Evaluation of stroke sequelae and rehabilitation effect on brain tumor by neuroimaging technique: A comparative study. by Xueliang Guo, Lin Sun

“…Furthermore, various machine learning models, such as Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Adaptive Boosting (AdaBoost), and K-Nearest Neighbor (KNN), have been employed to analyze tumor progression in the brain, with performance characterized by Hausdorff distance. …”
Get full text

Neural network-based forecasting and uncertainty analysis of new power generation capacity of electric energy by Xingyu Dou, Zehan Cui

“…Our model outperforms ARIMA, SVM, Gradient Boosting, CNN, and RNN in hourly, daily, and weekly predictions. …”
Get full text

A review of the effect of biofertilizers on productivity and aflatoxin production in groundnuts (Arachis hypogaea) by Tariro Munyari, Nancy Nleya, Kudakwashe Chitindingu, Melody Ndemera

Get full text

Exploiting Data Distribution: A Multi-Ranking Approach by Beata Zielosko, Kamil Jabloński, Anton Dmytrenko

“…One important aspect of data processing is feature selection. This paper proposes a research methodology for multi-level attribute ranking construction for distributed data. …”
Get full text

Is the Romanian organic grains value chain able to sustain the European Green Deal targets? by Iulia DAN, Valentin MIHAI, Ionel JITEA

“…Stakeholders propose several strategies to mitigate these challenges, including the implementation of consumer education initiatives, a focus on boosting domestic processing instead of relying on exports, legislative stability and the introduction of better-targeted financial incentives to support organic farming. …”
Get full text

Self-Confidence and Cognitive Speed: Key Predictors of Topspin Accuracy in Competitive Table Tennis by Jeki Haryanto, Clemens Drenowatz, Jon Mikel Picabea, Padli, Fiky Zarya, Yovhandra Ockta, Vlad Adrian Geantă

“…The results of this study can have a significant impact on training programs, where mental skills training, such as boosting self-confidence and enhancing cognitive processing speed, should be integrated into technical and tactical training routines. …”
Get full text

Machine learning and microfluidic integration for oocyte quality prediction by Hassan Saffari, Davood Fathi, Peyman Palay, Hamid Gourabi, Rouhollah Fathi

“…Supervised learning models (Random Forest, Decision Tree, K-Nearest Neighbors, eXtreme Gradient Boosting, Logistic Regression, Naive Bayes, Support Vector Machines, and Light Gradient Boosting Machine were evaluated. …”
Get full text

A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…Finally, machine learning algorithms such as Gaussian Naive Bayes (GaussianNB), Passive-Aggressive Aggregative Classifier (PAC), Nearest Centroid (NC), K-Nearest Neighbor Classification (KNN), Random Forest (RF), Support Vector Classification (SVC), Gradient Boosting Decision Tree (GBDT), and eXtreme Gradient Boosting (XGB) were established to predict the classification models of transportation stress in meat sheep. …”
Get full text

Landslide hazard early warning method for rock slopes using a hybrid LSTM-SARIMA data-driven model. by Yongxin Dai, Zijian Li, Jingbiao Lu

“…This paper proposes a comprehensive technical system for landslide early hazard warning in open-pit mine slopes, encompassing the full process of monitoring data acquisition and processing, analysis of influencing mechanisms, intelligent algorithm-based prediction, and the construction of early hazard warning indicators. …”
Get full text

Discovery of ultra-high strength aluminum alloys with high damage tolerance via interpretable chain-based machine learning by Lei Jiang, Xinbiao Zhang, Wentao Zhoutai, Zhilin Han, Minghong Mao, Wenli Xue, Jianxin Xie

“…Firstly, by integrating a gradient boosting regression model linking alloy composition (AC) and solution-aging processes (SAP) to tensile mechanical properties (TMP), including ultimate tensile strength σb, yield strength σy, and elongation A, with an explicit quantitative relationship between TMP and fatigue strength (FS), expressed as FS = ασbA1/4, a multi-scale interpretable prediction model was constructed to AC + SAP → TMP → FS. …”
Get full text

Transfer learning based hybrid feature learning framework for enhanced skin cancer diagnosis using deep feature integration by Maridu Bhargavi, Sivadi Balakrishna

“…These results demonstrate the strength of feature fusion and pre-processing in boosting how accurately skin cancer is identified and offer a robust and scalable automatic medical image classification solution.…”
Get full text

Valorization of fishery byproducts as a sustainable development strategy: Health-beneficial activity with an emphasis on anticancer peptides and stabilization through encapsulation... by Shima Kaveh, Younes Najafi Darmian, Seyed Mohammad Bagher Hashemi, Elahe Abedi

“…These by-products result in environmental pollution problems and high economic losses to the marine processing industry. Thus, the recovery of bioactive compounds from marine waste is attracting interest as an acceptable valorization strategy, providing an excellent source for producing high-value-added compounds, increasing the efficiency of the fish industry, boosting the economy, and reducing environmental pollution and sustainability concerns. …”
Get full text

Effect of Pulsed Electric Field Pretreatment on the Texture and Flavor of Air-Dried Duck Meat by Ning Zhang, Zihang Shi, Yangyang Hu, Yangying Sun, Changyu Zhou, Qiang Xia, Jun He, Hongbing Yan, Hui Yu, Daodong Pan

“…Pulsed electric field (PEF), a novel non-thermal processing technology, shows great potential in meat processing by regulating macromolecule metabolism and food quality. …”
Get full text

TECRR: a benchmark dataset of radiological reports for BI-RADS classification with machine learning, deep learning, and large language model baselines by Sadam Hussain, Usman Naseem, Mansoor Ali, Daly Betzabeth Avendaño Avalos, Servando Cardona-Huerta, Beatriz Alejandra Bosques Palomo, Jose Gerardo Tamez-Peña

“…We compared K-Nearest Neighbour (KNN), Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), Adaptive Boosting (AdaBoost), Gradient-Boosting (GB), Extreme Gradient Boosting (XGB), Long Short-Term Memory (LSTM), Bidirectional Encoder Representations from Transformers (BERT) and Biomedical Generative Pre-trained Transformer (BioGPT) classifiers. …”
Get full text

Optimal Computation Offloading Decisions Based on System Utility and Cost Balance by Bingxue Zhang, Xisheng Li, Jia You

“…Edge computing provides terminal users with computing resources and data processing capabilities by deploying edge nodes near Internet of Things (IoT) devices to meet the processing demands of terminal applications. …”
Get full text

Improving Streamflow Prediction Using Multiple Hydrological Models and Machine Learning Methods by Hiren Solanki, Urmin Vegad, Anuj Kushwaha, Vimal Mishra

“…We used Multiple Linear Regression, Random Forest (RF), Extreme Gradient Boosting (XGB), and Long Short‐Term Memory (LSTM) for the post‐processing of simulated streamflow from HMs. …”
Get full text

A machine learning approach for wind turbine power forecasting for maintenance planning by Hariom Dhungana

“…However, when considering computational resources such as memory and processing time, the XGBoost model provides optimal results, offering faster processing and reduced memory usage. …”
Get full text

ALGUNOS EJEMPLOS DE BUENAS PRACTICAS DE LA UTILIZACIÓN DE LA INTELIGENCIA ARTIFICIAL EN LA GESTIÓN DE SERVICIOS PÚBLICOS by LAURA ALVAREZ GARCIA

“…By analyzing various use cases, we will see how using AI-based tools improves the processing of administrative files from the two sides of RLE: the front office, with special reference to the provision of mandatory ser-vices, boosting their quality, reducing their cost, and increasing their efficiency; and the back office, implementing AI tools to streamline and automate administrative procedures.…”

Carbon-Supported Fe-Based Catalyst for Thermal-Catalytic CO₂ Hydrogenation into C₂₊ Alcohols: The Effect of Carbon Support Porosity on Catalytic Performance by Yongjie Chen, Lei Jiang, Simin Lin, Pei Dong, Xiaoli Fu, Yang Wang, Qiang Liu, Mingbo Wu

Get full text

Archaeological documentation and data sharing: digital surveying and open data approach applied to archaeological fieldworks by Mattia Previtali, Riccardo Valente

“…This is supported by governmental decisions and policies that are boosting the open data wave, and in this context archaeology is also affected by this new trend. …”
Get full text