Dropping packets with a linear function between two configured queue thresholds in Random Early Detection (RED) model is incapable of yielding satisfactory network performance. In this article, a new enhanced and effective active queue management algorithm, termed Double Function RED (DFRED in short) is developed to further curtail network delay. Specifically, DFRED algorithm amends the packet dropping probability approach of RED by dividing it into two sub-segments. The first and second partitions utilizes and implements a quadratic and linear increase respectively in the packet dropping probability computation to distinguish between two traffic loads: low and high. The ns-3 simulation performance evaluations clearly indicate that DFRED algorithm significantly controls the average queue occupancy and yields a reasonable gain in end-to-end-delay under different network conditions.
Face Detection by skin color in the field of computer vision is a difficult challenge. Detection of human skin focuses on the identification of pixels and skin-colored areas of a given picture. Since skin colors are invariant in orientation and size and rapid to process, they are used in the identification of human skin. In addition features like ethnicity, sensor, optics and lighting conditions that are different are sensitive factors for the relationship between surface colors and lighting (an issue that is strongly related to color stability). This paper presents a new technique for face detection based on human skin. Three methods of Probability Density Function (PDF) were applied to detect the face by skin color; these ar
... Show MoreIn many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an
... Show MoreBackground: Salmonella spp. are one of the most frequently reported causes of bacterial foodborne outbreak in the world.
Objective: This study has been conducted to detect salmonella as a major public health problem worldwide.
Methods: A total of 12 samples including 8 white meat (chicken) and 4 red meat (beef) samples were collected randomly from each sample; 25gr was separated and treated with 225ml of buffered peptone water, incubated at 37C°and 42C° for 24 hours. Samples were streaked on selective enteric agar.
Result: Totally 4 out of 8 chicken meat and one out of 4 red meat samples were contaminated with Salmonella spp.
Conclusion: These results confirmed the previous findings stating the proper packaging of meat prod
Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re
... Show MoreThis paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that
The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.
Background: Breast Cancer is the most common malignancy among the Iraqi population; the majority of cases are still diagnosed at advanced stages with poor prospects of cure. Early detection through promoting public awareness is one of the promising tools in its control. Objectives: To evaluate the baseline needs for breast cancer awareness in Iraq through exploring level of knowledge, beliefs and behavior towards the disease and highlighting barriers to screening among a sample of Iraqi women complaining of breast cancer. Methodology: Two-hundred samples were enrolled in this study; gathered from the National
The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla
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