An efficient enhanced stacked auto encoder assisted optimized deep neural network for forecasting Dry Eye Disease by Steffi Rajan, Suresh Ponnan

“…The approach described here is novel because it merges chaotic maps into FS, employs SLSTM-STSA for improved classification accuracy (CA), and optimizes with the adaptive quantum rotation of the Enhanced Quantum Bacterial Foraging Optimisation Algorithm (EQBFOA). The present study enhances prediction functions by extracting MGD-related features and complicated relationships from the DED dataset. …”
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Spatial and temporal distribution patterns and factors influencing hepatitis B in China: a geo-epidemiological study by Kang Fang, Na Cheng, Chuang Nie, Wentao Song, Yunkang Zhao, Jie Pan, Qi Yin, Jiwei Zheng, Qinglin Chen, Tianxin Xiang

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A transcriptomic landscape analysis of human necrotizing enterocolitis: Important roles of immune infiltration by Zhuojun Xie, Quan Kang, Yulu Shi, Junbao Du, Hao Jiang

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Modern advancements of energy storage systems integrated with hybrid renewable energy sources for water pumping application by Marwa M. Ahmed, Haneen M. Bawayan, Mohamed A. Enany, Mahmoud M. Elymany, Ahmed A. Shaier

“…The manuscript also highlights the integration of artificial intelligence (AI) to optimize energy management, predict irrigation demands, and improve operational efficiency. …”
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Integrated remote sensing, machine learning and geospatial approach for site selection of sewage treatment plants in the metropolitan city by S. Rajalakshmi, S. Subathradevi, Abdulaziz G. Alghamdi, Hadeel Alsolai

“…A Random Forest (RF) algorithm was applied to enhance spatial prediction. …”
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Impact of foam-mat drying conditions of “Gấc” aril on drying rate and bioactive compounds: Optimization by novel statistical approaches by Nguyen Minh Thuy, Vo Quoc Tien, Tran Ngoc Giau, Hong Van Hao, Vo Quang Minh, Ngo Van Tai

“…ANN model of 3–10–3 showed more accuracy and faster prediction capacity than RSM model did. ANN-GA model predicted the optimal conditions to be 13.31 % EA, 0.26 % xanthan gum and drying temperature of 73.1 °C, with the drying rate of 1.89 g-water/g-dry matter/min, β-carotene content of 395.88 μg/g, TPC of 1.68 mgGAE/g. …”
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Implementation of new technique for Face recognition based on quantum computing by Amjed Yousif Sahib

“…This technique is transforming the oracle of Grover's search algorithm into correlation oracle with feeding image. …”
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Association of the Tracked Trajectories and Marks by the Attraction Method During Secondary Processing of Radar Information by U. A. Aparovich

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Abilities of Using MS-Unit Computer Vision Hardware and Software Complex Studying Forensic Objects by I. V. Latyshov, V. A. Vasil’iev, I. G. Pal’chikova, E. S. Smirnov

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Efficient Conical Area Differential Evolution with Biased Decomposition and Dual Populations for Constrained Optimization by Weiqin Ying, Bin Wu, Yu Wu, Yali Deng, Hainan Huang, Zhenyu Wang

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Simulation of Magnetotargeting of Medicines Based on the Calculation of Permeability of Human Tissues by the Electromagnetic Field by A. V. Churakov, P. V. Kamlach, A. I. Ongarbayeva

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Potential accuracy of quasi-optimal radar meters of angular coordinates with scanning multi-channel antenna system by S. V. Kozlov, Vu Thanh Ha

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Regulation of the functional state of locomotive crew drivers using biofeedback training: factor analysis of experimental data by N. V. Shcherbina

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Smart Real-time Attendance System for Nigerian Universities by Mikailu Habila, Faseki N. Francisca, Luwani Ishaya, Muhammed Kabir Ahmed, Umar A. Muhammad, Haruna P. Charles

“…The system employs Convolutional Neural Networks (CNNs) and the ArcFace algorithm for facial feature extraction and identity verification. …”
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Persistence and Burn-in in Solar Coronal Magnetic Field Simulations by Eric J. Hall, Karen A. Meyer, Anthony R. Yeates

“…Simulations of solar phenomena play a vital role in space-weather prediction. A critical computational question for automating research workflows in the context of data-driven solar coronal magnetic field simulations is quantifying a simulation's burn-in time, after which a solar quantity has evolved away from an arbitrary initial condition to a physically more realistic state. …”
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A multicenter pragmatic implementation study of AI-ECG-based clinical decision support software to identify low LVEF: Clinical trial design and methods by Francisco Lopez-Jimenez, Heather M. Alger, Zachi I. Attia, Barbara Barry, Ranee Chatterjee, Rowena Dolor, Paul A. Friedman, Stephen J. Greene, Jason Greenwood, Vinay Gundurao, Sarah Hackett, Prerak Jain, Anja Kinaszczuk, Ketan Mehta, Jason O'Grady, Ambarish Pandey, Christopher Pullins, Arjun R. Puranik, Mohan Krishna Ranganathan, David Rushlow, Mark Stampehl, Vinayak Subramanian, Kitzner Vassor, Xuan Zhu, Samir Awasthi

“…Background: Artificial intelligence (AI) enabled algorithms can detect or predict cardiovascular conditions using electrocardiogram (ECG) data. …”
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Integrated export instream coefficient model for accurate nonpoint source pollution estimation and management in the Yellow River Basin by Xueting Wang, Lei Wu, Yongkun Luo, Yimu Liu, Ruowen Wang

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RISK FACTORS OF ARRHYTHMIAS IN PATIENTS WITH ACUTE DECOMPENSATION OF CHRONIC HEART FAILURE by N. V. Larionova, A. M. Shutov, M. V. Menzorov, E. V. Efremova, V. V. Kasalinskaya

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Super-resolution femtosecond electron diffraction reveals electronic and nuclear dynamics at conical intersections by Hui Jiang, Juanjuan Zhang, Tianyu Wang, Jiawei Peng, Cheng Jin, Xiao Zou, Pengfei Zhu, Tao Jiang, Zhenggang Lan, Haiwang Yong, Feng He, Dao Xiang

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Method of unknown protocol classification based on autoencoder by Chunxiang GU, Weisen WU, Ya’nan SHI, Guangsong LI

“…Aiming at the problem that a large number of unknown protocols exist in the Internet,which makes it very difficult to manage and maintain the network security,a classification and identification method of unknown protocols was proposed.Combined with the autoencoder technology and the improved K-means clustering technology,the unknown protocol was classified and identified for the network traffic.The autoencoder was used to reduce dimensionality and select features of network traffic,clustering technology was used to classify the dimensionality reduction data unsupervised,and finally unsupervised recognition and classification of network traffic were realized.Experimental results show that the classification effect is better than the traditional K-means,DBSCAN,GMM algorithm,and has higher efficiency.…”
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