Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

“…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”

Security in wire/wireless networks: sniffing attacks prevention/detection techniques in LAN networks & the effect on biometric technology by Al-Hemairy, Moh'd Hussain

“…Based on the surprising experimental results done by a previous study in the security lab which proposed an optimal algorithm to enhance their ability against the two famous network attacks; we implemented the proposed algorithm by this study and stimulate the experiment in order to test the algorithm performance. …”
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VEGAWES: variational segmentation on whole exome sequencing for copy number detection by Samreen Anjum (19651882)

“…We tested this algorithm on synthetic data and 100 Glioblastoma Multiforme primary tumor samples. …”

Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

“…Existing methods are either applicable only to data with limited observation errors, work only for partially shuffled data, sensitive to initialization, and/or work only with small dimensions. …”
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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. …”

High-order parametrization of the hypergeometric-Meijer approximants by Abouzeid M. Shalaby (16329062)

“…<p>In this work, we introduce an extension to the hypergeometric algorithm we developed before for the resummation of divergent series.The extension overcome the time-consuming problem we face in the parametrization process of the hypergeometric approximants. …”

Improving INS/GPS Integration for Mobile Robotics Applications by AbuHashim, Tariq Salman

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Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT) by Kouatli, Issam

“…Decision making and/or Decision Support Systems (DSS) using intelligent techniques like Genetic Algorithm and fuzzy logic is becoming popular in many new applications. …”
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization by Muhammad Salman Khan (7202543)

“…For stationary sources, the proposed system gives satisfactory performance in terms of quality, intelligibility, and separation speed, and generalizes well with the test data from a mismatched speech corpus. Its perceptual evaluation of speech quality (PESQ) score is 0.55 points better than a self-supervised learning (SSL) model and almost equivalent to the diffusion models at computational cost and training data which is many folds lesser than required by these algorithms. …”

Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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Generic DFT approach for pattern sensitive faults in word-orientedmemories by Amin, A.A.

“…A novel design for testability (DFT) strategy allows efficient built-in self-testing (BIST) of WOMs. By proper selection of the memory array tiling scheme, it is possible to implement O(n) BIST algorithms which test WOMs for various types of neighbourhood pattern sensitive faults (NPSFs). …”
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The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review by Uzair Shah (15740699)

“…The study selection process was carried out in three phases: study identification, study selection, and data extraction. …”

Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)

“…<p dir="ltr">Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”

Geographical Area Network—Structural Health Monitoring Utility Computing Model by Hasan Tariq (18131842)

“…Every gateway is routing the data to SHM-UCM servers running a geo-spatial patch health assessment and prediction algorithm. …”

Clustering Tweets to Discover Trending Topics about دبي (Dubai) by ALYALYALI, SALAMA KHAMIS SALEM KHAMIS

“…One of these social networks is Twitter - a microblogging hub and rich environment of data. Scanning tweets online is a hard task and searching effortlessly to find intended topic from huge amount of data is also time consuming. …”
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A Blockchain Model for Secure Communications in Internet of Vehicles by Mershad, Khaleel

“…The simulation results demonstrated the good performance of the HPBC algorithm when implemented within the IoV environment.…”
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Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings by Ahmad Yaser Alhaddad (7017434)

“…Testing the best model with data acquired from children performing interactions with toys produced a promising performance for the shake and throw behaviours. …”

Benchmark on a large cohort for sleep-wake classification with machine learning techniques by Joao Palotti (8479842)

“…However, the largest experiments conducted to date, have had only hundreds of participants. In this work, we processed the data of the recently published Multi-Ethnic Study of Atherosclerosis (MESA) Sleep study to have both PSG and actigraphy data synchronized. …”

Improving Rule Set Based Software Quality Prediction by Azar, Danielle

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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

“…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…”