Search results for "MAI"
showing 10 items of 6279 documents
Deep Learning-Based Real-Time Object Detection in Inland Navigation
2019
International audience; Semi-autonomous and fully-autonomous systems must have knowledge about the objects in their environment to ensure a safe navigation. Modern approaches implement deep learning techniques to train a neural network for object detection. This project will study the effectiveness of using several promising algorithms such as Faster R-CNN, SSD, and different versions of YOLO, to detect, classify, and track objects in near real-time fluvial domain. Since no dataset is available for this purpose in literature, we first started by annotating a dataset of 2488 images with almost 35 400 annotations for training the convolutional neural network architectures. We made this data s…
An introduction to knowledge computing
2014
This paper deals with the challenges related to self-management and evolution of massive knowledge collections. We can assume that a self-managed knowledge graph needs a kind of a hybrid of: an explicit declarative self-knowledge (as knowledge about own properties and capabilities) and an explicit procedural self-knowledge (as knowledge on how to utilize own properties and the capabilities for the self-management).We offer an extension to a traditional RDF model of describing knowledge graphs according to the Semantic Web standards so that it will also allow to a knowledge entity to autonomously perform or query from remote services different computational executions needed. We also introdu…
Multi-level optimization of a fiber transmission system via nonlinearity management
2006
Nonlinearity management is explored as a complete tool to obtain maximum transmission reach in a WDM fiber transmission system, making it possible to optimize multiple system parameters, including optimal dispersion pre-compensation, with fast simulations based on the continuous-wave approximation. © 2006 Optical Society of America.
A spatial algorithm to reduce phase wraps from two dimensional signals in fringe projection profilometry
2016
© 2015 Elsevier Ltd. All rights reserved. In this paper, we present a novel algorithm to reduce the number of phase wraps in two dimensional signals in fringe projection profilometry. The technique operates in the spatial domain, and achieves a significant computational saving with regard to existing methods based on frequency shifting. The method works by estimating the modes of the first differences distribution in each axial direction. These are used to generate a tilted plane, which is subtracted from the entire phase map. Finally, the result is re-wrapped to obtain a phase map with fewer wraps. The method may be able to completely eliminate the phase wraps in many cases, or can achieve…
Architecture and Language for Semantic Reduction of Domain-Specific Models in BPMS
2012
Nowadays each business process management system (BPMS) supports either an industry standard or its own specific modeling language. But no BPMS supports a specific language for each organization. We propose an architecture for building BPMS that allows creating a domain-specific modeling language for every client easily. The main problem is to bridge the gap between the domain-specific language and the executable language. We show that we can look at this problem as a classification of the domain-specific language constructs in the terms of the executable language. To solve this problem we present a novel model transformation language, with which this type of problem can be solved more natu…
A New Venture and a Commitment to Disciplinary Fusion in the Domain of Digital and Public Humanities
2020
First introduction to Magazén
An asynchronous covert channel using spam
2012
AbstractCurrent Internet e-mail facilities are built onto the foundation of standard rules and protocols, which usually allow a considerable amount of “freedom” to their designers. Each of these standards has been defined based on a number of vendor specific implementations, in order to provide common inter-working procedures for cross-vendor communication. Thus, a lot of optional and redundant information is being exchanged during e-mail sessions, which is available to implement versatile covert channel mechanisms.This work exploits this possibility by presenting a simple but effective steganographic scheme that can be used to deploy robust secret communication through spam e-mails. This s…
A risk evaluation framework for the best maintenance strategy: the case of a marine salt manufacture firm
2020
Highlights • This paper proposes a MCDM framework to support risk evaluation for maintenance activities. • The ANP is proposed to select the best maintenance strategy on the basis of real systems’ features. • The ELECTRE III is used to prioritise the main risks related to the interventions of the selected maintenance policy. • The proposed framework is applied to a core subsystem of a real-world marine salt manufacture firm.
Conceptual Differences Among Functional Size Measurement Methods
2007
The paper focuses on measuring and assessing the relation of adaptive maintenance process and quality of open source software (OSS). A framework for assessing adaptive maintenance process is proposed and applied. The framework consists of six sub- processes. Five OSSs with considerable number of releases have been studied empirically. Their main evolutionary and quality characteristics have been measured. The main results of the study are the following:. 1) Software maintainability is affected mostly by the activities of the 'analysis' maintenance sub-process. 2) Software testability is affected by the activities of all maintenance sub-processes. 3) Software reliability is affected mostly b…
Toward morphological thoracic EIT: major signal sources correspond to respective organ locations in CT.
2012
Lung and cardiovascular monitoring applications of electrical impedance tomography (EIT) require localization of relevant functional structures or organs of interest within the reconstructed images. We describe an algorithm for automatic detection of heart and lung regions in a time series of EIT images. Using EIT reconstruction based on anatomical models, candidate regions are identified in the frequency domain and image-based classification techniques applied. The algorithm was validated on a set of simultaneously recorded EIT and CT data in pigs. In all cases, identified regions in EIT images corresponded to those manually segmented in the matched CT image. Results demonstrate the abilit…