Human action recognition has gained popularity because of its wide applicability, such as in patient monitoring systems, surveillance systems, and a wide diversity of systems that contain interactions between people and electrical devices, including human computer interfaces. The proposed method includes sequential stages of object segmentation, feature extraction, action detection and then action recognition. Effective results of human actions using different features of unconstrained videos was a challenging task due to camera motion, cluttered background, occlusions, complexity of human movements, and variety of same actions performed by distinct subjects. Thus, the proposed method overcomes such problems by using the fusion of features concept for the development of a powerful human action descriptor. This descriptor is modified to create a visual word vocabulary (or codebook) which yields a Bag-of-Words representation. The True Positive Rate (TPR) and False Positive Rate (FPR) measures gave a true indication about the proposed HAR system. The computed Accuracy (Ar) and the Error (misclassification) Rate (Er) reveal the effectiveness of the system with the used dataset.
An idiom is a group of words whose meaning put together is different from the meaning of
individual words. English is a rich language when it comes to idioms, they represent variety. For
foreign learners, idioms are problematic because even if they know the meaning of individual
words that compose an idiom the meaning of it might be something completely different.
The present study investigates Iraqi third year college students’ recognition of idioms. To
achieve this, the researchers have conducted a test which comprises three questions. Certain
conclusions are reached here along with some suggestions and recommendations.
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.
... Show MoreThis study was aimed to monitor oral zinc sulfate role on local cervical proinflammatory cytokines in HPV-infected women comparing with these cytokines before treatment application. A cervical secretion got from 28 infected women before and after treatment with zinc sulfate, these samples assessed various markers of inflammation including interleukin-1β, IL-8, and IL-12. Results manifested that improve and clear the cervical HPV infections after three months of zinc treatment 46.43% and 21.43%, respectively. Viral infections with single and multiple HPV high-risk types are raising of studied cytokines after 3-month compared with single HPV low-risk type. Moreover, this increasing was statistically significant only in IL-12 and IL-1. Women
... Show MoreThe aim of the research is to test the effect of outsourcing human resources activities (independent variable) with its dimensions (outsourcing of staffing, outsourcing of training and development, outsourcing of wages and compensation, outsourcing of human resources information systems) on organizational winning (dependent variable) with its dimensions (the culture of winning, successful organizational change, continuous improvement, and adoption of risk). The research problem was the questions posed by the researcher, the most important of which is the extent to which the research sample realizes the importance of applying outsourcing to human resources activities and its role in organizational vi
... Show MoreIn 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.
Starting from 4, - Dimercaptobiphenyl, a variety of phenolic Schiff bases (methylolic, etheric, epoxy) derivatives have been synthesized. All proposed structure were supported by FTIR, 1H-NMR, 13C-NMR Elemental analysis all analysis were performed in center of consultation in Jordan Universty.
In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.
Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct
... Show MoreA hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m
... Show MoreEight isolates of P. aeruginosa were obtained out of 90 water samples. The isolated colonies were identified based on their morphology and biochemical characteristics, were confirmed as P. aeruginosa by the API 20E test system.
The percentages of P. aeruginosa recovery in this study were 8.8.% All isolates were able to produce greenish blue pigment (pyocyanin). Pyocyanin at all concentrations was significantly increased the percentage of fragmented DNA of peripheral blood lymphocyte cells compared to control , results showed that DNA fragmentation percentage was higher in concentration 50 μg/ml (70%,74.3%) at 24 hr,48hr respectively. In summary, results of recent study demonstrate that the pyocyanin, induces apoptosis of human periph