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2022 International Conference on Information and Knowledge Management Workshops, CIKM-WS 2022

作者： Giobergia, Flavio Department of Control and Computer Engineering Politecnico di Torino Turin Italy

Much like other learning-based models, recommender systems can be affected by biases in the training data. While typical evaluation metrics (e.g. hit rate) are not concerned with them, some categories of final users are heavily affected by these biases. In this work, we propose using multiple triplet losses terms to extract meaningful and robust representations of users and items. We empirically evaluate the soundness of such representations through several "bias-aware" evaluation metrics, as well as in terms of stability to changes in the training set and agreement of the predictions variance w.r.t. that of each user. © 2022 Copyright for this paper by its authors.

关键词： Recommender systems

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Robust Car-Following control of Connected and Autonomous Vehicles: A Stochastic Model Predictive control Approach

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-14页

作者： Zhang, Peiyu Tian, Daxin Zhou, Jianshan Chang, Mai Duan, Xuting Zhao, Dezong Cao, Dongpu Leung, Vicor C.M. Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China James Watt School of Engineering University of Glasgow Glasgow U.K Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Computer Science and Software Engineering Shenzhen University Shenzhen China

Vehicle platooning has attracted growing attention for its potential to enhance traffic capacity and road safety. This paper proposes an innovative distributed Stochastic Model Predictive control (SMPC) for a vehicle platoon system to enhance the robustness and safety of the vehicles in uncertain traffic environments. In particular, considering the similarity between the acceleration or deceleration behaviour of neighbouring vehicles and the spring-scale properties, we use a two-mass spring system for the first time to construct an uncertain dynamic model of a formation system. In the presence of uncertain perturbations with known distributional attributes (expectation, variance), we propose an objective function in the form of expectation along with probabilistic chance constraints. Subsequently, a state feedback control mechanism is devised accordingly. Under the cumulative probability distribution function of stochastic perturbations, we theoretically derive a computationally tractable equivalent of the SMPC model. Finally, simulation experiments are designed to validate the control performance of the SMPC platoon controllers, along with an analysis of the stability performance under varying probabilities. The experimental findings demonstrate that the model can be efficiently solved in real-time with appropriately chosen prediction horizon lengths, ensuring robust and safe longitudinal vehicle formation control. IEEE

关键词： Random processes

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A Compaction Method for STLs for GPU in-field test

A Compaction Method for STLs for GPU in-field test

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2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022

作者： Guerrero-Balaguera, Juan-David Rodriguez Condia, Josie E. Reorda, Matteo Sonza Department of Control and Computer Engineering Politecnico di Torino Torino Italy

ISBN: (纸本)9783981926361

Nowadays, Graphics Processing Units (GPUs) are effective platforms for implementing complex algorithms (e.g., for Artificial Intelligence) in different domains (e.g., automotive and robotics), where massive parallelism and high computational effort are required. In some domains, strict safety-critical requirements exist, mandating the adoption of mechanisms to detect faults during the operational phases of a device. An effective test solution is based on Self-Test Libraries (STLs) aiming at testing devices functionally. This solution is frequently adopted for CPUs, but can also be used with GPUs. Nevertheless, the in-field constraints restrict the size and duration of acceptable STLs. This work proposes a method to automatically compact the test programs of a given STL targeting GPUs. The proposed method combines a multi-level abstraction analysis resorting to logic simulation to extract the microarchitectural operations triggered by the test program and the information about the thread-level activity of each instruction and to fault simulation to know its ability to propagate faults to an observable point. The main advantage of the proposed method is that it requires a single fault simulation to perform the compaction. The effectiveness of the proposed approach was evaluated, resorting to several test programs developed for an open-source GPU model (FlexGripPlus) compatible with NVIDIA GPUs. The results show that the method can compact test programs by up to 98.64% in code size and by up to 98.42% in terms of duration, with minimum effects on the achieved fault coverage. © 2022 EDAA.

关键词： Graphics processing unit

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Fractional Order Sliding Mode control with Fuzzy Parameter Tuning Applied to a SCARA Robot

Fractional Order Sliding Mode Control with Fuzzy Parameter T...

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2024 IEEE International Multi-Conference on Smart Systems and Green Process, IMC-SSGP 2024

作者： Znidi, Aicha Abdelhedi, Fatma Nouri, Ahmed Said Derbel, Nabil National Engineering School of Gabes University of Gabes Lab: Numerical Control of Industrial Processes Tunisia College of Engineering King Abdulaziz University Department of Electrical and Computer Engineering Jeddah22254 Saudi Arabia University of Sfax National Engineering School of Sfax Control & Energy Management Laboratory Tunisia

ISBN: (纸本)9798350378382

This paper presents the application of Fractional Order Sliding Mode control (FO-SMC) in order to achieve a robust motion trajectory regulation in dynamic robot systems. The proposed control strategy benefits of both advantages of fractional calculus and sliding mode control to upgrade the robustness and the performances of the controller. Moreover, the paper proposes to use a fuzzy tuning of sliding mode controller in order to satisfy the capabilities of the actuators. The stability of the closed loop system has been demonstrated using the Lyapunov theory. Simulation results demonstrate the efficiency of the proposed method achieving precise trajectory tracking and robust performances, it has been shown that fuzzy tuning of the sliding function parameters significantly reduces control variable peaks, making the control more suitable for actuator application. © 2024 IEEE.

关键词： Sliding mode control

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R-CONV: An Analytical Approach for Efficient Data Reconstruction via Convolutional Gradients 25th

R-CONV: An Analytical Approach for Efficient Data Reconstru...

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25th International Conference on Web Information Systems engineering, WISE 2024

作者： Eltaras, Tamer Ahmed Malluhi, Qutaibah Savino, Alessandro Carlo, Stefano Di Qayyum, Adnan Politecnico Di Torino Control and Computer Engineering Department Turin10129 Italy Qatar University Doha Qatar Information Technology University of the Punjab Lahore Pakistan

ISBN: (纸本)9789819605750

In the effort to learn from extensive collections of distributed data, federated learning has emerged as a promising approach for preserving privacy by using a gradient-sharing mechanism instead of exchanging raw data. However, recent studies show that private training data can be leaked through many gradient attacks. While previous analytical-based attacks have successfully reconstructed input data from fully connected layers, their effectiveness diminishes when applied to convolutional layers. This paper introduces an advanced data leakage method to efficiently exploit convolutional layers’ gradients. We present a surprising finding: even with non-fully invertible activation functions, such as ReLU, we can analytically reconstruct training samples from the gradients. To the best of our knowledge, this is the first analytical approach that successfully reconstructs convolutional layer inputs directly from the gradients, bypassing the need to reconstruct layers’ outputs. Prior research has mainly concentrated on the weight constraints of convolution layers, overlooking the significance of gradient constraints. Our findings demonstrate that existing analytical methods used to estimate the risk of gradient attacks lack accuracy. In some layers, attacks can be launched with less than 5 % of the reported constraints. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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EQUILIBRIA AND STABILITY OF ONE MESSENGER RNA AND TWO MICRO RNA DYNAMICS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2022年第4期84卷 3-8页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

In this paper we study an ODE model on the microRNA-mRNA dynamics. We prove the existence of two equilibrium points (one with strictly positive compo-nents) and obtain a biologically consistent, sufficient asymptotic stability condition for the strictly positive equilibrium. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Asymptotic stability

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Performance Comparison of Kalman Filter and Extended Kalman Filter for Human Tracking and Prediction with Particle Swarm Optimisation 1

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Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2022

作者： Ajasa, Abiodun Afis Wahyudi, Nawawi Sophan Department of Control and Mechatronics Engineering School of Electrical Engineering Universiti Teknologi Malaysia Johor Malaysia Department of Electronics and Computer Engineering Lagos State University Epe Campus Lagos Nigeria

ISBN: (数字)9789811987038

ISBN: (纸本)9789811987021

In the past two decades, object tracking has progressively advanced in computer vision and image processing. Tracking is a collection of algorithms that detect and track objects in a video sequence. This has resulted in a broad variety of applications, including surveillance, biometric identification or biological imaging, human-machine interactions, traffic control, and intelligent vehicles, all of which have benefited from tracking applications. This paper presents an IoT-based human tracking system that employs the Kalman filter (KF) and extended Kalman filter (EKF) algorithms. However, the performance of the filters is impacted by noise. Therefore, instead of manually tuning the KF and EKF’s process noise and measurement error, particle swarm optimisation (PSO) is utilised to optimise them. Four 2-dimensional models (namely conventional KF and EKF, optimised KF-PSO, and EKF-PSO) were developed and evaluated using ten distinct human sets of data containing 100 samples each. The object’s tracked positions are estimated in horizontal and vertical directions. Accuracy analysis was used to compare the four models’ quality performance. With an average mean square error of 5.99 mm (or 0.599%), the EKF-PSO model outperformed the conventional EKF model, which had an error of 7.18 mm (or 0.718%). A 17.2 mm (or 1.72%) error was found in the KF-PSO model. The last one is the traditional KF model, yielding an error of 22.4 mm (or 2.24%). As a result of its higher accuracy, the EKF-PSO model outperforms the other three models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Secure-by-Construction Synthesis for control Systems

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IEEE Transactions on Automatic control 2025年第6期70卷 4170-4177页

作者： Zhong, Bingzhuo Liu, Siyuan Caccamo, Marco Zamani, Majid Thrust of Artificial Intelligence Information Hub The Thrust of Intelligent Transportation System Hub China KTH Royal Institute of Technology Division of Decision and Control Systems Stockholm Sweden Technical University of Munich TUM School of Engineering and Design Germany University of Colorado Boulder Department of Computer Science United States Ludwig Maximilian University Department of Computer Science Munich Germany

In this note, we present the synthesis of secure-by-construction controllers that address safety and security properties simultaneously in cyber-physical systems. Our focus is on studying a specific security property called opacity, which characterizes the system's ability to maintain plausible deniability of its secret behavior in the presence of an intruder. These controllers are synthesized based on a concept of so-called (augmented) control barrier functions. We propose conditions that facilitate the construction of the desired (augmented) control barrier functions and their corresponding secure-by-construction controllers. To compute these functions, we propose an iterative scheme that leverages iterative sum-of-square programming techniques. This approach enables efficient computation of these functions, particularly for polynomial systems. Finally, we validate the effectiveness of our results through a case study of a vehicle. © 1963-2012 IEEE.

关键词： Iterative methods

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RECLAIM: Reverse engineering Classification Metrics 5

RECLAIM: Reverse Engineering Classification Metrics

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5th IEEE International Conference on Artificial Intelligence and Knowledge engineering, AIKE 2022

作者： Giobergia, Flavio Baralis, Elena Department of Control and Computer Engineering Politecnico di Torino Turin Italy

ISBN: (数字)9781665471206

ISBN: (纸本)9781665471206

Being able to compare machine learning models in terms of performance is a fundamental part of improving the state of the art in a field. However, there is a risk of getting locked into only using a few possibly not ideal performance metrics, only for comparability with earlier works. In this work, we explore the possibility of reconstructing new classification metrics starting from what little information may be available in existing works. We propose three approaches to reconstruct confusion matrices and, as a consequence, other classification metrics. We empirically verify the quality of the reconstructions, drawing conclusions on the usefulness that various classification metrics have for the reconstruction task. © 2022 IEEE.

关键词： Classification (of information)

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Dipper Throated Optimization for Detecting Black-Hole Attacks inMANETs

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computers, Materials & Continua 2023年第1期74卷 1905-1921页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security and privacy,mobile ad-hoc network(MANET)continues to be in demand for additional debate and *** more MANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,MANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost MANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-MLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

关键词： Black-hole attack mobile ad-hoc network optimization dipper throated optimization

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