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International Workshop on Research and Education in Mechatronics (REM)

作者： Hayat Ait dahmad Hassan Ayad Alfonso García Cerezo Hajar Mousannif Department of Applied Physics Faculty of Sciences and Technics Cadi Ayyad University Marrakech Morocco Department of Systems Engineering and Automation School of industrial Engineering University of Malaga Malaga Spain Department of Informatics Faculty of Sciences Semlalia Cadi Ayyad University Marrakech Morocco

ISBN: (数字)9798331505974

ISBN: (纸本)9798331505981

Agriculture is a vital sector for many countries' economies, but it faces numerous challenges, with weeds being a significant issue. In this study, a deep learning model called YOLOv8-n was implemented on a Raspberry Pi 3B+ equipped with a 1080p resolution camera to detect weeds. The model's capability to identify weeds in real-time was demonstrated using a recorded video. Furthermore, tests conducted with photos taken from a cell phone revealed that the trained model achieved a mean Average Precision at 50 % Intersection over Union (mAP@50) of 0.92, indicating high accuracy. This research underscores the potential of combining deep learning models with cost-effective hardware to enhance agricultural efficiency.

关键词： Deep learning Productivity Accuracy Mechatronics Streaming media Real-time systems Hardware Mobile robots Faces Farming

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Quadratic Regression Model Based Predictive control of PMSM Drives with Field Weakening Operation Capability Constrained to the Linear Modulation Range

Quadratic Regression Model Based Predictive Control of PMSM ...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Kristóf Bándy Péter Stumpf Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. H-1111 Budapest Hungary

Continuous control Set Model Predictive control in power electronics has prospective outlooks, however, due to the computational requirements, these techniques are still underutilized. In the paper, a novel method is discussed that allows the reduction of the complex optimization underlying the predictive control algorithm. However, the optimization is further restricted with a non-linear (circular) constraint, that allows the modulator to remain in the linear modulation region. The paper offers an effective solution to the optimization problem, with simulation results showing the effectiveness of the proposed method.

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A Speech Cryptosystem Using the New Chaotic System with a Capsule-Shaped Equilibrium Curve

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Computers, Materials & Continua 2023年第6期75卷 5987-6006页

作者： Mohamad Afendee Mohamed Talal Bonny Aceng Sambas Sundarapandian Vaidyanathan Wafaa Al Nassan Sen Zhang Khaled Obaideen Mustafa Mamat Mohd Kamal Mohd Nawawi Faculty of Informatics and Computing Universiti Sultan Zainal AbidinMalaysia Department of Computer Engineering University of SharjahSharjah26666UAE Department of Mechanical Engineering Universitas Muhammadiyah TasikmalayaIndonesia Research and Development Centre Vel Tech UniversityAvadiChennaiIndia School of Artificial Intelligence and Automationand Key Laboratory of Image Processingand Intelligent Control of Education Ministry of ChinaHuazhong University of Scienceand TechnologyWuhan430074China Institute of Strategic Industrial Decision Modeling School of Quantitative SciencesUniversiti Utara Malaysia06010UUM SintokKedahMalaysia

In recent years,there are numerous studies on chaotic systems with special equilibrium curves having various shapes such as circle,butterfly,heart and *** paper describes a new 3-D chaotic dynamical system with a capsule-shaped equilibrium *** proposed chaotic system has two quadratic,two cubic and two quartic nonlinear *** is noted that the proposed chaotic system has a hidden attractor since it has an infinite number of equilibrium *** is also established that the proposed chaotic system exhibits multi-stability with two coexisting chaotic attractors for the same parameter values but differential initial states.A detailed bifurcation analysis with respect to variations in the system parameters is portrayed for the new chaotic system with capsule equilibrium *** have shown MATLAB plots to illustrate the capsule equilibrium curve,phase orbits of the new chaotic system,bifurcation diagrams and *** an engineering application,we have proposed a speech cryptosystem with a numerical algorithm,which is based on our novel 3-D chaotic system with a capsule-shaped equilibrium *** proposed speech cryptosystem follows its security evolution and implementation on Field Programmable Gate Array(FPGA)*** results show that the proposed encryption system utilizes 33%of the FPGA,while the maximum clock frequency is 178.28 MHz.

关键词： Chaos chaotic systems hidden attractors multi-stability bifurcation speech cryptosystem FPGA design

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Raman microscopic measurement of materials used on banknotes

Raman microscopic measurement of materials used on banknotes

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Circuits, Systems, Communications and Computers (CSCC), International Conference on

作者： Hana Tomášková Vladimír Vašek Department of electronic and measurements Faculty of Applied informatics Tomas Bata University in Zlin Zlín Czech Republic Department of automation and control engineering Faculty of Applied informatics Tomas Bata University in Zlin Zlín Czech Republic

ISBN: (纸本)9781665481878

The successful verification of the authenticity of banknotes, or the detection of counterfeits, is based on the combination of an effective measuring system and computer technology. In this paper, a modern diagnostic method Raman microscopy together with an exploratory tool for processing and interpreting multi-dimensional datasets, and cluster analysis, are used to study structural differences between paper and orange ink used on genuine banknotes. Six currencies of European countries were selected for this study: Croatian kuna, Czech crown, euro, Great British Pound, Polish zloty, and Swiss franc. Raman microscopy offers non-destructive, rapid analysis without any sample preparation and pre-processing, with the potential to recognize structural modification of substances, together with the advantages of optical microscopy. Cotton fibres, $\text{TiO}_{2}$ in two different modifications, and other additives are successfully identified within the spectra. The patterns found in mathematically processed Raman data, especially between the paper, indicate both, the similarities and differences across the various banknotes, even of the same currency. The results serve as a base of the spectral database for authenticity control of banknotes and classification of the materials used.

关键词： Optical fibers Optical microscopy Databases Statistical analysis Microscopy Process control Ink

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Sensor Node Fault Detection in Wireless Sensor Networks Utilizing Node-Level Diagnostics

Sensor Node Fault Detection in Wireless Sensor Networks Util...

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Reliable Distributed Systems

作者： Dominik Widhalm Karl M. Goeschka Wolfgang Kastner Department Electronic Engineering University of Applied Sciences Technikum Wien Vienna Austria Faculty of Informatics TU Wien Automation Systems Group Vienna Austria

Sensor node faults are a serious threat to wireless sensor networks. They can cause node crashes or lead to the transmission of corrupted data. Especially the latter endangers the quality of subsequent data analyses. Most related fault detection approaches consider the sensor nodes as black boxes. They neglect vital information available on the node level. Consequently, most of these approaches can not distinguish between (i) irregular but correctly sensed data events and (ii) data corruption caused by soft faults. In contrast, our contribution integrates node-level diagnostics with the characteristics of the sensor data. We utilize this node-level diagnostic information to present our fault detection approach. Based on simulations and practical experiments, we show the correctness and efficiency of our approach. The results show that our approach offers a high fault detection rate and can differentiate between events and faults. Furthermore, it consumes a justifiably small overhead of resources and energy.

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A Hybrid Adaptive Filter for Head Tracking in Augmented Reality (AR)-based Flight Simulators

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IEEE Transactions on Computers 2025年

作者： Nwobodo, Onyeka J. Kuaban, Godlove Suila Nkemeni, Valery Wereszczynski, Kamil Cyran, Krzysztof A. Silesian University of Technology Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Gliwice Poland Polish Academy of Sciences Institute of Theoretical and Applied Informatics Poland University of Buea Laboratory of Electrical Engineering and Computing Faculty of Engineering and Technology Buea Cameroon

This paper presents a novel approach for head tracking in augmented reality (AR) flight simulators using an adaptive fusion of Kalman and particle filters. This fusion dynamically balances the strengths of both algorithms, leveraging Kalman filters for computational efficiency and particle filters for handling non-linearities based on real-time factors such as sensor noise and head movement patterns. Our method demonstrates superior tracking precision and reduced latency, making it particularly effective for immersive pilot training in AR-based flight simulations. While focused on flight simulation, our approach holds high potential for broader applications in other AR and virtual reality (VR) environments where precise, real-time head tracking is crucial. These results provide actionable design guidance for developers optimizing tracking systems in environments that require fast response times and high accuracy. Future extensions of this research could explore the generalization of our approach across diverse AR applications, including human-computer interaction (HCI), medical simulations, and gaming. © 1968-2012 IEEE.

关键词： Flight simulators

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Mathematical modeling of flow washing of preserved rawhides 26

Mathematical modeling of flow washing of preserved rawhides

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26th International Conference on Circuits, Systems, Communications and Computers, CSCC 2022

作者： Janacova, Dagmar Mokrejs, Pavel Vasek, Vladimir Drga, Rudolf Dept. of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Nad Stráněmi 4511 Zlín760 01 Czech Republic Dept. of Polymer Engineering Faculty of Technology Tomas Bata University in Zlín Vavrekova 5669 Zlín760 01 Czech Republic Dept. of Security Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Nad Stráněmi 4511 Zlín760 01 Czech Republic

ISBN: (纸本)9781665481861

This paper presents a mathematical model of flow washing with the initial volume of the washing bath of preserved raw hides by salt. The main result of this work is the determination of the concentration field of the preservative in the raw material depending on the washing time and the size of the washing water flow, based on the correct laboratory-determined diffusion coefficient of the preservative using a tortuous factor. The paper points out the usefulness of applying theoretical tools of chemical engineering in areas such as the tanning industry. © 2022 IEEE.

关键词： Washing

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Dynamic Analysis and Circuit Design of a New 3D Highly Chaotic System and its Application to Pseudo Random Number Generator (PRNG) and Image Encryption

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SN Computer Science 2024年第4期5卷 420页

作者： Sambas, Aceng Benkouider, Khaled Kaçar, Sezgin Ceylan, Nurdoğan Vaidyanathan, Sundarapandian Sulaiman, Ibrahim Mohammed Mohamed, Mohamad Afendee Ayob, Ahmad Faisal Mohamad Muni, Sishu Shankar Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Besut Terengganu Kuala 22200 Malaysia Department of Mechanical Engineering Universitas Muhamadiyah Tasikmalaya Tamansari Gobras Tasikmalaya 46196 Indonesia Department of Electronics Faculty of Technology Badji-Mokhtar University B.P. 12 Sidi Ammar Annaba 23000 Algeria Department of Electrical and Electronics Engineering Sakarya University of Applied Sciences Serdivan Sakarya 54050 Turkey Department of Mechanical Engineering Adıyaman University Merkez Adıyaman 02040 Turkey Centre for Control Systems Vel Tech University Tamil Nadu Chennai 600062 India School of Quantitative Science University Utara Malaysia Sintok Kedah Bukit Kayu Hitam 06010 Malaysia Faculty of Education and Arts Sohar University Sohar 311 Oman Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Gong Badak Terengganu Kuala Terengganu 21300 Malaysia Department of Physical Sciences Department of Physical Sciences Indian Institute of Science Education and Research Mohanpur Kolkata 741246 India

In this paper, a new 3D dynamical system with four quadratic nonlinear terms is presented. It is shown that the proposed chaotic system has two saddle-foci, unstable, equilibrium points. Thus, the proposed chaotic system exhibits self-excited chaotic attractors. Dynamical analysis methods such as Lyapunov exponents spectrum, bifurcation diagrams, and phase portraits are used to explore the complex dynamical behaviors of the proposed chaotic system and analyze its basic qualitative properties. It is shown that the maximal Lyapunov exponent (MLE) of the new chaotic system is 7.196, which is a high value. The proposed highly chaotic system exhibits high complexity and it will be very useful for applications in cryptography, encryption and secure communications. The physical feasibility of the proposed system is verified by implementing its electronic circuit schematic using Multisim software. Additionally, a PRNG has been developed using the derived state variables and analyze with NIST-800–22 test. Lastly, we developed a PRNG-based image encryption and employ it for an encryption. The experimental outcomes obtained prove that the 3D chaotic system-based encryption application presented in this section has a very good performance. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Chaos Image encryption Pseudo random number generator

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Assessment of Depression Level Based on Multi-Scale 3D Convolution and Expression Videos 3

Assessment of Depression Level Based on Multi-Scale 3D Convo...

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3rd International Conference on Computer Vision and Pattern Analysis, ICCPA 2023

作者： Cao, Qishuang Gao, Junlong Lv, Zeying Li, Mi Department of Automation Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing100124 China Engineering Research Center of Digital Community Ministry of Education Beijing100124 China

ISBN: (纸本)9781510667563

The automatic diagnosis of depression using deep learning has recently shown significant progress, and 3DCNN has been applied to assessing depression levels from videos. There are two problems to be encountered applying 3DCNN, including insufficient data to train the model and an insufficient diversity of features extracted on a single scale. An approach is presented in this paper to address these issues. Firstly, we augmented the raw data by adding noise and applying rotations to increase the amount of the training set. Secondly, we constructed a 3DCNN to extract more diverse features from multiscales. We evaluated our proposed method on the AVEC 2014. Our approach achieved MAE=7.13 and RMSE=9.16, demonstrating its effectiveness in improving the accuracy of depression assessment compared to existing approaches. © 2023 SPIE.

关键词： Deep learning

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Automated Depression Diagnosis Based on Facial Expression and Deep Dual-Stream Convolutional Neural Networks 3

Automated Depression Diagnosis Based on Facial Expression an...

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3rd International Conference on Computer Vision and Pattern Analysis, ICCPA 2023

作者： Chen, Yangyang Chen, Yingyu Li, Mi Department of Automation Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing100124 China Engineering Research Center of Digital Community Ministry of Education Beijing100124 China

ISBN: (纸本)9781510667563

Depression is a common mental illness characterized by symptoms such as low mood, pessimism, and insomnia. In this study, we developed a deep Dual-Stream CNN to automatically diagnose and classify depression in expression video sequences. The network has two branches that extract static features and dynamic features from static and dynamic expressions, respectively, which are then fused for depression classification. The experiments were performed on the AVEC2014 database, and the results showed that the Dual-Stream model significantly improved the classification performance of depression, achieving an accuracy of 69.08% in depression categorization. © 2023 SPIE.

关键词： Convolutional neural networks

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