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Hydrodynamic parameter estimation using statistical machine learning for dynamic radiography

Hydrodynamic parameter estimation using statistical machine ...

2023 Computational Optical Sensing and Imaging, COSI 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： De, Soumi Klasky, Marc Korobkin, Oleg Sidharth, G.S. Xu, Xiaojian Computer Computational and Statistical Sciences Division Los Alamos National Laboratory United States Theoretical Division Los Alamos National Laboratory United States Department of Aerospace Engineering Iowa State University United States Department of Electrical Engineering & Computer Science University of Michigan United States

Characterization of material properties of objects undergoing strong deformations is an important task in material science. Using neural networks with dynamic features extracted from radiographic projections we obtain... 详细信息

ISBN: (纸本)9781957171289

关键词： Parameter estimation

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Correction to: Automated explainable and interpretable framework for anomaly detection and human activity recognition in smart homes (Neural Computing and Applications, (2025), 10.1007/s00521-025-10991-3)

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Neural Computing and Applications 2025年第16期37卷 9309-9310页

作者： Kim, Tae Hoon Ojo, Stephen Krichen, Moez Alamro, Meznah A. Mihoub, Alaeddine Sampedro, Gabriel Avelino School of Information and Electronic Engineering Zhejiang University of Science and Technology No. 318 Zhejiang Hangzhou China Department of Electrical and Computer Engineering College of Engineering Anderson University AndersonSC29621 United States Al-Baha University Al-Baha65528 Saudi Arabia ReDCAD Laboratory University of Sfax Sfax3038 Tunisia Department of Information Technology College of Computer and Information Science Princess Nourah Bint Abdul Rahman University Riyadh11564 Saudi Arabia Department of Management Information Systems College of Business and Economics Qassim University P.O. Box: 6640 Buraidah51452 Saudi Arabia Department of Computer Science University of the Philippines Diliman Quezon City1101 Philippines

In this article, the author’s name Stephen Ojo was incorrectly written as Stepehn Ojo and the affiliation details for author Stephen Ojo was incorrectly given as ‘department of electrical and computer engineering, College of engineering Anderson, Anderson University, Anderson, SC 29621, USA’ but should have been ‘department of electrical and computer engineering, College of engineering, Anderson University, Anderson, SC 29621, USA’. In addition, the affiliation details for author Gabriel Avelino Sampedro were incorrectly given as ‘College of computer Studies, De La Salle University, 2401 Taft Ave., Malate, 1004 Manila, Philippines and Faculty of Information and Communication Studies, University of the Philippines Open University, 4031 Los Baños, Philippines’ but should have been ‘department of computer Science, University of the Philippines Diliman, 1101 Quezon City, Philippines’. The original article has been corrected. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

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Water droplets play a role in Internet of Things applications

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Droplet 2024年第3期3卷 27-48页

作者： Feng Wen Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore Center for Intelligent Sensors and MEMS(CISM) National University of SingaporeSingapore i-Lab Key Laboratory of Multifunctional Nanomaterials and Smart SystemsSuzhou Institute of Nano-Tech and Nano-Bionics(SINANO)Chinese Academy of Sciences(CAS)SuzhouChina NUS Graduate School—Integrative Sciences and Engineering Programme(ISEP) National University of SingaporeSingapore

Water droplets help life in nature survive,thrive,and *** water droplet serv-ing as one of the indispensable elements in the Internet of Things(IoT),many droplet-oriented technologies,such as microfluidics,droplet manipulation,electrowetting,and energy harvesting,make rapid progress driven by material science,computer science,and ***-based wearable devices are endowed with advantages such as flexibility,sensing ability,and automation for various parameter ***,the continuous exploration of droplet manipulation has led to the emergence of a wide variety of manipulation ***,electrowetting that utilizes exter-nal fields modifying liquid–solid surfaces has found its applications in various areas,including droplet transportation,microfabrication,and *** energy gener-ation from water droplets also presents exciting opportunities for the development of novel electricity *** approaches for droplet utilization underscore the immense potentials and versatilities of droplet-based technologies in the IoT ***,this mini review presents the fundamental droplet-based technologies by summarizing their working mechanisms and methods,device structures,and *** the challenges in materials,fabrication,and system integration,this review shows the overall development roadmap in terms of improved functionality and performance and highlights the opportunities toward multifunctional,self-sustainable,and intelligent systems,which is called for IoT construction.

关键词： IoT utilize fabrication

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Design and Development of a Microcontroller Based Solar PV Cooker 4

Design and Development of a Microcontroller Based Solar PV C...

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4th International Conference on Ubiquitous Computing and Intelligent Information systems, ICUIS 2024

作者： Morake, Anita Samikannu, Ravi Akila, L. Karpagam, R. Rohini, R. Yahya, Abid Botswana International University of Science and Technology Department of Electrical and Communications Systems Engineering Palapye Botswana Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Ece Chennai India Periyar Maniammai Institute of Science and Technology Department of Electrical and Electronics Engineering Thanjavur India Easwari Engineering College Department of Electrical and Electronics Engineering Ramapuram India Vivekanandha College of Engineering for Women Department of Computer Science and Engineering Tiruchengode India

ISBN: (纸本)9798331529635

This study proposes an innovative approach to improve solar cooking systems by combining microcontroller technology and deep-learning techniques. The Solar-PV Microcontroller-based Cooker concept aims to provide a sustainable and eco-friendly cooking method by harnessing the sun's power. This innovative approach addresses global energy conservation and access to clean cooking options, particularly in areas where conventional methods contribute to deforestation and indoor air pollution. The system includes inputs for cooking duration and temperature monitoring, enhancing solar energy efficiency and user experience. The study investigates how deep learning algorithms can be incorporated into the microcontroller-based solar cooker system to enhance functionality and versatility. Cooking settings can be automatically adjusted to maximize energy consumption and cooking results by analyzing real-time data from sensors and human inputs. The hybrid approach combines the best features of deep learning with microcontroller technology, demonstrating the significance of renewable energy in a cleaner, more efficient future. The Solar-Pv cooker demonstrates the possibilities of fusing culinary technology with computer algorithms, showcasing the potential of renewable energy in a cleaner, more efficient future. © 2024 IEEE.

关键词： Indoor air pollution

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First-principles insights into lithium and magnesium ion dynamics for high-performance silicon and silicon-germanium anodes

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Journal of Power Sources 2025年 650卷

作者： Zand, Ali Lashani Energy Storage Laboratory Department of Electrical and Computer Engineering College of Engineering University of Tehran Tehran14395-515 Iran

Silicon (Si) anodes offer high theoretical capacity for lithium-ion batteries but suffer from severe volume expansion, leading to structural degradation and capacity loss. This study explores silicon-germanium (SiGe) composites as an alternative anode material using Density Functional Theory (DFT) and Ab Initio Molecular Dynamics (AIMD) simulations to evaluate thermodynamic stability, structural adaptability, and charge transport behavior under ion insertion. The results show that Ge incorporation lowers formation energy barriers, facilitating Li and Mg insertion while reducing mechanical stress and volume expansion. The SiGe framework exhibits greater flexibility, enabling superior Li-ion mobility, while Mg-ion diffusion remains constrained due to stronger electrostatic interactions. Extended AIMD simulations at 300 K, 750 K, and 1200 K further confirm SiGe's structural resilience and improved ion transport. Projected Density of States (PDOS) calculations, along with Electron Localization Function (ELF) analysis, reveal enhanced charge distribution in SiGe, supporting its stability during cycling. By offering greater thermodynamic stability, reduced volumetric strain, and enhanced ion transport, SiGe presents a promising anode material for next-generation lithium- and magnesium-ion batteries. These findings provide valuable insights into alloy design strategies, bridging the gap between fundamental materials science and practical energy storage applications. © 2025 Elsevier B.V.

关键词： Mechanical stability

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Deep CNN Model for Multimodal Medical Image Denoising

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computers, Materials & Continua 2022年第11期73卷 3795-3814页

作者： Walid El-Shafai Amira A.Mahmoud Anas M.Ali El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

In the literature,numerous techniques have been employed to decrease noise in medical image modalities,including X-Ray(XR),Ultrasonic(Us),Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and Positron Emission Tomography(PET).These techniques are organized into two main classes:the Multiple Image(MI)and the Single Image(SI)*** the MI techniques,images usually obtained for the same area scanned from different points of view are used.A single image is used in the entire procedure in the SI *** denoising techniques can be carried out both in a transform or spatial *** paper is concerned with single-image noise reduction techniques because we deal with single medical *** most well-known spatial domain noise reduction techniques,including Gaussian filter,Kuan filter,Frost filter,Lee filter,Gabor filter,Median filter,Homomorphic filter,Speckle reducing anisotropic diffusion(SRAD),Nonlocal-Means(NL-Means),and Total Variation(TV),are ***,the transform domain noise reduction techniques,including wavelet-based and Curvelet-based techniques,and some hybridization techniques are ***,a deep(Convolutional Neural Network)CNN-based denoising model is proposed to eliminate Gaussian and Speckle noises in different medical image *** model utilizes the Batch Normalization(BN)and the ReLU as a basic *** a result,it attained a considerable improvement over the traditional *** previously mentioned techniques are evaluated and compared by calculating qualitative visual inspection and quantitative parameters like Peak Signal-to-Noise Ratio(PSNR),Correlation Coefficient(Cr),and system complexity to determine the optimum denoising algorithm to be applied *** on the quality metrics,it is demonstrated that the proposed deep CNN-based denoising model is efficient and has superior denoising performance over the traditionaldenoising techniques.

关键词： Image enhancement medical imaging speckle noise Gaussian noise denoising filters CNN denoising

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Privacy Preserving Quantum Search Mechanism Using Grover's Algorithm 1

Privacy Preserving Quantum Search Mechanism Using Grover's A...

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1st International Conference on Quantum Communications, Networking, and Computing, QCNC 2024

作者： Ju, Keyi Qin, Xiaoqi Zhong, Hui Zhang, Xinyue Pan, Miao Liu, Baoling State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China University of Houston Department of Electrical and Computer Engineering HoustonTX77204 United States Kennesaw State University Department of Computer Science MariettaGA30060 United States

ISBN: (纸本)9798350366778

Quantum computing changes the way of solving complex problems and handling vast datasets. The introduction of quantum search algorithms, notably Grover's algorithm, addresses the inefficiencies of classical search methods in handling vast datasets by offering substantial speed improvements. However, an inherent aspect of quantum searches is their failure probability. This paper aims to explore the relationship between the failure probability in Grover's algorithm and the privacy guarantees of differential privacy (DP). We further investigate the impact of several quantum circuit parameters, including the number of shots, the number of solutions within the dataset, and circuit noise levels, on this failure probability. Our analysis demonstrates the indirect connection between these quantum circuit elements and the privacy guarantees of DP. Through Monte Carlo simulations, we offer an in-depth analysis that paves the way for secure and faster data querying methods. © 2024 IEEE.

关键词： Differential privacy

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A Compliant Robot-Assisted Mold Polishing Application Using the Franka Emika Robot 49

A Compliant Robot-Assisted Mold Polishing Application Using ...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Xenya, Michael Christopher Cortesao, Rui Institute of Systems and Robotics University of Coimbra Electrical and Computer Engineering Department Coimbra3030-290 Portugal FOE GCTU PMB100 Accra Ghana

ISBN: (纸本)9798350331820

Metal mold casting for many application areas remains imperfect since this involves the control of numerous factors that affect workpiece quality. Surface roughness which remains one of the many issues related to metal mold cast is often mitigated by means of grinding and polishing. As many attempts are being made to address this challenge through robot-assisted techniques, we focus on rapid mold polishing using the Franka Emika (FE) robot and its programming resources, including a built-in impedance control architecture. To accomplish the objective, mold surface segmentation is necessary. For each segment, the polishing approach is based on surface normals, relative motion, and torque sensor data. Results were obtained with open platform communication-unified architecture (opc-ua) client and server that record torque and force data. Results show that tuning internal impedance control parameters for polishing tasks is feasible. © 2023 IEEE.

关键词： Polishing

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Characterizing Structured versus Unstructured Environments based on Pedestrians’ and Vehicles’ Motion Trajectories

arXiv

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arXiv 2025年

作者： Golchoubian, Mahsa Ghafurian, Moojan Azad, Nasser Lashgarian Dautenhahn, Kerstin Department of Systems Design Engineering University of Waterloo Canada Department of Electrical and Computer Engineering University of Waterloo Canada

Trajectory behaviours of pedestrians and vehicles operating close to each other can be different in unstructured compared to structured environments. These differences in the motion behaviour are valuable to be considered in the trajectory prediction algorithm of an autonomous vehicle. However, the available datasets on pedestrians’ and vehicles’ trajectories that are commonly used as benchmarks for trajectory prediction have not been classified based on the nature of their environment. On the other hand, the definitions provided for unstructured and structured environments are rather qualitative and hard to be used for justifying the type of a given environment. In this paper, we have compared different existing datasets based on a couple of extracted trajectory features, such as mean speed and trajectory variability. Through K-means clustering and generalized linear models, we propose more quantitative measures for distinguishing the two different types of environments. Our results show that features such as trajectory variability, stop fraction and density of pedestrians are different among the two environmental types and can be used to classify the existing datasets. Copyright © 2025, The Authors. All rights reserved.

关键词： Trajectories

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A Patient Specific Algorithm for Plasmodium Malaria Detection on Cell Images

A Patient Specific Algorithm for Plasmodium Malaria Detectio...

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2023 IEEE National Aerospace and Electronics Conference, NAECON 2023

作者： Narayanan, Barath Narayanan De Silva, Manawaduge Supun Hardie, Russell C. University of Dayton Research Institute Sensor and Software Systems Division Dayton United States University of Dayton Department of Electrical and Computer Engineering Dayton United States

ISBN: (纸本)9798350338782

computer-aided detection of plasmodium malaria on cell images from digital microscopy provides an invaluable second opinion to medical experts. Traditionally, well-established deep learning algorithms are widely used to detect plasmodium, but these techniques have not been deployed due to the uninterpretable nature of the decisions made by the network. To address this, we present an ensemble method that fuses the predictions based on the class activation mapping (CAM) results from multiple networks via a novel selector network. We study the performance on a publicly available dataset of cell images by using three convolutional neural network architectures, Xception, ResNet50, and InceptionV3,to produce CAM results for the selector network and performance comparison. Our proposed approach helps enhance doctors' trust and outperforms the traditional methods by 1%. © 2023 IEEE.

关键词： Diseases

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