A Characterization of the Diffuse Galactic Emissions at Large Angular Scales Using the Tenerife Data by J. F. Macías-Pérez, R. D. Davies, R. Watson, C. M. Gutierrez, R. Rebolo

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Monitoring Grassland Tourist Season of Inner Mongolia, China Using Remote Sensing Data by Quansheng Ge, Xi Yang, Zhi Qiao, Haolong Liu, Jun Liu

“…Monitoring when tourist seasons occur using satellite data has been an area of growing research interest in recent decades. …”
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Evaluating the efficiency of insurance companies in Vietnam using Data Envelopment Analysis and truncated regression by Phuong Anh Nguyen, Hoan Phuong Anh Lam

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Data Search Process Optimization using Brute Force and Genetic Algorithm Hybrid Method by Yudha Riwanto, Muhammad Taufiq Nuruzzaman, Shofwatul Uyun, Bambang Sugiantoro

“…High accuracy and speed in data search, which are aims at finding the best solution to a problem, are essential. …”
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Dissecting crosstalk induced by cell-cell communication using single-cell transcriptomic data by Jiawen Hou, Wei Zhao, Qing Nie

“…While multiple methods have been developed to infer CCC networks and their downstream response using single-cell RNA-seq data (scRNA-seq), the potential crosstalk between pathways connecting CCC with its downstream targets has been ignored. …”
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Predictive Analysis of Maritime Congestion Using Dynamic Big Data and Multiscale Feature Analysis by Yalin Wu

“…This study proposes an innovative congestion prediction approach using dynamic big data analysis of vessel trajectories and multiscale feature analysis. …”
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Use of expert elicitation in the field of occupational hygiene: Comparison of expert and observed data distributions. by David Michael Lowry, Lin Fritschi, Benjamin J Mullins, Rebecca A O'Leary

“…These elicited fitted distributions were then compared to measured data distributions, the results of which had been collected as part of an occupational hygiene program assessing full-shift exposures to the same contaminants and job roles assessed by the experts. …”
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Case Study on the Maintenance of a Construction Monitoring Using USN-Based Data Acquisition by Sangyong Kim, Yoonseok Shin, Gwang-Hee Kim

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Big Data Analysis Using Apache Spark MLlib and Hadoop HDFS with Scala and Java by Hoger Khayrolla Omar, Alaa Khalil Jumaa

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Data Checking of Asymmetric Catalysis Literature Using a Graph Neural Network Approach by Eduardo Aguilar-Bejarano, Viraj Deorukhkar, Simon Woodward

“…The range of chemical databases available has dramatically increased in recent years, but the reliability and quality of their data are often negatively affected by human-error fidelity. …”
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Use of cover data to model species abundance distributions through continuous probability functions by Halime Moradi, Paulo Inácio Prado, Jens Oldeland, Paulo A. V. Borges, Simone Fattorini

“…Abstract Species abundance distribution (SAD) models describe the abundances of the species within ecological communities. SAD modelling has been developed using frequency distributions that require the use of count data (number of individuals). …”
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Data-driven analysis of climate impact on tomato and apple prices using machine learning by Sunghyun Yoon, Tae-Hwa Kim, Dong Sub Kim

“…Machine learning has been used in various areas, but there are few studies on price prediction for agricultural products. …”
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Adaptive Learning Approach for Human Activity Recognition Using Data from Smartphone Sensors by Leonidas Sakalauskas, Ingrida Vaiciulyte

“…In this case, a recognition algorithm must be re-trained with training data of a specific size. Thus, an adaptive (also known as, online or incremental) learning algorithm would be useful in this situation. …”
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MODELING THE PROFITABILITY OF TELECOMMUNICATION SUB-SECTOR STOCKS USING PANEL DATA REGRESSION ANALYSIS by Ni Putu Nanik Hendayanti, Maulida Nurhidayati

“…This study aims to model telecommunications subsector companies' profitability on the Indonesian stock exchange using panel data regression analysis. The panel data regression analysis mixes cross-section data and time series data in which the same cross-section unit is sampled at various times. …”
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Dynamics of changes in lake volume and surface area using multi-source geospatial data by Julzarika Atriyon, Suhadha Argo Galih

“…The main objective of this study is to monitor the dynamics of changes in the volume and surface area of Lake Singkarak from 1883 to 2023 using multi-source geospatial data. The Dutch East Indies topography-bathymetry (1883) map and the DTM/bathymetry (2023) data were used. …”
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TRIDENT: Text-Free Data Augmentation Using Image Embedding Decomposition for Domain Generalization by Yoonyoung Choi, Geunhyeok Yu, Hyoseok Hwang

“…To mitigate the effects of distribution shifts, domain generalization (DG) aims to enable models to generalize effectively to unseen target domains. Recent DG approaches use generative models like diffusion models to augment data with text prompts. …”
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Land use classification through fusion of remote sensing images and multi-source data by Guo Zhiqian, Ren Yushui, Li Xin, Ma Kang, Qian Shujun

“…This indicates that the method can effectively enhance the features of land remote sensing images through remote sensing and multi-source data fusion, and has ideal accuracy for multi-class land use classification, which can achieve accurate classification of land use.…”
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Ground data analysis for PM2.5 Prediction using predictive modeling techniques by Elham Nourmohammad, Yousef Rashidi

“…Results: Results indicate that XGBoost excelled in daily predictions when using solely meteorological data, achieving an R² score of 0.998674, while ARIMA demonstrated strong predictive capacity but struggled with added complexity. …”
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Soil moisture estimation using multi linear regression with terraSAR-X data by G. García, M. Brogioni, V. Venturini, L. Rodriguez, G. Fontanelli, E. Walker, S. Graciani, G. Macelloni

“…Besides ground measurements, remote sensing has proven to be an excellent tool for the monitoring of spatial and temporal distributed data of the most relevant Earth surface parameters including soil’s parameters. …”
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Big data processing using hybrid Gaussian mixture model with salp swarm algorithm by R. Saravanakumar, T. TamilSelvi, Digvijay Pandey, Binay Kumar Pandey, Darshan A. Mahajan, Mesfin Esayas Lelisho

“…Abstract The traditional methods used in big data, like cluster creation and query-based data extraction, fail to yield accurate results on massive networks. …”
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