CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer’s disease by Jingyuan Liu, Xiaojie Yu, Hidenao Fukuyama, Toshiya Murai, Jinglong Wu, Qi Li, Zhilin Zhang

“…Addressing this obstacle is crucial for improving diagnostic accuracy and optimizing treatment strategies for those affected by AD. …”
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A Deep Learning Method for Photovoltaic Power Generation Forecasting Based on a Time-Series Dense Encoder by Xingfa Zi, Feiyi Liu, Mingyang Liu, Yang Wang

“…Deep learning has become a widely used approach in photovoltaic (PV) power generation forecasting due to its strong self-learning and parameter optimization capabilities. In this study, we apply a deep learning algorithm, known as the time-series dense encoder (TiDE), which is an MLP-based encoder–decoder model, to forecast PV power generation. …”
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Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. Regarding the Vis/NIR spectrophotometer dataset, good predictive performances were achieved for TSS (R² = 0.855) and DM (R² = 0.857), while the performance for TA was unsatisfactory (R² = 0.681). …”
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Simple Yet Powerful: Machine Learning-Based IoT Intrusion System With Smart Preprocessing and Feature Generation Rivals Deep Learning by Kazim Kivanc Eren, Kerem Kucuk, Fatih Ozyurt, Omar H. Alhazmi

“…In contrast, classical machine learning techniques offer a more efficient alternative but are often overlooked due to a lack of focus on data pre-processing, which is critical for achieving optimal performance. Here we propose a classical machine learning system, built around a Random Forest classifier paired with a novel feature extraction algorithm adapted from Explainable Boosted Linear Regression (EBLR). …”
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The Long-Term Surface Deformation Monitoring and Prediction of Hutubi Gas Storage Reservoir in Xinjiang Based on InSAR and the GWO-VMD-GRU Model by Wang Huang, Wei Liao, Jie Li, Xuejun Qiao, Sulitan Yusan, Abudutayier Yasen, Xinlu Li, Shijie Zhang

“…The data is processed through wavelet transformation for denoising, followed by the application of a Gray Wolf Optimization (GWO) algorithm combined with Variational Mode Decomposition (VMD) to decompose both surface deformation and gas pressure data. …”
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A METHODOLOGICAL APPROACH TO DESIGNING EXPERIMENTS WHEN DEALING WITH IDENTIFICATION TESTS FOR MEDICINAL PRODUCT COMPONENTS (AS ILLUSTRATED BY ASCORBIC ACID) by Yu. B. Purim, M. L. Kruglyakova, L. N. Bulanova, M. V. Agapkina, L. N. Stronova, T. N. Bokovikova, E. P. Gernikova

“…The whole complex of the studies performed helped to determine qualitative reactions and optimal conditions for identification testing of the analysed substance.…”
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Formation of Whipped Yeast-Free Bread Crumb with Intensive Microwave Convective Baking by Gazibeg O. Magomedov, Anatoly А. Khvostov, Aleksey А. Zhuravlev, Magomed G. Magomedov, Aleksei S. Taratukhin, Inessa V. Plotnikova

“…The presented approach, together with the method of optical evaluation of air bubbles, allows us to develop an algorithm for optimal control of the process of combined baking bread. …”
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Anorexia-cachexia syndrome in cancer patients: pathogenetic aspects and treatment options by A. V. Snegovoy, V. B. Larionova, I. V. Kononenko

“…First, it will allow optimizing monitoring of cancer patients predisposed to CACS development during anticancer treatment. …”
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The Hybrid Market Segmentation of Electric Vehicles in Ukraine Using Data Science Methods by Andrusyk Yevhenii V., Guryanova Lidiya S.

“…This market, on one hand, demonstrates exponential growth, while on the other, it develops in the context of significant economic and social challenges, which shapes a unique consumer behavior. …”
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Screening OSA in Chinese Smart Device Consumers: A Real-World Arrhythmia-Related Study by Chen Y, Zhang H, Li J, Xu P, Guo Y, Xie L

“…Age emerged as an independent predictor of arrhythmia risk, while hypertensive OSA patients were older, more obese, and experienced prolonged nocturnal hypoxia (Time length of SpO2< 90%, P=0.020). …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Furthermore, the Ordered Weighted Averaging (OWA) algorithm and the Partical Swarm Optimization-Support Vector Machine (PSO-SVM) model were combined to simulate future GDV scenarios for 2030–2050 under three development preferences: environment oriented, status quo, and economically oriented. …”
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Identifying low-risk breast cancer patients for axillary biopsy exemption: a multimodal preoperative predictive model by Jiaqi Zhang, Jianing Zhang, Zhihao Liu, Yudong Zhou, Xiaoni Zhao, Yalong Wang, Danni Li, Jinsui Du, Chenglong Duan, Yi Pan, Qi Tian, Feiqian Wang, Ke Wang, Lizhe Zhu, Bin Wang

“…Abstract Background As the most prevalent female malignancy worldwide, breast cancer frequently involves axillary lymph node metastasis (ALNM), which critically affects therapeutic algorithms. Current guidelines mandate preoperative ultrasound-guided axillary biopsy for suspicious lymph nodes, potentially exposing some low-risk patients with negative results to invasive risks. …”
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Computer-Aided Diagnosis and Staging of Pancreatic Cancer Based on CT Images by Min Li, Xiaohan Nie, Yilidan Reheman, Pan Huang, Shuailei Zhang, Yushuai Yuan, Chen Chen, Ziwei Yan, Cheng Chen, Xiaoyi Lv, Wei Han

“…The least absolute shrinkage and selection operator (LASSO) algorithm was chosen for feature selection. In contrast to no feature selection, the model optimization time decreased by 19.94 seconds while maintaining precision. …”
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Using proximal sensor data for soil salinity management and mapping by Yan GUO, Yin ZHOU, Lian-qing ZHOU, Ting LIU, Lai-gang WANG, Yong-zheng CHENG, Jia HE, Guo-qing ZHENG

“…We concluded that two management zones are optimal to guide precision management. Zone A had an average salinity level of about 165 mS m−1, in which salt-tolerant crops, such as cotton and barley can grow normally, while crops such as soybean and cowpeas may be planted using leaching and increasing the mulching film methods to reduce the accumulation of salt in surface soil. …”
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A Fusion XGBoost Approach for Large-Scale Monitoring of Soil Heavy Metal in Farmland Using Hyperspectral Imagery by Xuqing Li, Huitao Gu, Ruiyin Tang, Bin Zou, Xiangnan Liu, Huiping Ou, Xuying Chen, Yubin Song, Wei Luo, Bin Wen

“…The traditional laboratory-based methods for monitoring soil heavy metals are limited for large-scale applications, while hyperspectral imagery data-based methods still face accuracy challenges. …”
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Adaptive User Pairing With Non-Orthogonal Medium Access Choices for Balanced Coexistence of Mission-Critical and eMBB Services in Cellular IoT by Farnaz Khodakhah, Aamir Mahmood, Patrik Osterberg, Mikael Gidlund

“…By using this derived threshold, we design an adaptive pairing algorithm that achieves near-optimal QoS for MC users and maximizes eMBB data rates. …”
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Modified Diagnostic Criteria Tools for Familial Hypercholesterolemia without the Requirement for Clinical Genetic Testing: Rationale and Design of the MOOCS Adaptive Clinical Trial by Satyanarayana Upadhyayula

“…Various available FH diagnostic tools are grouped together in the FH diagnostic criteria tool universal algorithm. Background: The standard diagnostic criteria tools for FH require GT. …”
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The Influence of Viewing Geometry on Hyperspectral-Based Soil Property Retrieval by Yucheng Gao, Lixia Ma, Zhongqi Zhang, Xianzhang Pan, Ziran Yuan, Changkun Wang, Dongsheng Yu

“…The viewing geometry had limited effects on the choice of preprocessing method and retrieval algorithm. Among the preprocessing methods, D1, SG + D1, and SG + D2 outperformed the others, while PLSR achieved a higher accuracy than SVM and CNN when retrieving soil properties. …”
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DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…Deep learning approaches like graph autoencoders are utilized to perform anomaly detection through obtaining node embeddings while dealing with the network nonlinearity and sparsity issues. …”
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Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images:... by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue, Zeyu Zhang

“…By designing a texture-aware data prior algorithm, a high-quality training dataset with geological rationality is generated. …”
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