AIMC Topic: Algorithms

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A Fast Weighted Fuzzy C-Medoids Clustering for Time Series Data Based on P-Splines.

Sensors (Basel, Switzerland)
The rapid growth of digital information has produced massive amounts of time series data on rich features and most time series data are noisy and contain some outlier samples, which leads to a decline in the clustering effect. To efficiently discover...

Failure Mode Detection and Validation of a Shaft-Bearing System with Common Sensors.

Sensors (Basel, Switzerland)
Failure mode detection is essential for bearing life prediction to protect the shafts on the machinery. This work demonstrates the rolling bearing vibration measurement, signals converting and analysis, feature extraction, and machine learning with n...

On the Problem of State Recognition in Injection Molding Based on Accelerometer Data Sets.

Sensors (Basel, Switzerland)
The last few decades have been characterised by a very active application of smart technologies in various fields of industry. This paper deals with industrial activities, such as injection molding, where it is required to monitor continuously the ma...

An Automated Machine Learning Approach for Real-Time Fault Detection and Diagnosis.

Sensors (Basel, Switzerland)
This work presents a novel Automated Machine Learning (AutoML) approach for Real-Time Fault Detection and Diagnosis (RT-FDD). The approach's particular characteristics are: it uses only data that are commonly available in industrial automation system...

Evaluating Patients' Experiences with Healthcare Services: Extracting Domain and Language-Specific Information from Free-Text Narratives.

International journal of environmental research and public health
Evaluating patients’ experience and satisfaction often calls for analyses of free-text data. Language and domain-specific information extraction can reduce costly manual preprocessing and enable the analysis of extensive collections of experience-bas...

Reducing systematic review burden using Deduklick: a novel, automated, reliable, and explainable deduplication algorithm to foster medical research.

Systematic reviews
BACKGROUND: Identifying and removing reference duplicates when conducting systematic reviews (SRs) remain a major, time-consuming issue for authors who manually check for duplicates using built-in features in citation managers. To address issues rela...

Convolution neural network with batch normalization and inception-residual modules for Android malware classification.

Scientific reports
Deep learning technology is changing the landscape of cybersecurity research, especially the study of large amounts of data. With the rapid growth in the number of malware, developing of an efficient and reliable method for classifying malware has be...

Experimental exploration of a ribozyme neutral network using evolutionary algorithm and deep learning.

Nature communications
A neutral network connects all genotypes with equivalent phenotypes in a fitness landscape and plays an important role in the mutational robustness and evolvability of biomolecules. In contrast to earlier theoretical works, evidence of large neutral ...

Environmental and Geographical (EG) Image Classification Using FLIM and CNN Algorithms.

Contrast media & molecular imaging
Intelligent machines have grown in importance in recent years in object recognition in terms of their ability to envision, comprehend, and reach decisions. There are a lot of complicated algorithms that accomplish AI utilities. In addition to their u...

A CTR prediction model based on session interest.

PloS one
Click-through rate prediction has become a hot research direction in the field of advertising. It is important to build an effective CTR prediction model. However, most existing models ignore the factor that the sequence is composed of sessions, and ...