Implementing FFE-MLSD With Improved BER and Reduced Complexity for Long-Reach PAM4 Wireline Receivers by Hanseok Kim, Sihyun Lee, Piljun Jeong, Jaeha Kim, Woo-Seok Choi

“…Simulation results show two orders of magnitude improvement in BER over conventional LMS-based FFE coefficient optimization. In addition, to mitigate the MLSD complexity, Top-K selection approach is proposed to select only the most relevant K branches for MLSD computation using a pre-computed lookup table. …”
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Germplasm Selection and Comprehensive Evaluation of Maize Inbred Lines at Germination and Seedling Stage for Saline–Alkali Tolerance by Shaoqi Ren, Jian Tan, Shuna Zhou, Haixiao Sun, Honggang Li, Wenjin Li, Nuo Li, Jinfeng Wu, Xuejiao Ren, Jiabin Ci, Weiguang Yang

“…The results indicate complex correlations among various traits at different growth stages. …”
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Predicting the evolution of pH and total soluble solids during coffee fermentation using near-infrared spectroscopy coupled with chemometrics by Vicente Tirado-Kulieva, Carlos Quijano-Jara, Himer Avila-George, Wilson Castro

“…The relevant wavelengths were then selected using the β coefficients, the important projection of variables (VIP), and the CAFS method. …”
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Optimal Stopping Theory-Based Online Node Selection in IoT Networks for Multi-Parameter Federated Learning by Seda Dogan-Tusha, Faissal El Bouanani, Marwa Qaraqe

“…This study introduces a novel optimal stopping theory (OST) based online node selection scheme for low complex and multi-parameter FL procedure in IoT networks. …”
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Complexation reaction with Sm(III): a facile spectrophotometric quantification of daunorubicin in pharmaceutical preparation and biological fluids by Basima A. A. Saleem

“…Optimal conditions for the formation of the pink complex were established by studying various factors, including pH, time, samarium concentration, and temperature. …”
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MSCPUnet: A multi-task neural network for plot-level crop classification in complex agricultural areas by Kedi Fang, Shengwei Zhang, Yongting Han, Lin Yang, Meng Luo, Lu Liu, Qian Zhang, Bo Wang

“…High-precision mapping of agricultural crops in complex planting areas is a prerequisite for precision agricultural management. …”
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Smart material selection strategies for sustainable and cost-effective high-performance concrete production using deep learning by T. Seethalakshmi, M. Murugan, P. Maria Antony Sebastin Vimalan

“…The creation of high-performing concrete (HPC) is greatly influenced by the selection of materials, with cost and sustainability factors playing a bigger part in contemporary building techniques. …”
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DeepAT: A Deep Learning Wheat Phenotype Prediction Model Based on Genotype Data by Jiale Li, Zikang He, Guomin Zhou, Shen Yan, Jianhua Zhang

“…This provides a data-driven selection criterion for genomic selection, making the selection process more efficient and targeted. …”
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SCM-DL: Split-Combine-Merge Deep Learning Model Integrated With Feature Selection in Sports for Talent Identification by Didem Abidin, Muhammed G. Erdem

“…The SCM-DL integrated with the RFE_DTC feature selection method achieved the highest performance for six features, yielding an accuracy rate of 97.40% and a Matthews Correlation Coefficient performance rate of 96.6%. …”
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An Effective and Interpretable Sleep Stage Classification Approach Using Multi-Domain Electroencephalogram and Electrooculogram Features by Xin Xu, Bei Zhang, Tingting Xu, Junyi Tang

“…Recent research efforts on automated sleep staging have focused on complex deep learning architectures that have achieved modest improvements in classification accuracy but have limited real-world applicability due to the complexity of model training and deployment and a lack of interpretability. …”
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A data-centric and interpretable EEG framework for depression severity grading using SHAP-based insights by Anruo Shen, Jingnan Sun, Xiaogang Chen, Xiaorong Gao

“…However, most EEG-based machine learning diagnostic studies focus on boosting classification accuracy through complex algorithms and small, homogenous datasets. …”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. The proposed explainable artificial intelligence feature selection method was compared to conventional feature selection techniques, including mutual information, chi-square coefficient, maximal information coefficient, Fisher separation criterion and variance thresholding. …”
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Genotypic and Phenotypic Association of Agronomic Features in Triticale Genotypes under Drought Stress Conditions by Hassan Basiri, Omid Alizadeh, Forud Bazrafshan, Mehdi Zare, Mohammad Yazdani

“…However, creating diversity, selecting genotypes, and studying different traits will help scientists in this direction. …”
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SNPs and other features as they predispose to complex disease: genome-wide predictive analysis of a quantitative phenotype for hypertension. by Joong-Ho Won, Georg Ehret, Aravinda Chakravarti, Richard A Olshen

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Selection of Frequency Estimation of 6-10 kV-Overhead Lines’ Technical Condition Based on Reliability Statistical Studies by Basmanov V.G., Kholmanskikh V.M.

“…The most essential result is the experimental and theoretical confirmation that the complex indicator of reliability, i.e., the technical preparedness coefficient with account of self-eliminating failures, can be used as the frequency criterion for verification of the OL technical condition. …”
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Optimizing demulsifier selection for crude oil dehydration: a fuzzy TOPSIS-based multi-criteria decision-making approach by Jianyong Yu, Merwa Alhadrawi, Farag M. A. Altalbawy, Ahmed Rasol Hasson, M. Mehdi Shafieezadeh

“…Abstract The effective separation of water from crude oil is essential for maintaining oil quality, optimizing production efficiency, and minimizing operational challenges in the petroleum industry. However, selecting an optimal demulsifier remains a complex problem due to the need to balance separation efficiency, environmental impact, cost-effectiveness, and ease of application. …”
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Selection of Trajectories to Improve Thermal Fields During the Electric Arc Welding Process Using Hybrid Model CFD-FNN by Sixtos A. Arreola-Villa, Alma Rosa Méndez-Gordillo, Alejandro Pérez-Alvarado, Rumualdo Servín-Castañeda, Ismael Calderón-Ramos, Héctor Javier Vergara-Hernández

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COMPLEX ASSESSMENT OF RISK FACTORS FOR PRECISE CHOICE OF REVASCULARIZATION STRATEGY IN ST ELEVATION MYOCARDIAL INFARCTION AND MULTIVESSEL CORONARY DISEASE by R. S. Tarasov, V. I. Ganyukov, E. S. Kagan, O. L. Barbarash, L. S. Barbarash

“…Invention of the model of differentiated strategy selection of revascularization in acute myocardial infarction with ST elevation (STEMI) and multivessel disease (MVD).Material and methods. …”
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Constrained search space selection based optimization approach for enhanced reduced order approximation of interconnected power system models by Bala Bhaskar Duddeti, Asim Kumar Naskar, V. P. Meena, Jitendra Bahadur, Ibrahim A. Hameed

“…Abstract Metaheuristic search-based optimization strategies have recently emerged to obtain approximated models for interconnected complex power systems. However, these algorithms are frequently criticized for randomly selecting lower and upper search space boundaries and taking longer to simulate. …”
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Artificial intelligence for herbicide recommendation: Case study for the use of clomazone in Brazilian soils by Hamurábi Anizio Lins, Matheus de Freitas Souza, Lucrecia Pacheco Batista, Luma Lorena Loureiro da Silva Rodrigues, Francisca Daniele da Silva, Bruno Caio Chaves Fernandes, Stefeson Bezerra de Melo, Paulo Sergio Fernandes das Chagas, Daniel Valadão Silva

“…Multilayer perceptron (MLP) ANN models were used to predict clomazone sorption. The variables were selected using the feature selection tool using the physical and chemical properties of the soils. …”
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