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All Journal International Journal of Electrical and Computer Engineering International Journal of Evaluation and Research in Education (IJERE) AGRIVITA, Journal of Agricultural Science
Muhammad Nadeem, Muhammad
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Agriculture, Biological Sciences & Forestry Computer Science & IT Education Electrical & Electronics Engineering

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Genotype by Environment Interactions in Barley (Hordeum vulgare L.) Cultivars for Nutritional Quality Assessment Quddos, Abdul; Nadeem, Muhammad; Ahsan, Samreen; Khaliq, Adnan; Chughtai, Muhammad Farhan Jahangir; Rebezov, Maksim; Terent’ev, Sergei; Tryabas, Yulia; Ermolaev, Vladimir; Iskakova, Galiya; Konovalov, Sergey; Gayvas, Alexei; Shariati, Mohammad Ali
AGRIVITA, Journal of Agricultural Science Vol 43, No 3 (2021)
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v43i3.2925

Abstract

In current study twenty-five barley genotypes were grown under RCBD (randomized complete block design). Barley flour was analyzed for proximate composition, β-glucan content, soluble and insoluble dietary fiber. Based on the results of nutritional quality best line (4158) was selected for the preparation of wheat flour supplemented bread. The sensory evaluation of bread was carried out to assess its suitability for consumers. The data obtained from all the experiments was subjected to statistical analysis by CRD. The results indicated that the highest moisture content (13.47%), protein content (13.93%), fat content (3.39%), fiber content (7.08%), ash content (2.67%) and NFE (71.54%) were observed in lines 4220, 4158, 4149, 4193, 4233, 4220 respectively. Similarly, significant differences for β-glucan (4.99%), total dietary fiber (16.62%), soluble (6.23%) and insoluble dietary fiber contents (10.36%) were observed in barley line 4193, 4233, 4168 and 4233, respectively. The bread prepared with the addition of 5% flour to wheat flour was liked most by the judges after the control bread. The current study showed significant potential of flour to be used by baking industry for the preparation of bread and other food products by the addition of flour. 
Applications of machine learning in operational aspects of academia: a review Nadeem, Muhammad; Farag, Wael; Uykan, Zekeriya; Helal, Magdy
International Journal of Evaluation and Research in Education (IJERE) Vol 13, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v13i5.29324

Abstract

Educational institutions, propelled by digital transformation and sophisticated machine learning (ML) algorithms, amass plentiful data, facilitating the execution of complicated decision-making tasks previously inconceivable. ML’s pervasive influence extends beyond pedagogy and research, profoundly altering the fabric of academia and reshaping university functionalities. Its deployment in university administration enhances efficacy, efficiency, and operational streamlining across diverse levels. This article conducts a comprehensive review of extant knowledge pertaining to the diverse applications of ML in non-teaching domains within academic settings, delineating avenues for future research. The recognized findings furnish a robust foundation for the further exploration and refinement of ML applications, particularly within the administrative and operational realms of academia. A consequential outcome of this transformative integration is the mitigation of teachers’ administrative burdens. In practical terms, this liberation affords educators the opportunity to redirect their time and energy towards their primary responsibilities of educating and fostering the intellectual development of their students.
A comparison of approaches for modeling software security requirements using unified modeling language extensions Hassan, Syed Muhammad Junaid; Shahab, Aamir; Tabba, Fatima Ali; Alrammal, Muath; Abu-Amara, Fadi; Nadeem, Muhammad
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i3.pp2911-2927

Abstract

The unified modeling language (UML) supports extension mechanisms called stereo-types, tagged values, and constraints to extend its modeling capabilities. These extension mechanisms are utilized to create new and customized profiles. Their applications in modeling emerging security requirements are discussed. To model authentication, availability, integrity, access control, confidentiality, data integrity, non-repudiation, authorization, encryption, hashing, and session mechanisms, a set of novel stereotypes is proposed in this paper. The proposed stereotypes inherit from baseline security requirements. Further, security concepts within the UML diagram are represented using these stereotypes. In addition, the proposed stereotypes were evaluated with the help of human subject evaluation using real-world scenarios to illustrate the usefulness of these stereotypes in modelling security requirements. The contribution of this paper is a stereotyped model security requirements and library of existing security notations with high quality symbols which can be incorporated in existing and new stereotypes and diagrams to facilitate the process of security requirement modelling. Results indicate that the proposed stereotyped model improves the modeling process of security requirements. It also provides a better representation of emerging security mechanisms in software design. Finally, during the software development process, stakeholders enjoy improved communication and understanding of security requirements.
Co-Authors Abu-Amara, Fadi Ahsan, Samreen Alrammal, Muath Ammar Ahmad, Ammar Chughtai, Muhammad Farhan Jahangir Ermolaev, Vladimir Farag, Wael Gayvas, Alexei Hassan, Syed Muhammad Junaid Helal, Magdy Iskakova, Galiya Khaliq, Adnan Konovalov, Sergey Mohammad Ali Shariati Quddos, Abdul Rebezov, Maksim Shahab, Aamir Tabba, Fatima Ali Terent’ev, Sergei Tryabas, Yulia Uykan, Zekeriya