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Enabling High-Speed Connectivity in Urban Environments Through Composite Base Stations and Dynamic Spectrum Scheduling

Enabling High-Speed Connectivity in Urban Environments Throu...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Muhammad Farhan Khan Adnan Rashid Adeel Iqbal Dirk Pesch Confirm Centre for Smart Manufacturing University College Cork Cork Ireland Dep. of Electrical & Information Engineering Politecnico di Bari Bari Italy Dep. of Electrical and Computer Engineering COMSATS University Islamabad Pakistan

The combination of Composite Base Stations (CBSs) and Dynamic Spectrum Scheduling (DSS) can enable high-speed connectivity in urban environments, providing seamless connectivity to users and supporting a wide range of high-bandwidth applications. This paper investigates the performance of CBSs combining Fifth Generation (5G) cellular network and Fourth Generation (4G) Long-Term Evolution (LTE) modes in an urban environment such as a university campus. The comparison considers sub-6GHz and mmWave frequencies (28GHz) and a DSS to improve network performance and increase overall system capacity. The results show that the CBS approach improves network performance, increasing system capacity and provides high-speed connectivity to users. Additionally, this research highlights the potential of mmWave frequencies for use in heterogeneous networks to improve coverage over a large area. The findings of this study offer valuable insights for network planners and operators, demonstrating the benefits and challenges of CBS dep.oyment

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Multi-party secure communication using blockchain over 5G

Multi-party secure communication using blockchain over 5G

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Archana, K. Kareem, Z.H. Al-Farhani, Liwa H. Bagyalakshmi, K. Jenvi, Ignatia K. Majella Kumar, Ashok Department of Computer Engineering Pimpri Chinchwad College of Engineering and Research Maharashtra Pune India Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq System Analysis Control and Information Processing dep Academy of Engineering RUDN University Moscow Russia Sri Ranganathar Institute of Engineering and Technology Coimbatore India Mathematics Department Saveetha School of Engineering SIMATS Saveetha Nagar Chennai India Department of Computer Science Banasthali Vidyapith Rajasthan Banasthali India

ISBN: (纸本)9781032669663

One of the most critical problems facing the blockchain technology industry right now is how to protect the privacy of users’ data on the blockchain in a way that is both effective and cheap. Based on the Pedersen commitment and the Schnorr protocol, this study comes up with a secure multi-party computing protocol (BPLSM). By making the structure of the protocol and doing formal proof calculations, it has been shown that the protocol can be used in the blockchain network to combine private messages for efficient signing while keeping people’s identities secret. Furthermore, by looking at the nature and security of the protocol, it is also possible to find that the BPLSM protocol on the blockchain has a low cost of computing and a high level of information secrecy. Furthermore, it was found that the BPLSM protocol takes less time to check than the current mainstream BLS signature in a simple multi-party transaction with a fixed number of participants. © 2024 The Author(s).

关键词： Blockchain

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A Multivariate Functional Analysis of Inter-Hands Spatiotemporal Coordination in Human Bimanual Tasks and its Implications for Robotics

A Multivariate Functional Analysis of Inter-Hands Spatiotemp...

引用

International Conference on Autonomous Robots and Agents, ICARA

作者： Marco Baracca Andre Meixner Giuseppe Averta Paolo Salaris Tamim Asfour Matteo Bianchi Dept. of Information Engineering Research Center “E. Piaggio” University of Pisa Pisa Italy Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany Dep. of Control and Computer Engineering Politecnico di Torino Turin Italy

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Dual-arm manipulation is a key enabler for significantly enhancing the interaction between humans and robots, and their capabilities to purposefully shape the surrounding environment. However, the spatiotemporal coordination between the motion of the hands required for this type of actions makes their planning not trivial. A proper definition of these coordination patterns moving from the human example could simplify their translation on the robot side, fostering the generation of effective bimanual tasks. In this work, we propose Multivariate functional Principal Component Analysis (MfPCA) as a mathematical tool to encode inter-hands temporal kinematic covariations in terms of principal spatiotemporal coordination patterns in the Cartesian domain. We compared these patterns extracted from a dataset of human bimanual tasks with those resulting from the usage of classical fPCA, applied indep.ndently to each hand (univariate fPCA). We found that MfPCA allows for a better classification of the tasks, with respect to a state of the art taxonomy. For what concerns motion planning, MfPCA and fPCA yield similar accuracy in the reconstruction of the motion, but with a smaller number of principal components needed in the MfPCA case. These results, although preliminary, can open interesting perspectives for the usage of MfPCA for human-like bimanual motion planning and control of robotic manipulators, as well as for action recognition, to enable a more effective human-robot interaction.

关键词： Hands Translation Shape Robot kinematics Taxonomy Human-robot interaction Functional analysis Planning Spatiotemporal phenomena Principal component analysis

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Exploring Genetic Programming Models in computer-Aided Diagnosis of Skin Cancer Images

Exploring Genetic Programming Models in Computer-Aided Diagn...

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Congress on Evolutionary Computation

作者： Qurrat UI Ain Harith Al-Sahaf Bing Xue Mengjie Zhang School of Engineering and Computer Science Victoria University of Wellington Wellington New Zealand Dep. of Cybersecurity Engineering College of Engineering and Info. Technology AlShaab University Baghdad Iraq

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Extracting important information from complex skin lesion images is vital to effectively distinguish between different types of skin cancer images. In addition to providing high classification performance, such computer-aided diagnostic methods are needed where the models are interpretable and can provide knowledge about the discriminative features in skin lesion images. This underlying information can significantly assist dermatologists in identifying a particular stage or type of cancer. With its flexible representation and global search abilities, Genetic Programming (GP) is an ideal learning al-gorithm to evolve interpretable models and identify important features with significant information to discriminate between skin cancer classes. This paper provides an in-dep.h analysis of a recent GP-based feature learning method where different well-developed feature descriptors are integrated into the learning algorithms to extract high-level features for skin cancer image classification. The study explores the effectiveness of utilizing feature learning for this complex task and designing program structure to suit the problem domain as it has shown promising results compared to commonly used feature descriptors and an existing GP-based feature learning method developed for general image classification. This study analyzes the GP-evolved models to identify the prominent features and most effective feature descriptors important for the classification of these skin cancer images. The evolved models are interpretable, they provide knowledge that can assist dermatologists in making diagnoses in real-time clinical situations by identifying prominent skin cancer characteristics captured by the feature descriptors and learned during the evolutionary process.

关键词： Representation learning Visualization Computational modeling Genetic programming Feature extraction Skin Lesions

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Assessment and recognition in technical massive open on-line courses with and without on-line laboratories 14

Assessment and recognition in technical massive open on-line...

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14th IEEE Global engineering Education Conference, EDUCON 2023

作者： Martin, Sergio Castro, Manuel Sancristobal, Elio Diaz, Gabriel Garcia-Loro, Felix Perez, Clara Quintana, Blanca Gil, Rosario Plaza, Pedro Lopez, Africa Carro, German Robles, Antonio Tobarra, Llanos Rodriguez-Artacho, Miguel Ruiperez-Valiente, Jose A. Universidad Nacional de Educación A Distancia Electrical and Computer Engineering Department Madrid Spain Universidad Nacional de Educación A Distancia Dep. Sistemas de Comunicación y Control Madrid Spain Universidad Nacional de Educación A Distancia Dep. Lenguajes y Sistemas Informáticos Madrid Spain Masschusetts Institute of Technology Teaching Systems Lab United States

ISBN: (纸本)9798350399431

This paper describes the organization and results of several MOOCs delivered about technical topics (i.e., digital electronics, VHDL design on FPGAs, open education and OERs repositories and the use of STEAM technologies to encourage diversity and inclusion), where online laboratories have been used in some of them. An analysis of the enrollment, students participating on tasks or quizzes, drop-out rate and certifications requests have been done. © 2023 IEEE.

关键词： Drops

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GUI-PV Application Tool for Teaching Performance of PV System using MATLAB-Graphical User Interface Environment 1

GUI-PV Application Tool for Teaching Performance of PV Syste...

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1st IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2021

作者： Almaktoof, Ali Shebani, Nafaa Elfallah, Ali Cape Peninsula University of Technology Electrical Electronics and Computer Engineering Dep. Cape Town South Africa

ISBN: (纸本)9781665418560

A MATLAB-Graphical User Interface (GUI) based educational software which could aid in the analysis and education of photovoltaic (PV) modules is presented in this paper. The MATLAB-GUI for studying the PV module based on the evaluation of the current, voltage and power characteristics as well as performance evaluation of the PV module under different values of radiation and temperature are presented. The Graphical User Interface-Photovoltaic (GUI-PV) application is developed to simulate the characteristics of PV module and show the effects of temperature and solar radiation on the PV modules. In addition, the GUI-PV can provide PV module specifications and parameters including maximum power, current and voltage, fill factor and efficiency,...etc. Two GUI-PV models are developed for PV module characteristics and performance evaluation of solar module. Testing of the GUI-PV platform exposes that students who are trained using GUI-PV software easily understood the concept of a solar PV panel and defined the maximum power of the solar photovoltaic modules and some other parameters. © 2021 IEEE.

关键词： MATLAB

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Modelling and Determination of Short Circuit Traction Line Parameters for the Italian 3 kV DC Railway System

Modelling and Determination of Short Circuit Traction Line P...

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International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC)

作者： Antonio Di Pasquale Mario Pagano Fabio Villone Antonio Martinelli Luigi Rufolo Maurizio Santamaria Francesco Vaccaro Dep. of Electrical Engineering and Information Technology University of Naples Federico II Naples Italy Hitachi STS Naples Italy

In recent years, traction infrastructures for metro and railway systems are objects of relevant interest to improve public mobility according to the paradigm of smart grid and environmental sustainability. However, critical conditions due to short circuit faults may compromise the functionality of the entire power system. Therefore, protection systems have to promptly operate in presence of faults. This paper focuses on the Italian 3 $\mathbf{kV}$ DC railway traction power system. It aims to investigate the impact of traction line network parameters on the short-circuit current. With this regard, the system is, firstly, described according to the Multiconductor Transmission Line (MTL) model, and then represented by an equivalent lumped polyphase circuit. This circuit is used to determine the power line's equivalent resistance and inductance values, which can be used to set the protection devices installed at the Traction Power Substations (TPSs).

关键词： Resistance Analytical models Substations Short-circuit currents Transportation Transmission line measurements Traction power supplies

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Fine-Tuning Pre-Trained Models for Automated Analysis of Ophthalmic Imaging in Diagnosing Eye Diseases

Fine-Tuning Pre-Trained Models for Automated Analysis of Oph...

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information technology (ACIT)

作者： Rabia Emhamed Al Mamlook Ahmad Nasayreh Hasan Gharaibeh Mohammad Aljaidi Qais Al-Na'amneh Dalia Alzu'bi Hanin Bzizi Abdelrahman Abdeltawab Dep. of Business Administration Trine University Indiana USA Department of Industrial Engineering University Zawia Tripoli Libia Dep. Computer Science Yarmouk University Irbid Jordan Dep. of Computer Science Zarqa University Zarqa Jordan Dep. of Cyber Security Applied Science Private University Amman Jordan Dep. Information and Systems Engineering Concordia University Montreal Canada Dep of Biomedical Science Western Michigan University Kalamazoo MI USA Faculty of pharmacy Bani Sweif university Bani Suwayf Egypt

This paper searches into the convergence of such ad-vanced techniques with architectures like DenseNet201, VGG16, InceptionResNetV2, and NasNetMobile. Our focus centers on harnessing deep learning capabilities for the precise detection of eye ailments. Preliminary findings spotlight a notable uplift in diagnostic precision. Among the tested algorithms, the Nas-NetMobile architecture emerged superior, boasting an impressive accuracy rate of 92% on the chosen dataset. Through this work, we extend a significant advancement in the realm of automated eye disease diagnosis, potentially equipping medical professionals with sharper, swifter diagnostic tools. The outcomes presented herein could play a seminal role in sculpting more sophisticated and precise diagnostic approaches within ophthalmology.

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Bibliometric Analysis of research trends on Graph Neural Networks

Bibliometric Analysis of research trends on Graph Neural Net...

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International Symposium on Artificial Intelligence and Signal Processing (AISP)

作者： Meysam Alavi Arefeh Valiollahi Mansooreh Pakravan Information Technology dept Tarbiat Modares University Tehran Iran Electrical and Computer Engineering dep Tarbiat Modares University Tehran Iran

Graph Neural Networks (GNNs) are a powerful tool for analyzing complex systems and irregular data structures like graphs, revolutionizing tasks like node classification and link prediction. Therefore, regularly assessing scientific outputs to understand the current landscape is crucial. In this regard, scientometric analysis is utilized to assess, interpret, and anticipate the scientific standing of researchers, research institutions, academic journals, and countries on a global scale. Utilizing bibliometric techniques like distribution analysis, co-word networks, and scientific cooperations has proven valuable in unveiling the production trends of researchers in a scientific field, revealing both explicit and concealed dimensions. Despite existing surveys, a significant gap exists in the literature regarding bibliometric studies on the Web of Science (WoS) database in the emerging field of GNNs. This paper uses bibliometric analysis on WoS to explore the evolving GNN research area, covering contributors, collaborations, top journals, and trends identified through keywords and high citations. The research reveals that China, the United States, and Australia lead in publications on neural graph networks. Additionally, the findings underscore a predominant focus on graph neural networks within the realm of computer science.

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Machine Learning Approach to Detection of Offensive Language in Online Communication in Arabic 1

Machine Learning Approach to Detection of Offensive Language...

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1st IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2021

作者： Alakrot, Azalden Fraifer, Muftah Nikolov, Nikola S. The College of Medical Technology Department of Information Technology Yefren Libya The College of Industrial Technologies-CIT Department of Electronic Engineering Misurata Libya University of Limerick Dep. of Computer Science and Information System Limerick Ireland

ISBN: (纸本)9781665418560

This paper presents the results of several machine learning experiments, conducted with a dataset of YouTube comments in Arabic. The experiments aim at studying the impact of various text preprocessing, feature-extraction and feature-selection techniques on the accuracy of a document classifier for detection of offensive language in online communication in Arabic. Regarding data pre-processing, our experiments focus on filtering out noisy characters and normalising inconsistencies present in casual online writing in Arabic. The combined effect of these data preprocessing techniques and a few feature-extraction and feature-selection methods is then evaluated by training document classifiers. Our results give evidence that it is possible to train a classifier for the detection of offensive language on Arabic social media with reasonable overall accuracy of 0.84, and precision, recall and F1-score of 0.89, 0.76 and 0.81, respectively. © 2021 IEEE.

关键词： Support vector machines

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