Movement‐mediated community assembly and coexistence

UE Schlägel, V Grimm, N Blaum, P Colangeli… - Biological …, 2020 - Wiley Online Library
Organismal movement is ubiquitous and facilitates important ecological mechanisms that
drive community and metacommunity composition and hence biodiversity. In most existing …

A review of immersive technologies, knowledge representation, and AI for human-centered digital experiences

N Partarakis, X Zabulis - Electronics, 2024 - mdpi.com
The evolution of digital technologies has resulted in the emergence of diverse interaction
technologies. In this paper, we conducted a review of seven domains under a human-centric …

Big data emerging technology: insights into innovative environment for online learning resources

M Huda, A Maseleno, P Atmotiyoso… - … Journal of Emerging …, 2018 - learntechlib.org
Digital devices like tablets, smart phones, and laptop have become increasingly raised and
utilised in higher education. As a result, current trends on ICT (information and …

Model-based and model-free machine learning techniques for diagnostic prediction and classification of clinical outcomes in Parkinson's disease

C Gao, H Sun, T Wang, M Tang, NI Bohnen… - Scientific reports, 2018 - nature.com
In this study, we apply a multidisciplinary approach to investigate falls in PD patients using
clinical, demographic and neuroimaging data from two independent initiatives (University of …

Using deep learning and visual analytics to explore hotel reviews and responses

YC Chang, CH Ku, CH Chen - Tourism Management, 2020 - Elsevier
This study aims to use computational linguistics, visual analytics, and deep learning
techniques to analyze hotel reviews and responses collected on TripAdvisor and to identify …

Big data-driven contextual processing methods for electrical capacitance tomography

A Romanowski - IEEE Transactions on Industrial Informatics, 2018 - ieeexplore.ieee.org
This paper presents a new approach to analyzing measurement records from industrial
processes. The proposed methodology is based on the model of contextual processing and …

Sampling techniques for big data analysis

JK Kim, Z Wang - International Statistical Review, 2019 - Wiley Online Library
In analysing big data for finite population inference, it is critical to adjust for the selection bias
in the big data. In this paper, we propose two methods of reducing the selection bias …

Requirements for big data adoption for railway asset management

P McMahon, T Zhang, R Dwight - Ieee Access, 2020 - ieeexplore.ieee.org
Nowadays, huge amounts of data have been captured along with the day-to-day operation
of assets including railway systems. Hence, we have come to the era of big data. The …

Machine learning outperforms clinical experts in classification of hip fractures

EA Murphy, B Ehrhardt, CL Gregson, OA von Arx… - Scientific reports, 2022 - nature.com
Hip fractures are a major cause of morbidity and mortality in the elderly, and incur high
health and social care costs. Given projected population ageing, the number of incident hip …

Big data and the future of urban ecology: From the concept to results

J Yang - Science China Earth Sciences, 2020 - Springer
Urban ecology is experiencing the third paradigm shift. To understand the interactions
between the social system and the natural system in the city across time and space, and to …