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50th Euromicro conference on Software Engineering and advanced applications, SEAA 2024

ISBN: (纸本)9798350380262

The proceedings contain 74 papers. The topics discussed include: context-oriented programming and modeling in Julia with context petri nets;scenario-based field testing of drone missions;model-based reliability, availability, and maintainability analysis for satellite systems with collaborative maneuvers via stochastic games;incentivizing fairness in autonomous ecosystems;static timing analysis of cyber-physical systems with relaxed real-time constraints;hierarchical digital twin ecosystem for industrial manufacturing scenarios;dynamics-based identification of hybrid systems using symbolic regression;analyzing the potency of pretrained transformer models for automated program repair;and experimentation in software ecosystems: a systematic literature review.

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The Optimal Design of a Rotor System with Elastic Ring 10

The Optimal Design of a Rotor System with Elastic Ring

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10th IEEE International conference on Dependability in sensor, Cloud and Big Data systems and applications, DependSys 2024

作者： Shi, Yihang Yang, Zhongyu Feng, Yinli Liu, Di University of Chinese Academy of Sciences Chinese Academy of Sciences School of Aeronautics and Astronautics Natl. Key Lab. of Sci. and Technol. on Adv. Light-duty Gasturbine Inst. of Engineering Thermophysics Beijing China University of Chinese Academy of Sciences Chinese Academy of Sciences School of Engineering Sciences Natl. Key Lab. of Sci. and Technol. on Adv. Light-duty Gasturbine Inst. of Engineering Thermophysics Beijing China Chinese Academy of Sciences Institute of Engineering Thermophysics National Key Laboratory of Science and Technology on Advanced Light-duty Gasturbine Beijing China

ISBN: (纸本)9798331540500

Elastic ring (ER) is widely adopted for its compact size and ease of assembly and have become a prevalent type of elastic support within rotor-support systems. However, it may exhibit stiffness nonlinearity under specific operating conditions, potentially compromising the safety of the rotor system. This paper examines the influence of elastic ring stiffness on the critical speed of a specific aero-engine rotor support structure, focusing on related nonlinear phenomena. The Levenberg-Marquardt method was employed to optimize key parameters, including the stiffness and clearance of the elastic ring, with the second-order critical speed as the optimization goal. Finite element analysis was performed to validate the optimization results, which were found to be both effective and practically applicable. The finding provides a significant reference for the design and analysis of aero-engine rotor systems and similar applications. © 2024 IEEE.

关键词： Optimal systems

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Investigation of Hardware-Software Solutions for an Energy-Efficient Wireless sensor Network 12

Investigation of Hardware-Software Solutions for an Energy-E...

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12th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems: Technology and applications, IDAACS 2023

作者： Yatsenko, Anastasiia Parkhomenko, Anzhelika Wolff, Carsten Tulenkov, Artem Parkhomenko, Andriy National University Zaporizhzhia Polytechnic Zaporizhzhia Ukraine Institute for the Digital Transformation of Application and Living Domains University of Applied Sciences and Arts Dortmund Germany

ISBN: (纸本)9798350358056

This work is devoted to the study of methods and tools for minimizing power consumption of wireless sensor networks. The results of processing experimental data for various operating modes of network nodes, as well as options for organizing their power supply and software settings are given. Practical recommendations have been developed to improve the energy efficiency of wireless sensors networks for the Smart Home systems. © 2023 IEEE.

关键词： communication module energy efficiency Smart Home system solar panel wireless sensors network

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Adaptive Vision sensor Based on Nonlinear Negative Photoconductivity Behavior

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advanced FUNCTIONAL MATERIALS 2025年

作者： Jin, Chenxing Wang, Jingwen Liu, Wanrong xu, Yunchao Shi, xiaofang Li, Ruihan Sun, Jia Yang, Junliang Cent South Univ Sch Phys Hunan Key Lab Super Microstruct & Ultrafast Proc Changsha 410083 Hunan Peoples R China Cent South Univ Sch Elect & Informat Changsha 410083 Hunan Peoples R China Cent South Univ Coll Mech & Elect Engn State Key Lab Precis Mfg Extreme Serv Performance Changsha 410083 Hunan Peoples R China Shanghai Inst Microsyst & Informat Technol State Key Lab Transducer Technol 865 Changning Rd Shanghai 200050 Peoples R China

In-sensor adaptive visual systems represent a promising technology applicable across various fields. This method significantly enhances image quality while reducing system complexity, thereby holding substantial scientific significance and practical applications. This study emulates a light-triggered depolarization neuromorphic response utilizing an In2O3/C8-BTBT heterojunction transistor device equipped with ion-gel gating. When the heterojunction device is exposed to UV light, electrons in the In2O3 layer recombine with holes in the C8-BTBT layer, leading to a rapid decrease in photocurrent and resulting in a significant negative photoresponse. The device is capable of simulating spike-dependent inhibitory currents and multilevel storage capabilities. Moreover, the proposed device is employed in constructing a UV-adaptive retina, facilitating in-sensor adaptive computational imaging by leveraging its unique dependence on UV intensity and temporal characteristics, thereby significantly enhancing the visualization of image details.

关键词： adaptive computational imaging negative photoresponse optical stimulation depolarization

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Smart Energy-Efficient Encryption for Wireless Multimedia sensor Networks Using Deep Learning

IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY

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IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY 2024年 5卷 5745-5763页

作者： Khashan, Osama A. Khafajah, Nour M. Alomoush, Waleed Alshinwan, Mohammad Alomari, Emad Rabdan Acad Res & Innovat Ctr Abu Dhabi U Arab Emirates Middle East Univ MEU Res Unit Amman Jordan Skyline Univ Coll Sch Informat Technol Sharjah U Arab Emirates Appl Sci Private Univ Fac Informat Technol Amman Jordan Heriot Watt Univ Sch Engn & Phys Sci Dubai U Arab Emirates

Wireless multimedia sensor networks (WMSNs) have gained considerable attention across various applications due to their capabilities for real-time multimedia data collection, efficient monitoring, and flexible deployment. Despite advancements, challenges persist in ensuring security, optimizing efficiency, and minimizing energy consumption due to the open remote medium, large volumes of multimedia, and inherent resource constraints in WMSNs. This paper introduces an innovative energy-efficient protection model for WMSNs, leveraging advanced deep learning techniques. The model utilizes a lightweight Tiny YOLO-v7 framework to dynamically identify objects within captured images, thereby reducing the need to transmit superfluous data. Moreover, the model combines the lightweight Speck cipher for the encryption of detected objects with a scrambling method that permutes and shuffles all image pixels. An effective key management scheme is also integrated to secure communication and image exchange among nodes within the network. By restricting encryption and transmission to sensitive images containing foreign objects, the proposed model significantly reduces operational overhead. The experimental results showcase the effectiveness of the proposed model in reducing node power consumption by approximately 49% compared to conventional methods, which encrypt and transmit all generated images. Furthermore, the model demonstrates a significant 50% improvement in extending network lifetime compared to related encryption solutions. The security analysis substantiates the model's resistance against diverse attacks, ensuring compliance with the stringent security requirements of WMSNs. Furthermore, the model exhibits strong potential for real-time applications in dynamic monitoring and secure environments.

关键词： Object detection Encryption Wireless sensor networks Wireless communication Communication system security Real-time systems Energy efficiency image encryption deep learning wireless multimedia sensor network energy efficiency lightweight security

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Nonlinear Optical Materials for sensor Protection against Pulsed Laser Radiation in the Visible Spectral Region 2

Nonlinear Optical Materials for Sensor Protection against Pu...

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advanced Materials, Biomaterials, and Manufacturing Technologies for Security and Defence II 2024

作者： Dengler, Stefanie Henrichsen, Michael Fraunhofer IOSB Fraunhofer Institute of Optronics System Techhnologies and Image Exploitation Gutleuthausstr. 1 Ettlingen76275 Germany

ISBN: (纸本)9781510681187

The growing use of lasers increases the risk of accidental or intentional damage to human eyes and optical sensor systems. Current protection equipment is based on optical filters with fixed spectral transmission bands or shutter systems, but optical filters only work in predefined wavebands and shutter-systems are too slow to protect against pulsed laser radiation. Passive self-activated devices, in contrast, offer the potential for short response times with a simple design. Nonlinear optical materials with the capability to strongly attenuate intense laser beams are particularly interesting. In this work, we present our research on the protection capability of C60 and self-produced silver nanoparticles as functional materials in a real application case. A camera with CMOS sensor can be completely protected from being damaged up to a maximum measured input energy of 2 mJ. Therefore, it has been demonstrated that optical limiting materials can be suitable in laser protection applications. © 2024 SPIE.

关键词： Silver nanoparticles

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Enhancing Agricultural Pesticide Application Through a Custom-Built Hexacopter Equipped with advanced Control and Navigation systems 2

Enhancing Agricultural Pesticide Application Through a Custo...

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2nd International conference on Technology Innovation and Its applications, ICTIIA 2024

作者： Sagala, Albert Sinaga, Petrus Manik, Irfan Siagian, Sandro Institut Teknologi Del Toba Indonesia

ISBN: (纸本)9798350351613

Nowadays, technology has been developed to assist farmers in spraying pesticides. This research aims to design a low-cost drone that can spray pesticides on plants. The drone implemented is a type of hexacopter made of aluminium material with dimensions of 1130 mm and is controlled by Pixhawk. The drone moves using six propellers, each 15x5.5 inches in size, mounted on the Sunnysky x4112S 485 KV brushless motor. The drone can be flown manually and autonomously with several motion modes such as hover, roll, pitch, and yaw. For drone stability, a PID (Proportional-Integral-Derivative) controller was applied. Additionally, the Hexacopter is equipped with an ul- trasonic sensor to maintain a position of 1-2 meters above the tree. The drone has been tested and can fly for 7 minutes and 2 seconds without a load and for a maximum of 3 minutes and 48 seconds with a full tank of water, using a 6S 6200 mAh LiPo battery. © 2024 IEEE.

关键词： Drones

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Flexible Thermoelectric BiSbTe/Carbon Paper/BiSbTe Sandwiches for Bimode Temperature-Pressure sensors

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advanced FUNCTIONAL MATERIALS 2025年第5期35卷

作者： Shu, Min He, Zhengxi Zhu, Junjie Ji, Yuru Zhang, xuefei Zhang, Chuanrui Chen, Mengran Zong, Peng-an Nanjing Tech Univ Coll Mat Sci & Engn Nanjing 211800 Peoples R China Nucl Power Inst China Sci & Technol Reactor Syst Design Technol Lab Chengdu 610213 Peoples R China Tsinghua Univ Sch Mat Sci & Engn State Key Lab New Ceram & Fine Proc Beijing 100084 Peoples R China

Bimode temperature-pressure sensors hold significant promise in personal health monitoring, wearables and robotic signal detection. Traditional bimode sensors typically combine two independent sensors, leading to fabrication complexity. This study develops a bimode temperature-pressure sensor by using a facile electrodeposition method to create sandwiched BiSbTe/Carbon Paper/BiSbTe thin films and stacking them to a vertical structure. It demonstrates high sensitivity for temperature sensing, capable of detecting temperature difference as low as 1 K, and a rapid response time of 0.92 s due to a vertical structure. Utilizing its thermoelectric mechanism, the sensor achieves self-powered sensing for finger touch and respiration states. Furthermore, its island-like contact surface ensures high sensitivity with an extremely fast response time of 0.17 s, by rapidly changing contact resistance under pressure, allowing it to detect various human behaviors, including body movements and micro-expressions. Beyond its sensing capabilities, the film excels in flexibility, electromagnetic interference shielding, and stability, presenting significant potential for integration into self-powered electronic skin systems for health monitoring, wearables, artificial intelligence, and other electronic skin applications.

关键词： bimode bismuth telluride carbon flexible sandwich temperature-pressure sensor thermoelectric

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A Predictive Maintenance Platform for a Conveyor Motor sensor System Using Recurrent Neural Networks 5th

A Predictive Maintenance Platform for a Conveyor Motor Senso...

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5th International conference on Neural Computing for advanced applications (NCAA)

作者： Kiangala, Kahiomba Sonia Wang, Zenghui Univ South Africa UNISA Dept Elect & Smart Syst Engn ZA-1709 Johannesburg Gauteng South Africa

ISBN: (纸本)9789819770007;9789819770014

Since the effusion of Industry 4.0 (I40) and smart manufacturing, predictive maintenance (PdM) has become critical to prevent severe system breakdowns and costly production downtime in various industries. Several state-of-the-art Artificial Intelligence (AI) approaches, such as machine learning models (ML), empower the PdM design concept to produce more accurate outcomes. In this study, we propose the development of a PdM platform that effectively detects future possible warnings and failures in the vibration speed sensor of a conveyor motor. We build the platform backend using recurrent neural networks (RNN) regression ML models to predict vibration speed values and their trends. We train our RNN models using univariate time-series historical vibration sensor data recorded over the years. The experimental results demonstrate the robustness of our platform built on RNN models compared to other traditional regression machine learning models such as Extreme Gradient Boosting (xGboost). We compare the effectiveness of the PdM platform with two RNN models: a basic RNN model and a long short-term memory (LSTM) model. Unlike other regression PdM systems focusing on predicting devices Remaining Useful Life (RUL), our PdM platform forecasts and generates new vibration sensor data based on the desired future time range. It also pinpoints set warning and failure values and indicates when these faults are more likely to occur. Factories can utilize this feature for analytics purposes.

关键词： Conveyor Motor sensor Predictive Maintenance (PdM) Recurrent Neural Networks (RNN) Regression Models time-series data

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MEMS Gas sensor Array Fault Diagnostic Unit for Microsystem applications 5

MEMS Gas Sensor Array Fault Diagnostic Unit for Microsystem ...

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5th International conference on Sensing, Measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2024

作者： Fu, Jie Yang, Jian Fu, Hongshuo Liu, Bing Zheng, Wenbin Fu, Ping Harbin Institute of Technology School of Electronics and Information Engineering Harbin China No.703 Research Institute of Cssc Harbin China

ISBN: (纸本)9798331529192

With the rapid development of the Internet of Things and environmental sensing systems, intelligent microsystems based on MEMS (Micro-Electro-Mechanical systems) sensor arrays for environmental sensing have broad application prospects and advantages in fields such as environmental monitoring, medical diagnostics, and battlefield perception. These systems, particularly those aimed at machine olfaction, integrate MEMS gas sensor arrays with pattern recognition algorithms to monitor gases in the environment in real-time. The performance of these systems heavily depends on the accuracy of the MEMS gas sensor array signals. However, due to the characteristics of the sensitive materials and integrated manufacturing processes, environmental changes can cause failures in the MEMS gas sensor arrays, leading to abnormal operation of the entire microsystem. Therefore, this paper designs a fault diagnosis unit for MEMS gas sensor arrays tailored for microsystem applications, measuring 19mm x 19mm x 3mm. This unit can identify five types of sensor faults: shock, bias, constant output, power loss, and precision degradation. It also features fault isolation and localization capabilities, providing a basis for data recovery in case of MEMS gas sensor failures. The fault diagnosis unit employs a multi-task fault diagnosis algorithm based on 1D CNN-LSTM, achieving a fault identification accuracy of 99.93%, fault isolation accuracy of 99.43%, and fault localization accuracy of 98.12%. It occupies 194k of FLASH and 20k of SRAM, with an average running time of 234ms and a power consumption of 11.58mW. © 2024 IEEE.

关键词： Chemical sensors

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