Comparing Blind Image Quality Metrics for Reliable Image Assessment by Cristian George Fieraru, Maria Biserica, Ioana Cristina Plajer, Mihai Ivanovici

“…Reliable image quality assessment is essential not only in digital photography but also as a key metric for evaluating the performance of algorithms and models designed for image quality enhancement or generation. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…The proposed approach employs Decision Tree (DT) algorithms to uncover patterns linked to service failures. …”
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Multiscale Modeling of Meandering Fluvial Reservoir Architecture Based on Multiple-Point Geostatistics: A Case Study of the Minghuazhen Formation, Yangerzhuang Oilfield, Bohai Bay... by Jia Li, Chengyan Lin, Xianguo Zhang, Chunmei Dong, Yannan Wei, Wenyan Ning, Changcheng Han, Wei Guo

“…The produced model conforms geologically realistically and enables the prediction of interwell permeability variation to enhance oil recovery.…”
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Demystifying multiple sclerosis diagnosis using interpretable and understandable artificial intelligence by Chadaga Krishnaraj, Khanna Varada Vivek, Prabhu Srikanth, Sampathila Niranjana, Chadaga Rajagopala, Palkar Anisha

“…Hence, supervised machine learning (ML) algorithms and several hyperparameter tuning techniques, including Bayesian optimization, have been utilized in this study to predict MS in patients. …”
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Phenology-Aware Machine Learning Framework for Chlorophyll Estimation in Cotton Using Hyperspectral Reflectance by Chunbo Jiang, Yi Cheng, Yongfu Li, Lei Peng, Gangshang Dong, Ning Lai, Qinglong Geng

“…Notably, the optimal prediction accuracy was achieved with fewer than five spectral features. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Machine learning models were developed to classify suspicious web domains and predict their vulnerability to XSS attacks. Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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Validation of CT perfusion-based vascular territory mapping: correlation to visual pial grading and outcome measures by Michael Valente, Henry Ma, Andrew Bivard, Bernard Yan, Mark Parsons, Chushuang Chen, Milanka Visser

“…VTM variables were not predictive of anterior collateral grade or stroke outcome measures. …”
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Dynamic control of a 10 MW solar-autothermal hybrid biomass gasifier for round-the-clock processing with stable syngas production by Axel Curcio, Sylvain Rodat, Valéry Vuillerme, Stéphane Abanades

“…Insufficient solar power is dynamically counterbalanced by in situ oxy-combustion, to maintain the reaction temperature at 1200 K and the total H2 + CO flowrate production at 1000 NL/s. A Model Predictive Control (MPC) algorithm is thus implemented, and the feasibility of hybridized operation is demonstrated on a second-per-second basis. …”
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Defect intelligent recognition of membrane product based on deep learning by Maonian Wu, Ling Li, Wei Peng, Tao Wu, Jinwei Yu, Bo Zheng, Shaojun Zhu

“…This module is designed to efficiently capture tiny defects in images, prioritize defect information features, and ultimately enhance the model’s predictive performance and accuracy in defect recognition tasks. …”
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Robust Framework for PMU Placement and Voltage Estimation of Power Distribution Network by Nida Khanam, Mohd. Rihan, Salman Hameed

“…The suggested method uses a hybrid Multi-Objective Particle Swarm Optimization and Differential Evolution (MOPSO-DE) algorithm to find the best PMU positions and the Weighted Least Squares (WLS) method to estimate voltage magnitude. …”
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Implementation of laser-light backscattering imaging for authentication of the geographic origin of Indonesia region citrus by Muhammad Achirul Nanda, S. Rosalinda, Rahmat Budiarto, Inna Novianty, Taufik Ibnu Salim, Pradeka Brilyan Purwandoko, Dimas Firmanda Al Riza

“…Furthermore, a combination of the gray-level co-occurrence matrix (GLCM) method and support vector machine (SVM) algorithm was applied to extract texture features and build a classification model, respectively. …”
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Estimation of performance measures in a novel M/M/1 queueing model with reverse balking: A simulation-based approach by Asmita Tamuli, Dhruba Das, V. Deepthi, Amit Choudhury, Dibyajyoti Bora, Bhushita Patowari, Supahi Mahanta

“…Moreover, Bayesian estimates yield lower RMSE compared to ML estimates, highlighting their superior accuracy and robustness. Additionally, predictive probabilities for the number of customers in the system are obtained. …”
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The future of precision orthopaedics: personalized data-driven practice by Deiary F. Kader, Andrew Coppola, Aditya Vijay, Andreas Fontalis, Fares S. Haddad

“…However, challenges related to data quality, algorithm transparency, ethical considerations, and infrastructure development must be addressed to ensure robust and equitable implementation. …”
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Pioneering CPMI framework for accurate state-of-health assessment in Lithium ion battery power management using FBG sensors by Taher M. Ghazal, Ali Q. Saeed, Mosleh M. Abualhaj, Taj-Aldeen Naser Abdali, Munir Ahmad

“…The proposed system employs a support vector-based classification algorithm that categorizes operational states based on FBG sensor data streams, identifying deviations from optimal temperature and voltage ranges. …”
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Unveiling diagnostic biomarkers and therapeutic targets in lung adenocarcinoma using bioinformatics and experimental validation by Sixuan Wu, Yuanbin Tang, Qihong Pan, Yaqin Zheng, Yeru Tan, Junfan Pan, Yuehua Li

“…In addition, a machine learning model constructed based on Stepglm[backward] with the random forest algorithm achieved the highest C-index (0.999) and screened eight core genes, among which ST14 was noted for its excellent predictive ability. …”
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Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes by Zhaoyang Wang, Shuo Wang, Damien Ernst, Chenguang Xiao

“…Automated Class Imbalance Learning (AutoCIL) is an emerging paradigm that leverages Combined Algorithm Selection and Hyperparameter Optimization (CASH) to automate the configuration of resampling strategies and classifiers for imbalanced classification tasks. …”
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Snow Depth Retrieval Using Sentinel-1 Radar Data: A Comparative Analysis of Random Forest and Support Vector Machine Models with Simulated Annealing Optimization by Yurong Cui, Sixuan Chen, Guiquan Mo, Dabin Ji, Lansong Lv, Juan Fu

“…In this study, we used Sentinel-1 radar data and employed a simulated annealing algorithm to select the optimal influencing factors from radar backscatter characteristics and spatiotemporal geographical parameters within the study area. …”
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An integrated Artificial neural network technique to optimize the various parameters of Pineapple/SiO2/epoxy-based nanocomposites under NaOH treatment by Natrayan Lakshmaiya, Naga Dheeraj Kumar Reddy Chukka, Seeniappan Kaliappan, V. Balaji, Nimel Sworna Ross, Ramya Maranan

“…Quantitative optimisation using the Taguchi technique Depending on the S/N ratio of Taguchi refinement, the nanocomposite with the maximum mechanical performance contains 20 % pineapple fibre with a length of 10 mm, 5 % nano SiO2, and 6 h of NaOH treatment. The ANN predictive algorithm and the Taguchi L27 array show that the experiment and projected data for tensile, flexural, and impact are within 3 % and 4 %. …”
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Unravelling Antimicrobial Resistance in <i>Mycoplasma hyopneumoniae</i>: Genetic Mechanisms and Future Directions by Raziallah Jafari Jozani, Mauida F. Hasoon Al Khallawi, Darren Trott, Kiro Petrovski, Wai Yee Low, Farhid Hemmatzadeh

“…Additionally, bioinformatic tools utilizing machine learning algorithms, such as CARD and PATRIC, can predict resistance traits, with PATRIC predicting 7 to 12 AMR genes and CARD predicting 0 to 3 AMR genes in 24 whole genome sequences available on NCBI. …”
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Research on Data-Driven Performance Assessment and Fault Early Warning of Marine Diesel Engine by Haiyan Wang, Zihan Wang, Biao Shi

“…To enable proactive prediction of marine diesel engine failure time and root causes, thereby reserving sufficient time for maintenance, this study proposes a data-driven multi-algorithm integration framework for performance assessment and fault early warning in marine diesel engines. …”
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