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Global Emerging technology Blockchain Forum: Blockchain & Beyond (iGETblockchain), IEEE

作者： Hongchi Wu Binhao Fang Cheng Xiang Gregory Cohen André van Schaik Bharath Ramesh Department of Electrical and Computer Engineering Advanced Control Technology Lab National University of Singapore Singapore International Center for Neuromorphic Systems The MARCS Institute for Brain Behaviour and Development Western Sydney University Sydney Australia

Neuromorphic intelligent systems are motivated by the observation that biological organisms - from algae to primates - excel in swiftly sensing their environment, reacting promptly to its perils and opportunities. Furthermore, biological organisms function more resiliently than our most advanced machines, with a fraction of their power requirements. Taking inspiration from how primates and humans have successfully evolved higher cognitive intelligence within social constructs, this paper proposes neuromorphic systems to be built and governed on a public distributed ledger platform. However, following in the footsteps of generic AI research, neuromorphic benchmarks and algorithms are developed in isolation. Furthermore, as a relatively niche research field, there is limited access to the actual neuromorphic sensors and large publicly available curated data, exacerbating the slow research progress. Nonetheless, centralized neuromorphic datasets and algorithms pose a threat to secure closed-loop behavior and learning outcomes, both commonly modulated in biological organisms via social interactions. This paper makes the case for early adoption of distributed ledger technology by neuromorphic systems and benchmarks to avoid the pitfalls endured by AI research – showcasing competing event-based gesture recognition systems on the Ethereum smart contract platform. This shift towards real-world and dynamic systems on a distributed ledger platform will improve collaboration among neuromorphic researchers while enabling healthy competition via incentives. Smart contract protocols allow model behavior monitoring, setting new learning tasks and increase in baseline performance, and naturally provides a governance framework for evolving neuromorphic systems. The code is publicly made available at: https://***/BruceFang123.

关键词： Neuromorphics Distributed ledger Smart contracts Biological systems Benchmark testing Blockchains Sensors

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Diagnosis of COVID-19 from X-rays using combined CNN-RNN architecture with transfer learning

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BenchCouncil Transactions on Benchmarks, Standards and Evaluations 2022年第4期2卷 100088-100088页

作者： Islam, Md. Milon Islam, Md. Zabirul Asraf, Amanullah Al-Rakhami, Mabrook S. Ding, Weiping Sodhro, Ali Hassan Department of Computer Science and Engineering Khulna University of Engineering & Technology Khulna9203 Bangladesh Research Chair of Pervasive and Mobile Computing Information Systems Department College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia School of Information Science and Technology Nantong University Nantong226019 China Department of Computer Science Kristianstad University KristianstadSE-29188 Sweden Shenzhen Institutes of Advanced technology Chinese Academy of Sciences Shenzhen China

Combating the COVID-19 pandemic has emerged as one of the most promising issues in global healthcare. Accurate and fast diagnosis of COVID-19 cases is required for the right medical treatment to control this pandemic. Chest radiography imaging techniques are more effective than the reverse-transcription polymerase chain reaction (RT-PCR) method in detecting coronavirus. Due to the limited availability of medical images, transfer learning is better suited to classify patterns in medical images. This paper presents a combined architecture of convolutional neural network (CNN) and recurrent neural network (RNN) to diagnose COVID-19 patients from chest X-rays. The deep transfer techniques used in this experiment are VGG19, DenseNet121, InceptionV3, and Inception-ResNetV2, where CNN is used to extract complex features from samples and classify them using RNN. In our experiments, the VGG19-RNN architecture outperformed all other networks in terms of accuracy. Finally, decision-making regions of images were visualized using gradient-weighted class activation mapping (Grad-CAM). The system achieved promising results compared to other existing systems and might be validated in the future when more samples would be available. The experiment demonstrated a good alternative method to diagnose COVID-19 for medical staff. All the data used during the study are openly available from the Mendeley data repository at https://***/datasets/mxc6vb7svm. For further research, we have made the source code publicly available at https://***/Asraf047/COVID19-CNN-RNN. © 2023 The Authors

关键词： COVID-19

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A new electric field mill array with each of the mill’s rotor controlled precisely by a GPS module:Equipment and initial results

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Earth and Planetary Physics 2024年第2期8卷 423-435页

作者： Kozo Yamashita Hironobu Fujisaka DaoHong Wang Hiroyuki Iwasaki Kazuo Yamamoto Koichiro Michimoto Masashi Hayakawa Department of Production Systems Engineering and Sciences Komatsu UniversityNu 1-3 Shicho-machiKomatsuIshikawa 923-8511Japan Fujisaka Technology Office 1058-5 Yoshizawa-choOhta-shiGunma 373-0019Japan Department of Electrical Electronic and Computer EngineeringGifu University1-1 YanagidoGifu CityGifu 501-1193Japan Cooperative Faculty of Education Gunma University4-2-Aramaki-machiMaebashiGunma 371-8510Japan Department of Electrical and Electronic Engineering Chubu University1200 Matsumoto-choKasugaiAichi 487-8501Japan Independent Researcher Kosenba Town 2-44-11-406Kawagoe CitySaitama350-0036Japan Advanced Wireless&Communications Research Center The University of Electro-Communications1-5-1 ChofugaokaChofuTokyo 182-8585Japan

We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning *** is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple *** multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed ***,there is no such EFM with specified speed and phase control performance of the rotary ***,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS *** EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test *** we describe the design and a simple calibration method for our new EFM *** analysis method based on the assumption of a simple monopole charge structure is also *** validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF *** results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.

关键词： lightning electrostatic field electric field mill electric field change

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Fast accurate position control of light-responsive liquid crystal elastomer actuator

Fast accurate position control of light-responsive liquid cr...

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Asian Control Conference

作者： Xinyu Nie Jundong Wu Yawu Wang Chun-Yi Su Daiki Sato Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Gina Cody School of Engineering and Computer Science Concordia University Montreal Quebec Canada Laboratory for Future Interdisciplinary Research of Science and Technology (FIRST) Tokyo Institute of Technology Yokohama Kanagawa Japan The School of Engineering Tokyo University of Technology Tokyo Japan

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

Light-responsive liquid crystal elastomers (LCEs) are promising for soft robot actuators due to their ability to respond to light stimuli and produce deformation. In order to realize their application in soft robots, fast and accurate position control is essential. Based on the intrinsic physical nature of LCE actuator's deformation, a terminal sliding mode controller (TSMC) is designed to efficiently adjust the temperature of the actuator, thus directly controlling the actuator deformation. In order to achieve the target temperature, a prediction model is established to predict the target temperature corresponding to the target displacement. Moreover, a proportional integration controller is applied to eliminate model errors and disturbances. The feasibility of the control strategy is experimentally verified, and compared with conventional PID controller. The results prove that the proposed control strategy can achieve fast and accurate control of displacement.

关键词： Heating systems Actuators Accuracy Deformation Position control Process control Elastomers

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Fully integrated hybrid microwave photonic receiver

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Photonics Research 2022年第6期10卷 1472-1483页

作者： JIACHEN LI SIGANG YANG HONGWEI CHEN XINGJUN WANG MINGHUA CHEN WEIWEN ZOU Beijing National Research Center for Information Science and Technology(BNRist) Department of Electronic EngineeringTsinghua UniversityBeijing 100084China State Key Laboratory of Advanced Optical Communications System and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center(imLic)Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Microwave photonic receivers are a promising candidate in breaking the bandwidth limitation of traditional radio-frequency(RF)*** further balance the performance superiority with the requirements regarding size,weight,and power consumption(SWa P),the implementation of integrated microwave photonic microsystems has been considered an upgrade ***,up to now,to the best of our knowledge,chip-scale fully integrated microwave photonic receivers have not been reported due to the limitation of material *** this paper,we report a fully integrated hybrid microwave photonic receiver(FIH-MWPR)obtained by comprising the indium phosphide(In P)laser chip and the monolithic silicon-on-insulator(SOI)photonic circuit into the same substrate based on the low-coupling-loss micro-optics *** from the integration of all optoelectronic components,the packaged FIH-MWPR exhibits a compact volume of 6 cmand low power consumption of 1.2 *** FIH-MWPR supports a wide operation bandwidth from 2 to 18 ***,its RF-link performance to down-convert the RF signals to the intermediate frequency is experimentally characterized by measuring the link gain,the noise figure,and the spurious-free dynamic range metrics across the whole operation frequency ***,we have utilized it as a de-chirp receiver to process the broadband linear frequencymodulated(LFM)radar echo signals at different frequency bands(S-,C-,X-,and Ku-bands)and successfully demonstrated its high-resolution-ranging *** the best of our knowledge,this is the first realization of a chip-scale broadband fully integrated microwave photonic receiver,which is expected to be an important step in demonstrating the feasibility of all-integrated microwave photonic microsystems oriented to miniaturized application scenarios.

关键词： method microwave bands

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Direct Distillation between Different Domains

arXiv

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arXiv 2024年

作者： Tang, Jialiang Chen, Shuo Niu, Gang Zhu, Hongyuan Zhou, Joey Tianyi Gong, Chen Sugiyama, Masashi School of Computer Science and Engineering Nanjing University of Science and Technology China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education China Jiangsu Key Laboratory of Image and Video Understanding for Social Security China Singapore Center for Advanced Intelligence Project RIKEN Japan The Graduate School of Frontier Sciences The University of Tokyo Japan

Knowledge Distillation (KD) aims to learn a compact student network using knowledge from a large pre-trained teacher network, where both networks are trained on data from the same distribution. However, in practical applications, the student network may be required to perform in a new scenario (i.e., the target domain), which usually exhibits significant differences from the known scenario of the teacher network (i.e., the source domain). The traditional domain adaptation techniques can be integrated with KD in a two-stage process to bridge the domain gap, but the ultimate reliability of two-stage approaches tends to be limited due to the high computational consumption and the additional errors accumulated from both stages. To solve this problem, we propose a new one-stage method dubbed "Direct Distillation between Different Domains" (4Ds). We first design a learnable adapter based on the Fourier transform to separate the domain-invariant knowledge from the domain-specific knowledge. Then, we build a fusion-activation mechanism to transfer the valuable domain-invariant knowledge to the student network, while simultaneously encouraging the adapter within the teacher network to learn the domain-specific knowledge of the target data. As a result, the teacher network can effectively transfer categorical knowledge that aligns with the target domain of the student network. Intensive experiments on various benchmark datasets demonstrate that our proposed 4Ds method successfully produces reliable student networks and outperforms state-of-the-art approaches. Copyright © 2024, The Authors. All rights reserved.

关键词： Distillation

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Short - Term Prediction of Coke Pushing Current Peak Based on Improved ARIMA Model

Short - Term Prediction of Coke Pushing Current Peak Based o...

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Industrial Cyber-Physical systems (ICPS)

作者： Haiyang Wei Luefeng Chen Jie Hu Yi Ren Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Tokyo Institute of Technology Yokohama Japan

Coke pushing current is an indicator to evaluate the difficulty of coke pushing operation. The higher coke pushing current is, the greater coke pushing resistance is, and the more difficult coke is to push out. Accurate prediction of current peak during future coke pushing operation can provide more time for production personnel to adjust production status and avoid difficult coke pushing in carbonization chamber. In this paper, a combination prediction model based on VMD (Variational Mode Decomposition) and improved ARIMA (Autoregressive Integrated Moving Average) models is proposed. Firstly, VMD algorithm is used to decompose time series of coke pushing current peak, de-noising data, and extracting main information of time series. Then, ARIMA model is used to predict mean change of linear elasticity and GARCH (Generalized Autore-gressive Conditional Heteroskedasticity) model is introduced to predict ARIMA model residual and improve heteroscedasticity of nonlinear part of time series, and then ARIMA-GARCH model is established. Finally, predicted value is obtained by the sum of each component prediction. The experimental results show that the proposed prediction model has a high prediction accuracy in the short-term prediction of coke pushing current peak. The scheme is applied to actual coking production to guide production of coke.

关键词： Resistance Ovens Time series analysis Noise reduction Production Predictive models Prediction algorithms

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Development of Virtual Learning Factory Toolkit for Production Engineering Education 13

Development of Virtual Learning Factory Toolkit for Producti...

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13th International DAAAM Baltic Conference and 29th International Baltic Conference, BALTMATTRIB 2021

作者： Mahmood, Kashif Otto, Tauno Kuts, Vladimir Terkaj, Walter Urgo, Marcello Haidegger, Geza Department of Mechanical and Industrial Engineering Tallinn University of Technology Tallinn Estonia STIIMA-CNR Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing National Research Council Milan Italy Manufacturing and Production Systems Division Department of Mechanical Engineering Politecnico di Milano Milan Italy SZTAKI – Institute for Computer Science and Control Budapest Hungary

The advent of industry 4.0 and the continuous digitalization of production ask for the enhancement of human skills and competences in the field of information and communication technology (ICT). Therefore, higher education has to keep pace with the global market needs for the necessary ICT skills and the overall understanding of the complexity of industries in 21st century. This paper focuses on the development and integration of Virtual Learning Factory (VLF) tools that can be used in production management and engineering education. The digital tools integrated in VLF toolkit can help students to exploit enabling technologies like simulation and virtual reality in their manufacturing studies and practical projects with industrial companies. © 2021 DAAAM International. All rights reserved.

关键词： Engineering education

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Toward parallel intelligence: an interdisciplinary solution for complex systems

arXiv

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arXiv 2023年

作者： Zhao, Yong Zhu, Zhengqiu Chen, Bin Qiu, Sihang Huang, Jincai Lu, Xin Yang, Weiyi Ai, Chuan Huang, Kuihua He, Cheng Jin, Yucheng Liu, Zhong Wang, Fei-Yue College of Systems Engineering National University of Defense Technology Changsha410073 China Hunan Institute of Advanced Technology Changsha410073 China Shanghai Institute of Infectious Disease and Biosecurity Shanghai200032 China Neuherberg Germany Department of Computer Science Hong Kong Baptist University 999077 Hong Kong State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling, analysis, management, and control. To meet these demands, the parallel systems method rooted in Artificial systems, Computational experiments, and Parallel execution (ACP) approach has been developed. The method cultivates a cycle, termed parallel intelligence, which iteratively creates data, acquires knowledge, and refines the actual system. Over the past two decades, the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines, offering versatile interdisciplinary solutions for complex systems across diverse fields. This review explores the origins and fundamental concepts of the parallel systems method, showcasing its accomplishments as a diverse array of parallel technologies and applications, while also prognosticating potential challenges. We posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation. © 2023, CC BY-NC-ND.

关键词： Iterative methods

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A Novel Platform to Control Biofouling in Pearl Oysters Cultivation

A Novel Platform to Control Biofouling in Pearl Oysters Cult...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Van-Nhan Tran Quan-Dung Pham Tan-Sang Ha Yue Him Wong Sai-Kit Yeung Division of Integrative Systems and Design School of Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong SAR Department of Computer Science and Engineering School of Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong SAR Institute for Advanced Study Shenzhen University Shenzhen Guangdong China

This paper presents a simple yet effective design of a platform to automate the task of shellfish aquaculture, specifically pearl oysters. Compared to traditional methods, our platform can eliminate the tedious task of cleaning the pearl oysters due to fouling. Inspired by the low and high tide characteristics of the intertidal zone, our platform employs an air-water displacement mechanism to periodically float pearl oysters above the water's surface, exposing fouling organisms to air and sunlight. While pearl oysters have developed the ability to stay alive during low tide, these fouling organisms cannot survive after prolonged exposure, thus preventing them from developing. Additionally, the platform provides an alternative approach to grow not only pearl oysters but also various types of shellfish, consequently benefiting the aquaculture industry. We introduce the design of the platform and provide a comprehensive analysis. We also demonstrate the practical deployment of the platform for cultivating pearl oysters.

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