Digital Commons Network^™

The Impact Of Objectively Recorded Smartphone Usage And Emotional Intelligence On Problematic Internet Usage, Sameha Alshakhsi, Khansa Chemnad, Mohamed Basel Almourad, Majid Altuwairiqi, John Mcalaney, Raian Ali

All Works

This study examined the effects of gender, age, objective smartphone usage data, and Emotional Intelligence (EI) on Problematic Internet Use (PIU) and its components (obsession, neglect, and control disorder). The study relied on objective data of smartphone usage as a representative of technology use collected by a monitoring application of smartphone usage. PIU and EI were measured through the Problematic Internet Usage Questionnaire short form (PIUQ-SF-6) and Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), respectively. The current cross-sectional study was carried out with 268 participants (Female: 61.6%, ages from 15 to 64) from ten different countries. The analysis was performed using …

Intelligent Health Care And Diseases Management System: Multi-Day-Ahead Predictions Of Covid-19, Ahed Abugabah, Farah Shahid

All Works

The rapidly growing number of COVID-19 infected and death cases has had a catastrophic worldwide impact. As a case study, the total number of death cases in Algeria is over two thousand people (increased with time), which drives us to search its possible trend for early warning and control. In this paper, the proposed model for making a time-series forecast for daily and total infected cases, death cases, and recovered cases for the countrywide Algeria COVID-19 dataset is a two-layer dropout gated recurrent unit (TDGRU). Four performance parameters were used to assess the model’s performance: mean absolute error (MAE), root …

Augmenting Ccam Infrastructure For Creating Smart Roads And Enabling Autonomous Driving, M. Jalal Khan, Manzoor Ahmed Khan, Obaid Ullah, Sumbal Malik, Farkhund Iqbal, Hesham El-Sayed, Sherzod Turaev

All Works

Autonomous vehicles and smart roads are not new concepts and the undergoing development to empower the vehicles for higher levels of automation has achieved initial milestones. However, the transportation industry and relevant research communities still require making considerable efforts to create smart and intelligent roads for autonomous driving. To achieve the results of such efforts, the CCAM infrastructure is a game changer and plays a key role in achieving higher levels of autonomous driving. In this paper, we present a smart infrastructure and autonomous driving capabilities enhanced by CCAM infrastructure. Meaning thereby, we lay down the technical requirements of the …

Legal Dispositionism And Artificially-Intelligent Attributions, Jerrold Soh

Research Collection Yong Pung How School Of Law

It is conventionally argued that because an artificially-intelligent (AI) system acts autonomously, its makers cannot easily be held liable should the system's actions harm. Since the system cannot be liable on its own account either, existing laws expose victims to accountability gaps and need to be reformed. Recent legal instruments have nonetheless established obligations against AI developers and providers. Drawing on attribution theory, this paper examines how these seemingly opposing positions are shaped by the ways in which AI systems are conceptualised. Specifically, folk dispositionism underpins conventional legal discourse on AI liability, personality, publications, and inventions and leads us towards …

Constrained Reinforcement Learning In Hard Exploration Problems, Pankayaraj Pathmanathan, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

One approach to guaranteeing safety in Reinforcement Learning is through cost constraints that are imposed on trajectories. Recent works in constrained RL have developed methods that ensure constraints can be enforced even at learning time while maximizing the overall value of the policy. Unfortunately, as demonstrated in our experimental results, such approaches do not perform well on complex multi-level tasks, with longer episode lengths or sparse rewards. To that end, wepropose a scalable hierarchical approach for constrained RL problems that employs backward cost value functions in the context of task hierarchy and a novel intrinsic reward function in lower levels …

Learning Control Policies For Stochastic Systems With Reach-Avoid Guarantees, Dorde Zikelic, Mathias Lechner, A. Thomas Henzinger, Krishnendu Chatterjee

Research Collection School Of Computing and Information Systems

We study the problem of learning controllers for discrete-time non-linear stochastic dynamical systems with formal reach-avoid guarantees. This work presents the first method for providing formal reach-avoid guarantees, which combine and generalize stability and safety guarantees, with a tolerable probability threshold p ∈ [0,1] over the infinite time horizon in general Lipschitz continuous systems. Our method leverages advances in machine learning literature and it represents formal certificates as neural networks. In particular, we learn a certificate in the form of a reach-avoid supermartingale (RASM), a novel notion that we introduce in this work. Our RASMs provide reachability and avoidance guarantees …

The Application Of Graph Technology For Improving Entity Resolution Results In The Context Of Group Membership, Md Abdus Salam Siddique

Theses and Dissertations

The main objective of Entity resolution (ER) is to find duplicate records within the same data table from the same source or different data tables from various sources. A traditional pair-wise supervised entity resolution matching depends on pre-built rules for finding matched records. On the other hand, unsupervised or semisupervised also relies on pair-wise matching. In the maximum case, group membership is left behind for consideration. In this dissertation, I have discussed the design, implementation and evaluation of a graph-based entity resolution for group membership to enhance the pair-wise matching ER system. I have designed and implemented a pipeline for …

Data Science Transfer Pathways From Associate's To Bachelor's Programs, Benjamin S. Baumer, Nicholas J. Horton

Statistical and Data Sciences: Faculty Publications

A substantial fraction of students who complete their college education at a public university in the United States begin their journey at one of the 935 public 2-year colleges. While the number of 4-year colleges offering bachelor’s degrees in data science continues to increase, data science instruction at many 2-year colleges lags behind. A major impediment is the relative paucity of introductory data science courses that serve multiple student audiences and can easily transfer. In addition, the lack of predefined transfer pathways (or articulation agreements) for data science creates a growing disconnect that leaves students who want to study data …

Secap Switch—Defeating Topology Poisoning Attacks Using P4 Data Planes, Dylan Smyth, Sandra Scott-Hayward, Victor Cionca, Sean Mcsweeney, Donna O'Shea

Department of Computer Science Publications

Programmable networking is evolving from programmable control plane solutions such as OpenFlow-based software-defined networking (SDN) to programmable data planes such as P4-based SDN. To support the functionality of the SDN, the correct view of the network topology is required. However, multiple attacks aimed at topology poisoning have been demonstrated in SDNs. While several controller-centralised security solutions have been proposed to defeat topology poisoning attacks, some attacks e.g., the Data Plane ARP Cache Poisoning Attack and the relay-type Link Fabrication Attack are difficult to detect using a fully centralised security solution. In this paper, we present the Security-Aware Programmable (SECAP) Switch—a …

Artificial Intelligence, Basic Skills, And Quantitative Literacy, Gizem Karaali

Numeracy

The introduction in November 2022 of ChatGPT, a freely available language-based artificial intelligence, has led to concerns among some educators about the feasibility and benefits of teaching basic writing and critical thinking skills to students in the context of easily accessed, AI-based cheating mechanisms. As of now, ChatGPT can write pretty convincing student-level prose, but it is still not very good at answering quantitatively rich questions. Therefore, for the time being, the preceding concerns may not be shared by a large portion of the numeracy education community. However, as Google and WolframAlpha are definitely capable of answering standard and some …

Chatgpt And The Rise Of Ai, Derek C. Schuurman

University Faculty Publications and Creative Works

Derek C. Schuurman considers the rise of AI from a Christian perspective in January 2023 in a blog post for the Christian Scholar's Review asking questions such as "how are people distinct from machines?" and "how can we discern norms for the responsible use of AI?" This blog post was one of the 2024 Word Awards Winners Honouring the Best of Canadian Christian Writing from 2023.

https://thewordguild.com/wp-content/uploads/2024/09/TWA-2024-Media-Release-Winners-List.pdf

Reinventing Cybersecurity Internships During The Covid-19 Pandemic, Lori L. Sussman

Journal of Cybersecurity Education, Research and Practice

The Cybersecurity Ambassador Program provides professional skills training for emerging cybersecurity professionals remotely. The goal is to reach out to underrepresented populations who may use Federal Work-Study (FWS) or grant sponsored internships to participate. Cybersecurity Ambassadors (CAs) develop skills that will serve them well as cybersecurity workers prepared to do research, lead multidisciplinary, technical teams, and educate stakeholders and community members. CAP also reinforces leadership skills so that the next generation of cybersecurity professionals becomes a sustainable source of management talent for the program and profession. The remote curriculum innovatively builds non-technical professional skills (communications, teamwork, leadership) for cybersecurity research …

Risk Perceptions About Personal Internet-Of-Things: Research Directions From A Multi-Panel Delphi Study, Paul M. Di Gangi, Barbara A. Wech, Jennifer D. Hamrick, James L. Worrell, Samuel H. Goh

Journal of Cybersecurity Education, Research and Practice

Internet-of-Things (IoT) research has primarily focused on identifying IoT devices' organizational risks with little attention to consumer perceptions about IoT device risks. The purpose of this study is to understand consumer risk perceptions for personal IoT devices and translate these perceptions into guidance for future research directions. We conduct a sequential, mixed-methods study using multi-panel Delphi and thematic analysis techniques to understand consumer risk perceptions. The results identify four themes focused on data exposure and user experiences within IoT devices. Our thematic analysis also identified several emerging risks associated with the evolution of IoT device functionality and its potential positioning …

Alpha Phi-Shing Fraternity: Phishing Assessment In A Higher Education Institution, Marco Casagrande, Mauro Conti, Monica Fedeli, Eleonora Losiouk

Journal of Cybersecurity Education, Research and Practice

Phishing is a common social engineering attack aimed to steal personal information. Universities attract phishing attacks because: 1) they store employees and students sensitive data, 2) they save confidential documents, 3) their infrastructures often lack security. In this paper, we showcase a phishing assessment at the University of Redacted aimed to identify the people, and the features of such people, that are more susceptible to phishing attacks. We delivered phishing emails to 1.508 subjects in three separate batches, collecting a clickrate equal to 30%, 11% and 13%, respectively. We considered several features (i.e., age, gender, role, working/studying field, email template) …

Semantic Orientation Of Crosslingual Sentiments: Employment Of Lexicon And Dictionaries, Arslan Ali Raza, Asad Habib, Jawad Ashraf, Babar Shah, Fernando Moreira

All Works

Sentiment Analysis is a modern discipline at the crossroads of data mining and natural language processing. It is concerned with the computational treatment of public moods shared in the form of text over social networking websites. Social media users express their feelings in conversations through cross-lingual terms, intensifiers, enhancers, reducers, symbols, and Net Lingo. However, the generic Sentiment Analysis (SA) research lacks comprehensive coverage about such abstruseness. In particular, they are inapt in the semantic orientation of Crosslingual based code switching, capitalization and accentuation of opinionative text due to the lack of annotated corpora, computational resources, linguistic processing and inefficient …

Research On System Of Virtual-Reality Fusion And Inquiry-Based Learning, Yongning Zhu, Zeru Lou, Tianxiang Wu, Jianmin Wang

Journal of System Simulation

Abstract: With the increasing interest in personalized and self-motivated education, emphasizing active learning and practical experiences, inquiry-based learning (IBL) is attracting interest in education. Considering the requirement for inquiry-based education, a framework of full process inquiry-based learning environment in the real-virtual worlds is designed. As an example, a mixed-reality chemical experiment system is developed. The metadata including user behavior data, interactive suite status and interactive interface status is collected through physical sensing. By mapping real-world status to the virtual world avatar, virtual experiments are simulated with computational dynamic solvers and real-time rendering. The generated images are sent back to the …

Metamobility: Connecting Future Mobility With Metaverse, Haoxin Wang, Ziran Wang, Dawei Chen, Qiang Liu, Hongyu Ke, Kyungtae Han

School of Computing: Faculty Publications

A Metaverse is a perpetual, immersive, and shared digital universe that is linked to but beyond the physical reality, and this emerging technology is attracting enormous attention from different industries. In this article, we define the first holistic realization of the metaverse in the mobility domain, coined as “metamobility”. We present our vision of what metamobility will be and describe its basic architecture. We also propose two use cases, tactile live maps and meta-empowered advanced driver-assistance systems (ADAS), to demonstrate how the metamobility will benefit and reshape future mobility systems. Each use case is discussed from the perspective of the …

Artificial Intelligence Mechanisms In Countering Violent Extremism, Ammar Al-Babli

Journal of Police and Legal Sciences

The research idea revolves around the mechanisms of artificial intelligence in monitoring and combating extremist groups' dissemination of bad, misleading ideas, destructive ideologies, fake images, and videos, especially those related to terrorism and extremism. Artificial intelligence can be used to confront violent extremism on social media platforms. Social media companies widely use artificial intelligence in their efforts to remove and ban terrorist content from their platforms. The research includes threats arising from cyberspace, such as terrorism, promotion, recruitment, exploitation, and hate speech, to random email, as the ultimate goal of terrorists is to undermine societies and political systems by generating …

A Deep Learning Based Dual Encoder–Decoder Framework For Anatomical Structure Segmentation In Chest X-Ray Images, Ihsan Ullah, Farman Ali, Babar Shah, Shaker El-Sappagh, Tamer Abuhmed, Sang Hyun Park

All Works

Automated multi-organ segmentation plays an essential part in the computer-aided diagnostic (CAD) of chest X-ray fluoroscopy. However, developing a CAD system for the anatomical structure segmentation remains challenging due to several indistinct structures, variations in the anatomical structure shape among different individuals, the presence of medical tools, such as pacemakers and catheters, and various artifacts in the chest radiographic images. In this paper, we propose a robust deep learning segmentation framework for the anatomical structure in chest radiographs that utilizes a dual encoder–decoder convolutional neural network (CNN). The first network in the dual encoder–decoder structure effectively utilizes a pre-trained VGG19 …

Machine Learning Models Interpretability For Malware Detection Using Model Agnostic Language For Exploration And Explanation, Ikuromor Mabel Ogiriki

Theses and Dissertations

The adoption of the internet as a global platform has birthed a significant rise in cyber-attacks of various forms ranging from Trojans, worms, spyware, ransomware, botnet malware, rootkit, etc. In order to tackle the issue of all these forms of malware, there is a need to understand and detect them. There are various methods of detecting malware which include signature, behavioral, and machine learning. Machine learning methods have proven to be the most efficient of all for malware detection. In this thesis, a system that utilizes both the signature and dynamic behavior-based detection techniques, with the added layer of the …

Towards A Framework For Privacy-Preserving Pedestrian Analysis, Anil Kunchala, Mélanie Bouroche, Bianca Schoen-Phelan

Conference papers

The design of pedestrian-friendly infrastructures plays a crucial role in creating sustainable transportation in urban environments. Analyzing pedestrian behaviour in response to existing infrastructure is pivotal to planning, maintaining, and creating more pedestrian-friendly facilities. Many approaches have been proposed to extract such behaviour by applying deep learning models to video data. Video data, however, includes an broad spectrum of privacy-sensitive information about individuals, such as their location at a given time or who they are with. Most of the existing models use privacy-invasive methodologies to track, detect, and analyse individual or group pedestrian behaviour patterns. As a step towards privacy-preserving …

Safe Space: To Help Minimize Cyberbullying And Support Social Well-Being, Eiman Rana

CISLA Senior Integrative Projects

The perverseness of cyberbullying as a growing and serious form of abuse with the potential for harm among children and youth needs to be recognized. In a resource-limited setting such as South Asia where youth have very little access to counseling within schools, the implications for mental health should be recognized. This research study explores whether our youth is capable of using technology in the right way to minimize cyberbullying and support social well-being.

Index Terms - Cyberbullying, Social Well-being, User Experience Design, and Usability Study.

Research@Smu: Sustainable Living, Singapore Management University

Research Collection Office of Research

Sustainable Living is one of the three key priorities of the SMU 2025 Strategy, and the University is committed to develop it into an area of cross-disciplinary strength. The articles in this booklet highlight impactful sustainability research accomplishments at SMU, which spans five broad pillars: Sustainable Business Operations; Sustainable Finance and Impact Assessment; Sustainable Ageing and Wellness; Sustainable Urban Infrastructure; and Sustainable Agro-business and Food Consumption.

Contents:

Sustainable Business Operations

• Managing the Load on Loading Bays
• Going the Last-mile
• Feeding a Growing World
• Pooling the Benefits of Sharing a Ride

Sustainable Finance and Impact Assessment

• When Going Green Becomes a …

A Computational Analysis Of Hybrid Genome Assembly Strategies, Joseph Walewski

Computer Science Honors Papers

The central dogma of molecular biology states that DNA is transcribed to RNA and then translated into proteins. Since DNA is the starting material for many of biology’s macromolecules, it has been referred to as “nature’s instruction book.” The sum of all DNA in a cell is referred to as the genome, and genome sequencing is how we interpret the DNA.

Due to limitations on currently available technology, it is not possible to retrieve the entire genome in one contiguous set of data. Therefore, genome sequencing is a computer science problem as sequencing “reads” must be stitched together to obtain …

Differentially Private Stochastic Convex Optimization In (Non)-Euclidean Space Revisited, Jinyan Su, Changhong Zhao, Di Wang

Machine Learning Faculty Publications

In this paper, we revisit the problem of Differentially Private Stochastic Convex Optimization (DP-SCO) in Euclidean and general `dp spaces. Specifically, we focus on three settings that are still far from well understood: (1) DP-SCO over a constrained and bounded (convex) set in Euclidean space; (2) unconstrained DP-SCO in `dp space; (3) DP-SCO with heavy-tailed data over a constrained and bounded set in `dp space. For problem (1), for both convex and strongly convex loss functions, we propose methods whose outputs could achieve (expected) excess population risks that are only dependent on the Gaussian width of the constraint set, rather …

The Open Charge Point Protocol (Ocpp) Version 1.6 Cyber Range A Training And Testing Platform, David Elmo Ii

Browse all Theses and Dissertations

The widespread expansion of Electric Vehicles (EV) throughout the world creates a requirement for charging stations. While Cybersecurity research is rapidly expanding in the field of Electric Vehicle Infrastructure, efforts are impacted by the availability of testing platforms. This paper presents a solution called the “Open Charge Point Protocol (OCPP) Cyber Range.” Its purpose is to conduct Cybersecurity research against vulnerabilities in the OCPP v1.6 protocol. The OCPP Cyber Range can be used to enable current or future research and to train operators and system managers of Electric Charge Vehicle Supply Equipment (EVSE). This paper demonstrates this solution using three …

Leveraging Explainable Artificial Intelligence (Xai) To Understand Performance Deviations In Load Tests Of Large Software Systems, Eric Shoemaker

Theses, Dissertations and Capstones

Performance testing generates vast amounts of data, making it challenging for human analysts to process within a reasonable timeframe. Therefore, black-box machine learning models are often used to determine pass/fail status, but these models lack transparency and cannot explain why a test has failed, leading to a time-consuming manual analysis process. To address this issue, this thesis proposes using Explainable Artificial Intelligence (XAI) to improve the trustworthiness of black-box and interpretable models in performance testing. The proposed approach leverages the Shapley Additive Explanation (SHAP) algorithm as a surrogate model to help performance analysts understand the decision-making process of black-box machine …

Establishing The Legal Framework To Regulate Quantum Computing Technology, Kaya Derose

Catholic University Journal of Law and Technology

No abstract provided.

A Visual Tour Of Dynamical Systems On Color Space, Jonathan Maltsman

HMC Senior Theses

We can think of a pixel as a particle in three dimensional space, where its x, y and z coordinates correspond to its level of red, green, and blue, respectively. Just as a particle’s motion is guided by physical rules like gravity, we can construct rules to guide a pixel’s motion through color space. We can develop striking visuals by applying these rules, called dynamical systems, onto images using animation engines. This project explores a number of these systems while exposing the underlying algebraic structure of color space. We also build and demonstrate a Visual DJ circuit board for …

Building Coleus Academy, Janessa Unseld

Mahurin Honors College Capstone Experience/Thesis Projects

Coleus Academy, a nonprofit e-learning platform, has been created to address the deficits left by the de-emphasis and, at times, outright omission of practical skill-centric education in American curriculums. There exists a gap between the degree of knowledge necessary to engage with adult life and the extent of that knowledge that is actually possessed by emerging adults. Prominent legislations are among the numerous efforts to address this issue. However, there is a deeply fractured market where resources are proving too expensive, too sparse, or hyper-specific to the point of limited usability. Compounded with disparities in when, where, and to whom …