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Practical Application of the Dynamic Output-Only Iterative Learning control Design To The Crane System*

IFAC-PapersOnLine 2022年第12期55卷 476-481页

作者： Lukasz Hladowski Krzysztof Galkowski Eric Rogers Institute of Control and Computation Engineering University of Zielona Góra ul. Podgórna 50 65-246 Zielona Góra Poland Institute of Automation Electronic and Electrical Engineering University of Zielona Góra ul. prof. Z. Szafrana 2 65-516 Zielona Góra Poland Department of Electronics and Computer Science University of Southampton Southampton SO17 1BJ UK

Iterative learning control applies to systems that repeatedly execute the same finite duration task. The distinguishing feature of this form of control action is that all data generated on a previous execution of the task are available to compute the control action for the subsequent execution. This paper uses the linear repetitive process stability analysis and optimization techniques to design a dynamic controller that, in contrast to previous designs in the repetitive process/2D systems setting, does not require measurement of the state dynamics or observer-based estimation. Supporting experimental validation results are also given.

关键词： Iterative learning control repetitive processes output control

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Use of agile software development method to manage academic resources

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AIP Conference Proceedings 2022年第1期2481卷

作者： Anupriya Sharma Ghai Divya Kapil Lakshita Sejwal Atika Gupta Swati Devliyal 1Department of Computer Applications Graphic Era Hill University Dehradun India 2Department of Computer Science & Engineering KCC Institute of Technology & Management Noida India 3Department of Computer Science and Engineering Graphic Era University Dehradun India

Agile is a method that moves quickly, lightly, and approachable in developing a software process. The primary goal of agile methodology is to produce high-quality software in a quicker time. It is using this methodology for developing the Academic Resource in a system provided by software for maintaining academic and financial records of data efficiently and conveniently. The administration of any academic association must make records of students registered and the staff of the university on paper and keep them safe, which is a tedious task due to the increase in manual work that reduced the utilization of the efficiency of staff. This paper describes a systematic approach to developing a user-friendly, flexible, and easy-to-maintain environment for academic resources using agile's extreme programming. The execution of the different tasks to develop the system is used to widen the horizons in Agile Methodologies step by step.

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Adaptive Neural Backstepping control of Nonlinear Fractional-Order Systems with Input Quantization

Research Square

引用

Research Square 2021年

作者： Cheng, Chao Wang, Huanqing Shen, Haikuo Liu, Peter Xiaoping School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China Department of Mathematics Bohai University Jinzhou121000 China Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada

This article addresses the tracking control problem of uncertain fractional-order nonlinear systems in the presence of input quantization and external disturbance by combining with radial basis function(RBF) neural networks(NNs), fractional-order disturbance observer(FODO) and backstepping method. The unknown nonlinearities of fractional-order systems is approximated by RBF NNs. The design of hysteretic quantizer achieves quantification of input signal and avoids chattering. The FODO is utilized to evaluate the external disturbance exist in fractional-order systems. According to fractioanlorder Lyapunov stability analysis, the bounds of all the signals in the closed-loop system is proved. The effectiveness of the proposed method is confirmed by the simulation results. © 2021, CC BY.

关键词： Closed loop systems

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Implicit identification of biometric gait pattern with multilayered back propagation

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AIP Conference Proceedings 2022年第1期2520卷

作者： Vinod P. R. Anitha A. Usha Gopalakrishnan 1Department of Computer Science and Engineering Noorul Islam Centre for Higher Education Kumarakovil Thuckalay Kanyakumari District TamilNadu India. 2Department of Computer Science and Engineering Musaliar College Of Engineering and Technology Pathanamthitta Kerala India.

Smartphone authentication is a widely discussed topic of research in the recent time because of the wide range of security sensitive personal applications and the associated private data. Traditional authentication methods like PIN, passwords, graphical pattern can’t identify the actual user , since the one who enters the credentials correctly will get access to the smartphone application and its data. Physiological biometric security mechanisms like fingerprint and face recognition can provide moderate security to sensitive applications and data but are vulnerable to impersonation, spoofing and presentation attacks. Behavioral biometrics on the other hand, where authentication is done using the behavioral pattern, are proved to be an effective authentication mechanism and can be deployed as continuous and transparent which improve the usability and effectiveness of the authentication system. The proposed work in this paper is based on behavioral biometrics and the dataset is collected from 30 subjects, keeping the smartphone in 4 different positions, performing 5 different activities with each activity contributing to 63000 samples. The data collected are applied to a random forest classifier and the results are compared with different number of folds for cross validation, varying maximum depth for the tree and the number of generated sub trees.

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Performance Analysis of Reconfigurable Intelligent Surface Assisted Two-Way NOMA Networks

arXiv

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arXiv 2022年

作者： Liu, Ziwei Yue, Xinwei Zhang, Chao Liu, Yuanwei Yao, Yuanyuan Wang, Yafei Ding, Zhiguo The Key Laboratory of Modern Measurement & Control Technology Ministry of Education and also The School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The Department of Electrical Engineering Princeton University Princeton United States The School of Electrical and Electronic Engineering The University of Manchester Manchester United Kingdom

This paper investigates the performance of reconfigurable intelligent surface assisted two-way non-orthogonal multiple access (RIS-TW-NOMA) networks, where a pair of users exchange their information through a RIS. The influence of imperfect successive interference cancellation on RIS-TW-NOMA is taken into account. To evaluate the potential performance of RIS-TW-NOMA, we derive the exact and asymptotic expressions of outage probability and ergodic rate for a pair of users. Based on the analytical results, the diversity orders and high signal-to-noise ratio (SNR) slopes are obtained in the high SNR regime, which are closely related to the number of RIS elements. Additionally, we analyze the system throughput and energy efficiency of RIS-TW-NOMA networks in both delay-limited and delay-tolerant transmission modes. Numerical results indicate that: 1) The outage behaviors and ergodic rate of RIS-TW-NOMA are superior to that of RIS-TW-OMA and two-way relay OMA (TWR-OMA);2) As the number of RIS elements increases, the RIS-TW-NOMA networks are capable of achieving the enhanced outage performance;and 3) By comparing with RIS-TW-OMA and TWR-OMA networks, the energy efficiency and system throughput of RIS-TW-NOMA has obvious advantages. © 2022, CC BY-NC-ND.

关键词： Energy efficiency

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Towards to robust and generalized medical image segmentation framework

arXiv

引用

arXiv 2021年

作者： Chen, Yurong Zhang, Hui Wang, Yaonan Liu, Lizhu Wu, Q.M. Jonathan Yang, Yimin National Engineering Laboratory of Robot Visual Perception and Control Technology School of Robotics Hunan University Hunan Changsha410082 China Department of Electrical and Computer Engineering University of Windsor WindsorONN9B3P4 Canada Department of Computer Science Lakehead University Vector Institute TorontoM5G 1M1 Canada

—To mitigate the radiologist’s workload, computer-aided diagnosis with the capability to review and analyze medical images is gradually deployed. Deep learning-based region of interest segmentation is among the most exciting use cases. However, this paradigm is restricted in real-world clinical applications due to the poor robustness and generalization. The issue is more sinister with a lack of training data. In this paper, we address the challenge from the representation learning point of view. We investigate that the collapsed representations, as one of the main reasons which caused poor robustness and generalization, could be avoided through transfer learning. Therefore, we propose a novel two-stage framework for robust generalized segmentation. In particular, an unsupervised Tile-wise AutoEncoder (T-AE) pretraining architecture is coined to learn meaningful representation. Furthermore, this learned prior knowledge is transferred to the segmentation benchmark. Coupled with an image reconstruction network, the representation keeps to be decoded, encouraging the model to capture more semantic features. Experiments of lung segmentation on multi chest X-ray datasets are conducted. Empirically, the comprehensive results demonstrate the superior generalization capability of the proposed framework on unseen domains in terms of high performance and robustness to corruption, especially under the scenario of the limited training data. © 2021, CC BY.

关键词： computer aided diagnosis

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Fully Passive Quantum Key Distribution

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Physical Review Letters 2023年第22期130卷 220801-220801页

作者： Wenyuan Wang Rong Wang Chengqiu Hu Victor Zapatero Li Qian Bing Qi Marcos Curty Hoi-Kwong Lo Department of Physics University of Hong Kong Pokfulam Road Hong Kong Vigo Quantum Communication Center University of Vigo Vigo E-36310 Spain Escuela de Ingeniería de Telecomunicación Department of Signal Theory and Communications University of Vigo Vigo E-36310 Spain AtlanTTic Research Center University of Vigo Vigo E-36310 Spain Department of Electrical and Computer Engineering University of Toronto Toronto Ontario M5S 3G4 Canada Centre for Quantum Information and Quantum Control (CQIQC) University of Toronto Toronto Ontario M5S 1A7 Canada Cisco Systems San Jose California 95134 USA Department of Physics University of Toronto Toronto Ontario M5S 1A7 Canada Quantum Bridge Technologies Inc. 100 College Street Toronto Ontario M5G 1L5 Canada

We propose a fully passive linear optical quantum key distribution (QKD) source that implements both random decoy-state and encoding choices with postselection only, thus eliminating all side channels in active modulators. Our source is general purpose and can be used in, e.g., BB84, the six-state protocol, and reference-frame-independent QKD. It can even potentially be combined with measurement-device-independent QKD to achieve robustness against side channels in both detectors and modulators. We also perform a proof-of-principle experimental source characterization to show its feasibility.

关键词： Optical quantum information processing Quantum communication Quantum cryptography Quantum optics Quantum protocols

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Disease detection based on blood type using inference forward chaining method

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AIP Conference Proceedings 2023年第1期2484卷

作者： S. V. Dewi Marniati N. H. Ali M. D. Payana D. R. Yusian H. Asma 1Department of Information System Faculty of Computer Science Ubudiyah Indonesia University Indonesia. 2Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Nerus Terengganu Malaysia.

Blood type is a permanent and irreversible innate human being. In general, there are 4 types of blood, A, B, O and AB. According to the nature, blood is the key to the entire human immune system, as well as creating antibodies to ward off various diseases and infections. There is a correlation between a disease with a certain blood type. But the knowledge about causes of diseases by blood type is still rarely known by public. This paper presents an implementation of the forward chaining method in the diagnosis diseases based on blood type in getting early knowledge about disease. The Forward Chaining method is used as an inference engine to work based on the fact and symptoms to get the conclusion or result. By utilizing expert system technology and the inference forward chaining method, an android based mobile application is designed to provide early information about diseases that can be caused by blood type. This method will analyze the diagnosis based-on disease database. Testing system using 20 data samples, the diagnostic results showed 17 samples were successfully diagnosed with a match of 80%, and 3 samples with a match of 85%. Based on the test results, the percentage of success reached 81%. Finally, it can be concluded that the disease detection application based on blood type can be used to help user to diagnose diseases earlier and know how to make the prevention against these diseases without meet medical experts. It is more efficient with time, cost, and energy.

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Software reliability models based on machine learning techniques: A review

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AIP Conference Proceedings 2022年第1期2463卷

作者： Bejjam Vasundhara Devi R. Kanniga Devi 1Department of Computer Science and Engineering Sreenidhi Institute of Science and Technology Hyderabad – 501301 Telangana India 2Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Krishnankoil-626126 Tamilnadu India

In order to create outstanding quality, reliable software, the software business has many problems. The reliability of software is important for the reliability of the system. The quality of the software is impressive. It compares with the reliability of hardware by reflecting the perfection of architecture and the reliability of hardware. This paper examines emerging literature focused on machine learning approaches of software reliability models. We can divide the reliability analysis of software into three components: modelling, measuring and improvement. Following the analysis of full applicable articles concerning defects that occur during the elimination of fault, we have proposed a method focusing on the most relevant software reliability parameters using machine learning methods.

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One-half reflected entropy is not a lower bound for entanglement of purification

arXiv

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arXiv 2023年

作者： Couch, Josiah Nguyen, Phuc Racz, Sarah Stratis, Georgios Zhang, Yuxuan Beth Israel Deaconess Medical Center BostonMA02215 United States Brandeis University WalthamMA02453 United States Theory Group Weinberg Institute Department of Physics The University of Texas at Austin AustinTX78712 United States Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Department of Physics The University of Texas at Austin AustinTX78712 United States Department of Physics Centre for Quantum Information and Quantum Control University of Toronto 60 Saint George St. TorontoONM5S 1A7 Canada Vector Institute MaRS Centre TorontoONM5G 1M1 Canada

In recent work, Akers et al. proved that the entanglement of purification Ep(A : B) is bounded below by half of the q-Rényi reflected entropy SR(q)(A : B) for all q ≥ 2, showing that Ep(A : B) = 1/2 SR(q)(A : B) for a class of random tensor network states. Naturally, the authors raise the question of whether a similar bound holds at q = 1. Our work answers that question in the negative by finding explicit counter-examples, which we arrive at through numerical optimization. Nevertheless, this result does not preclude the possibility that restricted sets of states, such as CFT states with semi-classical gravity duals, could obey the bound in question. Copyright © 2023, The Authors. All rights reserved.

关键词： Entropy

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