AIMC Topic: Algorithms

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Detection of Middlebox-Based Attacks in Healthcare Internet of Things Using Multiple Machine Learning Models.

Computational intelligence and neuroscience
The huge number of network traffic data, the abundance of available network features, and the diversity of cyber-attack patterns mean that intrusion detection remains difficult even though many earlier efforts have succeeded in building the Internet ...

A stochastic numerical approach for a class of singular singularly perturbed system.

PloS one
In the present study, a neuro-evolutionary scheme is presented for solving a class of singular singularly perturbed boundary value problems (SSP-BVPs) by manipulating the strength of feed-forward artificial neural networks (ANNs), global search parti...

On Detecting Cryptojacking on Websites: Revisiting the Use of Classifiers.

Sensors (Basel, Switzerland)
Cryptojacking or illegal mining is a form of malware that hides in the victim's computer and takes the computational resources to extract cryptocurrencies in favor of the attacker. It generates significant computational consumption, reducing the comp...

Regressing Image Sub-Population Distributions with Deep Learning.

Sensors (Basel, Switzerland)
Regressing the distribution of different sub-populations from a batch of images with learning algorithms is not a trivial task, as models tend to make errors that are unequally distributed across the different sub-populations. Obviously, the baseline...

A Sampling-Based Algorithm with the Metropolis Acceptance Criterion for Robot Motion Planning.

Sensors (Basel, Switzerland)
Motion planning is one of the important research topics of robotics. As an improvement of Rapidly exploring Random Tree (RRT), the RRT* motion planning algorithm is widely used because of its asymptotic optimality. However, the running time of RRT* i...

Classification of Normal and Malicious Traffic Based on an Ensemble of Machine Learning for a Vehicle CAN-Network.

Sensors (Basel, Switzerland)
Connectivity and automation have expanded with the development of autonomous vehicle technology. One of several automotive serial protocols that can be used in a wide range of vehicles is the controller area network (CAN). The growing functionality a...

CNN and SVM-Based Models for the Detection of Heart Failure Using Electrocardiogram Signals.

Sensors (Basel, Switzerland)
Heart failure (HF) is a serious condition in which the heart fails to supply the body with enough oxygen and nutrients to function normally. Early and accurate detection of heart failure is critical for impeding disease progression. An electrocardiog...

Setting up of a machine learning algorithm for the identification of severe liver fibrosis profile in the general US population cohort.

International journal of medical informatics
BACKGROUND: The progress of digital transformation in clinical practice opens the door to transforming the current clinical line for liver disease diagnosis from a late-stage diagnosis approach to an early-stage based one. Early diagnosis of liver fi...

Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models.

Journal of clinical epidemiology
BACKGROUND AND OBJECTIVES: We sought to summarize the study design, modelling strategies, and performance measures reported in studies on clinical prediction models developed using machine learning techniques.

Machine Learning Models for Slope Stability Classification of Circular Mode Failure: An Updated Database and Automated Machine Learning (AutoML) Approach.

Sensors (Basel, Switzerland)
Slope failures lead to large casualties and catastrophic societal and economic consequences, thus potentially threatening access to sustainable development. Slope stability assessment, offering potential long-term benefits for sustainable development...