Latest research trends in gait analysis using wearable sensors and machine learning: A systematic review
Gait is the locomotion attained through the movement of limbs and gait analysis examines
the patterns (normal/abnormal) depending on the gait cycle. It contributes to the …
the patterns (normal/abnormal) depending on the gait cycle. It contributes to the …
[HTML][HTML] Groundwater quality forecasting modelling using artificial intelligence: A review
This review paper closely explores the techniques and significances of the most potent
artificial intelligence (AI) approaches in a concise and integrated way, specifically in the …
artificial intelligence (AI) approaches in a concise and integrated way, specifically in the …
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone
Background Cardiovascular diseases kill approximately 17 million people globally every
year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) …
year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) …
A new hybrid grey wolf optimizer-feature weighted-multiple kernel-support vector regression technique to predict TBM performance
Full-face tunnel boring machine (TBM) is a modern and efficient tunnel construction
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …
Automated DDOS attack detection in software defined networking
Abstract Software-Defined Networking (SDN) is a networking paradigm that has redefined
the term network by making the network devices programmable. SDN helps network …
the term network by making the network devices programmable. SDN helps network …
Machine-learning phase prediction of high-entropy alloys
High-entropy alloys (HEAs) have been receiving intensive attention due to their unusual
properties that largely depend on the selection among three phases: solid solution (SS) …
properties that largely depend on the selection among three phases: solid solution (SS) …
Modeling and simulating of reservoir operation using the artificial neural network, support vector regression, deep learning algorithm
D Zhang, J Lin, Q Peng, D Wang, T Yang… - Journal of …, 2018 - Elsevier
Reservoirs and dams are vital human-built infrastructures that play essential roles in flood
control, hydroelectric power generation, water supply, navigation, and other functions. The …
control, hydroelectric power generation, water supply, navigation, and other functions. The …
Machine learning aided Android malware classification
N Milosevic, A Dehghantanha, KKR Choo - Computers & Electrical …, 2017 - Elsevier
The widespread adoption of Android devices and their capability to access significant
private and confidential information have resulted in these devices being targeted by …
private and confidential information have resulted in these devices being targeted by …
Biomass microwave pyrolysis characterization by machine learning for sustainable rural biorefineries
Y Yang, H Shahbeik, A Shafizadeh, N Masoudnia… - Renewable Energy, 2022 - Elsevier
Microwave heating is a promising solution to overcome the shortcomings of conventional
heating in biomass pyrolysis. Nevertheless, biomass microwave pyrolysis is a complex …
heating in biomass pyrolysis. Nevertheless, biomass microwave pyrolysis is a complex …
An efficient and scalable analysis framework for variant extraction and refinement from population-scale DNA sequence data
The analysis of next-generation sequencing data is computationally and statistically
challenging because of the massive volume of data and imperfect data quality. We present …
challenging because of the massive volume of data and imperfect data quality. We present …