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Exploring Retinal Vessel Segmentation: Deep Learning Models and Their applications

Exploring Retinal Vessel Segmentation: Deep Learning Models ...

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Advancement in Computation & Computer technologies (InCACCT), international conference on

作者： Tanishq Soni Sheifali Gupta Komuravelly Sudheer Kumar Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Computer Science and Artificial Intelligence SR University Warangal Telangana India

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Retinal vascular segmentation is essential for the early identification and monitoring of numerous ocular and systemic conditions, including diabetic retinopathy, glaucoma, and hypertension. The emergence of deep learning methodologies, particularly convolutional neural networks (CNNs) and U-Net architectures, has markedly enhanced the precision and efficacy of retinal vascular segmentation. This review paper extensively examines contemporary deep learning methodologies, concentrating on model structures, problems, and assessment measures. This paper discusses the strengths of deep learning techniques in improving upon the limitations of traditional image processing methods, such as thresholding and edge detection, while handling complex vascular structures and varied image quality. It also emphasizes the availability of publicly accessible datasets, namely DRIVE, STARE, and CHASE_DB1, as research tools in this discipline. Despite this significant progress, a lot remains to be desired, including large-scale annotated datasets, computational demand, and problems in generalization across diverse populations. Finally, the paper concluded with some future directions by integrating explainable deep learning, multi-modal imaging, and the development of lightweight models that are more appropriate for real-time clinical use.

关键词： Deep learning Image segmentation Thresholding (Imaging) Reviews Computational modeling Computer architecture Real-time systems Data models Retinal vessels Unsupervised learning

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A Finite Control Set based Model Predictive Controller for Load Power Sharing applications in Inverter Fed Microgrids

A Finite Control Set based Model Predictive Controller for L...

引用

Power, Control and Computing technologies (ICPC2T), conference on

作者： Devarapalli Vimala B. Lokeshgupta V. Naresh Kumar Department of Electrical and Electronics Engineering SRM University Andhra Pradesh

ISBN: (数字)9798331530402

ISBN: (纸本)9798331530419

Microgrids have gained more attention in recent days due to the efficient integration of various distributed energy resources. However, the load power sharing between the distribution generators (DGs) in the microgrids is one of the major challenges, especially at the peak load demand condition. This paper proposes a finite control set-based model predictive controller (FCS-MPC) for the DG-fed inverters in microgrid applications. A universal droop controller model is also considered into account to generate the reference values for the proposed FCS-MPC controller for improved power sharing. The main goal of this paper is to efficiently regulate the power flow from/to the parallel DGs in a microgrid environment. The proposed control method is able to share equal load power, though there is a mismatch in line impedances in the AC microgrid network. In this study, the microgrid test system with two parallel DGs is used to evaluate the performance of the proposed model. To show the effectiveness of the proposed control method, the simulation results of the proposed model have also been compared with the conventional droop control technique. The proposed model has superior performance compared to the conventional droop controller in terms of load power sharing and maintaining tolerance limits, as evidenced by the simulation results.

关键词： simulation Computational modeling Power control Microgrids Predictive models Inverters Generators Distributed power generation Load modeling Load flow

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Evaluation of Cuckoo Search MPPT Algorithm for Solar Photovoltaic Inverter applications

Evaluation of Cuckoo Search MPPT Algorithm for Solar Photovo...

引用

Sustainable Energy technologies and Computational Intelligence (SETCOM), international conference on

作者： Vijaychandra Joddumahanthi Yatindra Gopal Janaki Pakalapati Veda Prakash Kakinada Varshitha Potnuru V.D.K.S.R. Rajesh Department of Electrical and Electronics Engineering Lendi Institute of Engineering and Technology Vizianagaram AP India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

As the demand for renewable energy sources continues to grow, optimizing the efficiency of solar photovoltaic (PV) systems becomes increasingly important. This study illustrates a solar PV system that determines maximum power point tracking (MPPT) in solar inverter applications adopting a Cuckoo Search Algorithm (CSA). The CSA provides a distinctive approach for determining the maximum power under various scenarios and is modeled after the brood parasitism of some cuckoo species. This study examines the algorithm’s performance in real-time tracking of maximum power output, analyzing its responsiveness to change in irradiance and temperature. simulation results using MATLAB demonstrate that the CSA achieves greater efficiency and faster convergence compared to traditional MPPT methods.

关键词： Maximum power point trackers Photovoltaic systems Renewable energy sources Software packages simulation Rectifiers Mathematical models Inverters Voltage control Load modeling

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Design and simulation of an Intelligent Traffic Management System Using Vehicular Networks

Design and Simulation of an Intelligent Traffic Management S...

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Intelligent Data Communication technologies and Internet of Things (IDCIoT), international conference on

作者： P. Tapan Datta D.Lalith Kumar S. Tanoj Shinu M Rajagopal Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

In this study , the reasearch is focused on the simulation of vehicular communication networks, especially intelligent traffic systems, to enhance dependability, safety, and optimality in communication. The simulation is performed using the OMNeT++ simulator and is integrated with the Veins framework that uses the IEEE 802.11p protocol for V2V and V2I communications. Importing real-world traffic scenarios into the framework is obtained via the use of SUMO through TraCIScenarioManager. Other features of the framework include the definition of mobility models, dynamic obstacles, and detailed radio propagation modeling. TraCIDemo11p is used for mobility and communication by both RSUs and vehicles with applications in beaconing and channel switching. The whole framework analyzes smart traffic management solutions, providing as much insight into their performance based upon the communication reliability and overall efficiency in vehicular networks.

关键词： Protocols Vehicle-to-infrastructure simulation Vehicular ad hoc networks Switches Radio propagation Safety Security Reliability Vehicle dynamics

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Enhancing Building Safety: A Brief Review of Agent-Based modeling for Fire Evacuation simulation 16

Enhancing Building Safety: A Brief Review of Agent-Based Mod...

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16th international conference on Ambient Systems, Networks and technologies Networks, ANT 2025 / 8th international conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Kasereka, Selain K. Kabwe, Ortega M. Kinyanta, Maria W.K. Kasongo, Audrey L. Ilunga, Godwill W.K. Muhambya, Katya Tashev, Tasho Kyamakya, Kyandoghere Mathematics Statistics and Computer Science Department University of Kinshasa Kinshasa Democratic Republic Congo Faculty of English Engineering Studies Technical University of Sofia Sofia Bulgaria ABIL Research Center Kinshasa Democratic Republic Congo Faculty of Computer Science Université Nouveaux Horizons Lubumbashi Democratic Republic Congo Ganpat University Faculty of Computer Application Gujarat India Université Libre des Pays des Grands Lacs Faculty of Sciences and Technology Goma Democratic Republic Congo Institute of Smart Systems Technologies University of Klagenfurt Klagenfurt Austria Polytechnic Faculty University of Kinshasa Kinshasa Democratic Republic Congo

The issue of building evacuation in the event of a fire is a significant concern in urban planning and architecture. In the absence of appropriate measures, an emergency situation can potentially result in disastrous outcomes. In this review article, we explore the application of agent-based modeling (ABM) in the simulation of building evacuations in the event of a free breakout. To address this issue, we present a synthesis of findings from several studies, highlighting the advantages of ABM in modeling complex evacuation dynamics such as crowd behavior, consideration of multiple parameters, and decision-making processes. Additionally, we provide insight into the simulation tools and techniques used in studies that demonstrate the practical applications of ABM in enhancing evacuation strategies. Furthermore, we identify current challenges, research gaps, and propose future directions to enhance the accuracy and effectiveness of fire evacuation modeling and simulations. This study aims to contribute to the improvement of proposed solutions and models for the development of successful, effective, and reliable evacuation plans to enhance the safety of occupants in buildings. © 2025 The Author(s).

关键词： Agent-based modeling Agent-Based simulation Building Safety Disaster Evacuation Fire Breakout

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Enhanced Healthcare Through Metaverse Integration: Explainable AI and Blockchain for Trust, Security, and Immersive Experiences

Enhanced Healthcare Through Metaverse Integration: Explainab...

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Computational Intelligence Approaches and applications (ICCIAA), international conference on

作者： Bilal Ibrahim Sowan Hazem Qattous Mohammad Fasha Ahmad Altarawneh Dept. of Bus. Intell. & Data Analytics University of Petra Amman Jordan Dept. of Software Engineering Princess Sumaya University for Technology Amman Jordan Dept. of Computer Science Brunel University of London London UK

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

The metaverse, a dynamic blend of virtual and augmented reality, holds extraordinary promise for reshaping the healthcare landscape. By integrating advanced technologies such as virtual reality (VR), artificial intelligence (AI), blockchain, and digital twins, the metaverse introduces transformative opportunities in patient care, medical education, and healthcare operations. These tools foster immersive, personalized, and data-driven environments, significantly improving diagnostic precision, therapeutic strategies, and training methodologies. This paper provides a framework to utilize this potential while navigating key concerns, including systems scale, user customization, and ethical adequacy. In that case, the framework's goal should be eliminating existing limitations and barriers within healthcare systems by utilizing state-of-the-art technologies with real-world applications. The framework involves virtual consultation sites that enable provider-patient interactions, intelligent virtual agents with specific care recommendations, blockchain integration for data integrity, and dynamic VR segments that are functional in delivering healthcare education and training. The study focuses on scenario-based modeling and the use of pilot deployment in various healthcare settings to test for practicability and feasibility. The research also emphasizes that ethical issues and inclusion during the design and implementation of the innovations should also consider society's values regarding the medical field and promote equal access to healthcare. This framework proves a comprehensive blueprint for continuous progress and places the metaverse as one cornerstone in the global healthcare system.

关键词： Training Ethics Technological innovation Solid modeling Metaverse Medical services Blockchains Digital twins Security Medical diagnostic imaging

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The SUBLime Network: Sustainable Building Lime applications via Circular Economy and Biomimetic Approaches 18th

The SUBLime Network: Sustainable Building Lime Applications ...

引用

18th international Brick and Block Masonry conference, IB2MaC 2024

作者： Lourenço, Paulo B. Azenha, Miguel Pereira, João M. ISISE ARISE Department of Civil Engineering University of Minho Guimarães Portugal

ISBN: (纸本)9783031733093

Lime mortars play a crucial role in European and global masonry construction, offering several advantages over cement-based alternatives. These include low water penetration, improved breathability, better moisture control, enhanced workability, and lower carbon footprint. Moreover, lime-based mortars are compatible with ancient masonry, making them essential for the conservation of heritage buildings. Initiated in 2021 and funded by the European Commission, the SUBLime Network is a collaborative effort involving six academic institutions, twelve partner organizations, and fifteen PhD students. Its primary goal is to train researchers across various scientific and engineering disciplines to develop sustainable innovation solutions for lime mortars and plasters. This encompasses both new construction projects and the preservation of historical structures. SUBLime’s focus areas include material characterization, numerical modeling of multi-physics behavior, functionality, and sustainability in lime use. The project emphasizes innovative approaches such as biomimetic and closed-loop recycling methods. Specific contributions encompass microstructural and chemical characterization, testing methodologies, simulation of microstructural development, understanding of phenomena like creep and shrinkage, and development of functional materials. These efforts align with current EU objectives on environmental performance, striving towards carbon neutrality and increased sustainability in construction practices. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mortar

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Federal Cloud Computing Adoption Case Study: A Retrospective Analysis as a Precursor to Optimized Quantum Adoption methodologies 20th

Federal Cloud Computing Adoption Case Study: A Retrospective...

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20th international conference on Grid, Cloud, and Cluster Computing, GCC 2024, 3rd international conference on Quantum technologies, ICEQT 2024, and 21st international conference on modeling, simulation and Visualization Methods, MSV 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024

作者： Hornage, James Capitol Technology University LaurelMD20708 United States Springer Heidelberg Tiergartenstr. 17 Heidelberg69121 Germany

ISBN: (纸本)9783031858833

Slowed federal adoption of cloud computing was due to a combination of major changes in information technology (IT) ecosystem and the lack of a new model to address adoption challenges in the evolving environment. Since cloud computing adoption is still ongoing, the federal government continues to focus on the steps necessary to move the government forward from a state of partial adoption. This paper analyzes the government approach to cloud computing adoption to identify changes that can be implemented to optimize quantum computing adoption. The research found that evolving cloud definitions, required governance changes, cloud workforce competition, competing enterprise requirements, and contracting approach issues were the primary adoption impediments. © The Author(s) 2025.

关键词： Cloud platforms

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Dual-Band Monopole Antenna Design for Low Profile IoT and Medical applications

Dual-Band Monopole Antenna Design for Low Profile IoT and Me...

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Sustainable Energy technologies and Computational Intelligence (SETCOM), international conference on

作者： Potluru Yuva Sekhar T. Venkata Sai Karthik Kanhesh Agrawal M.Sai Debasisa Patra Sambhudutta Nanda School of Electronics Engineering VIT-AP UNIVERSITY Amaravati India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

This paper presents the design of Dual-band compact microstrip patch antenna. The antenna was made of a material like FR-4 as a substrate and copper for the patch and ground. The design has a resonating frequency of $2.373 \mathbf{~ G H z}$ and 2.673 GHz for many small scale applications, and industrial applications with some significant Transmission characteristics. The proposed antenna was fabricated using a $30 \times 30 \mathrm{~mm}$ FR4 material substrate. This antenna has good characteristics for IoT communications, which is light weight and small in profile making its fabrication cost-effective as fabrication process easy. The height of the substrate is taken 1.5 mm as per consideration of bands and return losses. The design modeling incorporates highend simulation techniques using microwave CST Studio, allowing for the optimization of key performance metrics, including directivity, gain, and efficiency.

关键词： Fabrication Patch antennas Dual band Resonant frequency Microstrip antennas Resonance Internet of Things Microstrip Antennas Substrates

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Accelerating Reliability Analysis for Aging and Self-Heating using Machine Learning

Accelerating Reliability Analysis for Aging and Self-Heating...

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IEEE international Symposium on Quality Electronic Design

作者： Tarek Mohamed Hussam Amrouch Semiconductor Test and Reliability University of Stuttgart Stuttgart Germany Chair of AI Processor Design Technical University of Munich TUM School of Computation Information and Technology Munich Institute of Robotics and Machine Intelligence

ISBN: (数字)9798331509422

ISBN: (纸本)9798331509439

The relentless drive for advanced technologies, fueled by the demands of AI and safety-critical applications, has intensified the focus on transistor aginga pivotal concern that undermines both transistor reliability and overall circuit performance. This issue is further exacerbated by advancements in packaging and 3D integration, where elevated operating temperatures accelerate aging mechanisms. As technology nodes scales below 3 nm, transistor self-heating emerges as a fundamental challenge, driven by the thermal constraints of 3D confined structures. Traditional physics-based simulation tools, such as Technology CAD (TCAD), struggle to meet the growing computational demands of these intricate designs, with escalating simulation times that impede comprehensive design exploration and optimization. Here, we present a novel framework leveraging machine learning (ML) to accelerate transistor and circuit reliability analysis. These ML-driven methodologies achieve accurate predictions of self-heating and aging effects, enabling rapid identification of aging-prone transistors while drastically reducing computational overhead. Furthermore, by obviating the need to share proprietary, physics-based models from semiconductor foundries, these techniques preserve data confidentiality, addressing critical industry concerns. Such approach not only enhances the scalability of reliability assessments but also offers a transformative pathway for tackling the multifaceted challenges of next-generation semiconductor technologies.

关键词： Solid modeling Accuracy Accelerated aging Machine learning Reliability engineering Foundries Transistors Integrated circuit reliability Integrated circuit modeling Three-dimensional integrated circuits

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