Prognosis of air quality index and air pollution using machine learning techniques by Mostafa M. Abdelmalek, Hatem Mahmoud, Hassan Shokry

“…While the dataset includes six pollutants (PM10, PM2.5, NO2, SO2, CO, and O3), only three—PM2.5, PM10, and CO—were selected for AQI prediction based on their higher feature importance as determined using the Random Forest technique. …”
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RGB-T Object Detection With Failure Scenarios by Qingwang Wang, Yuxuan Sun, Yongke Chi, Tao Shen

“…Finally, a kernel similarity-aware illumination module (KSIM) is introduced to dynamically adjust the weighting of RGB and thermal features by incorporating both illumination intensity and the similarity between modalities. …”
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Research on fault localization method of valve area in converter station based on metric learning and knowledge reasoning by WEI Yun, LI Xianwei, ZHANG Yanlong, CAO Hui, XU Dan, QIU Junhong

“…A data dimensionality reduction network based on metric learning is constructed to achieve feature extraction of recorded electrical quantities by maximizing inter class distance and minimizing intra class distance. …”
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Brokel: Towards enabling multi-level cloud elasticity on publish/subscribe brokers by Vinicius Facco Rodrigues, Ivam Guilherme Wendt, Rodrigo da Rosa Righi, Cristiano André da Costa, Jorge Luis Victória Barbosa, Antonio Marcos Alberti

“…Aiming at bypassing the aforesaid problems, this article proposes Brokel, a multi-level elasticity model for Pub/Sub brokers. …”
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Deep Learning-Based Prediction of Pitch Response for Floating Offshore Wind Turbines by Ruifeng Chen, Ke Zhang, Min Luo, Ye An, Lixiang Guo

“…The comprehensive framework, which encompasses feature selection, data processing, deep learning model construction, and interpretation, demonstrates significant potential for addressing a broad range of engineering problems through deep learning methodologies.…”
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Clinical manifestations in Egyptian Pompe disease patients: Molecular variability and enzyme replacement therapy (ERT) outcomes by Mohamed Abdelghafar Hussein, Heba ElTaher, Ranim Mahmoud, Donia Sobh, Mohammad Al-Haggar

“…This condition leads to muscle weakness, respiratory problems, and heart abnormalities in affected individuals. …”
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Improving the Reliability of Biometric Authentication Processes Using a Model for Reducing Data Drift by Vladimir Zh. Kuklin, Naur Z. Ivanov, Alexander N. Muranov, Islam A. Alexandrov, Elena Yu. Linskaya

“…Modern complexes providing biometric identification face several problems, such as information drift caused by the variability of facial patterns, voice timbres, and current states. …”
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Statistical Analysis of the Patterns of Global Investment Development in China by A. V. Loseva

“…Statistical analysis of the indicators of foreign investment activity of China over a long period of time allows us to evaluate and characterize its strategic behavior as one of the world’s largest investors, focused primarily on solving the problems of developing its own economy and its global expansion in the long term. …”
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Flight safety level improvement methodology based on the pilot model by A. D. Barabash, S. F. Borodkin, M. A. Kiselev, Yu. V. Petrov

“…This is specified by a wide variety of problems that require the search for complex, interconnected solutions. …”
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Fast evaluation on the fatigue level of copper contact wire based on laser induced breakdown spectroscopy and supervised machine learning for high speed railway by Wenfu Wei, Langyu Xia, Zefeng Yang, Huan Zhang, Like Pan, Jian Wu, Guangning Wu

“…This mechanical fatigue can lead to a decrease in the mechanical strength of the contact wire, and ultimately lead to problems such as wire detachment, fracture, or breakage, posing a serious safety hazard to the electrified railway system. …”
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Green Apple Detector Based on Optimized Deformable Detection Transformer by Qiaolian Liu, Hu Meng, Ruina Zhao, Xiaohui Ma, Ting Zhang, Weikuan Jia

“…The new method first introduces the ResNeXt network to extract image features to reduce information loss in the feature extraction process; secondly, it improves the accuracy and optimizes the detection results through the deformable attention mechanism; and finally, it uses a feed-forward network to predict the detection results. …”
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Deep Forest Modeling: An Interpretable Deep Learning Method for Mineral Prospectivity Mapping by Yue‐Lin Dong, Zhen‐Jie Zhang

“…Feature importance analysis shows that geological structure and magmatism significantly influence PCD prediction. …”
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Synergizing TabNet and SHAP for PM10 Forecasting: Insights From Makkah, Saudi Arabia by Abdulrazak H. Almaliki, Afaq Khattak

“…This study utilizes the TabNet model to estimate PM10 concentrations, taking advantage of its ability to perform sparse feature selection and sequential decision-making to uncover complex relationships among different environmental variables. …”
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Robotic arm target detection algorithm combined with deep learning by ZHANG Lei, ZHANG Wang, YUAN Yuan

“…Existing target detection algorithms deployed on robotic arms would occupy a large amount of system resources, have poor real-time detection performance, and have a large number of model parameters. To address these problems, an improved YOLOv5 target detection algorithm was proposed. …”
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Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…Besides, the Improved Osprey Optimization Algorithm (IOOA)-based feature selection is employed to classify the most relevant features, enhancing the efficiency of the system by reducing dimensionality. …”
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A low cost compact network TAP device with Raspberry Pi 4 by Murat Varol, Murat İskefiyeli

“…There is a necessarity to monitor the network to detect any kind of attacks or problems. Determining which device is the source of the problem and vulnerability is also a problem. …”
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Few-shot Named Entity Recognition via encoder and class intervention by Long Ding, Chunping Ouyang, Yongbin Liu, Zhihua Tao, Yaping Wan, Zheng Gao

“…However, prior knowledge may become a confounding factor affecting the relation between sample features and real labels. This problem leads to bias and difficulty accurately capturing class. …”
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Contrastive Transformer Network for Track Segment Association with Two-Stage Online Method by Zongqing Cao, Bing Liu, Jianchao Yang, Ke Tan, Zheng Dai, Xingyu Lu, Hong Gu

“…Traditional methods often rely on simplistic assumptions about target motion and statistical techniques for track association, leading to problems such as unrealistic assumptions, susceptibility to noise, and suboptimal performance limits. …”
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Toward Sustainable Agriculture: DPA-UNet for Semantic Segmentation of Landscapes Using Remote Sensing Imagery by J. Kavipriya, G. Vadivu

“…This work presents a new architecture called Deep Pro Agri-UNet (DPA-UNet) meant specifically for agricultural field segmentation with high-resolution images sourced from Google Earth Pro in order to solve these problems. DPA-UNet improves the model’s ability to extract discriminative features and properly separate spectrally similar land classes by means of a multi-branch spatial and channel attention mechanism at the model’s bottleneck layer. …”
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Graph-theoretical model of global human interactome reveals enhanced long-range communicability in cancer networks. by Evgeny Gladilin

“…As an alternative to compact differential signatures, global features of genetic cell machinery are conceivable. …”
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