Machine learning-based prediction of speed of sound in fatty acid ethyl esters by Kusum Yadav, Shahad Almansour, Lulwah M. Alkwai, Anupam Yadav, Mehrdad Mottaghi

“…This conclusion was drawn from extensive statistical evaluations and visualization techniques. CNN achieved an R² value of 0.9996, with low average absolute relative error and mean squared error, outperforming other tested algorithms. …”
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Design optimization of multipoles radial magnetic bearings for large industrial rotors by Antoine S. Dimitri, Nada A. Rashed, Hesham A. Hegazi, Mohamed H. El-Shazly

“…The magnetic force equations are derived as function of the number of poles of the AMB. Two different optimization techniques are implemented: Sequential quadratic programming (SQP), and genetic algorithm (GA). …”
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Development of data driven models to accurately estimate density of fatty acid ethyl esters by Walid Abdelfattah, Munthar Kadhim Abosaoda, Hardik Doshi, H. S. Shreenidhi, Manoranjan Parhi, Devendra Singh, Prabhjot Singh, Abdolali Yarahmadi Kandahari

“…The objective of this study is to construct advanced predictive algorithms using various machine learning methods, including AdaBoost, Decision Trees, KNN, Random Forests, Ensemble Learning, CNN, and SVR. …”
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Double-transmitting and Sextuple-receiving Borehole Transient Electromagnetic Method and Experimental Study by Bo Wang, Shengdong Liu, Shining Li, Fubao Zhou

“…The results show that the double-transmitting and sextuple-receiving borehole TEM has decent resolution ability in detecting the radial azimuth of the anomaly, and the effective resolution is 30°. The geometric difference among induced voltages of different measuring points can be used to evaluate the radial depth of the anomaly qualitatively. …”
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The study on dynamic modeling and path planning of a manta ray-inspired underwater glider by Yi Zhang, Jianing Zhang, Zhiyang Guo, Lei Zhang, Yuchen Shang, Weimin Chen

“…The path planning problem is transformed into a multi-objective optimization problem by incorporating the performance evaluation model into the research and solved using the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) algorithm for different motion strategies. …”
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Optimization of OPM-MEG Layouts with a Limited Number of Sensors by Urban Marhl, Rok Hren, Tilmann Sander, Vojko Jazbinšek

“…System conversion was done by calculating a current distribution on the brain surface using minimum norm estimation (MNE). We evaluated the SSA’s performance under different protocols, for example, using measurements of single or combined OPM components. …”
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A Mixed-Integer Linear Programming Model for Addressing Efficient Flexible Flow Shop Scheduling Problem with Automatic Guided Vehicles Consideration by Dekun Wang, Hongxu Wu, Wengang Zheng, Yuhao Zhao, Guangdong Tian, Wenjie Wang, Dong Chen

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The Design and Evaluation of a Direction Sensor System Using Color Marker Patterns Onboard Small Fixed-Wing UAVs in a Wireless Relay System by Kanya Hirai, Masazumi Ueba

“…In this paper, we describe the detailed algorithm of the sensor, and its performance is evaluated by using the prototype sensor system. …”
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CT-Derived Features as Predictors of Clot Burden and Resolution by Quentin Auster, Omar Almetwali, Tong Yu, Alyssa Kelder, Seyed Mehdi Nouraie, Tamerlan Mustafaev, Belinda Rivera-Lebron, Michael G. Risbano, Jiantao Pu

“…These patients were referred for invasive cardiopulmonary exercise testing (CPET) at the University of Pittsburgh Medical Center from 2018 to 2022, for whom we have ground truth classification of chronic PE, as well as CT-derived features related to body composition, cardiopulmonary vasculature, and PE clot burden using artificial intelligence (AI) algorithms. We applied Lasso regularization to select parameters, followed by (1) Ordinary Least Squares (OLS) regressions to analyze the relationship between clot burden and the selected parameters and (2) logistic regressions to differentiate between chronic and resolved patients. …”
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Evaluation of a Machine Learning Model Based on Laboratory Parameters for the Prediction of Influenza A and B in Chongqing, China: Multicenter Model Development and Validation Stud... by Weiwei Hu, Yulong Liu, Jian Dong, Xuelian Peng, Chunyan Yang, Honglin Wang, Yong Chen, Shan Shi, Jin Li

“…The CatBoost (CATB) algorithm was optimized via 5-fold cross-validation and random grid search using 24 routine blood parameters. …”
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An application of eye movement parameters collected from mass market devices for the estimation of a text comprehension by Ksenia Babanova, Arsen Revazov, Konstantin Chernozatonskiy, Andrey Pikunov, Victor Anisimov

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Three-Dimensional Adaptive Modulation and Coding for DDO-OFDM Transmission System by Xi Chen, Zhenhua Feng, Ming Tang, Borui Li, Huibin Zhou, Songnian Fu, Deming Liu

“…The introduced look-up table operation can reduce the iterations and improve the convergence speed. To evaluate the performance of the proposed algorithm, we tailor the system parameters of direct detection optical OFDM (DDO-OFDM) to investigate the difference of effective data rate (EDR) between fixed schemes and proposed adaptive modulation and coding (AMC) schemes. …”
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Accelerated preprocessing in task of searching substrings in a string by A. V. Mazurenko, N. V. Boldyrikhin

“…The paper lists eight algorithms. The developed algorithms are evaluated. …”
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Sentence Embedding Generation Framework Based on Kullback–Leibler Divergence Optimization and RoBERTa Knowledge Distillation by Jin Han, Liang Yang

“…Using TF-IDF-weighted cosine similarity evaluation, our model achieved a τ of 0.528, ρ of 0.518, and an MAE of 1.343. …”
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Enhanced Transmission Expansion Planning With a High Confidence Strategy Considering Fluctuations in Solar PV Generation and Electricity Demand by Siripat Somchit, Niphon Kaewdornhan, Rongrit Chatthaworn

“…To address this issue, this work proposes an enhanced TEP-based 24-hour situation optimized by an improved Binary Differential Evolution (BDE) algorithm assisted by the logistic map for adjusting the mutation factor and crossover rate. …”
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Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers by Ahmed Chiheb Ammari, Wael Labidi, Rami Al-Hmouz

“…AFBO is evaluated using real-world trace-driven simulations and compared against benchmark multi-objective algorithms, including multi-objective particle swarm optimization (MOPSO), simulated annealing-based bi-objective differential evolution (SBDE), and the baseline Multi-Objective Firefly Algorithm (MOFA). …”
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Optimal Structure to Maximize Torque per Volume for the Consequent-Pole PMSM and Investigating the Temperature Effect by Alireza Hosseinpour, Ahmed Abbas, Mahmoud Oukati Sadegh, Atif Iqbal, Aymen Flah, Lukas Prokop, Enas Ali, Ramy N. R. Ghaly

“…Therefore, to maximize the torque/volume ratio, four metaheuristic optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), and Teaching Learn Base Optimization (TLBO), have been implemented, and the mentioned index is optimized. …”
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Integral Approach-Based Sensitive Protection of Autotransformers for Turn-to-Turn Faults by Krzysztof Solak, Waldemar Rebizant, Frank Mieske

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An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid by Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal

“…Non-linear, coupled partial differential equations are transformed into ordinary differential equations with similarity scaling to characterize heat transfer and fluid flow, which are then numerically solved using the modified finite difference method (the Keller-Box method). …”
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GRL-ITransformer: An Intelligent Method for Multi-Wind-Turbine Wake Analysis Based on Graph Representation Learning With Improved Transformer by Kang Han, Li Xu

“…After that, the data driven method is employed to update the parameters, and the superiority of GRL-ITransformer is highlighted by analyzing and comparing with the existing five classical intelligent algorithms (belongs to four categories). The comprehensive results show that GRL-ITransformer has excellent performance in wind turbine wake field prediction and reconstruction, and always possesses the lowest error for a series of error evaluation indexes among all models.…”
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