In many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally that the speed up of the proposed method compared with traditional approaches approximately reaches up to 20 times depending on the block parameters.
The use of deep learning.
The study aimed to identify the future thinking skills of university students and which of these skills are prevalent. The sample of the study consisted of (400) male and female students from the university students. In order to achieve the goals of the research, the researcher built a measure of future thinking skills based on Torrance theory (2003). Psychometric properties of the standards were extracted, which are represented by honesty and consistency and the application of the measures to the research sample. The researchers found that Future thinking skills of university students, and that the skill of future planning is the most common skill among the research sample.
The aim of this work is to develop an axi-symmetric two dimensional model based on a coupled simplified computational fluid dynamics (CFD) and Lagrangian method to predict the air flow patterns and drying of particles. Then using this predictive tool to design more efficient spray dryers. The approach to this is to model what particles experience in the drying chamber with respect to air temperature and humidity. These histories can be obtained by combining the particles trajectories with the air temperature/humidity pattern in the spray dryer. Results are presented and discussed in terms of the air velocity, temperature, and humidity profiles within the chambers and compared for drying of a 42.5% solids solution in a spray chamber
... Show MoreDifferent ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach
The significant shortage of usable water resources necessitated the creation of safe and non-polluting ways to sterilize water and rehabilitate it for use. The aim of the present study was to examine the ability of using a gliding arc discharge to inactivate bacteria in water. Three types of Bacteria satisfactory were used to pollute water which are Escherichia coli (Gram-negative), Staphylococcus aurous (Gram-positive) and salmonella (Gram-negative). A DC power supply 12V at 100 Hz frequency was employed to produce plasma. pH of water is measured gradually during the plasma treatment process. Contaminated water treated by gliding arc discharge at steadying the gas flow rate (1.5 l/mi
Doses for most drugs are determined from population-level information, resulting in a standard ?one-size-fits-all’ dose range for all individuals. This review explores how doses can be personalised through the use of the individuals’ pharmacokinetic (PK)-pharmacodynamic (PD) profile, its particular application in children, and therapy areas where such approaches have made inroads.
The Bayesian forecasting approach, based on population PK/PD models that account for variability in exposure and response, is a potent method for personalising drug therapy. Its potential utility is eve