Search results for "computer.software_genre"
showing 10 items of 3858 documents
Epistemic uncertainty in fault tree analysis approached by the evidence theory
2012
Abstract Process plants may be subjected to dangerous events. Different methodologies are nowadays employed to identify failure events, that can lead to severe accidents, and to assess the relative probability of occurrence. As for rare events reliability data are generally poor, leading to a partial or incomplete knowledge of the process, the classical probabilistic approach can not be successfully used. Such an uncertainty, called epistemic uncertainty, can be treated by means of different methodologies, alternative to the probabilistic one. In this work, the Evidence Theory or Dempster–Shafer theory (DST) is proposed to deal with this kind of uncertainty. In particular, the classical Fau…
TREEZZY2, a Fuzzy Logic Computer Code for Fault Tree and Event Tree Analyses
2004
In conventional approach to reliability analysis using logical trees methodologies, uncertainties in system components or basic events failure probabilities are approached by assuming probability distribution functions. However, data are often insufficient for statistical estimation, and therefore it is required to resort to approximate estimations. Moreover, complicate calculations are needed to propagate uncertainties up to the final results. In our work, in order to take account of the uncertainties in system failure probabilities, the methodology based on fuzzy sets theory is used both in fault tree and event tree analyses. This paper just presents our work in this issue, which resulted…
PESI - a taxonomic backbone for Europe
2015
Reliable taxonomy underpins communication in all of biology, not least nature conservation and sustainable use of ecosystem resources. The flexibility of taxonomic interpretations, however, presents a serious challenge for end-users of taxonomic concepts. Users need standardised and continuously harmonised taxonomic reference systems, as well as highquality and complete taxonomic data sets, but these are generally lacking for nonspecialists. The solution is in dynamic, expertly curated web-based taxonomic tools. The Pan-European Species-directories Infrastructure (PESI) worked to solve this key issue by providing a taxonomic e-infrastructure for Europe. It strengthened the relevant social (…
Effective feature descriptor-based new framework for off-line text-independent writer identification
2018
Feature engineering is a key factor of machine learning applications. It is a fundamental process in writer identification of handwriting, which is an active and challenging field of research for many years. We propose a conceptually computationally efficient, yet simple and fast local descriptor referred to as Block Wise Local Binary Count (BW-LBC) for offline text-independent writer identification of handwritten documents. Proposed BW-LBC operator, which characterizes the writing style of each writer, is applied to a set of connected components extracted and cropped from scanned handwriting samples (documents or set of words/text lines) where each labeled component is seen as a texture im…
Toward Optimal LSTM Neural Networks for Detecting Algorithmically Generated Domain Names
2021
Malware detection is a problem that has become particularly challenging over the last decade. A common strategy for detecting malware is to scan network traffic for malicious connections between infected devices and their command and control (C&C) servers. However, malware developers are aware of this detection method and begin to incorporate new strategies to go unnoticed. In particular, they generate domain names instead of using static Internet Protocol addresses or regular domain names pointing to their C&C servers. By using a domain generation algorithm, the effectiveness of the blacklisting of domains is reduced, as the large number of domain names that must be blocked g…
Automatic Content Analysis of Computer-Supported Collaborative Inquiry-Based Learning Using Deep Networks and Attention Mechanisms
2020
Computer-supported collaborative inquiry-based learning (CSCIL) represents a form of active learning in which students jointly pose questions and investigate them in technology-enhanced settings. Scaffolds can enhance CSCIL processes so that students can complete more challenging problems than they could without scaffolds. Scaffolding CSCIL, however, would optimally adapt to the needs of a specific context, group, and stage of the group's learning process. In CSCIL, the stage of the learning process can be characterized by the inquiry-based learning (IBL) phase (orientation, conceptualization, investigation, conclusion, and discussion). In this presentation, we illustrate the potential of a…
CitySearcher: A City Search Engine For Interests
2017
We introduce CitySearcher, a vertical search engine that searches for cities when queried for an interest. Generally in search engines, utilization of semantics between words is favorable for performance improvement. Even though ambiguous query words have multiple semantic meanings, search engines can return diversified results to satisfy different users' information needs. But for CitySearcher, mismatched semantic relationships can lead to extremely unsatisfactory results. For example, the city Sale would incorrectly rank high for the interest shopping because of semantic interpretations of the words. Thus in our system, the main challenge is to eliminate the mismatched semantic relationsh…
Combining feature extraction and expansion to improve classification based similarity learning
2017
Abstract Metric learning has been shown to outperform standard classification based similarity learning in a number of different contexts. In this paper, we show that the performance of classification similarity learning strongly depends on the data format used to learn the model. We then present an Enriched Classification Similarity Learning method that follows a hybrid approach that combines both feature extraction and feature expansion. In particular, we propose a data transformation and the use of a set of standard distances to supplement the information provided by the feature vectors of the training samples. The method is compared to state-of-the-art feature extraction and metric lear…
The FBN2 gene: new mutations, locus-specific database (Universal Mutation Database FBN2), and genotype-phenotype correlations.
2009
International audience; Congenital contractural arachnodactyly (CCA) is an extremely rare disease, due to mutations in the FBN2 gene encoding fibrillin-2. Another member of the fibrillin family, the FBN1 gene, is involved in a broad phenotypic continuum of connective-tissue disorders including Marfan syndrome. Identifying not only what is in common but also what differentiates these two proteins should enable us to better comprehend their respective functions and better understand the multitude of diseases in which these two genes are involved. In 1995 we created a locus-specific database (LSDB) for FBN1 mutations with the Universal Mutation Database (UMD) tool. To facilitate comparison of …
Web-based real-time data acquisition system as tool for energy efficiency monitoring
2013
A web-based data acquisition system is proposed as a research tool of the energy efficiency monitoring project of the test stands. Basic requirements for the architecture of the data acquisition system are discussed. The architecture of the data acquisition system is proposed to provide the real-time interface with sensors, to acquire and to log data from all sensors with fixed rate, and to deliver logged data through FTP to the end-user.