Framework for prediction and classification of non functional requirements: a novel vision

N Handa, A Sharma, A Gupta - Cluster Computing, 2022 - Springer
Requirement Engineering has radicalized data analytics by playing a pivotal role in
planning requirements strategies and activities. It has emerged as a leading domain of …

Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed

Z Shaukat, W Zafar, W Ahmad, IU Haq, G Husnain… - Healthcare, 2023 - mdpi.com
The intricate and multifaceted nature of diabetes disrupts the body's crucial glucose
processing mechanism, which serves as a fundamental energy source for the cells. This …

[PDF][PDF] Mitigating Noise in Quantum Software Testing Using Machine Learning

A Muqeet, T Yue, S Ali… - arXiv preprint cs.SE …, 2024 - web-backend.simula.no
Quantum Computing (QC) promises computational speedup over classic computing for
solving complex problems. However, noise exists in current and near-term quantum …

[PDF][PDF] Towards Aspect Based Components Integration Framework for Cyber-Physical System.

S Ali, Y Hafeez, M Bilal, S Saeed… - Computers, Materials & …, 2022 - cdn.techscience.cn
Cyber-Physical Systems (CPS) comprise interactive computation, networking, and physical
processes. The integrative environment of CPS enables the smart systems to be aware of …

FEPP: Advancing Software Risk Prediction in Requirements Engineering Through Innovative Rule Extraction and Multi-Class Integration

M Binsawad, B Khan - IEEE Access, 2024 - ieeexplore.ieee.org
The increasing complexity of software projects makes it difficult to predict risks in software
requirements, which is a crucial and essential part of the Software Development Life Cycle …

A Proposed Model for Embedding Risk Proportion in Software Development Effort Estimation

RS Dewi, YS Dharmawan - Procedia Computer Science, 2024 - Elsevier
The risk of project implementation failure has always been a primary concern for software
development team managers. Previous studies have recommended that risk should be …

[PDF][PDF] A genetic algorithm-based feature selection approach for diabetes prediction

K Kangra, J Singh - Int J Artif Intell, 2024 - pdfs.semanticscholar.org
Genetic algorithms have emerged as a powerful optimization technique for feature selection
due to their ability to search through a vast feature space efficiently. This study discusses the …

[PDF][PDF] Comparing machine learning techniques for software requirements risk prediction

YP Vera, ÁF Del Carpio - Indonesian Journal of Electrical …, 2024 - researchgate.net
Software requirements are the most critical phase focused on documenting, eliciting, and
maintaining the stakeholders' requirements. Risk identification and analysis are preemptive …

[PDF][PDF] Towards Improving the Quality of Requirement and Testing Process in Agile Software Development: An Empirical Study

I Ilays, Y Hafeez, N Almashfi, S Ali, M Humayun, M Aqib… - 2024 - cdn.techscience.cn
Software testing is a critical phase due to misconceptions about ambiguities in the
requirements during specification, which affect the testing process. Therefore, it is difficult to …

A Novel Fitting Model for Practical AIS Abnormal Data Repair in Inland River

W He, X Liu, X Chu, Z Wang, P Fracz… - Elektronika ir …, 2021 - eejournal.ktu.lt
Affected by the environment of inland waterway, an Automatic Identification System (AIS)
collects lots of abnormal data, which significantly reduces the inland river navigation …