Reliability of a Low-Cost Inertial Measurement Unit (IMU) to Measure Punch and Kick Velocity by Lukas Pezenka, Klaus Wirth

“…Utilizing a low-cost mobile phone in conjunction with the PhyPhox app, acceleration data was collected and analyzed using a custom algorithm. This involved strike segmentation and numerical integration to determine velocity. …”
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Rock fracture mode and acoustic emission characteristics under true triaxial single-sided unloading path by Longpei Ma, Longpei Ma, Chongyan Liu, Guangming Zhao, Guangming Zhao

“…At the same time, in order to analyze the experimental data more thoroughly, the Gaussian mixture model (GMM) clustering algorithm was introduced to perform clustering analysis on the characteristic parameters of acoustic emission, so as to explore the damage and fracture patterns of the unloading rocks. …”
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Analisis Perbandingan Algoritma SVM, KNN, dan CNN untuk Klasifikasi Citra Cuaca by Mohammad Farid Naufal

“…KNN and SVM are Machine Learning classification algorithms, while CNN is a Deep Neural Networks classification algorithm. …”
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MORIME: A multi-objective RIME optimization framework for efficient truss design by Mohammad Aljaidi, Nikunj Mashru, Pinank Patel, Divya Adalja, Pradeep Jangir, Arpita, Sundaram B. Pandya, Mohammad Khishe

“…Usually, conventional optimization algorithms have difficulty in solving complex MOO tasks, and in generating diverse, high quality solutions for various structural configurations. …”
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Mapping global annual urban land cover fractions (2001–2020) derived with multi-objective deep learning by Haoyu Wang, Qian Wang, Xiuyuan Zhang, Shihong Du, Lubin Bai, Shuping Xiong

“…Accordingly, this study proposes a novel deep learning unmixing algorithm, Normalized Non-negative Multi-objective Residual T-ConvLSTM (NNMRT) model, with strong encoding and recognition capacities for extracting GAULCF. …”
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Machine learning-based pipeline for automated intracerebral hemorrhage and drain detection, quantification, and classification in non-enhanced CT images (NeuroDrAIn). by Samer Elsheikh, Ahmed Elbaz, Alexander Rau, Theo Demerath, Elias Kellner, Ralf Watzlawick, Urs Würtemberger, Horst Urbach, Marco Reisert

“…<h4>Conclusion</h4>We developed and statistically validated an automated pipeline for evaluating computed tomography scans after minimally invasive surgery for intracerebral hemorrhage. The algorithm reliably detects drains, quantifies drain coverage by the hemorrhage, and uses machine learning to detect malpositioned drains. …”
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Internet of Things Assisted Plant Disease Detection and Crop Management Using Deep Learning for Sustainable Agriculture by Eman A. Al-Shahari, Ghadah Aldehim, Mohammed Aljebreen, Jehad Saad Alqurni, Ahmed S. Salama, Sitelbanat Abdelbagi

“…The integration of Internet of Things (IoT) technology with deep learning (DL) algorithms has revolutionized plant disease detection and crop management and paved the way for sustainable agricultural practices. …”
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The method of preliminary localization of source of excessive air pollution to increase effectiveness of environmental monitoring and supervision in Russia by L. O. Shtripling, V. V. Bazhenov, Yu. V. Kalinin, N. S. Bazhenova, V. V. Merkulov

“…The paper presents an algorithm for the preliminary assessment of the location of pollution sources, emissions of which could lead to an excess of permissible concentrations in the air. …”
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Leveraging Thermal Infrared Imaging for Pig Ear Detection Research: The TIRPigEar Dataset and Performances of Deep Learning Models by Weihong Ma, Xingmeng Wang, Simon X. Yang, Lepeng Song, Qifeng Li

“…Overall, the TIRPigEar dataset demonstrates optimal performance when applied to the YOLOv9m algorithm. Utilizing thermal infrared imaging technology to detect pig ear information provides a non-contact, rapid, and effective method. …”
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Nonlinear Structural Fusion for Multiplex Network by Nianwen Ning, Feiyu Long, Chunchun Wang, Youjie Zhang, Yilin Yang, Bin Wu

“…Then, we construct a node similarity network based on embedding matrices and K-D tree algorithm. (2) In NSF, we present a nonlinear enhanced iterative fusion (EIF) strategy. …”
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Prediction of sentiment polarity in restaurant reviews using an ordinal regression approach based on evolutionary XGBoost by Dana A. Al-Qudah, Ala’ M. Al-Zoubi, Alexandra I. Cristea, Juan J. Merelo-Guervós, Pedro A. Castillo, Hossam Faris

“…The proposed PSO-XGB algorithm showed superior results when compared to support vector machine (SVM) and other optimization methods in terms of root mean square error (RMSE) for the English and Arabic datasets. …”
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A high-throughput ResNet CNN approach for automated grapevine leaf hair quantification by Nagarjun Malagol, Tanuj Rao, Anna Werner, Reinhard Töpfer, Ludger Hausmann

“…As final validation, 10,120 input images from a segregating F1 biparental population were used to evaluate the algorithm performance. ResNet CNN-based phenotypic results compared to ground truth data received by two experts revealed a strong correlation with R values of 0.98 and 0.92 and root-mean-square error values of 8.20% and 14.18%, indicating that the model performance is consistent with expert evaluations and outperforms the traditional manual rating. …”
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Variants of the Sliding Mode Control in Presence of External Disturbance for Quadrotor by Irfan Ahmad, Muwaida Liaquat, Fahad Mumtaz Malik, Hameed Ullah, Usman Ali

“…Secondly, kinodynamic Rapidly Exploring Random Tree with Fixed Node (RRT&#x002A;FN) which is an incremental sampling-based optimal algorithm has been implemented for online navigation and flight control of the quadrotor system. …”
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Causal Inference for Hypertension Prediction With Wearable E lectrocardiogram and P hotoplethysmogram Signa... by Ke Gon g, Yifan Chen, Xinyue Song, Zhizhong Fu, Xiaorong Ding

“…Finally, we used these features to detect hypertension via machine learning algorithms. Results We validated the proposed method on 405 subjects. …”
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Machine learning-based prognostic model for patients with anaplastic thyroid carcinoma by Yihan Sun, Da Lin, Xiangyang Deng, Yinlong Zhang

“…This study aimed to develop and validate a prognostic model for predicting survival outcomes for ATC patients using random survival forests (RSF), a machine learning algorithm. Methods A total of 1222 ATC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into a training set of 855 patients and a validation set of 367 patients. …”
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A Line of Sight/Non Line of Sight Recognition Method Based on the Dynamic Multi-Level Optimization of Comprehensive Features by Ziyao Ma, Zhongliang Deng, Zidu Tian, Yingjian Zhang, Jizhou Wang, Jilong Guo

“…In addition, this paper proposes an improved sand cat search algorithm for network parameter search, which improves search efficiency and search accuracy. …”
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Edge-Preserving Probabilistic Downsampling for Reliable Medical Segmentation in Resource-Constrained Environments by Shahzad Ali, Yu Rim Lee, Soo Young Park, Won Young Tak, Soon Ki Jung

“…Beyond preserving edge details more effectively than conventional nearest-neighbor downsampling, the proposed algorithm, when adapted for images, exhibits notable performance improvements over conventional bilinear interpolation. …”
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Enhancing climate resilience: A data-driven north rift weather prediction system for real-time forecasting and agricultural decision support by John W. Makokha, Peter W. Barasa, Geoffrey W. Khamala

“…This study presents the development and integration of predictive models for the Normalized Difference Vegetation Index (NDVI) and Bare Soil Index (BSI) using the XGBoost algorithm within the North Rift Weather Prediction System (NRWPS) to enhance ecosystem monitoring in Kenya's North Rift region. …”
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High-Precision Sub-Wavelength Motion Compensation Technique for 3D Down-Looking Imaging Sonar Based on an Acoustic Calibration System by Jun Wang, Peihui Liang, Junqiang Song, Pan Xu, Yongming Hu, Peng Zhang, Kang Lou, Rongyao Ren, Wusheng Tang

“…The imaging scheme adopts a time-domain spatial beam-forming method with the Back Projection (BP) algorithm as the core, and the formation of a virtual plane array can effectively improve the along-track resolution. …”
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Assessing the impact of climate and land use change on flood vulnerability: a machine learning approach in coastal region of Tamil Nadu, India by Devanantham Abijith, Subbarayan Saravanan, K S S Parthasarathy, Nagireddy Masthan Reddy, Janardhanam Niraimathi, Ahmed Ali Bindajam, Javed Mallick, Maged Muteb Alharbi, Hazem Ghassan Abdo

“…To identify flooded areas, the study utilised Google Earth Engine (GEE), Sentinel-1 data, and 12 geospatial datasets from multiple sources. A random forest algorithm was used for LULC change and flood susceptibility mapping. …”
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