The aim of the research is to identify learning difficulties and their role in children's perception of self-concept. The researcher adopted the descriptive and analytical approach method in this study. A questionnaire was designed by the researcher to collect some related information such as biodata, family, health, diagnostic and behavioral patterns of the case. In addition, the researcher adopted the scale of learning difficulties for elementary school students prepared by Zaidan Ahmed Al-Sartawi (1995), the scale of student appreciation for the survey of learning difficulties for primary school students by Michael Best, which was translated to the Arabic language by (Saeed Abdullah Debis). The researcher adopted also the Self-Concept

The objective of the present study is to determine the nature and direction of the correlation between mathematical excellence and learning styles as defined by the Entwistle, model in fifth-grade scientific female students. The descriptive correlational approach was implemented by the two researchers to accomplish the research objectives. A scale was developed to assess the learning styles of female students in the sample in accordance with the Entwistle, model. : (Knowledge, understanding, application, analysis, synthesis, evaluation, systematic thinking, creativity), and the research community was determined by the female students of the scientific fifth grade in the morning preparatory and secondary schools of the General Direct

This research study Blur groups (Fuzzy Sets) which is the perception of the most modern in the application in various practical and theoretical areas and in various fields of life, was addressed to the fuzzy random variable whose value is not real, but the numbers Millbh because it expresses the mysterious phenomena or uncertain with measurements are not assertive. Fuzzy data were presented for binocular test and analysis of variance method of random Fuzzy variables , where this method depends on a number of assumptions, which is a problem that prevents the use of this method in the case of non-realized.

In this work ,medical zinc oxide was produced from zinc scraps instead of traditional method which used for medical applications such as skin diseases, Iraq is importing around 50 ton/year for samarra plant the producted powder has apartical size less than 5 micron and the purity was more than 99.98%,also apilot plant of yield capacitiy 15 kg/8hours wsa designed and manufactured .

In this study, hydroxyapatite (HAP, Ca10(PO4)6(OH)2) has been prepared as bioceramic material with biological specifications useful to used for orthopedic and dental implant applications. Wet chemical processing seems to form the fine grain size and uniform characteristic nanocrystalline materials by the interstice factors controlling which affected the grain size and crystallinity in order to give good mechanical and/or constituent properties similar as natural bone. Fluorinated hydroxyapatite [4-6 wt% F, (FHA, Ca10(PO4)6(OH)2–Fx] was developed in new method for its posses to increased strength and to give higher corrosion resistance in biofluids than pure HAP moreover reduces the risk of dental caries. The phase's and functional groups

ABSTRACT

Naproxen(NPX) imprinted liquid electrodes of polymers are built using polymerization precipitation. The molecularly imprinted (MIP) and non imprinted (NIP) polymers were synthesized using NPX as a template. In the polymerization precipitation involved, styrene(STY) was used as monomer, N,N-methylenediacrylamide (N,N-MDAM) as a cross-linker and benzoyl peroxide (BPO) as an initiator. The molecularly imprinted membranes and the non-imprinted membranes were prepared using acetophenone(AOPH) and di octylphathalate(DOP)as plasticizers in PVC matrix. The slopes and detection limits of the liquid electrodes ranged from)-18.1,-17.72 (mV/decade and )4.0 x 10^-

This study was conducted to prepare protein concentrates from AL-Zahdidate’s pits by using alkaline methods where the chemical composition of the pits were (7.30, 1.04, 5.80, 8.68 and 77.19) % for each of the moisture, ash, protein, fat and carbohydrates respectively and the chemical composition of the concentrate protein was (6.62, 4.10, 26.70, 0.93, and 58.65) % respectively. The content of protein concentrate from the metallic elements (144.07, 25.11, 15.02, 0.49, 0.59, 0.27, 0.22 and 234.6) mg/ 100 g each of potassium, magnesium, calcium, iron, manganese, copper, zinc and phosphorus respectively. The results of SDS-PAGE showed five bands with weights molecular ranged between 11000-70000 Dalton. Give the biscuit which contain protei

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.       In this research, we pr