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In this article, we consider the problem of privacy-preserving distributed deep learning where data privacy is protected by fully homomorphic encryption. The aim is to develop a method for practical and scalable distributed deep learning with fully ...

As a result of the continuously growing volume of information available, browsing and querying of textual information in search of specific facts is currently a tedious task exacerbated by a reality where data presentation very often does not meet ...

Artificial intelligence (AI) is a crucial technology of industrial digitalization. Especially in the production industry, a great potential is present in optimizing existing processes, e.g., concerning resource consumption, emission reduction, ...

In the industrial domain, developing solutions that allow the identification, understanding, and correction of faults is essential due to the cost of handling such situations. However, to date, there are not many solutions capable of facilitating ...

This article presents an explainable fuzzy theoretic nonparametric deep model for an analysis of heart rate variability in application to stress assessment. We are concerned with the development of a model that evaluates and explains a short-time (3&#...

This paper introduces a variational analysis approach to the learning of a deep model formed via a nested composition of mappings. The fuzzy sets, being characterized by Gaussian type of membership functions, are used to represent ...

In various industrial production environments a burn-in phase of a specific settling-length precedes a stable (i.e. steady-state, stationary) process mode. The identification of the corresponding physical parameters may be difficult to perform in ...

The application of fuzzy theory to deep learning is limited, 1) under the realm of deep neural networks, 2) to the parametric form of modeling, and 3) relying on gradient-descent-based numerical algorithms for optimization because of lack of analytical ...

This study presents an optimal differential privacy framework for learning of distributed deep models. The deep models, consisting of a nested composition of mappings, are learned analytically in a private setting using variational optimization ...

The problem that we address here is given n job seekers and n job offers, where each job seeker has ranked all job offers in order of preference given by a suitability function, and vice versa; the goal is to compute the minimum set of skills to be ...

Nowadays, the volume of legal information available is continuously growing. As a result, browsing and querying this huge legal corpus in search of specific information is currently a tedious task exacerbated by the fact that data presentation ...

For years, the amount of data generated in many industrial production plants has been said to have great potential for improving maintenance processes. In order to leverage this potential in practice, however, it is necessary to overcome a number ...

The current paper describes our research towards a cloud infrastructure for the universal access and interaction with a number of services implementing methods for enriching, matching and querying information about job offers and applicant profiles in ...

Automatically providing suggestions for predicting the likely status of a mechanical component is a key challenge in a wide variety of industrial domains. Existing solutions based on ontological models have proven to be appropriate for fault diagnosis, ...

This book provides the most complete formal specification of the semantics of the Business Process Model and Notation 2.0 standard (BPMN) available to date, in a style that is easily understandable for a wide range of readers not only for experts in ...

This book presents a proposal for designing business process management (BPM) systems that comprise much more than just process modelling. Based on a purified Business Process Model and Notation (BPMN) variant, the authors present proposals for several ...

Due to the high costs of real-time experiments, performance simulation has become a widely accepted method of assessment for the quality of proposed solutions in the field of energy saving. Additionally, being able to simulate the behavior of the future ...

This book provides the most complete formal specification of the semantics of the Business Process Model and Notation 2.0 standard (BPMN) available to date, in a style that is easily understandable for a wide range of readers not only for experts in ...

Reducing energy consumption in buildings of all kinds is a key challenge for researchers since it can help to notably reduce the waste of energy and its associated costs. However, when dealing with residential environments, there is a major problem, ...

Assessing the reliability of industrial machinery is an important aspect within maintenance processes in order to maximize productivity and efficiency. In this paper we propose to use graphical models for fault detection in industrial machinery within a ...