Zobrazeno 1 - 10
of 6 587
pro vyhledávání: '"TIME-SERIES DATA"'
Autor:
Bhushankumar Nemade, Kiran Kishor Maharana, Vikram Kulkarni, Surajit mondal, G S Pradeep Ghantasala, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-30 (2024)
Abstract Having access to potable water is a fundamental right to well-being. Despite this, 3.4 million people die from diseases caused by water each year, and 1.1 billion people lack access to potable drinking water. Although industrialization, dura
Externí odkaz:
https://doaj.org/article/d2fa78ad5d4b48278d81f51b75d6231f
Publikováno v:
BioData Mining, Vol 17, Iss 1, Pp 1-30 (2024)
Abstract Background Timely identification of deteriorating patients is crucial to prevent the progression to cardiac arrest. However, current methods predicting emergency department cardiac arrest are primarily static, rule-based with limited precisi
Externí odkaz:
https://doaj.org/article/97640fd7f02c4404b84a6eac19422f24
Autor:
Liu, Zengkun, Hui, Justine
Publikováno v:
Sensor Review, 2024, Vol. 44, Issue 5, pp. 563-574.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/SR-03-2024-0183
Autor:
Subramanian Deepan, Murugan Saravanan
Publikováno v:
ETRI Journal, Vol 46, Iss 5, Pp 915-927 (2024)
We obtain the air quality index (AQI) for a descriptive system aimed to communicate pollution risks to the population. The AQI is calculated based on major air pollutants including O3, CO, SO2, NO, NO2, benzene, and particulate matter PM2.5 that shou
Externí odkaz:
https://doaj.org/article/fb880beab6d14836bf59bf2350dc736e
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract We proposed a deep learning method using a convolutional neural network on time-series (TS) images to detect and differentiate affected body parts in people with Parkinson’s disease (PD) and freezing of gait (FOG) during 360° turning task
Externí odkaz:
https://doaj.org/article/2e701bb2472d4ae4a7f25d557580e2bd
Publikováno v:
Natural Language Processing Journal, Vol 9, Iss , Pp 100120- (2024)
Generative AI, and in particular Large Language Models (LLMs), have gained substantial momentum due to their wide applications in various disciplines. While the use of these game changing technologies in generating textual information has already bee
Externí odkaz:
https://doaj.org/article/ba3c1c25b6e046f184d662dbacd2799e
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
Reconstructing high-quality Normalized Difference Vegetation Index time series data is essential for ecological and agricultural applications but remains challenging in heavily cloudy areas. Fusing Sentinel SAR and optical data with deep learning cou
Externí odkaz:
https://doaj.org/article/f5c9af088f254272a3f6bb04a9da38d8
Autor:
Qian Zhang, Xiangnan Liu, Tao Peng, Xiao Yang, Mengzhen Tang, Xinyu Zou, Meiling Liu, Ling Wu, Tingwei Zhang
Publikováno v:
GIScience & Remote Sensing, Vol 61, Iss 1 (2024)
Optical remotely sensed time series data have various key applications in Earth surface dynamics. However, cloud cover significantly hampers data analysis and interpretation. Despite synthetic aperture radar (SAR)-to-optical image translation techniq
Externí odkaz:
https://doaj.org/article/fb9062838a0346d9b9cd970bc8124824
Publikováno v:
Mathematical Biosciences and Engineering, Vol 21, Iss 4, Pp 4989-5006 (2024)
Due to irregular sampling or device failure, the data collected from sensor network has missing value, that is, missing time-series data occurs. To address this issue, many methods have been proposed to impute random or non-random missing data. Howev
Externí odkaz:
https://doaj.org/article/d4bd62fec1864f429ea1498affcca648
Publikováno v:
大数据, Vol 10, Pp 34-50 (2024)
The compression strategy plays an important role in the performance of IoT time series data storage system.However, the current compression strategies can not adapt to the characteristics of NVM and IoT time series data.This paper proposes a polymorp
Externí odkaz:
https://doaj.org/article/96c162386e4644f1969ba40b8d45a66e