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TechRxiv 2022年

作者： Tang, Ning Chang, Jieling Wang, Lingling Fu, Li Neusypin, Konstantin A. Selezneva, Maria S. Peng, Linping The School of Automation Science and Electrical Engineering Beihang University Beijing100191 China The Faculty of Computer Science and Control Systems Bauman Moscow State Technical University Moscow105005 Russia Experimental Teaching Demonstration Center of Mechanical and Control Engineering Beihang University Beijing100191 China The School of Mathematics and System Sciences Beihang University Beijing100191 China

In practical applications, commercial-grade Micro-Electro-Mechanical System (MEMS) gyros tend to exhibit dynamics sensitivities which are resistant to modeling by linear drift. To address the problem, a new nonlinear robust bias observer (NRBO) is proposed in this paper. Unlike the existing attitude and gyro bias nonlinear observers, we propose a dynamics-sensitive gyro bias decomposition method to tackle unknown nonlinear dynamic models of MEMS gyro bias. We expose the potential advantages of the proposed method: the global asymptotic stability of the NBRO and the robustness to the bias instability of MEMS gyros can be guaranteed through a rational design of the attitude-angular rate nonlinear dynamic coupling (AARNDC) term and the attitude-linear coupling (ALC) term. In addition, the attitude estimation with bias correction is given in the framework of NBRO. The experiment of a cable-parallel robot demonstrate the robustness to the bias instability and the accuracy improvement of MEMS gyros. © 2022, CC BY.

关键词： Gyroscopes

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A fast algorithm on generating concept lattice for symmetry formal context constructed from social networks

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Journal of Ambient Intelligence and Humanized Computing 2019年 1-8页

作者： Hao, Fei Yang, Yixuan Pang, Beibei Yen, Neil Y. Park, Doo-Soon Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an710062 China School of Computer Science Shaanxi Normal University Xi’an710119 China School of Computer Science and Engineering The University of Aizu Aizu965-8580 Japan Department of Computer Software Engineering Soonchunhyang University Asan31538 Korea Republic of

Formal concept analysis has been witnessed to be an effective soft computing methodology for data analysis, rule extraction and clustering, but how to build a formal concept lattice efficiently is always a challenge issue. Recent years, several deformation formal contexts are emerging for addressing current important research problems, such as virtual machines scheduling in mobile cloud computing and topological structure analysis in social networks. In this paper, we focus on the symmetry formal context where the objects and attributes are identical, and its formal concept lattice construction. Firstly, we explore the properties of symmetry formal context and discover a symmetry line which must appear in the expected formal concept lattice. Further, a fast algorithm for building concept lattice for symmetry formal context is presented. Then, five social network datasets are utilized for evaluating our proposed algorithm. Experimental results show that our algorithm can speed up 1.2 times and 3.45 times compared to the concept-matrix based concepts generation algorithm and incremental algorithm, respectively. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Formal concept analysis

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Beyond Jacobian-based tasks: Extended set-based tasks for multi-task execution and prioritization

arXiv

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arXiv 2023年

作者： Notomista, Gennaro Selvaggio, Mario Santos, María Mayya, Siddharth Pagano, Francesca Lippiello, Vincenzo Secchi, Cristian Department of Electrical and Computer Engineering University of Waterloo WaterlooON Canada Department of Electrical Engineering and Information Technology University of Naples Federico II Napoli Italy Department of Mechanical and Aerospace Engineering Princeton University PrincetonNJ08544 United States Amazon Robotics North ReadingMA01864 United States Department of Science and Methods of Engineering University of Modena and Reggio Emilia Modena Italy

The ability of executing multiple tasks simultaneously is an important feature of redundant robotic systems. As a matter of fact, complex behaviors can often be obtained as a result of the execution of several tasks. Moreover, in safety-critical applications, tasks designed to ensure the safety of the robot and its surroundings have to be executed along with other nominal tasks. In such cases, it is also important to prioritize the former over the latter. In this paper, we formalize the definition of extended set-based tasks, i.e., tasks which can be executed by rendering subsets of the task space asymptotically stable or forward invariant. We propose a mathematical representation of such tasks that allows for the execution of more complex and time-varying prioritized stacks of tasks using kinematic and dynamic robot models alike. We present and analyze an optimization-based framework which is computationally efficient, accounts for input bounds, and allows for the stable execution of time-varying prioritized stacks of extended set-based tasks. The proposed framework is validated using extensive simulations and experiments with robotic manipulators. Copyright © 2023, The Authors. All rights reserved.

关键词： Safety engineering

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Modeling Multiple Views via Implicitly Preserving Global Consistency and Local Complementarity

arXiv

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arXiv 2022年

作者： Li, Jiangmeng Qiang, Wenwen Zheng, Changwen Su, Bing Razzak, Farid Wen, Ji-Rong Xiong, Hui The University of Chinese Academy of Sciences Beijing China The Science & Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China The New York University Columbia University New York United States The Beijing Key Laboratory of Big Data Management and Analysis Methods Gaoling School of Artificial Intelligence Renmin University of China Beijing100872 China Guangzhou China Department of Computer Science & Engineering The Hong Kong University of Science and Technology Hong Kong

While self-supervised learning techniques are often used to mine hidden knowledge from unlabeled data via modeling multiple views, it is unclear how to perform effective representation learning in a complex and inconsistent context. To this end, we propose a new multi-view self-supervised learning method, namely consistency and complementarity network (CoCoNet), to comprehensively learn global inter-view consistent and local cross-view complementarity-preserving representations from multiple views. To capture crucial common knowledge which is implicitly shared among views, CoCoNet employs a global consistency module that aligns the probabilistic distribution of views by utilizing an efficient discrepancy metric based on the generalized sliced Wasserstein distance. To incorporate cross-view complementary information, CoCoNet proposes a heuristic complementarity-aware contrastive learning approach, which extracts a complementarity-factor jointing cross-view discriminative knowledge and uses it as the contrast to guide the learning of view-specific encoders. Theoretically, the superiority of CoCoNet is verified by our information-theoretical-based analyses. Empirically, our thorough experimental results show that CoCoNet outperforms the state-of-the-art self-supervised methods by a significant margin, for instance, CoCoNet beats the best benchmark method by an average margin of 1.1% on ImageNet. Copyright © 2022, The Authors. All rights reserved.

关键词： Supervised learning

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Amby: A Development Environment for Youth to Create Conversational Agents

SSRN

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SSRN 2022年

作者： Tian, Xiaoyi Kumar, Amit Solomon, Carly E. Calder, Kaceja D. Celepkolu, Mehmet Pezzullo, Lydia Boyer, Kristy Elizabeth Israel, Maya Department of Computer and Information Science and Engineering University of Florida 432 Newell Dr Floria Gainesville32611 United States Department of Educational Technology School of Teaching and Learning University of Florida 1221 SW 5th Ave GainesvilleFL32601 United States

Conversational AI such as Alexa and Google Home are increasingly ubiquitous in young people’s lives, but these young users are often not afforded the opportunity to learn about the inner workings of these technologies. One of the most powerful ways to foster this learning is to empower youth to create AI that is personally and socially meaningful to them. We have built a novel development environment, AMBY–"AI Made By You"–for youth to create conversational agents. AMBY was iteratively designed with, and for youth aged 12-13 through contextual inquiry and usability studies. AMBY is designed to foster AI learning with features that enable users to generate training datasets and visualize conversational flow. We report on results from a two-week summer camp deployment, and contribute design implications for conversational AI authoring tools that empower AI learning for youth. © 2022, The Authors. All rights reserved.

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Second-order Volterra Filter based on DFP Technique 4

Second-order Volterra Filter based on DFP Technique

引用

2019 4th International Seminar on computer Technology, Mechanical and Electrical Engineering, ISCME 2019

作者： Bai, Shulin Xu, Jiadong Zhang, Yumei School of Electronics and Information Northwestern Polytechnical University Xi'an Shaanxi710072 China Key Laboratory of Modern Teaching Technology School of Computer Science Shaanxi Normal University Xi'an Shaanxi710062 China

There have some problems caused by selection of improper parameters when LMS, NLMS or RLS algorithms are used to evaluate coefficients of a second-order Volterra filter. We propose a Davidon-Fletcher-Powell-based second-order Volterra filter (DFP-SOVF). The proposed filter is based on a posteriori error assumption and has a variable convergence factor. We give the recursive inverse auto-correlation matrix formulation and present computational complexity analysis. Then applying the proposed DFP-SOVF filter to single step predictions for pure Lorenz chaotic series, prediction results show that the DFP-SOVF filter can guarantee its convergence and stability and there have not divergence problems when using LMS and NLMS algorithms. © Published under licence by IOP Publishing Ltd.

关键词： Inverse problems

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Design and implementation of a novel approach for long-lived particle reconstruction in LHCb experiment at CERN

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computer Physics Communications 2025年

作者： Piotr Kulczycki Grzegorz Gołaszewski Tomasz Szumlak Szymon Łukasik AGH University of Krakow Faculty of Physics and Applied Computer Science Division for Information Technology and Systems Research Polish Academy of Sciences Systems Research Institute Centre of Information Technology for Data Analysis Methods

The subject of this paper is the improvement of the procedure to reconstruct long-lived particles in the LHCb (Large Hadron Collider beauty) experiment, one of the main experiments conducted by the European Organization for Nuclear Research CERN in Geneva. The goal of this procedure is to detect or, in other words, reconstruct long-lived particle tracks, based on observations obtained from measurement modules placed far apart, with a primary focus of eliminating erroneously created tracks, the so-called ghost-tracks. The investigated method is carried out by pairing proper trajectories and two autonomous filtering algorithms that are based on the nonparametric estimation of a distribution density as well as an autoencoder, a neural network designated for unsupervised learning. The values obtained from these two algorithms founded on complementary methodologies, mathematical statistics and computational intelligence, are combined with the t-norm. As a result, the number of ghost-tracks is reduced threefold when compared with the method primarily used. To evaluate the results of the designed procedure, a measure of the reconstruction quality, without the information whether a given track is real or only a ghost, is additionally created and effectively applied. Illustrative interpretations make it easier to potentially employ the method elaborated here to research tasks of similar conditions.

关键词： data analysis LHCb experiment long-lived particle ghost-track elimination computational intelligence numerical algorithm

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Physiotherapists’ knowledge, attitude and practice of clinical prediction rules in low-back pain

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Bulletin of Faculty of Physical Therapy 2024年第1期29卷 1-8页

作者： Mbada, Chidozie Emmanuel Afolabi, Victor Adeboye Oghumu, Saturday N. Gebrye, Tadesse Ademoyegun, Adekola Adje, Mishael Karstens, Sven Fatoye, Francis Department of Health Professions Faculty of Health and Education Manchester Metropolitan University Manchester UK Department of Medical Rehabilitation College of Health Sciences Obafemi Awolowo University Ile-Ife Nigeria Department of Physiotherapy Faculty of Allied Medical Sciences College of Medical Sciences University of Calabar Calabar Nigeria Department of Physiotherapy Osun State University Teaching Hospital Osogbo Nigeria Therapeutic Sciences Department of Computer Science Trier University of Applied Sciences Therapeutic Sciences Schneidershof Trier Germany LUNEX International University of Health Differdange Luxembourg

Clinical prediction rules (CPRs) are mathematical tools that are intended to guide clinicians in clinical decision making or predict a future outcome, but they seem rather unknown, under-utilized, or avoided by clinicians. This study aimed to assess knowledge, attitude, and practice of CPRs in low-back pain (LBP) among physiotherapists. A cross-sectional study involving 45 consenting specialist musculoskeletal physiotherapists from three public-funded teaching hospitals in Nigeria was carried out. An adapted validated questionnaire on facilitators and barriers to CPRs utilization, and a socio-demographic proforma were used to collect data. Descriptive and inferential statistics were employed to analyze data. Alpha level was set at p < 0.05. Respondents were mostly males (71.1%), married (64.4%) and first-degree holders (55.6%). Twenty-eight (62.2%) of the respondents had above-average knowledge of CPRs in LBP. Rates for positive attitude towards, and utilization of CPRs were 37.8% and 15.6%. Knowledge and attitude about CPRs in LBP were not significantly influenced by socio-demographic factors (p > 0.05). However, there was a significant association between the utilization of CPRs and years of experience (χ2 = 10.339 p = 0.016). Most Nigerian physiotherapists had above-average knowledge, but a negative attitude and low utilization of CPRs in LBP. Clinicians’ years of clinical experience influence the usage of CPR. There is a need to incorporate training in CPRs into undergraduate and continuous professional development programmes.

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Particle Swarm Optimization and L´evy Flight integration

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Procedia computer science 2021年 192卷 4658-4671页

作者： Joanna Kołodziejczyk Yuliia Tarasenko Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Żołnierska 49 71-210 Szczecin Poland

Particle Swarm Optimization (PSO) is a well-known and popular stochastic optimization method. The Lévy Flight (LF) properties were used to improve the canonical PSO known as premature convergence. The Lévy Flight was applied to change each particle walk on the fitness landscape. We analyze the literature modifications that concluded that Levy flight improved the PSO providing better search space exploration. Based on this conclusion, we propose new approaches to integrate Lévy Flight with PSO by changing initial points in the search space and learning strategies as inertia and constriction coefficients. We use seven standard test functions for an experimental evaluation and scores based on ranking to compare PSO variants. The ranked benchmarks were average performance, standard deviation, and best and worst found solutions obtained from multiple trials. The main contributions are a systematic overview of LF modifications applied in PSO and three new LF applications in canonical PSO procedure. The new approaches are swarm initialization based on LF, lower dimension LF inertia coefficient, and LF-based constriction factor. Another contribution is numerical evaluations on various benchmark functions with diverse characteristics. Two of the proposed modifications performed better or equal, and the third was only 2% worse than the best canonical PSO from the trial.

关键词： Particle Swarm Optimization Lévy Flight stochastic optimization

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Recurrence in dense-time AMS assertions

arXiv

引用

arXiv 2020年

作者： Sanyal, Sayandeep da Costa, Antonio Anastasio Bruto Dasgupta, Pallab Formal Methods Laboratory Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India

The notion of recurrence over continuous or dense time, as required for expressing Analog and Mixed-Signal (AMS) behaviours, is fundamentally different from what is offered by the recurrence operators of SystemVerilog Assertions (SVA). This article introduces the formal semantics of recurrence over dense time and provides a methodology for the runtime verification of such properties using interval arithmetic. Our property language extends SVA with dense real-time intervals and predicates containing real-valued signals. We provide a tool kit which interfaces with off-the-shelf EDA tools through standard VPI. Copyright © 2020, The Authors. All rights reserved.

关键词： Semantics

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