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Changlock Choi and Seong-Yun Hong
The increasing use of mobile devices and the growing popularity of location-based ser-vices have generated massive spatiotemporal data over the last several years. While it provides new opportunities to enhance our understanding of various urban dynamics...
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Kidoo Park, Yeongjeong Seong, Younghun Jung, Ilro Youn and Cheon Kyu Choi
The methods for improving the accuracy of water level prediction were proposed in this study by selecting the Gated Recurrent Unit (GRU) model, which is effective for multivariate learning at the Paldang Bridge station in Han River, South Korea, where th...
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Elisabetta Prezzi, Dario Donno, Maria Gabriella Mellano, Gabriele Loris Beccaro and Giovanni Gamba
The present work, based on a multivariate approach, may represent a rapid, effective, and low-cost tool, preliminary to genetic analysis, for the assessment of the traceability and quality of Castanea spp. nuts with no information on their origin.
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Song Hu, Qi Shao, Wei Li, Guijun Han, Qingyu Zheng, Ru Wang and Hanyu Liu
Data-driven predictions of marine environmental variables are typically focused on single variables. However, in real marine environments, there are correlations among different oceanic variables. Additionally, sea?air interactions play a significant rol...
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Matthieu Saumard
Speech Emotions Recognition (SER) has gained significant attention in the fields of human?computer interaction and speech processing. In this article, we present a novel approach to improve SER performance by interpreting the Mel Frequency Cepstral Coeff...
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Intan Filzah Mahmod, Saharshini Jeyasimman, Muhamad Shakirin Mispan, Farahaniza Supandi, Alfi Khatib and Mohd Zuwairi Saiman
Weedy rice (Oryza spp.) is a notorious weed that invades paddy fields and hampers the rice?s production and yield quality; thus, it has become a major problem for rice farmers worldwide. Weedy rice comprises a diverse morphology and phenotypic variation;...
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Zouhair Haddi, Bouchra Ananou, Miquel Alfaras, Mustapha Ouladsine, Jean-Claude Deharo, Narcís Avellana and Stéphane Delliaux
Atrial fibrillation (AF) is still a major cause of disease morbidity and mortality, making its early diagnosis desirable and urging researchers to develop efficient methods devoted to automatic AF detection. Till now, the analysis of Holter-ECG recording...
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Imke Rhoden, Daniel Weller and Ann-Katrin Voit
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Abdul Razaque, Marzhan Abenova, Munif Alotaibi, Bandar Alotaibi, Hamoud Alshammari, Salim Hariri and Aziz Alotaibi
Time series data are significant, and are derived from temporal data, which involve real numbers representing values collected regularly over time. Time series have a great impact on many types of data. However, time series have anomalies. We introduce a...
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Kidoo Park, Younghun Jung, Yeongjeong Seong and Sanghyup Lee
Since predicting rapidly fluctuating water levels is very important in water resource engineering, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) were used to evaluate water-level-prediction accuracy at Hangang Bridge Station in Han River, ...
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Mingxiang Cai, Mohammadreza Koopialipoor, Danial Jahed Armaghani and Binh Thai Pham
Assessing the behavior of earth dams under dynamic loads is one of the most significant problems with the design of such large structures. The purpose of this study is to provide new models for predicting dam dispersion in real earthquake conditions. In ...
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Abla Alzagameem, Michel Bergs, Xuan Tung Do, Stephanie Elisabeth Klein, Jessica Rumpf, Michael Larkins, Yulia Monakhova, Ralf Pude and Margit Schulze
1. The utilization of so-called low-input crops (i.e., Miscanthus grasses and fast-growing trees) as lignocellulosic feedstock for second generation biorefineries. 2. Lignin and lignin-derived materials as agrochemical products. 3. Chemometric methods to...
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Chenfei Shao, Chongshi Gu, Zhenzhu Meng and Yating Hu
Risk assessment of dam?s running status is an important part of dam management. A data-driven method based on monitored displacement data has been applied in risk assessment, owing to its easy operation and real-time analysis. However, previous data-driv...
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Feng Wang, Wenwen Li, Sizhe Wang and Chris R. Johnson
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Emerson Lazzarotto,Liliana Madalena Gramani,Anselmo Chaves Neto,Luiz Albino Teixeira Junior
Pág. 017 - 037
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Ng Chun Won,Chong Yen Wan,Mohmad Yazam Sharif
Pág. 117 - 122
The purpose of this paper is to discuss the process of screening, editing and preparation of initial data before any further multivariate analysis of the study concerning effect of leadership styles, social capital and social entrepreneurship on organiza...
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Wenke Markgraf, Jannis Lilienthal, Philipp Feistel, Christine Thiele and Hagen Malberg
The preservation of kidneys using normothermic machine perfusion (NMP) prior to transplantation has the potential for predictive evaluation of organ quality. Investigations concerning the quantitative assessment of physiological tissue parameters and the...
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Alessandra Biancolillo, Federico Marini, Cyril Ruckebusch and Raffaele Vitale
This review will offer a global overview of the chemometric approaches most commonly used in the field of spectroscopy-based food analysis and authentication. Three different scenarios will be surveyed: data exploration, calibration and classification. B...
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Satu M. Mustonen, Soile Tissari, Laura Huikko, Mikko Kolehmainen, Markku J. Lehtola, Arja Hirvonen
Pág. 2421 - 2430
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Dean Fantazzini, Julia Pushchelenko, Alexey Mironenkov and Alexey Kurbatskii
This paper examines the suitability of Google Trends data for the modeling and forecasting of interregional migration in Russia. Monthly migration data, search volume data, and macro variables are used with a set of univariate and multivariate models to ...
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