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Triboelectric Nanogenerators and Hybridized systems for Enabling Next-Generation IoT Applications

Research 2021年第1期2021卷 392-421页

作者： Qiongfeng Shi Zhongda Sun Zixuan Zhang Chengkuo Lee Department of Electrical&Computer Engineering National University of Singapore4 Engineering Drive 3SingaporeSingapore 117583 Center for Intelligent Sensors and MEMS National University of Singapore4 Engineering Drive 3SingaporeSingapore 117583 Smart Systems Institute National University of Singapore3 Research LinkSingaporeSingapore 117602 NUS Graduate School for Integrative Science and Engineering National University of SingaporeSingaporeSingapore 117456

In the past few years,triboelectric nanogenerator-based(TENG-based)hybrid generators and systems have experienced a widespread and flourishing development,ranging among almost every aspect of our lives,e.g.,from industry to consumer,outdoor to indoor,and wearable to implantable *** TENG technology has been extensively investigated for mechanical energy harvesting,most developed TENGs still have limitations of small output current,unstable power generation,and low energy utilization rate of multisource *** harvest the ubiquitous/coexisted energy forms including mechanical,thermal,and solar energy simultaneously,a promising direction is to integrate TENG with other transducing mechanisms,e.g.,electromagnetic generator,piezoelectric nanogenerator,pyroelectric nanogenerator,thermoelectric generator,and solar cell,forming the hybrid generator for synergetic single-source and multisource energy *** resultant TENG-based hybrid generators utilizing integrated transducing mechanisms are able to compensate for the shortcomings of each mechanism and overcome the above limitations,toward achieving a maximum,reliable,and stable output ***,in this review,we systematically introduce the key technologies of the TENG-based hybrid generators and hybridized systems,in the aspects of operation principles,structure designs,optimization strategies,power management,and system *** recent progress of TENG-based hybrid generators and hybridized systems for the outdoor,indoor,wearable,and implantable applications is also ***,we discuss our perspectives on the future development trend of hybrid generators and hybridized systems in environmental monitoring,human activity sensation,human-machine interaction,smart home,healthcare,wearables,implants,robotics,Internet of things(IoT),and many other fields.

关键词： IoT generator harvesting

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Complexity Leadership: On Time, On Budget

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IEEE engineering Management Review 2022年第2期50卷 12-16页

作者： Biggadike, Chris Evans, Richard Pei, Eujin Ultra Electronics Precision Air and Land Systems Department of Engineering CheltenhamGL51 6PN United Kingdom Dalhousie University Faculty of Computer Science HalifaxNSB3H 1W5 Canada Brunel University London Department of Design LondonUB8 3PH United Kingdom

In complex organizations, such as large international engineering firms, practicing managers may possess administrative, enabling, and adaptive leadership styles. Each of these leadership styles must be balanced, but key performance indicators can drive imbalance in engineering management projects. We provide practicing managers with some insights to these leadership styles and their interaction to understand their benefits and challenges that may be overcome. Furthermore, we present a 'balance check' that outlines symptoms of leadership imbalance to keep things from going awry. © 1973-2011 IEEE.

关键词： Managers

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Guest Editorial for Special Issue on Papers From 2023 IEEE International Conference on Flexible Printable Sensors and systems (FLEPS)

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2024年第5期3卷 172-172页

作者： Ng, Tse Nga Mantysalo, Matti Agarwala, Shweta Tee, Benjamin Kim, Woo Soo Grau, Gerd University of California at San Diego Department of Electrical and Computer Engineering La Jolla CA92093 United States Tampere University Department of Electrical Engineering Tampere Finland Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark National University of Singapore Department of Materials Science and Engineering Lower Kent Ridge Road 119077 Singapore Simon Fraser University Department of Mechatronic Systems Engineering BurnabyBCV5A 1S6 Canada York University Department of Electrical Engineering and Computer Science TorontoONM3J 1P3 Canada

This Special Issue of the IEEE Journal on Flexible Electronics (J-FLEX) showcases the expanded papers presented at the 2023 IEEE International Conference on Flexible Printable Sensors and systems (FLEPS), held in Boston, MA, USA. FLEPS was organized by the IEEE Sensors Council. The advancements in flexibility and printability are reshaping the landscape of electronic device design and production, sparking great enthusiasm globally for the field of flexible and printable electronics. FLEPS served as an excellent platform for engaging in discussions about the latest advancements in the field and shaping future pathways for sensors utilizing unconventional materials and manufacturing technologies. FLEPS garnered an enthusiastic response, attracting leading experts, researchers, and innovators from both academia and industry. The technical program of FLEPS 2023 comprised over 150 presentations spanning three days. Submitted papers underwent a rigorous peer-review process. The authors whose papers were accepted were encouraged to submit extended versions for consideration, hence the creation of this special issue. © 2022 IEEE.

关键词： Paper

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LSGAN‑AT:enhancing malware detector robustness against adversarial examples

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Cybersecurity 2021年第1期4卷 594-608页

作者： Jianhua Wang Xiaolin Chang Yixiang Wang Ricardo JRodríguez Jianan Zhang Beijing Key Laboratory of Security and Privacy in Intelligent Transportation Beijing Jiaotong University3 ShangyuancunBeijing 100044China Department of Computer Science and Systems Engineering University of ZaragozaCalle María de Luna 1Zaragoza 50018Spain

Adversarial Malware Example(AME)-based adversarial training can effectively enhance the robustness of Machine Learning(ML)-based malware detectors against *** quality is a key factor to the robustness *** Adversarial Network(GAN)is a kind of AME generation method,but the existing GAN-based AME generation methods have the issues of inadequate optimization,mode collapse and training *** this paper,we propose a novel approach(denote as LSGAN-AT)to enhance ML-based malware detector robustness against Adversarial Examples,which includes LSGAN module and AT *** module can generate more effective and smoother AME by utilizing brand-new network structures and Least Square(LS)loss to optimize boundary *** module makes adversarial training using AME generated by LSGAN to generate ML-based Robust Malware Detector(RMD).Extensive experiment results validate the better transferability of AME in terms of attacking 6 ML detectors and the RMD transferability in terms of resisting the MalGAN black-box *** results also verify the performance of the generated RMD in the recognition rate of AME.

关键词： Adversarial malware example Generative adversarial network Machine learning Malware detector Transferability

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Transmissive glucose concentration plasmonic Au sensor based on unclad optical fiber

Transmissive glucose concentration plasmonic Au sensor based...

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Bioengineering (ENBENG), Portuguese Meeting in

作者： Cristina Cunha Ana Sofia Assunção Catarina S. Monteiro Cátia Leitão João P. Mendes Susana Silva Orlando Frazão Susana Novais Department of Physics and Astronomy Faculty of Sciences of the University of Porto INESC TEC-Institute for Systems and Computer Engineering Technology and Science Porto Portugal Physics Department i3N University of Aveiro Aveiro portugal Faculty of Sciences of the University of Porto INESC TEC-Institute for Systems and Computer Engineering Technology and Science Porto Portugal CIQUP Chemistry Research Center Faculty of Sciences of the University of Porto INESC TEC-Institute for Systems and Computer Engineering Technology and Science Porto Portugal INESC TEC-Institute for Systems and Computer Engineering Technology and Science Porto Portugal

Using surface resonance (SPR) as a sensitivity enhancer, this work describes the development of a transmissive multimode optical fiber sensor with a gold (Au) thin film that measures glucose concentration. The fiber's cladding was initially removed, and an Au layer was then sputtered onto its surface to simultaneously excite SPR and reflect light, making the SPR sensor extremely sensitive to changes in the environment's refractive index. A range of glucose concentrations, from 0.0001 to 0.5000 g/ml, were tested on the sensor. A maximum sensitivity of 161.302 nm/(g/mL) was attained for the lowest glucose concentration, while the highest concentration yielded a sensitivity of 312.000 nm/(g/mL). The proposed sensor's compact size, high sensitivity, good stability and practicality make it a promising candidate for a range of applications, including detecting diabetes.

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Global scale solar energy harnessing: An advanced intra-hourly diffuse solar irradiance predicting framework for solar energy projects

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Neural Computing and Applications 2024年第18期36卷 10585-10598页

作者： El-kenawy, El-Sayed M. Bailek, Nadjem Bouchouicha, Kada Zerouali, Bilel Hassan, Muhammed A. Kuriqi, Alban Jamil, Basharat Colak, Ilhami Khalil, Adel Ibrahim, Abdelhameed Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura35111 Egypt Laboratory of Mathematics Modeling and Applications Department of Mathematics and Computer Science Faculty of Sciences and Technology Ahmed Draia University of Adrar Adrar01000 Algeria Energies and Materials Research Laboratory Faculty of Sciences and Technology University of Tamanghasset Tamanrasset10034 Algeria MEU Research Unit Middle East University Amman Jordan Adrar01000 Algeria Vegetal Chemistry-Water-Energy Laboratory Faculty of Civil Engineering and Architecture Department of Hydraulic Hassiba Benbouali University of Chlef Ouled Fares Chlef02180 Algeria Mechanical Power Engineering Department Faculty of Engineering Cairo University Giza12613 Egypt School of Architecture University of Waterloo 7 Melville St S CambridgeONN1S 2H4 Canada CERIS Instituto Superior Tecnico Universidade de Lisboa Lisbon Portugal Civil Engineering Department University for Business and Technology PristinaKosovo10000 High Temperature Processes Unit IMDEA Energy Institute Av. Ramón de La Sagra 3 Móstoles Madrid28935 Spain Faculty of Engineering and Architectures Nisantasi University Istanbul Turkey Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura35516 Egypt

Diffuse horizontal irradiance (DHI) forecasts are critical for adopting solar photovoltaic technology. Yet, they can lack reliability given the limited and uncertain meteorological data available for desert areas. This research develops a new sine cosine dipper throated optimization (SCDTO) technique, targeting DHI prediction even given such data constraints. SCDTO uniquely hybridizes sine cosine metaheuristics, adept at exploration, with dipper throat optimization, providing focused exploitation. This hybridization aims to create a robust ensemble model capable of delivering reliable DHI predictions despite climatic uncertainty. The ensemble model, employing various input combinations, was rigorously evaluated across multiple meteorological stations. The SCDTO algorithm exhibited remarkable performance improvements, yielding substantial reductions exceeding 93% in root mean squared error and 98% in mean absolute error at key stations in Morocco, including Tan-Tan, Zagora, Erfoud, and Oujda. Comparative analyses against established optimization algorithms consistently underscored the superior predictive capabilities of SCDTO. Visualizations, including box plots and histograms, demonstrated SCDTO’s efficacy in minimizing prediction errors, particularly for Tan-Tan, Zagora, and Erfoud stations. Also, statistical validation through one-way analysis of variance (ANOVA) further affirmed the significance of the proposed SCDTO method. Therefore, this hybrid metaheuristic optimization enables more accurate DHI predictions from limited meteorological data. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Solar energy

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FISS GAN:A Generative Adversarial Network for Foggy Image Semantic Segmentation

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1428-1439页

作者： Kunhua Liu Zihao Ye Hongyan Guo Dongpu Cao Long Chen Fei-Yue Wang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China State Key Laboratory of Automotive Simulation and Control and the Department of Control Science and Engineering Jilin University(Campus Nanling)Changchun 130025China Mechanical and Mechatronics Engineering Department at the University of Waterloo 200 University Avenue West WaterlooON N2L 3G1Canada State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

Because pixel values of foggy images are irregularly higher than those of images captured in normal weather(clear images),it is difficult to extract and express their *** method has previously been developed to directly explore the relationship between foggy images and semantic segmentation *** investigated this relationship and propose a generative adversarial network(GAN)for foggy image semantic segmentation(FISS GAN),which contains two parts:an edge GAN and a semantic segmentation *** edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation *** semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation *** on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance.

关键词： Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation

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Engine Failure Detection of Raw Mill Machine via Discrete Variational Auto-encoder

Engine Failure Detection of Raw Mill Machine via Discrete Va...

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2022 International Conference on Data and Software engineering, ICoDSE 2022

作者： Abruzi, Izhar Brur Iqbal, Mohammad Mukhlash, Imam Rukmi, Alvida Mustika Kurniati, Nani Kimura, Masaomi Institut Teknologi Sepuluh Nopember Sukolilo Department of Mathematics Surabaya60111 Indonesia Institut Teknologi Sepuluh Nopember Sukolilo Department of Industrial and Systems Engineering Surabaya60111 Indonesia Shibaura Institute of Technology Department of Computer Science and Engineering 3 Chome-7-5 Toyosu Tokyo Koto135-8548 Japan

ISBN: (数字)9798350397055

ISBN: (纸本)9798350397055

We present a deep learning model to detect failure engine state by observing the discrete latent sensor behaviors. Further, we investigate the behaviors from the reconstruction loss of the model until we find its value starting to jump out (anomaly stage). As a result, this work aims to forecast the failure time of the engine as early as possible. To notice the anomaly, we formulate a piecewise function based on alpha -quantile of the loss value inside the proposed model. Unlike the existing studies focusing on the continuous latent, this work draws the discrete latent from discrete variational auto-encoder (DVAE) to predict the failure state better. For evaluation purposes, we evaluated the proposed model on a real dataset from the raw mill machine of a cement factory in Indonesia. From the experiments, we are satisfied to see the proposed model performances detecting the failure state of the raw mill machine as early as possible compared to the state-of-the-art model. © 2022 IEEE.

关键词： Engines

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Stolt Interpolation-Free Range Migration Algorithm for Dynamic-Aperture-Based Computational MIMO Microwave Imaging

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IEEE Access 2025年 13卷 83082-83094页

作者： Skouroliakou, Vasiliki García-Fernandez, Maria Álvarez-Narciandi, Guillermo Cotton, Simon Yurduseven, Okan Queen’s University Belfast Centre for Wireless Innovation School of Electronics Electrical Engineering and Computer Science BelfastBT3 9DT United Kingdom University of Oviedo Group of Signal Theory and Communications Department of Electrical Electronic Communications and Systems Engineering Gijón33203 Spain

Computational imaging (CI) techniques realized by dynamic metasurface antennas (DMAs) offer significant advantages in the hardware design reducing the cost of such systems. In this paper, we present a physical layout based solely on DMA panels that can be used to synthesize electrically large apertures suitable for microwave imaging. Although hardware is significantly simplified, the challenge of using CI DMA-based systems presents itself in the signal processing layer. This is because in microwave CI the transfer function of the antennas is used to encode information from the imaged target scene and compress it into a single (or a few) channel(s). As a consequence, real-time Fourier-based image reconstruction algorithms cannot be directly applied because of the nature of the compressed back-scattered signals. In this work, we propose an algorithm that employs a decompression step such that the signal is converted to a suitable form for spatial frequency domain processing. The proposed technique mitigates the challenges of applying the algorithm in the near-field. Crucially, it also eliminates the need for a computationally expensive Stolt interpolation step, which can be a significant bottleneck for conventional Fourier-based image reconstruction algorithms. Numerical and experimental CI results are presented to validate the ability of the proposed system and algorithm to produce reconstructed images of good quality. The benefits of the proposed algorithm in terms of execution time and storage requirements are also explored in this work. © 2013 IEEE.

关键词： Image reconstruction

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Introduction of the Up-to-Date Current Development Activities and the Power Beam Control Experiment Project from the LEO for the Realization of the Operational SSPS 74

Introduction of the Up-to-Date Current Development Activitie...

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74th International Astronautical Congress, IAC 2023

作者： Ijichi, Koichi Yanagawa, Hiroki Kitabatake, Hidetoshi Inada, Hitomi Kashimura, Osamu Tanaka, Koji Ishikawa, Ryo Honjo, Kazuhiko Ishimura, Kosei Japan Space Systems 3-5-8 Shibakoen Minato-ku Tokyo105-0011 Japan Japan Aerospace Exploration Agency Institute of Space and Astronautical Science 3-1-1 Yoshinodai Chuo-ku Kanagawa Sagamihara252-5210 Japan Department of Computer and Network Engineering The University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo182-8585 Japan Waseda University Dept. of Modern Mechanical Engineering School of Creative Science and Engineering 30401 Okubo Shinjuku-ku Tokyo169-8555 Japan

The outline of the project and the up-to-date status and the progress of the power transmission system towards the realization of the Space Solar Power System (SSPS) will be presented including newly started power transmission demonstration project from the LEO satellite to the ground based on the established technologies by the development projects preceded. Japan Space systems and organized team have been engaged in the SSPS project for more than 30 years and the current power transmission system development project for SSPS was started under METI in the year 2019. The project consisted of three major tasks. The first is to develop system and to establish necessary technologies for so called power generation and transmission panel (PGTP) whose size is about 50 cm square and 10 cm thick, and the target weight should be less than 9 kg. This panel is going to be a unit to consist of the practical power generation and transmission system from the space for the operational SSPS in the GEO as the goal. The second is to improve the total efficiency from DC input to output RF power to exceed 60%. The third is to demonstrate long-range wireless power transmission from flying vehicle to the ground. And then, the power transmission demonstration experiment project from the LEO to the ground with 150kg class satellite started at the end of the year 2022, and is going to be introduced in this paper. This project consisted of the power beaming and configuring technologies from the on the orbit phase array transmission system integrated on the LEO satellite to the ground distributed beam configuration measuring system, and also to demonstrate power transmission based on the preceding development results. Copyright © 2023 by the International Astronautical Federation (IAF). All rights reserved.

关键词： LEO satellite Microwave Moon power SSPS WPT

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