Strategies for the next cycles of intrapopulation improvement of sour passion fruit by Leandro R. Fachi, Willian Krause, Kecy S. de Lima, Eileen A. Santos, Fernando H. de L. e Silva

“…The present study aimed to quantify the genetic diversity among progenies of a sour passion fruit population based on morphoagronomic variables of flowers and fruits using the Ward-MLM (modified location model) procedure, which was efficient in quantifying genetic diversity and allowed the identification and consistent formation of three groups within the population. …”
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Enhanced Offline Writer Recognition System Employing Blended Multi-Input CNN and Bi-LSTM Model on Diverse Handwritten Texts by Naresh Purohit, Subhash Panwar

“…By integrating CNN and Bi-LSTMs, the proposed model combines spatial and temporal information, offering a comprehensive representation of handwriting. …”
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A Novel Parameter Estimation Method for Pneumatic Soft Hand Control Applying Logarithmic Decrement for Pseudo‐Rigid Body Modeling by Haiyun Zhang, Kelvin HoLam Heung, Gabrielle J. Naquila, Ashwin Hingwe, Ashish D. Deshpande

“…However, most modeling techniques face computational efficiency and complexity of parameter identification issues. …”
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ResGRU: A Novel Hybrid Deep Learning Model for Compound Fault Diagnosis in Photovoltaic Arrays Considering Dust Impact by Xi Liu, Hui Hwang Goh, Haonan Xie, Tingting He, Weng Kean Yew, Dongdong Zhang, Wei Dai, Tonni Agustiono Kurniawan

“…With the widespread deployment of photovoltaic (PV) power stations, timely identification and rectification of module defects are crucial for extending service life and preserving efficiency. …”
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Performance Comparison of Multi-Objective Optimizers for Dynamic Balancing of Six-Bar Watt Linkages Using a Fully Cartesian Model by María T. Orvañanos-Guerrero, Claudia N. Sánchez, Luis Eduardo Robles-Jiménez, Sara Carolina Gómez-Delgado

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Computational histology reveals that concomitant application of insect repellent with sunscreen impairs UV protection in an ex vivo human skin model by Sophie Charrasse, Titouan Poquillon, Charlotte Saint-Omer, Audrey Schunemann, Mylène Weill, Victor Racine, Abdel Aouacheria

“…Our data show that application of the commercial sun cream provided efficient protection against UV effects in our ex vivo skin model, whereas application of the mosquito repellent as a single product exerted no protective or toxic effect. …”
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Deep hybrid architecture with stacked ensemble learning for binary classification of retinal disease by Priyadharsini C, Asnath Victy Phamila Y

“…Purpose: Early retinal disease identification is vital since symptoms are passive at initial stages but lead to irreversible vision loss at advanced stages. …”
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DGCA3QM: DESIGN OF A DUAL GENETIC ALGORITHM BASED AUTOREGRESSION MODEL FOR CORRELATIVE PREDICTION OF AIR QUALITY METRICS by Harna M. Bodele, G. M. Asutkar, Kiran G. Asutkar

“…But these models are either highly complex, or showcase low efficiency levels, which limits their applicability when used for big data scenarios. …”
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Novel Continuous-Time Markov Chain-Based Model for Performance Analysis of Hybrid Free Space Optics and Radio Frequency Communications by Vladimir Shakhov, Nikolai Shakhov, Insoo Koo

“…The results facilitate the identification of an optimal trade-off between the cost of switching configurations and communication efficiency. …”
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Artificial intelligence in primary aldosteronism: current achievements and future challenges by Yisi Xu, Benjin Liu, Xuqi Huang, Xudong Guo, Ning Suo, Shaobo Jiang, Hanbo Wang

“…For screening, machine learning models integrate multidimensional data to improve the efficiency of PA detection, facilitating large-scale population screening. …”
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Integrating HEC-RAS, GIS, and LISREL for assessing and enhancing urban building resilience against flood threats: Comprehensive model and analysis by Faraz Estelaji, Rahim Zahedi, Arash Gitifar, Alireza Naseri, Mohammad Hossein Yari, Bita Rouhi Asl, Bita Abedi

“…This study employs a comprehensive approach to achieve a resilience model for critical buildings facing floods. The research process involves the identification of city assets based on leveling criteria, utilizing GIS technology for spatial mapping. …”
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About simulation environment for modeling the Internet of Things components and applications using visual flow-based programming tools and cloud services by A. A. Andrushevich, I. S. Vojteshenko, O. Ju. Emelianova

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Larger models yield better results? Streamlined severity classification of ADHD-related concerns using BERT-based knowledge distillation. by Ahmed Akib Jawad Karim, Kazi Hafiz Md Asad, Md Golam Rabiul Alam

“…This work focuses on the efficiency of the knowledge distillation approach in generating a lightweight yet powerful BERT-based model for natural language processing (NLP) applications. …”
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Research on the Applicability of Hybrid RANS/LES Models to Predict the Flow Behavior in Bulb Tubular Pump Under Rated and Stall Conditions by Longyue Sun, Qiang Pan, Linlin Geng, Desheng Zhang, Xavier Escaler

“…The vortex identification method Omega is used to visualize the vortex structure characteristics of the time‐averaged flow field, uncovering large‐scale stall vortex structures under small flow conditions, with the blending RANS/LES turbulence model offering superior resolution of vortex structures. …”
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USE OF A NUMERICAL ANALYTICAL MODEL FOR ASSESSING THE FUNCTIONAL EFFECTIVENESS OF AN INFORMATION PROTECTION SYSTEM BY ANALYSING ITS PROBABILISTIC-TEMPORAL CHARACTERISTICS by V. P. Alferov, A. V. Butskikh, A. V. Krisilov, A. D. Popov, E. A. Rogozin

“…The developed model, which can be used to study the dynamics of transitions between states of an information protection system against unauthorised access in an automated system, as well as to optimise the time it takes to complete functional tasks, can also be used to improve the operational efficiency of these systems.…”
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Establishing a differential diagnosis model between primary membranous nephropathy and non-primary membranous nephropathy by machine learning algorithms by Shangmei Cao, Shaozhe Yang, Bolin Chen, Xixia Chen, Xiuhong Fu, Shuifu Tang

“…Using the decision tree, random forest, support vector machine, and extreme gradient boosting (Xgboost) to establish a differential diagnosis model for PMN and non-PMN. Based on the true positive rate, true negative rate, false-positive rate, false-negative rate, accuracy, feature work area under the curve (AUC) of subjects, the best performance of the model was chosen.Results The efficiency of the Xgboost model based on the above evaluation indicators was the highest, which the diagnosis of PMN of the sensitivity and specificity, respectively 92% and 96%.Conclusions The differential diagnosis model for PMN was established successfully and the efficiency performance of the Xgboost model was the best. …”
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Assessment of the effectiveness and prospects for the development of the activities of the Ukrainian Chamber of Commerce in conditions of environmental uncertainty by O. M. Vinichenko, N. Yu. Naumenko, L. D. Harmider

“…A multiple linear regression model of the dependence of the financial result of the chamber on its income and expenses was developed. …”
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Early Fault Detection in Electro-Pneumatic Actuators using Mathematical Modelling and Machine Learning: A Bottling Company Case Study by Samuel Olufemi Amudipe, Adeyinka Moses Adeoye, Aderonke Oluwaseunfunmi Akinwumi, Rotimi Adedayo Ibikunle, Segun Adebayo

“…The application of feature selection methods helped find essential variables to boost performance metrics in models. The research created valuable insights by reaching 90% success in operational state identification between normal and anomalous conditions across various test scenarios, which leads to an adaptable predictive maintenance system. …”
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A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

“…This increases the prediction accuracy by 10% and boosts the F1 score for low-yield area identification by 5%. Additionally, we introduce other improved model architectures: a custom UNet with attention mechanisms, Heterogeneous Graph Neural Networks (HGNNs), and Variational Auto-encoders. …”
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Multiple deep learning models based on MRI images in discriminating glioblastoma from solitary brain metastases: a multicentre study by Chao Kong, Ding Yan, Kai Liu, Yong Yin, Changsheng Ma

“…Abstract Objective Development of a deep learning model for accurate preoperative identification of glioblastoma and solitary brain metastases by combining multi-centre and multi-sequence magnetic resonance images and comparison of the performance of different deep learning models. …”
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