A Video SAR Multi-Target Tracking Algorithm Based on Re-Identification Features and Multi-Stage Data Association by Anxi Yu, Boxu Wei, Wenhao Tong, Zhihua He, Zhen Dong

“…In this study, some key challenges in ViSAR systems are addressed, including the abundance of low-confidence shadow detections, high error rates in multi-target data association, and the frequent fragmentation of tracking trajectories. …”
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A Sensor Data Prediction and Early-Warning Method for Coal Mining Faces Based on the MTGNN-Bayesian-IF-DBSCAN Algorithm by Mingyang Liu, Xiaodong Wang, Wei Qiao, Hongbo Shang, Zhenguo Yan, Zhixin Qin

“…By integrating original concentration data and residual features, gas anomalies are effectively identified by the proposed method, with the detection rate reaching a range of 93–96% and the false alarm rate controlled below 5%. …”
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Spatiotemporal Variation in Carbon and Water Use Efficiency and Their Influencing Variables Based on Remote Sensing Data in the Nanling Mountains Region by Sha Lei, Ping Zhou, Jiaying Lin, Zhaowei Tan, Junxiang Huang, Ping Yan, Hui Chen

“…A comprehensive evaluation of the variations in carbon use efficiency (CUE) and water use efficiency (WUE) in the Nanling Mountains Region (NMR) is crucial for gaining insights into the intricate relationships between climate change and ecosystem processes. This study evaluates the spatiotemporal rates of dynamics in CUE, WUE, gross primary productivity (GPP), net primary productivity (NPP), and evapotranspiration (ET) over the period from 2001 to 2023, using remote sensing data and linear regression analysis. …”
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The effect of engaging unpaid informal providers on case detection and treatment initiation rates for TB and HIV in rural Malawi (Triage Plus): A cluster randomised health system i... by George Bello, Brian Faragher, Lifah Sanudi, Ireen Namakhoma, Hastings Banda, Rasmus Malmborg, Rachael Thomson, S Bertel Squire

“…Data were obtained from patient registers. Poisson regression models with robust standard errors were used to express the effectiveness of the intervention as incidence rate ratios (IRR).…”
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Improved chaotic fruit fly optimization with elman neural network based data-driven approach on product reviews classification by Mohammed Alghamdi, Najla I. Al-shathry, Yahia Said, Hasan Beyari, Shaymaa Sorour, Khalid Nazim Abdul Sattar, Fouad Shoie Alallah, Abdulrhman Alshareef

“…The major goal of the ENLPPR-ICFFO method is to detect and classify the sentiments existing in product ratings. To accomplish this, the presented ENLPPR-ICFFO method employs data pre-processing to be consistent. …”
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Amino acid sequence assignment from single molecule peptide sequencing data using a two-stage classifier. by Matthew Beauregard Smith, Zack Booth Simpson, Edward M Marcotte

“…Whatprot's hybrid kNN-HMM approach enables the efficient interpretation of fluorosequencing data using a full proteome reference database and should now also enable improved sequencing error rate estimates.…”
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Improving Data Entry Quality in Enterprise Applications With NLP Methods: A Model Proposal Based on BERT and Deep Learning by H. Canli

“…Incorrect or incomplete data causes many problems such as prolonged approval processes, decreased trust in data, and negative impact on analysis capabilities. …”
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KRSA: An R package and R Shiny web application for an end-to-end upstream kinase analysis of kinome array data. by Erica A K DePasquale, Khaled Alganem, Eduard Bentea, Nawshaba Nawreen, Jennifer L McGuire, Tushar Tomar, Faris Naji, Riet Hilhorst, Jaroslaw Meller, Robert E McCullumsmith

“…Peptide array technologies like the PamStation12 from PamGene allow for generating high-throughput, multi-dimensional, and complex functional proteomics data. As the adoption rate of such technologies increases, there is an imperative need for software tools that streamline the process of analyzing such data. …”
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Developing a modelling environment of spacecraft solar array in low Earth orbit using real-time telemetry data by Ahmed Mokhtar, Mohamed Ibrahim, Mohamed E. Hanafy, Fawzy H. Amer ElTohamy, Yehia Z. Elhalwagy

“…The results demonstrate the success of the SSA operation in converting sunlight into electrical energy with a high conversion rate.…”
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Estimation for spatial semi-functional partial linear regression model with missing response at random by Benchikh Tawfik, Almanjahie Ibrahim M., Fetitah Omar, Attouch Mohammed Kadi

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Vehicle Text Data Compression and Transmission Method Based on Maximum Entropy Neural Network and Optimized Huffman Encoding Algorithms by Jingfeng Yang, Zhenkun Zhang, Nanfeng Zhang, Ming Li, Yanwei Zheng, Li Wang, Yong Li, Ji Yang, Yifei Xiang, Yu Zhang

“…It can also achieve a higher compression rate and data transmission integrity, and after decompression it can basically guarantee no distortion. …”
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An integrated hydrological model to simulate terrestrial water storage in a large river basin: Evaluation using GRACE data by Sai Srinivas Gorugantula, BVN P Kambhammettu

“…Study region: Krishna River Basin, India Study focus: Integrated hydrological models that simulate surface and subsurface processes, and their interactions in a single framework are essential for effective management of large-scale river basins. …”
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Data driven modeling of TiO2 PVP nanofiber diameter using LSTM and regression for enhanced functional performance by Harshada Mhetre, Sagar Pande, Babita Singla, Pavan Hiremath, Samriddh Sahu, Sarvesh Sorte, Ketan Kotecha, Nithesh Naik

“…The acquired data underwent analysis using LSTM and regression models to assess their predictive capabilities. …”
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Meteorological measurement and simulation datasets to understand the complex circulation over a tropical inter-Andean valleyMendeley Data by Andres V. Ardila, Carlos M. González, Felipe Cifuentes, German Rueda-Saa, Rodrigo Jimenez

“…Following a rigorous validation process, 83% of the 4.7 million original data points were retained, with solar radiation exhibiting the highest rate of invalidity (37.6%). …”
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Reduced order data driven framework for computation of the unsteady lid-driven cavity flow using dynamic mode decomposition by Karim Mazaheri, Mohammad Kazem Moayyedi, Mohammad Hadi Dehghan

“…Validation of CFD computation was assessed, and independence of the DMD modes from the data collection process was investigated. A data set of 400 snapshots of the flow field at three different Reynolds numbers were used to identify the DMD modal structure. …”
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Is Namalycastis abiuma (Grube, 1871) (Annelida: Nereididae) restricted to its type-locality? Evidence from morphological and molecular data by Paulo Ricardo Alves, Christopher J. Glasby, Paulo Cesar Paiva, Cinthya Simone Gomes Santos

“…For species delimitation, we applied the Generalized Mixed Yule Coalescent (GMYC), the Assemble Species by Automatic Partitioning (ASAP), and the Multi-rate Poisson Tree Processes (mPTP) tests. Results from GMYC and ASAP suggest that Namalycastis abiuma may be endemic to the type-locality and that all other populations studied represent a second distinct species. …”
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Is Namalycastis abiuma (Grube, 1871) (Annelida: Nereididae) restricted to its type-locality? Evidence from morphological and molecular data by Paulo Ricardo Alves, Christopher J. Glasby, Paulo Cesar Paiva, Cinthya Simone Gomes Santos

“…For species delimitation, we applied the Generalized Mixed Yule Coalescent (GMYC), the Assemble Species by Automatic Partitioning (ASAP), and the Multi-rate Poisson Tree Processes (mPTP) tests. Results from GMYC and ASAP suggest that Namalycastis abiuma may be endemic to the type-locality and that all other populations studied represent a second distinct species. …”
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Unraveling the neural dynamics of mathematical interference in english reading: A novel approach with deep learning and fNIRS data by Zhijie Liang, Ling Wang, Jianyu Su, Bo Sun, Daifa Wang, Juan Yang

“…Utilizing this dataset, a novel deep learning model named AC-LSTM is proposed, amalgamating Transformer and LSTM architectures to identify residual mathematical cognition during the English learning process. The AC-LSTM model achieves an exceptional accuracy rate of 99.8 %, surpassing other machine learning and deep learning models. …”
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Analysing LULC transformations using remote sensing data: insights from a multilayer perceptron neural network approach by Khadim Hussain, Kaleem Mehmood, Sun Yujun, Tariq Badshah, Shoaib Ahmad Anees, Fahad Shahzad, Nooruddin, Jamshid Ali, Muhammad Bilal

“…The MLP-NN model demonstrated impressive performance, with a skill measure of 0.8724 and an accuracy rate of 89.08%. The accuracy of the LULC estimates for 2022 was verified by comparing them with observed data, ensuring the model’s reliability. …”
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Associations of eating and drinking habits with cardiovascular disease and diabetes in the adult population: data from the ESSE-RF epidemiological study by N. S. Karamnova, A. I. Rytova, O. B. Shvabskaya, Yu. K. Makarova, S. A. Maksimov, Yu. A. Balanova, S. E. Evstifeeva, A. E. Imaeva, A. V. Kapustina, G. A. Muromtseva, S. A. Shalnova, O. M. Drapkina

“…The response rate was ~80%. Dietary characteristics were assessed by frequency method.Results. …”
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