New Approach of Blind Adaptive Equalizer Based on Genetic Algorithms by Caroline A. D. Silva, Marcelo A. C. Fernandes

“…Unlike traditional methods that rely on linear programming and suffer from local minima issues, this technique utilizes a stochastic linear programming cost function with GAs for robust optimization. The proposed method termed Blind Linear Equalizer based on genetic algorithm (BLE-GA) enhances performance by leveraging a GA’s ability to handle stochastic variables, offering rapid convergence and resilience against signal noise and inter-symbol interference. …”
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THE STRUCTURE OF HAPPINESS REPRESENTATION FOR RUSSIAN AND AMERICAN REPRESENTATIVES by S. Yu. Zhdanova, A. V. Pecherkina, A. A. Strokanov

“…Statistical analysis of the data was based on the use of the coefficient of φ-angular Fisher transform, correlation coefficient φ, and cluster analysis.Results and scientific novelty. …”
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Shell and tube heat exchanger optimization: A critical literature assessment and fairness-based comparative performance analysis of meta-heuristic algorithms by Samet Gürgen

“…In order to make comparisons, the objective function, decision variables and their boundary values were taken as the same. …”
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Binary composite crossover genetic algorithm for locating critical slip surface by Wei Qin, Jiancheng Zhao

“…A reasonable combination of parameters for the binary composite crossover (BCC) operator in the RGA-BCC is determined through six benchmark function experiments. On this basis, the stability of five soil slopes from the literature was analysed using the RGA-BCC in combination with the Morgenstern and Price method, and the results obtained were compared with those in the published literature to demonstrate that the RGA-BCC is able to efficiently determine the CSSs of slopes and their minimum factors of safety. …”
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Phenotypic screen of early-developing larvae of the blood fluke, schistosoma mansoni, using RNA interference. by M M Mourão, Nathalie Dinguirard, Glória R Franco, Timothy P Yoshino

“…Although RNAi holds great promise as a functional genomics tool for larval schistosomes, our finding of potential off-target or nonspecific effects of some dsRNA treatments and variable efficiencies in specific gene knockdown indicate a critical need for gene-specific testing and optimization as an essential part of experimental design, execution and data interpretation.…”
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Effects of two types of repetitive transcranial magnetic stimulation on brain network in Parkinson’s disease by Shuo Liu, Shuo Yang, Chen Wang, Jiarui Li, Lei Wang

“…The iTBS group showed post-treatment changes involving more brain regions in spatiotemporal variability. This study demonstrates that compared to 10Hz-rTMS, iTBS can reduce treatment time while providing superior improvement in functional brain connectivity for PD patients.…”
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Optimally controlled heating of solid particles in a fluidised bed with a dispersive flow of the solid by Poświata Artur, Szwast Zbigniew

“…The mixing rate was described by the axial dispersion coefficient. As any economic values of variables describing analysing process are subject to local and time fluctuations, the accepted objective function describes the total cost of the process expressed in exergy units. …”
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Time-varying MVAR algorithms for directed connectivity analysis: Critical comparison in simulations and benchmark EEG data. by Mattia F Pagnotta, Gijs Plomp

“…Results from numerical simulations and from benchmark EEG recordings showed that: i) across a broad range of model orders all algorithms correctly reproduced patterns of interactions; ii) signal downsampling degraded connectivity estimation accuracy for most algorithms, although in some cases downsampling was shown to reduce variability in the estimates by lowering the number of parameters in the model; iii) single-trial modeling followed by averaging showed optimal performance with larger adaptation coefficients than previously suggested, and showed slower adaptation speeds than multi-trial modeling. …”
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Versatile machine learning algorithms for FTIR spectroscopy: differentiating crosslinked and non-crosslinked gelatin samples by Juliana Rincón-López, Eliana Álvarez-Valdés, Daniela Velez-Arango, Estefanía Rojas Zuleta, Leidy Yuliana Vargas Soto, Liliana Lellesch, Victor Alonso García Londoño, Milton Rosero-Moreano, Gonzalo Taborda-Ocampo

“…The functional and mechanical properties of the gelatin depend on the chemical and structural characteristics. …”
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Adsorption of Cd (II) Using Chemically Modified Rice Husk: Characterization, Equilibrium, and Kinetic Studies by Javier Montalvo-Andía, Warren Reátegui-Romero, Alexis D. Peña-Contreras, Walter F. Zaldivar Alvarez, María E. King-Santos, Víctor Fernández-Guzmán, José Luis Guerrero-Guevara, Jhon E. Puris-Naupay

“…In optimal experimental conditions, the maximum adsorption efficiency was 92.65%. Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) were used allowing the identification of the main functional groups and morphology of rice husk and treated rice husk, and the results showed an improvement of adsorption characteristics after rice husk treatment with NaOH. …”
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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

“…This study investigates the operational efficiency of the lab-scale oxidation ditch (OD) functioning in simultaneous nitrification and denitrification modes, focusing on forecasting biochemical oxygen demand (BOD₅) concentrations over a five-day horizon. …”
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Multiobjective Optimization of Stress-Release Boot of Solid Rocket Motor under Vertical Storage Based on RBF Model by Qiuwen Miao, Huihui Zhang, Zhibin Shen, Weiyong Zhou

“…Stress-release boot can effectively improve the structural integrity of SRM (solid rocket motor), but it will also influence the loading fraction and interior ballistic performance, so the purpose of this paper is to propose a multiobjective optimization method for stress-release boot. The design variables are the front and rear depth of the stress-release boot, and four optimization variables were determined according to the analysis of SRM performance. …”
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Comparative Analysis of ANFIS and State-ANFIS for Forecasting Cooking Oil Prices Based on Processed Palm Oil Yield (Crude Palm Oil) by Brodjol Sutijo Suprih Ulama, Fausania Hibatullah, Mochammad Reza Habibi, null Makkulau

“…Our analysis underscores S-ANFIS’s superiority over ANFIS, particularly with Gaussian membership functions, as it reduces RMSE and MAPE values by half while requiring fewer nodes, thereby improving computational efficiency. …”
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Application of machine learning and neural network models based on experimental evaluation of dissimilar resistance spot-welded joints between grade 2 titanium alloy and AISI 304 s... by Marwan T. Mezher, Alejandro Pereira, Rusul Ahmed Shakir, Tomasz Trzepieciński

“…The best prediction model was found to be the ANN model when training the conjugate gradient with the Polak-Ribiere updates (Traincgp) training function with the hyperbolic tangent sigmoid transfer function (Tansig) with the mean squared error (MSE) and correlation coefficient (R2) values recorded as 0.01886 and 0.94973, respectively. …”
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Comparative Study of the Impact of Corruption on the Human Development Index by T. M. Zharlygassinov, A. Zh. Panzabekova, M. S. Dosmanbetova

“…The reason for this is the significant negative impact of this phenomenon on the standard of living of citizens and the efficiency of the functioning of state bodies. However, the strength of such interaction may differ depending on the country and how conscientiously the employees of its state apparatus carry out their work. …”
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Statistical Identification of Parameters for Damaged FGM Structures with Material Uncertainties in Thermal Environment by Yalan Xu, Yu Qian, Kongming Guo

“…The numerical simulation results show the efficiency and effectiveness of the presented method for the identification of material parameter variability by using the measurable modal parameters of damaged FGM structures.…”
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Numerical discussion of phase-lag mixed integral equations with general discontinuous kernels by Abeer M. Al-Bugami, M. A. Abdou

“…This integral equation has coefficients that vary in time and phase-lag time. It was proven that this method linked the time variables to the kernel of the integral equation in terms of the existence of a single solution. …”
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COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) by Yuniar Farida, Ida Purwanti, Nurissaidah Ulinnuha

“…The analysis results obtained the best method in predicting ISSI values, namely nonparametric kernel regression using Nadaraya-Watson estimator and Gaussian kernel function with the MAPE value of 15% and the coefficient of determination of 85%. …”
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Assessing the effect of dynamics of unpredictable locust invasive behavior and its effect on food security and community livelihood by Mfano Charles Petro

“…Additionally, it was observed that the deterrent coefficient in the invaded and source zones (ηi and ηs) has a significant impact on controlling the dynamic behavior of locusts.…”
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Prediction of Pile Bearing Capacity Using Opposition-Based Differential Flower Pollination-Optimized Least Squares Support Vector Regression (ODFP-LSSVR) by Nhat-Duc Hoang, Xuan-Linh Tran, Thanh-Canh Huynh

“…Based on such datasets, LSSVR is capable of generalizing a multivariate function that estimates values of pile bearing capacity based on a set of variables describing pile characteristics and ground conditions. …”
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