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3rd International Conference on Image Processing and Robotics, ICIPRoB 2024

作者： Mehzabin, Kazi Mayesha Islam, Md. Zahidul Nur, Md. Ashaduzzaman Shidujaman, Mohammad Samani, Hooman Mi, Haipeng Independent University Bangladesh RIoT Center and Department of Computer Science and Engineering Dhaka Bangladesh Creative Computing Institute University of the Arts London London United Kingdom Tsinghua University Media and Interaction Lab Academy of Arts and Design Beijing China

ISBN: (纸本)9798350374766

Roopkotha is a storytelling robot that seamlessly combines traditional storytelling methods and technology, creating a captivating robot storyteller. We are creating a special prototype in the world of robots that tells stories in a way that is easy to understand and enjoy. In this era of technological advancement, Roopkotha combines voice recognition with Bangla Language processing, emotion recognition, human behavior detection. Roopkotha aims to revolutionize the way stories are told and engage with users on a deep emotional level. Furthermore, Roopkotha is equipped with advanced facial expressions and emotion recognition technology. The emotion recognition feature helps the robot to have a profound connection with the users. © 2024 IEEE.

关键词： Emotion Recognition

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Machine Learning Algorithms for the Detection of Threats in IoT Healthcare 1

Machine Learning Algorithms for the Detection of Threats in ...

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1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Arun, V. Shenbagavalli, P. Sridhar, T. Manivannan, B. Mahesh, T.R. Anitha, K. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Kattankulathur India Karunya Institute of Technology and Sciences Division of Digital Sciences India Alliance University Alliance College of Engineering and Design Bangalore India Computer Science and Engineering Namakkal India Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India Csi College of Engineering Department of Information Technology Tamilnadu Ooty India

ISBN: (纸本)9798350359756

IoT (Internet of Things) technology enables the connectivity and communication of healthcare-related equipment, medical devices, and sensors. This connectivity enables better monitoring, data collecting, and analysis, which leads to better patient outcomes and more effective healthcare delivery. However, with the rising use of linked devices, it is critical to detect and prevent Cyberattacks in order to secure sensitive patient information. In order to tackle this problem, the article delves into the application of machine learning methods like Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Logistic Regression (LR), Random Forest (RF), and Naive Bayes (NB), These algorithms were evaluated using the WUSTL EHMS2020 dataset and demonstrated the highest level of accuracy. © 2023 IEEE.

关键词： Internet of things

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Future intelligent autonomous robots, ethical by design. Learning from autonomous cars ethics

arXiv

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arXiv 2021年

作者： Dodig-Crnknovic, Gordana Holstein, Tobias Pelliccione, Patrizio Interaction Design Unit Department of Computer Science and Engineering Chalmers | University of Technology Gothenburg Sweden Division of Computer Science and Software Engineering School of Innovation Design and Engineering Mälardalen University Västerås Sweden Software Engineering Division Department of Computer Science and Engineering Chalmers | University of Gothenburg Gothenburg Sweden Department of Information Engineering Computer Science and Mathematics University of L'Aquila L'Aquila Italy

Development of the intelligent autonomous robot technology presupposes its anticipated beneficial effect on the individuals and societies. In the case of such disruptive emergent technology, not only questions of how to build, but also why to build and with what consequences are important. Thus, questions of values, good and bad, right and wrong, must be addressed in the context of the development, implementation, testing, use and disposal of technology. The field of ethics of intelligent autonomous robotic cars is a good example of research with actionable practical value, where a variety of stakeholders, including the legal system and other societal and governmental actors, as well as companies and businesses, collaborate bringing about shared view of ethics and societal aspects of technology. It could be used as a starting platform for the approaches to intelligent autonomous robot development considering human-machine interfaces in different phases of the life cycle of technology. Drawing from our work on ethics of autonomous intelligent robocars, and the existing literature on ethics of robotics, our contribution consists of a set of values and ethical principles with identified challenges and proposed approaches for meeting them. This may help stakeholders in the field of intelligent autonomous robotics to connect ethical principles with their applications. Our recommendations of ethical requirements for autonomous cars can be used for other types of intelligent autonomous robots, with the caveat for social robots that require more research regarding interactions with the users. We emphasize that existing ethical frameworks need to be applied in a context-sensitive way, by assessments in interdisciplinary, multi-competent teams through multi-criteria analysis. Furthermore, we argue for the need of a continuous development of ethical principles, guidelines, and regulations, informed by the progress of technologies and involving relevant stakeholders. Copyright

关键词： Intelligent robots

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Estimation of particle size distributions in solid/liquid suspensions based on wide-band ultrasound attenuation measurements

Estimation of particle size distributions in solid/liquid su...

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IEEE Symposium (IUS) Ultrasonics

作者： Johan E. Carlson Division of Systems and Interaction Department of Computer Science and Electrical Engineering Luleå University of Technology Lulea Sweden

This paper demonstrates a strategy for rapid estimation of particle size distributions based on wide-band ultrasound attenuation measurement in solid/liquid suspensions. The excess attenuation due to the presence of particle is first measured as a function of frequency, in a suspension of known particle mass fraction. A model of this attenuation that incorporates the dependency of ultrasound frequency, particle mass fraction, and particle size distribution is then required. An algorithm is then presented that estimates the parameters of the underlying model, thus obtaining an estimate of the particle size distribution. The algorithm is evaluated with numerical simulations as well as measurement on suspensions of Dolomite particles. The results show that the estimated particle size distribution agrees with what is to be expected from the mechanical sieving used in preparation of the samples.

关键词： Attenuation Attenuation measurement Suspensions Mathematical model Particle measurements Ultrasonic variables measurement Atmospheric measurements

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Multiple Cooperative Bilateral Teleoperation with Time-Varying Delay

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SICE Journal of Control, Measurement, and System Integration 2011年第2期4卷 89-96页

作者： Nam Duc Do Yusuke Yamashina Toru Namerikawa Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology Kanazawa University Department of System Design Engineering Keio University

This paper deals with a passive-decomposition based control of bilateral teleoperation between a single master robot and multiple cooperative slave robots with time varying delay. First, we decompose the dynamics of multiple slave robots into two decoupled dynamics by using the passive-decomposition: the shape-system describing dynamics of the cooperative works and the locked-system representing the overall behavior of the multiple slave robots. Second, we propose a PD control method for bilateral teleoperation to guarantee asymptotic stability of the system with time varying delay. Finally, experimental results show the effectiveness of the proposed teleoperation.

关键词： bilateral teleoperation SMMS time-varying delay Lyapunov stability

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Broken Rotor Bar Fault Detection Based on Uncertainty Ellipsoidal Intersection for Three Phase Induction Motors

Broken Rotor Bar Fault Detection Based on Uncertainty Ellips...

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Mediterranean Conference on Control & Automation

作者： Mohammed Obaid Mustafa George Nikolakopoulos Thomas Gustafsson Control Engineering Group Division of Systems and interaction Department of Computer Science Electrical and Space Engineering Lulea University of Technology

ISBN: (纸本)9781479909964

In this article a fault detection scheme for broken rotor bar fault detection in three phase induction motor is presented. In the proposed scheme the induction motor has been transformed in the equivalent two phase (q - d) space, while the modeling of the faulty case has been also formulated. The model has been identified by the utilization of the Set Membership Identification (SMI) algorithm that has the merit of identifying both the parameters of the motor as also providing uncertainty bounds in both the healthy and the faulty cases. Based on the adopted methodology, the uncertainty bounds and the corresponding identified parameters of the induction motor is presented as 3D-ellipsoids, while a novel fast and efficient fault detection scheme has been proposed that is able to track iteratively the ellipsoid centers, the distance among centers, the intersection between the initial and a priori known converged states of the motor and the current ones, before or after the fault occurrence. Detailed analysis of the proposed approach and the fault detection strategy, as also extended simulation results are being presented that prove the efficiency of the suggested scheme.

关键词： Defect detection three-phase induction motor induction motors rotor bar Motor Intersection Crossing THREE-PHASE BREAKS

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Determining Event Ordering in Mobile Ad Hoc Networks

Determining Event Ordering in Mobile Ad Hoc Networks

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International Conference on computer science and Network Technology (ICCSNT)

作者： Wu, Dan Rao, Weixiong Liu, Dawei Sheng, Bin Wang, Yue Network and Telecommunication Division Guangdong Electric Power Design Institute China Joint Research Center in Ubiquitous Computing Macao Polytechnic Institute Macao School of Information Central University of Finance and Economics China Department of Computer Science University of Helsinki Finland Department of Computer Science and Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9781457715846

Determining event ordering has always been a crucial issue in distributed computing. A well known model for describing event ordering is the happened-before relation. However, the traditional happened-before relation model is inadequate to faithfully characterize event ordering in recent emerging mobile ad hoc networks (MANETs), which usually have no fixed supporting infrastructure and may experience dynamic network topology changes. In this paper, we first propose a new relation, called the extended-happened-before relation, to model the ordering of events for a MANET. Then we present an algorithm to assign logical time to events such that the extended-happened-before relation between events can be decided by comparing their timestamps. We finally show how to construct consistent global snapshots in a MANET when the ordering of events can be determined.

关键词： Distributed computing Event ordering Logical time Mobile ad hoc networks

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Analyzing the Behaviour of Tree-Based Neural Networks in Regression Tasks

arXiv

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arXiv 2024年

作者： Samoaa, Peter Farahani, Mehrdad Longa, Antonio Leitner, Philipp Chehreghani, Morteza Haghir Data Science and AI Division Chalmers University of Technology Gothenburg Sweden Interaction Design and Software Engineering Division Chalmers University of Technology Gothenburg Sweden Department of Information Engineering and Computer Science University of Trento Trento Italy

The landscape of deep learning has vastly expanded the frontiers of source code analysis, particularly through the utilization of structural representations such as Abstract Syntax Trees (ASTs). While these methodologies have demonstrated effectiveness in classification tasks, their efficacy in regression applications, such as execution time prediction from source code, remains underexplored. This paper endeavours to decode the behaviour of tree-based neural network models in the context of such regression challenges. We extend the application of established models—tree-based Convolutional Neural Networks (CNNs), Code2Vec, and Transformer-based methods—to predict the execution time of source code by parsing it to an AST. Our comparative analysis reveals that while these models are benchmarks in code representation, they exhibit limitations when tasked with regression. To address these deficiencies, we propose a novel dual-transformer approach that operates on both source code tokens and AST representations, employing cross-attention mechanisms to enhance interpretability between the two domains. Furthermore, we explore the adaptation of Graph Neural Networks (GNNs) to this tree-based problem, theorizing the inherent compatibility due to the graphical nature of ASTs. Empirical evaluations on real-world datasets showcase that our dual-transformer model outperforms all other tree-based neural networks and the GNN-based models. Moreover, our proposed dual transformer demonstrates remarkable adaptability and robust performance across diverse datasets. © 2024, CC BY-NC-SA.

关键词： Regression analysis

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Twiddle-factor-based FFT algorithm with reduced memory access 16

Twiddle-factor-based FFT algorithm with reduced memory acces...

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16th International Parallel and Distributed Processing Symposium, IPDPS 2002

作者： Jiang, Yingtao Zhou, Ting Tang, Yiyan Wang, Yuke Department of Electrical and Computer Engineering University of Nevada Las Vegas Las VegasNV89119 United States ASIC Design Division Gennum Corporation KanadaON Canada Department of Computer Science University of Texas at Dallas RichardsonTX75083 United States

ISBN: (纸本)0769515738

In microprocessor-based systems, memory access is expensive due to longer latency and higher power consumption. In this paper, we present a novel FFT algorithm to reduce the frequency of memory access as well as multiplication operations. For an N-point FFT, we design the FFT with two distinct sections: (1) The first section of the FFT structure computes the butterflies involving twiddle factors WNj(j ≠ 0) through a computation/partitioning scheme similar to the Hoffman coding. In this section, all the butterflies sharing the same twiddle factor will be clustered and computed together. In this way, redundant memory access to load twiddle factors is avoided. (2) In the second section, the remaining (N - 1) butterflies involving the twiddle factor WN0are computed with a register-based breadth first tree traversal algorithm. This novel twiddle factor-based FFT is tested on the TIT MS320C62x digital signal processor. The results show that, for a 32-point FFT, the new algorithm leads to as much as 20% reduction in clock cycles and an average of 30% reduction in memory access than that of the conventional DIF FFT. © 2002 IEEE.

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Stator winding short circuit fault detection based on set membership identification for three phase induction motors

Stator winding short circuit fault detection based on set me...

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Mediterranean Conference on Control and Automation (MED)

作者： Mohammed Obaid Mustafa George Nikolakopoulos Thomas Gustafsson Department of Computer Science Electrical and Space Engineering Division of Systems and interaction Luleå University of Technology Lulea Sweden

In this article a fault detection scheme for stator winding short circuit fault detection in the case of a three phase induction motor is being presented. The three phase motor is being modeled in the equivalent two phase motor (q-d) space, while the modeling of the faulty case is being also formulated. The motor is being identified by the utilization of Set Membership Identification (SMI) that has the merit of identifying both the parameters of the motor as also providing uncertainty safety bounds by calculating orthotopes which bounds the systems parameter vector. Based on the volume and the trend of these orthotopes, rules for identifying the existence of a fault are being presented. If the current values of the identified parameters do not lie inside the safety bounds in the healthy case, but lie in an area that is being defined by the model of the short circuit case, then a fault is being triggered. Detailed analysis of the proposed approach as also extended simulation results are being presented that prove the efficiency of the suggested scheme.

关键词： Stator windings Circuit faults Induction motors Mathematical model Fault detection Rotors

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