APPROACH TO IMAGE ANALYSIS FOR COMPUTER VISION SYSTEMS by N. A. Iskra

“…Experiments were conducted on test datasets provided by Visual Genome database, developed by researchers from Stanford University to evaluate object detection algorithms, image captioning models, and other relevant image analysis tasks. …”
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Comparison of Machine Learning and Statistical Approaches of Detecting Anomalies Using a Simulation Study by Klaudia Lenart

“…Implications and recommendations: For the statistical methods included in the study, knowledge about the distribution of the variables was crucial while the supervised machine learning algorithms required acquiring a training dataset. Unlike machine learning algorithms, the statistical methods performed with similar accuracy even when the change in the marginal distribution parameters’ value was smaller. …”
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The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…The performance of these techniques is rigorously evaluated through extensive experimentation. The results demonstrate that the proposed method outperforms conventional algorithms in regression tasks, particularly in terms of computational efficiency, data processing speed, and model training stability, while also exhibiting high scalability. …”
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A novel univariate feature selection with ANOVA F-test-based machine learning model for Intrusion Detection Framework of Robotics system by Narinder Verma, Neerendra Kumar, Kuljeet Singh, Abeer Aljohani, Anurag Sinha, Syed Abid Hussain

“…The NSL-KDD dataset is utilized for training and evaluating machine learning models due to the inclusion of a wide range of attack scenarios and normal instances. …”
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An Improved YOLOv8-Based Dense Pedestrian Detection Method with Multi-Scale Fusion and Linear Spatial Attention by Han Gong, Tian Li, Lijuan Wang, Shucheng Huang, Mingxing Li

“…Finally, to improve training efficiency, a novel weighted loss function named DFL-SIoU is developed to accelerate model convergence. …”
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Comparison of Machine Learning Methods for Predicting Electrical Energy Consumption by Retno Wahyusari, Sunardi Sunardi, Abdul Fadlil

“…The dataset was divided into training and testing sets using different ratios (90:10, 80:20, 50:50) to evaluate model performance. …”
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Enhancing Real-time Herbal Plant Detection in Agricultural Environments with YOLOv8 by Ranty Deviana Siahaan, Herimanto Pardede, Iustisia Natalia Simbolon, Ivanston Simbolon, Dian Jorgy Gultom

“…The YOLOv8 model was trained with this dataset to detect herbal plant objects. …”
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Pandemic velocity: Forecasting COVID-19 in the US with a machine learning & Bayesian time series compartmental model. by Gregory L Watson, Di Xiong, Lu Zhang, Joseph A Zoller, John Shamshoian, Phillip Sundin, Teresa Bufford, Anne W Rimoin, Marc A Suchard, Christina M Ramirez

“…We evaluated the model by training it on progressively longer periods of the pandemic and computing its predictive accuracy over 21-day forecasts. …”
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A general two-group constants estimator for 17x17 PWR assembly configurations using artificial neural networks by Gökhan Pediz, M. Alim Kırışık

“…The accuracy of the trained ANN is evaluated by multiplication factor calculations for selected benchmarks. …”
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Research on the Exchange Rate Forecast of the Pound Sterling and the Dollar Based on Neural Networks by Chen Jiantao, Song Yining

“…Through meticulous adjustments, the paper determines the optimal number of neurons in the concealed layers to achieve a harmonious equilibrium between the model's complexity and its aptitude for generalization. During the training phase, the back-propagation algorithm is employed to reduce prediction errors, and rigorous cross-validation techniques are utilized to precisely evaluate the model's performance. …”
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Cultural intelligence and inclusive leadership in a diverse IT sector: a framework for effective collaboration by Камрун Нахар, Омар Фарук, Захир Райхан

“…Based on a mixed-methods study with 600 participants from worldwide IT businesses, the paper proposes CQL-IncluNet, a prediction algorithm to model and evaluate collaboration.  Statistics show that CQ and IL interact statistically, explaining 68% of cooperation effectiveness variance.  …”
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A real-time virtual liver simulator using position based dynamics with compliant constraints for medical applications by Yufan Guo, Dongliang Kou, Xukun Zhang, Lihua Zhang, Kai Cao

“…To overcome this limitation, we present a novel real-time liver simulation algorithm leveraging Extended Position-Based Dynamics (XPBD). …”
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Unraveling the Drivers of ESG Performance in Chinese Firms: An Explainable Machine-Learning Approach by Hyojin Kim, Myounggu Lee

“…Empirical findings demonstrate that random forest algorithms significantly outperform multivariate linear regression in capturing nonlinear ESG relationships. …”
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A simple yet effective approach for predicting disease spread using mathematically-inspired diffusion-informed neural networks by ByeongChang Jeong, Yeon Ju Lee, Cheol E. Han

“…GCNs are a recent deep learning algorithm designed to learn spatial relationship from graph-structured data. …”
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ProvNavigator: shadow path guided attack investigation method by XI Hao, FAN Hao, YUAN Shenyang, ZHU Jinyu, CHEN Changhua, WAN Hai, ZHAO Xibin

“…Recent research has alleviated this issue to some extent by integrating audit logs and application logs, showcasing advantages such as no need for program instrumentation, model training, or taint analysis. However, existing log fusion techniques either rely on complex fusion rules or require reverse engineering of applications, necessitating algorithm adjustments when facing new applications, which limits their general applicability. …”
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Design optimization of wood-carved window grilles in historical architectures using stable diffusion model and intuitionistic Fuzzy VIKOR by Xinhui Kang, Jiao Wang

“…First, 2476 window grille patterns were collected to create a diverse database to support algorithm training. Next, the SDM was employed to learn the design patterns of the window carvings, generating designs that blend traditional charm with innovative styles. …”
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Machine Learning Applications for Physical Activity and Behaviour in Early Childhood: A Systematic Review by Markel Rico-González, Carlos D. Gómez-Carmona

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A Ship Underwater Radiated Noise Prediction Method Based on Semi-Supervised Ensemble Learning by Xin Huang, Rongwu Xu, Ruibiao Li

“…Accurate prediction of ship underwater radiated noise (URN) during navigation is critical for evaluating acoustic stealth performance and analyzing detection risks. …”
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Enhancing the e-commerce shopping experience with IoT-enabled smart carts in smart stores by Jian Wang

“…A neuro-fuzzy approach is employed to evaluate the efficiency of the proposed model. The neural network model is trained using a dataset split into three segments: 65% for training, 15% for validation, and 20% for testing. …”
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DETERMINATION OF COFFEE FRUIT MATURITY LEVEL USING IMAGE HISTOGRAM AND K-NEAREST NEIGHBOR by Irene Devi Damayanti, Aryo Michael

“…The procedure for choosing and evaluating the coffee fruit's physical quality is one of the most crucial steps. …”
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