The development of a disruption responsive smart room technology with attendance management system by Jennifer P. Juaneza

“…It outlines the key features of the technology, such as the use of sensors to identify environmental changes, the creation of algorithms to comprehend and react to these changes, and the integration of smart devices to facilitate smooth communication and control. …”
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The Aboveground Biomass Estimation of the Grain for Green Program Stands Using UAV-LiDAR and Sentinel-2 Data by Gaoke Yueliang, Gentana Ge, Xiaosong Li, Cuicui Ji, Tiancan Wang, Tong Shen, Yubo Zhi, Chaochao Chen, Licheng Zhao

“…Key variables such as tasseled cap greenness (TCG), red-edge normalized difference vegetation index (RENDVI), and visible-band difference vegetation index (VDVI) were identified as highly important. …”
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Machine learning-based identification of histone deacetylase-associated prognostic factors and prognostic modeling for low-grade glioma by Keshan Wen, Weijie Zhu, Ziyi Luo, Wei Wang

“…Prognostic accuracy was evaluated using Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curves. …”
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Photodynamic therapy in the treatment of recurrent nasal cavity and paranasal sinus cancer by M. V. Vusik, V. I. Shtin, O. V. Cheremisina, K. Yu. Menshikov, V. A. Novikov

“…The purpose of the study was to evaluate the effectiveness of treatment of patients with recurrent nasal cavity and paranasal sinus cancer using photodynamic diagnosis (PDD) and photodynamic therapy (FDT).Material and Methods. …”
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Identification and mechanism analysis of biomarkers related to butyrate metabolism in COVID-19 patients by Wenchao Zhou, Hui Li, Juan Zhang, Changsheng Liu, Dan Liu, Xupeng Chen, Jing Ouyang, Tian Zeng, Shuang Peng, Fan Ouyang, Yunzhu Long, Yukun Li

“…Six machine learning algorithms were employed to determine the best model for identifying biomarkers, and receiver operating characteristic (ROC) curves were plotted to evaluate the diagnostic value of the biomarkers in COVID-19. …”
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OpenSRANE, a Flexible and Extensible Platform for Quantitative Risk Assessment of NaTech Events by Bijan SayyafZadeh, Abdolreza S. Moghadam, Mahdi Sahrifi, Eslam Kashi

“…The software is based on the Monte Carlo method, but it is possible to implement other algorithms and approaches to it. Object-oriented programming and separation of the different parts of the software can increase the readability of the program, allowing researchers in different disciplines to focus easily on studying or developing the desired part with minimal interference from other parts. …”
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Efficiency of the Photoluminescent Method for Monitoring the Homogeneity of Feed Mixtures in Animal Husbandry by M. V. Belyakov, E. A. Nikitin, I. Yu. Efremenkov

“…The spectral evaluation systems for controlling the feed mixtures homogeneity were analyzed. …”
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A Robust Conformal Framework for IoT-Based Predictive Maintenance by Alberto Moccardi, Claudia Conte, Rajib Chandra Ghosh, Francesco Moscato

“…At its core, this paper leverages the commercial modular aero-propulsion system simulation (CMAPSS) dataset to evaluate different artificial intelligence (AI) prognostic algorithms for remaining useful life (RUL) forecasting while supporting the estimation of a robust confidence interval (CI). …”
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Assessing the Cause of Death for Men with Prostate Cancer Using Official Mortality Statistics or a Dedicated Cause of Death Committee: Results from 30-year ERSPC Rotterdam Data by Sebastiaan Remmers, Ivo I. de Vos, Frederique B. Denijs, Renée C.A. Leenen, Tycho M.T.W. Lock, Arjen Noordzij, Wim J. Kirkels, Chris H. Bangma, Monique J. Roobol

“…For men with prostate cancer (PCa) within the European Randomized Study of Screening for Prostate Cancer (ERSPC), the cause of death is determined by a Cause of Death Committee (CODC) that evaluates all medical records using a fixed algorithm. …”
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Influence disabling the cylynders of internal combustion engine on working process earthmovers machines by S. S. Zhuravlev

“…The article considers the effects of disabling the cylinder to change the characteristics of the engine earth-moving machines in various operating modes, calculated the diesel engines with subsequent analysis of their performance under different algorithms disable cylinders, evaluated the possibility of using additional flywheel to increase the technological parameters of the machine during operation.…”
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Effectiveness of machine learning models in diagnosis of heart disease: a comparative study by Waleed Alsabhan, Abdullah Alfadhly

“…By subjecting the ML models to exhaustive experimentation, this study evaluates the effects of different feature scaling, namely standardization, minmax scaling, and normalization technique on their performance. …”
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Machine Learning-Based Classification for Crop-Type Mapping Using the Fusion of High-Resolution Satellite Imagery in a Semiarid Area by Aicha Moumni, Abderrahman Lahrouni

“…The monitoring of cultivated crops and the types of different land covers is a relevant environmental and economic issue for agricultural lands management and crop yield prediction. …”
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Automated Vertebral Bone Quality Determination from T1-Weighted Lumbar Spine MRI Data Using a Hybrid Convolutional Neural Network–Transformer Neural Network by Kristian Stojšić, Dina Miletić Rigo, Slaven Jurković

“…These methods use different algorithms for CSF extraction from the segmentation of the spinal canal using T1- and T2-weighted image data and applying erosion to the vertebral ROI to avoid a sharp change in SI at the edge of the vertebral body.…”
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An efficient interpretable framework for unsupervised low, very low and extreme birth weight detection. by Ali Nawaz, Amir Ahmad, Shehroz S Khan, Mohammad Mehedy Masud, Nadirah Ghenimi, Luai A Ahmed

“…We employed fourteen different anomaly detection algorithms and evaluated their performance using Area Under the Receiver Operating Characteristics (AUCROC) and Area Under the Precision-Recall Curve (AUCPR) metrics. …”
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Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis by Hanglin Cheng, Yihao Li, Ruiheng Zhang, Weiguang Zhang

“…The image quality of different blending methods was quantitatively evaluated using metrics such as structural similarity index and peak signal-to-noise ratio, as well as Depthanything. …”
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Forage biomass estimation using UAV-based remote sensing and machine learning: A tool for assessing management practices by Biquan Zhao, Jeremy Hiller, Tala Awada, Brian Wardlow, Galen Erickson, Yeyin Shi

“…Using UAV-derived forage dry matter (DM) maps collected over two years from for managed Bromus inermis dominated pastures in eastern Nebraska, we evaluated the impacts of grazing and fertilization management practices on biomass. …”
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Pre-transplant IE1-specific T-cell response and CD8+ T-cell count as predictive markers of treated HCMV reactivation in kidney transplant recipients by Federica Zavaglio, Irene Cassanti, Irene Cassanti, Marilena Gregorini, Marilena Gregorini, Maria Antonietta Grignano, Teresa Rampino, Daniele Lilleri, Fausto Baldanti, Fausto Baldanti

“…Potential cut-off and diagnostics algorithm should be better investigated in a large patients setting.…”
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Prediction of early breast cancer patient survival using ensembles of hypoxia signatures. by Inna Y Gong, Natalie S Fox, Vincent Huang, Paul C Boutros

“…We demonstrate that the best way of merging preprocessing methods varies from signature to signature, and that there is likely no 'best' preprocessing pipeline that is universal across datasets, highlighting the need to evaluate ensembles of preprocessing algorithms. Further, we developed novel signatures for each preprocessing method and the risk classifications from each were incorporated in a meta-random forest model. …”
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Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation by Wanli Xiong, Qiqi Cao, Lu Jia, Min Chen, Tao Liu, Qingyan Zhao, Yanhong Tang, Bo Yang, Li Li, Shaobo Shi, He Huang, Congxin Huang, China Atrial Fibrillation Center Project Team

“…Calibration analysis indicated no significant difference between predicted and observed values (p = 0.181). …”
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A Synergistic Framework for Coupling Crop Growth, Radiative Transfer, and Machine Learning to Estimate Wheat Crop Traits in Pakistan by Rana Ahmad Faraz Ishaq, Guanhua Zhou, Aamir Ali, Syed Roshaan Ali Shah, Cheng Jiang, Zhongqi Ma, Kang Sun, Hongzhi Jiang

“…The integration of the Crop Growth Model (CGM), Radiative Transfer Model (RTM), and Machine Learning Algorithm (MLA) for estimating crop traits represents a cutting-edge area of research. …”
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