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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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)

Spider monkey optimizations: application review and results by 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 by 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. …”

Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique by Iqbal Hassan (22155274)

“…In this study, we harnessed the capabilities of a four-channel, wearable EEG device that captured brain activity data during two distinct CL states: Baseline (representing a non-CL, resting state) and the Stroop Test (a CL-inducing state). …”

An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting by 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. …”

A method for efficient NoC test scheduling using deterministic routing by Harmanani, Haidar

“…This paper presents a method for NoCs test scheduling using simulated annealing. The method uses a deterministic routing algorithm that minimizes test time while avoiding blocking. …”
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An Evolutionary Meta-Heuristic for State Justification in Sequential Automatic Test Pattern Generation by El-Maleh, Aiman H.

“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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An evolutionary meta-heuristic for state justification insequential automatic test pattern generation by El-Maleh, A.H.

“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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An Iterative Heuristic for State Justi�cation in Sequential Automatic Test Pattern Generation by El-Maleh, Aiman H.

“…State justifcation is one of the most time-consuming tasks in sequential Automatic Test Pattern Generation (ATPG). For states that are difficult to justify, deterministic algorithms take significant CPU time without much success most of the time. …”
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Intelligent Bilateral Client Selection in Federated Learning Using Game Theory by 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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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…As a function of the proposed objective, ensembling algorithms applicable to network security have been investigated and evaluated, and a methodology for detecting infected PAGE 2 hosts using ensembling has been developed, based on experiments designed and tested with real datasets. …”
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Malware detection for mobile computing using secure and privacy-preserving machine learning approaches: A comprehensive survey by Faria Nawshin (21841598)

Convergence behavior of the normalized least mean fourth algorithm by 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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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms by Ghulam Mustafa (458105)

“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”

Evolutionary algorithm for predicting all-atom protein structure by Mansour, Nashat

“…We present an improved version of a scatter search (SS) algorithm for predicting all-atoms protein structures using a recent energy model. …”
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Three-phase simulated annealing algorithms for exam scheduling by Mansour, Nashat

“…We empirically compare 3PSA with a 4-phase clustering-based heuristic algorithm using realistic data. Our experimental results show that 3PSA produces good exam schedules, which are better than those of the clustering heuristic procedure.…”
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Recent Advances of Chimp Optimization Algorithm: Variants and Applications by Daoud, Mohammad Sh.

“…Chimp Optimization Algorithm (ChOA) is one of the recent metaheuristics swarm intelligence methods. …”
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