GeoRoma: il servizio cartografico unificato di Roma Capitale by Redazione MediaGEO

“…This transformation has taken shape through the development of a modern WebGIS platform and the public release of new tools for accessing spatial data. Alongside the institutional Geoportal, the city has recently launched GeoRoma, a mobile application designed to make key geographic information available to users—citizens, professionals, and administrators alike—in an intuitive and location-aware format. …”
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Evaluating Sugarcane Yield Estimation in Thailand Using Multi-Temporal Sentinel-2 and Landsat Data Together with Machine-Learning Algorithms by Jaturong Som-ard, Savittri Ratanopad Suwanlee, Dusadee Pinasu, Surasak Keawsomsee, Kemin Kasa, Nattawut Seesanhao, Sarawut Ninsawat, Enrico Borgogno-Mondino, Filippo Sarvia

“…Yield data collection is an expensive and time-consuming practice that often limits the number of samples collected. …”
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Portable XRF and Vis-NIR spectrometry for predicting chemical properties of forest soils in the Amazon: Insights into sensor data dimensionality reduction by Quésia Sá Pavão, Paula Godinho Ribeiro, Gutierre Pereira Maciel, Sérgio Henrique Godinho Silva, Suzana Romeiro Araújo, Antonio Rodrigues Fernandes, José Alexandre Melo Demattê, Pedro Walfir Martins e Souza Filho, Silvio Junio Ramos

“…Proximal sensor data integrated with machine learning algorithms have been successful in assessing soil chemical parameters. …”
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Using GPS and accelerometer data to precisely record egg laying, incubation and chick hatching of Cinereous Vultures (Aegypius monachus) in-situ by Cornel Cotorogea, Emilian Stoynov, Atanas Grozdanov, Simeon Marin, Hristo Valeriev Peshev, Ivelin Ivanov, Georgi P. Stoyanov

“…As the chick grows and requires less brooding, the accelerometer graph returns to pre-incubation values, indicating the adult's return to a more typical posture on the nest.This methodology offers advantages over traditional monitoring techniques, providing continuous, precise, and non-invasive data acquisition. Its application can enhance conservation programs by enabling timely interventions, improving breeding success rates, and contributing to a deeper understanding of Cinereous Vulture reproductive biology. …”
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Data mining-based screening of prevalent mixture systems in aquatic environments: A case study of antibiotics in the Yangtze River Basin by Ting-Ting Ding, Shi-Lin Du, Hong-Yi Liang, Ya-Hui Zhang, Yong Tao, Ming-Xiao Li, Jin Zhang, Shu-Shen Liu

“…PMSS enables efficient data mining of chemical concentrations, allowing for the identification of a small number of prevalent mixture systems from numerous theoretical possibilities. …”
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Inversion of Leaf Chlorophyll Content in Different Growth Periods of Maize Based on Multi-Source Data from “Sky–Space–Ground” by Wu Nile, Su Rina, Na Mula, Cha Ersi, Yulong Bao, Jiquan Zhang, Zhijun Tong, Xingpeng Liu, Chunli Zhao

“…This study proposes an improved method based on multi-source data, combining the Sentinel-2A spectral response function (SRF) and computer algorithms, to overcome the limitations of traditional methods. …”
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A combined data assimilation and deep learning approach for continuous spatio-temporal SWE reconstruction from sparse ground tracks by Matteo Guidicelli, Kristoffer Aalstad, Désirée Treichler, Nadine Salzmann

“…To overcome these drawbacks, here, we present a combined probabilistic data assimilation and deep learning approach to reconstruct spatio-temporal SWE from observations of snow depth along ground tracks, imitating ICESat-2 tracks in view of a potential future global application.Our approach is based on assimilating SWE and snow cover information in a degree-day model with an iterative ensemble smoother (IES) which allows temporally reconstructing SWE along hypothetical ground tracks separated by 3 km. …”
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Using routine primary care data in research: (in)efficient case studies and perspectives from the Asthma UK Centre for Applied Research by David Price, Jennifer K Quint, Andrew Wilson, Hilary Pinnock, Andrew Bush, Amy Hai Yan Chan, Holly Tibble, Steve Cunningham, Stephen Turner, Kay Wang, Luke Daines, Mome Mukherjee, Gwyneth A Davies, Steven Julious, Tracy Jackson, Deepa Varghese, Rami A Alyami, Noelle Morgan

“…Practical consequences included a trial that over-recruited by 20% in order to randomise 144 practices with all required permissions, and a 5-year delay in reporting a trial while retrospectively applied regulations were satisfied to allow data linkage.Conclusions Overcoming the substantial barriers of using routine primary care data will require a streamlined governance process, standardised understanding/application of regulations and adequate National Health Service IT (Information Technology) capability. …”
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Leveraging moisture elimination and hybrid deep learning models for soil organic carbon mapping with multi-modal remote sensing data by Yilin Bao, Xiangtian Meng, Weimin Ruan, Huanjun Liu, Mingchang Wang, Abdul Mounem Mouazen

“…Currently, SOC prediction remains challenging due to unresolved moisture disturbances, underutilized multimodal remote sensing data, and uncertain model transferability. To address these challenges, a new paradigm integrating moisture elimination with advanced hybrid deep learning has been developed. …”
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Nutritional risk, functional decline, and symptom burden in lung cancer: a study based on PG-SGA scores and biochemical data by Shasha Shen, Shasha Shen, Shiyun Xing, Shiyun Xing, Tingting Shen, Li Niu, Xiaojing Tian, Xiaojing Tian, Hu Ma, Hu Ma, Xiaoxia Gou, Xiaoxia Gou

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Penerapan Algoritma K-Means Untuk Mengelompokkan Kepadatan Penduduk Di Provinsi DKI Jakarta by Frisma Handayanna, Sunarti Sunarti

“…The research proves that the test results carried out clustering iterations of population density data were obtained in three iterations. For the results obtained by calculations using the K-Means method and using the rapidminer application, the results obtained were of the same value, namely the cluster with the highest population density of three districts/cities, namely South Jakarta, East Jakarta and West Jakarta whose population density continues to increase. …”
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The use of Remote Sensing Technology in geological Investigation and mineral Detection in El Azraq-Jordan by Samih Al-Rawashdeh, Bassam Saleh, Mufeed Hamzah

“…A remote sensed lineament map was produced using two different methods: (i) application of directional filters and edge enhancement; and (ii) data fusion of ETM+ with SAR image. …”
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Optimizing hybrid models for forest leaf and canopy trait mapping from EnMAP hyperspectral data with limited field samples by Nizom Farmonov, Susanne Walden, Eric Martinée, Christian Lampei, Mona Schreiber, Lars Opgenoorth, Anjaharinony Andry Ny Aina Rakotomalala, Tobias Müller, Nina Farwig, Stefan Pinkert, Lucy Saueressig, Annabell Rosemarie Wagner, Robert R. Junker, Jochem Verrelst, Jörg Bendix

“…The application of optimized hybrid GPR models to the study area enabled area-wide landscape forest trait mapping with minimal computational effort.…”
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POSSIBILITIES FOR ECHOCARDIOGRAPHIC DETERMINATION OF PULMONARY ARTERY PRESSURE IN PATIENTS WITH SYSTEMIC CONNECTIVE TISSUE DISEASES: DATA OF A RHEUMATOLOGY EXPERT CENTER by E. V. Nikolaeva, Yu. O. Korsakova, I. A. Kurmukov, S. I. Glukhova, N. N. Yudkina, A. V. Volkov

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PROFILING IN THE RECRUITMENT OF SUBJECTS FOR CLINICAL TRIALS IN THE LIGHT OF GDPR by Natalia Domagała, Bartłomiej Oręziak, Marek Świerczyński

“…This issue is particularly important due to the regulatory framework for profiling adopted under GDPR (the General Data Protection Regulation). GDPR is of crucial importance for the R&D activities pursued by the pharmaceutical industry and in personalized medicine, and one of the biggest challenges is the practical application of its rules in profiling activities. …”
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Support Vector and Linear Regression Machine Learning Model on Amperometric Signals to Predict Glucose Concentration and Hematocrit Volume by Kirti Sharma, Pawan K. Tiwari, Sanjay Kumar Sinha

“…Data represents a compendium of information that perpetually expands with each passing moment, contributed by individuals worldwide. …”
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Research beyond Randomised Controlled Trial: The Importance of Pragmatic Clinical Trials for Generating Real-world Evidence in Current Healthcare by Sangita Jogdand, Smruti Besekar, Satyawan Singh Patel

“…The potential of Real-world Evidence (RWE) to provide valuable insights from Real-world Data (RWD) has drawn a lot of attention recently. …”
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Boosting Crowdsourced Annotation Accuracy: Small Loss Filtering and Augmentation-Driven Training by Yanming Fu, Weigeng Han, Jingsang Yang, Haodong Lu, Xin Yu

“…Crowdsourcing platforms provide an efficient and cost-effective means to acquire the extensive labeled data necessary for supervised learning. However, the labels provided by untrained crowdsourcing workers often contain a considerable amount of noise. …”
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Subgroups: A Python library for Subgroup Discovery by Antonio Lopez-Martinez-Carrasco, Jose M. Juarez, Manuel Campos, Francisco Mora-Caselles

“…Furthermore, the Subgroups Library has been successfully employed in diverse scientific papers and projects, underscoring its efficacy and versatility as a valuable tool for SD exploration and application.…”
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La campagna per il Referendum Costituzionale 2020 e la comunicazione antipopulista su Facebook: un’applicazione di Content Analysis dagli esordi accademici del primo Crowdtangle by Gabriella Punziano, Francesco Marrazzo, Suania Acampa

“… Closing free access to online platform APIs has changed social research in digital spaces. Access to data is now managed and regulated exclusively by proprietary platforms, which have shared various tools to data extraction with precise rules to data access. …”
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