An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…Deep learning models, while effective, are associated with high computational costs and large data requirements. As an alternative, Echo State Networks (ESNs) are more computationally efficient, but their predictive accuracy can be constrained by the use of simplistic neuron models and a dependency on hyperparameter tuning.MethodsThis paper proposes a framework, the Echo State Network based on an Enhanced Intersecting Cortical Model (ESN-EICM). …”
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Approaches to Addressing Service Selection Ties in Ad Hoc Mobile Cloud Computing by Ayotuyi Tosin Akinola, Matthew Olusegun Adigun

“…These mechanisms were evaluated using the experimental method. The evaluation of the mechanisms mainly focused on the metrics that evaluate the satisfaction of users' interest via the quantitative evaluation. …”
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Blended teaching of university mathematics courses based on Online Merge Offline model by Yuping Zhang, Changzhou Dong

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Quantitative Evaluation and Preoperative Planning Using Three‐Dimensional CT Profiles Improves the Accuracy of Bony Correction Under Primary Hip Arthroscopy and Clinical Outcomes i... by Feng Zheng, Wang Daofeng, Song Guanyang, Li Yue, Wang Xuesong

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IoT‐Based Elderly Health Monitoring System Using Firebase Cloud Computing by Adhan Efendi, Muhammad Imam Ammarullah, Indra Griha Tofik Isa, Meli Puspita Sari, Jasmine Nurul Izza, Yohanes Sinung Nugroho, Hamid Nasrullah, Denny Alfian

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Research on asynchronous robust federated learning method in vehicle computing power network by YIN Hongbo, WANG Shuai, ZHANG Ke, ZHANG Yin

“…The synchronous training mechanism of traditional federated learning was not suitable for dynamic vehicle computing power network scenarios, and lacked effective detection mechanisms under the threat of malicious vehicle attacks. …”
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Multi-Branch CNN-LSTM Fusion Network-Driven System With BERT Semantic Evaluator for Radiology Reporting in Emergency Head CTs by Selene Tomassini, Damiano Duranti, Abdallah Zeggada, Carlo Cosimo Quattrocchi, Farid Melgani, Paolo Giorgini

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Evaluation of accuracy and membrane perforation in robotic-assisted implant surgery for transalveolar sinus floor elevation: a retrospective case series by Tao Yang, Wenjing Yi, Wenan Xu, Xiaojian Xing, Buling Wu

“…This study aimed to assess implant placement accuracy and membrane perforation in robotic computer-assisted implant surgery (r-CAIS) for TSFE. …”
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Comparing traditional natural language processing and large language models for mental health status classification: a multi-model evaluation by Thomas Kallstenius, Andrea Johansson Capusan, Gerhard Andersson, Adam Williamson

“…We compared the results of the three computational approaches and overfitting was monitored through validation loss across epochs for the fine-tuned LLM. …”
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An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment by Santhosh Kumar Medishetti, Ganesh Reddy Karri

“…Task scheduling in Cloud-Fog computing environments is a critical aspect of optimizing resource allocation and enhancing performance. …”
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Modeling and Performance Analysis of Task Offloading of Heterogeneous Mobile Edge Computing Networks by Wenwang Li, Haohao Zhou

“…Mobile edge computing architecture (MEC) can provide users with low latency services by integrating computing, storage and processing capabilities near users and data sources. …”
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Fast and fair split computing for accelerating deep neural network (DNN) inference by Dongju Cha, Jaewook Lee, Daeyoung Jung, Sangheon Pack

“…Additionally, we devise a low-complexity heuristic algorithm called fast and fair split computing (F2SC). Evaluation results demonstrate that F2SC reduces inference time by 3.8%∼20.1% compared to the conventional approaches while maintaining fairness.…”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…This paper details the model evaluation and demonstrates the feasibility and efficiency of edge intelligence in ventilator weaning decision support.…”
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Effect of gastric juice on the surface, optical, and mechanical properties of different computer-aided design/computer-aided manufacturing dental ceramics: A systematic review and... by Lorena Scaion Silva, Victor Augusto Alves Bento, Kevin Henrique Cruz, Victor Alves Nascimento, Aldiéris Alves Pesqueira, Eduardo Piza Pellizzer

“…Purpose: Effect of an erosive challenge on the surface, optical, and mechanical properties of prostheses manufactured using different types of dental ceramics for computer-aided design/computer-aided manufacturing (CAD/CAM). …”
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Computing Non-Dominated Flexible Skylines in Vertically Distributed Datasets with No Random Access by Davide Martinenghi

“…We introduce an algorithm for computing <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mrow><mi>ND</mi></mrow></mrow></semantics></math></inline-formula> in the NRA scenario, prove its correctness and optimality within its class, and provide an experimental evaluation covering a wide range of cases, with both synthetic and real datasets.…”
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Edge Computing Architectures for Low-Latency Data Processing in Internet of Things Applications by Banoth Sreenu, M Vineesha, Punna Hari Shankar, P Mathiyalagan, Prakash Vijay, M Jasmin

“…Apply large-scale edge computing solutions in enterprise scenarios: conduct a cost-benefit analysis Evaluation results show that the proposed design achieves substantial latency reduction, energy saving, and data security, recommending it to meet the needs of next generation IoT applications.…”
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Fast handover authentication scheme in 5G mobile edge computing scenarios by Weicheng ZHANG, Hongquan WEI, Shuxin LIU, Liming PU

“…The 5G internet of things brings the ultimate experience to users, but it also puts forward new challenges.Users’ requirements of ultra-low latency experience, access to business without sense during movement and security guarantee have attracted much attention.Mobile edge computing can meet the strict requirements of 5G with low latency, large connection and high bandwidth.As a computing paradigm with the coexistence of multi-trust domains, multi-entities and cross-trust domains are interconnected frequently.Identity authentication is particularly important for security protection.Through the research on the identity authentication mechanism under the existing edge computing paradigm, a lightweight fast handover authentication scheme based on pre-authentication was proposed.The proposed solution moved services and calculations from the cloud to the edge.Biometric fingerprint technology was used on the client side to defend against terminal theft attacks.Edge servers in different regions used pre-authentication scheme to meet fast switching requirements.The user and the edge server established a secure channel by negotiating a shared session key in real time, and the authentication scheme ensured lightweight operation with XOR and hash operation.The proposed scheme was evaluated from two aspects of security and performance.Theoretical design analysis and formal tool verification were carried out for security evaluation.The formal analysis tool, AVISPA, was used to verify the improved security of the proposed scheme in the presence of intruders.The performance was mainly evaluated from the computing cost and communication cost of the authentication scheme.The simulation results showed that the proposed scheme reduces communication cost, and the computational overhead can meet the needs of mobile terminals with limited resources.As the future work, the scheme will be improved from two aspects: one is to strengthen the scalability to ensure that users and edge servers can join and exit at any time, and the other one is to strengthen the universality of the scheme to meet the access deployment of third-party service providers.…”
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Land Use Analysis Using Machine-Learning Based on Cloud Computing Platform by Syukur Toha Prasetyo, Fahmi Arief Rahman, Sinar Suryawati, Slamet Supriyadi, Eko Setiawan

“…The application of machine-learning on a cloud computing platform (Google Earth Engine, GEE) in land use analysis enables efficient and rapid processing of spatial data on a wide scale. …”
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Future of Telepresence Services in the Evolving Fog Computing Environment: A Survey on Research and Use Cases by Dang Van Thang, Artem Volkov, Ammar Muthanna, Andrey Koucheryavy, Abdelhamied A. Ateya, Dushantha Nalin K. Jayakody

“…This survey investigates the convergence of telepresence services with fog computing, evaluating the latest advancements in research developments and practical use cases. …”
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Evaluating the value of machine learning models for predicting hematoma expansion in acute spontaneous intracerebral hemorrhage based on CT imaging features of hematomas and surrou... by Tianyu Yang, Tianyu Yang, Zhen Zhao, Yan Gu, Shengkai Yang, Yonggang Zhang, Lei Li, Ting Wang, Zhongchang Miao

“…ObjectiveThis study evaluates the utility of artificial intelligence (AI) for automated segmentation of intracranial hematomas and surrounding oedema in non-contrast computed tomography (CT) images. …”
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