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Articles by Hassan AE
Survey of neural network methods for predicting token prices in blockchain markets
Survey of neural network methods for predicting token prices in blockchain markets 1School of Economics and Management, Beijing Jiaotong University, Beijing, China 2School of Mechanical Engineering and Automation, Northeastern University, Shenyang, China DOI 10.7717/peerj-cs.3702 Academic Editor Ashutosh Dwivedi Subject Areas Artificial Intelligence, Neural Networks, Cryptocurrency, Blockchain Keywords Cryptocurrency, Token price prediction, Neural networks, On-chain features Copyright ©...
Activation function cyclically switchable convolutional neural network model
Neural networks are one of the modeling methods that play an important role in the fields of machine learning and deep learning (Goel, Goel & Kumar, 2023). The basic building blocks of these networks are artificial neurons inspired by biological nerve cells (Montesinos López, Montesinos López & Crossa, 2022; Liu et al., 2023).
Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting?
Data leakage detection in machine learning code: transfer learning, active learning, or low-shot prompting?
Mobile app review analysis for crowdsourcing of software requirements: a mapping study of automated and semi-automated tools
Requirement engineering (RE) is a vital component of software engineering, laying the groundwork for developing successful software systems (Beecham, Hall & Rainer, 2005; Chen et al., 2024). RE involves a continuous process from the communication to modeling stages to ensure flawless implementation of software systems (Gambo & Taveter, 2021a, 2021b, 2022; Zheng et al., 2024).
A retrospective analysis of a newly proposed imaging-etiologic classification for acute ischemic stroke with large vascular occlusion based on MRI and pathogenesis
AIS stands as one of the numerous public health issues that plague the world, frequently contributing to death and disability. The TOAST classification system, a categorization framework used to evaluate stroke types and determine their underlying causes, categorizes strokes into five main categories: large artery atherosclerosis, cardioembolic stroke, small artery occlusion, strokes of other determined etiology, and strokes of undetermined etiology.
A novel deep neural network structure for software fault prediction
The development of software entails intricate planning and substantial investments of time and resources. In software systems, the presence of latent and unforeseen faults represents an inevitable challenge (Khan & Nadeem, 2023). A software fault refers to a mismatch between the expected and actual output, which ultimately fails the final product (Akimova et al., 2021). Testing is a vital activity that ensures the production of fault-free and high-quality software.
Dynamic stacking ensemble for cross-language code smell detection
Code smells refer to poor design and implementation choices by software engineers that compromise overall software quality (Yamashita & Moonen, 2013). During the software development process, there are many types of code smells that might be injected into the code, such as the following: duplicated code, large class, long method, etc.
Mining software insights: uncovering the frequently occurring issues in low-rating software applications
Mining software insights: uncovering the frequently occurring issues in low-rating software applications 1Faculty of Information Technology, Beijing University of Technology, Beijing, China 2Department of Computer Science, School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield, United Kingdom 3Faculty of Computer Science and Technology, Beijing Institute of Technology, Haidian, Beijing, China DOI 10.7717/peerj-cs.2115 Academic Editor Tzung-Pei Hong Subject...
What are developers talking about information security? A large-scale study using semantic analysis of Q&A posts
Our research carried out an in-depth analysis to identify information security-oriented issues and their descriptive dimensions. Our study has revealed important findings for understanding the current issues in the field of information security, interactions and discussions based on information security, workflows, security paradigms, and solution proposals. We now discuss these findings in detail.
Enhancing software defect prediction: a framework with improved feature selection and ensemble machine learning
Misbah Ali conceived and designed the experiments, performed the experiments, analyzed the data, performed the computation work, prepared figures and/or tables, authored or reviewed drafts of the article, writing code, and approved the final draft.
An empirical study of software ecosystem related tweets by npm maintainers
An empirical study of software ecosystem related tweets by npm maintainers 1Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, Bangladesh 2Universitas Muhammadiyah Surakarta, Surakarta, Indonesia 3Noakhali Science and Technology University, Noakhali, Bangladesh 4Universitas Jenderal Soedirman, Purwokerto, Indonesia DOI 10.7717/peerj-cs.1669 Academic Editor Kaize Shi Subject Areas Network Science and Online Social Networks, Software Engineering, Text Mining,...
Contradiction in text review and apps rating: prediction using textual features and transfer learning
The prevalence of cell phones has impacted professional and domestic lives. Millions of apps related to beauty, medical care, surveillance, fitness, education, entertainment, and so on are available to aid in different aspects of daily life. Figure 1A shows that there are over 2.67 million apps accessible on the Play Store, a platform for Android OS from Google, (Statista, 2023a) as of March 2023.
Identification of mobile development issues using semantic topic modeling of Stack Overflow posts
Identification of mobile development issues using semantic topic modeling of Stack Overflow posts Department of Management Information Systems, Faculty of Economics and Administrative Sciences, Karadeniz Technical University, Trabzon, Turkey DOI 10.7717/peerj-cs.1658 Academic Editor Luca Ardito Subject Areas Software Engineering Keywords Mobile development issues, Mobile app development, Topic modeling, Stack Overflow Copyright © Licence This is an open access article distributed under the...
Relation Between Interleukin-6, Interleukin-10 And Interleukin-2 Receptor And Mortality In Severely Ill COVID-19 Patients
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Web content topic modeling using LDA and HTML tags
Second experiment’s results and discussion The results, as depicted in Fig. 6 (where A is based on CV metric, B is based on CUMass metric, C is based on CNPMI metric, and D is based on CUCI metric), indicate that the HTM model outperforms the LDA model in terms of overall performance.
Viz LVO versus Rapid LVO in detection of large vessel occlusion on CT angiography for acute stroke
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Mechanical Thrombectomy with Intra-arterial Thrombolysis versus Mechanical Thrombectomy Alone in Patients with Acute Ischemic Stroke: A Systematic Review and Meta-Analysis - PubMed
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Python code smells detection using conventional machine learning models
Statistical test To investigate the significance of detection performance differences between ML baselines, we employed the Wilcoxon signed-rank statistical test to compare the six used ML models. In order to examine if one model significantly outperforms another model, a hypothesis test is performed. The null hypothesis states, “There is no significant difference between the classifiers.”. We set the α value to 0.05.
What issues are data scientists talking about? Identification of current data science issues using semantic content analysis of Q&A communities
Data collection and extraction To provide an objective methodology, we used a data dump that included all posts shared on data science stack exchange (DSSE), a data science-specific Q&A platform (Stack Exchange, 2022). The datasets created and analyzed during this current study are publicly available in the Internet Archive repository (Internet Archive, 2022) as a data dump in XML format.
Trial of Endovascular Thrombectomy for Large Ischemic Strokes
Abstract Background: Trials of the efficacy and safety of endovascular thrombectomy in patients with large ischemic strokes have been carried out in limited populations. Methods: We performed a prospective, randomized, open-label, adaptive, international trial involving patients with stroke due to occlusion of the internal carotid artery or the first segment of the middle cerebral artery to assess endovascular thrombectomy within 24 hours after onset.
Software evolution: the lifetime of fine-grained elements
Introduction Although there is a significant body of work regarding the macroscopic characteristics (González-Barahona et al., 2009) and even laws (Lehman, 1980) of software evolution (Herraiz et al., 2013), much less is known about how software evolves at the microscopic scale, namely at the level of lines, statements, expressions, and individual tokens.
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