Real-Time Estimation Method of P-Wave Slowness Based on Kalman Filtering and STC by SUN Hao, CHEN Wenhui, SUN Xuekai, YU Weidong, LI Siyi, ZHAO Peng

“…The real-time extraction of acoustic interval time is of significant importance for rapidly evaluating reservoir quality and timely optimizing exploration and development decisions. …”
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A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach by Yuli Wang, Na Mei, Ziyi Zhou, Yuan Fang, Jiacheng Lin, Fanchen Zhao, Zhihong Fang, Yan Li

“…Finally, critical variables in the optimal model were screened based on the interpretable algorithms to build a decision tree to facilitate clinical application. …”
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Boosting Crowdsourced Annotation Accuracy: Small Loss Filtering and Augmentation-Driven Training by Yanming Fu, Weigeng Han, Jingsang Yang, Haodong Lu, Xin Yu

“…However, the labels provided by untrained crowdsourcing workers often contain a considerable amount of noise. Although the application of ground truth inference algorithms to deduce integrated labels effectively enhances label quality, a certain level of noise persists. …”
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DIFshilling: A Diffusion Model for Shilling Attacks by Weizhi Chen, Xingkong Ma, Bo Liu

“…Many current approaches either fail to capture the natural distribution of real user data or are highly tailored to specific RS algorithms, limiting their general applicability and effectiveness. …”
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Triple-layered security system: reliable and secured image communications over 5G and beyond networks by Tarek Srour, Mohsen A. M. El-Bendary, Mostafa Eltokhy, Atef E. Abouelazm

“…This paper presents the proposed vision of 5G and beyond security to build a research gap of existing and related technique that lack the adaptation, boosting gradient and complexity analysis, through design and evaluate the adapted and graded security system. This paper focuses on designing a security approach to make up the lacks of existing techniques. …”
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Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Data extraction focused on device types, sensor quality, compliance with health standards, and the predictive algorithms employed.ResultsWearable devices show promise in correlating physiological markers with CP, but few studies integrate predictive models. …”
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Opposition-based chaotic evolution for optimization by Tianshui Li, Yan Pei

“…The findings support the broader applicability of OBCE in real-world engineering design problems where solution quality and efficiency are critical.…”
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Microgrid Resilience Enhancement with Sensor Network-Based Monitoring and Risk Assessment Involving Uncertain Data by Tangxiao Yuan, Kossigan Roland Assilevi, Kondo Hloindo Adjallah, Ayité Sénah A. Ajavon, Huifen Wang

“…Subsequently, a decision risk assessment framework is constructed, integrating data quality evaluation and operational risk considerations, to drive strategy optimization through in-depth data analysis. …”
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Pixel-Based Long-Wave Infrared Spectral Image Reconstruction Using a Hierarchical Spectral Transformer by Zi Wang, Yang Yang, Liyin Yuan, Chunlai Li, Jianyu Wang

“…Recent advancements in computational spectral imaging, powered by advanced algorithms, have enabled the acquisition of high-quality spectral images in real time, such as with the Uncooled Snapshot Infrared Spectrometer (USIRS). …”
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Comparative Study on EDM Wire Cutting and CO2 Laser Cutting for High‐Precision Stainless Steel Sheet Processing by A. Parthiban, K. Ananthakumar, S. Ajith Arul Daniel, S. Sivaganesan, T. Sathish, Jayant Giri, A. Johnson Santhosh, Ahmad O. Hourani

“…This study conducts a comprehensive experimental analysis of these techniques, focusing on their performance when cutting stainless steel grades AISI 316L and 304. The research evaluates key process parameters influencing the cut quality, aiming to achieve minimal surface roughness. …”
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The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…Abstract This study addresses key challenges in optimizing agricultural industry structures and facilitating intelligent transformation through the application of deep learning algorithms and advanced optimization techniques. …”
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Capability-driven framework to automate discovery of bounded contexts in large-scale requirements engineering by Shohreh Ajoudanian, Maryam Nooraei Abadeh

“…We also provide the applicability of the approach from various points of view including quality and stability of bounded contexts, average precision, and query assessment. …”
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The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

“…For instance, machine learning models can evaluate patient records, lifestyle factors, and genetic information to deliver precise risk assessments and personalized recommendations. …”
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Enhancing classification of a large lower-limb motor imagery EEG dataset for BCI in knee pain patients by Chongwen Zuo, Yi Yin, Haochong Wang, Zhiyang Zheng, Xiaoyan Ma, Yuan Yang, Jue Wang, Shan Wang, Zi-gang Huang, Chaoqun Ye

“…This study evaluates the feasibility of applying an MI-BCI model to a large dataset of knee pain patients, utilizing a novel deep learning algorithm for signal decoding. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…By adopting scalable AI models and fostering interdisciplinary collaborations, healthcare systems can overcome existing barriers, integrating AI seamlessly into infection control policies and ultimately enhancing patient safety and care quality. Further research is needed to evaluate cost-effectiveness, real-world applications, and strategies (e.g., clinician training and the integration of explainable AI) to improve trust and broaden clinical adoption.…”
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Harnessing quantum power: Revolutionizing materials design through advanced quantum computation by Zikang Guo, Rui Li, Xianfeng He, Jiang Guo, Shenghong Ju

“…We introduce the loop framework for QUBO‐empowered materials design, including constructing high‐quality datasets that capture critical material properties, employing tailored computational methods for precise material modeling, developing advanced figures of merit to evaluate performance metrics, and utilizing quantum optimization algorithms to discover optimal materials. …”
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Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis. by Claudia Bühnemann, Simon Li, Haiyue Yu, Harriet Branford White, Karl L Schäfer, Antonio Llombart-Bosch, Isidro Machado, Piero Picci, Pancras C W Hogendoorn, Nicholas A Athanasou, J Alison Noble, A Bassim Hassan

“…Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality controlled tumour material could be achieved. …”
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Information Bottleneck-Based Domain Adaptation for Hybrid Deep Learning in Scalable Network Slicing by Tianlun Hu, Qi Liao, Qiang Liu, Georg Carle

“…Evaluating on a multi-cell network with time-varying slice configurations, the VIB-enhanced IDLA algorithm outperforms baselines such as heuristic and deep reinforcement learning-based solutions, achieving twice the convergence speed and 16.52% higher asymptotic performance after slicing configuration changes. …”
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Inferring Travel Modes from Cellular Signaling Data Based on the Gated Recurrent Unit Neural Network by Yanchen Wang, Fei Yang, Li He, Haode Liu, Li Tan, Cheng Wang

“…However, due to data privacy issues, the empirical evaluation of the performance of different identification methods is not yet sufficient. …”
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Radiomic Feature Extraction Based on Computed Tomography for Stroke Patients by Alamgir Hossain, Jolly Sultana, Shahed Hossain, Hafizur Rahman

“…Conclusion: In summary, stroke imaging analysis benefits greatly from the deployment of complex image processing techniques, reliable feature extraction methods, and cutting-edge segmentation algorithms. Accurate stroke lesion identification and stratification are made possible by the thorough assessment of diagnostic parameters such as ROC curves and the application of visualization tools such as heatmaps.…”
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