LCC-Net: Swin transformer-CNN hybrid for enhanced land cover classification in natural disaster monitoring by P. Shailaja, Pala Mahesh Kumar, Nalla Nikhitha, Kunta Neeraj Kumar Reddy, Enthala Mukesh Reddy, Goli Ganesh Reddy, Vadde Indu

“…The core of LCC-Net employs the Swin Transformer Convolutional Neural Network (ST-CNN), which leverages self-attention mechanisms to capture intricate spatial features and temporal dynamics. The ST-CNN outperforms traditional CNN models by providing a better contextual understanding of land cover variations associated with different disaster scenarios. …”
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Impact of Background Error Length Scale Tuning in WRF-3DVAR System on High-Resolution Radar Data Assimilation for Typhoon Doksuri Simulation by Weidi Zhai, Feifei Shen, Jing Liu, Haiyan Fei, Liu Yi, Shen Wan, Xiaolin Yuan

“…Using the WRF-ARW model in conjunction with the WRF-3DVAR data assimilation system, two assimilation configurations were tested with horizontal length scale factors of 1.0 and 0.25. …”
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Unleashing the power of AI in predicting the technological and phenolic maturity of pomegranates cultivated in Lebanon by Rim Ghannoum, Nourhan Taha, David D. Gaviria, Hiba N. Rajha, Nada El Darra, Shadi Albarqouni

“…Our results demonstrated that the MLP regressor achieved high predictive accuracy, with an R-squared value of 0.84 for TA, making it a reliable tool for predicting acidity levels. The model also showed strong performance in predicting phenolic content and color intensity, with R-squared values of 0.70 and 0.65 respectively, and an average classification accuracy of 71% for categorizing polyphenol levels. …”
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Enhancing Security in DNP3 Communication for Smart Grids: A Segmented Neural Network Approach by Shahid Allah Bakhsh, Muhammad Shahbaz Khan, Oumaima Saidani, Nada Alasbali, S. Qasim Abbas, Muhammad Almas Khan, Jawad Ahmad

“…A Segmented Neural Network (SNN) architecture is employed to analyze the DNP3 dataset, which is captured using CICFlowMeter3 and a DNP3 Parser, integrating Deep Neural Network (DNN), Long Short Term Memory (LSTM), and Random Neural Network (RandNN) models. In CICFlowMeter3, the model achieved an accuracy of 99.86%, whereas, on the DNP3 Parser, it improved to 99.75%, demonstrating outstanding performance. …”
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Multiband THz MIMO antenna with regression machine learning techniques for isolation prediction in IoT applications by Md Ashraful Haque, Kamal Hossain Nahin, Jamal Hossain Nirob, Md. Kawsar Ahmed, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Abeer D. Algarni, Mohammed ElAffendi, Ahmed A. Abd El-Latif, Abdelhamied A. Ateya

“…Our research assesses antenna performance using various methodologies, including simulation and RLC equivalent circuit models. …”
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Maize crop residue cover mapping using Sentinel-2 MSI data and random forest algorithms by Jia Du, Pierre-Andre Jacinthe, Kaishan Song, Longlong Zhang, Boyu Zhao, Hua Liu, Yan Wang, Weijian Zhang, Zhi Zheng, Weilin Yu, Yiwei Zhang, Dapeng Jiang

“…The method used random forest (RF) algorithms, 13 tillage indices and 9 textural feature indicators derived from Sentinel-2 data. The tillage indices with the best predictive performance were STI and NDTI (R2 of 0.85 and 0.84, respectively). …”
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METTL1-driven nucleotide metabolism reprograms the immune microenvironment in hepatocellular carcinoma: a multi-omics approach for prognostic biomarker discovery by Xie Weng, Yangyue Huang, Zhuoya Fu, Xingli Liu, Fuli Xie, Jiale Wang, Qiaohua Zhu, Dayong Zheng, Dayong Zheng

“…Non-negative matrix factorization (NMF) clustering stratified HCC patients into distinct subgroups with varied clinical features. Weighted Gene Co-expression Network Analysis (WGCNA) identified hub genes that were subsequently used to construct robust prognostic models via multiple machine learning algorithms. …”
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Teaching coherent descriptive speech to children of senior preschool age with speech underdevelopment problems by L. G. Shadrina, O. V. Efimova

“…It was proved that it is necessary to teach preschool children with speech disorders not only to speak by analogy and model structures, but also to formulate detailed meaningful descriptive statements. …”
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An exploration of distinguishing subjective cognitive decline and mild cognitive impairment based on resting-state prefrontal functional connectivity assessed by functional near-in... by Zhengping Pu, Zhengping Pu, Hongna Huang, Man Li, Hongyan Li, Xiaoyan Shen, Qingfeng Wu, Qin Ni, Yong Lin, Donghong Cui

“…FC strength and neuropsychological test scores were extracted as features to build classification and predictive models through machine learning. …”
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Enabling Robust Exoplanet Atmospheric Retrievals with Gaussian Processes by Yoav Rotman, Luis Welbanks, Michael R. Line, Peter McGill, Michael Radica, Matthew C. Nixon

“…However, this opportunity is accompanied by challenges: modeling assumptions and unaccounted-for noise or signal sources can bias retrieval outcomes and their interpretation. …”
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Identifying patterns of high intraoperative blood pressure variability in noncardiac surgery using explainable machine learning: a retrospective cohort study by Zheng Zhang, Jian Wu, Yi Duan, Linwei Liu, Yaru Liu, Jinghan Wang, Li Xiao, Zhifeng Gao

“…The overall population and each age subgroup (pediatric, adult, elderly) underwent independent 70/30 train-test splits for model development. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC). …”
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Multipool-CEST and CEST-based pH assessment as predictive tools for glioma grading, IDH mutation, 1p/19q codeletion, and MGMT promoter methylation in gliomas by Xinli Zhang, Jue Lu, Xiaoming Liu, Peng Sun, Qian Qin, Zhengdong Xiang, Lan Cheng, Xiaoxiao Zhang, Xiaotong Guo, Jing Wang

“…These features were subsequently employed for glioma grading and molecular genotyping of IDH, 1p/19q and MGMT. …”
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Multi-Strategy Enhancement of YOLOv8n Monitoring Method for Personnel and Vehicles in Mine Air Door Scenarios by Lei Zhang, Hongjing Tao, Zhipeng Sun, Weixun Yi

“…The experimental results indicate that the CGSW-YOLO model exhibits strong performance in monitoring man-vehicle interactions in mine air door scenarios. …”
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Detached housing utilized as shared houses: establishment process and living style – case study in Yamaguchi Prefecture by Tomoko Ohba, Mahito Nakazono, Akira Ushijima, Sachiko Mishima

“…The degree of satisfaction of the tenant's shared habitation is high; therefore these wooden private houses are model examples that demonstrate the possible practical use of wooden private houses as shared houses.…”
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Adaptive Assessment of Power System Transient Stability Based on Active Transfer Learning by Chenhao ZHAO, Zaibin JIAO, Chenghao LI, Di ZHANG, Penghui ZHANG

“…The update mechanism is started when the performance of the model decreases due to the change of the running scene. …”
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Advancing Self-Supervised Learning for Building Change Detection and Damage Assessment: Unified Denoising Autoencoder and Contrastive Learning Framework by Songxi Yang, Bo Peng, Tang Sui, Meiliu Wu, Qunying Huang

“…Extensive experiments were conducted on five public datasets, including xBD, LEVIR, LEVIR+, SYSU, and WHU, to evaluate the performance and generalization capabilities of the model. …”
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Application of Vis/NIR Spectroscopy in the Rapid and Non-Destructive Prediction of Soluble Solid Content in Milk Jujubes by Yinhai Yang, Shibang Ma, Feiyang Qi, Feiyue Wang, Hubo Xu

“…The KS method achieved the best preservation of the original data distribution, improving the model generalization. Several spectral preprocessing and feature selection methods were used to enhance the modeling performance. …”
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Optimizing IoT intrusion detection with cosine similarity based dataset balancing and hybrid deep learning by Arvind Prasad, Wael Mohammad Alenazy, Naved Ahmad, Gauhar Ali, Hanaa A. Abdallah, Sadique Ahmad

“…Additionally, we developed a hybrid deep learning model integrating RegNet and FBNet architectures to enhance feature extraction and classification performance. …”
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A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

“…It was shown that artificial neural networks were the most common kind of trained model, while several other models were often used as benchmarks for performance. …”
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Investigation of Asymmetrical Modes of Three-Phase Three Leg Combined Transformer-Phase-Shifter by Bosneaga V.A., Suslov V.M.

“…On the base of previously proposed model of three-phase three leg transformer windings connection scheme for combined transformer-phase shifter was made, for which calculations and analysis of specific characteristics of different steady state asymmetric modes were performed. …”
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