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Enhancement Three-Dimensional Localization of ArUco Marker Under Photon-Starved Conditions

Enhancement Three-Dimensional Localization of ArUco Marker U...

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international conference on control, automation and Systems ( ICCAS)

作者： Jin-Ung Ha Hyun-Woo Kim Myungjin Cho Min-Chul Lee Department of Computer Science and Networks Kyushu Institute of Technology Iizuka Fukuoka Japan School of ICT Robotics and Mechanical Engineering IITC Hankyong National University Anseong Kyonggi-do Republic of Korea

In this paper, we propose a method to improve the recognition rate of ArUco markers under photon-starved conditions by using preprocessing such as photon counting algorithm and histogram equalization to estimate the exact three-dimensional(3D) location of improved objects. In the conventional ArUco marker recognition technology, the recognition rate of ArUco markers decreases under photon-starved conditions, and the exact 3D location of the object cannot be estimated. In the conventional ArUco marker recognition technology, the photon counting algorithm can be used to estimate the 3D location of objects by recognizing ArUco markers under photon-starved conditions. However, the photon counting algorithm has the problem that the computation speed is slowed down when there are many photons to estimate, and the recognition rate of the ArUco marker is reduced when there are few photons to estimate. To solve these problems of the photon counting algorithm and improve the recognition rate of ArUco markers, we apply histogram equalization to ArUco markers with the photon counting algorithm. To verify the feasibility of the proposed method, we implement simulations using the Open Manipulator-X platform and show performance metrics such as Peak Signal-to-Noise Ratio (PSNR).

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Robust Phishing URL Classification Using FastText Character Embeddings and Hybrid Deep Learning

Robust Phishing URL Classification Using FastText Character ...

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robotics, automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE international conference on

作者： Abdullah Al-Sakib Zishad Hossain Limon Anamul Sakib Md Nuruzzaman Pranto Md Ariful Islam Shayma Sultana Md. Redwan Ahmed Shafiur Rahman Dept. of Information Technology Westcliff University CA USA Dept. of Computer Science Westcliff University CA USA Dept. of Business Administration International American University CA USA Dept. of Management Information System International American University CA USA Dept. of Computer Science and Engineering East West University Dhaka Bangladesh Dept. of Software Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

Phishing attacks are a major cybersecurity threat that resulted in over 1.2 million incidents in the first half of 2020. These attacks caused substantial financial losses and posed risks to individuals and organizations. Being able to identify fraudulent websites is crucial in order to effectively address these potential risks. This study introduces a novel method for detecting phishing URLs by using word and character embeddings to capture complex URL patterns. We used a dataset of 80,000 URLs, including 50,000 legitimate ones and 30,000 phishing instances, and applied thorough preprocessing techniques. We utilized word embeddings in FastText to handle unseen words, with the added advantage of n-gram representations. Additionally, we captured character-level features through dense character embeddings. We trained several machine learning and deep learning models, and one model, the Convolutional Bidirectional LSTM (CBiLSTM), stood out with an accuracy of 99.01% and an F1-score of 99.08%. Furthermore, we made a thorough comparison with the most advanced techniques available, and our findings demonstrated clear superiority over previous research. This study presents an effective approach for classifying phishing URLs, providing a valuable tool to combat fraud and protect against identity theft, thereby helping to minimize the financial and emotional harm experienced by victims.

关键词： Deep learning Uniform resource locators Training Adaptation models Phishing Prevention and mitigation Encoding Tokenization Real-time systems Robots

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Fractional order based RISE controller for autonomous aerial vehicle

Fractional order based RISE controller for autonomous aerial...

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Range Technology (ICORT), international conference on

作者： Abhishek Dixit Pooja Agrawal Ajay Misra Aeronautical Engineer (Electronics) Indian Air Force Delhi India School of Robotics Defence Institute of Advanced Technology Pune India Department of Aerospace Engineering Defence Institute of Advanced Technology Pune India

In this work, fractional order based robust integral of the sign of the error controller (FRISE) is proposed to achieve longitudinal and lateral stability for fixed wing autonomous aerial vehicle (AAV). The AAV dynamics under consideration are affected because of external disturbances. A robust control strategy is essential for mitigating the effects of external disturbances. In this regard, the proposed FRISE controller is a viable approach. The proposed FRISE controller consists of self tuned gain. Here, the mentioned self tuned gain is modeled as an error function based on a fractional order. The stability analysis based on Lyapunov is done for the proposed FRISE controller. The simulation results provide a comparison between the proposed FRISE controller and the conventional sliding mode controller (SMC). The effectiveness of the FRISE controller is also validated with performance indices based on Integral Absolute Time Error (IATE). As a result, the robustness provided by the FRISE controller makes it more efficient for real-time applications.

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A Review of Equipment and Signal Processing of The Automated Auscultation for Blood Pressure Measurement 3

A Review of Equipment and Signal Processing of The Automated...

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3rd international Symposium on Material and Electrical Engineering conference, ISMEE 2021

作者： Pratiwi, Nurdina Gita Setiawan, Agung W. Naufal, Dziban Lindayani, Linlin Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia STIKep Ppni Jawa Barat Departement of Nursing Bandung Indonesia

ISBN: (纸本)9781665423625

Blood pressure is a critical indicator that should be checked often to avoid hypertension symptoms, suggesting cardiac problems, strokes, and sudden death. Blood pressure should be measured as precisely as possible to provide proper diagnosis and treatment. The manual auscultation method is the gold standard for noninvasive blood pressure monitoring. However, this approach is still regarded as very subjective. Several automation approaches are being developed, including the oscillometric method, ultrasonography, PPG, and automated auscultation. Automated auscultation has been grown since around 2000, but this method is still not as developed as automatic oscillometric. Because the auscultation method is still the primary reference standard and automated methods might minimize blood pressure reading mistakes, this article will explicitly examine the automatic auscultation for blood pressure measurement, especially equipment and signal processing. Further development of automated auscultation will focus on using advanced technology, such as wireless devices and the Internet of Things (IoT). © 2021 IEEE.

关键词： Blood pressure

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Estimation of the Rate of Change of a Parameter Based on the Analysis of Its Time Series

Estimation of the Rate of Change of a Parameter Based on the...

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informatics, Electronics, and Radio Engineering (PIERE), international conference Problems of

作者： Sergei I. Klevtsov Institute of Radiotechnical Systems and Control Southern Federal University SFEDU Taganrog Russia

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

The paper considers the construction of a model for classifying the dynamics of change in the parameter of a technical object, which will allow you to predict the change in its state in the process of assessing the degree of serviceability of the object. The data reflecting the change of parameters in real time and presented in the form of time series of parameter values are used. A specified time interval, usually called a time window, is used to record a parameter change. The window, as it moves along the time axis, selects a specified number of samples in a series of parameter values. To classify the dynamics of parameter variation, it is proposed to use a representation of the time window points in the form of a Poincaré plot, which is actually a special type of repetition plot or a type of scatter plot. The ellipse compression factor (ellipticity) is used as a criterion, which encompasses the point cloud formed during the construction of the scatter diagram, for the time series of the technical parameter. A methodology for training and using the model, including the formation of classes of states of the dynamics of the object parameter and the calculation of criteria, is developed. The model has been tested. The model is aimed at assessing the possibility of dangerous changes in the operation of a technical object. The assessment is performed by a micro controller device, which, as a rule, is included in the control and management system of the object. The assessment is also carried out with reference to the time of operation of the object.

关键词： Point cloud compression Training Performance evaluation Time series analysis Predictive models Real-time systems Windows Object recognition informatics Monitoring

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A Discrete, Fractional Order, Memory-Effective State Space Model of a RLC Circuit

A Discrete, Fractional Order, Memory-Effective State Space M...

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international conference on automation, automation 2021

作者： Oprzędkiewicz, Krzysztof Department of Automatic Control and Robotics Faculty of Electrotechnics Automatic Control Informatics and Biomedical Engineering AGH University of Science and Technology al. A Mickiewicza 30 Krakow30-059 Poland

The paper presents a new, discrete, memory-effective state-space model of fractional RLC network. For the presented model its stability, positivity and reaction to different inital functions are analysed. Results are ... 详细信息

ISBN: (纸本)9783030748920

关键词： Timing circuits

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Fuzzy Logic and Neural Network-Based Intelligent control System for Quadruped Robot on Extreme Terrain 23

Fuzzy Logic and Neural Network-Based Intelligent Control Sys...

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23rd international conference on control, automation and Systems, ICCAS 2023

作者： Jeon, Jinwoo Jeong, Myungwoo Myung, Hyun School of Electrical Engineering KI-Robotics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of

ISBN: (纸本)9788993215274

The quadruped robot has the advantage of having a high degree of freedom of motion. Therefore, it has been used in various robot applications such as exploration. However, the quadruped robot is not easy to control due to the large number of joints. Existing control methodologies using proportional-integral-differential (PID) or model predictive control show decent performance on uniform terrain. However, the control performance is degraded in the extreme terrain where significant non-linear disturbance occurs. To tackle this problem, we propose FLONIC-Q: fuzzy logic and neural network-based intelligent control system for quadruped robots on extreme terrain. The proposed system includes high-level and low-level control using fuzzy logic and machine learning to deal with disturbances in extreme terrain. As demonstrated in the experiments, the proposed method performs superior to existing system response methods regarding absolute trajectory error and time analysis in various trajectory types. © 2023 ICROS.

关键词： Robot applications

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Increasing the Efficiency of Constructing 3D Models of Objects by Using a High-Speed Digital Filter

Increasing the Efficiency of Constructing 3D Models of Objec...

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informatics, Electronics, and Radio Engineering (PIERE), international conference Problems of

作者： Darya A. Grebenshchikova Andrey V. Kamenskiy Dept. of Television and Control Tomsk State University of Control Systems and Radioelectronics Tomsk Russia

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

The work is devoted to increasing the efficiency of constructing 3-dimensional models of objects, using human organs as an example, through the use of preprocessing of the initial data with a high-speed digital filter. The high-speed recursive-separable digital Laplacian filter “truncated pyramid”, previously developed by the authors, was taken as a filter. This filter, through the use of the properties of recursion and separability, reduces the amount of computational costs required for the processing process, however, there is a factor that slows down its operation, its sequential operating algorithm. In the work, the authors modified the structure of the algorithm from sequential to parallel, displaying the basic principles of operation of the parallel architecture of the recursive-separable Laplacian filter “truncated pyramid” for processing images used to build 3- dimensional models of objects. After conducting experimental studies, including testing the architecture on source images and comparing performance with an existing sequential algorithm, results were obtained that confirmed the effectiveness and applicability of the developed architecture to reduce computational costs. Test objects were constructed without processing and with processing with a modified filter, from which visually and due to the increase in the number of points used to form a dense point cloud, it is clear that the generated 3-dimensional models have increased their quality.

关键词： Point cloud compression Solid modeling Visualization Three-dimensional displays Laplace equations Computational modeling Filtering algorithms Computational efficiency Digital filters Testing

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A dexterous origami-inspired soft (DOIS) robot for objects reorientation and overturn

A dexterous origami-inspired soft (DOIS) robot for objects r...

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2021 IEEE international conference on Real-Time Computing and robotics, RCAR 2021

作者： Chen, Zhi Siu, Shipan Tin, Sinyee Liu, Yukhei Cao, Hanwen Gao, Yuan Zhou, Jianshu Liu, Yunhui Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong Center of Logistics Robotics

ISBN: (纸本)9781665436786

Soft robots have presented their potential for dexterous and smooth motion with inherent compliance, compact structure, and easy control over the traditional rigid robots. This paper presents a 3D printed origami-inspired soft robot (DOIS) robot, which is inspired by the zig-zag origami structure, capable of bi-lateral bending and linear extension/contraction in a compact structure. The motion range and dimension of DOIS robot are fully customizable. The actuation and control of DOIS robot are realized by two drive cables. Mounting a dedicated end-effector at the tip, the DOIS robot is capable of tackling challenges where robots need flexible motion such as object reorientation. We present two scenarios, egg reorientation and envelope flipping, to show the superiority of DOIS robot. The design, modeling, and control of DOIS robot are discussed in detail in this paper with related experimental validation. The proposed DOIS robot provides a practical solution for dexterous soft robot design. © 2021 IEEE.

关键词： End effectors

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A CNN Approach to Assess Environment Complexity for robotics Autonomous Navigation 3

A CNN Approach to Assess Environment Complexity for Robotics...

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IEEE 3rd international conference on Mechatronics, robotics and automation (ICMRA)

作者： Sartori, Daniele Ermacora, Gabriele Pei, Ling Zou, Danping Yu, Wenxian Shanghai Jiao Tong Univ Inst Sensing & Nav 800 Dongchuan Rd Shanghai 200240 Peoples R China

ISBN: (纸本)9781728190327

Growing interest exists in the evaluation of mobile robots performing autonomous navigation. The environment where the robot operates plays an important role in the successful execution of its autonomous mission. It is therefore crucial to assess the complexity of the environment where the vehicle is deployed. In this paper, we identify two parameters which represent meaningful metrics for the evaluation of how challenging a 2D environment is for autonomous navigation. We show how these two parameters can be estimated with a CNN architecture, given as input only a map of the environment. The method is validated on two different datasets and proves successful in achieving very accurate prediction results.

关键词： robot navigation environment evaluation CNN

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