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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Stanisic, Dusan Antic, Marija Kenjic, Dusan Bilac, Luka University of Novi Sad Faculty of Technical Sciences Department of Computing and Control Engineering Novi Sad Serbia

ISBN: (纸本)9798350347722

In recent years, manufacturers are working parallel in developing and integrating two in-vehicle systems, an Advanced Driver Assistance System (ADAS) and In-Vehicle Infotainment (IVI). ADAS's purpose is to increase safety and aid the driver while the vehicle is in motion, by using various sensors to perceive the vehicle surrounding or the driver's errors and respond accordingly. Consumer applications in the IVI domain would significantly benefit from accessing such vehicle-specific data. Unfortunately, due to active vehicle system architecture requirements, the IVI domain cannot achieve communication with the ADAS by following traditional signal-oriented mechanisms. In addition, Android paved its way into the IVI domain as the most common Operating System because of its high flexibility and customization, but without being adapted for communication with ADAS. This paper offers a solution for enabling Android applications to access ADAS data via Java services. Data is procured over GENIVI company's SOME/IP-based communication middleware, integrated within the services. Communication performance is measured, evaluated, and limitations are identified. © 2023 IEEE.

关键词： Advanced driver assistance systems

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A novel fractional physics-informed neural networks method for solving the time-fractional Huxley equation

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Neural computing and Applications 2024年第30期36卷 19097-19119页

作者： Shi, Jieyu Yang, Xiaozhong Liu, Xinlong School of Control and Computer Engineering North China Electric Power University Beijing102206 China Institute of Information and Computing School of Mathematics and Physics North China Electric Power University Beijing102206 China

The neural network methods in solving differential equations have significant research importance and promising application prospects. Aimed at the time-fractional Huxley (TFH) equation, we propose a novel fractional physics-informed neural networks (fPINNs) method. By integrating the physical information of the TFH equation into neural networks, the fPINNs are trained as a precise approximation model for solving the TFH equation. The fPINNs method involves calculating the Caputo fractional derivative using the L1 formula and estimating the integer-order derivative through the chain rule. The Adam algorithm is employed to optimize two kinds of loss functions constructed by hard and soft constraints, respectively. Through an analysis of the impact of fPINNs parameters on training results, we identify the optimal parameter configuration for solving both one-dimensional and two-dimensional (2D) TFH equations. Numerical examples validate the efficiency and robustness of the fPINNs method in solving TFH equations. Furthermore, numerical simulation of the 2D TFH problem demonstrates the method’s practical applicability to engineering problem. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Numerical methods

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Predicting Students’ Final Exam Scores Based on Their Regularity of Engagement with Pre-Class Activities in a Flipped Classroom 16

Predicting Students’ Final Exam Scores Based on Their Regul...

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16th International Conference on Computer Supported Education, CSEDU 2024

作者： Francišković, Teodor Sakal Anđelić, Ana Slivka, Jelena Luburić, Nikola Kovačević, Aleksandar Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad Trg Dositeja Obradovića 6 Novi Sad Serbia

ISBN: (纸本)9789897586972

Flipped Classroom (FC) is an active learning design requiring the students to engage in pre-class learning activities to prepare for face-to-face sessions. Identifying FC learning behaviors that lead to academic success remains a challenge. This paper addresses this challenge by conducting an empirical study in an undergraduate software engineering course employing the FC model. The empirical study draws on the data from an intelligent tutoring system that captured the learning traces of students performing pre-class activities. These traces provided indicators of students’ regularity of engagement, which were then matched to their final exam scores. Regression models were trained to predict final exam scores based on the regularity of engagement indicators. Students were clustered based on their regularity of engagement indicators to uncover actionable feedback for future course iterations. The case study confirms the generalizability of earlier findings that the regularity of engagement is vital for student performance and that course-specific predictors significantly impact the models’ prediction performance. Copyright © 2024 by Paper published under CC license (CC BY-NC-ND 4.0)

关键词： Students

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Generating Adversarial Patterns in Facial Recognition with Visual Camouflage

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Journal of Shanghai Jiaotong University (Science) 2024年 1-12页

作者： Bao, Qirui Mei, Haiyang Wei, Huilin Lü, Zheng Wang, Yuxin Yang, Xin Key Laboratory of Social Computing and Cognitive Intelligence of Ministry of Education School of Control Science and EngineeringSchool of Computer Science and Technology Dalian University of Technology Liaoning Dalian116024 China Systems Engineering Institute Academy of Military Sciences Beijing100141 China

Deep neural networks, especially face recognition models, have been shown to be vulnerable to adversarial examples. However, existing attack methods for face recognition systems either cannot attack black-box models, are not universal, have cumbersome deployment processes, or lack camouflage and are easily detected by the human eye. In this paper, we propose an adversarial pattern generation method for face recognition and achieve universal black-box attacks by pasting the pattern on the frame of goggles. To achieve visual camouflage, we use a generative adversarial network (GAN). The scale of the generative network of GAN is increased to balance the performance conflict between concealment and adversarial behavior, the perceptual loss function based on VGG19 is used to constrain the color style and enhance GAN’s learning ability, and the fine-grained meta-learning adversarial attack strategy is used to carry out black-box attacks. Sufficient visualization results demonstrate that compared with existing methods, the proposed method can generate samples with camouflage and adversarial characteristics. Meanwhile, extensive quantitative experiments show that the generated samples have a high attack success rate against black-box models. © 2023, Shanghai Jiao Tong University.

关键词： Face recognition

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Unit Test Generation Multi-Agent AI System for Enhancing Software Documentation and Code Coverage 32

Unit Test Generation Multi-Agent AI System for Enhancing Sof...

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32nd Telecommunications Forum, TELFOR 2024

作者： Stojanovic, Dimitrije Pavkovic, Bogdan Cetic, Nenad Krunic, Momcilo Vidakovic, Luka University of Novi Sad Faculty of Technical Sciences Departmant of Computing and Control Engineering Novi Sad Serbia LabSoft Novi Sad Serbia

ISBN: (纸本)9798350391053

Software development necessitates a robust testing plan though test development can be laborious and nonappealing task. We explore the utilization of the application artificial intelligence agents for generating and executing unit tests, enhancing the 'Mostly Basic Python Problems' dataset. We employ behavior-driven development within a three-agent system to generate user stories and unit tests. Empirical results indicate improvements in branch coverage, illustrating the effective utilization of large language models in software testing and development processes. © 2024 IEEE.

关键词： Software testing

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Detection of Hyperbolic Reflections on Real GPR Data Using YOLO Model Trained with Synthetic Data 47

Detection of Hyperbolic Reflections on Real GPR Data Using Y...

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47th International Conference on Telecommunications and Signal Processing, TSP 2024

作者： Bugarinović, Željko Gavrilović, Milan Ristić, Aleksandar Bugarinović, Milka Šarkanović Radulović, Aleksandra Govedarica, Miro University of Novi Sad Faculty of Technical Sciences Department for Computing and Control Engineering Trg Dositeja Obradovića 6 Novi Sad Serbia

ISBN: (纸本)9798350365597

This paper analyzes the application of the YOLO algorithm to automatically recognize hyperbolic reflections on radargrams. A specific shape of hyperbolic reflection on radargrams occurs with objects of circular cross-section that are scanned perpendicular to their axis, such as underground pipes. Requirements for processing a large number of radargrams are increasingly being imposed in practice. Therefore, the development of algorithms for the automated finding of hyperbolic reflections on radargrams has been intensified in recent years. Conventional methods take a lot of time and are more susceptible to noise than algorithms based on deep learning. One of such algorithms is also applied in this paper. The model was trained with 2000 synthetic radargrams generated using gprMax software. The basic idea is reflected in the analysis of the successful detection of hyperbolic reflections on real radargrams using a model trained only with synthetic radargrams. Experimental results show a high level of success. © 2024 IEEE.

关键词： Ground penetrating radar systems

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4K Video Coding Efficiency in UAV Systems 45

4K Video Coding Efficiency in UAV Systems

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Benjak, J. Hofman, D. Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Zagreb Croatia

ISBN: (纸本)9789532331035

With increasing requirements for high quality, low bandwidth video transmission systems, comes a demand for more ad hoc video encoders. Unmanned Aerial Vehicles (UAVs), or just drones, have recently grown in popularity and use. Therefore, in this paper, we provide an efficiency comparison of the two most popular video encoders in a First-person view (FPV) drone piloting system. We film all the test sequences ourselves, using a drone with an attached 4K camera. Each sequence captures a scene with different spatiotemporal characteristics. Because video encoders are sensitive to video content or scene complexity, instead of doing a comprehensive comparison of all sequences at once, we first classify all the sequences into four groups. Finally, we examine the compression efficiency by varying the parameters with the highest impact on encoder operation. The quality of compressed footage is determined using four objective video quality measures. Due to high computational complexity, tests were performed on several nodes of a supercomputer and the relative encoding times were also considered. © 2022 Croatian Society MIPRO.

关键词： Antennas

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Smooth Motion Planning of an Omnidirectional Mobile Robot in Dynamic Environments

Smooth Motion Planning of an Omnidirectional Mobile Robot in...

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2022 International Conference on Electrical, Computer, Communications and Mechatronics engineering, ICECCME 2022

作者： Šelek, Ana Seder, Marija Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

In this paper, a real-time smooth motion planning method for a four mecanum wheeled omnidirectional mobile robot in dynamic environments that generates a smooth collision-free trajectory is proposed. The method employs a graph-search-based path planning algorithm and a smoothing technique based on clothoids. It is suitable for real-time operation due to its computational simplicity and allows fast path replanning in case the robot encounters unknown and dynamic obstacles. Such a path is feasible for holonomic mobile robots since it does not contain sharp turns so the energy consumption is reduced. Our method is compared to the reactive model predictive control scheme in simulations. The comparison showed advantages of the proposed method in the reduced task execution time, path length, cumulative replanning time, and smooth velocity profile. © 2022 IEEE.

关键词： Motion planning

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BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization 26

BiERL: A Meta Evolutionary Reinforcement Learning Framework ...

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26th European Conference on Artificial Intelligence, ECAI 2023

作者： Wang, Junyi Zhu, Yuanyang Wang, Zhi Zheng, Yan Hao, Jianye Chen, Chunlin Department of Control Science and Intelligent Engineering Nanjing University China College of Intelligence and Computing Tianjin University China

ISBN: (纸本)9781643684369

Evolutionary reinforcement learning (ERL) algorithms recently raise attention in tackling complex reinforcement learning (RL) problems due to high parallelism, while they are prone to insufficient exploration or model collapse without carefully tuning hyperparameters (aka meta-parameters). In the paper, we propose a general meta ERL framework via bilevel optimization (BiERL) to jointly update hyperparameters in parallel to training the ERL model within a single agent, which relieves the need for prior domain knowledge or costly optimization procedure before model deployment. We design an elegant meta-level architecture that embeds the inner-level's evolving experience into an informative population representation and introduce a simple and feasible evaluation of the meta-level fitness function to facilitate learning efficiency. We perform extensive experiments in MuJoCo and Box2D tasks to verify that as a general framework, BiERL outperforms various baselines and consistently improves the learning performance for a diversity of ERL algorithms. © 2023 The Authors.

关键词： Reinforcement learning

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Magnetic Flux Servoing for Precise Localization Based on Gradient Tensor Contractions 19

Magnetic Flux Servoing for Precise Localization Based on Gra...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Martinovic, Dean Orsag, Matko University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Zagreb10000 Croatia

ISBN: (纸本)9798350320695

This paper focuses on bridge inspections performed by intelligent unmanned aerial vehicles (UAV). For this, small data loggers are placed by the UAVs at the bridge, which have to be removed later. In our previous work we presented the magnetic localization method SRIOD, which not only detects the center of the data logger but also its orientation. In this work we proof SRIOD in a real application and let a robotic arm locate a magnetic target. The hardware involved is presented including the control strategy for the robot. The motions of the robot and the magnetic target are captured with 12 Optitrack cameras in order to validate the localization quality. © 2023 IEEE.

关键词： Antennas

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