Abstract:
              In this study a type of polymeric composites from melting poly propylene as a basic substance with Palm fronds powder were prepared. Evaluation of polymeric composites was done by studying some of it is mechanical properties, which included:Yong modulus (E), Impact Strength (I.S), Brinell hardness (B.H) and Compression Strength (C.S). The polymeric composites were studied before and after reinforcment by comparing between them. There was an increase in resistance of Yong modulus (E), Impact Strength (I.S), Brinell hardness (B.H) and compression Strength (C.S). Also, the effect of some acids were studied such as (HCl, H₂

This field experiment was conducted at Research Station B, Department of Horticulture and Landscape Engineering, College of Agricultural Engineering Sciences, University of Baghdad, Jadiriyah during the fall season of 2019-2020 to evaluate the effect of cultivation dates and soil fertilization source on the growth, yield and quality of broccoli. A split plot design within the RCBD design with three replicates was applied as the Max F1 hybrid broccoli seedlings were transferred to the field at two dates 25, Sep. 2019 and 15, Oct. 2019, which were symbolized as A and B, respectively, and occupied at the main plot. After two weeks of cultivation, the soil fertilizers were applied three times during the season in 20 days between each applicati

This work aims to enhance acoustic and thermal insulation properties for polymeric composite by adding nanoclay and rock wool as reinforcement materials with different rations. A polymer blend of (epoxy+ polyester) as matrix materials was used. The Hand lay-up technique was used to manufacture the castings. Epoxy and polyester were mixed at different weight ratios involving (50:50, 60:40, 70:30, 80:20, and 90:10) wt. % of (epoxy: polyester) wt. % respectively. Impact tests for optimum sample (OMR), caustic and thermal insulation tests were performed. Nano clay (Kaolinite) with ratios ( 5 and 7.5% ) wt.% , also hybrid reinforcement materials involving (Kaolite 5 & 7.5 % wt.% + 10% volume fraction of rockwool ) were added as reinforcem

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles