Auto-indexing Arabic texts based on association rule data mining. (c2015) by Rouba G. Nasrallah

“…Our model denotes extracting new relevant words by relating those chosen by the previous classical methods, to new words using data mining rules. The model uses the Apriori Algorithm - an association rule algorithm for extracting frequent sets containing related items - to extract relations between words in the texts to be indexed with words from texts that belong to the same category. …”
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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data by Arshad, Muhammad Arbab

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Optimal supercharge scheduling of electric vehicles by Atallah, Ribal F.

“…The distributed game-theoretical approach recorded promising results especially when compared to the well-known shortest job first scheduling algorithm. Further, unlike the other approaches, which normally are centralized and suited for offline scheduling, the game-based method is suited for online scheduling since it played at anytime a batch of EVs requests charging services. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing by Jincheng Zhou (1887307)

“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”

Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining by Alqaryouti, Omar

“…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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An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems by Boukhari, Bahia

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Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm? by Saravanan Thirumuruganathan (11038038)

“…The resulting model achieves an 89% predictive accuracy using historical data. A unique aspect of the model is the incorporation of self-competence, where the model defers when it cannot reasonably make a recommendation. …”

Prediction of EV Charging Behavior Using Machine Learning by Shahriar, Sakib

“…Using data-driven tools and machine learning algorithms to learn the EV charging behavior can improve scheduling algorithms. …”
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Predicting Patient ICU Readmission Using Recurrent Neural Networks With Long Short-Term Memory by Nadia Rasheed (22997257)

Scalable parallel algorithms for dynamic programming on tree decomposition. (c2017) by Yassine, Mohamad M.

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Final exams scheduling for univeristies. (c2001) by Timany, Mazen Nuhad

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MAESTRO: Orchestrating Computational Offloading to Multiple FemtoClouds in Various Communication Environments by Hend Gedawy (23275984)

“…For MAESTRO, we build an integrated architecture that includes two new scheduling algorithms for assigning computing workloads to FemtoClouds. …”

Exploring Sentiment Analysis using Different Machine Learning Algorithms on Dialectal Arabic by AL MANSOORI, MOUZA

“…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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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems by Almajed, Rasha

“…There are a variety of ways in which AI technology can aid in the growth and profitability of a variety of industries. Such data can be parsed using ML and AI approaches in designed to check attacks on CPSs. …”
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Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms by Almahmood, Mothanna

“…Our study aimed to use data mining classification techniques, in order to classify the individual into two categories: user or non-user. …”
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Chlorophyll-a concentrations in the Arabian Gulf waters of arid region: A case study from the northern coast of Qatar by Sankaran, Rajendran

“…The performance of the algorithms was studied using WorldView-3 data, which provided the R2 values of 60% and the best suitability of the NDCI algorithm and MSI data to map the concentration of Chl-a. …”
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The Relation Between Respiratory & Acute Coronary Syndrome Using Data Mining Techniques by DOULEH, HANI ABDULLAH YOSEF ABU

“…The purpose of this study is to diagnose acute coronary syndrome using the widely available respiratory diagnosing tools and laboratory test results using data mining classification techniques (Decision tree, Gradient boosted tree, Neural Network, and Naïve Bias). …”
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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Alg... by Ali S. Alghamdi (12722891)

“…In this paper, the scheduling and management framework of an energy hub (EH) is presented with the aim of energy profit maximization in partnership with electricity, natural gas, and district heating networks (EGHNs) considering the coordinated multi-energy management based on the day-ahead market. …”

Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm by Ali S. Alghamdi (17541711)

“…The proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO, particle swarm optimization (PSO), and salp swarm algorithm (SSA). …”