Klasifikasi Multilabel Pada Gaya Belajar Siswa Sekolah Dasar Menggunakan Algoritma Machine Learning by I Kadek Nicko Ananda, Ni Putu Novita Puspa Dewi, Ni Wayan Marti, Luh Joni Erawati Dewi

“…The machine learning algorithms used to build the model are Decision Tree, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
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Climatic variables determining <i>Rhododendron</i> sister taxa distributions and distributional overlaps in the Himalayas by Madan Krishna Suwal, Ole Reidar Vetaas

“…We used Generalized Linear Modelling to select variables, and modelled the distribution of each species using Random Forest algorithms, predicting their potential distribution in current and future climates. …”
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Spatiotemporal Gap‐Filling of NASA Deep Blue Satellite Aerosol Optical Depth Over the Contiguous United States (CONUS) Using the UNet 3+ Architecture by Jeffrey S. M. Lee, S. Marcela Loría‐Salazar, Heather A. Holmes, Andrew M. Sayer

“…Abstract Due to sensor and algorithmic constraints, satellite aerosol optical depth (AOD) retrievals are spatially incomplete and have gaps caused by clouds and bright surfaces. …”
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Mapping County-Level Rice Planting Areas by Joint Use of High-Resolution Optical and Time Series SAR Imagery by Jia Xu, Haojie Wang, Lin Qiu, Hui Wang, Yang Mu

“…And the proposed method effectively integrated limited GF-6 imagery with time-series Sentinel-1 data and performed better than traditional machine learning algorithms like Random Forest and pixel-based methods, achieving an overall accuracy of over 88% and a Kappa coefficient of over 86% for the Dangtu and Rudong counties. …”
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Wind energy potential assessment using the Weibull distribution method for future energy self-sufficiency by Badr El Kihel, Nacer Eddine El Kadri Elyamani, Abdelhakim Chillali

“…A rigorous statistical analysis was conducted using the Weibull distribution and several parameter estimation algorithms: Maximum Likelihood Method, Jestus Method, Lysen Method, Moroccan Method, and Graphical Method. …”
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Exploring hypoxia-related genes in spinal cord injury: a pathway to new therapeutic targets by Shihuan Cheng, Le Li, Mengmeng Xu, Ningyi Ma, Yinhua Zheng

“…Exploring hypoxia-related genes in SCI may reveal potential therapeutic targets and improve our understanding of its pathogenesis.MethodsWe developed a diagnostic model using LASSO regression and Random Forest algorithms to investigate hypoxia-related genes in SCI. …”
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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…This research leverages various machine learning algorithms to develop predictive models trained on a comprehensive dataset of sensor-based soil moisture, matric suction, and soil temperature obtained from prototype ET covers, with known resistivity values. …”
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Performance Estimation of Low Power and Area-Efficient Parallel Pipelined FFT by Surya P, Arunachalaperumal C, Dhilipkumar S

“…It is also used in image and video processing and is critical for algorithms that manipulate pixels, scale, and compress data when many multiplications need to be performed quickly. …”
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Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics. by Wenlong Kuang, Jianwu Huang, Yulu Yang, Yuhua Liao, Zihua Zhou, Qian Liu, Hailang Wu

“…The 10 MI-related hub MitoDEGs were then obtained by eight different algorithms. Immunoassays showed a significant increase in monocyte macrophage and T cell infiltration. …”
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Extremist Ideology Classification in Kazakh: A Multi-Class Approach Using Machine Learning and Psycholinguistic Analysis by Shynar Mussiraliyeva, Milana Bolatbek, Kymbat Baisylbayeva

“…We employ a hybrid methodology that combines traditional text vectorization techniques, machine learning algorithms, and a psycholinguistic analysis module (PLAM) specifically adapted for the Kazakh language. …”
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Energy-Efficient Trajectory Planning With Joint Device Selection and Power Splitting for mmWaves-Enabled UAV-NOMA Networks by Ahmad Gendia, Osamu Muta, Sherief Hashima, Kohei Hatano

“…This paper proposes two energy-efficient reinforcement learning (RL)-based algorithms for millimeter wave (mmWave)-enabled unmanned aerial vehicle (UAV) communications toward beyond-5G (B5G). …”
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Lessons from national biobank projects utilizing whole-genome sequencing for population-scale genomics by Hyeji Lee, Wooheon Kim, Nahyeon Kwon, Chanhee Kim, Sungmin Kim, Joon-Yong An

“…We then introduce recent technological advances that enable efficient processing and analysis of large-scale WGS data, including improvements in variant calling algorithms, innovative methods for creating multi-sample VCFs, optimized data storage formats, and cloud-based computing solutions. …”
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Prediction of Current and Future Distributions of Chalcophora detrita (Coleoptera: Buprestidae) Under Climate Change Scenarios by Arif Duyar, Muhammed Arif Demir, Mahmut Kabalak

“…An ensemble model was created by using 11 different algorithms (Artificial Neural Network, Classification Tree Analysis, eXtreme Gradient Boosting, Flexible Discriminant Analysis, Generalised Additive Model, Generalised Boosting Model, Generalised Linear Model, Multivariate Adaptive Regression Splines, Maximum Entropy, Random Forest, Surface Range Envelope) to predict the potential suitable habitats of C. detrita. …”
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Optimising laboratory monitoring of chronic conditions in primary care: a quality improvement framework by Alex J Walker, Richard Croker, Jessica Watson, Andy Brogan, Darunee Whiting, Tom Lewis

“…The main difference from previous general practitioner practice algorithms was removing the requirement for full blood count and liver function test monitoring for many conditions. …”
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Automated pipeline for leaf spot severity scoring in peanuts using segmentation neural networks by Joshua Larsen, Jeffrey Dunne, Robert Austin, Cassondra Newman, Michael Kudenov

“…Results The pipeline incorporated a neural network that accurately determined the infected leaf surface area and identified dead leaves from plot-level cellphone imagery. Image processing algorithms then convert these labels into quality metrics that can efficiently score these images based on infected versus non-infected area. …”
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Diagnostic value of leukocytosis in patients presenting to the emergency department with abdominal pain: A retrospective observational study by Erkan Boğa

“…Further multicenter prospective studies are needed to validate these findings and improve diagnostic algorithms.…”
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Leveraging autoencoder models and data augmentation to uncover transcriptomic diversity of gingival keratinocytes in single cell analysis by Pradeep Kumar Yadalam, Prabhu Manickam Natarajan, Carlos M. Ardila

“…Clustering was performed using principal component analysis (PCA) and k-nearest neighbor (KNN) algorithms. Marker gene identification and differential expression analysis were used to characterize cell clusters. …”
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RP-HPLC and UV Spectrophotometric Analysis of Paracetamol, Ibuprofen, and Caffeine in Solid Pharmaceutical Dosage Forms by Derivative, Fourier, and Wavelet Transforms: A Comparison... by Hoang Vu Dang, Huong Truong Thi Thu, Ly Dong Thi Ha, Huong Nguyen Mai

“…Different signal-transforming algorithms were applied for UV spectrophotometric analysis of paracetamol, ibuprofen, and caffeine in ternary mixtures. …”
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A machine learning approach to assess the climate change impacts on single and dual-axis tracking photovoltaic systems by Udit Mamodiya, Indra Kishor, Priyam Ganguly, Isha Mukherjee, Nithesh Naik

“…Increasing computational efficiency, integrating energy storage mechanisms, and optimizing self-learning algorithms will be areas of focus for future research to make it more applicable.…”
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Identification and mechanistic insights of cell senescence-related genes in psoriasis by Guiyan Deng, Cheng Xu, Dunchang Mo

“…Protein-protein interaction networks, Gene Ontology, and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to explore the functions and pathways of these genes. Machine learning algorithms, including Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support vector machine-recursive feature elimination (SVE-RFE), were used to select feature genes that were validated by qRT-PCR. …”
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