Disasters, crises and wars are a serious and unforeseen threat. The capacity of the early warning system to monitor such crises is therefore crucial. The ability to make quick decisions in a short time is necessary to prevent crises from occurring. Here, the role and effectiveness of the early warning system emerges through its ability to monitor, record and analyze signals. It can also be evidenced by its ability to immediately convey these indicators to the concerned authorities to take measures that ensure these conflicts and disasters do not worsen. The system’s ability to detect disasters and crises, identify the crisis and its type, and use the scientific method and common sense to deal with it is something that contributes to findi

Background: The appointment system is a common practice in primary health care clinics in developed countries. The patients and health care providers in the primary health care setting perceived the appointment system as an indicator of good quality service.

Objective: The aim of this study was to survey patients’ and health care providers’ attitudes towards the introduction of an appointment system and their satisfaction with the existing ‘walk-in’ system in the primary health care setting.

Subjects and Methods: A questionnaire survey was conducted included a convenient sample of 234 patients as well as 76 health care providers from two primary health care center

An Optimal Algorithm for HTML Page Building Process

As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.