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Josephson junction based on high critical-temperature superconductors: analysis, microcontroller implementation, and suppression of coexisting and chaotic attractors

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The European Physical Journal B 2022年第9期95卷 1-13页

作者： Ngongiah, Isidore Komofor Ramakrishnan, Balamurali Natiq, Hayder Pone, Justin Roger Mboupda Kuiate, Gaetan Fautso Department of Physics Faculty of Science University of Bamenda Bamenda Cameroon Center for Nonlinear Systems Chennai Institute of Technology Chennai India Information Technology College Imam Ja’afar Al-Sadiq University Baghdad Iraq Research Unit of Automation and Applied Computer (RUAIA) Electrical Engineering Department of IUT-FV University of Dschang Bandjoun Cameroon Department of Physics Higher Teacher Training College University of Bamenda Bamenda Cameroon Department of Mechanical and Industrial Engineering National Higher Polytechnic Institute University of Bamenda Bamenda Cameroon

A Josephson junction (JJ) based on high critical-temperature superconductors described by a linear resistive–capacitive–inductance shunted junction (LRCLSJ) model with unharmonic current-phase relation (UCPR) is theoretically and experimentally investigated in this paper. The numerical simulations indicate that JJ based on high critical-temperature superconductors exhibits excitable mode, regular spiking, periodic bursting, relaxation oscillations, chaotic attractors, and coexisting attractors. The theoretical investigations are verified experimentally through the microcontroller implementation. In addition, the coexistence between chaotic and limit cycle attractors found in JJ based on high critical-temperature superconductors is controlled to the desired trajectory using the linear augmentation control method. Finally, analytical calculations and numerical simulations are carried out to show the serviceableness of the two designed single controllers in suppressing chaos in JJ based on high critical-temperature superconductors.

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Knowledge graph enhanced neural collaborative recommendation

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Expert Systems with Applications 2021年 164卷 113992-113992页

作者： Sang, Lei Xu, Min Qian, Shengsheng Wu, Xindong Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education Hefei 230009 China Faculty of Engineering and Information Technology University of Technology Sydney Sydney 2007 Australia School of Computer Science and Information Engineering Hefei University of Technology Hefei 230009 China Institute of Automation Chinese Academy of Sciences Beijing 100190 China Mininglamp Academy of Sciences Mininglamp Technology Beijing 100084 China

Existing neural collaborative filtering (NCF) recommendation methods suffer from severe sparsity problem. Knowledge Graph (KG), which commonly consists of fruitful connected facts about items, presents an unprecedented opportunity to alleviate the sparsity problem. However, pure NCF models can hardly model the high-order connectivity in KG, and ignores complex pairwise correlations between user/item embedding dimensions. To address these problems, we propose a novel Knowledge graph enhanced Neural Collaborative Recommendation (K-NCR) framework, which effectively combines user–item interaction information and auxiliary knowledge information for recommendation task into three parts: (1) For items, the proposed propagating model learns the representation of item entity. It recursively aggregates information from its multi-hop neighbours in KG, and employs an attention mechanism to discriminate the importance of the relation type to mine users’ potential preferences. (2) For users, another heterogeneous attention weights are leveraged to strengthen the embedding learning of users. (3) The user and item embeddings are then fed into a newly designed two-dimensional interaction map with convolutional hidden layers to model the complex pairwise correlations between their embedding dimensions explicitly. Extensive experimental results on three benchmark datasets demonstrate the effectiveness of our K-NCR framework. © 2020

关键词： Attention mechanism Graph convolutional networks Knowledge graph Neural collaborative filtering Recommendation system

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AbdomenCT-1K: Is abdominal organ segmentation a solved problem?

arXiv

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arXiv 2020年

作者： Ma, Jun Zhang, Yao Gu, Song Zhu, Cheng Ge, Cheng Zhang, Yichi An, Xingle Wang, Congcong Wang, Qiyuan Liu, Xin Cao, Shucheng Zhang, Qi Liu, Shangqing Wang, Yunpeng Li, Yuhui He, Jian Yang, Xiaoping Department of Mathematics Nanjing University of Science and Technology China Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences China AI Lab Lenovo Research School of Automation Nanjing University of Information Science and Technology China Shenzhen Haichuang Medical CO. LTD. China Institute of Bioinformatics and Medical Engineering Jiangsu University of Technology China School of Biological Science and Medical Engineering Beihang University China Beijing Infervision Technology CO. LTD. China School of Computer Science and Engineering Tianjin University of Technology China Department of Computer Science Norwegian University of Science and Technology Norway School of Electronic Science and Engineering Nanjing University China Suzhou LungCare Medical Technology Co. Ltd China Bioengineering Biological and Environmental Science and Engineering Division King Abdullah University of Science and Technology Saudi Arabia Department of Computer and Information Science Faculty of Science and Technology University of Macau China School of Biomedical Engineering Southern Medical University China Institutes of Biomedical Sciences Fudan University China Computational Biology University of Southern California United States Department of Radiology Nanjing Drum Tower Hospital The Affiliated Hospital Nanjing University Medical School China Department of Mathematics Nanjing University China

With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets. However, most of the existing abdominal datasets only contain single-center, single-phase, single-vendor, or single-disease cases, and it is unclear whether the excellent performance can generalize on diverse datasets. This paper presents a large and diverse abdominal CT organ segmentation dataset, termed AbdomenCT-1K, with more than 1000 (1K) CT scans from 12 medical centers, including multi-phase, multi-vendor, and multi-disease cases. Furthermore, we conduct a large-scale study for liver, kidney, spleen, and pancreas segmentation and reveal the unsolved segmentation problems of the SOTA methods, such as the limited generalization ability on distinct medical centers, phases, and unseen diseases. To advance the unsolved problems, we further build four organ segmentation benchmarks for fully supervised, semi-supervised, weakly supervised, and continual learning, which are currently challenging and active research topics. Accordingly, we develop a simple and effective method for each benchmark, which can be used as out-of-the-box methods and strong baselines. We believe the AbdomenCT-1K dataset will promote future in-depth research towards clinical applicable abdominal organ segmentation methods. © 2020, CC BY-NC-SA.

关键词： computerized tomography

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Corrigendum to: “Time-relevant stability of 2D systems” [Automatica 47 (11) (2011) 2373–2382]

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Automatica 2012年第10期48卷 2737-2737页

作者： D. Napp P. Rapisarda P. Rocha Department of Systems Engineering and Automation University of Valladolid Spain CSPC group School of Electronics and Computer Science University of Southampton Southampton United Kingdom Department of Electrical and Computer Engineering Faculty of Engineering University of Porto Portugal

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Developing an AI literacy test for junior secondary students: The first stage

Developing an AI literacy test for junior secondary students...

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IEEE International Conference on Teaching, Assessment and Learning for engineering (TALE)

作者： King Woon Yau Ching Sing Chai Thomas K. F. Chiu Helen Meng Irwin King Savio Wai-Ho Wong Chandni Saxena Yeung Yam Faculty of Engineering The Chinese University of Hong Kong Shatin Hong Kong China Department of Curriculum and Instruction The Chinese University of Hong Kong Shatin Hong Kong China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Shatin Hong Kong China Department of Computer Science and Engineering The Chinese University of Hong Kong Shatin Hong Kong China Department of Educational Psychology The Chinese University of Hong Kong Shatin Hong Kong China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong China

Artificial Intelligence (AI) education for K-12 is increasingly important as the emerging AI technologies are pervasively infused into human daily lives. Eleven countries have endorsed and implemented the AI curricula at K-12 levels [1]. The "Five Big Ideas" about AI, as proposed by the Association for the Advancement of Artificial Intelligence (AAAI) and the computer science Teacher Association (CSTA) have emerged to form the core components of K-12 AI education [2], [3]. However, the assessment of students’ learning in AI education for K-12 is still in its initial stage. Surveys and interviews are the major assessing tools based on students’ self- perceptions. Standardized tests on students’ AI literacy are still rare. This paper focuses on the first stage of an AI literacy test based on the Five Big Ideas for Grade 7 to Grade 9 students. The test aims to measure the changes of students’ AI literacy before and after attending a one-year AI course. The preliminary findings show the students have increased in their AI literacy after attending the course. The test can provide insights for understanding students’ competencies and needs in AI literacy and improving the curriculum guidelines for students’ effective learning.

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A Pilot Study on the Development and Validation of AI Literacy Test Items for Grade 7 to Grade 9 Students

A Pilot Study on the Development and Validation of AI Litera...

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International Symposium on Educational Technology (ISET)

作者： Yifan Chen King Woon Yau Ching Sing Chai Thomas K. F. Chiu Helen Meng Irwin King Savio Wai-Ho Wong Yeung Yam Faculty of Engineering The Chinese University of Hong Kong Shatin Hong Kong China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Shatin Hong Kong China Department of Curriculum and Instruction The Chinese University of Hong Kong Shatin Hong Kong China Department of Computer Science and Engineering The Chinese University of Hong Kong Shatin Hong Kong China Department of Educational Psychology The Chinese University of Hong Kong Shatin Hong Kong China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong China

ISBN: (数字)9798350361414

ISBN: (纸本)9798350361421

To provide K-12 students with an understanding of AI’s potential opportunities and challenges, AI education has been incorporated into the technology curriculum. Most existing methods for assessing students’ AI literacy rely on self-assessment questionnaires, which may not offer an objective measure of their understanding. This study, therefore, sought to develop and validate a 25 -item multiple-choice test tailored for Hong Kong secondary school students to gauge their AI literacy. A total of 144 students from six secondary schools participated in a pilot test. Item Response Theory (IRT) incorporating a Markov Chain Monte Carlo (MCMC) algorithm, was developed to estimate the difficulty and discrimination indices of test items. The 3-Parameter Logistic (3-PL) model was selected for its effectiveness in providing a more nuanced understanding of item characteristics. Preliminary analysis suggested that the test warrants further revision and enhancement, as evidenced by a Kuder-Richardson Formula 20 (KR-20) reliability coefficient of 0.68. Nonetheless, all test items exhibited satisfactory discrimination capabilities, indicating their proficiency in differentiating among varying levels of respondent aptitude. Thus, this study can provide a foundation for developing a standardized AI literacy test in the future.

关键词： Monte Carlo methods Atmospheric measurements Instruments Educational technology Particle measurements Reliability Iterative methods

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An experiential learning approach to learn AI in an online workshop

An experiential learning approach to learn AI in an online w...

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IEEE International Conference on Teaching, Assessment and Learning for engineering (TALE)

作者： Yuan Xu Ching Sing Chai Helen Meng Savio Wai Ho Wong King Woon Yau Thomas K. F. Chiu Irwin King Yeung Yam Faculty of Engineering The Chinese University of Hong Kong Hong Kong SAR China Department of Curriculum and Instruction The Chinese University of Hong Kong Hong Kong SAR China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong SAR China Department of Educational Psychology The Chinese University of Hong Kong Hong Kong SAR China Department of Computer Science & Engineering The Chinese University of Hong Kong Hong Kong SAR China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong SAR China

As educating K-12 students about artificial intelligence (AI) gains prominence, the question of which pedagogical approach could promote the learning of AI needs exploration. This study aims to investigate the feasibility and effectiveness of learning fundamental AI concepts through online experiential learning. A total of 673 secondary school students participated in a two-day online workshop. A set of pre-and-post questionnaires was applied to assess students' understanding of fundamental AI concepts and their perceptions to learn AI. The results showed the online workshop was effective in improving students’ knowledge of AI and their motivation to learn about it. These findings suggested that the use of online experiential learning approach to learn AI is not only feasible but also appropriate for secondary school students. Furthermore, this study discussed the practical implications of incorporating experiential learning into online learning experience for K-12 students, providing insights into the potential of online workshops as a means of learning AI.

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Analysis of the EMF Parameters of the Stator Winding in the Run-Down Mode for Diagnosing Faults in an Induction Motor

Analysis of the EMF Parameters of the Stator Winding in the ...

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Smart Information Systems and Technologies (SIST), IEEE International Conference on

作者： Assel Yussupova Alexandra Potapenko Alexandr Neftissov Dariya Urazalimova Oleh Serbin Department of Electrical Engineering and Automation Toraighyrov University Pavlodar Kazakhstan Faculty of Computer Science Toraighyrov University Pavlodar Kazakhstan Research and innovation center “Industry 4.0” Astana IT University Astana Kazakhstan Dr. Habil. (Social sciences Communication) Chief Executive Officer CEO & Executive Director Yaroslav Mudryi National Library of Ukraine Professor of Kyiv National University of Culture and Arts Ukraine

In industry, as well as in power plants and substations of developed countries, induction motor (IM) are the most common electrical machine. They consume a large amount of the generated electricity. At the same time, they account for a sufficient number of failures of all electrical equipment. In this case, the proportion of failures due to a break in a squirrel-cage rotor, according to various authors, can reach about 5-10%. However, experimental studies at a number of plants and power plants in the Pavlodar region have shown that the damage factor of the squirrel-cage IM rotor is much higher. As a rule, the breakage of the squirrel-cage rotor rods does not lead to an immediate failure of the IM, but is accompanied by a deterioration in its electromechanical characteristics. Basically, the harm from the operation of such IM is expressed in increased energy consumption. Moreover, a year of its operation leads to an excessive consumption of electricity, comparable to the cost of the IM itself. The article shows that today there are a large number of proposals for a method for diagnosing damage to the short-circuited rotor winding of an induction motor (IM) during operation. However, their sensitivity is limited by the need for detuning from fluctuations in the parameters of the electrical network, vibrations of the IM and the uneven moment of resistance of its load. Most of these effects can be eliminated if IM diagnostics are carried out based on the analysis of the EMF parameters in the stator winding in the rundown mode. The authors have analyzed the parameters of the EMF of the stator winding at all stages of the rundown mode and substantiated the use of the presented method for diagnosing faults in an induction motor.

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HIGH-RISE BUILDINGS UNDER EARTHQUAKE EXCITATION: STABILIZATION USING SMC

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IFAC Proceedings Volumes 2006年第16期39卷 776-781页

作者： Georgi M. Dimirovski Jun Zhao Miomir K. Vukobratovic Dogus University Faculty of Engineering Dept. of Computer Engineering Acibadem Zeamet Sk. 21 Kadikoy TR-34722 Istanbul Rep. of Turkey Fax: ++90-216-327-9631 Tel: ++90-216-327-1104 SS Cyril and Methodius University Faculty of Electrical Engineering Rugjer Boskovic b.b. Karpos II MK-1000 Skopje Rep. of Macedonia Northestern University School of Information Science and Engineering Institute of Control Science Shenyang Liaoning CN-110004 P. R. of China Fax: ++86-24-8367-2273 Tel: ++86-24-2389-3000 Mihailo Pupin Institute Laboratory of Robotics & Automation Volgina 15 Karaburma 11000 F. R. Serbia and Montenegro Fax: ++381-11-2775-870 Tel: ++381-11-2774-236

The goal to control the dynamics of high-rise buildings either to ameliorate the damage or prevent their destruction when subject to an earthquake excitation has been subject of extensive research. All known control designs have advantages and disadvantages as well as operating limits. The application of sliding-mode control to controlling earthquake induced vibrations of a multi-story structural system as an active seismic compensation plus base isolation has been investigated. The performance has been compared to the one of traditional industrial controls, and relevant conclusions drawn. Simulation results, carried out using El Centro earthquake acceleration, have shown that the sliding mode control can decrease significantly displacements of the floors.

关键词： Earthquake sliding mode control structural systems vibration control

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Stability Analysis of Fuzzy Logic Control Systems for a Class of Nonlinear SISO Discrete-Time Systems

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IFAC Proceedings Volumes 2011年第1期44卷 13612-13617页

作者： Radu-Emil Precup Marius-Lucian Tomescu Stefan Preitl Emil M. Petriu Claudia-Adina Dragoş Department of Automation and Applied Informatics “Politehnica” University of Timisoara Bd. V. Parvan 2 RO-300223 Timisoara Romania (Tel: +40-256403229 Computer Science Faculty “Aurel Vlaicu” University of Arad Complex Universitar M Str. Elena Dragoi 2 RO-310330 Arad Romania Department of Automation and Applied Informatics “Politehnica” University of Timisoara Bd. V. Parvan 2 RO-300223 Timisoara Romania School of Information Technology and Engineering University of Ottawa 800 King Edward Ottawa Ontario K1N 6N5 Canada

Abstract This paper suggests a new stability analysis theorem dedicated to a class of fuzzy logic control systems. The fuzzy logic control systems consist of nonlinear Single Input-Single Output (SISO) discrete-time processes controlled by Takagi-Sugeno fuzzy logic controllers. The stability analysis is conducted on the basis of Lyapunov's direct method with quadratic Lyapunov function candidates. The theorem proves that if the derivative of the Lyapunov function candidate is negative definite in the active region of each fuzzy rule then the fuzzy logic control system will be asymptotically stable in the sense of Lyapunov. Sufficient stability conditions are offered. An example related to the design of a stable fuzzy logic control system for the discrete-time Lorenz chaotic system and simulation results are included.

关键词： Discrete-time systems fuzzy logic control Lyapunov function candidates nonlinear systems stability analysis

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