Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information by Zuhaib Nishter, Fangzong Wang

“…This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…Timely identification is crucial for efficient intervention, as untreated diabetic retinopathy can progress to irreversible vision loss. …”
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Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…This deep learning method is computationally efficient, fast, and reliable for synthetic image realizations. …”
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Cost-effective process design for methanol synthesis from carbon dioxide hydrogenation by Sheng-Zhong Huang, Chih-Yao Lin, Chianghui Wang, Akhmat Fauzan Saputra, Henggar Yudha Hananto, Nicolas Justin Sutanto, Anggit Raksajati, Vincentius Surya Kurnia Adi

“…Accordingly, this research introduces an optimization framework capable of handling diverse process configurations, operating variables, and their interactions. This approach enables effective optimization using total annual cost (TAC) as the objective function and significantly enhances process design efficiency. …”
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Multi-Objective Optimal Design of 200 kW Permanent Magnet Synchronous Motor Based on NSGA-II by Chengxu Sun, Qi Li, Tao Fan, Xuhui Wen, Ye Li, Hongyang Li

“…Interior permanent magnet synchronous motors (IPMSMs) are widely applied as drive motors in electric vehicles because they have the advantages of high power density, high efficiency, and excellent dynamic performance. This paper introduces a framework for multi-objective optimization, tailored for the demands of V-Shaped IPMSMs, which involves high-dimensional variables. …”
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COVID-19 recovery: benefits of multidisciplinary respiratory rehabilitation by Wim Janssens, Greet Hermans, Rik Gosselink, Daniel Langer, Thierry Troosters, Hilde Beyens, Stephanie Everaerts, Arne Heyns, Natalie Lorent

“…Impressive results on physical recovery were determined after 6 weeks and 3 months, with significant improvement of lung function, muscle force and exercise capacity variables. …”
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Fusion of Multimodal Audio Data for Enhanced Speaker Identification Using Kolmogorov-Arnold Networks by Aryaman Tamotia, Dhruv Shantu Karmokar, Rethi Komal, K. Khadar Nawas, A. Shahina, A. Nayeemulla Khan

“…One of the critical innovations within this design is a class of trainable activation functions that eliminate the need for traditional weight parameters, thereby providing scalable and computationally efficient solutions. …”
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Codesign of Transmit Waveform and Receive Filter with Similarity Constraints for FDA-MIMO Radar by Qiping Zhang, Jinfeng Hu, Xin Tai, Yongfeng Zuo, Huiyong Li, Kai Zhong, Chaohai Li

“…Finally, the Riemannian limited-memory Broyden–Fletcher–Goldfarb–Shanno (RL-BFGS) algorithm is employed to optimize the variables in parallel. Simulation results demonstrate that our method achieves a 0.6 dB improvement in SINR compared to existing methods while maintaining competitive computational efficiency. …”
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Parametric-modeling-based multi-objective thermoelastic optimization of rudder structures by Shi Guanghui, Bao Yuhao, Wu Wenhua, Guo Guiqiang, Lin Ye, Zhang Xiaopeng, Tao Ran

“…To efficiently analyze and optimize the structural performance of rudder structures, a parametric optimization model for the radial configuration of reinforcement ribs is constructed. …”
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Robust Optimization Research of Cyber–Physical Power System Considering Wind Power Uncertainty and Coupled Relationship by Jiuling Dong, Zilong Song, Yuanshuo Zheng, Jingtang Luo, Min Zhang, Xiaolong Yang, Hongbing Ma

“…Furthermore, the deterministic power balance constraints are relaxed into inequality constraints that account for wind power forecasting errors through fuzzy variables. The lower-level model focuses on minimizing traffic load shedding by establishing a topology–function-constrained information network traffic model based on the maximum flow principle in graph theory, thereby improving the efficiency of network flow transmission. …”
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Research on Robust Adaptive Model Predictive Control Based on Vehicle State Uncertainty by Yinping Li, Li Liu

“…To overcome these limitations, three key innovations are introduced: a three-degree-of-freedom vehicle dynamic model integrated with recursive least squares-based online estimation of tire slip stiffness for real-time lateral force compensation; an adaptive weight adjustment mechanism that dynamically balances control energy consumption and tracking accuracy by tuning cost function weights based on real-time state errors; and a dynamic constraint relaxation strategy using slack variables with variable penalty terms to resolve infeasibility while suppressing excessive constraint violations. …”
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Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model by Moses Oluwatobi Fajobi, Olumuyiwa Ajani Lasode, Adekunle Akanni Adeleke, Peter Pelumi Ikubanni, Ayokunle Olubusayo Balogun, Prabhu Paramasivam

“…The Gaussian membership function (Gauss-mf) was implemented for the fuzzification of input variables, while the hybrid algorithm was selected for the learning and mapping of the input-output dataset. …”
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Retrieval of carbon and inorganic phosphorus during hydrothermal carbonization: ANN and RSM modeling by Abolfazl Shokri, Mohammad Amin Larki, Ahad Ghaemi

“…Next, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were used to compare the results and improve the model fit. …”
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Support vector regression model for the prediction of buildings’ maximum seismic response based on real monitoring data by Dongwang Tao, Shizhe Fang, Haixu Liu, Jianqi Lu, Jiang Wang, Qiang Ma

“…Our results demonstrate that SVR-MDR model outperform other machine learning models such as kernel ridge regression and decision tree models, and SVR-MDR and RSVR-MDR models outperform conventional loglinear regression and multinomial models, because SVR can map the complex nonlinear function of multiple variables and consider the available information of buildings especially the fundamental frequency. …”
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Effect of Solvent and Grain Color on the Biological Activities of Maize Grain by Yolanda Salinas-Moreno, Miguel Ángel Martínez-Ortiz, Eduardo Padilla-Camberos, José Luis Ramírez-Díaz, Alejandro Ledesma-Miramontes, Ivone Alemán de la Torre, Alberto Santillán-Fernández

“…The color of maize grain, ranging from pink to purple, is related to the presence of phenolic compounds whose efficient extraction is affected by the solvent used. …”
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The Relationship between Optimism and Mindfulness with Cognitive Performance in Older Adults by Sanaz Ghannadi, Morteza Tarkhan

“…Furthermore, 34% of the variance in cognitive function was explained by optimism and mindfulness.Conclusion: Therefore, based on the findings of the present study, it can be concluded that optimism and mindfulness are important variables in predicting cognitive function (p < 0.05).…”
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CGF with Bio-Oss collagen as grafting materials for simultaneous implant placement after osteotome sinus floor elevation: a prospective study by Bashar Shahood, Seba Harphoush, Belal O. M. Muhaisen, Jing Qiu

“…The Implants Survival Rate (ISR) was the primary outcome variable. Secondary outcome variables included radiographic measurements assessed at four follow-up time points, the Implant Stability Quotient (ISQ), and bone density (B). …”
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Performance evaluation of atmospheric water generation in different climates using thermoelectric cooling by Ali M. Ashour, Sarmad A. Ali, Saif Ali Kadhim, Luttfi A. Al-Haddad, Ali Habeeb Askar, Farhan Lafta Rashid, Ravishankar Sathyamurthy

“…In contrast, the variable voltage mode improves efficiency by 30 %, albeit with a lower water yield. …”
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Mechanical Properties and Statistical Damage Constitutive Model of Rock under a Coupled Chemical-Mechanical Condition by Yun Lin, Feng Gao, Keping Zhou, Rugao Gao, Hongquan Guo

“…To investigate the mechanical damage evolution process of rock under a coupled chemical-mechanical (CM) condition, an improved statistical damage constitutive model was established using the Drucker-Prager (D-P) strength criterion and two-parameter Weibull distribution. The damage variable correction coefficient and chemical damage variable which was determined by porosity were also considered in the model. …”
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Some New Connection Relations Related to Classical Orthogonal Polynomials by Wathek Chammam, Wasim Ul-Haq

“…In this paper, we deal with a problem of positivity of linear functionals in the linear space ℙ of polynomials in one variable with complex coefficients. …”
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