DBN Rashid, International Journal of English Linguistics, 2019 - Cited by 2

Background There is an increasing need for pharmacists to incorporate more patient care targeting. Consequently, the productivity of pharmacy programs can be enhanced by evaluating the advantages and disadvantages of pharmacy curriculum. Objectives To assess the beliefs, perceptions, and challenges of the College of Pharmacy –The University of Baghdad PharmD graduates regarding the PharmD program. Method Qualitative research methodology was implemented. Graduate PharmD candidates were interviewed either inperson or via telephone. The interviews were conducted in a semi-structured format, utilizing a predetermined interview guide that included open-ended questions. Thematic analysis was implemented to analyze the data. Results A total of 2

So I present in the hands of the honorable reader what God Almighty has made easy for me in terms of what I dealt with in the rule (the principle of permissive things) and what branches from it and what is related to it.
This research was divided into an introduction, a preface, three demands, and a conclusion.
The preamble is to explain the meaning of the rule in language and terminology and the definition of the legal rule and what is related to it. The first requirement is to explain the rule that we have in our hands and the words related to its text - and is it a fundamentalist or jurisprudential rule? .
As for the second requirement - in the difference of scholars and their opinions in whether the origin of things is permi

The current theoretical research targeted to construct a model of terrorist personality and its differentiation from psychopathic personality . Several assumptions or theories of perspectives of psychopathic personality have been compared with the terrorist personality studies that concerned . The suggested theoretical  model is interrupting the terrorist personality . The conclusions , discussions are mentioned. Finally, recommendation is suggested .

Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent $\left({}\right)$

The research aims to identify the level of functional engagement and hope-based thinking of kindergarten teachers, identify if there is a significant difference in functional engagement and hope-based thinking in terms of specialization and years of service for kindergarten teachers, identify if there is a significant correlation between functional engagement and hope-based thinking of kindergarten teachers. The current research is determined by kindergarten teachers in the Second Rusafa Baghdad Education Directorate for the academic year (2022-2023). In order to achieve the objectives of the research, the researcher prepared a functional engagement scale, which consists of (45) items in three areas: Perceptual and functional engagement

In the field of data security, the critical challenge of preserving sensitive information during its transmission through public channels takes centre stage. Steganography, a method employed to conceal data within various carrier objects such as text, can be proposed to address these security challenges. Text, owing to its extensive usage and constrained bandwidth, stands out as an optimal medium for this purpose. Despite the richness of the Arabic language in its linguistic features, only a small number of studies have explored Arabic text steganography. Arabic text, characterized by its distinctive script and linguistic features, has gained notable attention as a promising domain for steganographic ventures. Arabic text steganography harn

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