Adaptive Real-Time Transmission in Large-Scale Satellite Networks Through Software-Defined-Networking-Based Domain Clustering and Random Linear Network Coding by Shangpeng Wang, Chenyuan Zhang, Yuchen Wu, Limin Liu, Jun Long

“…Experimental results indicate that the proposed method reduced resource allocation task execution time by at least 18.03% compared to traditional methods and enhanced task scheduling efficiency by at least 14.01%. …”
Get full text

A Game Theoretical Priority-Aware R2V Task Offloading Framework for Vehicular Fog Networks by Kinda Khawam, Maurice Khabbaz, Joe Saad

“…The first level utilizes a two-stage Stackelberg game to incentivize vehicles within RSU coverage to allocate a portion of their computing resources. The second level focuses on task assignment to participating vehicles. …”
Get full text

Artificial intelligence analysis in cyber domain: A review by Liguo Zhao, Derong Zhu, Wasswa Shafik, S Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, Alisa Craig

“…This method permits for the allocation of multiple log source types through a sliding time window and provides a scalable solution, which is a much-needed function.…”
Get full text

Machine Learning-Driven Multimodal Feature Extraction and Optimization Strategies for High-Speed Railway Station Area by Xiang Li, Fa Zhang, Ziyi Liu, Yao Wei, Runlong Dai, Zhiyue Qiu, Yuxin Gu, Hong Yuan

“…The nine-category strategic recommendations with defined quantitative threshold intervals provide decision-makers with visually intuitive, operationally implementable, and practically significant guidance for spatial planning and resource allocation.…”
Get full text

Path Algebra-Driven Classification Solution to Realize User-Centric Performance-Oriented Virtual Network Embeddings by Stelios Prekas, Panagiotis A. Karkazis, Panagiotis Trakadas

“…The intense diversity of the Next-Generation Networking environments like 6G and the forthcoming deployment of immersive applications with varied user-specific requirements transform the efficient allocation of resources into a real challenge. Traditional solutions like the shortest path algorithm and mono-constraint methodologies are inadequate to handle customized user-defined performance parameters and effectively classify physical resources according to these intricate demands. …”
Get full text

Optimizing wireless dynamic charging infrastructure for electric vehicles: A predictive and adaptive framework leveraging decision-dependent uncertainties and renewable energy util... by Yanjia Wang, Xianlong Li, Mohannad Alhazmi, Da Xie, Xitian Wang

“…By leveraging predictive analytics and decision-dependent uncertainty modeling, the proposed framework dynamically optimizes lane deployment, energy resource allocation, and operational strategies. The mathematical modeling captures multi-objective optimization goals, including cost minimization, renewable energy integration, carbon emission reduction, and system resilience under uncertainties. …”
Get full text

Superimposed Training-Based Channel Estimation for MIMO Relay Networks by Xiaoyan Xu, Jianjun Wu, Shubo Ren, Lingyang Song, Haige Xiang

“…Through the superposition of a group of additional training vectors at the relay subject to power allocation, the separated estimates of the source-relay and relay-destination channels can be obtained directly at the destination, and the accordance with the two-hop AF strategy can be guaranteed at the same time. …”
Get full text

A Study on Spatial and Temporal Changes and Synergies/Trade-Offs of the Production-Living-Ecological Functions in Mountainous Areas Based on the Niche Width Model by Yaling Li, Ruoying Song, Ping Ren

“…As a typical ecologically fragile mountainous area, Liangshan Yi Autonomous Prefecture in Sichuan Province faces challenges of irrational land resource allocation and uncoordinated urbanization. …”
Get full text

The moderating role of professional grief in the relationship between job stress dimensions and turnover intention among nurses by Xue Liang, Jue Wang

“…Methods This study utilized linear regression models and the Extreme Gradient Boosting machine (XGBoost) learning algorithm to analyze the impact of the total score of job stress and their dimensions on turnover intention. …”
Get full text

Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

“…Early and accurate prediction of acute kidney injury (AKI), disease severity, renal replacement therapy (RRT) requirements, and mortality risk is essential for timely identification of high-risk individuals, personalized treatment planning, and optimal allocation of healthcare resources. We aimed to develop and externally validate an interpretable multi-task machine learning (ML) model to predict four clinical outcomes in patients with rhabdomyolysis: AKI, disease severity, the need for RRT, and in-hospital mortality. …”
Get full text

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

“…This paper proposes a heterogeneous node deployment algorithm based on regional density, which divides the network regionally by raster and heterogeneous node communication range, and determines the optimal location of heterogeneous nodes by regional density, realizing the reasonable allocation and utilization of network resources. …”
Get full text

Toward Energy Efficiency and Fairness in UAV-Based Task Offloading by Mohamed El-Emary, Ali Ranjha, Diala Naboulsi, Razvan Stanica

“…The proposed system proves scalable and robust, making it suitable for real-time deployment in resource-constrained environments with dynamic workloads.…”
Get full text

Workload Forecasting Methods in Cloud Environments: An Overview by Samah Aziz, Manar Kashmoola

“…Cloud computing is becoming increasingly popular due to its on-demand resource allocation and scalability. It is essential to precisely anticipate workload as applications and users on cloud-based services increase to distribute resources effectively and avoid service interruptions. …”
Get full text

A crack detection and quantification method using matched filter and photograph reconstruction by Liu Zhen-liang, Zhou An, Ran Xin-ru, Wu Yun-peng, Zhao Wei-gang, Zhang Hao

“…This 3D model, annotated with detected cracks, provides an intuitive and comprehensive representation of bridge damage, facilitating informed decision making in maintenance planning and resource allocation. To verify the accuracy of the enhanced matched filter algorithm, it was compared with other digital image processing methods on public datasets, achieving average results of 97.9% for Pixel Accuracy (PA), 72.5% for the F1-score, and 58.1% for Intersection over Union (Iou) across three typical sub-datasets. …”
Get full text

Machine learning model for prediction of palliative care phases in patients with advanced cancer: a retrospective study by Junchen Guo, Yunyun Dai, Sishan Jiang, Junqingzhao Liu, Xianghua Xu, Yongyi Chen

“…Conclusions The prediction model developed in this study based on the machine learning algorithm showed good performance, offering significant potential for facilitating timely interventions, enhancing symptom management, and optimizing palliative care resource allocation in advanced cancer patients in mainland China.…”
Get full text

Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

“…Abstract For modeling dairy cattle data, fuzzy logic offers the capability to manage uncertainty, enhance accuracy, facilitate informed decision-making, and optimize resource allocation. A critical aspect of dairy cattle production is the modeling of mastitis, an udder infection that affects milk quality and yields significant economic consequences. …”
Get full text

Reliable transmission mechanism with differentiated protection in virtualized fiber-wireless access network by Ruyan WANG, Yishuang GAO, Xiao CHEN

“…In view of the different reliability requirements of network service,a reliable transmission mechanism with differentiated protection was proposed in virtualized fiber-wireless access network.The quality of protection required by users and the fees that can be paid were used as a prerequisite.The backup protection resources were flexibly allocated by quantifying the multi-level protection quality with the probability of recovery.Then,for reducing traffic congestion and the unprotected services,the level service differentiation algorithm was used to choose protection link which was satisfied with the level of protection quality.The results show the proposed mechanism has more advantages in terms of long-term benefit-to-cost ratio and underlying network resource overhead,and provides users with a more flexible virtual network transmission while satisfying users’ reliability requirements.…”
Get full text

Com-BIS: A Community-Based Barter Incentive Scheme in Socially Aware Networking by Li Liu, Qiuyuan Yang, Xiangjie Kong, Hannan Bin Liaqat, Ahmedin Mohammed Ahmed, Nakema Deonauth, Feng Xia

“…We consider this problem as a resource allocation problem and propose a community-based Barter incentive scheme for SAN paradigm (Com-BIS). …”
Get full text

Remaining Useful Life Prediction of Aero-Engine Based on Improved GWO and 1DCNN by Lihua Shen, Yucheng Wang, Baorui Du, Hailong Yang, He Fan

“…With the deepening adoption of whole-lifecycle management paradigms in aviation equipment, accurate prediction of remaining useful life has emerged as a pivotal technical enabler for ensuring flight safety and optimizing maintenance resource allocation. This study systematically addresses limitations in existing data-driven remaining useful life prediction methodologies through comprehensive optimizations spanning data preprocessing protocols and model architectural enhancements. …”
Get full text

Machine Learning and Deep Learning-Based Atmospheric Duct Interference Detection and Mitigation in TD-LTE Networks by Rasendram Muralitharan, Upul Jayasinghe, Roshan G. Ragel, Gyu Myoung Lee

“…This can adversely affect telecommunication systems, as cells with similar frequencies can interfere with each other due to frequency reuse, which is intended to optimize resource allocation. Thus, the downlink signals of one base station will travel a long distance via the atmospheric duct and interfere with the uplink signals of another base station. …”
Get full text