Search results for " machine"
showing 10 items of 1317 documents
Transformations that preserve learnability
1996
We consider transformations (performed by general recursive operators) mapping recursive functions into recursive functions. These transformations can be considered as mapping sets of recursive functions into sets of recursive functions. A transformation is said to be preserving the identification type I, if the transformation always maps I-identifiable sets into I-identifiable sets.
Optimised assembly mode reconfiguration of the 5-DOF Gantry-Tau using mixed-integer programming
2010
Pulished version of an article in the journal: Meccanica. Also available from the publisher at: http://dx.doi.org/10.1007/s11012-010-9404-y This paper presents a systematic approach based on Mixed Integer Linear Programming for finding an optimal singularity-free reconfiguration path of the 5-DOF Gantry-Tau parallel kinematic machine. The results in the paper demonstrate that singularity-free reconfiguration (change of assembly mode) of the machine is possible, which significantly increases the usable workspace. The method has been applied to a full-scale prototype and the singularity-free path has been verified both in simulations and with physical experiments using real-time control of th…
FMI4j: A Software Package for working with Functional Mock-up Units on the Java Virtual Machine
2018
This paper introduces FMI4j, a software package for working with Functional Mock-up Units (FMUs) on the Java Virtual Machine (JVM). FMI4j is written in Kotlin, which is 100% interoperable with Java, and consists of programming APIs for parsing the meta-data associated with an FMU, as well as running them. FMI4j is compatible with FMI version 2.0 for Model Exchange (ME) and Co-Simulation (CS). Currently, FMI4j is the only software library targeting the JVM supporting ME 2.0. In addition to provide bare-bones access to such FMUs, it provides the means for solving them using a range of bundled fixedand variable-step solvers. A command line tool named FMU2Jar is also provided, which is capable …
Structured Output SVM for Remote Sensing Image Classification
2011
Traditional kernel classifiers assume independence among the classification outputs. As a consequence, each misclassification receives the same weight in the loss function. Moreover, the kernel function only takes into account the similarity between input values and ignores possible relationships between the classes to be predicted. These assumptions are not consistent for most of real-life problems. In the particular case of remote sensing data, this is not a good assumption either. Segmentation of images acquired by airborne or satellite sensors is a very active field of research in which one tries to classify a pixel into a predefined set of classes of interest (e.g. water, grass, trees,…
Clinically-Driven Virtual Patient Cohorts Generation: An Application to Aorta
2021
The combination of machine learning methods together with computational modeling and simulation of the cardiovascular system brings the possibility of obtaining very valuable information about new therapies or clinical devices through in-silico experiments. However, the application of machine learning methods demands access to large cohorts of patients. As an alternative to medical data acquisition and processing, which often requires some degree of manual intervention, the generation of virtual cohorts made of synthetic patients can be automated. However, the generation of a synthetic sample can still be computationally demanding to guarantee that it is clinically meaningful and that it re…
Emulation of 2D Hydrodynamic Flood Simulations at Catchment Scale Using ANN and SVR
2021
Two-dimensional (2D) hydrodynamic models are one of the most widely used tools for flood modeling practices and risk estimation. The 2D models provide accurate results
Object-Oriented Operational Semantics
2016
Operational semantics is one way of providing meaning to an executable language. On a high level of abstraction, operational semantics means to define an interpreter or an abstract machine for the language. In this article, we review the concept of operational semantics in the scope of meta-model-based language definitions and identify challenges and issues. We provide a clean conceptual approach using an object-oriented runtime environment and state change operations, which relies on an underlying abstract virtual machine. We present the approach using a sample language.
Deep Convolutional Neural Network for HEp-2 fluorescence intensity classification
2019
Indirect ImmunoFluorescence (IIF) assays are recommended as the gold standard method for detection of antinuclear antibodies (ANAs), which are of considerable importance in the diagnosis of autoimmune diseases. Fluorescence intensity analysis is very often complex, and depending on the capabilities of the operator, the association with incorrect classes is statistically easy. In this paper, we present a Convolutional Neural Network (CNN) system to classify positive/negative fluorescence intensity of HEp-2 IIF images, which is important for autoimmune diseases diagnosis. The method uses the best known pre-trained CNNs to extract features and a support vector machine (SVM) classifier for the …
A multi-process system for HEp-2 cells classification based on SVM
2016
An automatic system for pre-segmented IIF images analysis was developed.A non-standard pipeline for supervised image classification was adopted.The system uses a two-level pyramid to retain some spatial information.From each cell image 216 features are extracted.15 SVM classifiers one-against-one have been implemented. This study addresses the classification problem of the HEp-2 cells using indirect immunofluorescence (IIF) image analysis, which can indicate the presence of autoimmune diseases by finding antibodies in the patient serum. Recently, studies have shown that it is possible to identify the cell patterns using IIF image analysis and machine learning techniques. In this paper we de…
Automated detection of microaneurysms using robust blob descriptors
2013
International audience; Microaneurysms (MAs) are among the first signs of diabetic retinopathy (DR) that can be seen as round dark-red structures in digital color fundus photographs of retina. In recent years, automated computer-aided detection and diagnosis (CAD) of MAs has attracted many researchers due to its low-cost and versatile nature. In this paper, the MA detection problem is modeled as finding interest points from a given image and several interest point descriptors are introduced and integrated with machine learning techniques to detect MAs. The proposed approach starts by applying a novel fundus image contrast enhancement technique using Singular Value Decomposition (SVD) of fun…