Search results for "UML"
showing 10 items of 407 documents
Risk assessment of component failure modes and human errors using a new FMECA approach: application in the safety analysis of HDR brachytherapy
2014
Failure mode, effects and criticality analysis (FMECA) is a safety technique extensively used in many different industrial fields to identify and prevent potential failures. In the application of traditional FMECA, the risk priority number (RPN) is determined to rank the failure modes; however, the method has been criticised for having several weaknesses. Moreover, it is unable to adequately deal with human errors or negligence. In this paper, a new versatile fuzzy rule-based assessment model is proposed to evaluate the RPN index to rank both component failure and human error. The proposed methodology is applied to potential radiological over-exposure of patients during high-dose-rate brach…
FADaC
2019
Solid state drives (SSDs) implement a log-structured write pattern, where obsolete data remains stored on flash pages until the flash translation layer (FTL) erases them. erase() operations, however, cannot erase a single page, but target entire flash blocks. Since these victim blocks typically store a mix of valid and obsolete pages, FTLs have to copy the valid data to a new block before issuing an erase() operation. This process therefore increases the latencies of concurrent I/Os and reduces the lifetime of flash memory. Data classification schemes identify data pages with similar update frequencies and group them together. FTLs can use this grouping to design garbage collection strategi…
A more distinctive representation for 3D shape descriptors using principal component analysis
2015
Many researchers have used the Heat Kernel Signature (or HKS) for characterizing points on non-rigid three-dimensional shapes and Classical Multidimensional Scaling (Classical MDS) method in object classification which we quote, in particular, the example of Jian Sun et al. (2009) [1]. However, in this paper, the main focuses on classification that we propose a concise and provably factorial method by invoking Principal Component Analysis (PCA) as a classifier to improve the scheme of 3D shape classification. To avoid losing or disordering information after extracting features from the mesh, PCA is used instead of the Classical MDS to discriminate-as much as possible-feature points for each…
The Content Web-Accessibility of Information and Technology Support in a Complex System of Educational and Social Inclusion
2018
Support for the socialization of people with special needs is an urgent task in the European space. The study of the system of educational and social inclusion requires an interdisciplinary approach, and a large number of components, their hierarchy, and other features states that the system of inclusion is complex, and therefore requires appropriate means of its modeling - complex networks, graphs, appropriate modeling languages, etc. An important stage in the study of complex systems is the evaluation of their information and technology component in terms of the web accessibility. The use of the recommendations outlined in the WCAG 2.0 while developing information technologies as a compon…
Minimal Dynamic Equilibria
2018
We define dynamic models as multiperiod models with no static representations and demonstrate that current prevalent asset pricing empirical implementations are inconsistent with dynamic equilibria. Specifically, empirical implementations are misspecified with respect to three essential asset pricing questions (TEQ): dependency on higher moments, complexity of risk premia, and mean-variance efficiency of the “market portfolio” (ability to proxy pricing kernels/SDFs). While we already know that “Merton” models, and their derivatives, differ from static models in all TEQ, we show that this is the case even the “minimal” dynamic equilibria.
Body Image and Virtual Reality in Eating Disorders: Is Exposure to Virtual Reality More Effective than the Classical Body Image Treatment?
2009
Body image (BI) disturbances are considered to be central in eating disorders (ED) psychopathology. There are few studies focused on the treatment of BI disturbances in ED, and most of them have used "traditional methods." The purpose of the present study was to probe the effectiveness of one specific component in the assessment and treatment of BI in ED by means of virtual reality (VR). Two treatment conditions were applied: (a) The Standard Body Image Treatment Condition (SBIT) and (b) the VR Condition. Thirteen eating disordered patients were randomly assigned to one of those conditions. No differences between both conditions were found in general ED measures, but patients treated in the…
Nonlinear Dynamics Techniques for the Detection of the Brain Areas Using MER Signals
2008
A methodology for identifying brain areas from the brain MER signals (microelectrode recordings) is presented, which is based on a nonlinear feature set. We propose nonlinear dynamics measures such as correlation dimension, Hurst exponent and the largest Lyapunov exponent to characterize the dynamic structure. The MER records belong to the Polytechnical University of Valencia, 24 records for each zone (black substance, thalamus, subthalamus nucleus and uncertain area). The detection of each area using characteristics derived from complexity analysis was obtained through a classifier (support vector machine). The joint information between areas is remarkable and the best accuracy result was …
A Novel System for Multi-level Crohn’s Disease Classification and Grading Based on a Multiclass Support Vector Machine
2020
Crohn’s disease (CD) is a chronic inflammatory condition of the gastrointestinal tract that can highly alter patient’s quality of life. Diagnostic imaging, such as Enterography Magnetic Resonance Imaging (E-MRI), provides crucial information for CD activity assessment. Automatic learning methods play a fundamental role in the classification of CD and allow to avoid the long and expensive manual classification process by radiologists. This paper presents a novel classification method that uses a multiclass Support Vector Machine (SVM) based on a Radial Basis Function (RBF) kernel for the grading of CD inflammatory activity. To validate the system, we have used a dataset composed of 800 E-MRI…
Measuring the Novelty of Natural Language Text Using the Conjunctive Clauses of a Tsetlin Machine Text Classifier
2020
Most supervised text classification approaches assume a closed world, counting on all classes being present in the data at training time. This assumption can lead to unpredictable behaviour during operation, whenever novel, previously unseen, classes appear. Although deep learning-based methods have recently been used for novelty detection, they are challenging to interpret due to their black-box nature. This paper addresses \emph{interpretable} open-world text classification, where the trained classifier must deal with novel classes during operation. To this end, we extend the recently introduced Tsetlin machine (TM) with a novelty scoring mechanism. The mechanism uses the conjunctive clau…
An MDE Approach for Rapid Prototyping and Implementation of Dynamic Reconfigurable Systems
2015
This article presents a co-design methodology based on RecoMARTE, an extension to the well-known UML MARTE profile, which is used for the specification and automatic generation of Dynamic and Partially Reconfigurable Systems-on-Chip (DRSoC). This endeavor is part of a larger framework in which Model-Driven Engineering (MDE) techniques are extensively used for modeling and via model transformations, generating executable models, which are exploited by implementation tools to create reconfigurable systems. More specifically, the methodological aspects presented in this article are concerned with expediting the conception and implementation of the hardware platform and the integration of corre…