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IEEE Sensors Letters 2025年

作者： Patle, Kamlesh Yogi, Pooja Maru, Devkaran Agrawal, Yash Palaparthy, Vinay S. Moez, Kambiz DAIICT System Design Lab Department of Information and Communication Technology Gandhinagar382007 India University of Alberta iCAS Department of Electrical and Computer Engineering Faculty of Engineering EdmontonABT6G 2V4 Canada

Prolonged leaf wetness is a critical factor influencing the development and spread of plant diseases, particularly fungal pathogens, which thrive in moist environments. These pathogens negatively impact crop health, photosynthesis, nutrient absorption, and agricultural productivity. Accurately measuring leaf wetness duration (LWD) is essential for early disease detection and mitigation strategies. Leaf wetness sensors (LWS) are designed to detect wetness on leaf surfaces. Traditional LWS, fabricated using printed circuit boards (PCBs), have been extensively studied and are commercially available, such as the PHYTOS-31. However, flexible LWS are preferred due to their ability to conform to the natural shape of leaves, improving accuracy, better contact resistance, and durability under field conditions. However, these sensors exhibited limitations such as electrode oxidation and peeling, reducing stability and wetness sensitivity over time. To overcome these challenges, this study investigates replacing conventional metal-based interdigitated electrodes (IDEs) with graphene-based IDEs, leveraging graphene's superior electrical, mechanical, and thermal properties. The fabricated flexible graphene LWS has been evaluated for its sensitivity, response time, hysteresis, temperature response, and stability, which are about ≈26,000%, ≈ 35 seconds, ≈ 5%, ≈ 6.79%, and 5 months, respectively. Benchmarking against the commercially available PHYTOS-31 LWS demonstrated an absolute error of ±3%, confirming the reliability and accuracy. These results validate the potential of graphenebased flexible LWS for accurate and long-term monitoring of leaf wetness duration in agricultural and ecological applications. © 2017 IEEE.

关键词： Microbial electrodes

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Positioning Control for Voice Coil Motor Using Unbalanced Multilevel Inverter Topology

Positioning Control for Voice Coil Motor Using Unbalanced Mu...

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International Conference on Mechatronics (ICM)

作者： Gaku Takei Hidemine Obara Ryo Haneda Takahiro Nozaki Graduate School of Science and Technology Keio University Yokohama Japan Department of Physics Electrical and Computer Engineering Yokohama National University Yokohama Japan Department of System Design Engineering Keio University Yokohama Japan

ISBN: (数字)9798331533892

ISBN: (纸本)9798331533908

This article proposes a new multi-level inverter (MLI) based on flying capacitor inverter (FCI), with focused on high-precision positioning control for a voice coil motor (VCM). Multi-level inverters (MLIs) have the characteristic that increasing the number of output voltage levels reduces the output voltage error. However, as the number of levels increases, the number of circuit elements increases, and the circuit becomes more complex. In addition, the output voltage amplitude for each level is constant in conventional inverters. As a result, such as high-precision positioning control of VCM, designing an appropriate inverter for a reference wave that contains a large amount of low-voltage components increases the number of circuit elements. Therefore, this paper proposes a MLI with two unbalanced dc-input voltages, referred to as unbalanced MLIs (UMLIs) hereinafter. This topology uses two different dc-input voltages, and it is possible to reduce the output voltage level in extremely low-voltage range compared to other voltage levels. Simulation results when the high-precision positioning control of the VCM confirm that the proposed UMLIs improves the control performance compared to the conventional FCIs with equal number of output voltage levels and uniform level widths.

关键词： Coils Low voltage Simulation Switches Multilevel inverters Motors Topology Sensors Voltage control Motion control

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An investigation of supervised machine learning models for predicting drivers’ ethical decisions in autonomous vehicles

Decision Analytics Journal

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Decision Analytics Journal 2025年 14卷

作者： Singh, Amandeep Murzello, Yovela Pokhrel, Sushil Samuel, Siby Department of System Design Engineering University of Waterloo Waterloo ON N2L 3G1 Canada

Vehicle-pedestrian interactions in autonomous vehicles (AVs) present complex challenges that require advanced decision-making algorithms. Understanding the factors influencing ethical decision-making (EDM) in critical situations is essential as AVs become more prevalent. This study addresses a gap in AV research by using predictive analytics methods to develop models that assess decision-making outcomes under varying time pressures. We recruited 204 participants from North America, aged 18-30 years and 65 years and above, for an online experiment. Participants viewed video clips from a driving simulator that simulated ethical dilemmas. They had to decide whether the AV should stay in its lane or change lanes by pressing the spacebar. The principal component analysis identified age, distraction, and trust in automation as the key factors influencing decision-making. Several machine learning models were optimized to predict decision outcomes, with the Gaussian Naive Bayes model demonstrating strong performance across different time pressures. Feature importance analysis highlighted the significant roles of age and trust in automation. Partial dependence plots illustrated the interaction between these factors and their influence on decision-making outcomes under time constraints. These findings contribute to the development of personalized decision-making algorithms for AVs. Predictive analytics provides valuable insights into improving AV systems’ safety, trust, and ethical behavior by accounting for individual differences in decision-making. © 2025 The Author(s)

关键词： Autonomous vehicles Moral judgement Pedestrian safety Predictive analytics Supervised machine learning Utilitarianism

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designing a Real-Time Medication Intake and Adherence Dashboard: Features, Functionality, and Data Display to Meet the Needs of Patients, Care Partners and Healthcare Providers

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Journal of Medical systems 2025年第1期49卷 1-18页

作者： Faisal, Sadaf Baby, Bincy Samoth, Devine Ghaffar, Faisal Aslam, Yusra Stavropoulos, Alexander McCready-Branch, Brent Elba, Ghada Gill, Jasdeep Kaur Choudhuri, Prapti Patel, Tejal School of Pharmacy University of Waterloo Kitchener ON Canada Canadian Pharmacists Association Toronto ON Canada System Design Engineering Department University of Waterloo Waterloo ON Canada Schlegel-UW Research Institute for Aging Waterloo ON Canada

To determine the key features, utilities, and functionalities of an adherence dashboard so that patients, care partners, and healthcare providers can effectively use it to identify and improve medication nonadherence. A qualitative study was conducted in four stages. In Stage 1, semi-structured interviews and focus groups were conducted with patients, care partners, and healthcare providers after showing existing dashboards to gain feedback and determine their needs and preferences for the dashboard. In Stage 2, data gathered from Stage 1 were used to develop paper prototypes. In Stage 3, these prototypes were evaluated by participants to refine the design. Finally, in Stage 4, a framework for the key components of the adherence dashboard was developed based on user feedback. Some of the key features identified include individualized medication adherence, overall adherence summaries, customizable notifications, real-time data visualization, and integration with existing healthcare systems such as electronic health records (EHR). Participants also highlighted the importance of intuitive design, ease of navigation, secure data handling, and the ability to customize the dashboard according to user preferences. This study identifies key features and functionalities and provides a user-centered framework for designing a real-time medication adherence dashboard tailored to the needs of patients, caregivers, and healthcare providers. Future work will focus on developing a fully functional dashboard, integrating it into clinical practice, and evaluating its effectiveness in improving medication adherence. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Adherence Dashboard Features Functionalities Medication Utilities

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Event-Camera Based Relative Navigation systems for a Rocket Upper-Stage

Event-Camera Based Relative Navigation Systems for a Rocket ...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Murayama, Shingo Takahashi, Masaki Fukuda, Seisuke School of Science for Open and Environmental Systems Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama223-8522 Japan Faculty of Science and Technology Department of System Design Engineering Keio University 3-14-1 Hiyoshi Kohoku-ku Kanagawa Yokohama Japan Department of Spacecraft Engineering Institute of Space and Astronautical Science Japan Aerospace Exploration Agency Kanagawa Sagamihara252-5210 Japan

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Active debris removal has become crucial. The removal of the upper stages of the rocket, which are the most common type of debris, is receiving increased attention. In the case of debris removal from the upper stage of a rocket, it is considered to recognize the circular structure of the upper stage of the rocket, which appears as an ellipse on the image plane, as a payload attach fitting (PAF) using the navigation sensor, and to approach it. Approaching the debris requires tracking the ellipses during the approach after initially recognizing the inner and outer ellipses of the PAF. Thus, the navigation sensor must be robust to sunlight for stable ellipse recognition. Consequently, we propose an initial PAF recognition method using an event camera due to its robust features as a navigation sensor. In the initial recognition, image processing is applied to event frames that accumulate asynchronous output events. As the inner ellipse of the PAF is suitable for feature extraction, we proposed a method to recognize the outer ellipse using the value of the inner ellipse after initial recognition of the inner ellipse. Additionally, when the recognition of the inner or outer ellipse fails, we propose extending the event accumulation time and repeating the process. The effectiveness of the proposed method was verified by numerical analysis using a simulator. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Rockets

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design, Analysis and Verification of AMBA AXI4.0

Design, Analysis and Verification of AMBA AXI4.0

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Visual Analytics and Data Visualization (ICVADV), International Conference on

作者： Aashima Lalit Mohan Saini School of VLSI and Embedded System Design National Institute of Technology Kurukshetra Haryana India Department of Electrical Engineering National Institute of Technology Kurukshetra Haryana India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

AMBA AXI was developed by ARM in 2003 upgrading it to AMBA AXI 4.0 in 2014. AMBA AXI4.0 is a fast, efficient, high frequency, high performance, high bandwidth SOC (system-on-chip) protocol that is used for communication between CPU (central processing unit) and FPGA (field programmable gate arrays). It has five communication channels for reading and writing between master and slave. It supports burst transactions and has handshake mechanism, which makes it suitable for high data transfers rate and for pipeline processing of instructions. It finds applications in various ARM (advanced RISC (reduced instruction set computer) machine) based FPGAs like Zynq-7000, Zynq Ultrascale+, Spartan 7, Arria 10 etc. This work implements the AXI4.0 protocol for communication between master and slave for 32 bits of data transfer and verification of using protocol checker.

关键词： Reduced instruction set computing Visual analytics Communication channels Writing Data transfer Main-secondary Central Processing Unit system-on-chip Field programmable gate arrays Pipeline processing

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FPGA-Based In-Vehicle Occupancy Detection Using mmWave Radar With Mexican Hat Wavelet Transform

IEEE Sensors Letters

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IEEE Sensors Letters 2025年第5期9卷

作者： Mohan, Anand Meena, Hemant Kumar Wajid, Mohd Srivastava, Abhishek Malaviya National Institute of Technology Department of Electrical Engineering Jaipur302017 India Aligarh Muslim University Department of Electronics Engineering Aligarh202002 India International Institute of Information Technology Centre for VLSI Design Embedded System Technology Hyderabad500032 India

A demonstration of the implementation of vehicle occupancy detection on hardware-software is shown in this letter. For the purpose of validating applications for vehicle occupancy detection, a hardware field programmable gate array (FPGA) platform, also known as Python productivity for zynq ultrascale+ MPSoC (PYNQ-ZU), is a feasible embedded architecture. Automatic in-car occupancy monitoring is an important technology in modern transportation, with major implications for safety, energy efficiency, and smart vehicle management. One of the primary benefits of millimeter wave (mmWave) radar is its ability to accurately detect the number and location of vehicle occupants, mmWave radar ensures robust detection under all lighting and weather conditions. In our research, the proposed approach was applied to point cloud images. Following the generation of 3-D point cloud images, two filters, top-view (TV), and front-view (FV), were used to improve vehicle occupancy detection. These filters transformed 3-D images into 2-D ones. TV filter was found to be more effective than the FV filter. After filtering the 2-D images, Mexican Hat Wavelet Transform (MHWT) was used to extract features from them. Four machine learning methods were then used to determine vehicle seat occupancy, with logistic regression (LR) and support vector machine producing the highest results, with an accuracy of 98%. In comparison to existing methods, the proposed approach, which utilizes mmWave radar, TV Filter, MHWT, FPGA (PYNQ-ZU), and LR, was determined to significantly improve the accuracy of vehicle occupancy detection. © 2017 IEEE.

关键词： Image enhancement

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Residential tree canopy configuration and mortality in 6 million Swiss adults: a longitudinal study

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The Lancet Planetary Health 2025年第3期9卷 e186-e195页

作者： Chi, Dengkai Manoli, Gabriele Lin, Brenda Aerts, Raf Yang, Jun Hahs, Amy Richards, Daniel Meili, Naika Zhu, Yue Qiu, Yeshan Wang, Jing Burlando, Paolo Fatichi, Simone Tan, Puay Yok Singapore–ETH Centre Future Cities Laboratory Global Singapore Laboratory of Urban and Environmental Systems École Polytechnique Fédérale de Lausanne Lausanne Switzerland CSIRO Environment Brisbane QLD Australia Division of Ecology Evolution and Biodiversity Conservation University of Leuven Leuven Belgium Risk and Health Impact Assessment Sciensano Brussels Belgium Department of Earth System Science Institute for Global Change Studies Ministry of Education Ecological Field Station for East Asian Migratory Birds Tsinghua University Beijing China School of Agriculture Food and Ecosystem Sciences Burnley Campus The University of Melbourne Richmond Melbourne VIC Australia Manaaki Whenua – Landcare Research Lincoln New Zealand Institute of Environmental Engineering ETH Zurich Zurich Switzerland Department of Architecture College of Design and Engineering National University of Singapore Singapore Department of Civil and Environmental Engineering College of Design and Engineering National University of Singapore Singapore

Background: Residential exposure to trees has been associated with reduced mortality risks. We hypothesise that in addition to tree canopy cover, tree canopy configuration also plays a role in exposure–mortality relationships. As there is limited evidence on this hypothesis, especially longitudinal evidence, we performed a nationwide study to investigate the residential tree canopy configuration–mortality associations in the Swiss population. Methods: In this longitudinal study, the tree canopy cover and configuration metrics within 500 m of individuals’ residences were quantified using high-resolution tree canopy data (1 × 1 m) from 2010 to 2019. We developed single-exposure and multi-exposure time-varying Cox regression models to estimate the associations between the different exposure metrics and natural-cause and cause-specific mortality in Swiss adults (aged from 20 years to 90 years). Mortality and census data were taken from the Swiss National Cohort (SNC). We estimated the hazard ratios (HRs) and corresponding 95% CIs per IQR increase in the metrics adjusting for personal sociodemographic and contextual covariates. We also explored the effect modification by tree canopy cover, PM₁₀, air temperature, urbanisation level, age, sex, and area-based local socioeconomic position. Findings: Our analyses included 6 215 073 individuals from the SNC between 2010 and 2019. In the fully adjusted single-exposure models, we observed protective associations between natural-cause mortality risk and tree canopy cover (IQR 12·4%, HR 0·979 [95% CI 0·975–0·983]) and configuration metrics describing the aggregation (6·3%, 0·831 [0·823–0·840]), and connectedness (2·9%, 0·946 [0·938–0·953]);and detrimental associations with two metrics describing the fragmentation (211 patches per 100 ha, 1·073 [1·066–1·080]) and shape complexity (1·9, 1·094 [1·089–1·100]) of patches. The associations were generally preserved with other common causes of death. According to the multi-expo

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Evaluation of Mechanical and Thermomechanical Water Vapor Compression Techniques for Enabling High Temperature Lift Hydration-Based Chemical Heat Pumps

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Journal of Energy Resources Technology, Part A: Sustainable and Renewable Energy 2025年第1期1卷 011703页

作者： Armatis, Paul D. Sabharwall, Piyush Fronk, Brian M. School of Mechanical Industrial and Manufacturing Engineering Oregon State University 1500 SW Jefferson Way Corvallis OR 97331 Nuclear System Design and Analysis Division Idaho National Laboratory Idaho Falls ID 83415 Department of Mechanical Engineering The Pennsylvania State University University Park PA 16802

Achieving high temperature lifts (⁠>200K⁠) via a chemical heat pump based on salt hydration/dehydration reactions requires the transport of water vapor from low to high pressure. Alternative compression approaches require condensing of low-pressure water vapor, pumping of liquid water, and subsequent evaporation when the low-side pressure corresponds to sub-ambient water saturation temperatures. Thus, this study compares four steam compression methods for use within a chemical heat pump system based on a reversible calcium oxide hydration/dehydration reaction with a temperature lift from350∘Cheat to>600∘C⁠. Purely mechanical and thermochemical/mechanical compression technologies are considered. A parametric study of maximum allowable temperature, the isentropic efficiency of mechanical compressors, the effectiveness of heat exchangers, and the assumed allowable heat exchanger pressure drop is conducted to determine the mechanical and thermal energy consumed per kilogram of compressed steam. The system complexity in terms of the number of main system components, maximum pressure ratio, and maximum allowable temperature is estimated. Model results show an absorption-based steam compressor has the highest exergetic efficiency for the required chemical heat pump conditions. This system configuration was then experimentally demonstrated to illustrate the impact of system performance on component effectiveness.

关键词： steam chemical heat pump energy storage systems vapor compressor high pressure ratio

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Parallel multi-layer sensor fusion for pipe leak detection using multi-sensors and machine learning

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engineering Applications of Artificial Intelligence 2025年 153卷

作者： Satterlee, Nicholas Zuo, Xiaowei Lee, Chang-Whan Park, Choon-Wook Kang, John S. Department of Mechanical Engineering San Diego State University CA San DiegoCA92182 United States School of Mechanical System Design Engineering Seoul National University of Science and Technology Seoul01811 Korea Republic of Department of Undeclared Majors Kyungpook National University Daegu41566 Korea Republic of

Effective pipe leak detection is critical for maintaining the structural integrity and efficiency of water distribution systems and preventing damage such as sinkholes. Traditional leak detection methods often rely on single sensors, overlooking the advantages of multi-sensor configurations that capture diverse leak-related phenomena. To address this limitation, the study proposes an innovative machine learning-based sensor fusion approach called Parallel Multi-Layer Sensor Fusion (PMLSF), which leverages Convolutional Neural Networks (CNN) and Few-Shot Learning (FSL) to enhance leak detection. PMLSF integrates data from multiple sensors, including hydrophone, acoustic emission, and vibration sensors. The comparative analysis demonstrates that the PMLSF with multi-sensor systems substantially outperforms the CNN-based FSL (CNN-FSL) approach with single-sensor systems, achieving a leak detection accuracy of 97.1 % and leak location classification accuracy between 95.5 % and 97.4 %. Additionally, the study investigates the use of the acoustic emission sensor combined with CNN-FSL for early detection of material failure in pipes, demonstrated by a Pencil Test that achieved 92.3 % accuracy in detecting pencil breakage on the pipe. These results indicate that combination of CNN-FSL for the acoustic emission sensor and PMLSF offers a comprehensive solution for detecting and localizing existing leaks while predicting potential failures, thus laying a robust foundation for the development of reliable and efficient water distribution monitoring systems. © 2025 The Authors

关键词： Acoustic emissions

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