Multi-level clustering and Prediction based energy efficient routing protocol to eliminate Hotspot problem in Wireless Sensor Networks. by Bhaskar Prince, Prabhat Kumar, Sunil Kumar Singh

“…Moreover, data collection by two data mules based on odd–even round number ensures balanced data traffic and energy distribution across the network. …”
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Prediction and sensitivity analysis of pressure pulsation in a LDI combustor based on a fully connected neural network by Qian Yao, Shize Tian, Wei Pan, Wu Jin, Jianzhong Li, Li Yuan

“…For test data, the FCNN achieves an average relative error (MRE) of 2.54 % for dominant frequency and a mean absolute error (MAE) of 0.64 % for pressure amplitude, suggesting high accuracy and generalization ability. …”
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Graph theory-based analysis of functional connectivity changes in brain networks underlying cognitive fatigue: An EEG study. by Yabing Lou, Rui Pi, Ruifeng Sun, Jilin Wu, Wei Wang, Ziman Zhu, Tengteng Dai, Weijun Gong

“…<h4>Objective</h4>This investigation was designed to analyze alterations in functional connectivity across brain networks associated with cognitive fatigue through electroencephalogram (EEG) data analysis. …”
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Temporal-Spatial Evolution Characteristics and Dynamic Mechanisms of Regional Cooperation Network in the Yangtze River Delta by Cao Xianzhong, Fan Zhiqian

“…This lacks a comprehensive measurement index system for regional cooperation levels using multidimensional connection data, and the dynamic factors and mechanisms of regional cooperation networks are unknown. …”
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GA-SVM method for single-phase grounding fault line selection in distribution network based on feature fusion by ZHANG Xiaopeng, BAI Jie, SUN Naijun, LI Jie, ZHENG Shuai, WAN Qingzhu

“…Aiming at the low accuracy of line selection method when the data amount of single-phase grounding fault in distribution network is small, a genetic algorithm optimized support vector machine (GA-SVM) method for single-phase grounding fault line selection in distribution network based on feature fusion is proposed, which adopts Fourier transform, the active power method and wavelet packet transform decompose the transient zero-sequence current of each line under different fault conditions, extracts four features, including fundamental wave amplitude, fifth harmonic amplitude, average active power component and wavelet energy value. …”
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Intelligent Detection of Oceanic Front in Offshore China Using EEFD-Net with Remote Sensing Data by Ruijie Kong, Ze Liu, Yifei Wu, Yong Fang, Yuan Kong

“…Approximately 4800 days of daily average sea temperature fusion data from CMEMS (Copernicus Marine Environment Monitoring Service) are used for analysis, and an Encoder-Edge-FPN-Decoder Network (EEFD-Net) structure is established to enhance the model’s accuracy in detecting the edges of oceanic fronts. …”
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Aerosols in the Mixed Layer and Mid-Troposphere from Long-Term Data of the Italian Automated Lidar-Ceilometer Network (ALICENET) and Comparison with the ERA5 and CAMS Models by Annachiara Bellini, Henri Diémoz, Gian Paolo Gobbi, Luca Di Liberto, Alessandro Bracci, Francesca Barnaba

“…Through original ALICENET algorithms, we also derive long-term aerosol vertical layering data, including the mixed aerosol layer (MAL) and elevated aerosol layers (EALs) heights. …”
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GNODEVAE: a graph-based ODE-VAE enhances clustering for single-cell data by Zeyu Fu, Chunlin Chen, Song Wang, Junping Wang, Shilei Chen

“…Results We present GNODEVAE, a novel architecture integrating Graph Attention Networks (GAT), Neural Ordinary Differential Equations (NODE), and Variational Autoencoders (VAE) for comprehensive single-cell analysis. …”
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Trends and spatial distribution of Human African Trypanosomiasis (HAT), Uganda, 2005 – 2015: A descriptive analysis of surveillance data by Susan Kizito, Charles W. Wamboga, Edridah Muheki Tukahebwa, Abbass Kakembo, Lilian Bulage, Alex Riolexus Ario

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Simple model based on artificial neural network for early prediction and simulation winter rapeseed yield by Gniewko Niedbała

“…The performed sensitivity analysis of the network examined the factors that have the greatest impact on the yield of winter rape. …”
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Comparative analysis of daily global solar radiation prediction using deep learning models inputted with stochastic variables by Amit Kumar Yadav, Raj Kumar, Meizi Wang, Gusztáv Fekete, Tej Singh

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Artificial neural network applying for justification of tractors undercarriages parameters by V. A. Kuz’Min, R. S. Fedotkin, V. A. Kryuchkov

“…It is possible by operating initial design-data base and using the designed artificial neural network to define missing parameters.…”
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Enhancing Mild Cognitive Impairment Auxiliary Identification Through Multimodal Cognitive Assessment with Eye Tracking and Convolutional Neural Network Analysis by Na Li, Ziming Wang, Wen Ren, Hong Zheng, Shuai Liu, Yi Zhou, Kang Ju, Zhongting Chen

“…This study developed and tested a supportive cognitive assessment system for MCI auxiliary identification, leveraging eye-tracking features and convolutional neural network (CNN) analysis. <b>Methods</b>: The system employed eye-tracking technology in conjunction with machine learning to build a multimodal auxiliary identification model. …”
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Multimorbidity Patterns in Patients with Pulmonary Arterial Hypertension Identified Through Hospital Discharge Records: A Network-Based Analysis by Shuyuan Zhang, Chengdong Yu, Jingya Zhou, Yi Wang, Ye Jin, Shuyang Zhang

“…This 10-year retrospective analysis was based on clinical data from hospital discharge records for individuals diagnosed with PAH (n = 2584). …”
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Experience in applying large language models to analyse quantitative sociological data by E. G. Ashikhmin, V. V. Levchenko, G. I. Seletkova

“…The article discusses the possibilities and limitations of using large language models (hereinafter referred to as LLM) to analyse quantitative data in sociological research. Also, attention is paid to the actor-network theory, according to which neural networks act as active participants of social interaction. …”
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Automated hypocenter determination of tectonic tremors in the Nankai subduction zone using convolutional neural networks combined with semblance analysis by Amane Sugii, Yoshihiro Hiramatsu, Takahiko Uchide, Kazutoshi Imanishi

“…Here, we developed and evaluated a convolutional neural network (CNN) model to classify tectonic tremors, earthquakes, and noise in seismic waveform data recorded by a seismic array in the Nankai subduction zone. …”
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Spatiotemporal Vegetation Dynamics, Forest Loss, and Recovery: Multidecadal Analysis of the U.S. Triple Crown National Scenic Trail Network by Amber R. Ignatius, Ashley N. Annis, Casey A. Helton, Alec W. Reeb, Dylan F. Ricke

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Solving the Problem of Determining the Mechanical Properties of Road Structure Materials Using Neural Network Technologies by N. E. Babushkina, A. A. Lyapin

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Performance Analysis of Cognitive Radio System Based on Outage Probability of Cognitive Transmission by Haomin Gao, Haifeng Zhao, Xiao Liang, Xiaomin Mu

“…It is an important part to design an optimal spectrum sensing and transmission framework in cognitive radio network.Considering that cognitive data transmission outage had effect on the performance of cognitive radio system,a novel spectrum sensing and transmission model based on the outage probability of cognitive transmission was proposed and the two phases of spectrum sensing and data transmission were jointly optimized.The model was formulated as a nonconvex optimization problem under the constraint of interference to primary user,which maximized the average achievable throughput by the joint optimization of sensing time and data transmission rate and simulated by means of the numerical method.The numerical analysis shows that a better tradeoff can be achieved among the protection of primary user,the throughput of cognitive system and transmission delay when the outage probability is cited and the constraint is satisfied.…”
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A Process Monitoring Framework for Imbalanced Big Data: A Wastewater Treatment Plant Case Study by Morteza Zadkarami, Ali Akbar Safavi, Krist V. Gernaey, Pedram Ramin

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