Effective abnormality detection and diagnosis in Magnetic Resonance Images (MRIs) requires a robust segmentation strategy. Since manual segmentation is a time-consuming task which engages valuable human resources, automatic MRI segmentations received an enormous amount of attention. For this goal, various techniques have been applied. However, Markov Random Field (MRF) based algorithms have pro...

This paper addresses the problem of video object segmentation, where the initial object mask is given in the first frame of an input video. We propose a novel spatiotemporal Markov Random Field (MRF) model defined over pixels to handle this problem. Unlike conventional MRF models, the spatial dependencies among pixels in our model are encoded by a Convolutional Neural Network (CNN). Specificall...

One of the newly developed methods for obtaining super finished surfaces for freeform is Magnetorheological finishing (MRF). MRF is an advanced finishing process in which the grinding force is controlled by magnetic field. The material removal in MRF is governed by the magnetorheological fluid which mainly consists of carbonyl iron (CI), abrasives particles, carrier fluids and additives. MRF pr...

Streams of sensor measurements arise from twitter, mobile phone networks, internet traffic, road traffic, home automation systems, seismic motion and sea level to mention just a few. The interactive exploration and modelling of such measurements from multiple sensors induces the need for algorithms that are capable of processing the data as it becomes available and that can quickly provide part...

PURPOSE MR fingerprinting (MRF) is a technique for quantitative tissue mapping using pseudorandom measurements. To estimate tissue properties such as T1 , T2 , proton density, and B0 , the rapidly acquired data are compared against a large dictionary of Bloch simulations. This matching process can be a very computationally demanding portion of MRF reconstruction. THEORY AND METHODS We introdu...

Insights derived from life-cycle assessment of solid waste management strategies depend critically on assumptions, data, and modeling at the unit process level. Based on new primary data, a process model was developed to estimate the cost and energy use associated with material recovery facilities (MRFs), which are responsible for sorting recyclables into saleable streams and as such represent ...

Research was conducted to explore the use of low pressure homogenization for extending functionality rice flours. The impact (0, 30, 50 MPa and 0, 1, 2, 3 passes) on particle size distribution long (LRF) medium (MRF) grain flour evaluated. level number passes resulted in a lower both Higher pressures led an increase due aggregation smaller particles. effect 30 or - physicochemical (composition,...

To improve the performance of vehicle suspension, this paper proposes a semi-active suspension with magnetorheological fluid (MRF) damper. We designed an optimized fuzzy skyhook controller grey wolf optimizer (GWO) algorithm base on new neuro-inverse model MRF Because inverse damper is difficult to establish directly, Elman neural network was applied. The novelty study application for vibration...

Accurate land cover classification (LCC) is essential for studying global change. Synthetic aperture radar (SAR) has been used LCC due to its advantage of weather independence. In particular, the dual-polarization (dual-pol) SAR data have a wider coverage and are easier obtain, which provides an unprecedented opportunity LCC. However, dual-pol weak discrimination ability limited polarization in...