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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Aeri, Manisha Yadav, Satya Prakash Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin Nicosia10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Mersin10 Turkey Graphic Era Hill University Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

The basic goal of the IoT is to permit the online connection and communication of everyday physical objects like appliances, vehicles, and other gadgets. This paves the way for effortless and automated data collection and exchange, as well as interaction between the objects themselves and with humans. The Internet of Everything (IoE) is an expansion of the Internet of Things (IoT) that aims to maximize and improve human life by connecting and making the most of all available resources (humans, information, and technology). The transportation, healthcare, agricultural, energy, and manufacturing sectors are all examples. The IoIT aims to incorporate AI and ML within the IoT's interconnected network of physical items. These objects can then independently behave in response to the information they have gathered and the instructions they have been given. This has the potential to lead to smarter, more efficient systems that can react to new information and human input in real time. The Internet of Things, the Internet of Everything, and the Industrial Internet of Things all have the same overarching goal: to pave the way for the development of more efficient and intelligent systems and processes that can enhance a wide range of human endeavors. However, in order to make sure that these technologies are used in a responsible and ethical way, it will be necessary to carefully analyze their consequences and the issues they provide. © 2023 IEEE.

关键词： Internet of things

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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

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computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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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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AI-Powered Drone to Address Smart City Security Issues 37th

AI-Powered Drone to Address Smart City Security Issues

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37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： Salama, Ramiz Al-Turjman, Fadi Culmone, Rosario Department of Computer Engineering Research Center for AI and IoT AI and Robotics Institute Near East University Nicosia Mersin 10 Nicosia Turkey Artificial Intelligence Engineering Department AI and Robotics Institute Near East University Mersin 10 Nicosia Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Mersin 10 Kyrenia Turkey Computer Science Division School of Science and Technology University of Camerino Camerino62032 Italy

ISBN: (纸本)9783031286933

The idea of a dazzling metropolis has drawn interest from all across the world. New innovations like blockchain, IoT, artificial intelligence, robots, and many other things were added to it. Security is one of the top issues for people living in big cities, and everyone wants to feel completely secure when traveling around every single day. In this research, we will look into how CEOs in affluent cities use and value robots, especially in terms of security. To understand the robot security the board stream, some approaches and intricacies are used. Following that is a discussion of issues with urban security and the application of artificial intelligence to drones as a management tool. The use of cutting-edge technology, such as blockchain, to support smart urban community management is covered in the last part. The smart city idea and all of its benefits for local inspection are supported by robotic use. The idea of thriving urban areas is spreading around the world and is crucial in the context of developing economies. We examined how to leverage cutting-edge technologies in this project to make it feasible. Artificial intelligence, robotics breakthroughs, and blockchain technologies all have significant effects. This research highlights their significance to analysts and how they consider them when assessing prospects. This project will be very beneficial for analysts and experts in a relevant subject. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Drones

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Visual recognition of wheel hubs with convolutional neural network 3

Visual recognition of wheel hubs with convolutional neural n...

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3rd International Conference on Consumer Electronics and computer Engineering, ICCECE 2023

作者： Dai, Yining Fang, Zaojun Zhong, Caiming Ningbo University Faculty of Electrical Engineering and Computer Science NingBo Zhejiang China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology NingBo Zhejiang China

ISBN: (纸本)9798350331578

The traditional recognition methods of wheel hubs are mainly based on extracted feature matching. In practical production, their accuracy, robustness and processing speed are usually greatly affected. To overcome these problems, this paper proposes a recognition method based on convolutional neural network. The basic steps include two parts: wheel image pre-processing and wheel model classification. The image processing method, mainly using the detection algorithm of hough circles, obtains the center coordinates and radius of the wheel. Then it maps the ring-shaped wheel in right-angle coordinates to polar coordinates by the center coordinates and radius. This stepcan extract the ring-shaped feature information of the wheel image and reduce the influence generated by redundant features. Then a network architecture with an improved Resnet is designed to classify the wheel models. Finally, the wheel model recognition algorithm is evaluated, and the effectiveness of the method is verified through the comparison experiments of SVM, KNN and other models. The experiments show that the recognition accuracy can reach about 99.8% for 10 kinds of wheels. © 2023 IEEE.

关键词： Wheels

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Grey Box Non-Recursive System Identification for a Third Order Electro-Hydraulic Actuator System: From Simulation to Practical Approaches 20

Grey Box Non-Recursive System Identification for a Third Ord...

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20th IEEE International Colloquium on Signal Processing and Its Applications, CSPA 2024

作者： Soon, Chong Chee Ghazali, Rozaimi Ghani, Muhamad Fadli Liew, Siaw-Hong Teng, Howe Cheng Zulkipli, Nur Farhanah Beh, Chong You Hanaffi, Mohd Saidi Department Of Engineering And Built Environment Penang Branch Campus Pulau Pinang Malaysia Centre For Robotics And Industrial Automation Fakulti Teknologi Dan Kejuruteraan Elektrik Melaka Malaysia Universiti Kuala Lumpur Perak Malaysia Faculty Of Computer Science And Information Technology Sarawak Kota Samarahan Malaysia

ISBN: (纸本)9798350382310

Engineering systems heavily rely on mathematical modeling, significantly influencing both system performance and the design of control systems. This paper thoroughly investigates the establishment of a third-order mathematical model for heavy machinery systems, with a specific emphasis on the ElectroHydraulic Actuator (EHA) system. The formulation of a double-acting EHA system model using a grey box system identification approach is outlined, encompassing the system's dynamics and behavior. In addition, the details of the EHA system experimental setup that is used for system identification are described. The identification process demonstrates promising performance, achieving an impressive accuracy of 89.1%, as highlighted in the results and discussion sections. © 2024 IEEE.

关键词： Hydraulic actuators

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Hough Transform for Detection of 3D Point Cloud Rotation

Hough Transform for Detection of 3D Point Cloud Rotation

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International Conference on Methods and Models in Automation and robotics (MMAR)

作者： Joanna Koszyk Łukasz Ambroziński Piotr Łabędź Department of Robotics and Mechatronics AGH University of Krakow Krakow Poland Faculty of Computer Science and Telecommunications Cracow University of Technology Krakow Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

In the field of mobile robotics, point clouds are widely used as an environment representation merged into a map. However, point cloud registration can be challenging when rapid movement occurs. In indoor environments, planelike features such as walls, floors, and ceilings are dominant and can be used to aid cloud merging. These features need to be extracted from point clouds. In this paper, we propose an open-source Hough transform implementation in Python. We have adapted this method, conventionally used for detecting shapes in images, to be applied to 3D point clouds and to detect planar features. To illustrate the point-cloud Hough transform algorithm, we generated synthetic point clouds. Additionally, we collected LiDAR measurements in the corridor. Processing the experimental data proved the algorithm’s ability to handle noise and measurement uncertainties. The study included an evaluation of the Hough transform by making a comparison to the ICP method. The Hough Transform provided more accurate results of corridor width measured on a merged point cloud by 0.06 m.

关键词： Point cloud compression Performance evaluation Accuracy Three-dimensional displays Simultaneous localization and mapping Shape Noise

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Towards experimental insight into magnetic flux distribution within the air gap of permanent magnet synchronous drive

Towards experimental insight into magnetic flux distribution...

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International Conference on Methods and Models in Automation and robotics (MMAR)

作者： Hubert Milanowski Adam Krzysztof Piłat Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics AGH University of Krakow Krakow Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

This report explores the experimental identification of magnetic flux density within the motor air gap, focusing on the development of a robot-based approach to automate the scanning procedure. Emphasis is placed on analyzing the distribution of magnetic flux within the motor’s spatial air gap, as well as the amplification of harmonics resulting from changes in air gap orientation. Drawing upon experimental findings, a model is proposed to illustrate the three-dimensional distribution of magnetic flux within the gap.

关键词： Solid modeling Magnetic flux density Automation Atmospheric modeling Air gaps Rotors Drives

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Respiratory Motion Compensation and Haptic Feedback for X-Ray-Guided Teleoperated Robotic Needle Insertion

Respiratory Motion Compensation and Haptic Feedback for X-Ra...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Ana Cordón Avila Mostafa Selim Momen Abayazid Faculty of Electrical Engineering Robotics and Mechatronics research group TechMed Centre Mathematics and Computer Science University of Twente AE Enschede The Netherlands

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Respiratory motion limits the accuracy and pre-cision of abdominal percutaneous procedures. In this paper, respiratory motion is compensated robotically using motion estimation models. Additionally, a teleoperated insertion is performed using proximity-based haptic feedback to guide physicians during insertion, enabling a radiation-free remote insertion for the end-user. The study has been validated using a robotic liver phantom, and five insertions were performed. The resulting motion estimation errors were below 3 mm for all directions of motion, and the overall resulting 3D insertion errors were 2.60 mm, 7.75 mm, and 2.86 mm for the superior-inferior, lateral, and anterior-posterior directions of motion, respectively. The proposed approach is expected to minimize the chances of inaccurate treatment or diagnosis due to respiratory-induced motion and reduce radiation exposure. A video summary can be found in: https://***/2Xw6AMe2mco

关键词： Three-dimensional displays Motion estimation Liver Phantoms Medical services Biomechatronics Needles Motion compensation Haptic interfaces Robots

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DTLM-DBP:Deep Transfer Learning Models for DNA Binding Proteins Identification

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computers, Materials & Continua 2021年第9期68卷 3563-3576页

作者： Sara Saber Uswah Khairuddin Rubiyah Yusof Ahmed Madani Department of Computer Engineering Faculty of EngineeringArab Academy of Science and TechnologyEgypt Centre for Artificial Intelligence&Robotics Malaysia-Japan International Institute of TechnologyUniversiti Teknologi Malaysia

The identification of DNA binding proteins(DNABPs)is considered a major challenge in genome annotation because they are linked to several important applied and research applications of cellular functions e.g.,in the study of the biological,biophysical,and biochemical effects of antibiotics,drugs,and steroids on *** paper presents an efficient approach for DNABPs identification based on deep transfer learning,named“DTLM-DBP.”Two transfer learning methods are used in the identification *** first is based on the pre-trained deep learning model as a feature’s extractor and *** different pre-trained Convolutional Neural Networks(CNN),AlexNet 8 and VGG 16,are tested and *** second method uses the deep learning model as a feature’s extractor only and two different classifiers for the identification *** classifiers,Support Vector Machine(SVM)and Random Forest(RF),are tested and *** proposed approach is tested using different DNA proteins *** performance of the identification process is evaluated in terms of identification accuracy,sensitivity,specificity and MCC,with four available DNA proteins datasets:PDB1075,PDB186,PDNA-543,and *** results show that the RF classifier,with VGG-Net pre-trained deep transfer learning features,gives the highest ***-DBP was compared with other published methods and it provides a considerable improvement in the performance of DNABPs identification.

关键词： DNABPs deep transfer learning AlexNet 8 VGG 16 SVM RF

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