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Studying the commonalities, mappings and relationships between non-functional requirements using machine learning

ِAlashqar, Abdelkareem M. (Elsevier, 2022-06-01)

Studying the interactions and relationships between non-functional requirements (NFRs) is important when developing software applications. This is because that a specific NFR may conflict, overlap or complement other NFRs. ...

Arabic Poetry Authorship Attribution and Verification Using Transfer Learning

الهليس, علاء (2022-01-01)

This paper employs a transfer learning approach to attribute and validate the authorship of Arabic poetry. Poetry authorship attribution is a technique of identifying a poet from an anonymous poem related to certain traits. ...

Online Recruitment Fraud Detection using ANN

Nasser, Ibrahim M.; Alzaanin, Amjad H.; Maghari, Ashraf Yunis (Institute of Electrical and Electronics Engineers (IEEE), 2021-09)

Online recruitment provides job-seekers an efficient search and reach for jobs. It also helps recruiters searching for qualified candidates which improves the recruitment process. However, employment scam has emerged as a ...

AUTOMATIC GENERATION OF UML DIAGRAMS FROM SCENARIO-BASED USER REQUIREMENTS

Alashqar, Abdelkareem M. (ScopeMed, 2021-06-01)

Effective software modeling tools are necessary for successful achievement of software engineering activities, especially when working in the analysis and design phase. Automating these tools facilitates work, makes it ...

A Survey on the Relationships between Quality Attributes of the ISO9126 Model

Alashqar, Abdelkareem M. (International Journals of Academic Research World (IJARW), 2021-03-01)

Considering quality attributes when developing software is inevitable. Quality attributes are also known as non-functional requirement that requested by software stakeholders. ISO9126 is one of the best-known quality models ...

Sentiment Analysis of Arabic Tweets on the Great March of Return using Machine Learning

Daher, Saad Tareq; Maghari, Ashraf Yunis; Abushawish, Hussam Fares (Universiti Utara Malaysia (UUM), 2021-02-01)

Social media platforms such as Twitter and Facebook are becoming powerful sources of people’s perception of major events. Most people use social media to express their views on various issues and events and develop their ...

COVID-19 Detection from Chest X-ray Scans using Machine Learning

Eljamassi, Duaa F.; Maghari, Ashraf Yunis (Institute of Electrical and Electronics Engineers (IEEE), 2020-12)

Recently, the virus (COVID-19) has spread widely throughout the world and has led to the examination of large numbers of suspected cases using standard COVID-19 tests and has become pandemic. Everyday life, public health ...

Sentiment Analysis of Arabic Tweets Using Supervised Machine Learning

Khalid Bolbol, Noor; Maghari, Ashraf Yunis (Institute of Electrical and Electronics Engineers (IEEE), 2020-12)

The information momentum available on social media is an appropriate environment for identifying users' reactions and attitudes towards a particular topic, products, or any issues. To analyze this data and extract useful ...

COVID-19 Detection in X-ray Images using CNN Algorithm

Musleh, Areej A.wahab Ahmed; Maghari, Ashraf Yunis (Institute of Electrical and Electronics Engineers (IEEE), 2020-12)

Based on the best published research from Stanford University, the CheXNet algorithm was developed to diagnose and detect pneumonia from chest X-rays. To achieve better performance than experienced radiologists from the ...

Sentiment Analysis of Mobile Phone Products Reviews Using Classification Algorithms

Salem, Mohammed A. M.; Maghari, Ashraf Y. A. (Institute of Electrical and Electronics Engineers (IEEE), 2020-12)

Sentiment analysis or opinion mining is a process of analyzing opinions and emotions to infer the tendencies and impressions shown on the analyzed data and classify them as positive or negative. Sentiment analysis is ...