AIMC Topic: Reproducibility of Results

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Improving Recognition of Overlapping Activities with Less Interclass Variations in Smart Homes through Clustering-Based Classification.

Computational intelligence and neuroscience
The systems of sensing technology along with machine learning techniques provide a robust solution in a smart home due to which health monitoring, elderly care, and independent living take advantage. This study addresses the overlapping problem in ac...

Voice-Assisted Image Labeling for Endoscopic Ultrasound Classification Using Neural Networks.

IEEE transactions on medical imaging
Ultrasound imaging is a commonly used technology for visualising patient anatomy in real-time during diagnostic and therapeutic procedures. High operator dependency and low reproducibility make ultrasound imaging and interpretation challenging with a...

Deep Learning for Joint Pilot Design and Channel Estimation in MIMO-OFDM Systems.

Sensors (Basel, Switzerland)
In MIMO-OFDM systems, pilot design and estimation algorithm jointly determine the reliability and effectiveness of pilot-based channel estimation methods. In order to improve the channel estimation accuracy with less pilot overhead, a deep learning s...

A Review on Technologies for Localisation and Navigation in Autonomous Railway Maintenance Systems.

Sensors (Basel, Switzerland)
Smart maintenance is essential to achieving a safe and reliable railway, but traditional maintenance deployment is costly and heavily human-involved. Ineffective job execution or failure in preventive maintenance can lead to railway service disruptio...

Predicting clinical trial outcomes using drug bioactivities through graph database integration and machine learning.

Chemical biology & drug design
The ability to estimate the probability of a drug to receive approval in clinical trials provides natural advantages to optimizing pharmaceutical research workflows. Success rates of clinical trials have deep implications for costs, duration of devel...

Unsupervised Domain Adaptive 1D-CNN for Fault Diagnosis of Bearing.

Sensors (Basel, Switzerland)
Fault diagnosis (FD) plays a vital role in building a smart factory regarding system reliability improvement and cost reduction. Recent deep learning-based methods have been applied for FD and have obtained excellent performance. However, most of the...

Breath odor-based individual authentication by an artificial olfactory sensor system and machine learning.

Chemical communications (Cambridge, England)
Breath odor sensing-based individual authentication was conducted for the first time using an artificial olfactory sensor system. Using a 16-channel chemiresistive sensor array and machine learning, a mean accuracy of >97% was successfully achieved. ...

An Optimization Model for Appraising Intrusion-Detection Systems for Network Security Communications: Applications, Challenges, and Solutions.

Sensors (Basel, Switzerland)
Cyber-attacks are getting increasingly complex, and as a result, the functional concerns of intrusion-detection systems (IDSs) are becoming increasingly difficult to resolve. The credibility of security services, such as privacy preservation, authent...

Role of artificial intelligence in MS clinical practice.

NeuroImage. Clinical
Machine learning (ML) and its subset, deep learning (DL), are branches of artificial intelligence (AI) showing promising findings in the medical field, especially when applied to imaging data. Given the substantial role of MRI in the diagnosis and ma...

Determination of parabens in wastewater samples via robot-assisted dynamic single-drop microextraction and liquid chromatography-tandem mass spectrometry.

Electrophoresis
Dynamic single-drop microextraction (SDME) was automatized employing an Arduino-based lab-made Cartesian robot and implemented to determine parabens in wastewater samples in combination with liquid chromatography-tandem mass spectrometry. A dedicated...