the proceedings contain 15 papers. the special focus in this conference is on Innovation and New Trends in Information Technology. the topics include: Intelligent Multi-agent distributed System for Improving and Secur...
ISBN:
(纸本)9783031473654
the proceedings contain 15 papers. the special focus in this conference is on Innovation and New Trends in Information Technology. the topics include: Intelligent Multi-agent distributed System for Improving and Secure Travel Procedures: Al-Karama-King Hussein Bridge Study Case;a New Approach for the Analysis of Resistance to Change in the Digital Transformation Context;augmented Data Warehouses for Value Capture;a parallel Processing Architecture for Querying distributed and Heterogeneous Data Sources;comprehensive Data Life Cycle Security in Cloud computing: Current Mastery and Major Challenges;systematic Mapping Study on applications of Deep Learning in Stock Market Prediction;exploring the Knowledge Distillation;intelligent Traffic Congestion and Collision Avoidance Using Multi-agent System Based on Reinforcement Learning;BERT for Arabic NLP applications: Pretraining and Finetuning MSA and Arabic Dialects;VacDist MAS for Covid-19 Vaccination Distribution: Palestine as a Case Study;Smart E-Waste Management System Utilizing IoT and DL Approaches;towards a Platform for Higher Education in Virtual Reality of Engineering Sciences;Robust Intelligent Control for Two Links Robot Based ACO Technique.
Handwritten signatures hold paramount importance in legal, financial, and administrative domains, necessitating the development of robust signature recognition tools for forensic applications. this paper introduces a ...
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ISBN:
(纸本)9798350373981;9798350373974
Handwritten signatures hold paramount importance in legal, financial, and administrative domains, necessitating the development of robust signature recognition tools for forensic applications. this paper introduces a handwritten signature recognition (HSR) model employing parallel Convolutional Neural Networks (CNN) tailored for forensic endeavors. Utilizing the parallel processing capabilities of CNN, our proposed approach adeptly analyzes and extracts discriminative features from handwritten signature images to facilitate precise recognition. In addition, we leverage several transfer learning techniques by parallelizing proven pre-trained CNNs. Extensive experimentation validates the efficacy of our approach on a standard dataset, demonstrating high accuracy and resilience in signature recognition tasks. the proposed approach exhibits substantial promise in augmenting forensic investigations by automating signature verification processes, thereby bolstering fraud detection efforts and upholding the integrity of legal documentation.
Virtual synchronous generator (VSG) has the problem of active power-frequency oscillation while providing inertia and damping for the system, especially in the parallel VSG system. therefore, an oscillation suppressio...
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ISBN:
(纸本)9798350365818;9798350365801
Virtual synchronous generator (VSG) has the problem of active power-frequency oscillation while providing inertia and damping for the system, especially in the parallel VSG system. therefore, an oscillation suppression strategy based on feedback-feedforward compound control (FFCC) is proposed. the output electromagnetic power feedback compensation and angular frequency feedforward compensation terms are constructed through first-order inertia and differential links, which effectively reduce the active power-frequency oscillation of the parallel VSG system without affecting the steady-state characteristics of the system. According to Lyapunov stability theory, the stability analysis is carried out, and the relevant parameters are designed. Finally, the simulation verifies the effectiveness and superiority of the proposed strategy to eliminate the parallel VSG grid-connected active power-frequency oscillation under the two-step disturbances of active power instruction and network frequency.
Function-as-a-Service (FaaS) has emerged as a revolutionary service platform, abstracting the complexities of hardware, operating systems, and web hosting services. this allows developers to focus solely on implementi...
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As the Internet of things (IoT) continues to grow rapidly, efficient resource utilization is crucial for the sustainability and performance of IoT networks. In this context, LoRa technology, known for its low-power, l...
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ISBN:
(纸本)9798400702341
As the Internet of things (IoT) continues to grow rapidly, efficient resource utilization is crucial for the sustainability and performance of IoT networks. In this context, LoRa technology, known for its low-power, long-range communication, has become popular for IoT applications. However, the limited energy and spectrum resources in Long Range (LoRa) networks present challenges in achieving optimal network performance in dense deployments. In particular, existing centralized approaches, such as LoRa Adaptive Data Rate, may fail to scale up to the large networks typical of IoT scenarios. To address all of these issues, we propose a smart, fully-distributed resource allocation scheme based on multi-agent cooperative Q-learning approach. Simulations results prove that our approach improves the Packet Delivery Ratio (PDR) and reduces the energy consumption of up to 43% as compared to fixed SF and random non-smart strategies, respectively, while also keeping the decision process at a device-level, with no centralized entities involved.
computing is evolving rapidly to cater to the increasing demand for sophisticated services, and Cloud computing lays a solid foundation for flexible on-demand provisioning. However, as the size of applications grows, ...
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ISBN:
(纸本)9798400702341
computing is evolving rapidly to cater to the increasing demand for sophisticated services, and Cloud computing lays a solid foundation for flexible on-demand provisioning. However, as the size of applications grows, the centralised client-server approach used by Cloud computing increasingly limits the applications' scalability. To achieve ultra-scalability, cloud/edge/fog computing converges into the compute continuum, completely decentralising the infrastructure to encompass universal, pervasive resources. the compute continuum makes devising applications benefitting from this complex environment a challenging research problem. We put the opportunities the compute continuum offers to the test through a real-world multi-view detection model (MvDet) implemented withthe FastFL C/C++ high-performance edge inference framework. Computational performance is discussed considering many experimental scenarios, encompassing different edge computational capabilities and network bandwidths. We obtain up to 1.92x speedup in inference time over a centralised solution using the same devices.
Serverless computing has shown vast potential for big data analytics applications, especially involving machine learning algorithms. Nevertheless, little consideration has been given in the literature to cloud-agnosti...
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this paper investigates the distributed consensus computing problem over heterogeneous opportunistic networks with heterogeneity in communication, caching and computing power. In existing work on distributed consensus...
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To enhance the inertia levels of power systems with a high proportion of renewable energy sources and bolster system stability, this paper proposes a novel distributed inertia compensation strategy based on the unique...
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ISBN:
(纸本)9798350365818;9798350365801
To enhance the inertia levels of power systems with a high proportion of renewable energy sources and bolster system stability, this paper proposes a novel distributed inertia compensation strategy based on the unique characteristics of asynchronous power residual capacity. By integrating the residual capacity features of asynchronous power sources and optimizing for overall grid cost, a model for inertia compensation clearance is constructed. Subsequently, a genetic algorithm approach is devised to solve the model, complemented by a coordinated operational method for inertia compensation and electricity trading, tailored to the trading dynamics of the electricity market. Case studies affirm that this compensation strategy effectively incentivizes the utilization of virtual synchronous generator technology by asynchronous power sources to convert surplus capacity into inertia. this strategy not only enhances the efficiency of asynchronous power sources but also improves the frequency response characteristics of power systems, elevates the inertia levels in systems heavily reliant on renewable energy sources, and fortifies overall system stability.
Common to many distributed systems such as the Internet-of-things (IoT) is decentralisation, often with a growing number of devices with diverse computational capabilities and security requirements. If integrated into...
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