AIMC Topic: Machine Learning

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Best of Both Worlds: Detecting Application Layer Attacks through 802.11 and Non-802.11 Features.

Sensors (Basel, Switzerland)
Intrusion detection in wireless and, more specifically, Wi-Fi networks is lately increasingly under the spotlight of the research community. However, the literature currently lacks a comprehensive assessment of the potential to detect application lay...

Application of machine learning for inter turn fault detection in pumping system.

Scientific reports
Pump fault diagnosis is essential for the maintenance and safety of the device as it is an important appliance used in various major sectors. Fault diagnosis at the proper time can reduce maintenance costs and save energy. This article uses a Simulin...

Prediction algorithm for ICU mortality and length of stay using machine learning.

Scientific reports
Machine learning can predict outcomes and determine variables contributing to precise prediction, and can thus classify patients with different risk factors of outcomes. This study aimed to investigate the predictive accuracy for mortality and length...

Machine learning-assisted prediction of pneumonia based on non-invasive measures.

Frontiers in public health
BACKGROUND: Pneumonia is an infection of the lungs that is characterized by high morbidity and mortality. The use of machine learning systems to detect respiratory diseases non-invasive measures such as physical and laboratory parameters is gaining ...

An empirical evaluation of sampling methods for the classification of imbalanced data.

PloS one
In numerous classification problems, class distribution is not balanced. For example, positive examples are rare in the fields of disease diagnosis and credit card fraud detection. General machine learning methods are known to be suboptimal for such ...

Machine learning and features for the prediction of thermal sensation and comfort using data from field surveys in Cyprus.

International journal of biometeorology
Perception can influence individuals' behaviour and attitude affecting responses and compliance to precautionary measures. This study aims to investigate the performance of methods for thermal sensation and comfort prediction. Four machine learning a...

Unsupervised and semi-supervised learning: the next frontier in machine learning for plant systems biology.

The Plant journal : for cell and molecular biology
Advances in high-throughput omics technologies are leading plant biology research into the era of big data. Machine learning (ML) performs an important role in plant systems biology because of its excellent performance and wide application in the ana...

Improving Network-Based Anomaly Detection in Smart Home Environment.

Sensors (Basel, Switzerland)
The Smart Home (SH) has become an appealing target of cyberattacks. Due to the limitation of hardware resources and the various operating systems (OS) of current SH devices, existing security features cannot protect such an environment. Generally, th...

Classification and Detection of Mesothelioma Cancer Using Feature Selection-Enabled Machine Learning Technique.

BioMed research international
Cancer of the mesothelium, sometimes referred to as malignant mesothelioma (MM), is an extremely uncommon form of the illness that almost always results in death. Chemotherapy, surgery, radiation therapy, and immunotherapy are all potential treatment...

Application of deep machine learning for the radiographic diagnosis of periodontitis.

Clinical oral investigations
OBJECTIVE: Successful application of deep machine learning could reduce time-consuming and labor-intensive clinical work of calculating the amount of radiographic bone loss (RBL) in diagnosing and treatment planning for periodontitis. This study aime...