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arXiv 2024年

作者： Li, Kejia Wang, Mengen Department of Electrical and Computer Engineering and Materials Science and Engineering Program SUNY BinghamtonNY13902 United States

CsPbI3 has been recognized as a promising candidate for optoelectronic device applications. To further improve the efficiency of the devices, it is imperative to better understand the surface properties of CsPbI3, which affect charge carrier transport and defect formation properties. In this study, we perform density functional theory calculations to explore the stability of the (001), (110), and (100) surfaces of orthorhombic CsPbI3, considering different stoichiometries and surface reconstructions. Our results show that, under the chemical potentials confined by the thermodynamically stable region of bulk CsPbI3, the CsI-terminated surfaces of (001) and (110) and the stoichiometric surface of (100) are stable. Among these three surfaces, the CsI-terminated (110) surface has the lowest surface energy and no mid-gap states, which benefits the transport properties of the material. © 2024, CC BY-NC-SA.

关键词： Stoichiometry

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Quantifier Elimination in Stochastic Boolean Satisfiability 25

Quantifier Elimination in Stochastic Boolean Satisfiability

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25th International Conference on Theory and Applications of Satisfiability Testing, SAT 2022

作者： Wang, Hao-Ren Tu, Kuan-Hua Jiang, Jie-Hong Roland Scholl, Christoph Graduate Institute of Electronics Engineering National Taiwan University Taipei Taiwan Graduate Institute of Electronics Engineering Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Computer Science Universität Freiburg Germany

ISBN: (纸本)9783959772426

Stochastic Boolean Satisfiability (SSAT) generalizes quantified Boolean formulas (QBFs) by allowing quantification over random variables. Its generality makes SSAT powerful to model decision or optimization problems under uncertainty. On the other hand, the generalization complicates the computation in its counting nature. In this work, we address the following two questions: 1) Is there an analogy of quantifier elimination in SSAT, similar to QBF? 2) If quantifier elimination is possible for SSAT, can it be effective for SSAT solving? We answer them affirmatively, and develop an SSAT decision procedure based on quantifier elimination. Experimental results demonstrate the unique benefits of the new method compared to the state-of-the-art solvers. © Hao-Ren Wang, Kuan-Hua Tu, Jie-Hong Roland Jiang, and Christoph Scholl.

关键词： Stochastic systems

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Surgical Tool Occlusion Detection and Segmentation Using Deep Transfer Learning: A Machine Vision Approach

Surgical Tool Occlusion Detection and Segmentation Using Dee...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Sevilla, Rovenson Alon, Alvin Sarraga Evangelista, Ryan S. Delos Santos Ligayo, Michael Angelo Arago, Ryan Flores Delos Santos, Ronnel Cabral Cunanan, Christopher Austria, Yolanda D. University of the Philippines Department of Electrical Engineering Technological Manila Philippines Center for AI Research Department of Trade and Industry Makati City Philippines School of Graduate Studies Sulu State College Sulu Philippines College of Engineering Quezon City University Quezon City Philippines College of Computing Studies Don Honorio Ventura State University Pampanga Philippines Bulacan State University Computer Engineering Department Bulacan Philippines Adamson University Department of Computer Engineering Manila Philippines

ISBN: (纸本)9798350369106

The combination of deep transfer learning and mask region-based convolutional neural network (Mask-RCNN) technology offers a groundbreaking approach to enhancing machine vision for surgical robots. The objective of this work is to enhance the accuracy and precision of identifying tools in surgical environments by investigating the use of deep transfer learning for detecting and segmenting occluded surgical tools. Our investigation exhibits the model's robustness in successfully recognizing and segmenting obstructed surgical tools, as seen by an exceptional Mean Average Precision (mAP) score of 93.8%. By conducting thorough testing and inference studies, the model demonstrated an outstanding ability to accurately identify various instruments, such as 'mayo,' 'clamp,' and 'scalpel,' even in difficult situations when objects were partially occluded. The use of Mask-RCNN enhances our investigation, representing a crucial advancement in enhancing surgical robotics with sophisticated segmentation skills. The research underscores the potential of Mask-RCNN in the field of machine vision for surgical robots, underlining the necessity for ongoing progress to tackle complexities for improved real-world implementation. © 2024 IEEE.

关键词： Machine vision

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Exploring the Science and Art of UAV Light Painting: From Equations and Pixels to Long-Exposure Photography

Exploring the Science and Art of UAV Light Painting: From Eq...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Leonardo A. Fagundes-Junior Celso O. Barcelos Raquel F. Vassallo Alexandre S. Brandão Department of Electrical Engineering Robotics Specialization Center Graduate Program on Computer Science Federal University of Viçosa Viçosa MG Brazil Department of Electrical Engineering Federal University of Espirito Santo Vitória ES Brazil

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

The use of Unmanned Aerial Vehicles (in short, UAVs, aka drones) for cultural and entertainment purposes, such as drone light shows, has grown exponentially. One such innovative and creative application is the visual arts using drones to explore long-exposure photography. Light painting are generally performed indoors and outdoors in a dedicated space with a human using a moving light source to create spectacular images and save the movement perception in a picture. In this work, we propose a robotic perception system designed to choreograph UAV movements based on time-parametric curves or image edges, serving as reference motions. Our framework begins by processing a digital image, extracting its contours through boundary tracing, and subsequently generating a safe, navigable, and precise path for UAV motion planning. This process involves optimizing waypoints within the UAV workspace to determine a feasible trajectory that encompasses all designated points or computes safe trajectories utilizing established mathematical equations. The validation of the motion planning is performed through light painting, where the UAV can either fly through the motion reference to mimic the original image. The generated trajectories on light painting mode by physical robots are compared against the ground-truth demonstrating the accuracy of the applied control scheme.

关键词： Photography Visualization Art Autonomous aerial vehicles Trajectory Planning Robots

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Enhancing Efficiency in Yolov8n for Real-Time Detection of Oil Palm Fruits in Plantations Using Mobileone and Cross-Fusion

SSRN

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SSRN 2024年

作者： Hugo, Gregory Mushlik, Muhammad Suharjito Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia

Accurate detection of fresh fruit bunches (FFB) ripeness in complex plantation environments is challenging due to occlusion, varying lighting, intricate visual features, and limited computational resources of mobile devices. To address this, a resource-efficient, real-time detection system was developed using an optimized YOLOv8n model. The model integrates MobileOne modules and Cross-Fusion blocks to enhance efficiency without compromising accuracy. Specifically, Conv and C2f modules were replaced with MobileOne modules, reducing parameters by 85% and 81%, respectively. Cross-Fusion improved feature fusion, and its combination with MobileOne (CF-MobileOne) achieved a 51% reduction in parameters while maintaining performance. The dataset comprised images from videos captured in plantations, annotated into five maturity stages: flower, unripe, underripe, ripe, and abnormal, and underwent augmentation with class balancing through manual undersampling. The model outperformed baseline YOLOv8 variants and heavier models like YOLOv9c and Faster R-CNN, achieving an mAP50 of 0.795 and an inference speed of 140.57 FPS. Hyperparameter tuning with a batch size of 64, SGD optimizer, and a learning rate of 0.01 yielded optimal results. Despite challenges in detecting certain classes due to visual similarities and environmental variations, the system effectively enhances productivity and efficiency in precision agriculture for the palm oil industry. © 2024, The Authors. All rights reserved.

关键词： Fruits

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Hardware Demonstration of Feedforward Stochastic Neural Networks with Fast MTJ-based p-bits

Hardware Demonstration of Feedforward Stochastic Neural Netw...

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2023 International Electron Devices Meeting, IEDM 2023

作者： Singh, Nihal Sanjay Niazi, Shaila Chowdhury, Shuvro Selcuk, Kemal Kaneko, Haruna Kobayashi, Keito Kanai, Shun Ohno, Hideo Fukami, Shunsuke Camsari, Kerem Y. University of California Santa Barbara Department of Electrical and Computer Engineering Santa BarbaraCA93106 United States Tohoku University Research Institute of Electrical Communication Sendai980-8577 Japan Tohoku University Graduate School of Engineering Sendai980-8577 Japan

ISBN: (纸本)9798350327670

Feedforward networks form the backbone of deep learning, used in deep multilayer perceptrons, convolutional neural networks, and deep belief networks. Even though stochastic activations of deep neural networks are highly desired, they are often avoided due to their heavy computational costs in traditional hardware. This paper presents the hardware implementation of inference in such deep feedforward stochastic networks with the fastest nanodevice-based probabilistic bits (p-bit) demonstrated to date. The stochasticity of low-barrier stochastic magnetic tunnel junctions (sMTJ) is used to create p-bits, routed back to a Field programmable Gate Array (FPGA) to build a hybrid CMOS+sMTJ computer. Unlike commonly implemented Boltzmann-Ising type undirected networks, feedforward networks require carefully ordered updates. We achieve such ordered updating by generating sequenced signals from the FPGA back to the p-bits. In addition, each neuron in a given layer is updated concurrently by the fluctuations of sMTJs, achieving layer-by-layer parallelism. Fast sMTJ-based p-bits are demonstrated using specially engineered sMTJs with in-plane anisotropy with microsecond fluctuations, three orders of magnitude faster than all previous demonstrations. We experimentally perform inference on two feedforward Belief Networks including a medical diagnosis example. We improve earlier projections based on the experimentally-demonstrated sMTJ parameters illustrating the potential of scaled-up versions of our system. © 2023 IEEE.

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Micromagnetics Simulation of Highly Efficient Oscillation of Magnetization in a Ferromagnetic Local Areas via Spin Waves Induced by Spin-Orbit Torque

Micromagnetics Simulation of Highly Efficient Oscillation of...

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2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023

作者： Koda, Tetsunori Muroga, Sho Endo, Yasushi Oshima College National Institute of Technology Department of Electronic Mechanical Engineering Suo-Oshima742-2193 Japan Akita University Graduate School of Engineering Science Department of Mathematical Science and Electrical-Electronic-Computer Engineering Akita010-8502 Japan Department of Electrical Engineering Graduate School of Engineering Tohoku University Sendai980-8579 Japan Tohoku University Center for Spintronics Research Network Sendai980-8577 Japan Sendai980-8577 Japan

ISBN: (纸本)9798350338362

We study numerical simulation of highly efficient oscillation of magnetization in a ferromagnetic local region using the spin-orbit torque. It is found that in the presence of multiple SOT regions, the precession motion can be excited at a lower current density through the interaction. This interaction is caused by spin waves, and as a result, phase control between the precession motions is possible through the gap between the areas. Our new finding indicates that the interaction between the wave source and the spin wave is very complex in devices that utilize the interference effects of spin waves. © 2023 IEEE.

关键词： Spin waves

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Set-based state estimation of a Li-ion cell using DC programming and constrained zonotopes

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IFAC-PapersOnLine 2023年第2期56卷 7147-7153页

作者： Angelo Tottoli Alesi A. de Paula Guilherme V. Raffo Bruno O.S. Teixeira Davide M. Raimondo Department of Electrical Computer and Biomedical Engineering University of Pavia Italy Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Electronic Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil

Advanced battery management systems (ABMSs) rely on mathematical models to ensure high battery safety and performance. One of the key tasks of a BMS is state estimation. In the following, we consider a single lithium-ion cell described with a dual polarization equivalent circuit model. To consider a realistic scenario, where the parameters have been identified from experimentally collected data, both parametric and measurement uncertainties are taken into account in the model. In particular, unknown but bounded uncertainties are assumed. In this setup, we address state estimation through a set-based approach using Constrained Zonotopes (CZ). Due to the model nonlinearities, a method able to propagate CZ through nonlinear mappings is demanded. Within this context, mean value and first-order Taylor CZ-based extensions were proposed which, however, might lead to conservative overestimation due to the sensitivity to the wrapping and dependency effects inherited from interval arithmetic. In the following, we suggest the use of DC programming as an alternative. The effectiveness of the proposed scheme is demonstrated in simulation for the considered Li-ion model.

关键词： Lithium-ion cells Nonlinear state estimation Uncertainty Set-based approach

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An Environmentally Friendly Fishing Android-Based Mobile Device App for Penghu Islands (Pescadores), Taiwan

An Environmentally Friendly Fishing Android-Based Mobile Dev...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Hung-Tu Lin Ke-Qing Yan Ying-Zun Fang Xiang-Rui Huang Liang-Bi Chen Department of Computer Science and Information Engineering National Penghu University of Science and Technology Penghu Taiwan Department of Electrical Engineering Master Program in Electrical Engineering and Computer Science National Penghu University of Science and Technology Penghu Taiwan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Penghu Islands (Pescadores), Taiwan's outlying islands surrounded by the sea, boast rich fishing resources that attract many anglers. However, successful fishing requires more than just gear: it involves understanding the varying fish species available in different locations, times, and climates, as well as adhering to relevant laws and regulations. To address these needs, this paper proposes an environmentally friendly fishing Android-based mobile device App specifically for the Penghu Islands. The proposed Android-based mobile device App aims to gather essential information, including local fishing regulations, aquatic safety tips, and important precautions. Its goal is to equip fishermen with the resources necessary to fish successfully and with peace of mind.

关键词： Sea measurements Length measurement Fish Regulation Mobile applications Tides Protection Smart phones Meteorology Lenses

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A review of hybrid EEG-based multimodal human–computer interfaces using deep learning: applications, advances, and challenges

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Biomedical engineering Letters 2025年 1-32页

作者： Lee, Hyung-Tak Shim, Miseon Liu, Xianghong Cheon, Hye-Ran Kim, Sang-Gyu Han, Chang-Hee Hwang, Han-Jeong Department of Electronics and Information Engineering Korea University 2511 Sejong-ro Jochiwon-eup Sejong-si30019 Korea Republic of Department of Artificial Intelligence Tech University of Korea Siheung Korea Republic of Department of Computer Information Korea University 2511 Sejong-ro Jochiwon-eup Sejong-si30019 Korea Republic of Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong Korea Republic of

Human–computer interaction (HCI) focuses on designing efficient and intuitive interactions between humans and computer systems. Recent advancements have utilized multimodal approaches, such as electroencephalography (EEG)-based systems combined with other biosignals, along with deep learning to enhance performance and reliability. However, no systematic review has consolidated findings on EEG-based multimodal HCI systems. This review examined 124 studies published from 2016 to 2024, retrieved from the Web of Science database, focusing on hybrid EEG-based multimodal HCI systems employing deep learning. The keywords used for evaluation were as follows: ‘Deep Learning’ AND ‘EEG’ AND (‘fNIRS’ OR ‘NIRS’ OR ‘MEG’ OR ‘fMRI’ OR ‘EOG’ OR ‘EMG’ OR ‘ECG’ OR ‘PPG’ OR ‘GSR’). Main topics explored are: (1) types of biosignals used with EEG, (2) neural network architectures, (3) fusion strategies, (4) system performance, and (5) target applications. Frequently paired signals, such as EOG, EMG, and fNIRS, effectively complement EEG by addressing its limitations. Convolutional neural networks are extensively employed for spatio-temporal-spectral feature extraction, with early and intermediate fusion strategies being the most commonly used. Applications, such as sleep stage classification, emotion recognition, and mental state decoding, have shown notable performance improvements. Despite these advancements, challenges remain, including the lack of real-time online systems, difficulties in signal synchronization, limited data availability, and insufficient explainable AI (XAI) methods to interpret signal interactions. Emerging solutions, such as portable systems, lightweight deep learning models, and data augmentation techniques, offer promising pathways to address these issues. This review highlights the potential of EEG-based multimodal HCI systems and emphasizes the need for advancements in real-time interaction, fusion algorithms, and XAI to enhance their adaptability, interpreta

关键词： Convolutional neural networks

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