Advancing biosensors with machine learning
Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis.
Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved …
Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved …
A review of clustering techniques and developments
This paper presents a comprehensive study on clustering: exiting methods and
developments made at various times. Clustering is defined as an unsupervised learning …
developments made at various times. Clustering is defined as an unsupervised learning …
Random forest bagging and x‐means clustered antipattern detection from SQL query log for accessing secure mobile data
RK Dhanaraj, V Ramakrishnan… - Wireless …, 2021 - Wiley Online Library
In the current ongoing crisis, people mostly rely on mobile phones for all the activities, but
query analysis and mobile data security are major issues. Several research works have …
query analysis and mobile data security are major issues. Several research works have …
COVID-SAFE: An IoT-based system for automated health monitoring and surveillance in post-pandemic life
In the early months of the COVID-19 pandemic with no designated cure or vaccine, the only
way to break the infection chain is self-isolation and maintaining the physical distancing. In …
way to break the infection chain is self-isolation and maintaining the physical distancing. In …
An ensemble intrusion detection technique based on proposed statistical flow features for protecting network traffic of internet of things
N Moustafa, B Turnbull… - IEEE Internet of Things …, 2018 - ieeexplore.ieee.org
Internet of Things (IoT) plays an increasingly significant role in our daily activities,
connecting physical objects around us into digital services. In other words, IoT is the driving …
connecting physical objects around us into digital services. In other words, IoT is the driving …
A deep learning method with wrapper based feature extraction for wireless intrusion detection system
SM Kasongo, Y Sun - Computers & Security, 2020 - Elsevier
In the past decade, wired and wireless computer networks have substantially evolved
because of the rapid development of technologies such as the Internet of Things (IoT) …
because of the rapid development of technologies such as the Internet of Things (IoT) …
Modeling flood susceptibility using data-driven approaches of naïve bayes tree, alternating decision tree, and random forest methods
Floods are one of the most devastating types of disasters that cause loss of lives and
property worldwide each year. This study aimed to evaluate and compare the prediction …
property worldwide each year. This study aimed to evaluate and compare the prediction …
Self-weighted robust LDA for multiclass classification with edge classes
Linear discriminant analysis (LDA) is a popular technique to learn the most discriminative
features for multi-class classification. A vast majority of existing LDA algorithms are prone to …
features for multi-class classification. A vast majority of existing LDA algorithms are prone to …
An ai‐based prediction model for drug‐drug interactions in osteoporosis and Paget's diseases from smiles
The skeleton is one of the most important organs in the human body in assisting our motion
and activities; however, bone density attenuates gradually as we age. Among common bone …
and activities; however, bone density attenuates gradually as we age. Among common bone …
Combogan: Unrestrained scalability for image domain translation
The past year alone has seen unprecedented leaps in the area of learning-based image
translation, namely CycleGAN, by Zhu et al. But experiments so far have been tailored to …
translation, namely CycleGAN, by Zhu et al. But experiments so far have been tailored to …