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6th Iranian International Conference on Microelectronics, IICM 2024

作者： Estakhroyeh, Hossein Rezaei Mehran, Mahdiyeh Rashedi, Esmat Shahid Bahonar University of Kerman RF MEMS and Bio-Nano Electronics Lab Department of Electrical Engineering Kerman Iran Graduate University of Advanced Technology Faculty of Electrical and Computer Engineering Kerman Iran

ISBN: (纸本)9798331511371

With an emphasis on the sensitivity of various gate-sensing layers, the current work sought to examine how well Ion-Sensitive Field-Effect Transistors (ISFETs) function as pH sensors. Reduced Graphene Oxide (rGO) has been investigated as a potential sensing material for ISFET sensors, however Metal Oxides have historically been the material of choice for the gate-sensing layer because of its stability and dependability. ISFET sensors using rGO as the sensing material and those with traditional Metal Oxide gate layers were thoroughly compared. The performance of the sensors was assessed under a range of operating situations by multiphysics modeling with finite element methods using COMSOL Multiphysics software. The results showed a considerable improvement in sensor performance when rGO was used as the gate-sensing layer. A lower threshold voltage needed to activate the sensor and a higher sensitivity to pH variations were two of these enhancements. In ISFET sensors for pH monitoring, this work emphasizes the benefits of adopting alternate gate materials, such rGO. For the purpose of creating more dependable and efficientpH-sensing instruments for a range of scientific and industrial applications, it is helpful to analyze the fundamental mechanics and performance characteristics of sensors. © 2024 IEEE.

关键词： Threshold voltage

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MULTIPLEXED SENSING MICROPROBE FOR BIOPROCESS MONITORING 26

MULTIPLEXED SENSING MICROPROBE FOR BIOPROCESS MONITORING

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26th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2022

作者： Sharma, Atul Alsaedi, Mossab K. Del-Rio-Ruiz, Ruben Asci, Cihan Tzanakakis, Emmanuel S. Sonkusale, Sameer Nano Lab Advanced Technology Laboratory Tufts University United States Department of Electrical & Computer Engineering Tufts University United States Department of Chemical and Biological Engineering Tufts University United States

ISBN: (纸本)9781733419048

Herein, we report a facile and scalable design and manufacturing of a suture-based multiplexed microprobe for continuous bioprocess monitoring of pH, pO2, and glucose. This enables accurate monitoring of the culture environment for optimal cell growth and production. Each sensing probe comprises a 3D printed microprobe casing that facilitates the insertion of distinct working and reference electrode sutures (≤1mm length). The performance of the fabricated microprobe was tested under adjusted laboratory conditions that mimic a bioreactor environment. The designed microprobe housing allows for simple insertion and removal of different sensing threads (sutures) that target and monitor different analytes. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

关键词： Bioreactors

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Nonspecular reflectors using one-step spray coating for brightness enhancement in reflective displays

Nonspecular reflectors using one-step spray coating for brig...

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EuroDisplay 2015 Conference

作者： Pan, Su Kwok, Hoi-Sing State Key Lab on Advanced Displays and Optoelectronics Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

We proposed a novel method to fabricate nonspecular reflectors by spray coating system, which are applied to enhance brightness near normal view direction when light is obliquely incident. Fabrication parameters are o... 详细信息

ISBN: (纸本)9781510833104

关键词： Luminance

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Reinforcement Learning Scheduling Research for Edge Servers 6

Reinforcement Learning Scheduling Research for Edge Servers

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6th International Conference on computer Network, Electronic and Automation, ICCNEA 2023

作者： Han, Yonggui Wang, Zhongsheng Xi'an Technological University School of Computer Science and Engineering Xi'an710021 China Monitoring and Control xi'An Technological University State and Provincial Joint Engineering Lab. of Advanced Network Xi'an China

ISBN: (纸本)9798350305388

The rapid development of the Internet of Things and big data has brought about massive amounts of data and the need for real-time responses, which traditional computing models can no longer meet. Edge computing comes into being, which pushes computing resources and services closer to the source of data generation so that data can be processed and analyzed closer to the user. The scheduling of siting strategies for edge servers is crucial for improving the performance of edge computing networks. Traditional scheduling methods for siting strategies are often based on rules or optimization algorithms, which lack adaptive and intelligent management of the network *** paper proposes a reinforcement learning DQN-based edge server siting policy scheduling method, which aims to achieve intelligent management and resource optimization of edge computing networks by learning the optimal policy. Experimental results show that the method has significant performance advantages in terms of delay, load balancing and energy consumption. The experiment adopts DQN algorithm, which is based on Q-learning and guides the agent to make decisions by optimizing Q-value function. In this paper, the reinforcement learning scheduling algorithm of edge server is studied and compared with other three algorithms. According to the experimental results, the proposed reinforcement learning scheduling algorithm reduces the delay by 7%, the energy consumption by 3%, and the load balancing by 20% compared with the other three algorithms. This shows that the algorithm has significant advantages in improving system performance. © 2023 IEEE.

关键词： Reinforcement learning

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A neural network approach to evaluate distribution system reliability

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1992 IEEE International Conference on Systems engineering

作者： Chen, Jiann-Liang Chang, Shao-Hung Advanced Technology Center Computer and Communication Research Lab Industrial Technology and Research Lnstitute Taiwan Depart. of Electrical Engineering Feng-Chia University Taichung Taiwan

ISBN: (纸本)0780307348

An effective method for evaluating the distribution system reliability using an artificial neural network (ANN) is proposed in the present paper. The ANN is constructed according to the back-propagation learning rule which is an iterative gradient algorithm designed to adjust the interconnection weights among processing elements. Therefore, the developed ANN is used to predict the distribution system reliability by the historic data. At the same time, the system average interruption frequency index (SAIFI and the system average interruption duration index (SAIDI) of a real distribution system are computed and compared with results generated by the network method. It was found that the deviation of the results computed by the proposed approach is below 1- and the required running time on a SUN network environment is less than 2 seconds. In addition, handling the distribution system configuration changes induced by overloading or faults, the ANN approach demonstrates an advantage over the network method. © 1992 IEEE.

关键词： Neural networks

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Impact of out-of-band interferers on MB-OFDM UWB transmission in radio over fiber systems

Impact of out-of-band interferers on MB-OFDM UWB transmissio...

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Optical Fiber Communication Conference, OFC 2012

作者： Hraimel, Bouchaib Zhang, Xiupu Ma, Luo Advanced photonic systems Lab Department of Electrical and Computer Engineering Concordia University Montreal QC H3G 1M8 Canada

ISBN: (纸本)9781557529381

We experimentally investigate the impact of out of band interferers on the performance of multiband OFDM UWB signal transmission in RoF systems. An acceptable EVM and ACPR of -17 dB and -20 dB can be achieved even after shifting by 30% from the optimum quadrature bias. Further improvement of EVM and ACPR can be achieved by using mixed polarization technique even under strong interference level when the bias is shifted near minimum transmission. © 2012 OSA.

关键词： Radio-over-fiber

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Formal verification of robot movements - A case study on home service robot SHR100

Formal verification of robot movements - A case study on hom...

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2005 IEEE International Conference on Robotics and Automation

作者： Kim, Moonzoo Kang, Kyo Chul Lee, Hyoungki Computer Science and Engineering Department Pohang University of Science and Technology Pohang Korea Republic of Interaction Lab. Samsung Advanced Institute of Technology Suwon Korea Republic of

ISBN: (纸本)078038914X

Home service robots have received much attention from both academia and industry because home service robots have wide range of potential applications such as home security, cleaning, etc. The robots need to add or update services frequently according to the changing needs of human users. Furthermore, reactive nature of the robots add complexity to develop robot applications. These challenges raise safety issues seriously. Considering that safe operation of home service robots is crucial, current practice of validating robot applications is, however, not mature enough for wide deployment of home service robots. In this paper, we present our experience of developing and formally verifying discrete control software of Samsung Home Robot (SHR) using Esterel. We give a brief background on Esterel, then illuminate our result in formally verifying stopping behavior of SHR. Through the verification, we could detect and solve a feature interaction problem which caused the robot not to stop when a user commanded the robot to stop. © 2005 IEEE.

关键词： Motion planning

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Fast shape matching and retrieval based on approximate dynamic space warping

Fast shape matching and retrieval based on approximate dynam...

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15th International Symposium on Artificial Life and Robotics, AROB '10

作者： Alajlan, Naif Advanced Lab. for Intelligent Systems Research Department of Computer Engineering King Saud University P.O.Box 51178 Riyadh 11543 Saudi Arabia

ISBN: (纸本)9784990288044

Dynamic space warping (DSW) has emerged as a very effective tool for matching shapes. However, a central computational difficulty associated with DSW arises when a boundary's starting point (or rotation angle) is unknown. In this paper, the HopDSW algorithm is proposed to speed up the starting point computation. Rather than performing an exhaustive search for the correct starting point as in classical approaches, the proposed algorithm operates in a coarse-to-fine manner. The coarse search is global and uses a hopping step to exclude points from the search. Then, the search is refined in the neighborhood of the solution of the coarse search. A criterion that governs selecting the hopping step parameter is given, which reduces the number of starting point computations by an order. For shape representation, triangle area signature (TAS) is computed from triangles formed by the boundary points. Experimental results on the MPEG-7 CE-1 database of 1400 shapes show that the proposed algorithm returns the solution of the exhaustive search with a high degree of accuracy and a considerable reduction in the number of computations. © 2010 ISAROB.

关键词： Dynamic programming

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Improved Drain Current Density of E-Mode AlGaN/GaN HEMT with Double-Doped P-Gate 14

Improved Drain Current Density of E-Mode AlGaN/GaN HEMT with...

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14th IEEE International Conference on Solid-State and Integrated Circuit Technology, ICSICT 2018

作者： Kuang, Wenteng Sun, Hui Liu, Meihua Lin, Xinnan Chen, Dongmin Shenzhen Key Lab of Advanced Electron Device and Integration School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China

ISBN: (纸本)9781538644409

A novel E-mode AlGaN/GaN HEMT with double-doped p-gate (DDP) is proposed to improve output current and verified by TCAD simulation. The heavily p-doped region of the AlGaN gate layer ensures enhancement-mode (E-mode) operation and the lightly p-doped region of the AlGaN gate layer reduces the channel resistance. The simulated results have demonstrated that DDP HEMT delivers a much larger maximum drain current (IMAX = 334 mA/mm) than the conventional p-gate (CP) HEMT (IMAX = 144 mA/mm) while maintaining a high threshold voltage (VTH ~1.5 V). The simulated results also indicate that the DDP gate structure could decrease the peak electric field (EC) and thus improve the reliability of the device under off-state high-drain-bias (HDBT). © 2018 IEEE.

关键词： Aluminum gallium nitride

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Automated Detection of Epileptic Spikes and Seizures Incorporating a Novel Spatial Clustering Prior

arXiv

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arXiv 2025年

作者： Dong, Hanyang Sheng, Shurong Wang, Xiongfei Gao, Jia-Hong Sun, Yi Yang, Wanli Xiao, Kuntao Teng, Pengfei Luan, Guoming Lv, Zhao School of Artificial Intelligence Anhui University Hefei230601 China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230088 China Department of Neurosurgery Beijing Key Laboratory of Epilepsy Sanbo Brain Hospital Capital Medical University Beijing China McGovern Institute for Brain Research Peking University Beijing China Center for MRI Research Academy for Advanced Interdisciplinary Studies Peking University Beijing China Beijing City Key Lab for Medical Physics and Engineering Institute of Heavy Ion Physics School of Physics Peking University Beijing China Anhui Province Key Laboratory of Multimodal Cognitive Computation School of Computer Science and Technology Anhui University Hefei230601 China

A Magnetoencephalography (MEG) time-series recording consists of multi-channel signals collected by superconducting sensors, with each signal’s intensity reflecting magnetic field changes over time at the sensor location. Automating epileptic MEG spike detection significantly reduces manual assessment time and effort, yielding substantial clinical benefits. Existing research addresses MEG spike detection by encoding neural network inputs with signals from all channel within a time segment, followed by classification. However, these methods overlook simultaneous spiking occurred from nearby sensors. We introduce a simple yet effective paradigm that first clusters MEG channels based on their sensor’s spatial position. Next, a novel convolutional input module is designed to integrate the spatial clustering and temporal changes of the signals. This module is fed into a custom MEEG-ResNet3D developed by the authors, which learns to extract relevant features and classify the input as a spike clip or not. Our method achieves an F1 score of 94.73% on a large real-world MEG dataset Sanbo-CMR collected from two centers, outperforming state-of-the-art approaches by 1.85%. Moreover, it demonstrates efficacy and stability in the Electroencephalographic (EEG) seizure detection task, yielding an improved weighted F1 score of 1.4% compared to current state-of-the-art techniques evaluated on TUSZ, whch is the largest EEG seizure dataset. Copyright © 2025, The Authors. All rights reserved.

关键词： Magnetoencephalography

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