Flexural Capacity Prediction of RC Beams Strengthened in Terms of NSM System Using Soft Computing by Amin Raeisi, Mohammad Kazem Sharbatdar, Hosein Naderpour, Pouyan Fakharian

“…In the first stage, A comprehensive and reliable database has been developed to leverage the predictive accuracy of neural networks in the computation of the flexural capacity of reinforced beams that utilize near-surface mounted reinforcement. …”
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Application of 5G + edge computing technology in intelligent monitoring construction of electricity business office by Wei Cui, Junwei Li, Wei Ge, Bo Zhang, Tianwei Liu

“…Abstract This paper proposes an architecture design of intelligent electric power business hall based on 5G + edge computing technology, which includes three layers: business layer, platform layer and network layer, and realizes intelligent service, management and operation and maintenance of electric power business hall. …”
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Advancing Emotionally Aware Child–Robot Interaction with Biophysical Data and Insight-Driven Affective Computing by Diego Resende Faria, Amie Louise Godkin, Pedro Paulo da Silva Ayrosa

“…This paper investigates the integration of affective computing techniques using biophysical data to advance emotionally aware machines and enhance child–robot interaction (CRI). …”
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Efficient Resource Allocation for Blockchain-Enabled Mobile Edge Computing: A Joint Optimization Approach by Moein Valitabar, Mohammad Fathi, Keivan Navaie

“…Performance evaluation results demonstrate the effectiveness of these algorithms, achieving significant reductions in total energy consumption while maximizing the efficiency of communication and computational resources. …”
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Evaluating a distance function by Abgrall, Rémi

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StrideHD: A Binary Hyperdimensional Computing System Utilizing Window Striding for Image Classification by Dehua Liang, Jun Shiomi, Noriyuki Miura, Hiromitsu Awano

“…Hyper-Dimensional (HD) computing is a brain-inspired learning approach for efficient and fast learning on today’s embedded devices. …”
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Evaluating epidemic forecasts in an interval format. by Johannes Bracher, Evan L Ray, Tilmann Gneiting, Nicholas G Reich

“…This article provides an overview of how established methods for the evaluation of quantile and interval forecasts can be applied to epidemic forecasts in this format. …”
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Evaluation of myocardial blood flow and coronary flow reserve — the physiological foundation and clinical significance of myocardial perfusion scintigraphy in the examination of pa... by A. V. Mochula, A. N. Maltseva, V. V. Shipulin, K. V. Zavadovsky

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Wordline Input Bias Scheme for Neural Network Implementation in 3D-NAND Flash by Hwiho Hwang, Gyeonghae Kim, Dayeon Yu, Hyungjin Kim

“…In this study, we propose a neuromorphic computing system based on a 3D-NAND flash architecture that utilizes analog input voltages applied through wordlines (WLs). …”
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Application-oriented resource matching model based on trust for internet-based virtual computing environment by Chun-ge ZHU, Xin-ran LIU, Yi-xian YANG, Hong ZHANG

“…In order to solve the problem of reasonable resource s ing in the virtual computing environment (iVCE),a resource matching model,based on trust “resource sliding window” model,was proposed.Firstly,the resources were classified in advance by their static properties.Then the resource nodes were evaluated by a trust model based on the time window and Bayesian algorithm,and the evaluated results as well as the resource load were fused to determine the levels of the dynamic real-time performance.Finally,the scheduling resources were allocated according to the comprehensive assessment of the static and dynamic properties of the resource nodes.The proposed model provides a basis of scheduling strategy for different resources with different tasks and attributes,thus achieving the goal of “proper resources’ serving proper tasks”.Simulation results show that,compared the previous scheduling algorithm,the proposed model has better performance in the success rate of task execution and the rate of resource utilization.…”
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A Secure Key-Aggregate Keyword Retrieval Scheme Over Encrypted Data in Cloud Computing by Chunwei Lou, Mingsheng Cao, Yaohua Luo, Hua Xu, Yuan Gao, Weiwei Wang, Dong Wang

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Modified grey wolf optimization for energy-efficient internet of things task scheduling in fog computing by Deafallah Alsadie, Musleh Alsulami

“…Abstract Fog-cloud computing has emerged as a transformative paradigm for managing the growing demands of Internet of Things (IoT) applications, where efficient task scheduling is crucial for optimizing system performance. …”
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Dynamic load balancing in cloud computing using predictive graph networks and adaptive neural scheduling by K. Rajammal, M. Chinnadurai

“…Additionally, reinforcement learning is incorporated in the proposed work to optimize SNN decisions based on feedback from the TGNN’s state predictions. Experimental evaluations of the proposed model with diverse workload scenarios demonstrate significant improvements in terms of throughput, energy efficiency, make span and response time. …”
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Evaluation mechanism of urban green competitiveness via a gray fuzzy comprehensive evaluation model by Cheng Wang, Xiyin Qiu, Hui Shen, Congjun Rao

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Enhancing Property-Based Token Attestation With Homomorphic Encryption (PTA-HE) for Secure Mobile Computing by Thinh Le Vinh, Huan Thien Tran, Samia Bouzefrane

“…Our main contributions are: the introduction of PTA-HE, which resolves these vulnerabilities by enabling computations directly on encrypted data, ensuring continuous protection and resilience against unauthorized access and manipulation; a strategic employment of Trusted Third Parties (TTPs) for secure attestation management, leveraging HE to maintain data confidentiality throughout the entire attestation workflow; rigorous experimental evaluations quantifying computational overhead, communication costs, latency, and scalability implications, transparently illustrating the performance trade-offs associated with enhanced security; and formal verification using the Scyther tool demonstrating PTA-HE’s superior correctness and robustness against multiple security threats, such as replay and man-in-the-middle attacks. …”
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Real-time human-robot interaction and service provision using hybrid intelligent computing framework. by Mohammed Albekairi, Meshari D Alanazi, Turki M Alanazi, Mohamed Vall O Mohamed, Khaled Kaaniche, Anis Sahbani, Ali Elrashidi

“…This research introduces a Hybrid Intelligent Computing Model (HICM) to improve robots' ability to process inquiries autonomously. …”
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Energy-aware federated learning for secure edge computing in 5G-enabled IoT networks by Milad Rahmati

“…Our method dynamically selects participating IoT devices based on energy constraints and computational capacity, reducing unnecessary communication overhead. …”
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Stage-based colorectal cancer prediction on uncertain dataset using rough computing and LSTM models by K. Supriya, A. Anitha

“…Abstract Artificial intelligence (AI) is an attractive field of Computer Science that helps to classify and to predict various real-time applications. …”
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Federated Learning With Sailfish-Optimized Ensemble Models for Anomaly Detection in IoT Edge Computing Environment by Aravam Babu, A. Bagubali

“…Traditional centralized approaches suffer from computational inefficiencies, increased latency, and privacy concerns, making them unsuitable for real-time anomaly detection in distributed IoT environments. …”
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SmartBoot: Real-Time Monitoring of Patient Activity via Remote Edge Computing Technologies by Gozde Cay, Myeounggon Lee, David G. Armstrong, Bijan Najafi

“…Adherence to offloading devices is critical for wound healing but remains inadequately monitored in real-world settings. This study evaluates the SmartBoot edge-computing system—a wearable, real-time remote monitoring solution integrating an inertial measurement unit (Sensoria Core) and smartwatch—for its validity in quantifying cadence and step count as digital biomarkers of frailty, and for detecting adherence. …”
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