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International Conference on Computing, engineering, and Design (ICCED)

作者： Agung Pangestu Iing Sodikin Muhammad Yusro Rum Sapundani Rosyid Ridlo Al Hakim Sinka Wilyanti Electrical Engineering Department Faculty of Engineering and Computer Science Jakarta Global University Depok Indonesia Department of Electronic Engineering Faculty of Engineering State University of Jakarta Jakarta Indonesia Electromedical Engineering Technology Faculty of Health Science University of Muhammadiyah Purwokerto Purwokerto Indonesia Graduate Program in Electrical Engineering Faculty of Engineering and Computer Science Jakarta Global University Depok Indonesia

ISBN: (纸本)9781665453905

Research has been carried out to monitor vehicle tires before they are used and can reduce damage, including overcoming vehicle fuel waste because air pressure is continuously monitored. This research aims to utilize the MPX5500DP sensor as an air pressure device, the LM35 sensor as a temperature reader, and a buzzer based on IoT to build a tire pressure monitoring system (TPMS). The MPX5500DP and LM35 sensor inputs to the Arduino Uno microcontroller are distributed by the NodeMCU, fitted with a Wi-Fi module. The Blynk application sends and displays the data on a smartphone using the IoT-based. Based on this research, data on the percentage of errors in monitoring air pressure and tire temperature on vehicles were obtained by comparing the data to the pressure gauge and thermometer: 1—the results of the average reading of the sensor error value. MPX5500DP air pressure against pressure gauge is 5.3%. 2—the average reading of the LM35 sensor error value on the temperature thermometer is 6.8%. With this research, the air pressure and temperature in the tires can be monitored in real-time via a smartphone using the IoT-based.

关键词： Temperature measurement Temperature distribution Thermometers Microcontrollers Tire pressure Real-time systems Pressure gauges

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Waveform Development for Neurotransmitter Detection on Novel Boron-Doped Diamond Microelectrodes

Waveform Development for Neurotransmitter Detection on Novel...

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International IEEE/EMBS Conference on Neural engineering, CNE

作者： Bhavna Gupta Mason L. Perillo Isabelle E. Christensen James R. Siegenthaler Robert Rechenberg Michael F. Becker Wen Li Erin K. Purcell Neuroscience Program at Michigan State University East Lansing MI USA Department of Biomedical Engineering Michigan State University East Lansing MI USA Department of Mechanical Engineering Michigan State University East Lansing MI USA Fraunhofer Center Midwest East Lansing MI USA Department of Electrical and Computer Engineering Michigan State University East Lansing MI USA Department of Biomedical Engineering and the Department of Electrical and Computer Engineering Michigan State University East Lansing MI USA

Technologies capable of detecting changes in neurochemical signals can be used to understand the underlying mechanisms of neurological diseases. They are also important components of systems which rely on neurochemical sensing as a source of feedback for closed-loop neuromodulation[1], [2]. Recently, our research team has developed a boron-doped diamond microelectrode (BDDME) fiber for neurotransmitter detection using fast-scan cyclic voltammetry (FSCV). These electrodes have several potential benefits in comparison to more traditional, carbon fiber microelectrodes (CFMEs), including a wider working potential window, customizable fabrication, and increased resistance to etching. Given the unique characteristics of BDDMEs in comparison to CFMEs, there is a need to re-examine and optimize the potential waveforms used for neurotransmitter detection. In this study, we explored waveform parameters (holding potential, scan rate, and application frequency) for serotonin detection on BDDME fibers. We found that frequency attenuation of normalized peak currents was mitigated on BDDMEs in comparison to CFMEs. Effects of varying holding potential and scan rate were qualitatively similar between the two electrode types. Frequency effects suggest that repeating the measurements at BDDME at higher frequency does not decrease the current as drastically as on the CFME. However, both electrodes showed optimal current response at 10 Hz. These studies represent an important step forward in our development of a next-generation, chronically implantable electrochemical sensor for neurotransmitter detection.

关键词： Resistance Electric potential Optical fiber sensors Microelectrodes Neurotransmitters Diamonds Frequency measurement

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Corner cutting connects chiral colorimetry to net electric flux in lossless all-dielectric metasurfaces

arXiv

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arXiv 2024年

作者： Haddadin, Zaid Nguyen, Anna M.Y. Poulikakos, Lisa V. Department of Electrical & Computer Engineering UC San Diego La Jolla CA92093-0021 United States Department of Mechanical & Aerospace Engineering UC San Diego La Jolla CA92093-0021 United States Program of Materials Science & Engineering UC San Diego La Jolla CA92093-0021 United States

All-dielectric metasurfaces can produce structural colors, but the most advantageous design criteria are still being investigated. This work numerically studies how the two-dimensional shape of nanoparticles affects the colorimetric response under circularly polarized light (CPL) to develop a sensor distinguishing CPL orientations. Using lossless dielectric materials (silicon nitride on silicon dioxide), we achieve far-field dichroism by modifying oblong nanoparticles into L-shaped structures through corner cuts. This design suppresses one electric dipole under CPL illumination, leading to differential colorimetric responses. We link these responses to a decoupling effect in the near-field net electric flux. Our findings provide design guidelines for all-dielectric, lossless colorimetric sensors of chiral light. Copyright © 2024, The Authors. All rights reserved.

关键词： Silicon nitride

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A Development of Object Detection System based on Deep Learning Approach to Support the Laparoscope Manipulating Robot (LMR)

A Development of Object Detection System based on Deep Learn...

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2022 International electrical engineering Congress, iEECON 2022

作者： Sonsilphong, Suphachoke Sonsilphong, Amornthep Hormdee, Daranee Khampitak, Kovit Khon Kaen University Data Science Health Informatics Program Academic Affairs Faculty of Medicine Khon Kaen Thailand Rajamangala University of Technology Isan Department of Electrical Engineering Khon Kean Thailand Khon Kaen University Embedded System RD Group Department of Computer Engineering Faculty of Engineering Khon Kean Thailand Khon Kean University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kean Thailand

ISBN: (纸本)9781665402064

This paper presents the development of an object detection system based on the deep learning approach of computer vision to support the laparoscopic surgical robotic position control system. The system comprises two main phases, the training phase, and the real-time operating phase. In the training phase, a modified YOLOv4 algorithm is proposed to be adopted within the Darknet framework for training the weights of detection models. The best detection model is then selected to be assigned to the object detector in the real-time operating phase. The validation result of the detection model across the experiment datasets is 90% accuracy on average during the training phase. To validate the viability of real-time object detection, the proposed system was implemented in two test-cases of gynecologic surgery with the soft-body cadavers. © 2022 IEEE.

关键词： Laparoscopy

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Adaptive Environment-Aware Robotic Arm Reaching Based on a Bio-Inspired Neurodynamical Computational Framework

Adaptive Environment-Aware Robotic Arm Reaching Based on a B...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Dimitrios Chatziparaschis Shan Zhong Vasileios Christopoulos Konstantinos Karydis Dept. of Electrical and Computer Engineering Univ. of California Riverside Riverside CA USA Neuroscience Graduate Program Univ. of California Riverside Riverside CA USA Dept. of Bioengineering Univ. of California Riverside Riverside CA USA

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Bio-inspired robotic systems are capable of adaptive learning, scalable control, and efficient information processing. Enabling real-time decision-making for such systems is critical to respond to dynamic changes in the environment. We focus on dynamic target tracking in open areas using a robotic six-degree-of-freedom manipulator with a bird-eye view camera for visual feedback, and by deploying the Neurodynamical Computational Framework (NeuCF). NeuCF is a recently developed bio-inspired model for target tracking based on Dynamic Neural Fields (DNFs) and Stochastic Optimal Control (SOC) theory. It has been trained for reaching actions on a planar surface toward localized visual beacons, and it can retarget or generate stop signals on the fly based on changes in the environment (e.g., a new target has emerged, or an existing one has been removed). We evaluated our system over various target-reaching scenarios. In all experiments, NeuCF had high end-effector positional accuracy, generated smooth trajectories, and provided reduced path lengths compared with a baseline cubic polynomial trajectory generator. In all, the developed system offers a robust and dynamic-aware robotic manipulation approach that affords real-time decision-making.

关键词： Visualization Accuracy Target tracking Robot vision systems Real-time systems Polynomials Generators Trajectory Robots Manipulator dynamics

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Design of an Assisted Learning System Based on ChatGPT 23

Design of an Assisted Learning System Based on ChatGPT

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Proceedings of the 2023 6th Artificial Intelligence and Cloud Computing Conference

作者： Chia-Chuan Tsao Yen-Hung Lin Chien-Hsing Chou Kuan-Ning Chang Ping-Hsuan Han Department of Mathematics and Information Education National Taipei University of Education Taiwan Department of Electrical and Computer Engineering Tamkang University Taiwan Doctoral Program in Design National Taipei University of Technology Taiwan Department of Interaction Design National Taipei University of Technology Taiwan

ISBN: (纸本)9798400716225

This paper describes a system that utilizes ChatGPT as an auxiliary learning tool to assist students in overcoming learning difficulties. By providing ChatGPT with relevant domain-specific knowledge in advance, the system enhances the accuracy of responses. Additionally, the interface design facilitates students in posing high-quality questions, thereby obtaining precise answers. This paper aims to use this system design to help students address learning challenges, increase motivation for learning, and reduce the cost of developing domain-specific chatbots, thus enabling its application in a broader range of educational fields.

关键词： ChatGPT chatbot computer-assisted instruction question-answering system teaching and learning

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Optoelectric Raman Nanosensors: Overcoming Intrinsic Limit in Nano-biosensing

Research Square

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Research Square 2024年

作者： Lian, Bin Li, Huaizhi Guo, Jianhe Fan, Donglei Emma Materials Science and Engineering Program Texas Materials Institute The University of Texas AustinTX78712 United States Walker Department of Mechanical Engineering Texas Materials Institute The University of Texas at Austin AustinTX78712 United States Chandra Family Department of Electrical and Computer Engineering The University of Texas at Austin AustinTX78712 United States

It is intrinsically difficult to detect low-concentration biomolecules with both ultra-sensitivity and high speed for early-stage disease diagnosis. The challenge originates from the small size of nanosensors, which enables ultra-sensitivity biosensing, while also substantially increases the detection time of dilute molecules. in this work, we report an original optoelectric sensing scheme, along with an innovative device design and a strategic fabrication approach to overcome such a challenge in biosensing. The proposed scheme exploits the profound optoelectric effect of semiconductor silicon nanowires, which can readily enrich trace-amounts of biomolecules at the point of laser and simultaneously detect Raman signals of focused molecules. The device design includes large arrays of silicon nanorods with electrodes integrated at their roots, and surface-distributed dense plasmonic silver nanoparticles for surface-enhanced Raman spectroscopy (SERS) detection. Operating at only -0.8 V in an electrochemical cell, these optoelectric nanosensors readily achieve a 150-fold signal enhancement, improving the detection limit of probing molecules, adenine, by five orders of magnitude, to 0.6 fM. The enhancement effect is robust, observed across concentrations from 1 μM to 1 fM. The working mechanism is general, not only for detecting small molecules, such as adenine, but also for large charged molecules, such as Vertebrate DNA. The underlying novel mechanism is unraveled by multiscale numerical simulations and calculations. This research, addressing an arduous bottleneck issues in nanobiosensing, is expected to inspire a new class of biochemical sensors, important for the practical detection of trace-amount biochemicals in solution, important for clinic relevant early-stage disease diagnostics. © 2024, CC BY.

关键词： Nanorods

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Wigner non-negative states that verify the Wigner entropy conjecture

arXiv

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arXiv 2024年

作者： Qian, Qipeng Gagatsos, Christos N. Program in Applied Mathematics The University of Arizona TucsonAZ85721 United States Department of Electrical and Computer Engineering The University of Arizona TucsonAZ85721 United States Wyant College of Optical Sciences The University of Arizona TucsonAZ85721 United States

We present further progress, in the form of analytical results, on the Wigner entropy conjecture set forth in [Phys. Rev. A 104, 042211 (2021)] and [J. Phys. A: Math. Theor. 50 385301]. Said conjecture asserts that the differential entropy defined for non-negative, yet physical, Wigner functions is minimized by pure Gaussian states while the minimum entropy is equal to 1 + ln π. We prove this conjecture for the qubits formed by Fock states |0) and |1) that correspond to non-negative Wigner functions. In particular, we derive an explicit form of the Wigner entropy for those states lying on the boundary of the set of Wigner non-negative qubits. We then consider general mixed states and derive a sufficient condition for the conjecture’s validity. Lastly, we elaborate on the states which are in accordance with our condition. Copyright © 2024, The Authors. All rights reserved.

关键词： Entropy

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Ev-TTA: Test-Time Adaptation for Event-Based Object Recognition

arXiv

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arXiv 2022年

作者： Kim, Junho Hwang, Inwoo Kim, Young Min Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence INMC Seoul National University Korea Republic of

We introduce Ev-TTA, a simple, effective test-time adaptation algorithm for event-based object recognition. While event cameras are proposed to provide measurements of scenes with fast motions or drastic illumination changes, many existing event-based recognition algorithms suffer from performance deterioration under extreme conditions due to significant domain shifts. Ev-TTA mitigates the severe domain gaps by fine-tuning the pre-trained classifiers during the test phase using loss functions inspired by the spatio-temporal characteristics of events. Since the event data is a temporal stream of measurements, our loss function enforces similar predictions for adjacent events to quickly adapt to the changed environment online. Also, we utilize the spatial correlations between two polarities of events to handle noise under extreme illumination, where different polarities of events exhibit distinctive noise distributions. Ev-TTA demonstrates a large amount of performance gain on a wide range of event-based object recognition tasks without extensive additional training. Our formulation can be successfully applied regardless of input representations and further extended into regression tasks. We expect Ev-TTA to provide the key technique to deploy event-based vision algorithms in challenging real-world applications where significant domain shift is inevitable. © 2022, CC BY.

关键词： Object recognition

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The KIND Dataset: A Social Collaboration Approach for Nuanced Dialect Data Collection 18

The KIND Dataset: A Social Collaboration Approach for Nuance...

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18th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2024 - Student Research Workshop, SRW 2024

作者： Yamani, Asma Z. Alziyady, Raghad AlYami, Reem Albelali, Salma A. Abouhagar, Leina Almulhim, Jawharah Alsulami, Amjad Alfarraj, Motaz Al-Zaidy, Rabeah Department of Information and Computer Science King Fahd University of Petroleum & Minerals Saudi Arabia Center for Integrative Petroleum Research CIPR King Fahd University of Petroleum & Minerals Saudi Arabia Department of Electrical Engineering King Fahd University of Petroleum & Minerals Saudi Arabia SDAIA-KFUPM Joint Research Center for AI King Fahd University of Petroleum & Minerals Saudi Arabia Preparatory Year Program King Fahd University of Petroleum & Minerals Saudi Arabia Department of Computer Science Imam Abdulrahman Bin Faisal University Saudi Arabia Saudi Data & AI Authority Saudi Arabia

ISBN: (纸本)9798891760905

Nuanced dialects are a linguistic variant that pose several challenges for NLP models and techniques. One of the main challenges is the limited amount of datasets to enable extensive research and experimentation. We propose an approach for efficiently collecting nuanced dialectal datasets that are not only of high quality, but are versatile enough to be multipurpose as well. To test our approach we collect the KIND corpus, which is a collection of fine-grained Arabic dialect data. The data is short texts, and unlike many nuanced dialectal datasets, it is curated manually through social collaboration efforts as opposed to being crawled from social media. The collaborative approach is incentivized through educational gamification and competitions for which the community itself benefits from the open source dataset. Our approach aims to achieve: (1) coverage of dialects from under-represented groups and fine-grained dialectal varieties, (2) provide aligned parallel corpora for translation between Modern Standard Arabic (MSA) and multiple dialects to enable translation and comparison studies, (3) promote innovative approaches for nuanced dialect data collection. We explain the steps for the competition as well as the resulting datasets and the competing data collection systems. The KIND dataset is shared with the research community. © 2024 Association for Computational Linguistics.

关键词： Data acquisition

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