Unsupervised outlier detection in multidimensional data حسب 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 حسب 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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Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data حسب 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. …"

Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment حسب Zakaria Tolba (16904718)

"…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …"

Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning حسب 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). …"

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

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

Graph Contraction for Mapping Data on Parallel Computers حسب 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 حسب 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 حسب 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 حسب Mohammed, Omniyah Gul

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Particle swarm optimization algorithm: review and applications حسب 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 حسب 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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Intelligent Fusion of Deep Features for Improved Waste Classification حسب Kashif Ahmad (12592762)

The Effects of Data Mining on Small Businesses in Dubai حسب AlMutawa, Rasha

"…While there are numerous studies on the best data mining models and their uses, even on certain industries, this study focuses on the applications more than the algorithms and models and their usefulness for small businesses specifically. …"
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Spider monkey optimizations: application review and results حسب Abualigah, Laith

"…Optimization algorithms are applied to find efficient solutions in different problems in several fields such as the routing in wireless networks, cloud computing, big data, image processing and scheduling, and so forth. …"
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A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation حسب Khaled Dhibi (16891524)

"…The proposed approach deals with system uncertainties (current/voltage variability, noise, measurement errors, ⋯) by using an interval-valued data representation, and with large-scale systems by using a dataset size-reduction framework. …"

An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting حسب Mohamed Massaoudi (16888710)

"…First, the NARXNN model acquires the data to generate a residual error vector. Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …"

Intelligent Bilateral Client Selection in Federated Learning Using Game Theory حسب Wehbi, Osama

"…To overcome this problem, we present in this paper FedMint, an intelligent client selection approach for federated learning on IoT devices using game theory and bootstrapping mechanism. Our solution involves designing (1) preference functions for the client IoT devices and federated servers to allow them to rank each other according to several factors such as accuracy and price, (2) intelligent matching algorithms that take into account the preferences of both parties in their design, and (3) bootstrapping technique that capitalizes on the collaboration of multiple federated servers in order to assign initial accuracy value for the new connected IoT devices. …"
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Convergence behavior of the normalized least mean fourth algorithm حسب Zerguine, A.

"…Unlike the LMF algorithm, the convergence behavior of the NLMF algorithm is independent of the input data correlation statistics. …"
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