Search results for "computer.software_genre"
showing 10 items of 3858 documents
A Short Presentation of LucSim
2017
LucSim is a cellular automata (CA) dedicated to geographical analysis and spatial simulation for researchers and advanced planning institutes, providing user-friendly software in order to analyze and simulate land use changes and dynamics. Two complementary models are integrated in the CA: (1) a Markov Chain used to calculate transition matrices from a date to another, and (2) a Decision Tree able to automatically determine a set of transition rules to be applied on land use data. LucSim includes GIS compatibility functions allowing to display ESRI shapefiles and is based on raster georeferenced images saved in TIF format. It was mostly applied on French urban case studies.
A Novel Method to Characterize User Sessions of Educational Software
2013
Abstract Software applications destined for the educational environment have a long history and have evolved side by side with the progress of technology from simple computer assisted instruction programs to sophisticated eLearning platforms. A study that we have conducted on a sample of 395 children aged 6 through 12, coming from both the rural and the urban environments, shows that an increasing number of children use computer related technologies. Given their exposure to these technologies it is imperative that the educational applications be designed in a way that takes into account the children's abilities, interests and the demands for their development. We have proposed a 5-dimension…
Enforcing mobile security with location-aware role-based access control
2013
This paper describes how location-aware role-based access control RBAC can be implemented on top of the Geospatial eXtensible Access Control Markup Language GeoXACML. It furthermore sketches how spatial separation of duty constraints both static and dynamic can be implemented using GeoXACML on top of the XACML RBAC profile. The solution uses physical addressing of geographical locations, which facilitates easy deployment of authorisation profiles to the mobile device. Location-aware RBAC can be used to implement location-dependent access control and also other security enhancing solutions on mobile devices, such as location-dependent device locking, firewall, intrusion prevention or payment…
A Scratch-based Graphical Policy Editor for XACML
2015
This paper proposes a policy-maker-friendly editor for the extensible Access Control Markup Language (XACML) based on the programming language Scratch. Scratch is a blocks-based programming language designed for teaching children programming, which allows users to build programs like a puzzle. We take this concept one step further with an XACML policy editor based on the graphic programming elements of Scratch implemented in Smalltalk. This allows for aiding the user on how to build policies by grouping blocks and operators that fit together and also indicating which blocks that will stick together. It simplifies building the XACML policies while still having an XACML “feel” of the graphic …
Improving Isolation of Blindly Separated Sources Using Time-Frequency Masking
2008
A refinement technique based on time-frequency masking is proposed to improve source isolation in blind audio source separation algorithms. The refinement technique uses an energy-normalized source-to-interference ratio in order to identify and eliminate interfering energy from the extracted sources. Some examples using this refinement method with different separation algorithms are discussed. The results show that source isolation can be significantly enhanced with negligible degradation of the separated sources.
Contrastive Learning with Continuous Proxy Meta-data for 3D MRI Classification
2021
Traditional supervised learning with deep neural networks requires a tremendous amount of labelled data to converge to a good solution. For 3D medical images, it is often impractical to build a large homogeneous annotated dataset for a specific pathology. Self-supervised methods offer a new way to learn a representation of the images in an unsupervised manner with a neural network. In particular, contrastive learning has shown great promises by (almost) matching the performance of fully-supervised CNN on vision tasks. Nonetheless, this method does not take advantage of available meta-data, such as participant’s age, viewed as prior knowledge. Here, we propose to leverage continuous proxy me…
Which Is Which? Evaluation of Local Descriptors for Image Matching in Real-World Scenarios
2019
Matching with local image descriptors is a fundamental task in many computer vision applications. This paper describes the WISW contest held within the framework of the CAIP 2019 conference, aimed at benchmarking recent descriptors in challenging planar and non-planar real image matching scenarios. According to the contest results, the descriptors submitted to the competition, most of which based on deep learning, perform significantly better than the current state-of-the-art in image matching. Nonetheless, there is still room for improvement, especially in the case of non-planar scenes.
Locality-Sensitive Hashing for Massive String-Based Ontology Matching
2014
This paper reports initial research results related to the use of locality-sensitive hashing (LSH) for string-based matching of big ontologies. Two ways of transforming the matching problem into a LSH problem are proposed and experimental results are reported. The performed experiments show that using LSH for ontology matching could lead to a very fast matching process. The quality of the alignment achieved in these experiments is comparable to state-of-the-art matchers, but much faster. Further research is needed to find out whether the use of different metrics or specific hardware would improve the results. peerReviewed
What is the validity of the sorting task for describing beers? A study using trained and untrained assessors
2008
In the sensory evaluation literature, it has been suggested that sorting tasks followed by a description of the groups of products can be used by consumers to describe products, but a closer look at this literature suggests that this claim needs to be evaluated. In this paper, we proposed to examine the validity of the sorting task to describe products by trained and untrained assessors. The experiment reported here consisted in two parts. In a first part, participants sorted nine commercial beers and then described each group with their own words or with a list of terms. In a second part, participants were asked to match each beer with one of their own sets of descriptors. The matching tas…
Do trained assessors generalize their knowledge to new stimuli?
2005
Previous work showed that trained assessors are better at discriminating and describing familiar chemico-sensorial stimuli than novices. In this study, we evaluated whether this superiority holds true for new stimuli. We first trained a group of subjects to characterize beer flavors over a two year period. After training was accomplished, we compared the performance of these trained assessors with the performance of novice subjects for discrimination and matching tasks. The tasks were performed using both well-learned and new beers. Trained assessors outperformed novices in the discrimination task for learned beers but not for new beers. But on the matching task, trained assessors outperfor…