Evaluating Wind Speed Forecasting Models: A Comparative Study of CNN, DAN2, Random Forest and XGBOOST in Diverse South African Weather Conditions by Fhulufhelo Walter Mugware, Caston Sigauke, Thakhani Ravele

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Hybrid modeling approaches for predicting COVID-19 mortality: A comparative study across USA, France, and India by B. Uppalaiah, D. Mallikarjuna Reddy, K. Rajalakshmi, P. Vignesh, V. Govindan, Siriluk Donganont

“…This paper proposes and assesses three Gaussian Process-based hybrid models—GP-RBM (Random Boosting Machine), GP-LSTM (Long Short-Term Memory), and GP-CNN (Convolutional Neural Network)—for forecasting COVID-19 mortality cases in the USA, France, and India. …”
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NeuroMorse: a temporally structured dataset for neuromorphic computing by Ben Walters, Yeshwanth Bethi, Taylor Kergan, Binh Nguyen, Amirali Amirsoleimani, Jason K Eshraghian, Saeed Afshar, Mostafa Rahimi Azghadi

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A rapid recognition method for radar active jamming based on the Hybrid 3_CNN‐Transformer model by Jingjing Wei, Lei Yu, Yinsheng Wei, Rongqing Xu

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Optimizing Remote Sensing Image Retrieval Through a Hybrid Methodology by Sujata Alegavi, Raghvendra Sedamkar

“…Low-level features are extracted using the modified Multiscale Multiangle Completed Local Binary Pattern (MSMA-CLBP) algorithm to capture local contexture features, while high-level features are obtained through a hybrid CNN structure combining pretrained networks (Alexnet, Caffenet, VGG-S, VGG-M, VGG-F, VGG-VDD-16, VGG-VDD-19) and a fully connected dense network. …”
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Combination of artificial intelligence endoscopic diagnosis and Kimura‐Takemoto classification determined by endoscopic experts may effectively evaluate the stratification of gastr... by Kumiko Kirita, Seiji Futagami, Ken Nakamura, Shuhei Agawa, Nobue Ueki, Kazutoshi Higuchi, Mayu Habiro, Rie Kawawa, Yusuke Kato, Tomohiro Tada, Katsuhiko Iwakiri

“…The trained neural network generated a continuous number between 0 and 1 for gastric atrophy. …”
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Geographical feature and method factors significantly influence the reliability of ecological source information transmission at multi-scale by Kai Li, Wei Wu, Shiqi Tian, Linjuan Li, Zhe Li, Yue Cao

“…We employed Morphological Spatial Pattern Analysis (MSPA) and Comprehensive Evaluation (CE) methods to identify ecological sources across different extents and grain sizes, while analyzing the influence of various factors on information transmission. …”
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Geological characteristics and key technologies for exploration and development of the Yanchuannan coalbed methane field, Ordos Basin by Xipeng HE, Cui XIAO, Yuqiao GAO, Xin LI, Tao GUO, Xiao CAI

“…By highlighting the suitability of the well pattern and fracture networks, this study established a well pattern – fracture network – productivity – economic benefit integrated strategy tailored to varying geological conditions. …”
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Network and systems biology approaches help investigate gene regulatory interactions between Salmonella disease and host in chickens: Model‐based in silico evidence combined with g... by Reza Tohidi, Hoda Javaheri Bargourooshi, Arash Javanmard

“…The role of these promising biomarkers in our networks against SE susceptibility is essentially confirmed by these results. …”
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Web-Biometrics for User Authenticity Verification in Zero Trust Access Control by Taisho Sasada, Yuzo Taenaka, Youki Kadobayashi, Doudou Fall

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Three-Dimensional Analysis of Seepage in Fractured Rock Masses and Evaluation of the Accuracy of Empirical Methods for Predicting Permeability in Cutoff Walls: A Case Study of Cham... by Alireza Baghbanan, Masoud Dararbi, Amirhosein Momeni, Ahmad Rahmani Shahraki, Amin Azhari

“…This study focuses on the investigation of the permeability of fractured rock masses and the design of a cutoff wall using numerical modeling techniques. The fracture network was modeled using the discrete element method (DEM) in the 3DEC software, considering the joint patterns specific to the region. …”
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Improving the Performance of Charge Trapping Memtransistor as Synaptic Device by Ti-Doped HfO₂ by Yu-Che Chou, Wan-Hsuan Chung, Chien-Wei Tsai, Chin-Ya Yi, Chao-Hsin Chien

“…We used NeuroSim simulator with multilayer perceptron and convolutional neural network models to evaluate the pattern recognition accuracy of neural network hardware accelerator using CTMTs as synaptic devices and benchmarked the performance of our CTMT with those of other types of synaptic devices.…”
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Probabilistic forecasting of renewable energy and electricity demand using Graph-based Denoising Diffusion Probabilistic Model by Amir Miraki, Pekka Parviainen, Reza Arghandeh

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A neuronal imaging dataset for deep learning in the reconstruction of single-neuron axons by Liya Li, Liya Li, Ying Hu, Ying Hu, Xiaojun Wang, Pei Sun, Tingwei Quan

“…To address these challenges, we propose a distance field-supervised segmentation network designed to enhance image signals effectively. …”
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Knowledge Discovery in Databases of Proteomics by Systems Modeling in Translational Research on Pancreatic Cancer by Mathilde Resell, Elisabeth Pimpisa Graarud, Hanne-Line Rabben, Animesh Sharma, Lars Hagen, Linh Hoang, Nan T. Skogaker, Anne Aarvik, Magnus K. Svensson, Manoj Amrutkar, Caroline S. Verbeke, Surinder K. Batra, Gunnar Qvigstad, Timothy C. Wang, Anil Rustgi, Duan Chen, Chun-Mei Zhao

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A Method for Localization of Cellular Users From Call Detail Records by Steven W. Ellingson

“…The performance of the proposed method is evaluated by “best server” analysis of measurements acquired from drive testing in the vicinity of Winter Garden, Florida, observing three 700 MHz-band LTE cellular networks serving this area. …”
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Pore scale fracturing fluid occurrence mechanisms in multi-scale matrix-fracture system of shale gas reservoir by XIA Haibang, HAN Kening, SONG Wenhui, WANG Wei, YAO Jun

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Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm by Fatemeh Hataminia, Anahita Azinfar

“…The sensitivity to neuron number in the hidden layers for DSLG was more pronounced compared to the PSLG pattern, and the mean square error (MSE) was calculated for this evaluation. …”
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LSTM model to predict missing data of dissolved oxygen in land-based aquaculture farm by Sang-Yeon Lee, Deuk-Young Jeong, Jinseo Choi, Seng-Kyoun Jo, Dae-Heon Park, Jun-Gyu Kim

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Forecasting arctic sea ice extent trend using time series models: NNAR, SARIMA and SARIMAX using the data prior to the COVID-19 pandemic by Benoit Ahanda, Türkay Yolcu, Rachel Watson

“…Abstract This research paper aims to examine the patterns of Arctic sea ice extent (ASIE) between 1979 and 2020 by using monthly data acquired from NSIDC. …”
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