[HTML][HTML] A systematic literature review on obesity: Understanding the causes & consequences of obesity and reviewing various machine learning approaches used to …
Obesity is considered a principal public health concern and ranked as the fifth foremost
reason for death globally. Overweight and obesity are one of the main lifestyle illnesses that …
reason for death globally. Overweight and obesity are one of the main lifestyle illnesses that …
Big data and IoT-based applications in smart environments: A systematic review
This paper reviews big data and Internet of Things (IoT)-based applications in smart
environments. The aim is to identify key areas of application, current trends, data …
environments. The aim is to identify key areas of application, current trends, data …
Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions
The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …
lives, including environmental pollution, public security, road congestion, etc. New …
A review of local outlier factor algorithms for outlier detection in big data streams
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 …
are different from the normal form of a dataset. It has drawn considerable interest in the field …
Anomaly-based intrusion detection systems in iot using deep learning: A systematic literature review
The Internet of Things (IoT) concept has emerged to improve people's lives by providing a
wide range of smart and connected devices and applications in several domains, such as …
wide range of smart and connected devices and applications in several domains, such as …
Ubiquitous and smart healthcare monitoring frameworks based on machine learning: A comprehensive review
During the COVID-19 pandemic, the patient care delivery paradigm rapidly shifted to remote
technological solutions. Rising rates of life expectancy of older people, and deaths due to …
technological solutions. Rising rates of life expectancy of older people, and deaths due to …
An ensemble of prediction and learning mechanism for improving accuracy of anomaly detection in network intrusion environments
The connectivity of our surrounding objects to the internet plays a tremendous role in our
daily lives. Many network applications have been developed in every domain of life …
daily lives. Many network applications have been developed in every domain of life …
Anomaly detection using a sliding window technique and data imputation with machine learning for hydrological time series
L Kulanuwat, C Chantrapornchai, M Maleewong… - Water, 2021 - mdpi.com
Water level data obtained from telemetry stations typically contains large number of outliers.
Anomaly detection and a data imputation are necessary steps in a data monitoring system …
Anomaly detection and a data imputation are necessary steps in a data monitoring system …
Robust outlier detection based on the changing rate of directed density ratio
K Li, X Gao, S Fu, X Diao, P Ye, B Xue, J Yu… - Expert Systems with …, 2022 - Elsevier
The task of outlier detection aims at mining abnormal objects that deviate from normal
distribution. Traditional unsupervised outlier detection methods can detect most global …
distribution. Traditional unsupervised outlier detection methods can detect most global …
Recent advancement of data-driven models in wireless sensor networks: a survey
Wireless sensor networks (WSNs) are considered producers of large amounts of rich data.
Four types of data-driven models that correspond with various applications are identified as …
Four types of data-driven models that correspond with various applications are identified as …