Papers by Munther Abualkibash
User Acceptance of Smart Mobile Resources in Vehicular Technologies Based Upon User Experience and Comfortability: A Research Review
Machine learning is the current hot topic in the technology industry with many seeing what potent... more Machine learning is the current hot topic in the technology industry with many seeing what potential uses it has across many different fields. One such potential application is in a specific subset of smart mobility, resource optimization. This paper analyzes the use of machine learning techniques to optimize the performance and design of batteries and engines. By analyzing other works a generalized overview of the topic is achieved alongside suggestions for future research.
The purpose of this paper is to cover the many different pieces of research that have come out in... more The purpose of this paper is to cover the many different pieces of research that have come out in the last six years. By classifying the topics covered in these papers, and then analyzing the contents and suggestions made by them, this paper offers a conglomeration of the information stored to help others plan future research in the field. Analysis of how certain proposed solutions work, and how their results are achieved is also done with some real-world statistics. Using all this information, examples of future research into smart mobility are given based on the information parsed in the making of this paper.
Zenodo (CERN European Organization for Nuclear Research), Sep 26, 2023
This paper analyses ChatGPT 3.5 Turbo, the latest free version of the ChatGPT service. By using C... more This paper analyses ChatGPT 3.5 Turbo, the latest free version of the ChatGPT service. By using ChatGPT to create theoretical papers on itself, further insights are gained into the potential of ChatGPT and other generative artificial intelligence services as well as their weaknesses. Through this analysis presented, potential future avenues of research are suggested alongside necessary changes if services like ChatGPT wish to be used as a tool in academic works.
Integrating Art and Animation in Teaching Computer Programming for High School Students Experimental Study
This paper discusses the results of an experimental study that was conducted to explore the effec... more This paper discusses the results of an experimental study that was conducted to explore the effect of integrating art and animation in teaching computer programming on high school students' interest and knowledge in programming. The study aimed to explore the students' interest in pursuing a degree in Computer Science (CS) after graduation. Three groups of high school students were targeted with educational programming sessions, and the study variables were measured through pre and posttest surveys. A new web-based programming tool was developed and used as the treatment in this study. The developed tool includes the use of art, animation and code sharing to increase students' motivation in learning computer programming. The results of the study showed that the use of art, animation and code sharing increased students' knowledge, enjoyment, and motivation in learning computer programming, and hence, increased their interest in pursuing a degree in CS after graduation.
International Journal of Computer Science and Information Technology, Jun 29, 2019
Intrusion Detection System (IDS) has been an effective way to achieve higher security in detectin... more Intrusion Detection System (IDS) has been an effective way to achieve higher security in detecting malicious activities for the past couple of years. Anomaly detection is an intrusion detection system. Current anomaly detection is often associated with high false alarm rates and only moderate accuracy and detection rates because it's unable to detect all types of attacks correctly. An experiment is carried out to evaluate the performance of the different machine learning algorithms using KDD-99 Cup and NSL-KDD datasets. Results show which approach has performed better in term of accuracy, detection rate with reasonable false alarm rate.
Detecting Phishing Websites Based on Machine Learning Techniques
Lecture notes in networks and systems, 2023
Improved pruning algorithms in multiscale real-time object detection
Object detection is an important area of research in computer vision. One of the most popular app... more Object detection is an important area of research in computer vision. One of the most popular approaches for object detection is based on combining many weak classifiers together to achieve one strong classifier through a technique called Boosting. A modified version of this technique for real-time face detection was developed by Viola and Jones, where a weak classifier is created by iteratively selecting a best single feature from a set of a very large number of potential features. During the detection process, there is a need to apply pruning techniques on the candidate results from different scales to eliminate the weak candidates and keep the most promising one. This paper presents improved pruning algorithms that result in reducing the number of false positives. For object detection, a complete framework is implemented based on Viola and Jones, then the proposed pruning algorithms are applied to obtain better detection results.
The Theory of Planned Behavior and High School Students Interest in Computer Science
In this paper, the three variables suggested by the theory of planned behavior were examined to f... more In this paper, the three variables suggested by the theory of planned behavior were examined to find if they can be used as predictors for the high school students' interest in a Computer Science (CS) degree. A survey questionnaire was developed and tested for its validity, and then it was used to collect data from 65 high school students to find if there is any relationship between the students' interests in a CS degree and the three suggested variables. Students' gender was the moderating variable in the data analysis. The results show that two variables can be used as predictors for female students' interest, and only one predictor for male students' interest.
International Journal of Artificial Intelligence & Applications, May 30, 2019
Network intrusion detection often finds a difficulty in creating classifiers that could handle un... more Network intrusion detection often finds a difficulty in creating classifiers that could handle unequal distributed attack categories. Generally, attacks such as Remote to Local (R2L) and User to Root (U2R) attacks are very rare attacks and even in KDD dataset, these attacks are only 2% of overall datasets. So, these result in model not able to efficiently learn the characteristics of rare categories and this will result in poor detection rates of rare attack categories like R2L and U2R attacks. We even compared the accuracy of KDD and NSL-KDD datasets using different classifiers in WEKA.
International journal of integrating technology in education, Jun 30, 2021
With divergent educational processes brought forth through the unforeseen circumstances such as a... more With divergent educational processes brought forth through the unforeseen circumstances such as a global pandemic, students have become obligated to pursue virtual means towards obtaining their education. Therefore, this study seeks to review the different formats of virtual learning processes and methodologies that are currently made available to students based on student and user perception and technology adoption efforts. Through comparative analysis efforts identifying synchronous, hybrid and asynchronous virtual educational standards across multiple publications and understanding technology acceptance models (TAM) and theories such as perceived usefulness, it is understood that virtual learning efforts which pursue an asynchronous methodology are more comparable in contrast other formats.
Taekwondo Poomsae performance is a series of basic movements for offense and defense techniques. ... more Taekwondo Poomsae performance is a series of basic movements for offense and defense techniques. Despite the high popularity and long history of Taekwondo, there has been less effort to systemize Taekwondo Poomsae competition. In this paper, we propose a hierarchical approach to landmarks detection in Taekwondo Poomsae videos, which is a significant change in a series of movements. First, we propose a kinematic model for basic Poomsae movements based on the anatomic analysis of player's body parts. Second, we measure a player's movement from a Poomsae video using changed pixels. Third, we segment a Poomsae video into a number of movements, each of which contains the same semantic, i.e., basic Poomsae movement. Since the initial segments are usually oversegmented, we classify the segmented movements into higher level that represent significant movements of Poomsae performance. Finally, we identify landmarks from the created movement hierarchy. The experimental results show that the 70% of landmarks are detected correctly.
Emerging Research in the Security of Modern and Autonomous Vehicles
The last decade has witnessed considerable advancements in automating modern “connected” and Auto... more The last decade has witnessed considerable advancements in automating modern “connected” and Autonomous Vehicles (AVs), which are becoming an integral part of the modern transportation systems. Such advancements have been attributed to major strides in Machine Learning, Artificial Intelligence and processing technology. More importantly, the complexity of such systems and their lack of built-in security have brought to the spotlight the need for extensive research to understand the associated risks and propose mitigations for them. In this paper we briefly discuss the security aspects of modern vehicles and provide a concise literature review of the work that has been done in this domain. We focus on specific areas that are of interest to us and conclude by providing a plan for future related endeavors.
International journal of network security and applications, Sep 30, 2019
Machine learning has more and more effect on our every day's life. This field keeps growing and e... more Machine learning has more and more effect on our every day's life. This field keeps growing and expanding into new areas. Machine learning is based on the implementation of artificial intelligence that gives systems the capability to automatically learn and enhance from experiments without being explicitly programmed. Machine Learning algorithms apply mathematical equations to analyze datasets and predict values based on the dataset. In the field of cybersecurity, machine learning algorithms can be utilized to train and analyze the Intrusion Detection Systems (IDSs) on security-related datasets. In this paper, we tested different machine learning algorithms to analyze NSL-KDD dataset using KNIME analytics.
A Classifier to Detect Number of Machines Performing DoS Attack Against Arduino Oplà Device in IoT Environment
Parallel and Distributed Object Recognition
Object detection, such as face detection using supervised learning, often requires extensive trai... more Object detection, such as face detection using supervised learning, often requires extensive training for the computer, which results in high execution times. If the trained system needs retraining in order to accommodate a missed detection, waiting several hours or days before the system is ready may be unacceptable in practical implementations. This dissertation presents a generalized object detection framework vii TABLE OF CONTENTS
A Survey of Traffic Sign Recognition Systems Based on Convolutional Neural Networks
In this paper, we briefly discuss the applications of Convolutional Neural Networks (CNNs) model ... more In this paper, we briefly discuss the applications of Convolutional Neural Networks (CNNs) model to traffic sign recognition (TSR) systems. Traditionally, the TSRs have used different techniques to detect and classify visual data. The CNN s have been used separately to extract features and train the classifier as well as simultaneously for detection and classification tasks. One model that has been successful is the Fast Branch CNN model, which imitates biological mechanisms to become more efficient. While it is not the most accurate of the ones presented in this paper, the efficiency it exhibits under time-sensitive conditions is worth exploring because of the potential applications of such technology. The Fast Branch CNN model challenged the assumptions of past models, and this technology can only advance further if new models attempt to do the same.
International Journal of Computer Science and Information Technology
This paper analyses ChatGPT 3.5 Turbo, the latest free version of the ChatGPT service. By using C... more This paper analyses ChatGPT 3.5 Turbo, the latest free version of the ChatGPT service. By using ChatGPT to create theoretical papers on itself, further insights are gained into the potential of ChatGPT and other generative artificial intelligence services as well as their weaknesses. Through this analysis presented, potential future avenues of research are suggested alongside necessary changes if services like ChatGPT wish to be used as a tool in academic works.
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Papers by Munther Abualkibash