Results 61 to 70 of about 751,571 (292)

A data mining framework for time series estimation

Journal of Biomedical Informatics, 2010
Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation.
Hu, Xiao, Xu, Peng, Wu, Shaozhi, Asgari, Shadnaz, Bergsneider, Marvin   +4 more
openaire   +2 more sources

Photocatalytic Water Splitting on the Lunar Surface: Prospects for In Situ Resource Utilization

Advanced Materials Interfaces, EarlyView.
Water has been found in craters on the moon nearby locations which are illuminated >80% of the time. Photocatalysis uses energy from sunlight to drive chemical reactions such as water splitting to produce oxygen and hydrogen. It is a scalable technology that requires lighter equipment and utilizes resources available on the moon. ABSTRACT The discovery
Ranjani Kalyan, Thomas D. Small, Gregory F. Metha, Mahmoud Adel Hamza, Thomas J. O'Dea, Yideng Shen, Cameron J. Shearer   +6 more
wiley   +1 more source

Multiscale Average Absolute Difference (MSAAD): A Computationally Efficient and Nonparametric Adaptation of Line Length for Noisy, Uncontrolled Wearables Time Series

Algorithms
With the rise in physiological data sampled from wearable devices, efficient methods must be developed to encode temporal information for the comparison of time series arising from uncontrolled monitoring.
Jamison H. Burks, Wendy Hartogensis, Stephan Dilchert, Ashley E. Mason, Benjamin L. Smarr   +4 more
doaj   +1 more source

Combining Deep Neural Networks and Classical Time Series Regression Models for Forecasting Patient Flows in Hong Kong

IEEE Access, 2019
Deep Neural Networks (DNNs) has been dominating recent data mining related tasks with better performances. This article proposes a hybrid approach that exploits the unique predictive power of DNN and classical time series regression models, including ...
Shancheng Jiang, Ran Xiao, Long Wang, Xiong Luo, Chao Huang, Jenq-Haur Wang, Kwai-Sang Chin, Ximing Nie   +7 more
doaj   +1 more source

Time Series Data Mining: A Retail Application Using SAS Enterprise Miner [PDF]

, 2013
Modern technologies have allowed for the amassment of data at a rate never encountered before. Organizations are now able to routinely collect and process massive volumes of data.
Hebert, Daniel
core   +1 more source

HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks

, 2020
The unsupervised detection of anomalies in time series data has important applications in user behavioral modeling, fraud detection, and cybersecurity. Anomaly detection has, in fact, been extensively studied in categorical sequences.
Casiraghi, Giona, Eliassi-Rad, Tina, LaRock, Timothy, Nanumyan, Vahan, Scholtes, Ingo, Schweitzer, Frank   +5 more
core   +1 more source

Time series classification with ensembles of elastic distance measures [PDF]

, 2015
Several alternative distance measures for comparing time series have recently been proposed and evaluated on time series classification (TSC) problems.
A Stefan, Anthony Bagnall, H Deng, J Demšar, J Lin, J Lin, J Rodriguez, J Tanner, Jason Lines, L Breiman, M Baydogan, M Hall, PF Marteau, T Górecki, Y Jeong   +14 more
core   +1 more source

Laser‐Based Solidification of Cermets/Cemented Carbides: Processing‐Microstructure‐Property Relationships

Advanced Materials Technologies, EarlyView.
Recent research on laser‐processed cermets and cemented carbides highlights significant advancements, yet a notable paucity of studies and persistent challenges remain. Efforts are increasingly focused on developing low‐cost, environmentally friendly cermets as alternatives to conventional materials.
Himanshu Singh Maurya, Farid Akhtar, Konda Gokuldoss Prashanth   +2 more
wiley   +1 more source

Data Mining Peramalan Konsumsi Listrik dengan Pendekatan Cluster Time Series sebagai Preprocessing [PDF]

, 2016
Kondisi big data dan data time series memiliki permasalahan tersendiri didalam mengolah suatu data. Terle-bih lagi data tersebut juga multivariabel. Salah satu permasa-lahan yang terjadi adalah ketika proses identifikasi model yang sesuai untuk tiap ...
Fithriasari, K. (Kartika), Riyadi, M. A. (Mohammad), Widodo, D. A. (Dwiatmono)   +2 more
core  

KV-match: A Subsequence Matching Approach Supporting Normalization and Time Warping [Extended Version]

, 2018
The volume of time series data has exploded due to the popularity of new applications, such as data center management and IoT. Subsequence matching is a fundamental task in mining time series data. All index-based approaches only consider raw subsequence
Pan, Ningting, Wang, Chen, Wang, Jianmin, Wang, Peng, Wang, Wei, Wu, Jiaye   +5 more
core   +1 more source