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Optics and the Brain, BRAIN 2024 - Part of Optica Biophotonics Congress: biomedical Optics

作者： Liu, Bingxue Yaqoob, Zahid Boas, David A. Cheng, Xiaojun Department of Electrical and Computer Engineering Boston University MA02215 United States Neurophotonics Center Boston University MA02215 United States Department of Biomedical Engineering Boston University MA02215 United States

We present a microlens array-based laser speckle contrast imaging (mla-LSCI) system with multi-point illumination and wide field detection, which will give us a map of slow tissue dynamics across the mice cortex. ... 详细信息

ISBN: (纸本)9781957171340

关键词： Microlenses

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DLMetaChain: An IoT Data Lake Architecture Based on the Blockchain 13

DLMetaChain: An IoT Data Lake Architecture Based on the Bloc...

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13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022

作者： Pingos, Michalis Christodoulou, Panayiotis Andreou, Andreas Cyprus University of Technology Computer Engineering and Informatics Department of Electrical Engineering Limassol Cyprus Neapolis University Department of Computer Science Pafos Cyprus

ISBN: (数字)9781665463904

ISBN: (纸本)9781665463904

Nowadays, the IoT ecosystem is evolving rapidly, with multiple heterogeneous sources producing high volumes of data and processes transforming this data into meaningful or 'smart' information. These volumes of data, including IoT data, need to be stored in repositories that can host raw, unprocessed, relational and non-relational types of data, such as Data Lakes. Due to the weakness of metadata management, security & access control is one of the main challenges of Big Data storage architectures as Data Lakes can be replaced without oversight of the contents. Recently, the Blockchain technology has been introduced as an effective solution to build trust between different entities, where trust is either nonexistent or unproven, and to address security and privacy concerns. In this paper we introduce DLMetaChain, an extended Data Lake metadata mechanism that consists of data from heterogeneous data sources which interact with IoT data. The extended mechanism mainly focuses on developing an architecture to ensure that the data in the Data Lake is not modified or altered by taking into advantage the capabilities of the Blockchain. © 2022 IEEE.

关键词： Smart contract

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A Reinforcement Learning-Based Computational Model of Human Elbow Joint Operation for Effective Human-Machine Interface

A Reinforcement Learning-Based Computational Model of Human ...

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2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Yoo, Eunsoo Choi, Kyungrak Park, Hangue Sungkyunkwan University Department of MetaBioHealth Suwon Korea Republic of Texas A & M University Department of Electrical and Computer Engineering United States Sungkyunkwan University Department of Biomedical Engineering Department of Intelligent Precision Healthcare Convergence Department of MetaBioHealth Suwon Korea Republic of

ISBN: (纸本)9798331530839

Designing effective human-machine interfaces requires understanding complex interactions between humans and machines. However, even bi-directional communication that relies on sensor data is often insufficient due to the unpredictability of human behaviors. To better anticipate these behaviors, a computational model that reflects the operating principles of the human nervous system is essential. This study presents a computational neuromechanical model that focuses on human sensorimotor operations, particularly in the context of elbow joint rotation. The model leverages reinforcement learning (RL) to simulate the brain's reward mechanism in motor adjustment, with the reward function adjusted by a multiplication constant (M) that reflects individual variability in sensorimotor processing. Measurement and simulation data were evaluated based on their overlap ratios. The test results demonstrate that the RL-based model, when calibrated with an optimal M value, closely matches with measured motor outputs, indicating its potential for improving the effectiveness of the human-machine interface. © 2024 IEEE.

关键词： Reinforcement learning

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A Multimodality Electrochemical and Impedance Spectroscopy System-on-a-Chip With Temperature Sensing and Impedance-Boosting Techniques

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IEEE Transactions on biomedical Circuits and Systems 2023年第4期17卷 857-871页

作者： Lin, Yi-Jie Liu, Wei-Cheng Huang, Yu-Chiao Huang, Ying-Jie Yeh, Yung-Hua Chang, Min-Hua Lin, Shu-Ping Liao, Ying-Chih Liao, Yu-Te National Yang Ming Chiao Tung University Institute of Electrical and Computer Engineering Hsinchu300 Taiwan National Chung Hsing University Graduate Institute of Biomedical Engineering Taichung40227 Taiwan National Taiwan University Department of Chemical Engineering Taipei10617 Taiwan

This article presents a multimodal electrochemical sensing system-on-chip (SoC), including the functions of cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and temperature sensing. CV readout circuitry achieves an adaptive readout current range of 145.5 dB through an automatic range adjustment and resolution scaling technique. EIS has an impedance resolution of 9.2 mΩ Hz at a sweep frequency of 10 kHz and an output current of up to 120 μA. With an impedance boost mechanism, the maximum detectable load impedance is extended to 22.95 kΩ, while the total harmonic distortion is less than 1%. A resistor-based temperature sensor using a swing-boosted relaxation oscillator can achieve a resolution of 31 mK in 0-85 °C. The design is implemented in a 0.18 μm CMOS process. The total power consumption is 1 mW. © 2007-2012 IEEE.

关键词： Temperature sensors

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Pole Slipping in Droop-Based Grid-Forming Inverters

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IEEE Access 2025年 13卷 100338-100352页

作者： Negar Karimipour Hansi Wijayalath Arachchilage Amir Abiri Jahromi Behrooz Bahrani Mohammadreza F. M. Arani Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto ON Canada Department of Electrical and Computer Systems Engineering Monash University Clayton VIC Australia School of Electronic and Electrical Engineering University of Leeds Leeds U.K.

Integration of grid-forming inverter-based resources is considered as a viable solution to address the challenges associated with the dynamics of power systems with high penetration levels of inverter-based resources. Yet, various aspects of dynamic behaviour of grid-forming inverters during disturbances have remained unknown. This paper for the first time introduces the concept of pole slipping in grid forming inverters, referring to the loss of synchronism where the inverter’s internal phase angle deviates beyond 180° with respect to the grid, similar to synchronous generators losing step. It is revealed that this event in grid forming inverters can be stable or unstable. The differences between stable and unstable pole slipping are highlighted. The determining factors for the occurrence of stable and unstable pole slipping in grid forming inverters and equipment-level implications of pole slipping are identified and studied. A solution is proposed to mitigate stable and unstable pole slipping in grid-forming inverters by adjusting the operating reference power during the disturbance. The validity of the proposed concept of pole slipping in grid forming inverters and the proposed solution is tested and verified through extensive time-domain simulations and experimental results. The results verify that pole slipping is more likely to happen in high short circuit ratios (SCRs). It is revealed that unstable pole slipping does not occur at SCRs lower than 3.5. Simulation and experimental results demonstrate that a phase jump as small as 10° may lead to instability in a grid with SCRs equal or higher than 10. This is while in lower SCRs such phase jumps result in long fault recovery without causing pole slipping.

关键词： Inverters Synchronous generators Power system stability Grid forming Voltage Rotors Circuit stability Transient analysis Current limiters Stability criteria

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Organoid intelligence:Integration of organoid technology and artificial intelligence in the new era of in vitro models

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Medicine in Novel Technology and Devices 2024年第1期21卷 39-44页

作者： Huaiyu Shi Andrew Kowalczewski Danny Vu Xiyuan Liu Asif Salekin Huaxiao Yang Zhen Ma Department of Biomedical&Chemical Engineering Syracuse UniversitySyracuseNYUSA BioInspired Institute for Material and Living Systems Syracuse UniversitySyracuseNYUSA Department of Mechanical&Aerospace Engineering Syracuse UniversitySyracuseNYUSA Department of Electrical Engineering&Computer Science Syracuse UniversitySyracuseNYUSA Department of Biomedical Engineering University of North TexasDentonTXUSA

Organoid Intelligence ushers in a new era by seamlessly integrating cutting-edge organoid technology with the power of artificial ***,three-dimensional miniature organ-like structures cultivated from stem cells,offer an unparalleled opportunity to simulate complex human organ systems in *** the convergence of organoid technology and AI,researchers gain the means to accelerate discoveries and insights across various *** intelligence algorithms enable the comprehensive analysis of intricate organoid behaviors,intricate cellular interactions,and dynamic responses to *** synergy empowers the development of predictive models,precise disease simulations,and personalized medicine approaches,revolutionizing our understanding of human development,disease mechanisms,and therapeutic *** Intelligence holds the promise of reshaping how we perceive in vitro modeling,propelling us toward a future where these advanced systems play a pivotal role in biomedical research and drug development.

关键词： Organoids Machinelearning Deep learning Artificial intelligence Stem cells

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Floating Solenoid Cable Trap 46

Floating Solenoid Cable Trap

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Venegas, Roman Touchet-Valle, Edith Busher, Joseph Bowen, Donald McDougall, Mary P. Texas A&m University Department of Electrical and Computer Engineering College StationTX77840 United States Texas A&m University Department of Biomedical Engineering College StationTX77840 United States

ISBN: (纸本)9798350371499

In the current state of magnetic resonance imaging (MRI), transmission lines are vital in communicating with the transmitting and receiving networks. However, transmission lines, such as coaxial cables, operating at the radio frequencies (RF) used in MRI can be affected by common mode cable currents. These currents diminish received signals and put the patient at risk of RF burns. A common way to combat this issue is to implement cable traps on the transmission line(s). To effectively suppress cable currents and improve the ease of applying floating cable traps, a variation of a floating cable trap was created. The trap utilizes three LC circuits to provide an attenuation of -24 decibels (dB) at 127 MHz. The trap uses a custom 3D printed former that allows for straightforward construction and application onto a single RG-58 coaxial cable. © 2024 IEEE.

关键词： Coaxial cables

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A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow

A Machine Learning-Based Privacy-Preserving Approach to Inco...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Dindar, Burak Saner, Can Berk Polat, Dogukan Yigit Çakmak, Huseyin Kemâl Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany National University of Singapore Department of Electrical and Computer Engineering Singapore National University of Singapore School of Computing Singapore

ISBN: (纸本)9789531842976

In order to achieve the goal of a carbon-neutral power system, significant changes to the power grid are underway, necessitating enhanced interoperability between Transmission System Operators (TSOs) and Distribution System Operators (DSOs) for effective grid operation, particularly in light of the growing number of distributed generators (DGs). Data privacy concerns, however, complicate decision-making processes, particularly when integrating DGs into system-wide dispatch decisions. In this paper, we propose a machine-learning (ML)-based method to incorporate DGs located within the distribution system (DS) into dispatch decisions, adhering to data privacy by mitigating the exchange of sensitive data, such as system topology and demand profiles, between TSOs and DSOs. The methodology involves training three ML models to represent the behavior of the DS, thereby replacing the standard power flow model that contains sensitive information. Notably, we utilize a novel tailored neural network (NN) architecture to enhance computational efficiency in mapping the feasible region of the DS. Additionally, we employ open-source data to construct the Baden-Wü rttemberg (Germany) electricity grid, allowing to test our method not only on standard systems but also on a model that more accurately represents real-world power systems. The numerical case studies verify that the proposed method achieves results comparable to standard AC optimal power flow (AC-OPF) in both cost-optimality and computational time. © 2024 IEEE.

关键词： Differential privacy

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(ω1,ω2)-temporal random hyperbolic graphs

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Physical Review E 2024年第2期110卷 024309-024309页

作者： Sofoclis Zambirinis Fragkiskos Papadopoulos Department of Electrical Engineering Computer Engineering and Informatics <a href="https://***/05qt8tf94">Cyprus University of Technology</a> 3036 Limassol Cyprus.

We extend a recent model of temporal random hyperbolic graphs by allowing connections and disconnections to persist across network snapshots with different probabilities ω1 and ω2. This extension, while conceptually simple, poses analytical challenges involving the Appell F1 series. Despite these challenges, we are able to analyze key properties of the model, which include the distributions of contact and intercontact durations, as well as the expected time-aggregated degree. The incorporation of ω1 and ω2 enables more flexible tuning of the average contact and intercontact durations, and of the average time-aggregated degree, providing a finer control for exploring the effect of temporal network dynamics on dynamical processes. Overall, our results provide new insights into the analysis of temporal networks and contribute to a more general representation of real-world scenarios.

关键词： Evolving networks Networks & random structures Random graphs Evolving network models

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Hybrid Local Cache Model for Enhancing Performance and Memory Footprint of Mobile Heap Allocator 12

Hybrid Local Cache Model for Enhancing Performance and Memor...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Lee, Kyung-Seok Lee, Teahyung Eom, Young Ik Sungkyunkwan University Department of Digital Media and Communications Engineering Suwon Korea Republic of Sungkyunkwan University Department of Computer Science and Engineering Suwon Korea Republic of Sungkyunkwan University College of Computing and Informatics Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350340181

The representative mobile heap allocator that has been used in Android system, called SCUDO, supports two local cache models: the shared model and the exclusive model. However, neither the shared model nor the exclusive model cannot satisfy both memory usage and performance requirements simultaneously since mobile applications have diverse memory allocation/free patterns and the number of threads varies from single to several tens. This paper suggests a hybrid local cache model that aims to adaptively meet memory usage and performance goals. Our evaluation results show that our hybrid local cache model outperforms the shared model by up to 22% on allocation time, while preserving the memory usage. © 2023 IEEE.

关键词： Android (operating system)

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