Leveraging Open-Source Tools to Analyse Ground-Based Forest LiDAR Data in South Australian Forests by Spencer O’Keeffe, Bruce H. Thomas, Jim O’Hehir, Jan Rombouts, Michelle Balasso, Andrew Cunningham

“…This paper investigates the application of open-source software and methods for forest LiDAR analysis, with a focus on enhancing forest inventory metrics in the radiata pine forests of South Australia’s Green Triangle region. …”
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Sustainability, Reporting and Market Access for Grain and Oilseed Growers: Can Yield Data Provide More Rigour and Transparency? by Robert Clark, Peter Dahlhaus, Nathan Robinson, Elizabeth Morse‐McNabb

“…The time and cost incurred to collect these measurements could be reduced by using secondary data to report on sustainability. Yield data are already collected by many grain, and oilseed growers, and provide a transparent, evidence‐based way to optimise and report on fertiliser application at fine scale. …”
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2SpamH: A Two-Stage Pre-Processing Algorithm for Passively Sensed mHealth Data by Hongzhe Zhang, Jihui L. Diaz, Soohyun Kim, Zilong Yu, Yiyuan Wu, Emily Carter, Samprit Banerjee

“…In this work, we propose an unsupervised 2-Stage Pre-processing Algorithm for Passively Sensed mHealth Data (2SpamH) algorithm that uses device usage variables to infer the quality of passive sensing data from mobile devices. …”
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Comparison of Sugarcane Drought Stress Based on Climatology Data using Machine Learning Regression Model in East Java by Aries Suharso, Yeni Herdiyeni, Suria Darma Tarigan, Yandra Arkeman

“…The application of the results shows that climatological data with lag effects can accurately estimate water stress conditions in rainfed sugarcane. …”
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Estimating Subsurface Geostatistical Properties from GPR Reflection Data Using a Supervised Deep Learning Approach by Yu Liu, James Irving, Klaus Holliger

“…This strategy effectively addresses the notorious challenge of insufficient training data, which frequently impedes the application of deep-learning-based methods in applied geophysics. …”
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A data augmentation approach to enhance breast cancer detection using generative adversarial and artificial neural networks by Alawee Wissam H., Al-Haddad Luttfi A., Basem Ali, Al-Haddad Abdullah A.

“…Prior to analysis, the images were subjected to a sophisticated data augmentation process that leveraged data denoising, contrast enhancement, and the application of a generative adversarial network (GAN). …”
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Organizations` Responsibility in Maintaining the Security of Personal Data posted Online by Romanian Consumers: an Exploratory Analysis of Facebook and Linkedin by Andreea Ionescu, Laurenţiu-Dan Anghel, Gheorghe Jinga

“…It is a very useful and needed tool for Romanian companies, as it presents the users’ point of view, allowing them to find the best and most ethical way to do social data mining or use consumers’ private information, disclosed on such sites. …”
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Snow depth estimation in Northeast China based on space-borne scatterometer data and ML model with optimal features by Wenfei Chen, Lingjia Gu, Xiaofeng Li, Xintong Fan

“…This study indicates that spaceborne scatterometer data hold promise for SD estimation in snow monitoring applications.…”
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Synthetic Imaging Radar Data Generation in Various Clutter Environments Using Novel UWB Log-Periodic Antenna by Deepmala Trivedi, Gopal Singh Phartiyal, Ajeet Kumar, Dharmendra Singh

“…The proposed antenna has a highly directional radiation pattern with considerable high gain (more than 6 dBi) on the entire bandwidth. Synthetic data are generated for two different applications, namely through-the-wall imaging (TWI) and through-the-foliage imaging (TFI). …”
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IoT-Based Airport Noise Perception and Monitoring: Multi-Source Data Fusion, Spatial Distribution Modeling, and Analysis by Jie Liu, Shiman Sun, Ke Tang, Xinyu Fan, Jihong Lv, Yinxiang Fu, Xinpu Feng, Liang Zeng

“…The results of the practical application demonstrate that the proposed airport noise monitoring method can accurately reflect the spatiotemporal distribution patterns of airport noise and effectively correlate noise events, thereby providing robust data support for the development of airport noise control policies.…”
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NDEExplorer: Visual Analytics for Exploring Damage Modes via Multimodal Data in the Non-Destructive Examination of Composite Materials by Dongliang Guo, Lisha Zhou, Xingfa Luo

“…For users, the application of this system can help accurately identify the various material damage stages and their accompanying damage modes. …”
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A novel PV power prediction method with TCN-Wpsformer model considering data repair and FCM cluster by Tong Yang, Minan Tang, Hanting Li, Hongjie Wang, Chuntao Rao

“…The time code of the dataset obtained after data restoration and FCM clustering was spliced with the location code. …”
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Leveraging Machine Learning for Pediatric Appendicitis Diagnosis: A Retrospective Study Integrating Clinical, Laboratory, and Imaging Data by Mahdi Navaei, Zohre Doogchi, Fatemeh Gholami, Moein Kermanizadeh Tavakoli

“…Methods A retrospective analysis was conducted on 782 pediatric patients from the Regensburg Pediatric Appendicitis Data set. Clinical scores, laboratory markers, and imaging findings were analyzed. …”
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A Hybrid Data and Mechanism Model-driven Digital Twin Modelling Approach for Novel Traction Power Systems by Xin Li, Yingzhi Liu

“…Secondly, based on the measured data of photovoltaic (PV) power, the data are segmented according to its output time characteristics after preprocessing. …”
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Estimation of the future prevalence of diabetes based on data from the Brazilian Study of Cardiovascular Risk Factors in Adolescents (ERICA). by Barbara Pozzi Ottavio, Stéfani Sousa Borges, Márcia Gisele Santos da Costa, Maria Cristina Caetano Kuschnir

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Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans. by Mei Zhan, Matthew M Crane, Eugeni V Entchev, Antonio Caballero, Diana Andrea Fernandes de Abreu, QueeLim Ch'ng, Hang Lu

“…Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. …”
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Dynamic Sensor-Based Data Management Optimization Strategy of Edge Artificial Intelligence Model for Intelligent Transportation System by Nu Wen, Ying Zhou, Yang Wang, Ye Zheng, Yong Fan, Yang Liu, Yankun Wang, Minmin Li

“…In the intelligent transportation field, object recognition, detection, and location applications face significant real-time challenges. To address these issues, we propose an automatic sensor-based data loading and unloading optimization strategy for algorithm models. …”
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Employing the vertical electrical soundings (VES) and lithological data for defining the hydrostratigraphic unit in the mud Lapindo disaster area by Dian Chandrasasi, Sri Sangkawati Sachro, Suharyanto Suharyanto, Thomas Triadi Putranto

“…Therefore, the main objective of this study is to use integrated data from Vertical Electrical Soundings (VES) and lithology data to support the development of a hydrogeological model.In this study, the distribution of resistivity values is used to identify the presence of land. …”
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A Study on a Geohash Cell-Based Spatial Analysis Using Individual Vehicle Data for Linear Information by Kyu Soo Chong

“…This study aims to propose an area-based spatial analysis method that allows for the flexible application of analysis scales using individual vehicle data, as opposed to node and link generation for linear road networks. …”
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Deterministic and statistical calibration of constitutive models from full-field data with parametric physics-informed neural networks by David Anton, Jendrik-Alexander Tröger, Henning Wessels, Ulrich Römer, Alexander Henkes, Stefan Hartmann

“…Abstract The calibration of constitutive models from full-field data has recently gained increasing interest due to improvements in full-field measurement capabilities. …”
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