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17
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Introduction
Computer Scientist
Current institution
Education
January 2019 - January 2021
Publications
Publications (17)
Quantum computing is revolutionizing various fields, including operations research and queueing theory. This study presents a quantum method for simulating single-server Markovian (M/M/1) queues, making quantum computing more accessible to researchers in operations research. We introduce a dynamic amplification approach that adapts to queue traffic...
Clustering techniques are convenient tools for preparing and organizing unstructured and unclassified data. Depending on the data, they can be used to prepare for an analysis or to gain insight. However, choosing a clustering technique can be challenging when dealing with high-dimensional datasets. Most often, application requirements and data dist...
Data is essential for an organization to develop and make decisions efficiently and effectively. Machine learning classification algorithms are used to categorize observations into classes. The Naive Bayes (NB) classifier is a classification algorithm based on the Bayes theorem and the assumption that all predictors are independent of one another....
Quantum computing is a new and exciting field with the potential to solve some of the world’s most challenging problems. Currently, with the rise of quantum computers, the main challenge is the creation of quantum algorithms (under the limitations of quantum physics) and making them accessible to scientists who are not physicists. This study presen...
A substantial portion of global quantum computing research has been conducted using quantum mechanics, which recently has been applied to quantum computers. However, the design of a quantum algorithm requires a comprehensive understanding of quantum mechanics and physical procedures. This work presents a quantum procedure for estimating information...
Machine learning algorithms may have difficulty processing datasets with missing values. Identifying and replacing missing values is necessary before modeling the prediction for missing data. However, studies have shown that uniformly compensating for missing values in a dataset is impossible, and no imputation technique fits all datasets. This stu...
In today's world, data is essential for enhancing an organization's development and decision‐making processes. Implementing artificial intelligence is necessary to analyse data and make meaningful recommendations. Machine learning distance classification methods are used to classify observations in various algorithms, such as K‐nearest neighbours (...
A significant part of global quantum computing research has been conducted based on quantum mechanics, which can now be used with quantum computers. However, designing a quantum algorithm requires a deep understanding of quantum mechanics and physics procedures. This work presents a generic quantum “black box” for entropy calculation. It does not d...
An organization needs data to develop, maintain, and build intelligence systems. Creating recommendations based on AI procedures is critical when the data contains multiple features. However, reducing the number of features is a significant challenge to improve a model's accuracy and reduce multicollinearity when developing a descriptive or predict...
Anomaly detection is often used to identify and remove outliers in datasets. However, detecting and analyzing the pattern of outliers can contribute to future business decisions or increase the accuracy of a learning algorithm. Selecting the applicable outlier detection method for a dataset requires human intervention and analysis due to the challe...
As the technology domain overgrows, web platforms become a strong and powerful tool for development, collaboration , teamwork, and research. The goal of collaborative web platforms is to foster innovation by incorporating knowledge into processes, so the community can share information and solve problems more efficiently. In this work, we present t...
Music technology is known to have the ability to enhance creativity and creative development among students. A high level of engagement has been shown among students who studied and developed musical projects, and among students who were intellectually involved in the process of meaningful exploration. When students develop a music technology proje...
