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2023 IEEE Asia-Pacific Conference on computer Science and Data engineering, CSDE 2023

作者： Xie, Shuaiyue Chuah, Joong Huang Chai, Grace Mei Ting Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom University of Malaya Faculty of Engineering Department of Electrical Engineering Kuala Lumpur50603 Malaysia Smart Manufacturing Systems Research Group University of Southampton Malaysia Johor Iskandar Puteri79100 Malaysia

ISBN: (纸本)9798350341072

Driver fatigue is a significant cause of road accidents. Effective real-time fatigue detection systems are necessary to improve road safety. Utilizing a lightweight and fast model and creating an effective fatigue judgment rule is important in detecting fatigue in real-time. In this research, we propose a fatigue detection model based on You Look Only Once version 8 (YOLOv8) model to detect driver's facial features and use percentage of eyelid closure over the pupil over time (PERCLOS) and Percentage of Open Mouth (POM) indicators to identify fatigue. This research is divided into two parts. The first part involves creating, labeling, and preprocessing the dataset. We use the YawDD dataset as the original dataset and manually label a new dataset using the Roboflow platform. We then preprocessed the new dataset to train the YOLOv8 model for face features detection. In the second part, we established a multi-indicator fatigue determination rule that uses PERCLOS and POM indicators and set a threshold to determine whether the driver is fatigue. By combining the YOLOv8 model with the fatigue determination rules based on PERCLOS and POM, we successfully built a model to identify a driver's fatigue. Finally, the fatigue detection model based on YOLOv8 achieves a high accuracy rate of 96.9% and a high speed of 11.4 ms/frame in face features detection, surpassing other traditional models and previous generations of YOLO models. This model can effectively detect fatigue in both driver-driving pictures and videos. © 2023 IEEE.

关键词： Roads and streets

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Online Canonical Correlation Analysis via Rayleigh-Ritz Projections 58

Online Canonical Correlation Analysis via Rayleigh-Ritz Proj...

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58th Asilomar Conference on Signals, systems and computers, ACSSC 2024

作者： Kalantzis, Vassilis Traganitis, Panagiotis A. Kanatsoulis, Charilaos I. Ibm Research MIT-IBM Watson Ai Lab Yorktown HeightsNY United States Michigan State University Dept. of Electrical and Computer Engineering East LansingMI United States University of Pennsylvania Dept. of Electrical and Systems Engineering PhiladelphiaPA United States

ISBN: (纸本)9798350354058

Canonical correlation analysis (CCA) is a classical statistical tool that enables processing of multiview data in a plethora signal processing, machine learning and data mining applications, by identifying a common linear subspace from the available data views. Most algorithms tackling the CCA task require all the data per view to be available. Nevertheless, in many cases, data are not available in batch form and may arrive in streaming fashion. This work puts forth a novel, computationally efficient, projection based method for identifying and updating the common subspace on-the-fly, as new data arrive, while retaining its' fidelity. Preliminary numerical tests, on synthetic and real data benchmarks, showcase the potential of the proposed method. © 2024 IEEE.

关键词： Canonical Correlation Analysis Online Analy-sis Rayleigh-Ritz Projection

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Real-Time Implementation of Quadrotor UAV Control System Based on a Deep Reinforcement Learning Approach

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computers, Materials & Continua 2024年第12期81卷 4757-4786页

作者： Taha Yacine Trad Kheireddine Choutri Mohand Lagha Souham Meshoul Fouad Khenfri Raouf Fareh Hadil Shaiba Aeronautical Sciences Laboratory Aeronautical and Spatial Studies InstituteBlida 1 UniversityBlida0900Algeria Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Energy and Embedded Systems for Transportation Research Department ESTACA-LABMontigny-Le-Bretonneux78066France Department of Electrical Engineering University of SharjahSharjah27272United Arab Emirates Department of Computer Science College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

The popularity of quadrotor Unmanned Aerial Vehicles(UAVs)stems from their simple propulsion systems and structural ***,their complex and nonlinear dynamic behavior presents a significant challenge for control,necessitating sophisticated algorithms to ensure stability and accuracy in *** strategies have been explored by researchers and control engineers,with learning-based methods like reinforcement learning,deep learning,and neural networks showing promise in enhancing the robustness and adaptability of quadrotor control *** paper investigates a Reinforcement Learning(RL)approach for both high and low-level quadrotor control systems,focusing on attitude stabilization and position tracking tasks.A novel reward function and actor-critic network structures are designed to stimulate high-order observable states,improving the agent’s understanding of the quadrotor’s dynamics and environmental *** address the challenge of RL hyper-parameter tuning,a new framework is introduced that combines Simulated Annealing(SA)with a reinforcement learning algorithm,specifically Simulated Annealing-Twin Delayed Deep Deterministic Policy Gradient(SA-TD3).This approach is evaluated for path-following and stabilization tasks through comparative assessments with two commonly used control methods:Backstepping and Sliding Mode Control(SMC).While the implementation of the well-trained agents exhibited unexpected behavior during real-world testing,a reduced neural network used for altitude control was successfully implemented on a Parrot Mambo mini *** results showcase the potential of the proposed SA-TD3 framework for real-world applications,demonstrating improved stability and precision across various test scenarios and highlighting its feasibility for practical deployment.

关键词： Deep reinforcement learning hyper-parameters optimization path following quadrotor twin delayed deep deterministic policy gradient and simulated annealing

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ISAR-Image recognition using optimized HONN by a Metaheuristic algorithm 9

ISAR-Image recognition using optimized HONN by a Metaheurist...

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9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

作者： Elyounsi, Asma Tlijani, Hatem Bouhlel, Med Salim University of Gabes Res. Lab: Smart Systems for Engineering E-Health Based on Technologies of Image Telecomunications. National Engineering School of Gabes Tunisia University of Gafsa Research Lab: LARA Enit University of Tunis EL Manar National Engineering School of Gafsa Tunisia University of Sfax Res. Lab: Smart Systems for Engineering E-Health Based on Technologies of Image Telecomunications. ISBS.BP.1175 3038 Tunisia

ISBN: (数字)9781728184425

ISBN: (纸本)9781728184425

In the field of ISAR Data extraction, many drawbacks appear and make this field a very challenging one. Therefore, using higher order neural networks (HONN) became an useful way to cope with problems like the inability to scale with the complexity of the problem and the sluggish converge rate that results in a lengthy training period. The Functional Link Artificial Neural Network (FLANN), a higher order neural network, was optimized in this paper using a revolutionary metaheuristic inspired by the Firefly algorithm to identify radar targets. Results from experiments demonstrate the effectiveness of the training method. © 2022 IEEE.

关键词： Optimization

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Localization of Dengue Virus Likelihood Using Image Processing Technique 6

Localization of Dengue Virus Likelihood Using Image Processi...

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6th IEEE International Conference on Emerging smart Computing and Informatics, ESCI 2024

作者： Hosen, Md. Mahbub Islam, Md. Rahatul Tabassum, Faria Tonni, Syeda Thamina Noor, Malik Mohammad Nafiur Rahman, Shahid Northern University of Bangladesh Dept. of Computer Science and Engineering Dhaka Bangladesh Kyushu Institute of Technology Dept. of Human Intelligence Systems Wakamatsu Kitakyushu Japan Bangladesh University of Engineering and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh Bangladesh Advance Robotics Research Center Human Intelligence Lab Dhaka Bangladesh Canadian University of Bangladesh Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350306613

The Aedes mosquito, found in tropical areas, transmits, and causes dengue fever. The spread of the dengue fever virus from an infected Aedes mosquito bite typically takes between three and fifteen days to manifest itself clinically as dengue fever symptoms. Early and automated detection of this illness will reduce the occurrence of outbreaks and facilitate the digitization of the system. Our primary objective is to identify regions at high risk for dengue fever using limited image data through the utilization of sophisticated machine learning and image processing methods. This work showcases the application of transfer learning algorithms for the timely identification of regions at risk for dengue mosquito infestation, particularly in situations where obtaining early data on dengue outbreaks is challenging. The experiments included images of 2150 dengue-positive data sets and 1440 dengue-negative data sets. We used AI and image classifiers Yolo V4 Tin, Tensor Flow, Google Colab, etc. for the training data set, and the system makes predictions with a 99.63% accuracy rate. Our system has some unique attributes;it not only detects the percentage of dengue probability but also the specific dengue-prone location on the submitted image. © 2024 IEEE.

关键词： aedes mosquito dengue-prone image processing yolo v4 tiny

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A Comprehensive Study on Face Recognition Biases beyond Demographics

IEEE Transactions on Technology and Society

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IEEE Transactions on Technology and Society 2022年第1期3卷 16-30页

作者： Terhorst, Philipp Kolf, Jan Niklas Huber, Marco Kirchbuchner, Florian Damer, Naser Moreno, Aythami Morales Fierrez, Julian Kuijper, Arjan Department of Smart Living & Biometric Technologies Fraunhofer Institute for Computer Graphics Research IGD Darmstadt64283 Germany Interactive Graphics Systems Group Technical University of Darmstadt Darmstadt64289 Germany Biometrics and Data Pattern Analytics Lab-BiDA Lab Universidad Autonoma de Madrid Madrid28049 Spain

Face recognition (FR) systems have a growing effect on critical decision-making processes. Recent works have shown that FR solutions show strong performance differences based on the user's demographics. However, to enable a trustworthy FR technology, it is essential to know the influence of an extended range of facial attributes on FR beyond demographics. Therefore, in this work, we analyze FR bias over a wide range of attributes. We investigate the influence of 47 attributes on the verification performance of two popular FR models. The experiments were performed on the publicly available MAAD-Face attribute database with over 120M high-quality attribute annotations. To prevent misleading statements about biased performances, we introduced control group-based validity values to decide if unbalanced test data causes the performance differences. The results demonstrate that also many nondemographic attributes strongly affect recognition performance, such as accessories, hairstyles and colors, face shapes, or facial anomalies. The observations of this work show the strong need for further advances in making the FR system more robust, explainable, and fair. Moreover, our findings might help to a better understanding of how FR networks work, enhance the robustness of these networks, and develop more generalized bias-mitigating FR solutions. © 2022 IEEE.

关键词： Biometrics

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Optimization and Improvement of Reduced Ferrite DWPT Magnetic Link Structure with New Passive Reflection Windings Topology

Optimization and Improvement of Reduced Ferrite DWPT Magneti...

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Power Electronic and Drive systems and Technologies Conference (PEDSTC)

作者： Maryam Pakzaban Sadegh Vaez-Zadeh Sina Navaiyan-Kalat Advanced Motion Systems Research Lab School of Electrical and Computer Engineering Collage of Engineering University of Tehran Tehran Iran Advanced Motion Systems Research Lab and The Center of Excellence on Applied Electromagnetic Systems School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

Charging electric vehicles via dynamic wireless power transfer (DWPT) can be more cost-effective and safe than other charging methods if different system parts enjoy a proper design for a long way. Therefore, structural simplicity and, at the same time, the utilization of economic components in the magnetic link of such systems are significant advantages. Maximum reduction of expensive and brittle ferrite cores in the structure and their replacement with reflection windings will be an optimization strategy. In this paper, in order to achieve a robust and economic DWPT system with the ability to transfer suitable power while introducing a new topology of passive reflection windings, optimized rectangular pads (RP-RP) with 90-degree rotation are used as primary and secondary main pads.

关键词： Ferrites Couplings Coils Magnetic flux Magnetic cores Windings Reflection

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Robust Synchronizing Method for Unbalanced Weak Grid Connected Converters with High Power Quality

Robust Synchronizing Method for Unbalanced Weak Grid Connect...

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Power Electronic and Drive systems and Technologies Conference (PEDSTC)

作者： Pooriya Jamallo Sadegh Vaez-Zadeh Alireza Jabbarnejad Advanced Motion Systems Research Lab School of Electrical and Computer Engineering Collage of Engineering University of Tehran Tehran Iran Advanced Motion Systems Research Lab and The Center of Excellence on Applied Electromagnetic Systems School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

Renewable energy sources are usually installed far from the power grid. In these cases, transmission lines have a high impedance which causes voltage distortion at the point of common coupling (PCC). In addition, unbalanced grid voltage conditions may occur due to unbalanced loads and lines impedance. This problem increases the challenge of control system design in weak grid conditions. Moreover, any difference between the real amount of the line impedance and its amount in the control system causes the selection of improper voltage vectors. This paper proposes a sensorless direct power control based on the line impedance estimation that synchronizes the converter with the grid of the proposed PCC. It leads to improving the system performance under unbalanced weak grid conditions. The effectiveness of the proposed control system in comparison with the existing methods are shown by extensive analytical and simulation studies.

关键词： Couplings Renewable energy sources Reactive power Power transmission lines Simulation System performance Estimation

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RJoules: An Energy Measurement Tool for R 23

RJoules: An Energy Measurement Tool for R

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Proceedings of the 38th IEEE/ACM International Conference on Automated Software engineering

作者： Rajrupa Chattaraj Sridhar Chimalakonda Research in Intelligent Systems and Human Analytics Lab Department of Computer Science and Engineering Indian Institute of Technology Tirupati India

ISBN: (纸本)9798350329964

With the exponential growth of data, the demand for effective data analysis tools has increased significantly. R language, known for its statistical modeling and data analysis capabilities, has become one of the most popular programming languages among data scientists and researchers. As the importance of energy-aware software systems continues to rise, several studies investigate the impact of source code and different stages of machine learning model training on energy consumption. However, existing studies in this domain primarily focus on programming languages like Python and Java, resulting in a lack of energy measuring tools for other programming languages such as R. To address this gap, we propose "RJoules", a tool designed to measure the energy consumption of R code snippets. We evaluate the correctness and performance of RJoules by applying it to four machine learning algorithms on three different systems. Our aim is to support developers and practitioners in building energy-aware systems in R. The demonstration of the tool is available at https://***/yMKFuvAM-DE and related artifacts at https://***/RJoules/.

关键词： energy measurement

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Speech Separation for Low-Resource Languages

Speech Separation for Low-Resource Languages

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Borsdorf, Marvin Pan, Zexu Himmelmann, Pascal Li, Haizhou Schultz, Tanja Machine Listening Lab University of Bremen Bremen Germany Alibaba Group Singapore Department of Mathematics and Computer Science FernUniversität in Hagen Hagen Germany School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China Department of Electrical and Computer Engineering National University of Singapore Singapore Cognitive Systems Lab University of Bremen Bremen Germany

ISBN: (纸本)9798350368741

Speech separation aims to equip machines with the human ability of selective listening, i.e. to focus attention on specific information in spoken communication. Studies have shown that the language spoken in a cocktail party scenario matters. While the development of speech separation models can leverage extensive databases, for the majority of languages only very limited data is available. This work presents the very first study on speech separation for low-resource languages. We choose blind source separation as the task to be studied and analyze three strategies to overcome the data scarcity of two low-resource languages from the GlobalPhoneMS2 database. We show that data from other languages can be used to develop models that work for low-resource languages. Finetuning additionally boosts the performance, and training on multiple languages increases both performance and robustness. We show that dynamic mixing in the development helps to find a trade-off between performance and development time. © 2025 IEEE.

关键词： cocktail party problem GlobalPhone low-resource language multilingual speech separation

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