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3D Image Acquisition and Display: Technology, Perception and Applications, 3D, COSI, DH, FLatOptics, IS, pcAOP 2023 - Part of Imaging and Applied Optics Congress 2023

作者： Zhu, Jiabei Tian, Lei Department of Electrical and Computer Engineering Boston University MA02215 United States Department of Biomedical Engineering Boston University MA02215 United States

We propose a novel algorithm based on the split-step non-paraxial model for different intensity diffraction tomography setups to recover the 3D refractive index distribution of multiple-scattering biological samples. ... 详细信息

ISBN: (纸本)9781957171289

关键词： Multiple scattering

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Biomechanical Evaluation of Fingers Repetitive Voluntary Tasks in Chronic Stroke Survivors

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IEEE Access 2023年 11卷 143649-143656页

作者： Adeel, Muhammad Peng, Chih-Wei Lee, I-Jung Lin, Bor-Shing National Taipei University Department of Computer Science and Information Engineering New Taipei City237303 Taiwan Taipei Medical University School of Biomedical Engineering College of Biomedical Engineering Taipei11031 Taiwan Taipei Medical University School of Gerontology and Long-Term Care College of Nursing Taipei11031 Taiwan National Taipei University College of Electrical Engineering and Computer Science New Taipei City237303 Taiwan

A chronic stroke affects hand mobility limiting the normal functioning of the finger joints. The voluntary tasks with a repetitive motion can identify the limitation in the range of motion (ROM) to enhance the hand functioning of stroke survivors. Therefore, we compared two voluntary tasks fast ball squeezing (FBS) and slow ball squeezing (SBS), and analyzed the variability of these tasks for finger pressure and ROM in chronic stroke survivors. An experimental study with 22 healthy and 39 chronic stroke participants was conducted. All of them wore an upper limb motion capture device (UMCD) to record the active (AROM) of finger joints during FBS and SBS tasks for 20 repetitions. The data were analyzed into the joint angle and pressure to compare these tasks and their variability. While comparing the FBS and SBS tasks, left-side pressure and both sides' ROM attained the level of significance (p © 2013 IEEE.

关键词： Joints (anatomy)

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A Semi-Supervised Deep Learning Approach for Intrusion Detection and Classification for the Internet of Things

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biomedical Materials and Devices 2025年 1-17页

作者： Uthradevi, G. Thiruvasagam, P. Mythili, S. Manoj, S. Oswalt Department of Electronics and Communication Engineering Chennai Institute of Technology Tamil Nadu Kundrathur Chennai 600069 India Department of Electrical and Electronics Engineering Chennai Institute of Technology Tamil Nadu Kundrathur Chennai 600069 India Department of Biomedical Engineering PSNA College of Engineering and Technology Tamilnadu Dindigul 624622 India Department of Computer Science and Engineering Sri Krishna College of Engineering and Technology Tamil Nadu Kuniyamuthur 641008 India

Intrusion Detection Systems (IDS) are essential for protecting networks from cyber threats and ensuring the security of critical infrastructures. This paper introduces an innovative hybrid model that combines Deep Belief Networks (DBNs), Principal Component Analysis (PCA), and Support Vector Machines (SVM) with adversarial learning to enhance the detection of both known and emerging cyber threats. The proposed model achieves a strong balance of accuracy, efficiency, and scalability, making it highly effective for real-world applications. By incorporating adversarial learning, the system can detect zero-day exploits—previously unseen attacks—and adapt to evolving threats. This is achieved by training the model on adversarial samples, which improves its resilience to variations in attack patterns. SVM further enhances the model’s ability to classify known and unknown threats with high precision. The model was rigorously tested on two benchmark datasets, NSL-KDD and CICIDS2017, achieving outstanding results. It demonstrated a high accuracy rate of 99.73% on NSL-KDD and a low false positive rate of 0.55%, while on CICIDS2017, it achieved a false positive rate of 0.73%. The model also outperformed existing approaches in precision, recall, and F1-score, particularly in detecting complex attack types such as R2L (Remote-to-Local), U2R (User-to-Root), and Botnet attacks. Additionally, PCA reduced the feature space by 40%, significantly lowering the model’s inference time to just 9.0 ms per sample. This makes the model highly suitable for real-time intrusion detection in high-traffic network environments, where speed and efficiency are critical. Overall, this hybrid model strengthens cybersecurity defenses and contributes to building resilient infrastructures. By effectively detecting and mitigating cyber threats, it supports the creation of safer, fairer, and more inclusive digital communities. The integration of adversarial learning and dimensionality reduction ensures rob

关键词： Adversarial learning Cyber security Deep belief networks Dimensionality reduction Feature extraction IDS Networks PCA SVM

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High resolution and high sensitivity imaging magnetometer with magnetic nanoparticle and optical heterodyne detection

High resolution and high sensitivity imaging magnetometer wi...

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2024 Frontiers in Optics, FiO 2024

作者： Bartos, Jan Tis, Taleb Ba Park, Wounjhang Huang, Shu-Wei Department of Electrical Computer and Energy Engineering University of Colorado Boulder80309 United States Material Science and Engineering Program University of Colorado Boulder80309 United States

We present progress towards an imaging magnetometer using a magneto-optical polymer nanocomposite thin film, experimentally demonstrating 29nT/√Hz sensitivity with © Optica Publishing Group 2024, © 2024 The... 详细信息

关键词： Heterodyne detection

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Feature Matching via Topology-Aware Graph Interaction Model

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 113-130页

作者： Yifan Lu Jiayi Ma Xiaoguang Mei Jun Huang Xiao-Ping Zhang the Electronic Information School Wuhan UniversityWuhan 430072China IEEE Tsinghua Berkeley Shenzhen Institute Shenzhen 518071China the Department of Electrical Computer and Biomedical EngineeringToronto Metropolitan UniversityToronto ON M5B 2K3Canada

Feature matching plays a key role in computer vision. However, due to the limitations of the descriptors, the putative matches are inevitably contaminated by massive *** paper attempts to tackle the outlier filtering problem from two aspects. First, a robust and efficient graph interaction model,is proposed, with the assumption that matches are correlated with each other rather than independently distributed. To this end, we construct a graph based on the local relationships of matches and formulate the outlier filtering task as a binary labeling energy minimization problem, where the pairwise term encodes the interaction between matches. We further show that this formulation can be solved globally by graph cut algorithm. Our new formulation always improves the performance of previous localitybased method without noticeable deterioration in processing time,adding a few milliseconds. Second, to construct a better graph structure, a robust and geometrically meaningful topology-aware relationship is developed to capture the topology relationship between matches. The two components in sum lead to topology interaction matching(TIM), an effective and efficient method for outlier filtering. Extensive experiments on several large and diverse datasets for multiple vision tasks including general feature matching, as well as relative pose estimation, homography and fundamental matrix estimation, loop-closure detection, and multi-modal image matching, demonstrate that our TIM is more competitive than current state-of-the-art methods, in terms of generality, efficiency, and effectiveness. The source code is publicly available at http://***/YifanLu2000/TIM.

关键词： Feature matching graph cut outlier filtering topology preserving

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A Unified Modulated Model Predictive Control for a Two-Stage AC-DC Converter Interfacing a Vanadium Redox Flow Battery

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IEEE Transactions on Industry Applications 2025年

作者： Volpini, Andrea Salvo, Salvatore R. Di Tresca, Giulia Leuzzi, Riccardo Zanchetta, Pericle Electrical Computer and Biomedical Engineering Dept. Pavia Italy Department of Electrical and Information Engineering Bari Italy

With the increasing integration of renewable energy sources into electrical grids, energy storage systems have become crucial for stability and regulation. Thus, dedicated two-stage AC-DC converters are essential for integrating batteries into the grid infrastructure. These converters typically employ either single-phase or three-phase inverters paired with a Dual Active Bridge (DAB) in a back-to-back configuration, ensuring high efficiency and galvanic isolation. The conventional control scheme for such converters involves two separate PI-based control loops, one for each stage. This paper proposes a novel control strategy based on a Modulated Model Predictive Control (MMPC) algorithm for a two-stage AC-DC converter. The proposed approach utilizes a single cost-function optimization routine to simultaneously control both the grid-side and the battery-side stages, simplifying the control architecture and enhancing performance. Finally, the proposed MMPC is implemented on a DSP and FPGA-based board and the experimental results show that the proposed solution achieves faster dynamics than conventional control with no overshoots or undershoots. © 1972-2012 IEEE.

关键词： Predictive control systems

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High resolution and high sensitivity imaging magnetometer with magnetic nanoparticle and optical heterodyne detection

High resolution and high sensitivity imaging magnetometer wi...

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2024 Laser Science, LS 2024

作者： Bartos, Jan Ba Tis, Taleb Park, Wounjhang Huang, Shu-Wei Department of Electrical Computer and Energy Engineering University of Colorado Boulder80309 United States Material Science and Engineering Program University of Colorado Boulder80309 United States

We present progress towards an imaging magnetometer using a magneto-optical polymer nanocomposite thin film, experimentally demonstrating 29nT/√Hz sensitivity with © 2024 The Author(s). © Optica Publishing ... 详细信息

关键词： Heterodyne detection

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Change of electrical and Transport Properties of Nickel Oxide by Carrier Concentration and Temperature through First‑Principle Calculations

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Nanomanufacturing and Metrology 2023年第4期6卷 109-118页

作者： Nayem Md.Reza Shah Chang‑Dong Yeo Minyeong Choi Yang‑Ki Hong Jeong H.You Department of Mechanical Engineering Texas Tech UniversityLubbockTX 79409USA Department of Electrical and Computer Engineering and Material Science Ph.D.Program The University of AlabamaTuscaloosaAL 35487USA Department of Mechanical Engineering School of EngineeringUniversity of St.ThomasSt.PaulMN 55105USA

Nickel is typically used as one of the main components in electrical contact devices or *** oxide(NiO)is usually formed on the surfaces of electrodes and can negatively impact system performance by introducing electrical contact *** thermal,electrical,and transport properties of NiO,as a Mott insulator or a p-type semiconductor,can be altered by operating and environmental conditions such as temperature and stress/strain by *** this study,we inves-tigate the fundamental material properties of NiO through the first-principle ***,we obtain and compare the lattice parameter,magnetic moment,and electronic structure for NiO via the WIEN2K simulations with four different poten-tials(i.e.,GGA,GGA+U,LSDA,and LSDA+U).Then,using the WIEN2K simulation results with LSDA+U potential that produces a highly accurate bandgap for NiO,we calculate the electrical conductivity and electrical part of the thermal conductivity of nickel and NiO as a function of temperature and carrier concentration through the BoltzTraP *** simulation results revealed that the electrical conductivity relative to the relaxation time for NiO increases with the carrier concentration,while it shows a slightly decreasing trend with temperature under a fixed carrier *** contrast,the electrical part of the thermal conductivity shows an increasing trend considering carrier concentration and temperature.

关键词： Nickel oxide Magnetic moments Density of states Seebeck coefcient electrical conductivity

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Analysis of a Broadband Metamaterial Absorber at Terahertz Frequencies 6

Analysis of a Broadband Metamaterial Absorber at Terahertz F...

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6th International Conference on electrical Information and Communication Technology, EICT 2023

作者： Jyoti, Oishi Sarkar, Pritu Parna Habib, Md. Samiul Rajshahi University of Engineering & Technology Department of Electrical & Computer Engineering Rajshahi Bangladesh University of Texas Rio Grande Valley Department of Bioengineering & Biomedical Engineering EdinburgTX United States Rajshahi University of Engineering & Technology Department of Electrical & Electronic Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350370836

In this paper, we present a vanadium dioxide (VO2) based metamaterial absorber at terahertz (THz) frequencies, achieving near unity absorption from 3.5 THz to 5 THz through full vector numerical simulation which refers to a computational method that considers complete vector nature of electromagnetic fields in three dimensions. Our proposed absorber is based on a single layered elliptic shaped ring resonator, which provides more design freedom than the existing absorbers and is easier to fabricate. Our numerical simulations show that modifying the conductivity of VO2 significantly enhances the absorption peak, and reaches near-perfect absorption when the conductivity of VO2 reaches the metallic phase. We illustrate that for a specific conductivity of the metal layer, the absorption peak of the absorber can be controlled by adjusting the width of the ring, the ellipticity of the ring, and the thickness of the dielectric. We also explain the physical mechanism and origin of broadband absorption through impedance matching theory. We believe that our proposed absorber may find applications in sensing and imaging technology. © 2023 IEEE.

关键词： Vanadium dioxide

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Portable Multiparameter biomedical Sensor Fusion for Home Healthcare 2

Portable Multiparameter Biomedical Sensor Fusion for Home He...

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2nd International Conference on Recent Trends in Microelectronics, Automation, Computing, and Communications Systems, ICMACC 2024

作者： Vidyasagar, K.E.Ch Manchikanti, Venkata Jaideep Datta Kanduri, Harika Saikia, Manob Jyoti University of Memphis Biomedical Sensors and Systems Lab MemphisTN38152 United States Osmania University Department of Biomedical Engineering Hyderabad500007 India University of Memphis Electrical and Computer Engineering Department MemphisTN38152 United States

ISBN: (纸本)9798350366570

The ever-increasing focus on preventative healthcare and remote patient monitoring has driven the need for innovative solutions. Traditionally, measuring vital signs in both clinical and home settings has relied on a collection of individual devices, often leading to cluttered setups, patient discomfort, and potential inaccuracies due to user error. This paper proposes a multi-parameter acquisition system designed to address these limitations. The system integrates the measurement of essential parameters into a single, user-friendly device. This streamlined approach not only reduces measurement complexity but also improves patient comfort by eliminating the need for multiple devices and cumbersome wires. The design of the system, including its sensors, hardware components, and data processing unit is presented in detail. The device serves a dual purpose. Firstly, it empowers individuals at home by providing them with a single device to monitor their vital signs. Secondly, for hospitals, the device offers a streamlined and less cumbersome way to visualize essential patient parameters, allowing for improved monitoring efficiency. © 2024 IEEE.

关键词： Remote patient monitoring

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