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检索条件"机构=Dept. of Automatic Control and Computer Engineering"

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A Feature Fusion based Custom Deep Learning Model for Vehicle Make and Model Recognition

A Feature Fusion based Custom Deep Learning Model for Vehicl...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Triyas Ghosh Soumyajit Gayen Sourajit Maity Daria Valenkova Ram Sarkar Dept. of Computer Sc. and Engineering Jadavpur University Kolkata India Dept. of Automation and Control Processes Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (数字)9798350387568

ISBN: (纸本)9798350387575

Vehicle Make and Model Recognition (VMMR) is a pivotal task in various domains including surveillance, traffic management, and the automotive industry. Despite significant progress in deep learning approaches, existing VMMR systems still struggle to attain robust accuracy, particularly across diverse environments and viewing angles. In this paper, we propose a novel approach based on the fusion of two feature maps extracted from DenseNet201 and ResNet50V2 baseline models, respectively. Additionally, we employ a modified Convolutional Block Attention Module (CBAM) to enhance the resilience and precision of VMMR systems. By incorporating attention mechanisms in the feature extraction process, our modified CBAM model effectively captures both spatial and channel-wise dependencies, facilitating more potent discriminative feature representations. We assess our proposed approach through extensive experiments on two benchmark datasets namely Stanford Cars and CompCarsSV. Achieved accuracies are 93.51% and 99.03%, on Stanford Cars and CompCarsSV, respectively that are better than past methods. The code of our proposed model can be found at: https://***/JUVCSE/featurefusion.

关键词： Deep learning Industries Accuracy Surveillance Traffic control Feature extraction Robustness

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Robotic Arm Dataset (RoAD): A Dataset to Support the Design and Test of Machine Learning-Driven Anomaly Detection in a Production Line

Robotic Arm Dataset (RoAD): A Dataset to Support the Design ...

引用

Annual Conference of Industrial Electronics Society

作者： Alessio Mascolini Sebastiano Gaiardelli Francesco Ponzio Nicola Dall'Ora Enrico Macii Sara Vinco Santa Di Cataldo Franco Fummi Dept. of Control and Computer Engineering Polytechnic of Turin Italy Dept. of Engineering for Innovation Medicine University of Verona Italy Dept. of Regional and Urban Studies and Planning Polytechnic of Turin Italy

The early detection of anomalous behaviors from a production line is a fundamental aspect of Industry 4.0, facilitated by the collection of massive amounts of data enabled by the Industrial Internet of Things. Nonetheless, the design and validation of anomaly detection algorithms, mostly based on sophisticated Machine Learning models, heavily rely on the availability of annotated datasets of realistic anomalies, which is very difficult to obtain in a real production line. To address this problem, we introduce the Robotic Arm Dataset (RoAD), specifically designed to support the development and validation of Multivariate Time Series Anomaly Detection (MTSAD) algorithms. We collect and annotate a large number of data and metadata to characterize the motion and energy consumption of a collaborative robotic arm in a full-fledged production line and annotate a comprehensive set of healthy as well as realistic anomalies scenarios. To prove the significance of RoAD and encourage future developments, we benchmark several state-of-the-art anomaly detection algorithms on our newly introduced dataset, and we freely release it to the scientific community.

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Mutriku's Offshore Wave Power Plant Capture Chamber Model Validation

Mutriku's Offshore Wave Power Plant Capture Chamber Model Va...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Aitor J. Garrido Amparo Villasante Izaskun Garrido Dept. Aut. Control and Syst. Eng. Faculty of Engineering of Bilbao University of the Basque Country (UPV/EHU) Automatic Control Group - ACG. Inst. of Research and Development of Processes - IIDP. Bilbao Spain Automatic Control Group University of the Basque Country (UPV /EHU) Bilbao Spain

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

The strategic vision outlined in the EU Energy Road Map suggests that, by the year 2050, the use of ocean wave energy could fulfill up to 15% of the European Union's energy demands, while allowing a substantial reduction in carbon dioxide emissions, estimated at 136 million metric tons per megawatt-hour. The Spanish Renewable Energies Plan echoes this vision, placing a particular emphasis on the role of wave energy within Spain's energy portfolio. In this milieu, Oscillating Water Column (OWC) converters are emerging as a leading technology for the conversion of wave energy, able to operate from both terrestrial and marine platforms. This study introduces a detailed analytical model for the wave capture chamber of a static OWC wave energy generator, which has been specifically developed and parameterized for the Mutriku Marine Offshore Wave Power Plant (Mutriku's MOWC), located on the coastline of the Basque Country in Spain. The validation of the proposed model is conducted through the utilization of in-situ measured wave input data, alongside the experimental power output data procured from the operational plant. This dual-faceted validation approach ensures the robustness and applicability of the model in real-world scenarios.

关键词： Renewable energy sources Power measurement Wave power Roads Sea measurements Predictive models Data models

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Action Masked Deep Reinforcement learning for controlling Industrial Assembly Lines

Action Masked Deep Reinforcement learning for Controlling In...

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AI IoT Congress (AIIoT), World

作者： Ali Mohamed Ali Luca Tirel Dept. of Mechanical and Aerospace Engineering Carleton University Ottawa Canada Dept. of Computer Control and Management Engineering University of Rome "La Sapienza" Rome Italy

The scalability of control algorithms controlling industrial assembly lines either model-based or model-free is still a big barrier from the point of view of implementation. In this paper, various Deep Reinforcement learning (DRL) algorithms will be tested in a virtual environment of a generic industrial assembly line in terms of optimally with respect to optimal exact solutions, and computational time. The agents will take bigger rewards when they minimize the finishing time while maintaining constraints, such as time precedence between tasks. The control actions will be modeled as a task assignment matrix that assigns the tasks to be completed to specific workstations. Another control action is the resource allocation. Due to the big number of constraints, many actions will be unfeasible leading to a longer time of training of the agent to learn not to apply unfeasible actions, therefore action masking will be introduced to the DRL algorithms to reduce the action space only to the feasible actions, thereby significantly reducing training time. Proximal Policy Optimization (PPO) agent shows faster and more stable convergence to the optimal solution over the Deep-Q Network (DQN) family, including the double DQN and Dueling one.

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A Machine Learning Approach to Classify Network Traffic 13

A Machine Learning Approach to Classify Network Traffic

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13th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2021

作者： Jadav, Nilesh Dutta, Nitul Sarma, Hiren Kumar Deva Pricop, Emil Tanwar, Supeep Marwadi University Dept. of Computer Engineering Rajkot India Sikkim Manipal Inst. of Technology Dept. of Information Technology Majitar India Petroleum-Gas University of Ploiesti Automatic Control Comp and Elect. Dept Ploiesti Romania Nirma University Dept. of Computer Science and Eng. Ahmedabad India

ISBN: (纸本)9781665425346

There is a significant increase of cloud and networking-enabled applications, leading to an exponential growth of network traffic. Monitoring all these applications and their generated traffic is a challenging and complex task, especially in regard to anonymous networks used to access the Dark Web or darknet. Manual investigation of the network traffic to determine patterns of malicious activity is a very difficult task and the results might not be satisfactory. The usage of machine learning is the most viable approach for the classification of the traffic as normal or malign activity. This paper analyzes CIC-Darknet 2020 dataset to classify the benign and darknet traffic. Before applying any classifiers to our dataset, we have balanced it using Synthetic Minority Oversampling Technique (SMOTE). We have applied PCA to reduce dimensionality, furthermore, ensemble techniques, logistic classifiers, tree-classifiers, and Naive Bayes have been compared and evaluated thoroughly with various evaluation metrics Accuracy, Precision, Recall, F1-Score, and Mathew's Correlation Coefficient (MCC). © 2021 IEEE.

关键词： Machine learning

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A computer Vision-Based Solution for Assessing Prosthetic Leg Length Discrepancy

A Computer Vision-Based Solution for Assessing Prosthetic Le...

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E-Health and Bioengineering Conference (EHB)

作者： Otilia Zvorişteanu Dimitrie-Cristian Fodor Vasile-Ion Manta Neculai-Eugen Seghedin Ştefan-Daniel Achirei Dragoş-Florin Chitariu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania “Dr. Iacob Czihac” Military Emergency Clinical Hospital Iaşi Dept. of Digital Production Systems Faculty of Machine Manufacturing and Industrial Management “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

This paper presents a novel computer vision-based approach for assessing leg length discrepancy (LLD) in individuals with prosthetic limbs. The proposed solution uses image processing techniques to detect markers placed on the patient's knee, prosthesis, and a reference wall, allowing for precise measurement of limb alignment. Through a comparative analysis of the initial reference position, set by a specialist, and the current limb positioning, the algorithm identifies discrepancies in leg length. The system employs a non-invasive methodology, utilizing an IP camera to capture images and communicate them via Wi-Fi to a computing unit for further analysis. Experimental validation, conducted on simulated LLDs ranging from 1mm to 10mm, demonstrates the system's high sensitivity and accuracy in detecting subtle changes in limb alignment. This approach offers a scalable, automated alternative to traditional manual methods, improving both the reliability and ease of prosthetic adjustments.

关键词： Legged locomotion Wireless communication Limbs Prosthetic limbs Current measurement Manuals Cameras Reliability IP networks Wireless fidelity

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Identification and control of a Heat Exchanger

Identification and Control of a Heat Exchanger

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2021 International Symposium of Asian control Association on Intelligent Robotics and Industrial Automation, IRIA 2021

作者： Hanif, Omar Deshpande, Nihar G. Chatterjee, Medha The University of Sheffield Dept. of Automatic Control and Systems Engineering Sheffield United Kingdom Manchester United Kingdom Manchester United Kingdom

ISBN: (纸本)9781665433235

Heat exchangers are utilized in various industrial applications such as power generation, petroleum refinery, coal plants, etc. It is essential to model and control these applications to meet the desired outputs. This paper takes the experimental values of the heat exchanger, uses system identification techniques to model it, and then develops control schemes to control the same. Initially, conventional feedback control is developed. A feedforward algorithm is then added to regulate the external disturbances. Subsequently, the advanced control algorithms such as Internal Model control and Linear Quadratic Gaussian are implemented. The control starts from developing a simple Feedback control, then adding a feedforward controller to regulate the external disturbances and then advancing to Internal Model control and finally a Linear Quadratic Gaussian control. The responses, namely: servo responses (reference tracking), regulatory responses (input and output rejections), noise rejection responses, robust responses, and sudden step test responses, are compared for all the mentioned control schemes. Finally, the paper compares the four algorithms and gives an insight into each of their characteristics. © 2021 IEEE.

关键词： Feedback control

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Research of a Filter on Switchable Capacitors with Three-Phase control of Electronic Keys

Research of a Filter on Switchable Capacitors with Three-Pha...

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Wave Electronics and its Application in Information and Telecommunication Systems (WECONF)

作者： Darya Denisenko Alexey Titov Nikolay Butyrlagin Alexey Zhuk dept. of Scientific Research Don State Technical University Rostov-on-Don Russia dept. of Automatic Control Systems Southern Federal University Rostov-on-Don Russia dept. of Information Systems and Radio Engineering Don State Technical University Rostov-on-Don Russia

ISBN: (数字)9798350364989

ISBN: (纸本)9798350364996

A low frequencies filter of the second order on switched capacitors has been developed and studied, the distinctive feature of which is three-phase control of three electronic keys. In the proposed circuit, this allows, at constant parameters of the frequency-setting capacitors and a fixed switching frequency of electronic keys, to control the frequency of the filter pole by changing the ratio of the resistances of resistors in the general feedback circuit. The basic equations for the filter transmission coefficients at zero frequency and at the pole frequency are given, as well as formulas for calculating the pole frequency and pole attenuation at the second order. A simulation of the filter was made in the Micro-Cap environment, which shows that the considered circuit solution performs the functions of a low-pass filter. Considered filter on switched capacitors can be used to create new adaptive measuring systems and analog-digital signal processing devices.

关键词： Resistors Switching frequency Capacitors Low-pass filters Switches control systems Information filters

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Direct Data-Driven State-Feedback control of General Nonlinear Systems

Direct Data-Driven State-Feedback Control of General Nonline...

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IEEE Conference on Decision and control

作者： Chris Verhoek Patrick J. W. Koelewijn Sofie Haesaert Roland Tóth Dept. of Electrical Engineering Control Systems group Eindhoven University of Technology The Netherlands Institute for Computer Science and Control Budapest Hungary

Through the use of the Fundamental Lemma for linear systems, a direct data-driven state-feedback control synthesis method is presented for a rather general class of nonlinear (NL) systems. The core idea is to develop a data-driven representation of the so-called velocity-form, i.e., the time-difference dynamics, of the NL system, which is shown to admit a direct linear parameter-varying (LPV) representation. By applying the LPV extension of the Fundamental Lemma in this velocity domain, a state-feedback controller is directly synthesized to provide asymptotic stability and dissipativity of the velocity-form. By using realization theory, the synthesized controller is realized as a NL state-feedback law for the original unknown NL system with guarantees of universal shifted stability and dissipativity, i.e., stability and dissipativity w.r.t. any (forced) equilibrium point, of the closed-loop behavior. This is achieved by the use of a single sequence of data from the system and a predefined basis function set to span the scheduling map. The applicability of the results is demonstrated on a simulation example of an unbalanced disc.

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High-Speed Operational Amplifier Based On Complementary “Folded” Cascodes

High-Speed Operational Amplifier Based On Complementary “Fo...

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Informatics, Electronics, and Radio engineering (PIERE), International Conference Problems of

作者： Dmitry V. Kuznetsov Dmitriy V. Kleimenkin Nikolay N. Prokopenko Alexey E. Titov dept. of Scientific Research dept. of Information Systems and Radio Engineering Don State Technical University Rostov-na-Donu Russia dept. of Information Systems and Radio Engineering Don State Technical University Rostov-na-Donu Russia dept. of Automatic Control Systems Southern Federal University Rostov-na-Donu Russia

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

A significant disadvantage of classical operational amplifiers with a complementary “folded” cascode is that in the dynamic overload mode of the input differential stage, the maximum output current of the “folded” cascode is tightly coupled to the currents of the current-stabilizing bipoles that establish its static mode. This prevents (under the static current consumption limitations of the operational amplifier) a fast recharge of the integrating correction capacitor, which limits the maximum slew rate of the output voltage. The paper discusses new circuit solutions of CBJT operational amplifier based on complementary “folded” cascodes and input differential stage of dual-input stage subclass to increase slew rate from 215 V/µs to 8000 V/µs level. The problem solved here is to provide higher levels of “folded” cascode output current during the transient edge. This effect is achieved by introducing three additional small capacitance correction capacitors into the circuit. It is possible to introduce a special current limiting resistor in series with the third additional capacitor to reduce overshoot during the transient edge. The proposed modifications of operational amplifier have significant advantages in comparison with the classical ones based on complementary “folded” cascodes in terms of slew rate level. Results of computer modeling of the operational amplifier in LTSpice environment for silicon CBJT technological process with micron topological norms are presented.

关键词： Operational amplifiers Resistors Micrometers Limiting Capacitors Voltage Silicon Transient analysis Standards Switching circuits

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