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A novel hybrid ConvNeXt-based approach for enhanced skin lesion classification

Expert Systems with Applications 2025年 283卷

作者： Aruk, Ibrahim Pacal, Ishak Toprak, Ahmet Nusret Department of Computer Engineering Faculty of Engineering Erciyes University Kayseri38000 Turkey Department of Software Engineering Faculty of Engineering Architecture and Design Kahramanmaras Istiklal University Kahramanmaras46050 Turkey Department of Computer Engineering Faculty of Engineering Igdir University Igdir76000 Turkey Department of Electronics and Information Technologies Faculty of Architecture and Engineering Nakhchivan State University NakhchivanAZ 7012 Azerbaijan

Skin cancer is a serious health problem that, if not diagnosed correctly at an early stage, leads to disease progression, increased risk of metastasis, and decreased quality of life. Therefore, it is critical to develop accurate and effective rapid diagnosis methods to assist physicians and enable autonomous diagnosis. While deep learning-based methods generally rely on convolutional neural networks (CNNs) or vision transformers (ViTs), hybrid approaches remain limited. In this work, we propose a novel proposed model that combines the strengths of both CNN and ViT architectures. The model utilizes the CNN approach to extract local patterns and detailed textural features, while using ViT structures to capture long-range relationships between skin cancer regions. Initially, ConvNeXt blocks extract highly detailed local features such as texture, edges, and color transitions. Transformer blocks then model the contextual relationships and global structure of these features, effectively addressing data imbalance and improving the overall classification performance. For a fair evaluation, the model is tested on two widely recognized skin cancer datasets, HAM10000 and ISIC 2019, and compared with 10 CNN and 10 ViT-based models trained under the same conditions. The proposed model achieves 94.30% accuracy and 91.11% F1-score on HAM10000, and 92.50% accuracy and 90.38% F1-score on ISIC 2019, outperforming more than 20 deep learning models and literature. These results indicate that the integration of local and global features plays a critical role in accurately classifying skin lesions and can significantly assist dermatologists in clinical practice. © 2025 Elsevier Ltd

关键词： Dermatology

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Container Performance in Space Systems

Container Performance in Space Systems

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25th International Conference on Internet Computing and IoT, ICOMP 2024, and 22nd International Conference on Embedded Systems, Cyber-physical Systems, and Applications, ESCS 2024, held as part of the World Congress in Computer Science, Computer engineering and Applied Computing, CSCE 2024

作者： Alamgir, Shariar M. Bohra, Dhruv L. Nguyen, Elisabeth A. Embedded and Specialized Computing Department The Aerospace Corporation El SegundoCA United States Software Architecture and Engineering Department The Aerospace Corporation El SegundoCA United States

ISBN: (纸本)9783031859229

Critical embedded software, such as spacecraft flight software, requires high reliability, efficiency, and real-time performance while being capable enough to meet application needs. The increasing prevalence of Linux, and in particular Linux containers, presents opportunities for space systems but also poses potential risks since Linux was not designed to be a real-time operating system. In this study, we conducted a variety of experiments to look at both the overhead imposed by containers and the latency experienced in Linux using various combinations of patched OS and containers running on a Raspberry Pi 4. We found that containers have little impact on CPU utilization but do incur penalties in RAM, disk storage, and startup time. We also found the unpatched Linux kernel performs well for real time;and that, while the real-time kernel patch reduces both overall and maximum latency, it can negatively impact performance, particularly on single-core systems running non-real-time tasks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Linux

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Constraint effects on the hydroelasticity of very large floating structures

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Ocean engineering 2025年 331卷

作者： Zhang, Guiyong Li, Qiankun Jiang, Changqing el Moctar, Ould Sun, Zhe State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment School of Naval Architecture Engineering Dalian University of Technology Dalian116024 China Institute of Sustainable and Autonomous Maritime Systems University of Duisburg-Essen Duisburg47057 Germany

Offshore structures are continuously subjected to wave-induced loads, resulting in both rigid-body motion and elastic deformation. In very large floating structures (VLFSs), hydroelastic deformation is primarily characterized by vertical displacement, encompassing both oscillatory motion and flexible deflection. Hydroelastic analysis typically involves imposing constraints to restrict body motion in waves, which can significantly influence deformation behavior. To assess the impact of these constraints, this study examines how different boundary conditions affect the hydroelastic response of VLFSs. Specifically, five test cases with distinct constraint conditions are designed to systematically evaluate their effects across multiple wavelengths. A coupled numerical methodology integrating computational fluid dynamics (CFD) and computational structural dynamics (CSD) is developed to analyze hydroelastic deformation under these conditions. Strain distributions at key locations along the floating structure are examined under varying wave conditions. Results indicate that spring constraints provide a stable deformation pattern, aligning well with physical expectations in both long and short waves. This study highlights the critical role of constraint selection in VLFS modeling and suggests that future research should explore multi-directional wave effects and diverse restraint configurations to enhance VLFS design and performance. © 2025 The Author(s)

关键词： Offshore structures

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Towards Expanding Precise Timing for Collaborative Its with Deterministic Communications in 6G

Towards Expanding Precise Timing for Collaborative Its with ...

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IEEE Conference on Wireless Communications and Networking

作者： Hongxing Li Haotian Li Qianhan Gao Guochu Shou Yaqiong Liu Zhigang Guo Yihong Hu State Key Laboratory of Networking and Switching Technology School of Computer Science (National Pilot Software Engineering School) Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

The demand for precise timing continues to grow with the rapid development of smart cities, where intelligent transportation emerges as a critical application heavily dependent on accurate time distribution. Deterministic communication is anticipated to be a defining feature of nextgeneration mobile networks (6G), enabling end-to-end timecritical applications, and unlocking new possibilities for achieving end-to-end precise time synchronization as well. To cope with the challenge of delivering precise time synchronization across broader areas at a lower cost, this paper proposes a method to achieve end-to-end precise time synchronization by leveraging the deterministic characteristics of communication networks. Specially, the proposed approach adopts the software-Defined Networking (SDN) paradigm to implement deterministic networking for the seamless integration of Time-Sensitive Networking (TSN) and cellular networks. Furthermore, to mitigate the impact of wireless channel uncertainties on synchronization accuracy, we propose a network delay measurement mechanism based on the principle of time redundancy, designed to reduce end-to-end network delay variation. Experimental results validate the effectiveness of the proposed method, demonstrating its capability to constrain the end-to-end relative time error of wired and wireless converged networks to the microsecond scale, without necessitating modifications to the existing network infrastructure.

关键词： 6G mobile communication Wireless communication Cellular networks Uncertainty Accuracy Measurement uncertainty Transportation Delays Synchronization software defined networking

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Starfish optimization algorithm (SFOA): a bio-inspired metaheuristic algorithm for global optimization compared with 100 optimizers

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Neural Computing and Applications 2025年第5期37卷 3641-3683页

作者： Zhong, Changting Li, Gang Meng, Zeng Li, Haijiang Yildiz, Ali Riza Mirjalili, Seyedali School of Civil Engineering and Architecture Hainan University Haikou570228 China Department of Engineering Mechanics State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment Dalian University of Technology Dalian116024 China Ningbo Institute of Dalian University of Technology No. 26 Yucai Road Jiangbei District Ningbo315016 China School of Civil Engineering Hefei University of Technology Hefei230009 China Jianghuai Advance Technology Center Hefei230000 China BIM for Smart Engineering Centre Cardiff School of Engineering Cardiff University Queen’s Buildings Whales CardiffCF24 3AA United Kingdom Department of Mechanical Engineering College of Engineering Bursa Uludağ University Görükle Bursa16059 Turkey Centre for Artificial Intelligence Research and Optimisation Torrens University Australia Brisbane Australia University Research and Innovation Center Obuda University Budapest1034 Hungary

This work presents the starfish optimization algorithm (SFOA), a novel bio-inspired metaheuristic for solving optimization problems, which simulates behaviors of starfish, including exploration, preying, and regeneration. SFOA consists of two main phases of exploration and exploitation. The exploration phase mimics the explorative behavior of starfish by the hybrid search pattern of combining with the five-dimensional and unidimensional search patterns to increase the computational efficiency and ensure the search capacity. The exploitation phase simulates the preying and regeneration behaviors of starfish, with a two-directional search strategy and special movement, to ensure convergence in exploitation. This work validates SFOA’s performance on 65 benchmark functions from classical functions, CEC 2017 and CEC 2022 test suites, and compares with 100 different metaheuristic algorithms, including state-of-the-art optimizers, such as marine predators algorithm, water flow optimizer (WFO), LSHADE, LSHADE-cnEpSin, and LSHADE-SPACMA. Statistical results from one-on-one comparisons demonstrate that the proposed SFOA outperforms 95 compared algorithms in accuracy and 97 algorithms in efficiency, which is only worse than WFO both in accuracy and efficiency. The scalability analysis also demonstrates that SFOA has the capacity to solve high-dimensional benchmark functions. Furthermore, ten real-world engineering optimization problems illustrate the effectiveness of SFOA to achieve global solutions and exhibit stable results. In conclusion, SFOA is promising for solving various optimization problems. The source code of SFOA is publicly available at: https://***/matlabcentral/fileexchange/173735-starfish-optimization-algorithm-sfoa. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Particle swarm optimization (PSO)

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Resource Allocation for Semantic Segmentation Tasks in Autonomous Driving: A Likelihood Active Inference Approach

Resource Allocation for Semantic Segmentation Tasks in Auton...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Xinxin Zhu F. Richard Yu Ying He Biao He College of Computer Science and Software Engineering Shenzhen University China Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen China Research Institute for Smart Cities School of Architecture and Urban Planning Shenzhen University Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The latest Segment Anything Model enables realtime scene annotation and understanding for autonomous driving systems, enhancing driving safety. However, effectively allocating resources for real-time performance and accuracy remains challenging in edge-cloud architectures. Traditional reinforcement learning struggles with poor generalization and the explorationexploitation dilemma, making it difficult to define clear reward functions. To address this, we propose a likelihood active inference approach to optimize resource allocation and improve system resource utilization. We use "intelligence" as a high-level indicator to quantify the efficiency of cognition in active inference, evaluating the difference between predicted and actual states during policy exploration. Experimental results show our algorithm outperforms mainstream deep reinforcement learning algorithms, improving sample efficiency and suitability for dynamically changing task workloads.

关键词： Accuracy Heuristic algorithms Signal processing algorithms Signal processing Prediction algorithms Inference algorithms Real-time systems Resource management Speech processing Autonomous vehicles

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TPU Nonwoven Fabrics Enhanced the Erosion Resistance and Interlaminar Fracture Toughness of CF/EP Composites

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Journal of Applied Polymer Science 2025年

作者： Zhang, Jiale Lu, Yukun Li, Zhaoyang Fang, Mei College of Architecture & Civil Engineering Shangqiu Normal University Shangqiu China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial Equipment National Engineering Research Center for Advanced Polymer Processing Technology Zhengzhou University Zhengzhou China

Carbon fiber-reinforced polymer composites (CFRPs) are extensively employed in engineering applications owing to their exceptional strength-to-weight ratio and outstanding fatigue resistance. Nevertheless, when utilized in critical components such as aircraft wings, wind turbine blades, and structural elements, their performance and durability are frequently degraded by harsh environmental conditions. To address these challenges, thermoplastic polyurethane (TPU) nonwoven fabric was introduced as an interlayer in carbon fiber/epoxy (CF/EP) composites to improve both erosion resistance and interlaminar fracture toughness. Experimental investigations revealed remarkable enhancements in mechanical properties: the CF/TPU/EP composites exhibited a 28.6% increase in maximum load, an 11.8% improvement in tensile strength, and a substantial 45.3% augmentation in bending load compared to conventional CF/EP composites. Moreover, the erosion resistance demonstrated progressive enhancement with increasing impact angles (30° to 90°), showing improvements of 58%, 130%, 185%, 227%, and 292%, respectively. These results clearly demonstrate that the TPU-modified composites achieve superior interlaminar toughness while maintaining excellent mechanical performance. The significant improvements in both mechanical properties and erosion resistance suggest that CF/TPU/EP composites possess considerable potential for demanding applications in aerospace, marine, and construction engineering, particularly under severe service conditions. © 2025 Wiley Periodicals LLC.

关键词： resins synthesis and processing techniques thermosets

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An Efficient Intrusion Detection System using Advanced Machine Learning Techniques in SDN for Healthcare System

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Asif, Muhammad Waseem Aqdus, Aqsa Amin, Rashid Chaudhry, Shehzad Ashraf Alsubaei, Faisal S. Iqbal, Sajid Department of Computer Science and IT The University of Lahore Lahore54000 Pakistan Department of Computer Science University of Chakwal Chakwal48800 Pakistan Department of Computer Science and Information Technology College of Engineering Abu Dhabi University Abu Dhabi United Arab Emirates Department of Software Engineering Faculty of Engineering and Architecture Nisantasi University Istanbul Turkey The Department of Cybersecurity College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia

The quick advancement of healthcare systems necessitates robust and efficient network security keys to defend sensitive patient records and guarantee uninterrupted service delivery. The current IDS has many challenges, such as a high false positive rate, poor accuracy of detection, slow response to threats, and inability to scale well. This paper proposes an efficient and real-time intrusion detection system (IDS) using advanced machine learning techniques within a software-defined networking (SDN) framework specifically tailored for healthcare systems. The proposed architecture implements a Machine Learning (ML) model that combines the SVM and KNN to better identify malicious activities. Full sets of detection and mitigation capabilities are implemented to address different types of traffic in the network with the least interference. Through the different evaluation measures, the efficiency of the proposed model is assured. Network performance is determined by success rate queries, packet losses in each domain path, and the CPU being used by the system. Responsiveness is measured through delay metrics grounded on end-to-end delay, hop-to-hop packet delay, latency rate, and propagation delay. Moreover, model accuracy fidelity is reviewed via precision assessment, alpha (α) affecting the accuracy of the model, and confusion matrix with different techniques with the proposed hybrid SVM-KNN model. Last of all, a comparison of the security of the models in question strengthens the argument in favor of the proposed model. More specifically, flow and network topology diagrams are included to show how integration may be accomplished in linkage or merger with existing healthcare networks. The results also present a 30% overall advancement in detection and mitigation by presenting the hybrid SVM-KNN model to overcome other traditional models. This proposed model shows significant improvements not less than 20-30% improvement in CPU use, 30-50% reduction in end-to-end delay,

关键词： Decision trees

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Efficient clustering for NOMA with THz mMIMO D2D inspired 6G system model

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Telecommunication Systems 2025年第2期88卷 1-16页

作者： Jain, Preksha Gupta, Akhil Rakesh, Nitin Tanwar, Sudeep Pau, Giovanni Alqahtani, Fayez Tolba, Amr Indian Institute of Technology Bombay India Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Department of Computer Science and Engineering Institute of Technology Nirma University Ahmedabad India Faculty of Engineering and Architecture Kore University of Enna Enna Italy Software Engineering Department College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia Computer Science Department Community College King Saud University Riyadh Saudi Arabia

Terahertz (THz) communication, offering unprecedented bandwidth, is a key enabler for the high data rates envisioned in 6G wireless networks. To further enhance capacity and spectral efficiency, this paper proposes a novel 6G hybrid system model integrating THz communication with massive multiple-input multiple-output (mMIMO), cooperative non-orthogonal multiple access (NOMA), and device-to-device (D2D) communication within a heterogeneous network architecture comprising macrocells and small cells. This integrated approach aims to address the escalating demand for connectivity. A crucial aspect of our proposed system is the development of an Antenna Angle Bound (AAB) clustering technique. This innovative method leverages antenna parameters, specifically beam angle, and width, to intelligently group users. By forming clusters based on these spatial characteristics, the AAB technique minimizes inter-user interference, a critical challenge in mMIMO systems. This interference reduction directly contributes to significantly improving the overall system sum rate. Furthermore, we formulate an energy efficiency maximization problem to optimize power allocation coefficients across the various technologies employed. This optimization ensures a balance between achieving high data rates and minimizing energy consumption, a critical consideration for sustainable 6G deployments. The complex optimization problem is tackled using the alternating direction method of multipliers algorithm, which efficiently decomposes the problem into manageable sub-problems. The combination of THz communication, mMIMO, cooperative NOMA, D2D, the AAB clustering technique, and the optimized power allocation promises to deliver a substantial leap in performance for future 6G wireless communication systems, addressing the growing need for higher data rates and improved energy efficiency. The simulation shows that the proposed 6G hybrid system schemes perform better than the traditional models by attaini

关键词： 6G Energy efficiency optimization Hybrid system Interference mitigation mMIMO mmWave NOMA Power allocation THz

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Systems thinking-informed and data-driven urban decarbonisation framework for individual, community and urban scale climate action

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Science of the Total Environment 2025年 959卷 178152页

作者： Purcell, Lily Mahon, Joanne Mac Daly, Donal De Doncker, Ingrid Nyhan, Marguerite M. Discipline of Civil Structural and Environmental Engineering School of Engineering & Architecture University College Cork Ireland Environmental Research Institute University College Cork Lee Rd Sunday's Well CorkT23 XE10 Ireland 6Rockets Software Limited Trading as Future Planet Model Farm Road CorkT12A4PX Ireland

There is an urgent need to rapidly reduce greenhouse gas (GHG) emissions and, although human activity is a primary driver of emissions, a knowledge gap remains in terms of the key individual and collective drivers of emissions, and on how to harmonise citizen-led climate action with top-down emissions mitigation policy. In response to this, an urban decarbonisation framework which was informed by systems thinking was developed to support multi-level climate action and decision making. Another aim was to demonstrate the integration of a data-driven and activity-based GHG emissions model for individuals into the framework to enable decarbonisation. This model was populated using individual activity and lifestyle data which were collected for 172 people using a smartphone application. The resulting emissions drivers were identified as well as their interaction with the overarching urban decarbonisation framework. The research will have important implications in terms of informing emissions mitigation efforts at individual, community and urban scales. By applying the framework, individual data and GHG emissions modelled at scale can inform citizen and population-level actions and high-level emissions mitigation policy for accelerating the sustainability transition that our societies and cities must urgently undergo. © 2024

关键词： Greenhouse gas emissions

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