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2024 International Conference on Control, robotics and Informatics, ICCRI 2024

作者： Salloum, Hadi Bahrami, Mohammad Reza Matevosian, Artem Gamershmidt, Sofia Jnadi, Ali Mazzara, Manuel Innopolis University Faculty of Computer Science and Engineering Innopolis Russia Innopolis University Cyber-physical systems lab Innopolis Russia Institute of Robotics and Computer Vision Innopolis University Innopolis Russia

ISBN: (纸本)9798350380309

This paper explores the integration of quantum computing, specifically quantum annealing, into robotics for inspecting electrical transmission lines. By using quantum annealing's computational power, we address the dynamics of robot inspectors on transmission line conductors, enhancing the computational efficiency of managing the movements of robot inspectors on transmission line conductors. The use of these robots is crucial for performing efficient and safe inspections. We discuss the mathematical foundations of quantum annealing, transforming differential equations governing robot dynamics into Ising model Hamiltonians suitable for quantum annealing devices. Through experiments using D-Wave's 'Advantage' quantum annealer, we demonstrate the viability of quantum annealing in solving complex robotics problems, paving the way for advanced applications in the field. © 2024 IEEE.

关键词： Ising model

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A Mathematical Comparison Between Response-time Analysis and real-time Calculus for Fixed-Priority Preemptive Scheduling 34

A Mathematical Comparison Between Response-Time Analysis and...

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34th Euromicro Conference on real-time systems, ECRTS 2022

作者： Pollex, Victor Slomka, Frank INCHRON AG Erlangen Germany Institute of Embedded Systems/Real-Time Systems Faculty of Engineering and Computer Science Universität Ulm Germany

ISBN: (纸本)9783959772396

Fixed-priority preemptive scheduling is a popular scheduling scheme for real-time systems. This is accompanied by a vast amount of research on how to analyse and check whether these systems satisfy their real-time requirements. Two methods that emerged from this research are the response-time analysis and the real-time calculus. These two methods have been compared empirically on the basis of several abstract systems showing that for some systems one method gives better results than the other and for other systems both methods appear to give the same results. However, empirical analyses inherently contain uncertainty. To get a definitive answer we compare both methods mathematically and we show that both methods give the same results for systems that use fixed-priority preemptive scheduling and independent tasks. © Victor Pollex and Frank Slomka

关键词： real time systems

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Scalable and Low-Cost Remote Lab Platforms: Teaching Industrial robotics Using Open-Source Tools and Understanding Its Social Implications 16th

Scalable and Low-Cost Remote Lab Platforms: Teaching Indust...

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16th International Conference on Social robotics, ICSR + AI 2024

作者： Kumar, Amit Jose, Jaison Jain, Archit Kulkarni, Siddharth Arya, Kavi Centre for Systems and Control Indian Institute of Technology Bombay Mumbai India Embedded Real-Time Systems / e-Yantra Lab Indian Institute of Technology Bombay Mumbai India Computer Science and Engineering Department Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)9789819635214

With recent advancements in industrial robots, educating students in new technologies and preparing them for the future is imperative. However, access to industrial robots for teaching poses challenges, such as the high cost of acquiring these robots, the safety of the operator and the robot, and complicated training material. This paper proposes two low-cost platforms built using open-source tools like Robot Operating System (ROS) and its latest version ROS 2 to help students learn and test algorithms on remotely connected industrial robots. Universal robotics (UR5) arm and a custom mobile rover were deployed in different life-size testbeds, a greenhouse, and a warehouse to create an Autonomous Agricultural Harvester System (AAHS) and an Autonomous Warehouse Management System (AWMS). These platforms were deployed for a period of 7 months and were tested for their efficacy with 1,433 and 1,312 students, respectively. The hardware used in AAHS and AWMS was controlled remotely for 160 and 355 hours, respectively, by students over a period of 3 months. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Costs

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Optimizing Very Large Scale ITS Applications with Fast Fitness Evaluation

Optimizing Very Large Scale ITS Applications with Fast Fitne...

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IEEE Conference on Wireless Communications and Networking

作者： Nagacharan Teja Tangirala Rouven Rischert Christoph Sommer Alois Knoll Chair of Robotics Artificial Intelligence and Real-time Systems Technical University of Munich Munich Germany Faculty of Computer Science TU Dresden Germany

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

As wireless communication technology advances, the complexity of Vehicular Ad-hoc Network (VANET) simulations increases. This, however, is at odds with the need for increasingly large-scale Intelligent Transportation systems (ITS) scenarios to satisfy the demands of increasingly Artificial Intelligence (AI) based solutions. This paper aims to demonstrate that a high-performance simplified VANET simulator can be used for fitness evaluation without loss in solution quality. As an example, we implement a Roadside Unit (RSU) deployment approach based on a genetic algorithm. Disolv, a simplified VANET simulator, is used as a fitness evaluation tool. To validate the solution quality, the best solutions of a few select generations are evaluated with a fully-featured ns-3 driven VANET simulation. From the comparison of fitness values, it can be observed that the values from Disolv allow us to predict those obtained via ns-3. Further, the execution time analysis showcases the substantial performance gains of using a more abstract VANET simulator. A 4.6-hour analysis with Disolv contrasts approximately 300 days with ns-3 for the given scenario and settings. Finally, the potential applications and limitations of using a simplified VANET simulator are discussed.

关键词： Wireless communication Vehicular ad hoc networks Performance gain Complexity theory Artificial intelligence Optimization Intelligent transportation systems Genetic algorithms

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Poster: Disolv - Dataflow-Centric Integrated Simulation of Large-Scale VANETs

Poster: Disolv - Dataflow-Centric Integrated Simulation of L...

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IEEE Vehicular Networking Conference (VNC)

作者： Nagacharan Teja Tangirala Christoph Sommer Alois Knoll Chair of Robotics Artificial Intelligence and Real-time Systems Technical University of Munich Munich Germany Faculty of Computer Science TU Dresden Germany

ISBN: (数字)9798350362701

ISBN: (纸本)9798350362718

Large-scale VANET simulations are computationally intensive. Disolv is a simulation architecture proposed to support city-scale VANET studies. This paper describes software decisions taken to realize a concrete implementation of Disolv. We describe a common workflow and provide guidelines on best utilizing Disolv. Finally, a small experiment demonstrates the performance gains by comparing the execution times with state-of-the-art VANET simulators.

关键词： Computational modeling Vehicular ad hoc networks computer architecture Performance gain Software Guidelines

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Monkeypox Detection with Deep-Learning and Ensemble of Features: A Study 4

Monkeypox Detection with Deep-Learning and Ensemble of Featu...

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4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Rajinikanth, Venkatesan Taniar, David Damaševičius, Robertas Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Division of Research and Innovation Department of Computer Science and Engineering TN Chennai602105 India Monash University Faculty of Information Technology MelbourneVIC3800 Australia Centre of Real Time Computer Systems Kaunas University of Technology Kaunas44249 Lithuania

ISBN: (纸本)9798350387490

There is a growing global prevalence of infectious diseases in the human population and it is imperative to have precise diagnosis and therapy in order to effectively cure these diseases. Monkeypox (Mpox) is an infectious disease that can cause varying degrees of skin infection, ranging from minor to severe. The recent spread of Mpox has been confirmed as Public Health Emergency of International Concern (PHEIC) due to its large infection rate. This study aims to develop a deep-learning (DL) scheme for Mpox identification. To enhance the detection accuracy, this study considered preprocessed skin images for the analysis and employed the binary classification with Ensemble of Deep-Features (EDF) using 5-fold cross validation. The outcome of this investigation validate that the suggested deep learning tool enables the attainment of a detection accuracy of 100% on the augmented images from the Monkeypox Skin Images Dataset (MSID). Compared to the existing results in the literature, this research provides a significant result on the chosen MSID database. © 2024 IEEE.

关键词： Classification Ensemble of deep-features Healthcare Illness Monkeypox

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Brownian-Distribution Algorithm Optimized Efficientnet Features for Normal/Glaucoma Retinal Fundus Image Classification 4

Brownian-Distribution Algorithm Optimized Efficientnet Featu...

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4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Rajinikanth, Venkatesan Damaševičius, Robertas Taniar, David Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Division of Research and Innovation Department of Computer Science and Engineering TN Chennai602105 India Kaunas University of Technology Centre of Real Time Computer Systems Kaunas44249 Lithuania Monash University Faculty of Information Technolog MelbourneVIC3800 Australia

ISBN: (纸本)9798350387490

The eye is a critical sensory organ in human physiology, and any abnormality in the eye will result in vision problems ranging from mild to severe. Image-guided methods are frequently employed to conduct clinical-level eye health assessments, and retinal fundus imaging (RFI) is among the most frequently employed modalities for eye analysis. This research aims to implement a Deep-Learning (DL)-based technique for classifying the Normal/Glaucoma RFI database. This scheme consist following phases, image collection and labelling, feature extraction with EfficientNet, feature optimization using a novel Brownian-Distribution Algorithm (BDA), and binary classification with 3-fold cross validation. Initially, the proposed approach performs the classification with EfficientNet-model features and documents the results. Subsequently, the BDA is employed to optimize the features in order to identify the most significant ones. Serial features-fusion is then implemented to generate a new features vector. The results of this study confirm that this approach is capable of achieving a 100 % accuracy rate when the BDA optimized feature vector is utilized for the classification task. In the future, this application may be utilized to analyze the RFI collected from hospital. © 2024 IEEE.

关键词： Ophthalmology

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Femoropopliteal Artery Stent Detection in Fluoroscopy Using Otsu's Preprocessing and CNN Segmentation 4

Femoropopliteal Artery Stent Detection in Fluoroscopy Using ...

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4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

ISBN: (纸本)9798350387490

computer algorithm supported medical image analysis is a prevalent method in clinics, which effectively alleviates the diagnostic burden associated with traditional image assessment methods. This study aims to create a method that utilizes a Convolutional-Neural-Network (CNN) to accurately segment the Femoropopliteal Artery Stent (FAS) in Digital Fluoroscopy Images (DFI). In order to improve the accuracy of segmentation, this study used the combination of Otsu's tri-level thresholding and the Lévy-Flight Distribution Algorithm (LFDA). The suggested technique consists of many stages: collecting and resizing images and masks, boosting the DFI using Otsu and LFDA, using CNN-segmentation to extract the stent region, comparing segmented stent with mask, and calculating the required performance metrics. The efficacy of the suggested system is validated by analyzing the raw and thresholded DFI. The investigational results of this work affirm that this method achieves a higher level of accuracy (>96%) in segmenting images when the Otsu's preprocessed image is utilized. The experimental study employs the UNet-variants, and in the future, alternative CNN-segmentation methodologies can be utilized to validate the effectiveness of the presented scheme. © 2024 IEEE.

关键词： Convolutional neural networks

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Online Reduction of Exploration Space for Automated Underwater Modem Optimization

Online Reduction of Exploration Space for Automated Underwat...

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MILCOM, Military Communications Conference

作者： Marcel Rieß Steffen Moser Frank Slomka Institute of Embedded Systems/Real-Time Systems Faculty of Engineering Computer Science and Psychology Ulm University Germany

Developing efficient underwater communication systems is complex, as multiple factors impact communication quality. While rapid prototyping has been a common approach, it carries a high risk of failure. To address this challenge, model-based development and implementation have gained popularity. However, selecting the optimal combination of modulation type, correction properties, synchronization properties, and other parameters remains time-consuming and intricate. This paper presents an innovative approach to streamline the development process by reducing the exploration space. The proposed method evaluates potential solutions based on scenario-specific, application-specific, and performance-related upper and lower bounds for the selectable communication system. These bounds consider common underwater challenges, such as SNR degradation and multiple bounce loss, and distinguish between dynamic and static system analyses. By adopting this approach, existing analysis and development workflow achieve more optimized communication systems and afford more efficient variant selection using narrowing down the solution space and considering the specific requirements of each scenario. The approach’s effectiveness is demonstrated through case studies and evaluations, highlighting the benefits of reducing the exploration space and utilizing scenario-, application-, and performance-based bounds. This enables the development of robust and tailored underwater communication systems, improving communication quality and overall system performance.

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Facial Expression Recognition Model Depending on Optimized Support Vector Machine

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computers, Materials & Continua 2023年第7期76卷 499-515页

作者： Amel Ali Alhussan Fatma M.Talaat El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Doaa Sami Khafaga Mona Alnaggar Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Machine Learning&Information Retrieval Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Robotics and Intelligent Machines Department Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt

In computer vision,emotion recognition using facial expression images is considered an important research *** learning advances in recent years have aided in attaining improved results in this *** to recent studies,multiple facial expressions may be included in facial photographs representing a particular type of *** is feasible and useful to convert face photos into collections of visual words and carry out global expression *** main contribution of this paper is to propose a facial expression recognitionmodel(FERM)depending on an optimized Support Vector Machine(SVM).To test the performance of the proposed model(FERM),AffectNet is *** uses 1250 emotion-related keywords in six different languages to search three major search engines and get over 1,000,000 facial photos *** FERM is composed of three main phases:(i)the Data preparation phase,(ii)Applying grid search for optimization,and(iii)the categorization *** discriminant analysis(LDA)is used to categorize the data into eight labels(neutral,happy,sad,surprised,fear,disgust,angry,and contempt).Due to using LDA,the performance of categorization via SVM has been obviously *** search is used to find the optimal values for hyperparameters of SVM(C and gamma).The proposed optimized SVM algorithm has achieved an accuracy of 99%and a 98%F1 score.

关键词： Facial expression recognition machine learning linear dis-criminant analysis(LDA) support vector machine(SVM) grid search

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