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Deep learning models are often unaware of the inherent constraints of the task they are applied to. However, many downstream tasks require logical consistency. For ontology classification tasks, such constraints include subsumption and…
In this era of advanced manufacturing, it's now more crucial than ever to diagnose machine faults as early as possible to guarantee their safe and efficient operation. With the massive surge in industrial big data and advancement in sensing…
The fuzzy vault is an error tolerant authentication method that ensures the privacy of the stored reference data. Several publications have proposed the application of the fuzzy vault to fingerprints, but the results of subsequent analyses…
Tracking control for soft robots is challenging due to uncertainties in the system model and environment. Using high feedback gains to overcome this issue results in an increasing stiffness that clearly destroys the inherent safety property…
A multi-modal machine learning system uses multiple unique data sources and types to improve its performance. This article proposes a system that combines results from several types of models, all of which are trained on different data…
In order to properly train a machine learning model, data must be properly collected. To guarantee a proper data collection, verifying that the collected data set holds certain properties is a possible solution. For example, guaranteeing…
The modeling and analysis of degradation data have been an active research area in reliability and system health management. As the senor technology advances, multivariate sensory data are commonly collected for the underlying degradation…
Machine learning has emerged as a significant approach to efficiently tackle electronic structure problems. Despite its potential, there is less guarantee for the model to generalize to unseen data that hinders its application in real-world…
Wireless sensor networks suffer from false report injection attacks. This results in energy drain over sensor nodes on the event traversal route. Novel en-route filtering schemes counter this problem by filtering these attacks on designated…
Rapid growth of machine learning methodologies and their applications offer new opportunity for improved transformer asset management. Accordingly, power system operators are currently looking for data-driven methods to make better-informed…
Today manufacturers are using fuzzy logic in everything from cameras to industrial process control. Fuzzy logic controllers are easier to design and so are cheaper to produce. Fuzzy logic captures the impreciseness inherent in most input…
Fuzzy rule-based model is a powerful tool for imitating the human way of thinking and solving uncertainty-related problems as it allows for understandable and interpretable rule bases. The objective of this paper is to study the…
In the context of Industry 4.0, effective monitoring of multiple targets and states during assembly processes is crucial, particularly when constrained to using only visual sensors. Traditional methods often rely on either multiple sensor…
Detection of anomalous behaviors in data centers is crucial to predictive maintenance and data safety. With data centers, we mean any computer network that allows users to transmit and exchange data and information. In particular, we focus…
Accurately estimating risk in real-time is essential for ensuring the safety and efficiency of many applications involving autonomous robot systems. This paper presents a novel, generalizable algorithm for the real-time estimation of risks…
Along with the miniaturization of various types of sensors, a mass of intelligent terminals are gaining stronger sensing capability, which raises a deeper perception and better prospect of Internet of Things (IoT). With big sensing data,…
Insitu sensors and Wireless Sensor Networks (WSNs) have become more and more popular in the last decade, due to their potential to be used in various applications of many different fields. As of today, WSNs are pretty much used by any…
Fuzzy Rule Interpolation (FRI) methods can serve deducible (interpolated) conclusions even in case if some situations are not explicitly defined in a fuzzy rule based knowledge representation. This property can be beneficial in partial…
Data gathered from multiple sensors can be effectively fused for accurate monitoring of many engineering applications. In the last few years, one of the most sought after applications for multi sensor fusion has been fault diagnosis.…
Autonomous robots that assist humans in day to day living tasks are becoming increasingly popular. Autonomous mobile robots operate by sensing and perceiving their surrounding environment to make accurate driving decisions. A combination of…