Search results for "Machine"
showing 10 items of 2592 documents
Low Level Languages for the PAPIA Machine
1986
The paper presents the low-level languages implemented up to date to program the PAPIA machine. The parallel assembly-level P-MAGRO package, the microcode level instruction set and a machine simulating environment are described.
Influence of low concentration acid treatment on lithium disilicate core/veneer ceramic bond strength
2013
Objective: This study evaluated the influence of low concentration acid treatment on the shear bond strength between lithium disilicate (LD) infrastructure and veneering porcelain. The surface morphology characteristic after this acid treatment was also examined. Study Design: LD reinforced ceramic cylinders (n=10) (IPS e.max Press, Ivoclar-Vivadent, Schaan, Liechtenstein) were treated (LD-treated) with a low concentration acid solution (Invex Liquid – Ivoclar-Vivadent, Schaan, Liechtenstein) or not treated with the acid solution (LD-untreated). They were veneered with a glass ceramic (IPS e.max Ceram, Ivoclar-Vivadent, Schaan, Liechtenstein). A metal ceramic group (CoCr) was tested as cont…
Emulation of Leaf, Canopy and Atmosphere Radiative Transfer Models for Fast Global Sensitivity Analysis
2016
Physically-based radiative transfer models (RTMs) help understand the interactions of radiation with vegetation and atmosphere. However, advanced RTMs can be computationally burdensome, which makes them impractical in many real applications, especially when many state conditions and model couplings need to be studied. To overcome this problem, it is proposed to substitute RTMs through surrogate meta-models also named emulators. Emulators approximate the functioning of RTMs through statistical learning regression methods, and can open many new applications because of their computational efficiency and outstanding accuracy. Emulators allow fast global sensitivity analysis (GSA) studies on adv…
Responsive and Minimalist App Based on Explainable AI to Assess Palliative Care Needs during Bedside Consultations on Older Patients
2021
[EN] Palliative care is an alternative to standard care for gravely ill patients that has demonstrated many clinical benefits in cost-effective interventions. It is expected to grow in demand soon, so it is necessary to detect those patients who may benefit from these programs using a personalised objective criterion at the correct time. Our goal was to develop a responsive and minimalist web application embedding a 1-year mortality explainable predictive model to assess palliative care at bedside consultation. A 1-year mortality predictive model has been trained. We ranked the input variables and evaluated models with an increasing number of variables. We selected the model with the seven …
The combined distribution/assignment problem in transportation network planning: a parallel approach on hypercube architecture
1995
The joint distribution/assignment problem plays a central role in urban transport network planning. In this problem, according to the mathematical model proposed by S. P. Evans, the trips are iteratively calculated and assigned to the network in such a way that the resulting traffic flows pattern satisfies the selfish equilibrium condition. Unfortunately the number of variables and constraints increase hardly with the greatness of the networks causing long computational time for the equilibrium solution. In this paper an nCUBE 2 parallel computing architecture is employed to solve the combined problem and to asses the potential of MIMD machines to handle large scale transportation network p…
Minimizing weighted earliness-tardiness on parallel machines using hybrid metaheuristics
2015
We consider the problem of scheduling a set of jobs on a set of identical parallel machines where the objective is to minimize the total weighted earliness and tardiness penalties with respect to a common due date. We propose a hybrid heuristic algorithm for constructing good solutions, combining priority rules for assigning jobs to machines and a local search with exact procedures for solving the one-machine subproblems. These solutions are then used in two metaheuristic frameworks, Path Relinking and Scatter Search, to obtain high quality solutions for the problem. The algorithms are tested on a large number of test instances to assess the efficiency of the proposed strategies. The result…
Dynamic interface for machine vision systems
2002
Iconic programming intends to provide expressive tools to implement, to debug, and to execute programs. For this purpose, visual languages need pictorial constructs and metaphors to guide the design of algorithms in interactive fashion. In the paper a new class of dynamic visual interfaces, named DIVA (Dynamic Interface for Visual Applications), is introduced, its properties are described, and an application to visual compilers in a multi-processors system dedicated to image analysis is given. Moreover, a formal definition of dynamic icon (DI) is also given.
Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latencies
2018
We consider multiobjective optimization problems where objective functions have different (or heterogeneous) evaluation times or latencies. This is of great relevance for (computationally) expensive multiobjective optimization as there is no reason to assume that all objective functions should take an equal amount of time to be evaluated (particularly when objectives are evaluated separately). To cope with such problems, we propose a variation of the Kriging-assisted reference vector guided evolutionary algorithm (K-RVEA) called heterogeneous K-RVEA (short HK-RVEA). This algorithm is a merger of two main concepts designed to account for different latencies: A single-objective evolutionary a…
On Dealing with Uncertainties from Kriging Models in Offline Data-Driven Evolutionary Multiobjective Optimization
2019
Many works on surrogate-assisted evolutionary multiobjective optimization have been devoted to problems where function evaluations are time-consuming (e.g., based on simulations). In many real-life optimization problems, mathematical or simulation models are not always available and, instead, we only have data from experiments, measurements or sensors. In such cases, optimization is to be performed on surrogate models built on the data available. The main challenge there is to fit an accurate surrogate model and to obtain meaningful solutions. We apply Kriging as a surrogate model and utilize corresponding uncertainty information in different ways during the optimization process. We discuss…
Emergency Analysis: Multitask Learning with Deep Convolutional Neural Networks for Fire Emergency Scene Parsing
2021
In this paper, we introduce a novel application of using scene semantic image segmentation for fire emergency situation analysis. To analyse a fire emergency scene, we propose to use deep convolutional image segmentation networks to identify and classify objects in a scene based on their build material and their vulnerability to catch fire. We introduce our own fire emergency scene segmentation dataset for this purpose. It consists of real world images with objects annotated on the basis of their build material. We use state-of-the-art segmentation models: DeepLabv3, DeepLabv3+, PSPNet, FCN, SegNet and UNet to compare and evaluate their performance on the fire emergency scene parsing task. …