Influence of carbon,silicon and molybdenum on the separating and emulsifying behaviour of steel and slag

The influence of C, Si, and Mo on the surface tension of Armco iron, and on the interfacial tension between Armco iron and a 40%CaO/40%SiO₂/20%Al₂O₃ slag at 1550°C has been investigated. Surface tension was determined according to the drop weight method, and the interfacial tension by the drop detachment method. Based on these measurements, ternary interfacial tension diagrams are set up, which enable the separating and emulsifying tendencies of the related steel/slag/gas systems to be predicted. This is followed by the calculation of the meniscus radius as a function of interfacial tension in continuous casting, together with the assessment of its effect on lubrication.     

Nonlocal strain gradient finite element analysis of nanobeams using two-variable trigonometric shear deformation theory

In the present paper, a new trigonometric two-variable shear deformation beam nonlocal strain gradient theory is developed and applied to investigate the combined effects of nonlocal stress and strain gradient on the bending, buckling and free vibration analysis of nanobeams. The model introduces a nonlocal stress field parameter and a length scale parameter to capture the size effect. The governing equations derived are solved employing finite element method using a 3-nodes beam element, developed for this purpose. The predictive capability of the proposed model is shown through illustrative examples for bending, buckling and free vibration of nanobeams. Comparisons with other higher-order shear deformation beam theory are also performed to validate its numerical implementation and assess its accuracy within the nonlocal context.

     

Decision-driven scheduling

Real-Time Systems - This paper presents a scheduling model, called decision-driven scheduling, elaborates key optimality results for a fundamental scheduling model, and evaluates new heuristics...     

Microscale modeling of effective mechanical and electrical properties of textiles

A computational framework for assisting in the development of novel textiles is presented. Electronic textiles are key in the rapidly growing field of wearable electronics for both consumer and military uses. There are two main challenges to the modeling of electronic textiles: the discretization of the textile microstructure and the interaction between electromagnetic and mechanical fields. A director‐based beam formulation with an assumed electrical current is used to discretize the fabric at the level of individual fibrils. The open‐source package FEniCS was used to implement the finite element model. Contact integrals were added into the FEniCS framework so that multiphysics contact laws can be incorporated in the same framework, leveraging the code generation and automated differentiation capabilities of FEniCS to produce the tangents needed by the implicit solution method. The computational model is used to construct and determine the mechanical, thermal, and electrical properties of a representative volume elements of a plain woven textile. Dynamic relaxation to solve the mechanical fields and the electrical and thermal fields is solved statically for a given mechanical state. The simulated electrical responses are fit to a simplified Kirchhoff network model to determine effective resistances of the textile. Copyright © 2016 John Wiley & Sons, Ltd.     

A fast training method for memristor crossbar based multi-layer neural networks

The capacitance variation of capacitive accelerometer as a function of vibratory movement relative frequency is presented using a developed model validated by simulation and experimental tests. The damping rate effect on accelerometer capacitance variation is studied for four damping rate values. The first value is that of accelerometer used in the experimental tests, the second and third are taken from the recent works and the fourth is the value proposed in this work. A comparative study has been made to mount our improvements on the capacitive accelerometer performances by the comparison between the proposed accelerometers in the recent works. Finally, a new capacitive accelerometer with improved parameters is proposed having many benefits over the existing accelerometers. These benefits are: appropriate choice of damping rate (equal to 0.68), very low measurement error (limited to 0.5%), high accuracy (equal to 99.5%), low consumption of electrical energy and high sensitivity and reliability.     

Input fault detection and estimation using PI observer based on the ARX-Laguerre model

This work is dedicated to the synthesis of a new fault detection and identification scheme for the actuator and/or sensor faults modeled as unknown inputs of the system. The novelty of this scheme consists in the synthesis of a new structure of proportional-integral observer (PIO) reformulated from the new linear ARX-Laguerre representation with filters on system input and output in order to estimate the unknown inputs presented as faults. The designed observer exploits the input/output measurements to reconstruct the Laguerre filter outputs where the stability and the convergence properties are ensured by using Linear Matrix Inequality. However, a significant reduction of this model is subject to an optimal choice of both Laguerre poles which is achieved by a new proposed identification approach based on a genetic algorithm. The performances of the proposed identification approach and the resulting PIO are tested on numerical simulation and validated on a 2 ^{n d} order electrical linear system.     

Parallelized path-based search for constraint satisfaction in autonomous cognitive agents

The Journal of Supercomputing - Cognitive agents are typically utilized in autonomous systems for automated decision making. With the widespread use of autonomous systems in complex environments,...     

Background subtraction using finite mixtures of asymmetric Gaussian distributions and shadow detection

Foreground segmentation of moving regions in image sequences is a fundamental step in many vision systems including automated video surveillance, human-machine interface, and optical motion capture. Many models have been introduced to deal with the problems of modeling the background and detecting the moving objects in the scene. One of the successful solutions to these problems is the use of the well-known adaptive Gaussian mixture model. However, this method suffers from some drawbacks. Modeling the background using the Gaussian mixture implies the assumption that the background and foreground distributions are Gaussians which is not always the case for most environments. In addition, it is unable to distinguish between moving shadows and moving objects. In this paper, we try to overcome these problem using a mixture of asymmetric Gaussians to enhance the robustness and flexibility of mixture modeling, and a shadow detection scheme to remove unwanted shadows from the scene. Furthermore, we apply this method to real image sequences of both indoor and outdoor scenes. The results of comparing our method to different state of the art background subtraction methods show the efficiency of our model for real-time segmentation.     

System-wide energy optimization for multiple DVS components and real-time tasks

Most dynamic voltage and frequency scaling (DVS) techniques adjust only CPU parameters; however, recent embedded systems provide multiple adjustable clocks which can be independently tuned. When considering multiple components, energy optimal frequencies depend on task set characteristics such as the number of CPU and memory access cycles. In this work, we propose a realistic energy model considering multiple components with individually adjustable frequencies such as CPUs, system bus and memory, and related task set characteristics. The model is validated on a real platform and shows less than 2% relative error compared to measured values. Based on the proposed energy model, we present an optimal static frequency assignment scheme for multiple DVS components to schedule a set of periodic real-time tasks. We simulate the energy gain of the proposed scheme compared to other DVS schemes for various task and system configurations, showing up to a 20% energy reduction. We also experimentally verify energy savings of the proposed scheme on a real hardware platform.