Other Computer Sciences Commons^™

Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury

Dissertations

The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …

Stop Blaming My Users: Illumination Of The Technocentric Mythos Bias, Ervin H. Frenzel, Richard Lightcap

Journal of Cybersecurity Education, Research and Practice

 Abstract -This conceptual essay addresses the need for systemic and systematic transdisciplinary analytical techniques within cybersecurity and technical security. This conceptual essay is contingent upon recognition that cybersecurity is not simply technical in nature, it does not need an adversary, and more importantly it is based upon systems engineering and systems thinking.  The essay contributes a socio-technical attribution chain and field-specific ontology/taxonomy which distinguish user-triggered events from root causes, latent conditions, technical debt, validation failures, governance failures, and attribution bias before assigning responsibility to end users. It systematically defines an ontology inclusive of developer technical debt, organizational debt arising from …

Optimizing Information Security In Cloud Environments: A Risk Management Approach And Guide For Enterprise Cloud Security, Joshua Olusegun Oyeniyi, Oluwashina Akinloye Oyeniran

Journal of Cybersecurity Education, Research and Practice

In recent years, cloud computing has become increasingly integral to organizational operations due to its scalability, accessibility and cost effectiveness in managing data and resources. However, the rise in security threats and attacks on cloud environments necessitates having robust measures in place to protect data confidentiality, integrity and availability. This paper presents an optimized approach to cloud information security management by reviewing the current threat landscape, evaluating key risk management frameworks, and provided practical solutions for enhancing enterprise cloud security. The study examined three leading cloud security frameworks: the Cloud Controls Matrix (CCM) known for its cloud-specific controls, the NIST …

Real-Time Feedback-Driven Framework For Automated Cybersickness Mitigation, Md Jahirul Islam

Master's Theses

As technologies are becoming more advanced day by day, the embracement of virtual reality (VR) technology among users is also increasing in daily activities for various purposes, and subsequently, the barrier between the real and virtual world is fading. Despite the versatile uses, cybersickness (CS) is a major problem which is induced among users due to the immersive VR experience. There is a plethora of research findings and methods to measure the users’ CS such as virtual reality sickness questionnaire (VRSQ), simulator sickness questionnaire (SSQ), fast motion scale questionnaire (FMS), and others. Recently, machine learning approaches have also been adopted …

The Use Of Social Media For Organisational Learning: A Systematic Review Of Literature, Harry Moongela, Marie Hattingh

African Conference on Information Systems and Technology

Social media (categorised as Web 2.0 platforms) has been reported to significantly impact and improve organisational learning (OL), but there seems to be a lack of systematic literature reviews (SLR) covering the use of social media to facilitate OL. Thus, this article conducted a SLR for both social media and OL by presenting the significant concepts, models and frameworks from literature. A total number of 48 articles were found for the analysis method and the findings reveal important concepts such as types of OL, levels of OL and frameworks incorporating both social media and OL. The results also show that …

Factors Influencing The Perceptions Of Human-Computer Interaction Curriculum Developers In Higher Education Institutions During Curriculum Design And Delivery, Cynthia Augustine, Salah Kabanda

The African Journal of Information Systems

Computer science (CS) and information systems students seeking to work as software developers upon graduating are often required to create software that has a sound user experience (UX) and meets the needs of its users. This includes addressing unique user, context, and infrastructural requirements. This study sought to identify the factors that influence the perceptions of human-computer interaction (HCI) curriculum developers in higher education institutions (HEIs) in developing economies of Africa when it comes to curriculum design and delivery. A qualitative enquiry was conducted and consisted of fourteen interviews with HCI curriculum developers and UX practitioners in four African countries. …

Adapting An Online Learning Quality Assurance Framework In A Developing Country Setting: The Case Of A Hei In Malawi, Bennett Kankuzi, Menard Phiri, Robert Chanunkha, Jonathan Makuwira, Paul Makocho

African Conference on Information Systems and Technology

Covid-19 prompted many higher education institutions (HEIs), even in developing countries like Malawi, to abruptly shift from their traditional face-to-face mode of delivery to online learning. However, quality issues with online learning remain one of the greatest challenges to acceptance of online learning by many students and stakeholders. This paper presents an action research based study at the Malawi University of Science and Technology, in which an online learning quality assurance framework is adapted to a developed country setting. The adapted framework builds on the Online Learning Consortium (OLC) Quality Scorecard for the Administration of Online Programs. The contextualization and …

Characterization Of End-Users’ Engagement And Interaction Experience With Social Media Technologies, Yemisi Oyedele, Darelle Van Greunen

African Conference on Information Systems and Technology

People, particularly digital citizens, gain more technological experiences from their frequent usage of social media technologies. Their experience as end-users occurs before, during, and after their engagement and interaction with the technologies and is popularly described using behaviour-related definitions. However, an end-user's experience with technologies goes beyond the 'click-and-type" definition. This prompts the question, "what are the user experience elements that define and characterise end-users' engagement and interaction with social media technologies?". Using a case study-based approach, end-users' engagement and interaction with social media technologies were identified. The study's findings indicated that several user experience elements were characterised by emotions, …

An Empirical Study Of Thermal Attacks On Edge Platforms, Tyler Holmes

Symposium of Student Scholars

Cloud-edge systems are vulnerable to thermal attacks as the increased energy consumption may remain undetected, while occurring alongside normal, CPU-intensive applications. The purpose of our research is to study thermal effects on modern edge systems. We also analyze how performance is affected from the increased heat and identify preventative measures. We speculate that due to the technology being a recent innovation, research on cloud-edge devices and thermal attacks is scarce. Other research focuses on server systems rather than edge platforms. In our paper, we use a Raspberry Pi 4 and a CPU-intensive application to represent thermal attacks on cloud-edge systems. …

Energy Saving On Edges: State-Of-The-Art And Future Directions, Kousalya Banka

Symposium of Student Scholars

Internet of Things (IoT) comprises a set of devices that are interconnected ranging from our daily used objects to advanced networked devices. It is a constantly evolving phenomenon as the number of devices owned by the regular user is increasing at a rapid rate. These devices are used for various reasons such as social networking, monitoring, performing complex operations and with the increase of advanced technologies, they demand more energy to perform such tasks. Cloud computing enables these communications to seamlessly perform complex tasks in a cloud environment but utilizing these resources properly to perform at the best is the …

Characterizing The Vibrational Spectra Of Hydrogen Bonded Systems With Molecular Dynamics Simulations And Quantum Chemical Methods, Dalton Boutwell

Master of Science in Chemical Sciences Theses

We apply and assess the utility of DMD for the purpose of investigating complex spectral features in N₂H⁺···OC, N₂D⁺···OC, C₂O₄H^-, C₂O₄D^- and (HCOOH)₂. The proton transfer as a vibrational motion consists of diffuse qualities that can be accounted for with classical and quantum chemical analyses. Classical approaches yield a wealth of information about vibrational spectra at a reduced cost, as in the case of previously investigated N₄H⁺. The isoelectronic N₂H⁺···OC has …

Profile Modeling In Hierarchical Deep Architecture By Mutual Support, Honglai Peng, Meng Han, Jing (Selena) He

Master of Science in Computer Science Theses

Despite significant advances in the field of face analysis over last decade, the current studies are still limited to specific face computation tasks using deep learning approaches. In this paper, we propose an end-to-end hierarchical deep learning structure, called Multi-Features Convolutional Neural Networks (MFCNN), which can comprehensively implement face analysis including age, gender, race and emotion. Moreover, we take the advantages of the mutual support among different facial features from individual tasks to improve the performance of our model. We also contribute one all-labeling dataset called Multiple Facial Features Computation (MFFC) based on Apparent-age-V2 dataset. Firstly, we train four different …

Fast Clustering Using A Grid-Based Underlying Density Function Approximation, Daniel Brown

Master of Science in Computer Science Theses

Clustering is an unsupervised machine learning task that seeks to partition a set of data into smaller groupings, referred to as “clusters”, where items within the same cluster are somehow alike, while differing from those in other clusters. There are many different algorithms for clustering, but many of them are overly complex and scale poorly with larger data sets. In this paper, a new algorithm for clustering is proposed to solve some of these issues. Density-based clustering algorithms use a concept called the “underlying density function”, which is a conceptual higher-dimension function that describes the possible results from the continuous …

Ordinal Hyperplane Loss, Bob Vanderheyden

Doctor of Data Science and Analytics Dissertations

This research presents the development of a new framework for analyzing ordered class data, commonly called “ordinal class” data. The focus of the work is the development of classifiers (predictive models) that predict classes from available data. Ratings scales, medical classification scales, socio-economic scales, meaningful groupings of continuous data, facial emotional intensity and facial age estimation are examples of ordinal data for which data scientists may be asked to develop predictive classifiers. It is possible to treat ordinal classification like any other classification problem that has more than two classes. Specifying a model with this strategy does not fully utilize …

On The Yellow Brick Road, A Path To Enterprise Architecture Maturity, Avsharn Bachoo

The African Journal of Information Systems

This study concentrated on the relationship between the Enterprise Architecture (EA) maturity of an organization and the business value associated with it in the South African financial services environment. It was developed within the critical realism philosophy, which states that mechanisms generate events by accentuating the underlying EA mechanisms that lead to business value, as well as provide insights into the opportunities and challenges organizations experienced as they progressed to higher levels of maturity. Constructed using the resource-based view of the firm as the underlying theoretical framework, this research examined EA as an intangible resource and maturity as a source …

Improvement Of Decision On Coding Unit Split Mode And Intra-Picture Prediction By Machine Learning, Wenchan Jiang

Master of Science in Computer Science Theses

High efficiency Video Coding (HEVC) has been deemed as the newest video coding standard of the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The reference software (i.e., HM) have included the implementations of the guidelines in appliance with the new standard. The software includes both encoder and decoder functionality.

Machine learning (ML) works with data and processes it to discover patterns that can be later used to analyze new trends. ML can play a key role in a wide range of critical applications, such as data mining, natural language processing, image recognition, and expert systems. …

An Adapted Framework For Environmental Sustainability Reporting Using Mobile Technologies, Andre P. Calitz, Jaco F. Zietsman

The African Journal of Information Systems

Corporate governance is the process by which organisations are directed and controlled. King IV is regarded as the cornerstone of corporate governance for businesses and emphasises the importance of sustainability reporting in South Africa. Sustainability reporting guidelines inform organisations how to disclose their most critical affects on the environment, society and the economy. The Global Reporting Initiative (GRI) G4 sustainability reporting framework recommends the Standard Disclosures that all organisations should use to report their sustainability impacts and performance. Sustainability reporting frameworks proposed for the Higher Education sector require reporting principles specific to the needs of Higher Education Institutions (HEIs). The …

A Multiple Classifier System For Predicting Best-Selling Amazon Products, Michael Kranzlein

Master of Science in Computer Science Theses

In this work, I examine a dataset of Amazon product metadata and propose a heterogeneous multiple classifier system for the task of identifying best-selling products in multiple categories. This system of classifiers consumes the product description and the featured product image as input and feeds them through binary classifiers of the following types: Convolutional Neural Network, Na¨ıve Bayes, Random Forest, Ridge Regression, and Support Vector Machine. While each individual model is largely successful in identifying best-selling products from non best-selling products and from worst-selling products, the multiple classifier system is shown to be stronger than any individual model in the …

Analyzing Http Requests For Web Intrusion Detection, Sara Althubiti, Xiaohong Yuan, Albert Esterline

KSU Proceedings on Cybersecurity Education, Research and Practice

Many web application security problems related to intrusion have resulted from the rapid development of web applications. To reduce the risk of web application problems, web application developers need to take measures to write secure applications to prevent known attacks. When such measures fail, it is important to detect such attacks and find the source of the attacks to reduce the estimated risks. Intrusion detection is one of the powerful techniques designed to identify and prevent harm to the system. Most defensive techniques in Web Intrusion Systems are not able to deal with the complexity of cyber-attacks in web applications. …

Color Image Segmentation Using The Bee Algorithm In The Markovian Framework, Vehbi Dragaj

Master of Science in Computer Science Theses

This thesis presents color image segmentation as a vital step of image analysis in computer vision. A survey of the Markov Random Field (MRF) with four different implementation methods for its parameter estimation is provided. In addition, a survey of swarm intelligence and a number of swarm based algorithms are presented. The MRF model is used for color image segmentation in the framework. This thesis introduces a new image segmentation implementation that uses the bee algorithm as an optimization tool in the Markovian framework. The experiments show that the new proposed method performs faster than the existing implementation methods with …

Internet Of Things-Based Smart Classroom Environment, Amir R. Atabekov

Master of Science in Computer Science Theses

Internet of Things (IoT) is a novel paradigm that is gaining ground in the Computer Science field. There’s no doubt that IoT will make our lives easier with the advent of smart thermostats, medical wearable devices, connected vending machines and others. One important research direction in IoT is Resource Management Systems (RMS). In the current state of RMS research, very few studies were able to take advantage of indoor localization which can be very valuable, especially in the context of smart classrooms. For example, indoor localization can be used to dynamically generate seat map of students in a classroom. Indoor …

Tapjacking Threats And Mitigation Techniques For Android Applications, Vanessa Cooper

Dissertations, Theses and Capstone Projects

With the increased dependency on web applications through mobile devices, malicious attack techniques have now shifted from traditional web applications running on desktop or laptop (allowing mouse click- based interactions) to mobile applications running on mobile devices (allowing touch-based interactions). Clickjacking is a type of malicious attack originating in web applications, where victims are lured to click on seemingly benign objects in web pages. However, when clicked, unintended actions are performed without the user’s knowledge. In particular, it is shown that users are lured to touch an object of an application triggering unintended actions not actually intended by victims. This …

Hybrid Spread-Spectrum Tcp For Combating Fraudulent Cyber Activities Against Reconnaissance Attacks, Simon Enoch Yusuf, Olumide Longe

The African Journal of Information Systems

The inefficiencies of current intrusion detection system against fraudulent cyber activities attracts the attention of computer gurus, also known as “hackers” to exploit known weakness on a particular host or network. These hackers are expert programmers who mainly focus on how the Internet works, and they interact with each other to know its strengths and weaknesses. Then they develop advanced tools which an average attacker with little background can use to know the liveness, reachability and running service on the network. Once an attacker identifies these details, he can accurately launch an effective attack and get maximum benefit out of …