Morphometric Analysis of the Proximal and Distal Ends of Adult Dry Femur Bone: A Cross sectional Study in the Population of North Karnataka, India by Shilpa M Bhimalli, Agamdeep Singh Bedi, Mugdha Malik, Vinod Chandgadkar, Sheetal V Pattanshetti, Daksha Dixit

“…Aim: To quantify the morphometric parameters of the proximal and distal ends of the adult femur, including measurements of size, shape, and angular relationships. …”
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Evaluating reservoir permeability from core data: Leveraging boosting techniques and ANN for heterogeneous reservoirs by Amad Hussen, Tanveer Alam Munshi, Minhaz Chowdhury, Labiba Nusrat Jahan, Abu Bakker Siddique, Mahamudul Hashan

“…The majority of machine learning models applied to permeability determination are connected to well logs. …”
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An optimized ensemble ML-WQI model for reliable water quality prediction by minimizing the eclipsing and ambiguity issues by Ashifur Rahman, M. M. Mahbubul Syeed, Md. Rajaul Karim, Kaniz Fatema, Razib Hayat Khan, Mohammad Faisal Uddin

“…In addressing these, recently, data-driven approaches through the integration of machine learning or deep learning (ML/DL) techniques are notably applied to develop improved WQI models. …”
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Structural Feedback Analysis Based on Monitoring Data from Units with Different Spiral Case Embedding Methods at Three Gorges Hydropower Station by CHEN Qin, SU Hai-dong, DUAN Guo-xue, CUI Jian-hua, ZHOU Shi-hua

“…The three-dimensional finite element method was used to conduct feedback comparative analysis of relevant monitoring parameters to summarize the structural bearing patterns and differences among different embedding methods of spiral cases. …”
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Review on Rail Damage Detection Technologies for High-Speed Trains by Yu Wang, Bingrong Miao, Ying Zhang, Zhong Huang, Songyuan Xu

“…The most important optical detection method is machine vision detection. Ultrasonic detection can detect internal damage of the rail. …”
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Forecasting the development of poultry farming based on time series by Anatolii Kulyk, Katerina Fokina-Mezentseva, Alla Saiun, Daryna Saiun

“…Analysis of historical data allowed us to determine the optimal parameters of the models and obtain forecast values for time periods (months). …”
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SUMediPose: A 2D-3D pose estimation datasetDataverse by Chris-Mari Schreuder, Oloff Bergh, Lizé Steyn, Rensu P. Theart

“…Recent advancements in machine learning and computer vision, particularly in Pose Estimation (PE), offer promising alternatives. …”
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Quantitative detection of alkali metal Na based on laser-induced breakdown spectroscopy technology by Sijie SHEN, Chi LI, Wangzheng ZHOU, Zhenzhen WANG, Junjie YAN, Zongyu HOU, Zhe WANG, Yoshihiro DEGUCHI

“…The influence of experimental parameters on signal strength and signal-to-noise ratio is analyzed. …”
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Brain Age Prediction Using a Lightweight Convolutional Neural Network by Fatma Eltashani, Mario Parreno-Centeno, James H. Cole, Joao Paulo Papa, Fumie Costen

“…Much interest has recently been drawn to brain age prediction due to the significant development in machine learning and image processing techniques. …”
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A multimodal nomogram for benign-malignant discrimination of lung-RADS ≥4A nodules: integration of oxygen enhanced zero echo time MRI, CT radiomics, and clinical factors by Tiancai Yan, Ling Liu, Yuxin Li, Chunhui Qin, Haonan Guan, Tong Zhang

“…Nodule boundaries were manually contoured as regions of interest (ROIs) on both modalities. Six machine learning classifiers were applied to radiomic features (extracted from LDCT and OE-ZTE-MRI) and clinical parameters (age, smoking history, nodule diameter, calcification, etc.). …”
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Estimation of mangrove heights and aboveground biomass using UAV-LiDAR, Sentinel-1 and ZY-3 stereo images by Bolin Fu, Yingying Wei, Linhang Jiang, Hang Yao, Xiaomin Li, Yanli Yang, Mingming Jia, Weiwei Sun

“…In this study, we constructed mangrove height inversion models using multiple types of remote sensing data and machine learning algorithms (partial least squares regression (PLSR), random forest (RF), and mixture density network (MDN)). …”
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Tratamento de um problema de escalonamento considerando datas de entrega, turnos de produção e trocas de ferramentas via Busca Tabu Scheduling problem treatment considering due dat... by Antonio Gabriel Rodrigues, Arthur Tórgo Gómez

“…The FMS is composed by a versatile machine, a system for transport, handling and storage of materials and a computational system. …”
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Optimizing Osseodensification Drilling for Dental Implant Placement: An In Vitro Study by Xingru Tao, Jie Yang, Tai Ma, Ming Chen, Qinglong An, Dedong Yu

“…ABSTRACT Objectives This study aims to optimize the parameters of osseodensification drilling (OD) to improve the primary stability of dental implants in low‐density bone. …”
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The Novel iMPACT Tool and Quadrant Protocol for Peri-Implantitis: Surface Refinement and Re-Osseointegration Validated by SEM/EDS and Long-Term Clinical Case Reports by Gustavo Vicentis Oliveira Fernandes, Bruno Gomes dos Santos Martins, Juliana Campos Hasse Fernandes, Yankel Gabet, Amiram Vizanski

“…The null hypothesis was that there would be no improvement in the clinical parameters for the implants with peri-implantitis (PI) treated with the new protocol and tool. …”
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Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization by Seoyoon Kwon, Minsoo Ji, Min Kim, Juliana Y. Leung, Baehyun Min

“…This complex multi-million-dollar problem involves optimizing multiple parameters using computationally intensive reservoir simulations, often employing advanced algorithms such as optimization algorithms and machine/deep learning techniques to find near-optimal solutions efficiently while accounting for uncertainties and risks. …”
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Effects of Different Crystallization Protocols on Marginal Gap of Lithium Disilicate Single Crowns: SEM Analysis by Alon Shadur, Joseph Nissan, Diva Lugassy, Ariana Umansky, Eran Zenziper, Gil Ben-Izhack

“…For each plastic tooth, an identical pair of lithium disilicate crowns was milled (a total of 48 crowns) by a four-axis machine. Each paired sample was categorized into two groups: long crystallization (24 crowns) and short crystallization (24 crowns). …”
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Advanced Zero-Shot Learning (AZSL) Framework for Secure Model Generalization in Federated Learning by Muhammad Asif, Surayya Naz, Faheem Ali, Amerah Alabrah, Abdu Salam, Farhan Amin, Faizan Ullah

“…Federated learning (FL) introduces new perspectives in machine learning (ML) by enabling model training across decentralized devices. …”
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Slope deformation prediction based on GA–BP neural networks by Wenhui TAN, Kai LI, Huimin LIU, Meifeng CAI, Qifeng GUO

“…However, with advancements in artificial intelligence, machine learning has emerged as an important method for predicting slope deformation in open-pit mines. …”
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Sustainable extraction of phytochemicals from Mentha arvensis using supramolecular eutectic solvent via microwave Irradiation: Unveiling insights with CatBoost-Driven feature analy... by Zubera Naseem, Muhammad Bilal Qadir, Abdulaziz Bentalib, Zubair Khaliq, Muhammad Zahid, Fayyaz Ahmad, Nimra Nadeem, Anum Javaid

“…The categorical boosting (CatBoost) machine learning model was applied to optimize the extraction process against time (4–8 min), microwave power (160–320 W), and biomass quantity (1–2.0 g/10 mL) with DES. …”
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Body composition and changes with significant fibrosis in NAFLD: a cross-sectional analysis from a tertiary care center in Western India by Abhishek Yadav, Sunil Dadhich, Vivek Saini, Rajendra Bhati, Bobby Mitrolia

“…These findings suggest that body composition parameters may play a role in the progression of fibrosis in NAFLD. …”
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