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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Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…Secondly, to address missing values and noise in the data, preprocessing methods such as denoising, normalization, and feature extraction are employed to ensure data quality and model accuracy. Finally, in the selection of ML models, this study experiments with several common algorithms, including extreme gradient boosting (XGBoost), support vector machine (SVM), random forest (RF), and deep neural network (DNN). …”
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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

“…The result analysis of the various computerized experiments reveals that the time of algorithms are 2.13s for ciphering/hiding and 1.57s for deciphering/extracting. …”
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HOLa: HoloLens Object Labeling by Schwimmbeck Michael, Khajarian Serouj, Holzapfel Konstantin, Schmidt Johannes, Remmele Stefanie

“…As segmentation foundation models like the Segment Anything Model (SAM) begin to emerge, zero-shot segmentation requires only minimal human participation obtaining high-quality object masks. We introduce a HoloLens-Object-Labeling (HOLa) Unity and Python application based on the SAM-Track algorithm that offers fully automatic single object annotation for HoloLens 2 while requiring minimal human participation. …”
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Classroom Expression Recognition Based on Deep Learning by Yang Gao, Linyan Zhou, Jialiang He

“…In the field of education, classroom expression recognition technology has important application value. It can help teachers understand students’ emotions and learning attitudes and adjust teaching strategies in time to improve learning outcomes. …”
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Incentive Mechanism for Cloud Service Offloading in Edge–Cloud Computing Environment by Chendie Yao, Junjie Xie, Zhong Liu

“…In such edge–cloud computing environments, many cloud providers intend to offload cloud services to the edge nodes to offer high-quality services for data-intensive and latency-sensitive applications. …”
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Machine learning analysis of cardiovascular risk factors and their associations with hearing loss by Ali Nabavi, Farimah Safari, Ali Faramarzi, Mohammad Kashkooli, Meskerem Aleka Kebede, Tesfamariam Aklilu, Leo Anthony Celi

“…The accurate models identify high-risk groups, enabling timely intervention to improve quality of life. The subtle changes in hearing often go unnoticed, presenting a challenge for early hearing loss detection. …”
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Comparative analysis of single-view and multiple-view data collection strategies for detecting partially-occluded grape bunches: Field trials by Mar Ariza-Sentís, Hilmy Baja, Sergio Vélez, Rick van Essen, João Valente

“…This study compares two data acquisition methodologies for grape bunch detection and tracking in a commercial vineyard where leaf removal was not performed: a traditional single-view approach and a multiple-viewing method designed to mitigate fruit occlusion issues. The PointTrack algorithm, trained and validated using MOTS annotations, was employed to evaluate detection and tracking performance through metrics of three trials. …”
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PCA and PSO based optimized support vector machine for efficient intrusion detection in internet of things by Mutkule Prasad Raghunath, Shyam Deshmukh, Poonam Chaudhari, Sunil L. Bangare, Kishori Kasat, Mohan Awasthy, Batyrkhan Omarov, Rajesh R. Waghulde

“…After completing the preparation step, the data set is classified using several machine learning techniques such as support vector machine, linear regression, and random forest. Evaluating the veracity, exactness, and retrieval rate of different machine learning algorithms is crucial for choosing the most effective ones. …”
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Streaming LiDAR Scene Flow Estimation by Mazen Abdelfattah, Z. Jane Wang, Rabab Ward

“…This achieves substantial speedups while maintaining, and in some cases surpassing, full-scan accuracy. We rigorously evaluate our approach on the challenging Waymo and Argoverse datasets, demonstrating significant latency reduction without compromising scene flow quality. …”
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Use machine learning to predict treatment outcome of early childhood caries by Yafei Wu, Maoni Jia, Ya Fang, Duangporn Duangthip, Chun Hung Chu, Sherry Shiqian Gao

“…The aim of this study is to explore the application of machine learning in predicting the treatment outcome of ECC. …”
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The Efficiency of Complex Differential Treatment of the Patients with Systemic Lupus Erythematous Considering the Features of Bone Tissue Structure Remodeling by Abrahamovych U., Tsyhanyk L., Abrahamovych O., Farmaha M., Romaniuk O.

“…Received data testify to the fact of a reliably higher efficiency of our suggested differential treatment of bones for the patients with SLE. The evaluation of the application forms of LQ proves this fact. …”
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Artificial intelligence in psychiatry: A systematic review and meta-analysis of diagnostic and therapeutic efficacy by Moustaq Karim Khan Rony, Dipak Chandra Das, Most. Tahmina Khatun, Silvia Ferdousi, Mosammat Ruma Akter, Mst. Amena Khatun, Most. Hasina Begum, Md Ibrahim Khalil, Mst. Rina Parvin, Daifallah M Alrazeeni, Fazila Akter

“…The risk of bias assessment indicated high methodological rigor in most studies, though challenges like algorithmic biases and data quality remain. Conclusion AI demonstrates robust diagnostic and therapeutic capabilities in psychiatry, offering a data-driven approach to personalized mental healthcare. …”
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Integrating Multiple RIS for Enhanced SWIPT-IoT Performance: Optimization Strategies by Neha Sharma, Sumit Gautam, Symeon Chatzinotas, Bjorn Ottersten

“…Reconfigurable Intelligent Surfaces (RIS) are revolutionizing wireless communications by enhancing signal quality and extending network coverage, particularly in remotely located Internet-of-Things (IoT) applications. …”
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Investigation of the physically unclonable function of a configurable ring oscillator by A. A. Ivaniuk

“…This serves as a foundation for exploring new methods and algorithms for calculating unique PUF responses.…”
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A New Efficient Approach to Model Stiff Biogeochemical Reactive Transport Scenarios Across Groundwater Systems by Xiaochuang Bu, Heng Dai, Songhu Yuan, Ming Ye, Zhenxue Dai, Mohamad Reza Soltanian, Zhang Wen, Alberto Guadagnini

“…Overall, our approach offers a robust and efficient solution for modeling stiff biogeochemical processes in groundwater systems. Its successful application to diverse reaction networks highlights its potential for broad implementation in environmental and engineering contexts, paving the way for accurate and computationally feasible groundwater quality assessments.…”
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Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence by Sahar Rezaei, Farzan Asadirad, Alireza Motamedi, Mohammadsadegh Kamran, Farzaneh Parsa, Haniyeh Samimi, Parna Ghannadikhosh, Mahdi Zahmatyar, Seyed Ali Hosseinzadeh, Hossein Arabi

“…Through systematic analysis of 11 key studies across multiple international databases, we evaluated various AI architectures, including machine learning algorithms and deep learning networks, applied to qEEG data for AD detection. …”
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River total dissolved gas prediction using a hybrid greedy-stepwise feature selection and bidirectional long short-term memory model by Khabat Khosravi, Salim Heddam, Changhyun Jun, Sayed M. Bateni, Dongkyun Kim, Essam Heggy

“…Each model is trained and evaluated at one station and validated at the second station to assess transferability and generalization capability. …”
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An approach to forecasting damage due to unfavorable circumstances associated with indistinguishability of source data by V. F. Zolotukhin, A. V. Matershev, L. A. Podkolzina

“…The efficiency of predicting damage to complex systems depends directly on the quality of processing methods, systematization, and the amount of input data. …”
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