Routing in wireless sensor networks using machine learning techniques: Challenges and opportunities
Energy conservation is the primary task in Wireless Sensor Networks (WSNs) as these tiny
sensor nodes are the backbone of today's Internet of Things (IoT) applications. These nodes …
sensor nodes are the backbone of today's Internet of Things (IoT) applications. These nodes …
Machine learning algorithms for wireless sensor networks: A survey
Wireless sensor network (WSN) is one of the most promising technologies for some real-
time applications because of its size, cost-effective and easily deployable nature. Due to …
time applications because of its size, cost-effective and easily deployable nature. Due to …
Machine learning for microalgae detection and utilization
H Ning, R Li, T Zhou - Frontiers in Marine Science, 2022 - frontiersin.org
Microalgae are essential parts of marine ecology, and they play a key role in species
balance. Microalgae also have significant economic value. However, microalgae are too …
balance. Microalgae also have significant economic value. However, microalgae are too …
Augmented time regularized generative adversarial network (atr-gan) for data augmentation in online process anomaly detection
Supervised machine learning techniques, such as classification models, have been widely
applied to online process anomaly detection in advanced manufacturing. However, since …
applied to online process anomaly detection in advanced manufacturing. However, since …
Unsupervised online anomaly detection on multivariate sensing time series data for smart manufacturing
RJ Hsieh, J Chou, CH Ho - 2019 IEEE 12th conference on …, 2019 - ieeexplore.ieee.org
The emergence of IoT and AI has brought revolutionary change in various application
domains. One of them is Industry 4.0, also called Smart Manufacturing, which aims to …
domains. One of them is Industry 4.0, also called Smart Manufacturing, which aims to …
On application of one-class SVM to reverse engineering-based hardware Trojan detection
Due to design and fabrication outsourcing to foundries, the problem of malicious
modifications to integrated circuits known as hardware Trojans has attracted attention in …
modifications to integrated circuits known as hardware Trojans has attracted attention in …
Standalone noise and anomaly detection in wireless sensor networks: a novel time‐series and adaptive Bayesian‐network‐based approach
Wireless sensor networks (WSNs) consist of small sensors with limited computational and
communication capabilities. Reading data in WSN is not always reliable due to open …
communication capabilities. Reading data in WSN is not always reliable due to open …
Context-aware intelligence in resource-constrained IoT nodes: Opportunities and challenges
Editor's note: This article provides an academic perspective of the problem, starting with a
survey of recent advances in intelligent sensing, computation, communication, and energy …
survey of recent advances in intelligent sensing, computation, communication, and energy …
An outlier detection algorithm based on cross-correlation analysis for time series dataset
Outlier detection is a very essential problem in a variety of application areas. Many detection
methods are deficient for high-dimensional time series data sets containing both isolated …
methods are deficient for high-dimensional time series data sets containing both isolated …
Lightweight anomaly detection scheme using incremental principal component analysis and support vector machine
Wireless Sensors Networks have been the focus of significant attention from research and
development due to their applications of collecting data from various fields such as smart …
development due to their applications of collecting data from various fields such as smart …