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Liqiu Chen, Chongshi Gu, Sen Zheng and Yanbo Wang
Real and effective monitoring data are crucial in assessing the structural safety of dams. Gross errors, resulting from manual mismeasurement, instrument failure, or other factors, can significantly impact the evaluation process. It is imperative to elim...
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Fan Lin, Dengjie Chen, Cheng Liu and Jincheng He
This study pioneered a non-destructive testing approach to evaluating the physicochemical properties of golden passion fruit by developing a platform to analyze the fruit?s electrical characteristics. By using dielectric properties, the method accurately...
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Francisco Melo Pereira and Rute C. Sofia
This paper provides an analysis of two machine learning algorithms, density-based spatial clustering of applications with noise (DBSCAN) and the local outlier factor (LOF), applied in the detection of outliers in the context of a continuous framework for...
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Shengwei Jia, Nianyu Zou, Songhai Xu and Min Cheng
In this paper, an illumination measurement system is proposed and experimentally demonstrated. The system consists of two parts, including the illumination acquisition module mounted on the UAV and the real-time display interface of the cloud platform wi...
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Jaroslaw Kurek, Gniewko Niedbala, Tomasz Wojciechowski, Bartosz Swiderski, Izabella Antoniuk, Magdalena Piekutowska, Michal Kruk and Krzysztof Bobran
This research delves into the application of machine learning methods for predicting the yield of potato varieties used for French fries in Poland. By integrating a comprehensive dataset comprising agronomical, climatic, soil, and satellite-based vegetat...
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Omar Alghushairy, Raed Alsini, Terence Soule and Xiaogang Ma
Outlier detection is a statistical procedure that aims to find suspicious events or items that are different from the normal form of a dataset. It has drawn considerable interest in the field of data mining and machine learning. Outlier detection is impo...
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William Hurst, Aaron Boddy, Madjid Merabti and Nathan Shone
Hospital critical infrastructures have a distinct threat vector, due to (i) a dependence on legacy software; (ii) the vast levels of interconnected medical devices; (iii) the use of multiple bespoke software and that (iv) electronic devices (e.g., laptop...
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William Hurst, Casimiro A. Curbelo Montañez and Nathan Shone
Smart meters have become a core part of the Internet of Things, and its sensory network is increasing globally. For example, in the UK there are over 15 million smart meters operating across homes and businesses. One of the main advantages of the smart m...
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Felipe Bravo,Marek Fabrika,Christian Ammer,Susana Barreiro,Kamil Bielak,Lluis Coll,Teresa Fonseca,Ahto Kangur,Magnus Löf,Katarina Merganicová,Maciej Pach,Hans Pretzsch,Dejan Stojanovic,Laura Schuler,Sanja Peric,Thomas Rötzer,Miren del Río,Martina Dodan,Andrés Bravo-Oviedo
Pág. eR002
Aim of study: Modelling of forest growth and dynamics has focused mainly on pure stands. Mixed-forest management lacks systematic procedures to forecast the impact of silvicultural actions. The main objective of the present work is to review current know...
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Lars Drössler, Eric Agestam, Kamil Bielak, Malgorzata Dudzinska, Julia Koricheva, Mateusz Liziniewicz, Magnus Löf, Bill Mason, Hans Pretzsch, Sauli Valkonen and Klaas Wellhausen
Pine-spruce forests are one of the commonest mixed forest types in Europe and both tree species are very important for wood supply. This study summarized nine European studies with Scots pine and Norway spruce where a mixed-species stand and both monocul...
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