This study includes applying chemical tests on cow, sheep and chicken bones including both hallow and flat. The results of chemical tests on bones mentioned the moisture percentage which was between 4.95-7.32 %, and it was noticed the difference in protein percentage among different kinds of bones, The highest protien percentage was 39.62 % in hallow chicken bones and the lowest was in hallow sheep bones 20.31%, at the same time, the highest Ash percentage was in hallow sheep bones48.11% , whereas the highest percentage of fat was in hallow cow bones 30%. The chemical and physical tests were conducted for extracted fat from hallow and flat bones for cows, sheeps and chicken. It was found that peroxide values (PV), and free fatty acids (F

ABSTRACT

This study was conducted to determine the effect of various levels of hump fat (HF) used in manufacturing of camel, beef and chicken sausage to understand the effect of (HF) on physicochemical composition sausage, Different levels of hump fat (5, 7, and 10 %) were used, physicochemical compositions like (moisture, protein, fat, Ash, water holding capacity, shrinkage, cooking loss and pH) were determined. Results of the study revealed that moisture content showed high significant differences (P≤0.01)among treatments groups, Camel sausage and beef sausage tended to have highest values while chicken sausage reported the lowest value. The study showed no significant difference (P≤0.05) among the

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

Background: Asymmetry assessment is an important component of orthodontic diagnosis and treatment planning. Several studies attempted to find the relationship between craniometric asymmetry and skeletal jaws relationship and many authors found some extent of asymmetry in individuals with normal jaws relationship. The use of Computed tomography (CT) allows for the assessment of asymmetry on a dimensionally accurate volumetric image, aim of the study is to determine if there are differences in craniometric asymmetry between patient with skeletal class I and patients with skeletal class II relationship using Helical CT scan. Materials and Methods: Ninety individuals with clinically symmetrical faces were imaged with Helical CT scan, and aging

Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.

A reliable and environmental analytical method was developed for the direct determination of tetracycline using flow injection analysis (FIA) and batch procedures with spectrophotometric detection. The developed method is based on the reaction between a chromogenic reagent (vanadium (III) solution) and tetracycline at room temperature and in a neutral medium, resulting in the formation of an intense brown product that shows maximum absorption at 395 nm. The analytical conditions were improved by the application of experimental design. The proposed method was successfully used to analyze samples of commercial medications and verified throughout the concentration ranges of 25–250 and 3–25 µg/mL for both FIA and batch procedures, respecti

Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system