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Topics in graph algorithms
Published 2003“…This is achieved by implementing some algorithms for the vertex cover problem, and conducting experiments on real data sets. …”
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masterThesis -
44
Three-phase approach for curriculum-based course timetabling problem. (c2012)
Published 2012Subjects: “…Scheduling -- Data processing…”
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masterThesis -
45
A fast exact sequential algorithm for the partial digest problem
Published 2016“…Two types of simulated data, random and Zhang, are used to measure the efficiency of the algorithm. …”
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Software defect prediction. (c2019)
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masterThesis -
47
RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems.
Published 2020“…Our main contributions are: (i) a mechanism based on graph transformations to explore alternative execution strategies; (ii) a novel graph-based approach to determine efficient data movement plans among subtasks and platforms; and (iii) an efficient plan enumeration algorithm, based on a novel enumeration algebra. …”
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Improved search-tree algorithms for the cluster edit problem. (c2011)
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masterThesis -
49
Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data
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doctoralThesis -
50
Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining
Published 2021“…An integrated web application is developed to mock up the end-to-end process in ecommerce. Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …”
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Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
Published 2020“…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …”
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Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic
Published 2021“…Therefore, big data analytics field emerged to tame the generated big data, and use it to provide useful insights to the world. …”
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Sentiment analysis for Arabizi in social media. (c2015)
Published 2015“…We took the initiative to make use of this abundance of data by analyzing it and predicting sentiment. …”
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masterThesis -
54
Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…We present the new framework for the detection of cyberattacks, which makes use of AI and ML. We begin a process to cleaning up the data in the CPS database by applying normalization to eliminate errors and duplication. …”
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Allocation and re-allocation of data in a grid using an adaptive genetic algorithm
Published 2006“…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …”
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conferenceObject -
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Bee Colony Algorithm for Proctors Assignment.
Published 2015“…The Bee Colony algorithm is a recent population-based search algorithm that mimics the natural behavior of swarms of honey bees during the process of collecting food. …”
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Mapping realistic data sets on parallel computers
Published 1993“…The GC algorithm allows large-scale mapping to become efficient, especially when slow but high-quality mappers are used.…”
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conferenceObject -
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A novel encryption algorithm using multiple semifield S-boxes based on permutation of symmetric group
Published 2023“…The presented algorithm is mainly based on the Shannon idea of substitution–permutation network where the process of substitution is performed by the proposed S<sub>8</sub> semifield substitution boxes and permutation operation is performed by the binary cyclic shift of substitution box transformed data. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images
Published 2022“…Over the decade, numerous artificial neural network (ANN)-based techniques were adopted in order to diagnose and classify breast cancer due to the unique characteristics of learning key features from complex data via a training process. However, these schemes have limitations like slow convergence and longer training time. …”