This research aims to clarify the conceptual framework of social entrepreneurship shows the importance of the development of social entrepreneurship according to the contextual aspects and the social value achieved from these works. It also identifies the degree of level of a sample of women entrepreneurs in Iraq for the extent of the relationship between social entrepreneurship and women's empowerment. It also explains the impact of entrepreneurial work in empowering women and the extent to which there are individual differences between the average scores of the sample members’ estimation of the level of social entrepreneurship according to social status, age group, educational qualification, and specialization according to the scale of Bag, Bahn & Mc Cline (2000) which included (8) variables, (4) of which were selected for the current research (realization of the pioneering opportunity, creativity, risk taking, proactiveness) at a rate of (5) items for each variable making the total items 20. The second part measures the level of women's empowerment according to Hashemi and Schuler (1993), which included (7) variable and for the current research, (4) were selected: the sense of the self, economic security, the development of pioneering behavior in the public sphere, and participation in decision-making. At the rate of (4) items for each variable, so that the total number of the items of the second part becomes (16). A questionnaire was distributed to (63) female entrepreneurs who were randomly selected in the field of social work. The level of women's empowerment was high. Also, social entrepreneurship had a significant impact on the women's empowerment index, especially in the light of the Corona crisis. The results of the study showed that there is a direct relationship between the degree of appreciation of the members of the sample for the level of social entrepreneurship, and the degree of their appreciation for the level of women’s empowerment. They also revealed that there are differences between the average degrees of the respondents’ assessment of the level of social entrepreneurship due to demographic variables. The study recommended that the priorities of the public business agenda should focus on the requirements of attention social entrepreneurship projects for both sexes, especially women, because of their positive impact on various social, economic and political aspects.
This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it
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The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi
... Show MoreThe design, synthesis, and characterization of a star shaped 2,4,6-tris-(4`-carboxyphenoxy)-1,3,5-triazine liquid crystalline with columnar discotic mesophase properties establish H-bond interactions with 3,5-dialkoxypyidine were reported. The structures of the synthesized compounds were actually determined by elementary analysis, and FT-IR, ¹HNMR, ¹³CNMR, and mass spectroscopy. The mesomorphic properties of these mesogens were examined using differential scanning calorimetry (DSC) and optical polarizing microscopy (OPM). The synthesized molecules exhibited enantiotropic hexagonal columnar liquid crystal, which depends for the H- bond complex in a 1:3 ratio.
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database
Abstract
The current research aims to identify the level of E-learning among middle school students, the level of academic passion among middle school students, and the correlation between e-learning and academic passion among middle school students. In order to achieve the objectives of the research, the researcher developed two questionnaires to measure the variables of the study (e-learning and study passion) among students, these two tools were applied to the research sample, which was (380) male and female students in the first and second intermediate classes. The research concluded that there is a relationship between e-learning and academic passion among students.
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