VR interface, offering users a compelling and immersive way to manage their living space. The central hub acts as the backbone of the system, facilitating communication between the VR interface, sensors, and smart home devices. Performance metrics such as response time, latency, throughput, and power consumption are monitored to ensure optimal system operation. Security measures including user authentication and data encryption are implemented to protect user privacy and prevent unauthorized access. The Touch-Free Smart Home Controlling System based on VR Technology not only enhances convenience and accessibility but also represents a significant step forward in the evolution of smart home automation towards more intuitive and immersive user experiences.. © 2024 IEEE.

关键词： Gesture recognition

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A Double-Side Self-Tuning IPT Converter Immune to Parameters Variation Under Misalignment Condition 50

A Double-Side Self-Tuning IPT Converter Immune to Parameters...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Zou, Bowei Huang, Zhicong Iam, Io-Wa Chi-Seng, Lam Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangzhou China State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau China Institute of Microelectronics University of Macau China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China

ISBN: (纸本)9781665464543

For inductive power transfer (IPT) systems, the loosely coupled transformer (LCT) is a crucial component. Variations in the air gap can lead to fluctuations in the parameters of the LCT, such as self-inductance and mutual inductance, caused by positional deviations of the ferrite cores on both sides. However, such variable LCT parameters can damage the resonant tank, thus impacting transmission efficiency and output stability. To address this issue, this paper proposes a self-tuning S/S IPT system based on switch-controlled capacitors (SCCs). The system utilizes gradient descent methods independently on double-side to achieve decoupled tuning control. This approach effectively mitigates the impact of LCT parameter fluctuations without requiring wireless communication. Furthermore, all switches in the system operate at fixed frequencies and implement soft switching. Finally, a prototype is constructed to validate the effectiveness of the proposed system. © 2024 IEEE.

关键词： Energy transfer

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Silent ICU based on IEEE 11073 SDC

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Current Directions in Biomedical engineering 2023年第1期9卷 303-306页

作者： Kasparick, Martin Klotz, Tobias Andersen, Björn Thürk, Gregor Neumuth, Thomas Rockstroh, Max Rother, Benjamin Golatowski, Frank B. Braun Melsungen AG Carl-Braun-Straße 1 Melsungen 34212 Germany Drägerwerk AG & Co. KGaA Lübeck Germany ICCAS University of Leipzig Leipzig Germany Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock Germany

Patients and caregivers suffer from alarm-related noise in today's hospitals. While this is a topic for all fields of care, this challenge is especially relevant for intensive care units (ICUs). The noise harms patients, hinders the recovery process, or can even lead to psychosis. For the caregivers, noise causes an enormous stress level and in combination with the high number of clinically irrelevant or false alarms it leads to alarm fatigue and desensitization. These problems result in documented deaths of patients. Therefore, we present a demonstrator of a Silent ICU. Based on a distributed alarm system, the medical devices at the bedside do not create any audio alarm signals, as long as a remote alarm notification system is connected and works properly. An ICU bed place consists of devices from different manufacturers. Thus, a standardized interconnection is necessary. Therefore, we use IEEE 11073 Service-oriented Device Connectivity (SDC) to create a cross-manufacturer distributed alarm system with components from three different companies. A fourth company provides a documentation system for this demonstrator. Patients and caregivers will greatly benefit from Silent ICUs and smart distributed alarm systems that will be build based on interoperable cross-manufacturer environments. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Intensive care units

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Noise-Aware Speech Separation with Contrastive Learning

Noise-Aware Speech Separation with Contrastive Learning

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zizheng Zhang Chen Chen Hsin-Hung Chen Xiang Liu Yuchen Hu Eng Siong Chng School of Software and Microelectronics Peking University China School of Computer Science and Engineering Nanyang Technological University Singapore School of Electrical and Computer Engineering Georgia Institute of Technology USA

Recently, speech separation (SS) task has achieved remarkable progress driven by deep learning technique. However, it is still challenging to separate target speech from noisy mixture, as the neural model is vulnerable to assign background noise to each speaker. In this paper, we propose a noise-aware SS (NASS) method, which aims to improve the speech quality for separated signals under noisy conditions. Specifically, NASS views background noise as an additional output and predicts it along with other speakers in a mask-based manner. To effectively denoise, we introduce patch-wise contrastive learning (PCL) between noise and speaker representations from the decoder input and encoder output. PCL loss aims to minimize the mutual information between predicted noise and other speakers at multiple-patch level to suppress the noise information in separated signals. Experimental results show that NASS achieves 1 to 2dB SI-SNRi or SDRi over DPRNN and Sepformer on WHAM! and LibriMix noisy datasets, with less than 0.1M parameter increase.

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Advancing Brain-computer Interaction: EEG-based Eye Movement Recognition with AI 7

Advancing Brain-Computer Interaction: EEG-based Eye Movement...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Saidala, Ravi Kumar Ramnath, M. Komala, C.R. Vidhya, N.G. Taqui, Syed Noeman Rajendiran, M. Alliance University Department of Computer Science And Engineering Karnataka Bangalore560076 India Ramco Institute of Technology Department of Artificial Intelligence And Data Science Tamil Nadu Rajapalayam626117 India Hkbk College of Engineering Department of Information Science And Engineering Bengaluru560 045 India St. Joseph's Institute of Technology Omr Department of Information Technology Tamil Nadu Chennai600119 India Saveetha Institute of Medical And Technical Sciences Saveetha School of Engineering Department of Vlsi Microelectronics Tamil Nadu Chennai602105 India Panimalar Engineering College Department of Computer Science And Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798350359299

The integration of Electroencephalography (EEG) and Brain-computer Interface (BCI) technologies is causing an evolution in healthcare, accessibility, and neuroscience. This multidisciplinary method offers a non-invasive means to communicate and control through intentional eye movements, which is particularly promising for patients suffering from neurological illnesses. In this study, eye movements are identified using EEG data from the EPOC Flex wireless EEG brain device. Using advanced Deep Learning models such as the Deep Belief Network (DBN) and the Deep Residual Network (Deep ResNet), and attempted to distinguish four distinct eye movements: open, close, right, and left. Some of the primary metrics utilized for assessing these models were accuracy, precision, recall, and F1 score. The Deep ResNet model gives better results with an accuracy of 96.25%, recall of 95.85%, precision of 96.66%, and an F1 score of 96.24%. The findings suggest that BCI frameworks can leverage EEG-based eye movement detection to improve rehabilitation procedures and make computers and devices easier to operate. This study's findings open a path for future research into neurotechnological applications and human-computer interaction. © 2024 IEEE.

关键词： Eye movements

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Ferroelectrically gated two-dimensional bismuth oxyselenides for strain-invariant flexible synaptic thin-film transistors

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Science China(Information Sciences) 2025年第5期68卷 396-403页

作者： Jie WEN Fei XIAO Zheng-Dong LUO Dongxin TAN Xuetao GAN Dawei ZHANG Zhufei CHU Yinshui XIA Yan LIU Genquan HAN Hangzhou Institute of Technology Xidian University State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology School of MicroelectronicsXidian University Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technology Shaanxi Key Laboratory of Optical Information Technology School of Physical Science and Technology Northwestern Polytechnical University School of Materials Science and Engineering The University of New South Wales ARC Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET) The University of New South Wales Faculty of Electrical Engineering Computer Science Ningbo University

Two-dimensional van der Waals（2D vdW） semiconductors have proven to be of great importance for flexible thinfilm transistors（TFTs） owing to their intrinsic mechanical flexibility and superior electronic *** particular,bismuth oxyselenide（Bi2O2Se）,featuring ultrahigh electron mobility along with facile scalable thin-film growth methods,could offer a new option to deliver massively enhanced potential for flexible ***,it has remained a challenge to achieve nonvolatile flexible memory devices based on Bi2O2Se TFTs,thereby hindering the extension of Bi2O2Se TFTs to storage and emerging neuromorphic computing ***,a flexible synaptic TFT is demonstrated through the creation of a Bi2O2Se-based ferroelectric field-effect transistor（FeFET） structure on the flexible mica *** proposed device exhibits excellent nonvolatile memory characteristics,including a large memory window,excellent current modulation ratio,great retention,and strong ***,the Bi2O2Se-based FeFET can be operated as a synaptic device with analog conductance-modulating *** to the superior mechanical flexibility of the component materials and the mica substrate,the Bi2O2Se-based FeFETs can retain their performance against various bending states,showing a straininvariant electrical *** study marks the advancement of Bi2O2Se-based TFTs toward flexible nonvolatile memories and synaptic devices.

关键词： Bi$_{2}$O$_{2}$Se FeFET nonvolatile memory flexible device synaptic transistor

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Ultra Miniaturized Novel Antenna for Wireless Capsule Endoscopy System 19

Ultra Miniaturized Novel Antenna for Wireless Capsule Endosc...

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19th International Conference on Emerging Technologies, ICET 2024

作者： Un Noor, Syed Misbah Khan, Shahid Ali Shah, Syed Ahson Nasir, Jamal Sethi, Waleed Tariq Jan, Latif Dalarsson, Mariana Koziel, Slawomir Comsats University Department of Electrical and Computer Engineering Abbottabad Pakistan Gdansk University of Technology Department of Microelectronics Gdansk Poland Gwangju Institute of Science and Technology Graduate School of Energy Convergence Gwangju South Korea Gik Institute Faculty of Electrical Engineering Swabi Pakistan Iqra National University Department of Computer Science Peshawar Pakistan School of Electrical Engineering and Computer Science Kth Royal Institute of Technology Stockholm Sweden Gdansk University of Technology Faculty of Electronics Telecommunication and Computer Sciences Gdansk Poland

ISBN: (纸本)9798350379587

Wireless capsule endoscopes capture and transmit images of the human digestive system for use in medical diagnostics. The placement of the capsule makes it possible to pinpoint the illnesses. In this work, we propose an ultra-miniaturized antenna that can operate in the 2.4 GHz industrial, scientific, and medical (ISM) band for integration with a capsule. Minia-turization is achieved using the meander resonator technique, high permittivity substrate, and superstrate. The antenna is designed using Rogers RT/duroid 6010 substrate with a footprint of 2.8 × 2.8 × 0.5 mm³. A basic mathematical equation calculates the meander resonator's initial length for the required frequency. To the best of our knowledge, the proposed design provides the best performance, the smallest footprint, and a maximum peak gain of -28.6 dBi. Along with the antenna design, a 3D-printed capsule with dummy circuitry is used. The antenna's simulated bandwidth is 210 MHz. Good impedance matching is maintained along the whole digestive tract. The data is analyzed using stomach, small intestine, and colon models. With a link margin of 20 dB, the suggested antenna can send data at a speed of 1 Mbps across a two-meter distance in the whole digestive tract. To the best of our knowledge, this is the smallest endoscopic antenna listed for 2.45 GHz ISM bands in the literature. Based on the acquired results, the proposed design is a good candidate for the target medical applications. © 2024 IEEE.

关键词： endoscopic implantable novel antenna wireless capsule endoscopy (WCE)

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PUF-Based Privacy-Preserving Simultaneous Authentication Among Multiple Vehicles in VANET

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IEEE Transactions on Vehicular Technology 2024年第5期73卷 6727-6739页

作者： Awais, Syed Muhammad Yucheng, Wu Mahmood, Khalid Akram, Muhammad Wahid Hussain, Shafiq Das, Ashok Kumar Park, Youngho Chongqing University School of Microelectronics and Communication Engineering Chongqing400044 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin64002 Taiwan University of Lahore Department of Software Engineering Punjab Lahore54590 Pakistan University of Sahiwal Department of Computer Science Punjab Sahiwal57000 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Telangana Hyderabad500032 India Kyungpook National University School of Electronics Engineering Daegu41566 Korea Republic of

The intellectual and immense attainment of a smart city and auto-mobile vehicles are gradually growing. This growth drives Vehicular Ad-Hoc Network (VANET), a broadly operated complex network for inter-vehicular transmission to acquire information relevant to the vehicle location, road condition, traffic congestion, and speed. Generally, this information is procured through an open-source communication, which is susceptible to various security threats. In broad terms, the privacy of data in VANET is considered an imperative task. In this regard, many authentication protocols are formerly initiated for VANET. Most of these protocols are precarious owing to eavesdropping, replay, and impersonation attacks, etc. Furthermore, most existing protocols operates on enormous communication and computation rate, which turns them inadequate for VANET. This paper exhibits a lightweight privacy-preserving authentication protocol for n number of vehicles in VANET using the physical unclonable function (PUF) technique, and offers efficient and secure communication via public channels. Moreover, we evaluate our protocol formally and informally, showing that it is scalable, lightweight, and safe compared to formerly protocols. The rate of computation and communication is less than most related protocols. We also simulate the proposed scheme using the NS-3 simulator to measure its various network performance parameters. As a result, it is apparent through the beheld statistics that the presented protocol is beyond practical, efficient, and reliable for the secure dissemination of information in VANET. © 1967-2012 IEEE.

关键词： Vehicular ad hoc networks

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Advances in Noble Metal-Decorated Metal Oxide Nanomaterials for Chemiresistive Gas Sensors:Overview

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Nano-Micro Letters 2023年第6期15卷 353-427页

作者： Li‑Yuan Zhu Lang‑Xi Ou Li‑Wen Mao Xue‑Yan Wu Yi‑Ping Liu Hong‑Liang Lu State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics and SystemsSchool of MicroelectronicsFudan UniversityShanghai 200433People’s Republic of China School of Opto‑Electronic Information and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093People’s Republic of China State Key Laboratory of Metal Matrix Composites School of Material Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Highly sensitive gas sensors with remarkably low detection limits are attractive for diverse practical application fields including real-time environmental monitoring,exhaled breath diagnosis,and food freshness *** various chemiresistive sensing materials,noble metal-decorated semiconducting metal oxides(SMOs)have currently aroused extensive attention by virtue of the unique electronic and catalytic properties of noble *** review highlights the research progress on the designs and applications of different noble metal-decorated SMOs with diverse nanostructures(e.g.,nanoparticles,nanowires,nanorods,nanosheets,nanoflowers,and microspheres)for high-performance gas sensors with higher response,faster response/recovery speed,lower operating temperature,and ultra-low detection *** key topics include Pt,Pd,Au,other noble metals(e.g.,Ag,Ru,and Rh.),and bimetals-decorated SMOs containing ZnO,SnO_(2),WO_(3),other SMOs(e.g.,In_(2)O_(3),Fe_(2)O_(3),and CuO),and heterostructured *** addition to conventional devices,the innovative applications like photo-assisted room temperature gas sensors and mechanically flexible smart wearable devices are also ***,the relevant mechanisms for the sensing performance improvement caused by noble metal decoration,including the electronic sensitization effect and the chemical sensitization effect,have also been summarized in ***,major challenges and future perspectives towards noble metal-decorated SMOs-based chemiresistive gas sensors are proposed.

关键词： Noble metal Bimetal Semiconducting metal oxide Chemiresistive gas sensor Electronic sensitization Chemical sensitization

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