A New Hybrid PSO-HHO Wrapper Based Optimization for Feature Selection by Sumbul Azeem, Shazia Javed, Iftikhar Naseer, Oualid Ali, Taher M. Ghazal

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Federated and ensemble learning framework with optimized feature selection for heart disease detection by Olfa Hrizi, Karim Gasmi, Abdulrahman Alyami, Adel Alkhalil, Ibrahim Alrashdi, Ali Alqazzaz, Lassaad Ben Ammar, Manel Mrabet, Alameen E.M. Abdalrahman, Samia Yahyaoui

“…To improve classification performance while protecting data privacy, this study investigated a combined method that uses ensemble learning, feature selection, and federated learning (FL). The ensemble-based approaches proved the most predictive after testing several different machine learning (ML) models, including random forests, the light gradient boosting machine, support vector machines, k-nearest neighbors, convolutional neural networks, and long short-term memory. …”
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FEATURES OF LIFE PERSPECTIVE OF FORCED DISPLACED PERSONS DURING ARMED CONFLICT IN UKRAINE by Harkusha Inesa, Dubinskyi Serhii

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Generative Adversarial Networks for Climate-Sensitive Urban Morphology: An Integration of Pix2Pix and the Cycle Generative Adversarial Network by Mo Wang, Ziheng Xiong, Jiayu Zhao, Shiqi Zhou, Yuankai Wang, Rana Muhammad Adnan Ikram, Lie Wang, Soon Keat Tan

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WAYS OF IMPROVING SERVICE QUALITY IN NETWORK RETAIL by Valentyna A. Pavlova, Olena Yu. Meshal

“…The point system and evaluation method were defined. Based on the Harrington scale, a modified mystery shopper evaluation matrix was developed. …”
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Research of migration processes in electronic social networks by A. A. Grebenyuk, A. A. Subbotin

“…The study also gives important methodological features, the success of the results of any research conducted through the analysis of electronic social networks depends on the consideration of which. …”
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Aerial Images Segmentation with Graph Neural Network by A. V. Emelyanov, A. V. Emelyanov, V. A. Knyaz, V. A. Knyaz, V. V. Kniaz, V. V. Kniaz, S. Yu. Zheltov

“…The developed framework at first phase utilizes visual transformer for retrieving deep features from the input aerial image. The graph neural network then performs clustering of the extracted deep features to obtain semantic segmentation of the image. …”
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Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction by Ali M. Hasan, Asaad F. Qasim, Hamid A. Jalab, Rabha W. Ibrahim

“…The obtained features are classified using a long short-term memory (LSTM) neural network classifier. …”
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A feasibility study of ballet education using measurement and analysis on partial features of still scenes by So-Hyun Park, Gwang-Soo Hong, Sun-Woo Park, Aziz Nasridinov, In-Ja Park, Byung-Kyu Kim, Young-Ho Park

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Social Network Supported Process Recommender System by Yanming Ye, Jianwei Yin, Yueshen Xu

“…This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. …”
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Deep Multi-Component Neural Network Architecture by Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi

“…Existing neural network architectures often struggle with two critical limitations: (1) information loss during dataset length standardization, where variable-length samples are forced into fixed dimensions, and (2) inefficient feature selection in single-modal systems, which treats all features equally regardless of relevance. …”
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Revisiting Information Cascades in Online Social Networks by Michael Sidorov, Ofer Hadar, Dan Vilenchik

“…In this study we aim to address this gap by proposing a method to predict the activity of individual users in an OSN, relying solely on their interactions rather than prior knowledge of their social network. We evaluated our results on four large datasets, each comprising over 14 million tweets, recorded on <b>X</b> social network across four different topics over several month. …”
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Structural reinforcement-based graph convolutional networks by Jisheng Qin, Qianqian Wang, Tao Tao

“…Graph Convolutional Network (GCN) is a tool for feature extraction, learning, and inference on graph data, widely applied in numerous scenarios. …”
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Enhanced Skin Lesion Classification Using Deep Learning, Integrating with Sequential Data Analysis: A Multiclass Approach by Azmath Mubeen, Uma N. Dulhare

“…This study introduces a novel method for classifying skin lesions, including nodules, by combining a unified attention (UA) network with deep convolutional neural networks (DCNNs) for feature extraction. …”
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Vehicle re-identification with multiple discriminative features based on non-local-attention block by Lu Bai, Leilei Rong

“…The key to solve this difficulty is to make full use of the multiple discriminative features of vehicles. Therefore, this paper proposes a multiple discriminative features extraction network (MDFE-Net) that can enhance the distance dependence on the vehicle’s multiple discriminative features by non-local attention, which in turn enhances the discriminative power of the network. …”
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Deep multimodal representations and classification of first-episode psychosis via live face processing by Rahul Singh, Rahul Singh, Rahul Singh, Yanlei Zhang, Dhananjay Bhaskar, Dhananjay Bhaskar, Vinod Srihari, Cenk Tek, Xian Zhang, Xian Zhang, J. Adam Noah, J. Adam Noah, Smita Krishnaswamy, Smita Krishnaswamy, Smita Krishnaswamy, Joy Hirsch, Joy Hirsch, Joy Hirsch, Joy Hirsch, Joy Hirsch, Joy Hirsch

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A hybrid deep learning-based approach for optimal genotype by environment selection by Zahra Khalilzadeh, Motahareh Kashanian, Saeed Khaki, Lizhi Wang

“…Using a new yield dataset containing 93,028 records of soybean hybrids across 159 locations, 28 states, and 13 years, with 5,838 distinct genotypes and daily weather data over a 214-day growing season, we developed two convolutional neural network (CNN) models: one that integrates CNN and fully-connected neural networks (CNN model), and another that incorporates a long short-term memory (LSTM) layer after the CNN component (CNN-LSTM model). …”
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Prediction of Remaining Useful Life of Operating Mechanism Driven by Deep Feature in Classification Model by Xilei Dong, Fuping Zhang, Yunyang Ye, Huan Zhang

“…Accurate evaluation of the remaining service life of the operating mechanism plays an important role in ensuring the reliable operation of power transmission and distribution network. …”
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Cloud-Based Intrusion Detection Approach Using Machine Learning Techniques by Hanaa Attou, Azidine Guezzaz, Said Benkirane, Mourade Azrour, Yousef Farhaoui

“…Cloud computing (CC) is a novel technology that has made it easier to access network and computer resources on demand such as storage and data management services. …”
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Explainable AI Meets Synthetic Data: A Deep Learning Framework for Detecting Network Intrusion in NextG Network Infrastructure by Md Junayed Hossain, Khorshed Alam, Md Fahad Monir, Md Mozammal Hoque, Tarem Ahmed

“…The CNN and LSTM models, applied independently, leverage their respective strengths to extract spatial and temporal features from network traffic, achieving robust classification accuracy. …”
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