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Retinal disorder diagnosis based on hybrid deep learning models

Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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Vehicle Pseudonym Change Mechanism Based on Dynamic Game

Vehicle Pseudonym Change Mechanism Based on Dynamic Game

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2024 International Conference on Mechatronics and intelligent control, ICMIC 2024

作者： Zhao, Zheng Wang, Junren Mao, Qian Zhao, Qi Xie, Xin Dalian Maritime University Dalian China Liaoning University Shenyang China Northeastern University Shenyang China Hunan University of Information Technology Changsha China Hunan Province Higher Education Key Laboratory of Intelligent Sensing and Computing Changsha China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

intelligent Transportation systems (ITS), particularly vehicular ad-hoc networks, play a crucial role in improving road safety and traffic efficiency. However, transmitting vehicle location and identity data poses significant privacy risks, potentially allowing attackers to exploit this information. In this study, we developed a user-centric privacy model based on information entropy, enabling vehicles to monitor real-time location privacy levels. We also proposed a decision algorithm for pseudonym changes, dynamically identifying a cooperative set of vehicles for pseudonym alteration. Comparative experiments using SUMO and NS-3 simulations show that our scheme enhances location privacy while reducing pseudonym change frequency. This research provides valuable theoretical and technical foundations for ITS. © 2025 SPIE.

关键词： Vehicular ad hoc networks

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Designing Low-Power Industrial Networks with the Internet of Things 5th

Designing Low-Power Industrial Networks with the Internet of...

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5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Kannagi, A. Ansari, Tabish Nasurudeen Ahamed, N. Alam, Intekhab Karnataka Bangalore India Department of Civil Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

The Internet of Things (IoT) revolution is evolving conventional commercial networks to fulfill the demands of present-day technological advancements. Low-electricity business networks are becoming increasingly vital to allow a green communique between linked systems and remote monitoring and management of gadgets. Designing and deploying low-electricity networks for business programs brings many demanding situations, which include energy control, conversation latency, and cease-to-give-up safety. This summary will offer a top-level view of the layout issues while implementing IoT and occasional-power business networks, in addition to the capability of high-quality practices for ensuring low-strength, comfortable, and reliable communications among connected devices. Furthermore, IoT techniques for localizing network accessibility, improving facts accuracy, and boosting community performance may be discussed. Subsequently, some of the trendy trends and trends in the industrial networking area could be highlighted. Low-power business networks are getting increasingly important to allow the green conversation of connected structures and remote tracking of devices. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Capability Management Strength

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Optimal Scheduling of Solar PV Generators and Network Assets in Distribution Network 3rd

Optimal Scheduling of Solar PV Generators and Network Assets...

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3rd International Conference on intelligent computing Techniques for Smart Energy systems, ICTSES 2023

作者： Singh, Samarendra Pratap Kanwar, Neeraj Saraswat, Amit Department of Electrical Engineering Manipal University Jaipur Rajasthan Jaipur India

ISBN: (纸本)9789819784288

Load flow study (LFS) and optimal power flow (OPF) are the two important tools for power system operation and control. LFS determines the state variables of electrical network whereas OPF picks the best one among the set of load flow solutions while respecting the limits of state variables. This paper presents OPF model for optimal scheduling of solar PV generators (SPVGs), tap changer (TC) and switched capacitor banks (SCBs) in distribution network. The model considers minimization of two separate objective functions, the first one is line losses and the second is the curtailment of available solar PV power. The OPF model is implemented on the modified IEEE 33 bus distribution network, and solved using Particle Swarm Optimization (PSO) using DIgSILENT PowerFactory software. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Load flow optimization

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Investigation of Battery Temperature Impact on High Voltage Cable of Electric Vehicles 3rd

Investigation of Battery Temperature Impact on High Voltage ...

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3rd International Conference on intelligent computing Techniques for Smart Energy systems, ICTSES 2023

作者： Bukya, Mahipal Kumar, Rajesh Mathur, Akhilesh Department of Electrical and Electronics Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal576104 India Department of Electrical Engineering Malaviya National Institute of Technology Jaipur302017 India

ISBN: (纸本)9789819784288

The wire and cable business is experiencing a growing inclination towards sustainability. In contemporary times, the concept of sustainability has been deeply ingrained in the decision-making processes of almost all manufacturing activities. The power industry is currently experiencing a notable increase in the demand for cables and conductors, primarily attributed to the expansion of renewable energy sources. The escalating expansion of solar energy generation and the increasing adoption of electric vehicles drive the surge in demand for low-voltage and high-voltage (HV) cables. The need for high-performance cables and conductors has shown a notable surge. In electrical vehicles, high-voltage cables are laid on battery packs. The battery pack temperature is high as compared to the room temperature, so it may affect the electrical and thermal stresses of the cabling network of the electric vehicle. This study investigates the impact of battery temperature on EV cabling stresses. Simulated the battery pack temperature, variation of voltage, and electrical stress of the cable by using numerical techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Power cables

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Performance Analysis and Power Allocation for Massive MIMO ISAC systems

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IEEE Transactions on Signal Processing 2025年 73卷 1691-1707页

作者： Nguyen, Nhan Thanh Nguyen, Van-Dinh Nguyen, Hieu V. Ngo, Hien Quoc Swindlehurst, A. Lee Juntti, Markku University of Oulu Centre for Wireless Communications Oulu90014 Finland VinUniversity College of Engineering and Computer Science Hanoi100000 Viet Nam University of Science and Technology The University of Danang Faculty of Electronics and Telecommunication Engineering Da Nang50000 Viet Nam Queen’s University Belfast School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom Kyung Hee University Department of Electronic Engineering Yongin-si17104 Korea Republic of University of California Center for Pervasive Communications and Computing IrvineCA92697 United States

Integrated sensing and communications (ISAC) is envisioned as a key feature in future wireless communications networks. Its integration with massive multiple-input-multiple-output (MIMO) techniques promises to leverage substantial spatial beamforming gains for both functionalities. In this work, we consider a massive MIMO-ISAC system employing a uniform planar array with zero-forcing and maximum-ratio downlink transmission schemes combined with monostatic radar-type sensing. Our focus lies on deriving closed form expressions for the achievable communications rate and the Cramér–Rao lower bound (CRLB), which serve as performance metrics for communications and sensing operations, respectively. The expressions enable us to investigate important operational characteristics of massive MIMO-ISAC, including the mutual effects of communications and sensing as well as the advantages stemming from using a very large antenna array for each functionality. Furthermore, we devise a power allocation strategy based on successive convex approximation to maximize the communications rate while guaranteeing the CRLB constraints and transmit power budget. Extensive numerical results are presented to validate our theoretical analyses and demonstrate the efficiency of the proposed power allocation approach. © 1991-2012 IEEE.

关键词： Budget control

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Integrated train rescheduling and speed management in a railway network: A meso-micro approach based on direct multiple shooting and alternating direction method of multipliers

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2025年 174卷

作者： Xiu, Cong Pan, Jinyi D'Ariano, Andrea Zhan, Shuguang Feng, Tao Peng, Qiyuan Southwest Jiaotong Univ Sch Transportat & Logist Chengdu 610031 Peoples R China Hefei Univ Technol Sch Automot & Transportat Engn Hefei 230009 Peoples R China Univ Leeds Inst Transport Studies Leeds LS2 9JT England Roma Tre Univ Dept Civil Comp Sci & Aeronaut Technol Engn I-00146 Rome Italy Hong Kong Polytech Univ Dept Logist & Maritime Studies Hong Kong Peoples R China

The performance of high-speed railway systems is often affected by unavoidable disruptions, which impact the reliability of train operations and passenger satisfaction. In contrast to most existing studies, which focus on either train rescheduling or speed management in separate or sequential frameworks, this paper addresses the integrated train rescheduling and speed management problem during severe disruptions, considering power supply constraints on a bidirectional railway network. Specifically, this problem incorporates detailed train speed control into the rescheduling process and involves train rerouting strategies and flexible stops to mitigate disruption effects. To characterize the integrated problem, we develop a three-dimensional space-time-state network, where each arc corresponds to a detailed driving strategy. We then propose a mixed-integer nonlinear programming (MINLP) model to simultaneously optimize the train schedule (i.e., train order, departure and arrival times, and routes) and train speed profiles, with the goal of reducing both total passenger delays and train energy consumption. To efficiently solve the integrated model, we propose a two-stage approach based on the direct multiple shooting method and the alternating direction method of multipliers (ADMM). This approach is implemented by combining offline and online computing to meet real-time requirements. The effectiveness and efficiency of the proposed model and algorithm are verified through numerous experiments using real-world data from Chinese high-speed railways. Experimental results demonstrate that our integrated approach improves energy efficiency by an average of 19.40% in complete section blockage scenarios and 7.69% in temporary speed restriction scenarios, compared to methods that do not incorporate speed management.

关键词： High-speed railway Train rescheduling Train control Direct multiple shooting method Alternating direction method of multipliers

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Demand Response and Load Profile Analysis in Modern Electricity systems 3rd

Demand Response and Load Profile Analysis in Modern Electric...

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3rd International Conference on intelligent computing Techniques for Smart Energy systems, ICTSES 2023

作者： Swarnkar, Manini Jatav, Ajay Singh, Gurpinder Swarnkar, Anil Soni, Amit Niazi, Khaleequr Rehman Department of Computer Science Engineering Manipal University Jaipur Rajasthan Jaipur303007 India Department of Electrical Engineering Malaviya National Institute of Technology Jaipur Rajasthan Jaipur302017 India Department of Electrical Engineering Manipal University Jaipur Rajasthan Jaipur303007 India

ISBN: (纸本)9789819784288

This paper introduces a comprehensive investigation into the realm of electric load profile analysis, shedding light on its pivotal aspects and far-reaching implications for effective electricity management. The study places a particular emphasis on essential components such as household consumption segmentation, the identification of peak demand instances, computation of the load factor, and the extraction of consumption trends. These elements collectively contribute to a deeper understanding of power system optimization, underlining their significance in shaping strategies for efficient resource allocation and consumption control. By harnessing the capabilities of Google Colab, a cloud-based notebook environment built upon the Jupyter platform, this research aims to empower both data scientists and machine learning developers. This collaborative digital space facilitates seamless Python code execution while offering a shared platform for real-time cooperation, thus enhancing productivity and streamlining research efforts in load profile analysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Charging stations

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Mitigating Harmonics in Integrated Photovoltaic Grids with Plug-In Hybrid Electric Vehicles 3rd

Mitigating Harmonics in Integrated Photovoltaic Grids with P...

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3rd International Conference on intelligent computing Techniques for Smart Energy systems, ICTSES 2023

作者： Kishore, M.P. Shrivastava, Ashish Soni, Amit Vidya Vikas Institute of Engineering and Technology Karnataka Mysuru570028 India Shri Vishwakarma Skill University Haryana India Department of Electrical Engineering Manipal University Jaipur Rajasthan Jaipur303007 India

ISBN: (纸本)9789819784288

Recently, there has been a notable penetration of solar photovoltaic (PV) power into the grid, accompanied by a rising power demand for electric vehicles (EVs) load the distribution system. This convergence of PV and EV in the grid presents formidable challenges, particularly concerning grid synchronization during PV integration and power quality when EVs draw power from the grid. Managing the combined impact of PV penetration and EV utilization necessitates a controller capable of simultaneously addressing synchronization and power quality control. This study investigates the utilization of proportional-integral (PI) control methodologies to create an integrated controller that can effectively manage both photovoltaic (PV) and grid synchronization and address power quality concerns associated with electric vehicle (EVs) load. For PV power generation grid synchronization, a dual-control loop approach is employed, with one loop dedicated to EV battery charging control and the other focused on grid synchronization. To suppress harmonics in the grid current, the paper utilizes multicarrier Space Vector Pulse Width Modulation (SVPWM) in conjunction with PI control on the grid connected converter. The study includes the development of a MATLAB Simulink model to simulate the PV-EV-Grid setup, offering a thorough evaluation of the effectiveness of the controller. This paper contributes to the development of solutions for the challenges posed by PV integration and EV usage in the grid, enhancing the reliability and performance of sustainable energy systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Photovoltaics

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Congress on Smart computing Technologies, CSCT 2023

Congress on Smart Computing Technologies, CSCT 2023

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Congress on Smart computing Technologies, CSCT 2023

ISBN: (纸本)9789819780952

The proceedings contain 40 papers. The special focus in this conference is on Smart computing Technologies. The topics include: Artificial Intelligence in Fake News Detection and Analysis for Low-Resource Languages;machine Learning-Based Selection of Type 2 Diabetes Specific Genes and Microarray Datasets;Is Artificial Intelligence Trustworthy? An Empirical Investigation to Adopt Generative AI for Cyber Threat Intelligence Using Valence Framework;WOAGE-MobileNetV2 Model for Plantain Tree Pest Classification and Recognition;ERFC: Crop Prediction-Based Agricultural Environment Using Enhanced Random Forest Classification;Auto-encoder Convolutıonal Neural Network (AECNN) for Apple Fruit Flower Detection;optimizing Distribution of Print Media Using Metaheuristic Algorithms;intelligent Automatic Gate control System Based on Deep Learning;challenges to Plagiarism Detection and the Use of Voice Assistants in Everyday Life and Education;exploring the Factors that Influence Cambodian Consumers’ Purchase Intention After Viewing Smartphone Ads;A Novel Remote Sensing Image Retrieval Method Using Intersected Similarity and Clustering Index (ISCI) Transfer Learning;machine Learning-Based Predictive Modeling for Diabetes and Anemia Disease;diabetic Retinopathy Diagnosis Using a Two Stage Convolutional Neural Network;p300 Classification with ConvNets for Brain Invader;land Rate Prediction Using Computational Intelligence;Optimization-Based Cash Management Model for Microfinance Applications Using GSA and PSO;the Use of Graph Theory in Development of Routes for Thematic Objects;An Assessment of Requirement engineering Practices in the IT Companies of South Gujarat Region of India;A Novel Integrated Collaborative Intelligence Framework with Innovative BI Features for Industry 5.0;zero-Knowledge Proofs in Biometric Authentication systems: A Review;cardiovascular Disease Diagnosis Prediction System Using Machine Learning.

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