A Nondestructive Detection Method for the Muti-Quality Attributes of Oats Using Near-Infrared Spectroscopy by Linglei Li, Long Li, Guoyuan Gou, Lang Jia, Yonghu Zhang, Xiaogang Shen, Ruge Cao, Lili Wang

“…Subsequently, the optimal PLS model was obtained by integrating feature wavelength selection algorithms (CARS, SPA, UVE, LAR). After SD-SPA, total starch reached its optimal state (<i>R</i>_p² = 0.768, <i>RMSEP</i> = 2.057). …”
Get full text

Ensemble boosting-based soft-computing models for predicting the bond strength between steel and CFRP plate by Irwan Afriadi, Chanachai Thongchom, Divesh Ranjan Kumar, Suraparb Keawsawasvong, Warit Wipulanusat

“…The present study examines the bond behavior of CFRP sheets in steel beams using boosting-based ensemble machine learning approaches such as the XGBoost, GBM, CATBoost, LGBM, and ADABoost algorithms. For the machine learning boosting-based model approach, eight total input variables and one output variable were chosen to predict the maximum load (PU) of the bonding behavior between the CFRP and steel. …”
Get full text

Unveiling the effect of urinary xenoestrogens on chronic kidney disease in adults: A machine learning model by Bowen Zhang, Liang Chen, Tao Li

“…An interpretable machine learning (ML) model was developed to predict CKD using data from the National Health and Nutrition Examination Survey (NHANES) database spanning from 2007 to 2016. Four ML algorithms—random forest classifier (RF), XGBoost (XGB), k-nearest neighbors (KNN), and support vector machine (SVM)—were used alongside traditional logistic regression to predict CKD. …”
Get full text

Machine learning-based detection of medical service anomalies: Kazakhstan’s health insurance data by Maksut Kulzhanov, Alexander Wagner, Abylkair Skakov, Iliyas Mukhamejan, Saya Zhorabek, Ainur B. Qumar

“…This research aims to apply advanced ML algorithms to analyze data from the Republic of Kazakhstan’s Obligatory Health Insurance Fund (OHIF) and automatically detect anomalies in the structure of delivered medical services. …”
Get full text

Genetic analysis of non-syndromic peg lateralis using whole-exome sequencing by Junglim Choi, Junglim Choi, Sungnam Kim, Hyunsoo Ahn, Donghyo Kim, Sung-Won Cho, Sanguk Kim, Sanguk Kim, Sanguk Kim, Jae Hoon Lee

“…In-silico mutation impact analysis was performed using Polymorphism Phenotyping v2, sorting intolerant from the tolerant, and integrated score of co-evolution and conservation algorithms.ResultsWe identified a heterozygous allele for RP11-131H24.4 and OTOP1, which encodes the otopetrin-1 protein, a proton channel, in all 20 individuals. …”
Get full text

Effective Practices of Macroprudential Stress Testing as a Tool of Increasing the Stability of Russian Financial System in the Context of Macroeconomic Shocks by D. Yu. Desyatnichenko, O. V. Ryabov, O. Yu. Desyatnichenko

“…Based on the results of the study, the authors come to a number of conclusions that the role of the macroeconomic component in the procedures, methods, and algorithms for macroprudential stress testing used in Russia should increase, the degree of involvement and the sphere of responsibility for its results of key institutional units of the public administration system should expand, and macroprudential stress testing itself should not be limited to supervisory stress testing in everyday practice.…”
Get full text

Unraveling genetic predisposition and oxidative stress in vitiligo development and the role of artificial intelligence (AI) in diagnosis and management by Kocić Hristina, Lotti Torello, Jevtović-Stoimenov Tatjana, Wollina Uwe, Valle Yan, Lukić Stevo, Klisić Aleksandra

“…By analysing vast datasets, AI algorithms can identify patterns within complex genetic markers and clinical features, facilitating earlier and more precise detection of vitiligo. …”
Get full text

Quantitative Analysis of Structural Parameters Importance of Helical Temperature Microfiber Sensor by Artificial Neural Network by Juan Liu, Minghui Chen, Hang Yu, Jinjin Han, Hongyi Jia, Zhili Lin, Zhijun Wu, Jixiong Pu, Xining Zhang, Hao Dai

“…With the assistance of the evaluation algorithms based on the well-performed backpropagation neural network (BPNN), we quantitatively analyze the importance of the structural parameters of the supported helical microfiber (HMF) temperature sensor. …”
Get full text

Enhancing sex determination in forensic anthropology: A comparative analysis of cranial measurements using artificial neural network by Matheus Jhonnata Santos Mota, Alberto Calson Alves Vieira, Lucas Silva Lima, João Victor Melquiades Sátiro, Carlos Mathias de Menezes Neto, Patrízia Lisieux Prado Paixão, Gabriel Pedro Gonçalves Lopes, Lauro Roberto de Azevedo Setton, Carlos Eduardo de Andrade, Richard Halti Cabral

“…The data were divided into a test group (20 %) and a training group (80 %). Machine learning algorithms were developed using the Python language in the Google Colaboratory environment. …”
Get full text

Enhanced Feature Selection via Hierarchical Concept Modeling by Jarunee Saelee, Patsita Wetchapram, Apirat Wanichsombat, Arthit Intarasit, Jirapond Muangprathub, Laor Boongasame, Boonyarit Choopradit

“…The presented methods are evaluated based on all learned attributes with 10 datasets from the UCI Machine Learning Repository by using three classification algorithms, namely decision trees, support vector machines (SVM), and artificial neural networks (ANN). …”
Get full text

Segmentation of CAD models using hybrid representation by Claude Uwimana, Shengdi Zhou, Limei Yang, Zhuqing Li, Norbelt Mutagisha, Edouard Niyongabo, Bin Zhou

“…The first component of our hybrid system involves advanced mesh-labeling algorithms that harness the digitization of CAD properties to mesh models. …”
Get full text

COSMIC’s Large-scale Search for Technosignatures during the VLA Sky Survey: Survey Description and First Results by C. D. Tremblay, J. Sofair, L. Steffes, T. Myburgh, D. Czech, P. B. Demorest, R. A. Donnachie, A. W. Pollak, M. Ruzindana, Siemion A. P. V., S. S. Varghese, S. Z. Sheikh

“…Developing algorithms to search through data efficiently is a challenging part of searching for signs of technology beyond our solar system. …”
Get full text

Potential of Multi-Source Multispectral vs. Hyperspectral Remote Sensing for Winter Wheat Nitrogen Monitoring by Xiaokai Chen, Yuxin Miao, Krzysztof Kusnierek, Fenling Li, Chao Wang, Botai Shi, Fei Wu, Qingrui Chang, Kang Yu

“…Future work should validate these models using real satellite imagery and explore multi-source data fusion with advanced learning algorithms.…”
Get full text

Multimodal marvels of deep learning in medical diagnosis using image, speech, and text: A comprehensive review of COVID-19 detection by Md Shofiqul Islam, Khondokar Fida Hasan, Hasibul Hossain Shajeeb, Humayan Kabir Rana, Md. Saifur Rahman, Md. Munirul Hasan, AKM Azad, Ibrahim Abdullah, Mohammad Ali Moni

“…We explore the architecture of deep learning models, emphasising their data-specific structures and underlying algorithms. Subsequently, we compare different deep learning strategies utilised in COVID-19 analysis, evaluating them based on methodology, data, performance, and prerequisites for future research. …”
Get full text

From data to nutrition: the impact of computing infrastructure and artificial intelligence by Pierpaolo Di Bitonto, Michele Magarelli, Pierfrancesco Novielli, Donato Romano, Domenico Diacono, Lorenzo de Trizio, Angelo Mariano, Claudia Zoani, Riccardo Ferrero, Alessandra Manzin, Maria De Angelis, Roberto Bellotti, Sabina Tangaro

“…Additionally, it explores the concept of open data sharing and the integration of machine learning algorithms in the food industry to enhance food safety and product development. …”
Get full text

Microplastics in food products: Prevalence, artificial intelligence based detection, and potential health impacts on humans by M. Amin Mir, Muhammad Azhar Ali Khan, Bimal Krishna Banik, Syed M. Hasnain, Lina Alzayer, K. Andrews, Sani I. Abba

“…The research also highlights the necessity of better detection methods, like multispectral imaging and AI-based algorithms, to increase the precision and effectiveness of microplastic identification in food. …”
Get full text

FTIR-Based Microplastic Classification: A Comprehensive Study on Normalization and ML Techniques by Octavio Villegas-Camacho, Iván Francisco-Valencia, Roberto Alejo-Eleuterio, Everardo Efrén Granda-Gutiérrez, Sonia Martínez-Gallegos, Daniel Villanueva-Vásquez

“…The study assessed the performance of ML algorithms, such as k-nearest neighbors (k-NN), support vector machines (SVM), naive Bayes (NB), random forest (RF), and artificial neural networks architectures (including convolutional neural networks (CNNs) and multilayer perceptrons (MLPs)). …”
Get full text

Effect of Time-of-Flight and Regularized Reconstructions on Quantitative Measurements and Qualitative Assessments in Newly Diagnosed Prostate Cancer With F-Fluorocholine Dual Time... by Spencer C. Behr MD, Brett J. Mollard MD, Jaewon Yang PhD, Robert R. Flavell MD, PhD, Randall A. Hawkins MD, PhD, Youngho Seo PhD

“…Recent technical advances in positron emission tomography/magnetic resonance imaging (PET/MRI) technology allow much improved time-of-flight (TOF) and regularized iterative PET reconstruction regularized iterative reconstruction (RIR) algorithms. We evaluated the effect of TOF and RIR on standardized uptake values (maximum and peak SUV [SUV max and SUV peak ]) and their metabolic tumor volume dependencies and visual image quality for 18 F-fluorocholine PET/MRI in patients with newly diagnosed prostate cancer. …”
Get full text

Experimenting with learning-based image orientation approaches for photogrammetric mapping of <em>Posidonia oceanica</em> meadows by F. Menna, A. Calantropio, A. Pansini, G. Ceccherelli, E. Nocerino

“…A comparative analysis of traditional algorithms and AI-driven approaches for image orientation is presented on datasets that differ by acquisition protocols, depth, season, platform type, and imaging system. …”
Get full text

High-accuracy prediction of vessels’ estimated time of arrival in seaports: A hybrid machine learning approach by Sunny Md. Saber, Kya Zaw Thowai, Muhammad Asifur Rahman, Md. Mehedi Hassan, A.B.M. Mainul Bari, Asif Raihan

“…Compared to existing machine learning algorithms, our stacking model exhibits superior prediction performance. …”
Get full text