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International Conference on System Science and engineering (ICSSE)

作者： Shang-Wen Wong Yu-Chen Chiu Chi-Yi Tsai Doctoral Program in Robotics College of Engineering Tamkang University New Taipei City Taiwan Department of Electrical and Computer Engineering Tamkang University New Taipei City Taiwan

This paper proposes a pose estimation system for robot grasping based on a novel Object Affordance Detection and Segmentation (OADS) network. The proposed system consists of four modules: (1) OADS network; (2) point cloud extraction; (3) object pose estimation; (4) grasp pose estimation. Based on the OADS network, the proposed system achieves affordance-based object pose estimation results. The proposed grasp pose estimation system is evaluated on a laboratory-made dual-arm robot. Experimental results show that the proposed system achieves high detection rate and high accuracy in affordance detection and segmentation tasks, leading to a high success rate in object grasping tasks with lab-made dual-arm robot.

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GPU-Accelerated Vecchia Approximations of Gaussian Processes for Geospatial Data using Batched Matrix Computations

GPU-Accelerated Vecchia Approximations of Gaussian Processes...

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ISC High Performance 2024 Research Paper Proceedings (39th International Conference)

作者： Qilong Pan Sameh Abdulah Marc G. Genton David E. Keyes Hatem Ltaief Ying Sun Division of Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Statistics Program Extreme Computing Research Center King Abdullah University of Science and Technology Thuwal Jeddah Saudi Arabia

Gaussian processes (GPs) are commonly used for geospatial analysis, but they suffer from high computational complexity when dealing with massive data. For instance, the log-likelihood function required in estimating the statistical model parameters for geospatial data is a computationally intensive procedure that involves computing the inverse of a covariance matrix with size $n$ × n, where $n$ represents the number of geographical locations in the simplest case. As a result, in the literature, studies have shifted towards approximation methods to handle larger values of $n$ effectively while maintaining high accuracy. These methods encompass a range of techniques, including low-rank and sparse approximations. Among these techniques, Vecchia approximation is one of the most promising methods to speed up evaluating the log-likelihood function. This study presents a parallel implementation of the Vecchia approximation technique, utilizing batched matrix computations on contemporary GPUs. The proposed implementation relies on batched linear algebra routines to efficiently execute individual conditional distributions in the Vecchia algorithm. We rely on the KBLAS linear algebra library to perform batched linear algebra operations, reducing the time to solution compared to the state-of-the-art parallel implementation of the likelihood estimation operation in the ExaGeoStat software by up to 700X, 833X, 1380X on 32GB GV100, 80GB A100, and 80GB H100 GPUs, respectively, with the largest matrix dimension that can fully fit into the GPU memory in the dense Maximum Likelihood Estimation (MLE) case. We also successfully manage larger problem sizes on a single NVIDIA GPU, accommodating up to 1 million locations with 80GB A100 and H100 GPUs while maintaining the necessary application accuracy. We further assess the accuracy performance of the implemented algorithm, identifying the optimal settings for the Vecchia approximation algorithm to preserve accuracy on two real geos

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Wireless Galvanic Impulse Communication for High-Throughput, Low-Power, Miniaturized Neuromodulation Implants

Wireless Galvanic Impulse Communication for High-Throughput,...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Morgan Riley FNU Tala Mehdi Bandali Benjamin C. Johnson Biomedical Engineering Doctoral Program Boise State University Boise ID USA Dept. of Electrical and Computer Engineering Boise State University Boise ID USA

Deeply implanted bioelectronic devices that selectively record and stimulate peripheral nerves have the potential to revolutionize healthcare by delivering on-demand, personalized therapy. A key barrier to this goal is the lack of a miniaturized, robust, and energy-efficient wireless link capable of transmitting data from multiple sensing channels. To address this issue, we present a wireless galvanic impulse link that uses two 500μm diameter planar electrodes on the outside of a nerve cuff to transmit data to a wearable receiver on the skin’s surface at rates greater than 1Mbps. To achieve an energy-efficient, high data rate link, our protocol encodes information in the timing of narrow biphasic pulses that is reconstructed by the wearable receiver. We use a combination of modeling and in vivo and in vitro experimentation to demonstrate the viability of the link. We demonstrate losses lower than 60dB even with significant, 50mm lateral misalignment, ensuring a sufficient signal-to-noise ratio for robust operation. Using a custom, flexible nerve cuff, we demonstrate data transmission in a 14mm-thick rodent animal model and in a 42mm-thick heterogeneous human tissue phantom.

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Evaluating the Influence of Phase-Locked Loops on the Response of Grid-Following Inverter-Based Resources to Interconnection Transmission Line Faults

Evaluating the Influence of Phase-Locked Loops on the Respon...

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Workshop on Communication Networks and Power Systems (WCNPS)

作者： Pedro Henrique de Morais Martins Luciano Sales Barros Felipe Vigolvino Lopes Postgraduate Program in Renewable Energies Federal University of Paraíba Department of Computer Systems Federal University of Paraíba Department of Electrical Engineering Federal University of Paraíba

ISBN: (数字)9798331507152

ISBN: (纸本)9798331507169

In this paper, the influence of different Phase-Locked Loops (PLLs) on the fault response of a grid-following (GFL) Inverter-Based Resource (IBR) is evaluated. The analyzed IBR represents a wind power plant with rated power equal to 100 MVA, being composed of 50 turbines with 2 MVA each, whose controls follow the Brazilian grid code. Two PLL models are taken into account to conduct the proposed studies, which include the analysis of voltage and frequency estimated by each PLL, and currents injected into the IBR interconnection transmission line. The Synchronous Reference Frame (SRF) PLL and the Quadrature Signal Generator-based Second-Order Generalized Integrator (QSG-SOGI) PLL are considered, assessing their influence under different transmission line fault scenarios. The obtained results indicate that the PLL can present severe instabilities during faults, which can be more or less critical depending on the fault type and on the PLL type. Indeed, the results reveal that different PLLs can result in distinct behaviors of currents injected into the interconnection line, raising the importance of knowing the PLL structures when studies on IBR fault responses are of interest.

关键词： Power transmission lines Grid following Conferences Voltage Wind power generation Power system stability Frequency estimation Phase locked loops Inverter-based resource Turbines

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Microwave-Based Complementary Split-Ring Resonator for the Detection of Variations in Aqueous Media

Microwave-Based Complementary Split-Ring Resonator for the D...

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Microelectronics Technology and Devices (SBMicro)

作者： Reinaldo Velásquez Diego Tami Gilberto Medeiros-Ribeiro Cássio G. Rego Jhonattan C. Ramirez Graduate Program in Electrical Engineering UFMG Brazil Institute of Technological Sciences UNIFEI Brazil Department of Computer Science UFMG Brazil Department of Electronics Engineering UFMG Brazil

In this paper, we demonstrated a highly sensitive microwave-based resonator sensor capable of detecting variations in an aqueous medium of up to 0.94 mg/dL. In the presented device, the intrinsic resonant response (resonant amplitude, resonant frequency, and quality factor) is capacitively perturbed in reaction to the sample presence. To achieve higher sensitivity, the sample under testing generally is placed on the resonator surface, where the electric field is highly concentrated at the operating frequency. Thus, demonstrating excellent results in terms of sensitivity and reproducibility.

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A Framework to Support Collection, Processing and Analysis of Smart Vehicles Data

A Framework to Support Collection, Processing and Analysis o...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Mariana Azevedo Thais Medeiros Morsinaldo Medeiros Carlos M. D. Viegas Marianne Silva Ivanovitch Silva Daniel G. Costa Postgraduate Program in Electrical and Computer Engineering (PPgEEC) Federal University of Rio Grande do Norte - Natal Brazil INEGI Faculty of Engineering University of Porto Porto Portugal

ISBN: (数字)9798350311617

ISBN: (纸本)9798350311624

Thanks to the Internet of Things (IoT) revolution and advancements in embedded systems, the incorporation of an extensive array of sensors and computational resources into vehicles has become a reality, significantly enhancing their capabilities to produce relevant data. This has opened up new opportunities for acquiring and processing vehicular data in various areas, supporting new applications such as vehicular monitoring to the use of information for artificial intelligence for improved decision-making tasks. However, although the benefits are promising, there is a current challenge when providing flexible and standardized procedures to capture, process, and store this information for further analysis. In this context, this article proposes an framework to support the the handling of vehicular data, including data processing by a server and storage in a cloud database. This framework was validated through a real-world case study, analyzing the collected sensor data. The results indicated the feasibility of the proposal, contributing to the availability of vehicular data analysis in a way that is distinct from proposals in the literature. Additionally, this framework offers another significant contribution, related to the use of an appropriate database for time series, enabling scalability and high availability.

关键词： Data analysis Torque Databases Time series analysis Proposals Internet of Things Servers

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Automatic 2D Material Detection in Optical Images using Deep Learning Based computer Vision 4

Automatic 2D Material Detection in Optical Images using Deep...

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AI and Optical Data Sciences IV 2023

作者： Ramezani, Fereshteh Parvez, Sheikh Fix, J. Pierce Battaglin, Arthur Whyte, Seamus Borys, Nicholas J. Whitaker, Bradley Electrical and Computer Engineering Department Montana State University Bozeman United States Department of Physics Montana State University Bozeman United States Materials Science Program Montana State University Bozeman United States Optical Technology Center Montana State University Bozeman United States

ISBN: (纸本)9781510659810

computer vision algorithms can quickly analyze numerous images and identify useful information with high accuracy. Recently, computer vision has been used to identify 2D materials in microscope images. 2D materials have important fundamental properties allowing for their use in many potential applications, including many in quantum information science and engineering. In order to use these materials for research and product development, single-layer 2D crystallites must be prepared through an exfoliation procedure and then identified using reflected light optical microscopy. Performing these searches manually is a time-consuming and tedious task. Deploying deep learning-based computer vision algorithms for 2D material search can automate the flake detection task with minimal need for human intervention. In this work, we have implemented a new deep learning pipeline to classify crystallites of 2D materials based on coarse thickness classifications in reflected-light optical micrographs. We have used DetectorRS as the object detector and trained it on 177 images containing hexagonal boron nitride (hBN) flakes of varying thickness. The trained model achieved a high detection accuracy for the rare category of thin flakes ( © 2023 SPIE.

关键词： Object detection

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Correcting Negative Bias in Large Language Models through Negative Attention Score Alignment

arXiv

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arXiv 2024年

作者： Yu, Sangwon Song, Jongyoon Hwang, Bongkyu Kang, Hoyoung Cho, Sooah Choi, Junhwa Joe, Seongho Lee, Taehee Gwon, Youngjune L. Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of Samsung SDS Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

A binary decision task, like yes-no questions or answer verification, reflects a significant real-world scenario such as where users look for confirmation about the correctness of their decisions on specific issues. In this work, we observe that language models exhibit a negative bias in the binary decisions of complex reasoning tasks. Based on our observations and the rationale about attention-based model dynamics, we propose a negative attention score (NAS) to systematically and quantitatively formulate negative bias. Based on NAS, we identify attention heads that attend to negative tokens provided in the instructions as answer candidate of binary decisions, regardless of the question in the prompt, and validate their association with the negative bias. Additionally, we propose the negative attention score alignment (NASA) method, which is a parameter-efficient fine-tuning technique to address the extracted negatively biased attention heads. Experimental results from various domains of reasoning tasks and large model search space demonstrate that NASA significantly reduces the gap between precision and recall caused by negative bias while preserving their generalization abilities. Our codes are available at https://***/ysw1021/NASA. Copyright © 2024, The Authors. All rights reserved.

关键词： NASA

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Hysteresis Amplifier Model to Eliminate Multi-switching on IGBT Work

Hysteresis Amplifier Model to Eliminate Multi-switching on I...

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International Conference on electrical engineering, computer Science and Informatics (EECSI)

作者： Indra Roza Ira Devi Sara Tarmizi Tarmizi Nasaruddin Nasaruddin Doctoral Program School of Engineering Universitas Syiah Kuala Banda Aceh Indoensia Dept. Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia

The occurrence of multi-switching on an isolated gate bipolar transistor (IGBT) function can cause significant power dissipation and disrupt the power network. To overcome this problem, this paper designs a hysteresis amplifier model to reduce multi-switching in IGBTs. This software is used to simulate and analyze the performance of the hysteresis model amplifier. The hysteresis amplifier design is used to induce a hysteresis effect on the IGBT control signal. This effect produces an output frequency of 50 Hz with a 50% duty cycle. The working mechanism of this design includes the formation of a hysteresis window on the IGBT control signal, +2.00 V to +2.52 V. If the design result of the control signal is at least +2.50 V to +2.48 V, the IGBT enters the active state when Vout1 reaches +3.51 V. The design results in the control signal reaching a maximum value of +2.50 V to +2.51 V. The IGBT transitions to the active state when the voltage at Vout2 reaches a threshold of +3.51 V. The automatic implementation of the hysteresis window effectively reduces the occurrence of multi-switching by ensuring that a switch event occurs when the control signal is within the specified hysteresis window range. The current transformer detects changes in current through the variable resistor when Vin +2.00V to Vin +2.52 V. By understanding the characteristics and implementation of the model, it is possible to formulate intelligent control strategies aimed at increasing the efficiency and stability of system power through the use of IGBT.

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Harmonics Step Filter Control Model In Household Electricity

Harmonics Step Filter Control Model In Household Electricity

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computer System, Information Technology, and electrical engineering (COSITE), International Conference on

作者： Faisal Irsan Pasaribu Ira Devi Sara Tarmizi Tarmizi Nasaruddin Nasaruddin Doctoral Program School of Engineering Universitas Syiah Kuala Banda Aceh Indonesia Dept. Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia

A passive harmonic filter is a type of filter designed to mitigate the adverse impacts of harmonics by effectively attenuating multiple harmonic frequencies or a broad frequency spectrum. The objective of implementing a double-tuned damped passive filter is to improve the overall performance of the system with respect to electric power quality. This paper is to develop a simulation model for a harmonic step filter control system that meets the requirements of household electricity. This system is designed to regulate various parameters such as current, voltage, frequency, power factor, active power, and reactive power of the electrical load. The ultimate goal is to enhance control and improve the quality of electricity consumption. household. The proposed research methodology involves the development of a 6-step control simulation model utilizing Matlab Simulink. Subsequently, a control design model will be implemented using the ESP 32 microcontroller, PZEM004t sensor, and PZCT-02CT sensor. Additionally, a relay module will be employed to activate the damped double-tuned filter. This relay module comprises 6 steps, each equipped with a filter designed to respond gradually based on the power quality value. The results show that the Total Harmonic Distortion Voltage (THDv) is at 7.07%, the Total Harmonic Distortion Current (THDi) is at 47.55%, and a power factor of 0.68. By implementing the proposed damped double-tuned filter, a reduction in harmonic values can be achieved. Specifically, the THDv can be reduced to 1.1%, the THDi can be reduced to 0.65%, and the power factor can be improved to 0.77.

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