Non-parametric feature selection and machine learning based seasonal GHI prediction for SAPV systems in India by Aadyasha Patel, Gnana Swathika O․V․

“…Performance is evaluated based on error metrics revealing that Gaussian Process Regression model outperformed others in various Indian climatic conditions, while Ensemble of Trees model was less effective across all conditions.…”
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Digital Storytelling and Brand Trust Drive Generation Z in Skincare Purchase Decisions by Maulana Aditya Alfian Noor, Rizky Aditya Wirayudha, Siska Ernawati Fatimah

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AI driven prediction of early age compressive strength in ultra high performance fiber reinforced concrete by Mohamed Abdellatief, Wafa Hamla, Hassan Hamouda

“…These models include support vector regression (SVR), random forest (RF), artificial neural network (ANN), gradient boosting (GB), and Gaussian Process Regression (GPR). …”
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Cross language transformation of free text into structured lobectomy surgical records from a multi center study by Xiongwen Yang, Yi Xiao, Di Liu, Huiyin Deng, Jian Huang, Yubin Zhou, Chuanzhou Dai, Jun Wu, Dan Liu, Maoli Liang, Chuan Xu

“…Nonetheless, GPT-4o shows great potential in standardizing surgical records, streamlining workflows, and boosting care and research in thoracic oncology.…”
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Modern Approaches to Detect and Classify Comment Toxicity Using Neural Networks by Sergey V. Morzhov

“…The growth of popularity of online platforms which allow users to communicate with each other, share opinions about various events, and leave comments boosted the development of natural language processing algorithms. …”
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Stuck-at Faults Tolerance and Recovery in MLP Neural Networks Using Imperfect Emerging CNFET Technology by An Qi Zhang, Amr M. S. Tosson, Dylan Ma, Rebecca Fang, Lan Wei

“…On the other hand, applications with inherent error resilience and high-performance demands would suppress the impact of process imperfection and benefit from the performance boost. …”
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Current Status of Enhanced Oil Recovery Projects Using Carbon Dioxide (EOR CO₂) in Croatia by Paolo Blecich, Igor Wolf, Tomislav Senčić, Igor Bonefačić

“…The CO₂ source is a natural gas processing plant, which released the CO₂ into the atmosphere prior to the EOR project. …”
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Bayesian surrogate assisted neural network model to predict the hydrogen storage in 9-ethylcarbazole by Ahsan Ali, Mohammad Usman, Hafiz Muhammad Ali, Uzair Sajjad, Md. Abdul Aziz, M. Nasiruzzaman Shaikh

“…To enhance the predictive accuracy and develop an optimal DNN model, Bayesian Surrogate Random Forest (BSRF), Bayesian Surrogate Gaussian Process (BSGP), and Bayesian Surrogate Gradient Boost Regression Trees (BSGBRT) were integrated with deep neural networks (DNNs). …”
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Engine and Emission Performance of Renewable Fuels in a Small Displacement Turbocharged Diesel Engine by Ornella Chiavola, Jonas Matijošius, Fulvio Palmieri, Erasmo Recco

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Application of UHPLC-ESI-MS/MS-Based Metabonomic Techniques to Analyze the <i>Cordyceps cicadae</i> Metabolic Profile Changes to the CO(NH₂)₂ Response Mechani... by Miaomiao Wang, Zhicai Zhang, Fenghui Shi, Weijie Wu

“…Nitrogen source is a necessary nutrient factor in the process of mycelial growth and metabolite synthesis. …”
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Multi-criteria decision analysis for regional-scale flood susceptibility mapping in Kerala state, India by M. S. Kendagannaswamy, C. K. Roopa, B. S. Harish, M. S. Mukesh

“…An efficient framework integrating Light Gradient Boosting Machine (LightGBM) learning models with the Analytic Hierarchy Process (AHP) is proposed to address this issue by enhancing flood susceptibility understanding and informed decision-making. …”
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Development of a Self-Updating System for the Prediction of Steel Mechanical Properties in a Steel Company by Machine Learning Procedures by Valerio Zippo, Elisa Robotti, Daniele Maestri, Pietro Fossati, David Valenza, Stefano Maggi, Gennaro Papallo, Masho Hilawie Belay, Simone Cerruti, Giorgio Porcu, Emilio Marengo

“…This study is focused on the implementation of statistical learning methods for the prediction of the mechanical properties of steel products from the chemical profile of the raw material and the process parameters. The integration of this model into the production process allows a large-scale steel industry to predict steel properties with heightened accuracy, optimizing the manufacturing process for minimal waste and improved consistency. …”
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Estimation and validation of solubility of recombinant protein in E. coli strains via various advanced machine learning models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…Various models, including AdaBoost, Decision Tree Regression (DT), Gaussian Process Regression (GPR), and K-Nearest Neighbors (KNN) are applied to capture the intricate relationships between experimental factors and protein solubility. …”
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Improved production of thermostable pectinase from novel Bacillus siamensis (BIOSMNF45) using computational-conventional approach by Anushka Satpathy, Koel Mukherjee, Vinod Kumar Nigam

“…Abstract The demand for thermostable pectinase in the global commercial market has expanded progressively at a rapid pace. Many industrial processes are operated at elevated temperatures to break down plant polysaccharides (pectin) owing to the significant use of thermotolerant pectinase. …”
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Tourism marketing: Channel, factor, and strategy for foreign market share in Badung Regency by Nyoman Ariana, I Ketut Sutama, Ida Bagus Gde Pujaastawa, Agung Suryawan Wiranatha, I Gusti Bagus Arya Yudiastina, Wayan Agung Panca P

“…Data analysis used Importance Performance Analysis (IPA) and Analytical. Hierarchy Process (AHP) methods, supported by SPSS and Expert Choice software. …”
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Enhancing FDG Production Efficiency on Explora FDG4 Synthesis Module: A Journey of Innovation and Excellence at Neurospinal & Cancer Care Post Graduate Institute by Syed Muhammad Haider Zaidi, Fatima Batool, Naheed Ghaffar

“…It indicates that more stable and efficient production can be achieved through regular maintenance, process monitoring, and process improvement. Conclusion: FDG production can be boosted by regular maintenance, process monitoring, and process improvements on internal processes, as shown in this study. …”
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<i>Zingiber officinale</i> Polysaccharide Silver Nanoparticles: A Study of Its Synthesis, Structure Elucidation, Antibacterial and Immunomodulatory Activities by Xiaoyu Chang, Huina Xiao, Mingsong Li, Yongshuai Jing, Kaiyan Zheng, Beibei Hu, Yuguang Zheng, Lanfang Wu

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Developing a confidence interval-based fuzzy testing method using the small bias estimator of the six sigma quality index by Kuen-Suan Chen, Kuei-Kuei Lai, Chun-Min Yu, Yu-Jin Hsu

“…Meanwhile, this approach is also beneficial to the advancement of smart manufacturing practices, thereby boosting process quality and product value in the industry.…”
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LAND SUITABILITY ASSESSMENT FOR SOYBEAN (GLYCINE MAX) IN BARDAGHAT MUNICIPALITY USING GIS TECHNIQUES by Birendra Tiwar, Amrit Dumre, Mahesh Jaishi

“…The central aim of this research is to assess land suitability for soybean cultivation within the study area, with the overarching objective of boosting crop productivity and refining land use planning strategies. …”
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Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…Further, it provides a scalable avenue toward multi-objective and exploratory process optimizations that could extend well beyond the confines of traditional experimental design.…”
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