The current study performed in order to detect and quantify epicatechin in two tea samples of Camellia sinensis (black and green tea) by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Extraction of epicatechin from black and green tea was done by using two different methods: maceration (cold extraction method) and decoction (hot extraction method) involved using three different solvents which are absolute ethanol, 50% aqueous ethanol and water for both extraction methods using room temperature and direct heat respectively. Crude extracts of two tea samples that obtained from two methods were fractionated by using two solvents with different polarity (chloroform and ethyl acetate). Qualitative and quantitative determinations of epicatechin in tea samples were investigated. Epicatechin identification was made by utilizing preliminary chemical tests and TLC. This identification was also boosted by HPLC and the quantity of epicatechin was determined in all ethyl acetate fractions of two tea samples. This research revealed the existence of epicatechin in black and green tea according to TLC and HPLC. Aqueous ethanol 50% was the best solvent for extraction of epicatechin from leaves of tea. Quantitative estimation of epicatechin by HPLC revealed that ethyl acetate fraction of DGTAE contains the higher concentration of epicatechin than other analyzed fractions. Conclusion, tea is an excellent source of catechins particularly epicatechin that possessed various pharmacological effects.
The research aims to know the impact of workers values on their performance which is reflected on increasing productivity and improving its quality as well as the organization's progress and success. Application of this research took place in the General Company Of Electrical Industries; it contained four main pillars; the first involved research methodology، regarding the problem، importance، aim، basic theory، and method of data collection، the second is dedicated to the theoretical framework related to the research basic variables (values and workgroups) the third is assigned to analyze the actual data by using number of statistical methods، such as mathematical medium and standard deviation and also spearman rank
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The research aims to monitor the image of the man in the group (The Cart and the Rain) by the storyteller (Badiaa Amin); With the aim of highlighting an aspect of feminist writing, especially with regard to the relationship of women to men, and determining the form adopted by the storyteller in drawing the features of men.
The research used the descriptive-analytical method in the space of its textual formation, which aims to stand on the text and deconstruct its narrative significance. To provide a comprehensive picture of it.
Three images of the man appeared in the group's stories, represented by (the authoritarian, the negative, and the positive), and the image of the authoritarian ma
... Show MoreFor a long time, the intensification of profit represented a major goal for the company management ,but this goal confirmed a series of restrictions such the constriction on short period, the time rather than on long and medium strategic goal, the relationships with customers ,the supplies, employees , This goal is replaced by another one (intensification of the company's value) ,and the fortune of the share holders itself ,for the purpose of creating value, the company must generate great outcomes to cover the operating expense and to insure the a suitable compensation to the invested capital (the market value added) is the indication used to estimate the company ability to create value –added the development
... Show MoreDigital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different
... Show MoreGlobal Navigation Satellite Systems (GNSS) have become an integral part of wide range of applications. One of these applications of GNSS is implementation of the cellular phone to locate the position of users and this technology has been employed in social media applications. Moreover, GNSS have been effectively employed in transportation, GIS, mobile satellite communications, and etc. On the other hand, the geomatics sciences use the GNSS for many practical and scientific applications such as surveying and mapping and monitoring, etc.
In this study, the GNSS raw data of ISER CORS, which is located in the North of Iraq, are processed and analyzed to build up coordinate time series for the purpose of detection the
... Show MoreOne of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca
... Show MoreOne of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th
... Show MoreWildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
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