Search results for "computer.software_genre"
showing 10 items of 3858 documents
Blockchain Based Delegatable Access Control Scheme for a Collaborative E-Health Environment
2018
Modern electronic healthcare (e-health) settings constitute collaborative environments requiring sophisticated fine-grained access control mechanisms to cater their access demands. Access delegatability is quite crucial to realize fine-grained, flexible access control schemes compatible with such environments. In this paper, we addressed this issue through proposing an attribute based access control scheme integrated with controlled access delegation capabilities suitable for a multi-domain e-health environment. We have utilized the blockchain technology to manage attribute assignments, delegations as well as revocations. The scheme enables delegations in a controlled manner without jeopard…
Indexing Multimedia Learning Materials in Ultimate Course Search
2016
International audience; Multimedia is the main support for online learning materials and the size of multimedia learning materials is growing with the popularity of online programs offered by Universities. Ultimate Course Search (UCS) is a tool that aims to provide efficient search of course materials. UCS integrates slides, lecture videos and textbook content into a single platform with search capabilities. The keywords extracted from the textbook index and the power-point slides are the basis of the indexing scheme. The slides are indexed on the keywords and the videos are indexed on the slides. The correspondence between the slides and video segments is established using the meta-data pr…
Modelling Dependencies Between Classifiers in Mobile Masquerader Detection
2004
The unauthorised use of mobile terminals may result in an abuse of sensitive information kept locally on the terminals or accessible over the network. Therefore, there is a need for security means capable of detecting the cases when the legitimate user of the terminal is substituted. The problem of user substitution detection is considered in the paper as a problem of classifying the behaviour of the person interacting with the terminal as originating from the user or someone else. Different aspects of behaviour are analysed by designated one-class classifiers whose classifications are subsequently combined. A modification of majority voting that takes into account some of the dependencies …
A Learning Automata Local Contribution Sampling Applied to Hydropower Production Optimisation
2017
Learning Automata (LA) is a powerful approach for solving complex, non-linear and stochastic optimisation problems. However, existing solutions struggle with high-dimensional problems due to slow convergence, arguably caused by the global nature of feedback. In this paper we introduce a novel Learning Automata (LA) scheme to attack this challenge. The scheme is based on a parallel form of Local Contribution Sampling (LCS), which means that the LA receive individually directed feedback, designed to speed up convergence. Furthermore, our scheme is highly decentralized, allowing parallel execution on GPU architectures. To demonstrate the power of our scheme, the LA LCS is applied to hydropower…
A Forecasting Support System Based on Exponential Smoothing
2010
This chapter presents a forecasting support system based on the exponential smoothing scheme to forecast time-series data. Exponential smoothing methods are simple to apply, which facilitates computation and considerably reduces data storage requirements. Consequently, they are widely used as forecasting techniques in inventory systems and business planning. After selecting the most adequate model to replicate patterns of the time series under study, the system provides accurate forecasts which can play decisive roles in organizational planning, budgeting and performance monitoring.
A symbolic distributed event detection scheme for Wireless Sensor Networks
2016
Due to the possibility of extensive and pervasive deployment of many tiny sensor devices in the area of interest, Wireless Sensor Networks (WSNs) result particularly suitable to detect significant events and to react accordingly in industrial and home scenarios. In this context, fuzzy inference systems for event detection in WSNs have proved to be accurate enough in treating imprecise sensory readings to decrease the number of false alarms. Besides reacting to event occurrences, the whole network may infer more information to enrich the event semantics resulting from reasoning processes carried out on the individual nodes. Contextual knowledge, including spatial and temporal relationships, …
A Neural Network model for the Evaluation of Text Complexity in Italian Language: a Representation Point of View
2018
Abstract The goal of a text simplification system (TS) is to create a new text suited to the characteristics of a reader, with the final goal of making it more understandable.The building of an Automatic Text Simplification System (ATS) cannot be separated from a correct evaluation of the text complexity. In fact the ATS must be capable of understanding if a text should be simplified for the target reader or not. In a previous work we have presented a model capable of classifying Italian sentences based on their complexity level. Our model is a Long Short Term Memory (LSTM) Neural Network capable of learning the features of easy-to-read and complex-to-read sentences autonomously from a anno…
Multi-pass execution of functional logic programs
1994
An operational semantics for functional logic programs is presented. In such programs functional terms provide for reduction of expressions, provided that they ground. The semantics is based on multi-pass evaluation techniques originally developed for attribute grammars. Program execution is divided into two phases: (1) construction of an incomplete proof tree, and (2) its decoration into a complete proof tree. The construction phase applies a modified SLD-resolution scheme, and the decoration phase a partial (multi-pass) traversal over the tree. The phase partition is generated by static analysis where data dependencies are extracted for the functional elements of the program. The method g…
Toward Self-Supervised Feature Learning for Online Diagnosis of Multiple Faults in Electric Powertrains
2021
This article proposes a novel online fault diagnosis scheme for industrial powertrains without using historical faulty or labeled training data. The proposed method combines a one-class support vector machine (SVM) based anomaly detection and supervised convolutional neural network (CNN) algorithms to online detect multiple faults and fault severities under variable speeds and loads. The one-class SVM algorithm is to derive a score for defining faults or health classes in the first stage, and the resulting health classes are used as the training data for the CNN-based classifier in the second stage. Within this framework, the self-supervised learning of the proposed CNN algorithm allows the…
An attribute based access control scheme for secure sharing of electronic health records
2016
Electronic health records (EHRs) play a vital role in modern health industry, allowing the possibility of flexible sharing of health information in the quest of provisioning advanced and efficient healthcare services for the users. Although sharing of EHRs has significant benefits, given that such records contain lot of sensitive information, secure sharing of EHRs is of paramount importance. Thus, there is a need for the realization of sophisticated access control mechanisms for secure sharing of EHRs, which has attracted significant interest from the research community. The most prominent access control schemes for sharing of EHRs found in literature are role based and such solutions have…