Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review by Yasir Ali (799969)

“…<div><p>Internet of Things (IoT) driven systems have been sharply growing in the recent times but this evolution is hampered by cybersecurity threats like spoofing, denial of service (DoS), distributed denial of service (DDoS) attacks, intrusions, malwares, authentication problems or other fatal attacks. …”

THE FUTURE OF MEDICINE, healthcare innovation through precision medicine: policy case study of Qatar by M. Walid Qoronfleh (14153088)

“…Consequently, the big data revolution has provided an opportunity to apply artificial intelligence and machine learning algorithms to mine such a vast data set. …”

Intelligent route to design efficient CO₂ reduction electrocatalysts using ANFIS optimized by GA and PSO by Majedeh Gheytanzadeh (17541927)

“…<p dir="ltr">Recently, electrochemical reduction of CO₂ into value-added fuels has been noticed as a promising process to decrease CO₂ emissions. …”

Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches by Mohammad, Areej Osama

Get full text

Precision nutrition: A systematic literature review by Daniel Kirk (17302798)

“…Machine learning, a subbranch of Artificial Intelligence, has promise to aid in the development of predictive models that are suitable for Precision Nutrition. As such, recent research has applied machine learning algorithms, tools, and techniques in precision nutrition for different purposes. …”

Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR) by Elaine Beller (44602)

“…Fortunately, many tasks of systematic reviews have the potential to be automated or may be assisted by automation. Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. …”

An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation by El-Maleh, Aiman H.

“…In this work, we propose a hybrid approach which uses a combination of evolutionary and deterministic algorithms for state justification. A new method based on Genetic algorithms is proposed, in which we engineer state justification sequences vector by vector. …”
Get full text

An evolutionary meta-heuristic for state justification insequential automatic test pattern generation by El-Maleh, A.H.

“…In this work, we propose a hybrid approach which uses a combination of evolutionary and deterministic algorithms for state justification. A new method based on Genetic Algorithms is proposed, in which we engineer state justification sequences vector by vector. …”
Get full text
Get full text

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma by Rawan AlSaad (14159019)

“…Recently, deep learning models have achieved state-of-the-art performance for many healthcare prediction tasks. …”

Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging by Maricar, Mohammed Farook

Get full text

Approximate XML structure validation based on document–grammar tree similarity by Tekli, Joe

“…In this paper, we propose an original method for measuring the structural similarity between an XML document and an XML grammar (DTD or XSD), considering their most common operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes (e.g., ?…”
Get full text
Get full text
Get full text
Get full text

Approximate XML structure validation technical report by Tekli, Joe

“…In this paper, we propose an original method for measuring the structural similarity between an XML document and an XML grammar (DTD or XSD), considering their most common operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes (e.g., ?…”
Get full text
Get full text
Get full text

Future Prediction of COVID-19 Vaccine Trends Using a Voting Classifier by Syed Ali Jafar Zaidi (19563178)

“…Multiple ML algorithms are used to improve decision-making at different aspects after forecasting. …”

Predicting User Behavior over the Web by Al Safadi, Amal Adnan

Get full text

The Frontiers of Deep Reinforcement Learning for Resource Management in Future Wireless HetNets: Techniques, Challenges, and Research Directions by Abdulmalik Alwarafy (17984104)

“…To this end, we carefully identify the types of DRL algorithms utilized in each related work, the elements of these algorithms, and the main findings of each related work. …”

An efficient cache replacement strategy for the hybrid cache consistency approach in a mobile environment. (c2008) by Zeitunlian, Aline Michel

Get full text
Get full text

An efficient cache replacement strategy for the hybrid cache consistency approach by Haraty, Ramzi A.

“…Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. …”
Get full text
Get full text
Get full text

CubeSat Communication Subsystems: A Review of On-Board Transceiver Architectures, Protocols, and Performance by Amr Zeedan (17983750)

“…<p dir="ltr">Small satellite communications recently entered a period of massive interest driven by the uprising commercial and civil space applications and motivated by various technological advances. …”

Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

“…In this research, we evaluate the performance of traditional machine learning algorithms and data sampling techniques for JITDP problems and compare the model performance with the performance of a DL-based prediction model. …”

ML-Based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks by Muhammad Asif Khan (7367468)

“…In this paper, we propose data-driven machine learning (ML) schemes to efficiently solve these problems in wireless LAN (WLAN) networks. …”