Design of a Machine Learning-Based Platform for Currency Market Prediction: A Fundamental Design Model by Kevin Gordillo-Orjuela, Paulo Alonso Gaona-García, Carlos Enrique Montenegro-Marín

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Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

“…Dark fermentation process from low-cost renewable substrates for simultaneous wastewater treatment and hydrogen production (H2) is suitable due to economic viability and environmental sustainability. …”
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A Bag-of-Words Approach for Information Extraction from Electricity Invoices by Javier Sánchez, Giovanny A. Cuervo-Londoño

“…It is typical to rely on machine-learning techniques to automate the process, reduce manual labor, and minimize errors. …”
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Advancing risk assessment in renewable power plant construction: an integrated DEA-SVM approach by Reza Rasinojehdehi, Seyyed Najafi

“…Subsequently, a SVM is developed to monitor the process, concluding with tailored risk treatment and monitoring processes specifically designed for the unique context of Iran's solar energy landscape.…”
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Fake News Detection System using Machine Learning with Recurrent Neural Networks by Kuditat O. Jimoh, Lawrence O. Omotosho, Ibrahim K. Ogundoyin, Olajide Y. Adebayo

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Microsporidian infection of mosquito larvae changes the host-associated microbiome towards the synthesis of antimicrobial factors by Artur Trzebny, Abigail D. Taylor, Jeremy K. Herren, Johanna K. Björkroth, Sylwia Jedut, Miroslawa Dabert

“…The host-associated microbiome of the mosquito can play a pivotal role in various physiological processes of this host, including its vector competence for pathogens. …”
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Approximate Symmetries and Conservation Laws for Mechanical Systems Described by Mixed Derivative Perturbed PDEs by Shamaoon A., Agarwal P., Cesarano C., Jain S.

“…In response to this challenge, we embarked on the rectification process. By integrating these additional terms into our model, we could modify the conserved vectors, deriving new modified conserved vectors. …”
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Multi-material additive manufacturing of conductor-insulator compounds for battery cell cap fabrication by Thomas Bareth, Daniel Eder, Maja Lehmann, Georg Schlick, Christian Seidel

“…Initial results from mono-material ceramic manufacturing were followed by a detailed analysis of the multi-material process between the metals and ceramics. Various strategies for optimizing the material transition zone were explored, with the most effective approach incorporating a stepped interface design combined with overlapping laser vectors to compensate for thermal shrinkage. …”
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Short-Term Load Forecasting Based on Feature Selection and Combination Model by Yusong XU, Shanhua ZOU, Xianling LU

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Prediction of Rheological Parameters of Polymers by Machine Learning Methods by T. N. Kondratieva, A. S. Chepurnenko

“…Along with these methods, due to the capability to process data with highly nonlinear dependences between features, machine learning methods such as the k-nearest neighbor method, and the support vector machine (SVM) method, are widely used in related areas. …”
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VIRTUAL MODELS OF LIGHT BACKSCATTERING IN RING LASERS by A. S. Bessonov, E. A. Petrukhin

“…A mathematical description of the backscattering processes based on the determination of the complex coupling parameters of counterpropagating waves is presented. …”
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Predicting biogas production in real scale anaerobic digester under dynamic conditions with machine learning approach by M. Erdem Isenkul, Sevgi Güneş-Durak, Yasemin Poyraz Kocak, İnci Pir, Mertol Tüfekci, Güler Türkoğlu Demirkol, Selçuk Sevgen, Aslı Seyhan Çığgın, Neşe Tüfekci

“…Biogas production through anaerobic digestion (AD) of industrial organic waste and wastewater offers a sustainable method for energy recovery. However, since process efficiency heavily relies on operational factors, continuous monitoring of the AD process and the implementation of necessary operational strategies are crucial. …”
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Advancing Geotechnical Evaluation of Wellbores: A Robust and Precise Model for Predicting Uniaxial Compressive Strength (UCS) of Rocks in Oil and Gas Wells by Mohammadali Ahmadi

“…The investigation encompasses Linear Regression, ensemble methods (including Random Forest, Gradient Boosting, XGBoost, and LightGBM), support vector machine-based regression (SVM-SVR), and multilayer perceptron artificial neural network (MLP-ANN) models. …”
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New Heuristics Method for Malicious URLs Detection Using Machine Learning by Maher Kassem Hasan

“…All the optimization processes, model performances, and integration into the real-time cybersecurity infrastructures, along with the strengths and limitations, are discussed in this paper. …”
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Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning by YU Ting1, ZHANG Yinyin2, ZHANG Ruizhi3, JIN Wenlei2, LUO Yingting2, ZHU Shengfeng3, HE Hui1, YE Guoan1, GONG Helin4

“…Spent fuel reprocessing is an important nuclear energy process which aimed at recovering resources and managing radioactive materials to control potential hazards. …”

CLASSIFICATION AND PREDICTION OF BENTHIC HABITAT FROM SCIENTIFIC ECHOSOUNDER DATA: APPLICATION OF MACHINE LEARNING ALGORITHMS by Baigo HAMUNA, Sri PUJIYATI, Jonson Lumban GAOL, Totok HESTIRIANOTO

“…The classification and prediction process of benthic habitats uses two machine learning algorithms, Random Forest (RF) and Support Vector Machine (SVM), in XLSTAT Basic+ software. …”
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Group-Specific SVM With Bilevel Programming Methods for Parameter Optimization and Explainable AI in Urban Quality of Life Prediction by Gonzalo Rios-Vasquez, Hanns De La Fuente-Mella, Jose Ceroni-Diaz

“…These findings provide valuable insights for policymakers, supporting data-driven decision-making processes for urban development and resource allocation. …”
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Modeling and Analysis of Dynamics of Rigid–Flexible Coupled Parallel Robots by Leilei Wang, Wei Xu, Fei Guo, Hao Yan, Yunxue Wang

“…Rigid–flexible coupled robots have problems such as vibration and elastic deformation caused by the flexibility of the members during the motion process, which significantly impacts the system’s motion accuracy and dynamics performance. …”
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HashTrie:a space-efficient multiple string matching algorithm by Ping ZHANG, Yan-bing LIU, Jing YU, Jian-long TAN

“…The famous multiple string matching algorithm AC consumed huge memory when the string signatures were massive,thus unable to process high speed network traffic efficiently.To solve this problem,a space-efficient multiple string matching algorithm-HashTrie was proposed.This algorithm adopted recursive hash function to store the patterns in bit-vectors in place of the state transition table in order to reduce space consumption.Further more it made use of the rank operation for fast verification.Theoretic analysis shows that the space complexity of HashTrie is O(|P|),which is linear with the size of pattern set |P|and is independent of the alphabetsize σ.The space complexity is superior to the complexity O(|P|σlog|P|)of AC.Experiments on synthetic datasets and real-world datasets(such as Snort,ClamAV and URL)show that HashTrie saves up to 99.6% storage cost compared with AC,and in the meanwhile it runs at a matching speed that is about half of AC.HashTrie is a space-efficient multiple string matching algorithm that is appropriate to search large scale pattern strings with short lengths.…”
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Research of the Combined Trajectory Planning of Descartes Space and Joint Space by Lai Xiao, Liu Yong, Luo Wenguo, Dai Yanxia, Zeng Han

“…Through the closed loop vector method,kinematics equation is established and the space trajectory is fitted based B spline function model,the motion curve of the joint space planning and the motion curve of Descartes space planning and the motion curve of combined space planning are obtained. …”
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