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Self-Powered Clamp-On Pyroelectric Tactile sensor for Intelligent Recognition of Film Materials

SusMat 2025年第1期5卷 111-121页

作者： Shengjie Yin Hongyu Li Yun Ji Yuke Li Chris R.Bowen Ya Yang Beijing Key Laboratory of Micro-Nano Energy and Sensor Center for High-Entropy Energy and SystemsBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijingChina School of Nanoscience and Technology University of Chinese Academy of SciencesBeijingChina Center on Nanoenergy Research Institute of Science and Technology for Carbon Peak&NeutralityGuangxi UniversityNanningChina Key Laboratory of Blue Energy and Systems Integration(Guangxi University) Education Department of Guangxi Zhuang Autonomous RegionGuangxi UniversityNanningChina School of Physical Science&Technology Guangxi UniversityNanningChina Department of Mechanical Engineering University of BathBathUK

Tactile sensors are a potential solution for material ***,current potential tactile sensors for material identification are pressed,expensive,and *** we report a clamped-on pyroelectric tactile sensor on the basis of a ferroelectric Bi_(0.5)Na_(0.5)TiO_(3) material to identify different film *** fabricated device exhibits different heat absorption capacities while in contact with different materials,leading to a different temperature change in the ferroelectric material under the same *** a result,the device can recognize different materials by comparing the pyroelectric charge via integrating the obtained current under the same irradiation of 365nmlight-emitting *** clamped-on pyroelectric tactile sensor can identify six individual materials with a high accuracy of 98.8%and a fast response of 40 *** of the above processes can be accomplished with an intelligent material identification *** device provides a new solution for material identification and lays a foundation for smart factories and laboratories.

关键词： Bi_(0.5)Na_(0.5)TiO_(3)(BNT) material identification pyroelectric effect tactile sensor

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Environmental multi-physics coupled tribovoltaic effect for energy harvesting

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National Science Open 2025年第2期4卷 159-182页

作者： Yuan Feng Zhi Zhang Likun Gong Ruifei Luan Zhaozheng Wang Sicheng Dong Chi Zhang Center on Nanoenergy Research Institute of Science and Technology for Carbon Peak&NeutralityKey Laboratory of Blue Energy and Systems Integration(Guangxi University)Education Department of Guangxi Zhuang Autonomous RegionSchool of Physical Science&TechnologyGuangxi UniversityNanning 530004China Beijing Key Laboratory of Micro-Nano Energy and Sensor Center for High-Entropy Energy and SystemsBeijing Institute of Nanoenergy and NanosystemsChinese Academy of SciencesBeijing 101400China School of Nanoscience and Engineering University of Chinese Academy of SciencesBeijing 100049China

The tribovoltaic effect represents a newly discovered semiconductor effect for mechanical-to-electrical energy ***,the semiconductor interfaces are typically susceptible to environmental multi-physics fields,such as illumination,temperature,and humidity,which can affect the energy conversion process of the tribovoltaic *** this review,we provide a comprehensive overview of the current research status of the environmental multi-physics coupled tribovoltaic effect for energy *** summarize the electrical output characteristics of tribovoltaic nanogenerators(TVNGs)in various physical field environments and the impact mechanisms of these fields on electrical performance,demonstrating their ability to capture and convert a wide range of mechanical energies,including wind,rain,waves,and *** discuss the fundamental principles underlying these devices,their potential applications,and the key chal-lenges and opportunities for future *** review deepens our understanding of the energy harvesting mechanism of the tribovoltaic effect in multi-physics *** a multi-physics energy harvesting strategy not only broadens the scope and efficiency of energy harvesting but also drives the development of novel energy conversion devices,proposing fresh ideas for future innovations in sustainable energy solutions.

关键词： tribovoltaic effect multi-physics field semiconductor interface contact electrification energy harvesting

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Housekeeping Using Multi-Agent Service Robotics

Housekeeping Using Multi-Agent Service Robotics

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International Conference on Robotics and Artificial Intelligence (ICRAI)

作者： Muhammad Faiq Malik Haris Shahid Muhammad Haris Saleem Hassan Nazir Ahmed Nouman Mechatronics Engineering Department University of Engineering & Technology Taxila Pakistan Centre for Applied Autonomous Sensor Systems (AASS) Örebro University Örebro Sweden

Service robotics in dynamic environments is a challenging yet exciting field that has witnessed incredible advances in the last few decades. The credit for these advancements goes to artificial intelligence and robotics technological progressions. The housekeeping domain is an example of a service robotics domain. A high-level task planner can compute a plan of action, while low-level functionalities like perception and motion planning can ensure feasibility. We propose a solution to the housekeeping problem that utilizes the expressiveness of action language C+ to formalize actions and compute an action plan. To check for feasibility in the real world, we execute the action plans in a physics simulator, GAZEBO. We also propose benchmark instances for the housekeeping domain and evaluate our planning and execution times approach. We report possible execution failures for the benchmark instances and offer plausible solutions, such as hybrid planning, plan execution monitoring, and conditional planning.

关键词： Industries Automation Service robots Computational modeling Benchmark testing Planning Task analysis

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Applications of Hybrid Conditional Planning in Service Robotics

Applications of Hybrid Conditional Planning in Service Robot...

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International Conference on Robotics and Artificial Intelligence (ICRAI)

作者： Ahmed Nouman Muhammad Khurram Saleem Centre for Applied Autonomous Sensor Systems (AASS) Örebro University Örebro Sweden Mechatronics Engineering Department University of Engineering & Technology Taxila Pakistan

Hybrid planning computes task plans in full observability (a sequence of possible actuation actions) via the integration of low-level feasibility checks in classical planning approaches. Conditional planning extends the classical planning framework to account for plans under partial observability. We use a hybrid conditional planning approach to compute plans that include sensing and actuation actions in solving real-world problems by addressing uncertainties due to incomplete information at the planning phase. We generate a hybrid conditional plan of actions using parallel instances of a non-monotonic hybrid HCPLAN that supports defaults, integration of external computations, and non-deterministic actions. We show our hybrid conditional planning framework's HCPLAN applicability through service robotics scenarios with manipulation and navigation tasks. Furthermore, we evaluate the effect of parallel threads on the computation of hybrid conditional framework on different benchmark scenarios for the service robotics domains.

关键词： Uncertainty Service robots Navigation Knowledge based systems Robot sensing systems Hybrid power systems Planning

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Planning for Learning Object Properties

arXiv

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arXiv 2023年

作者： Lamanna, Leonardo Serafini, Luciano Faridghasemnia, Mohamadreza Saffiotti, Alessandro Saetti, Alessandro Gerevini, Alfonso Traverso, Paolo Fondazione Bruno Kessler Trento Italy Department of Information Engineering University of Brescia Italy Center for Applied Autonomous Sensor Systems University of Örebro Sweden

autonomous agents embedded in a physical environment need the ability to recognize objects and their properties from sensory data. Such a perceptual ability is often implemented by supervised machine learning models, which are pre-trained using a set of labelled data. In real-world, open-ended deployments, however, it is unrealistic to assume to have a pre-trained model for all possible environments. Therefore, agents need to dynamically learn/adapt/extend their perceptual abilities online, in an autonomous way, by exploring and interacting with the environment where they operate. This paper describes a way to do so, by exploiting symbolic planning. Specifically, we formalize the problem of automatically training a neural network to recognize object properties as a symbolic planning problem (using PDDL). We use planning techniques to produce a strategy for automating the training dataset creation and the learning process. Finally, we provide an experimental evaluation in both a simulated and a real environment, which shows that the proposed approach is able to successfully learn how to recognize new object properties. © 2023, CC BY.

关键词： autonomous agents

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Detection of TEMPEST audio compromising signal using artificial intelligence 15

Detection of TEMPEST audio compromising signal using artific...

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15th International Conference on Communications, COMM 2024

作者： Vizitiu, Alexandru-Madalin Dobrescu, Lidia Molder, Cristian Sebacher, Bogdan Trip, Bogdan Catalin Butnariu, Vlad Florian National University of Sciences and Technologies Politehnica Bucharest Faculty of Electronics Telecommunications and Information Technology Bucharest Romania "Ferdinand I"Military Technical Academy Center of Excellence in Robotics and Autonomous Systems - CERAS Bucharest Romania Military Technical Academy "Ferdinand I" Department of Applied Informatics Bucharest Romania

ISBN: (纸本)9798350355956

In the contemporary landscape of cybersecurity, electronic devices are increasingly susceptible to various forms of exploitation, with TEMPEST (Transient Electromagnetic Pulse Emanation Standard) attacks posing a significant threat. This article delves into the application of artificial intelligence (AI) for detecting vulnerabilities in electronic devices through audio signal analysis within the TEMPEST domain. By leveraging advanced AI techniques, particularly machine learning algorithms, this study identifies a novel approach regarding the TEMPEST evaluation of electronic devices which process audio signal using artificial intelligence. The process involves the collection and processing of audio signals emanating from electronic devices, followed by the application of AI models to detect the presence of audio information in the received signal. The findings underscore the efficacy of AI involved in TEMPEST evaluation of electronic devices. © 2024 IEEE.

关键词： artificial intelligence audio emission security TEMPEST

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Determine electronic devices vulnerabilities using artificial intelligence 15

Determine electronic devices vulnerabilities using artificia...

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15th International Conference on Communications, COMM 2024

ISBN: (纸本)9798350355956

As electronic devices proliferate in both personal and professional settings, their susceptibility to electromagnetic vulnerabilities has become a critical concern. This article explores the use of artificial intelligence (AI) to identify and mitigate the risks associated with audio signal eavesdropping, a prevalent threat in the realm of electromagnetic security. By analyzing the electromagnetic emissions from electronic devices, AI techniques can detect unintended audio signal leaks that may compromise sensitive information. The study employs machine learning algorithms to process and evaluate these emissions. Results demonstrate the enhanced precision and efficiency of AI related to audio signal eavesdropping. This research not only underscores the importance of AI in fortifying the electromagnetic security of electronic devices but also paves the way for innovative approaches to safeguard against increasingly sophisticated eavesdropping techniques. © 2024 IEEE.

关键词： artificial intelligence audio communications security TEMPEST

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize Computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Discrimination between Cynomolgus Monkey (Macaca Fascicularis) and Humans using Machine Learning and Heart Rate Variability Indices

Discrimination between Cynomolgus Monkey (Macaca Fasciculari...

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2022 World Automation Congress, WAC 2022

作者： Kaneko, Itaru Hirahara, Daisuke Hayano, Junichiro Mozos, Oscar Martinez Yuda, Emi Center for Data-driven Science and Artificial Intelligence Tohoku University Sendai Japan Department of Health Sciences Graduate School of Medicine Tohoku University Sendai Japan Center for Applied Autonomous Sensor Systems ÖRebro University Örebro Sweden Nagoya City University Nagoya Japan

ISBN: (数字)9798888314449

ISBN: (纸本)9798888314449

In recent years, from the viewpoint of privacy protection policy, research on the personal identification of human bio-signals has been prominent. However, it is not well known whether indices obtained from biological time series data, such as ECGs, have personal identifiability, and it is not clear and can they be discriminated from animal ECGs. In this study, we visualized Heart Rate Variability (HRV) indices data of a cynomolgus monkey (Macaca Fascicularis) and a newborn using T-SNE, which is often used for data dimensionality compression in unsupervised learning, and UMAP, which is a new method. As a result, it was difficult to discriminate between cynomolgus monkey and newborn HRV indices. © 2022 TSI Enterprises.

关键词： Electrocardiograms

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Benchmarking Multi-Robot Coordination in Realistic, Unstructured Human-Shared Environments

Benchmarking Multi-Robot Coordination in Realistic, Unstruct...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Lukas Heuer Luigi Palmieri Anna Mannucci Sven Koenig Martin Magnusson Center for Applied Autonomous Sensor Systems (AASS) Örebro University Sweden Robert Bosch GmbH Corporate Research Stuttgart Germany Department of Computer Science University of Southern California Los Angeles United States of America

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Coordinating a fleet of robots in unstructured, human-shared environments is challenging. Human behavior is hard to predict, and its uncertainty impacts the performance of the robotic fleet. Various multi-robot planning and coordination algorithms have been proposed, including Multi-Agent Path Finding (MAPF) methods to precedence-based algorithms. However, it is still unclear how human presence impacts different coordination strategies in both simulated environments and the real world. With the goal of studying and further improving multi-robot planning capabilities in those settings, we propose a method to develop and benchmark different multi-robot coordination algorithms in realistic, unstructured and human-shared environments. To this end, we introduce a multi-robot benchmark framework that is based on state-of-the-art open-source navigation and simulation frameworks and can use different types of robots, environments and human motion models. We show a possible application of the benchmark framework with two different environments and three centralized coordination methods (two MAPF algorithms and a loosely-coupled coordination method based on precedence constraints). We evaluate each environment for different human densities to investigate its impact on each coordination method. We also present preliminary results that show how informing each coordination method about human presence can help the coordination method to find faster paths for the robots.

关键词： Uncertainty Navigation Robot kinematics Software algorithms Benchmark testing Prediction algorithms Software

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