Dual-Channel CNN-Based Framework for Automated Rebar Detection in GPR Data of Concrete Bridge Decks by Sepehr Pashoutani, Mohammadsajjad Roudsari, Jinying Zhu

“…Performance was assessed through the visual comparison of the generated bridge amplitude maps against ground-truth data, as well as precision, recall, and F1-score metrics. …”
Get full text

Development of a customised data management system for a COVID-19-adapted colorectal cancer pathway by Malcolm G Dunlop, Yasuko Maeda, Janice Miller, Frances Gunn, Farhat VN Din

“…We assessed its performance and robustness.Methods A system was developed using Microsoft Excel (2007) to retain the spreadsheets’ intuitiveness of direct data entry. Visual Basic for Applications (VBA) was used to construct a user-friendly interface to enhance efficiency of data entry and segregate the data for operational tasks.Results Large data segregation was possible using VBA macros. …”
Get full text

A Tailored Compliance Solution for Securing Personal Data privacy under Law 18-07 in Algeria by Mohamed kamel Benkaddour, Redouane Guettal, Ph.D

“…The development of this application was carried out with the Microsoft Visual FoxPro V.9 language, thus allowing the creation of a database and interfaces adapted to the needs of algerian companies to comply with Law 18-07 and guarantee the security of personal data. …”
Get full text

A beautiful place: investigating the determinants of perceived scenic beauty in Austrian landscapes with social media data by Miroslav Despotovic, Christoph Hauser

“…Abstract This study investigates the determinants of perceived scenic beauty in Austrian municipalities using social media data. Employing a multimodal approach, we analyze geo-referenced metadata and visual content from Flickr, focusing on the number of “favorite” clicks as a proxy for landscape attractiveness. …”
Get full text

High-Res Acoustic and Environmental Data to Monitor Bombus dahlbomii Amid Invasive Species, Habitat Loss by Patrick Chwalek, Marie Kuronaga, Isamar Zhu, Sophia Montague, Victoria Campopiano Robinson, Josefina Lohrmann, Cristian Alfonso Villagra Gil, David Susič, Anton Gradišek, Johannes Schul, Joseph A. Paradiso, Marina Arbetman

“…Additionally, our robust data annotation techniques enhance the dataset’s reliability for future modeling work.…”
Get full text

Depression restoration in university students: Data-driven insights across three types of campus greennessOSF by Chaoyi Cui, Qianchen He, Huiming Liu

“…Exploratory and confirmatory factor analyses validated the measurement model, confirming the reliability and theoretical coherence of constructs such as Perceived Greenness, Perceived Restoration, and Self-Rating Depression. The data allow for a robust investigation into how different campus spatial configurations and green space attributes—such as accessibility, quality, and visual appeal—relate to student mental well-being. …”
Get full text

Does Sensory Function Decline Independently or Concomitantly with Age? Data from the Baltimore Longitudinal Study of Aging by Shekhar K. Gadkaree, Daniel Q. Sun, Carol Li, Frank R. Lin, Luigi Ferrucci, Eleanor M. Simonsick, Yuri Agrawal

Get full text

Short-Wave Infrared (SWIR) Imaging for Robust Material Classification: Overcoming Limitations of Visible Spectrum Data by Hanbin Song, Sanghyeop Yeo, Youngwan Jin, Incheol Park, Hyeongjin Ju, Yagiz Nalcakan, Shiho Kim

“…Our method leverages SWIR’s distinct reflectance characteristics, particularly for materials containing moisture, and demonstrates a significant improvement in accuracy. Specifically, SWIR data achieved near-perfect classification results with an accuracy of 99% for distinguishing real from artificial objects, compared to 77% with visible spectrum data. …”
Get full text

An iterative approach for estimating domain-specific cognitive abilities from large scale online cognitive data by Valentina Giunchiglia, Dragos-Cristian Gruia, Annalaura Lerede, William Trender, Peter Hellyer, Adam Hampshire

“…However, variability in peoples’ home devices, visual and motor abilities, and speed-accuracy biases confound the specificity with which online tasks can measure cognitive abilities. …”
Get full text

Evaluation of the Effect of Political Advertisements on Voters with Psychophysiological Data Harvesting Technique: The Case of 2023 Presidential Elections by Yaren Demirel

“…The aim of this study is to evaluate voters' levels of interest and focus on the political advertisements used by presidential candidates during the second round of the 2023 presidential elections, utilizing the Psychophysiological Data Harvesting technique. According to the research findings, significant differences were identified among participants' psychophysiological outputs regarding the political advertisement videos aired during the second round of the 2023 presidential elections. …”
Get full text

Identification of spatial and temporal land cover alterations in the Jakarta TOD areas utilizing Google Earth data by Tanuda Pedro Rusdiono, Adi Wibowo

Get full text

Seafloor Sediment Classification Using Small-Sample Multi-Beam Data Based on Convolutional Neural Networks by Haibo Ma, Xianghua Lai, Taojun Hu, Xiaoming Fu, Xingwei Zhang, Sheng Song

“…To overcome the scarcity of seafloor sediment acoustic image data, we applied a deep convolutional generative adversarial network (DCGAN) for data augmentation, incorporating a de-normalization and anti-normalization module into the original DCGAN framework. …”
Get full text

Machine learning-assisted early detection of keratoconus: a comparative analysis of corneal topography and biomechanical data by Arkadiusz Syta, Arkadiusz Podkowiński, Tomasz Chorągiewicz, Robert Karpiński, Jakub Gęca, Dominika Wróbel-Dudzińska, Katarzyna E Jonak, Dariusz Głuchowski, Marcin Maciejewski, Robert Rejdak, Kamil Jonak

“…Abstract Keratoconus is a progressive eye disease characterized by the thinning and bulging of the cornea, leading to visual impairment. Early and accurate diagnosis is crucial for effective management and treatment. …”
Get full text

Pre-Filtering SCADA Data for Enhanced Machine Learning-Based Multivariate Power Estimation in Wind Turbines by Bubin Wang, Bin Zhou, Denghao Zhu, Mingheng Zou, Haoxuan Luo

“…First, thresholds for pitch angle and rotor speed are determined based on SCADA data distribution, and the filtering effect is visualized. …”
Get full text

Digital Forensic Analysis of UAV Flight Data Using Static and Dynamic Methods in Coal Mining Area by Muhammad Yusuf Halim, Ahmad Luthfi

“…Dynamic acquisition yielded 64 media files including 63 photographs (.JPG and .jpg) with 10 deleted, 14 videos (.MP4, .MOV, .SWF) with 6 deleted, 11 audio files, 4 plain text files, 31 deleted files, 3 EXIF metadata records containing GPS coordinates, and 3 unidentified log files. The GPS data from EXIF metadata was visualized in Google Earth to map flight paths and confirm boundary violations. …”
Get full text

Comparative analysis of oral disorder burden in China and globally from 1990 to 2021 based on GBD data by Peixin Zheng, Xiaoting Qiu, Lingxiao Zhang, Peizhang Liu, Zeyi Peng, Zhijian Huang

“…All statistical analyses and data visualizations were conducted using R. In 2021, the burden of oral disorders in China accounted for a significant proportion of the global burden. …”
Get full text

Bayesian network modeling applied to food risks: Data from General Administration of Customs of China as an example by Xuanyu Ying, Anni Lu, Qiang Cai, Jun Lu

“…BN modeling is a rich and flexible analytical technique capable of elucidating complex food data. It is a data-driven graphical modeling technique and exploratory tool that visually presents dependencies and causal associations while retaining statistical rigor in holistic level inference. …”
Get full text

Quantifying nocturnal thrush migration using sensor data fusion between acoustics and vertical‐looking radar by Silvia Giuntini, Juha Saari, Adriano Martinoli, Damiano G. Preatoni, Birgen Haest, Baptiste Schmid, Nadja Weisshaupt

“…Abstract Studying nocturnal bird migration is challenging because direct visual observations are difficult during darkness. …”
Get full text

Machine learning for epithelial ovarian cancer platinum resistance recurrence identification using routine clinical data by Li-Rong Yang, Mei Yang, Liu-Lin Chen, Yong-Lin Shen, Yuan He, Zong-Ting Meng, Wan-Qi Wang, Feng Li, Zhi-Jin Liu, Lin-Hui Li, Yu-Feng Wang, Xin-Lei Luo

“…Conversely, the LR model based on lasso regression yielded commendable results as well; it achieved an AUC of 0.738, a sensitivity of 0.541, a specificity of 0.836, with a cut-off value established at 0.154 and an accuracy rate of 79.6%. Finally, we visualized both models through nomograms to illustrate the significance of each variable involved in their development.ConclusionsWe have successfully developed predictive models for platinum-resistant recurrence of epithelial ovarian cancer, utilizing routine clinical and laboratory data. …”
Get full text

Spatially predicting ecosystem service patterns in boreal drained peatlands forests using multisource satellite data by Kaapro Keränen, Anwarul Islam Chowdhury, Parvez Rana

“…We mapped five ESs: bilberry yield, visual amenity, biodiversity conservation, carbon storage, and timber production using Landsat 8–9, Sentinel-2, and PlanetScope data. …”
Get full text