Hiromitsu Goto,Wataru Souma
Hiromitsu Goto
Against the backdrop of electrification and supply chain resilience, the global automotive industry is in an era of great transformation. Using component supply information provided by MarkLines, this study investigated the impact on inter-...
AI applied to Saudi Arabia higher education: systematic literature review-SLR with PRISMA and VOSviewer [0.03%]
应用于沙特阿拉伯高等教育的AI系统化文献回顾（SLR）：具有PRISMA和VOS viewer的方法
Jehad Alqurni
Jehad Alqurni
This study explored the role of artificial intelligence in higher education in Saudi Arabia. It aims to identify trends, key contributors, influential papers, collaborations, and important research areas from January 2022 to February 2026 t...
A cost-sensitive random forest framework for ARP spoofing detection in Internet of Medical Things networks [0.03%]
一种成本敏感的随机森林框架，用于医疗事物网络中的ARP欺骗检测
Siddhartha Singhal,Kakelli Anil Kumar
Siddhartha Singhal
Introduction: ARP spoofing poses a major security threat to Internet of Medical Things (IoMT) networks by enabling man-in-the-middle attacks that compromise the integrity of life-critical communications. Existing intrusio...
Machine learning approach for predicting the severity risk of obstructive sleep apnea syndrome [0.03%]
机器学习预测阻塞性睡眠呼吸暂停综合征严重程度风险的模型研究
Qi Wang,Xiaoyu Yang,Shuran Xu et al.
Qi Wang et al.
Background: Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) has a high global prevalence and is prone to causing various serious complications. Our objective is to develop severity stratification of OSAHS by integrating...
A dataset-centric review of IoT and IIoT intrusion detection: realism, evaluation biases, and future research directions [0.03%]
从数据集角度回顾物联网和工业物联网的入侵检测：现实情况、评估偏差及未来研究方向
Dwarsala Sreedhar Reddy,Kakelli Anil Kumar
Dwarsala Sreedhar Reddy
The rapid growth of IoT and IIoT expands the cyber-attack surface of interconnected and safety-critical systems, and, as such, IDSs have become a fundamental security mechanism. Although very impressive results have been reported for machin...
Noise-robust temporal-spectral fusion transformers for EEG-based cognitive state classification in aviation environments [0.03%]
基于EEG的认知状态分类的鲁棒时频融合变压器在航空环境中的应用
Quynh Anh Nguyen,Nam Anh Dao,Long Nguyen
Quynh Anh Nguyen
Attention-related Pilot Performance Decrements (APPD) contribute substantially to aviation incidents, yet existing electroencephalography (EEG)-based monitoring methods often lack generalization, robustness to noise, and effective temporal-...
A prognostic tool for pulmonary collapse: nomogram-based prediction of 28-day mortality [0.03%]
预测肺不张28天内死亡率的预后模型
Xinming He,Wenchong Yu,Yuling Li et al.
Xinming He et al.
Background: Pulmonary collapse is a common and serious respiratory condition, but there is no dedicated bedside tool to estimate prognosis. This study aimed to develop a nomogram to predict 28-day mortality in patients wi...
Evolutionary multi-agent reinforcement learning for crisis-aware demographic policy optimization [0.03%]
基于危机意识的进化型多智能体强化学习人口政策优化方法研究
Anton V Dozhdikov,Arseniy M Sitkovskiy
Anton V Dozhdikov
Demographic systems face unprecedented challenges from simultaneous crises. Conventional statistical demography techniques and agent-based models often struggle to capture nonlinear inter-regional interactions during periods of severe socio...
Influence of localized roadway surface obstacles on vehicular emissions under real-world urban driving conditions [0.03%]
城市道路局部障碍物对车辆排放影响研究
Victor Cardoso Oliveira,Thiago Iachiley Araújo de Souza,Nicole Souza Batista et al.
Victor Cardoso Oliveira et al.
Introduction: Vehicular emissions are a major source of air pollution in tropical urban environments. While the impacts of technology, traffic flow, and driving behavior on pollutant formation are well established, the in...
Adaptive class-aware feature selection for high-dimensional and imbalanced multi-class network intrusion detection [0.03%]
自适应类感知特征选择在高维和不平衡的多类网络入侵检测中的应用
Joseph P Mchina,Neema Mduma,Ramadhani S Sinde
Joseph P Mchina
High-dimensional feature spaces and severe class imbalance remain fundamental challenges for Machine Learning-based Network Intrusion Detection Systems (ML-NIDS), where minority attack categories are frequently overlooked during feature sel...