Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

“…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …”

Data Redundancy Management in Connected Environments by Mansour, Elio

“…., building) equipped with sensors that produce and exchange raw data. Although the sensed data is considered to contain useful and valuable information, yet it might include various inconsistencies such as data redundancies, anomalies, and missing values. …”
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Unsupervised outlier detection in multidimensional data by Atiq ur Rehman (14153391)

“…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …”

Android Malware Detection Using Machine Learning by Al Ali, Shaikha

“…Detecting and preventing malware is crucial for several reasons, including the security of personal information, data loss and tampering, system disruptions, financial losses, and reputation damage. …”
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Automatic and Intelligent Stressor Identification Based on Photoplethysmography Analysis by Sami Elzeiny (16891521)

“…In particular, this study proposes a novel algorithm that first detects instances of stress and then classifies the stressor type using photoplethysmography (PPG) data from wearable smartwatches. …”

A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network by Fareed Ahmad (134672)

Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning by Zulfiqar Ali (117651)

“…This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”

Understanding key drivers affecting students’ use of artificial intelligence-based voice assistants by Hamad Al Shamsi, Jawaher

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A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm by Amirsajjad Rahmani (17541453)

Secure Storage of Crypto Wallet Seed Phrase Using ECC and Splitting Technique by Syeda Tayyaba Bukhari (21842078)

Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

“…We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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Mapping realistic data sets on parallel computers by Mansour, N.

“…The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.…”
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Parallel genetic algorithm for disease-gene association by Mansour, Nashat

“…In this work, we combine few successful strategies from the literature and present a parallel genetic algorithm for the Tag SNP Selection problem. Our results compared favorably with those of a recognized tag SNP selection algorithm using three different data sets from the HapMap project.…”
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Novel algorithms for accurate DNA base-calling by Mohammed, Omniyah Gul

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Particle swarm optimization algorithm: review and applications by Abualigah, Laith

“…The main procedure of the PSO algorithm is presented. Future researchers can use the collected data in this survey as baseline information on the PSO and PSO's applications.…”
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New enumeration algorithm for regular boolean functions by Nasrallah, Walid F.

“…This algorithm exploits the equivalence between regular Boolean functions and positive threshold functions that can be used to represent instances of the knapsack problem. …”
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Parallel Algorithm for Hardware Implementation of Inverse Halftoning by Siddiqi, Umair F.

“…The algorithm is based on Lookup Tables from which the inverse halftone value of a pixel is directly determined using a pattern of pixels. …”
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Empirical comparison of regression test selection algorithms by Mansour, Nashat

“…In the maintenance phase, the regression test selection problem refers to selecting test cases from the initial suite of test cases used in the development phase. In this paper, we empirically compare five representative regression test selection algorithms, which include: Simulated Annealing, Reduction, Slicing, Dataflow, and Firewall algorithms. …”
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Parallel algorithm for hardware implementation of inverse halftoning by Siddiqi, U.F.

“…The algorithm is based on lookup tables from which the inverse halftone value of a pixel is directly determined using a pattern of pixels. …”
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Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)