Digital Commons Network^™

Fspde: A Full Stack Plausibly Deniable Encryption System For Mobile Devices, Jinghui Liao, Niusen Chen, Lichen Xia, Bo Chen, Weisong Shi

Michigan Tech Publications

In today’s digital landscape, the ubiquity of mobile devices underscores the urgent need for stringent security protocols in both data transmission and storage. Plausibly deniable encryption (PDE) stands out as a pivotal solution, particularly in jurisdictions marked by rigorous regulations or increased vulnerabilities of personal data. However, the existing PDE systems for mobile platforms have evident limitations. These include vulnerabilities to multi-snapshot attacks over RAM and flash memory, an undue dependence on non-secure operating systems, traceable PDE entry point, and a conspicuous PDE application prone to reverse engineering. To address these limitations, we have introduced FSPDE, the first Full-Stack mobile …

Ct-To-Mri Synthesis For High-Dose-Rate Brachytherapy Treatment Planning, Rachel Nicole Gordon

Master's Theses

High-dose-rate (HDR) brachytherapy is a radiation treatment modality that places radioactive sources directly in cancerous regions. Radiation treatment planning for HDR prostate brachytherapy utilizes both CT and MRI to visualize the path of the radioactive source and the prostate gland, respectively. In this work, we propose GAN-CM, a method for conditional CT-to-MRI translation that is based on Generative Adversarial Networks (GANs). The proposed method uses the typical generator-discriminator design of GANs with a modified generator that incorporates semantic masks obtained from the domain image. The use of semantic masks allows GAN-CM to better capture the anatomical details and tissue characteristics …

Specification, Enforcement, And Measurement Of Integrity Policies, Kevin Dennis

USF Tampa Graduate Theses and Dissertations

The first step to improving an organization's security posture is to define the organization's security goals. At a technical level, these goals are expressed as security policies. Security policies are predicates over programs, that return true or false if the program adheres to the policy. Defining these policies correctly is thus essential to ensuring the overarching security goals are met, but it is often quite difficult to translate human-oriented goals into their technical policy counterparts. In addition, these policies must be specified so that they are enforceable while minimizing false positives and false negatives. Integrity policies, which specify how data …

Development Of Cyber Security Platform For Experiential Learning, Abhishek Vaish, Ravindra Kumar, Samo Bobek, Simona Sternad

Journal of Cybersecurity Education, Research and Practice

The cyber security education market has grown-up exponentially, with a CAGR of 13.9 % as reported by Data Intelo. The report published by the World Economic Fo- rum 2023 indicates a shortfall of 2.27 million cyber security experts in 2021 across different roles and hence manifest that Skill-based cyber security education is the need of the hour. Cybersecurity as a field has evolved as a multi-discipline, multi-stakeholder and multi-role discipline. Therefore, the need to address formal education with an outcome-based philosophy is imperative to address for a wider audience with varied past training in their formal education. With the Internet …

Liability For Use Of Artificial Intelligence In Medicine, Nicholson W. Price Ii, Sara Gerke, I. Glenn Cohen

Book Chapters

While artificial intelligence (AI) has substantial potential to improve medical practice, errors will certainly occur, sometimes resulting in injury. Who will be liable? Questions of liability for AI-related injury raise not only immediate concerns for potentially liable parties but also broader systemic questions about how AI will be developed and adopted. The landscape of liability is complex, involving healthcare providers and institutions and the developers of AI systems. In this chapter, we consider these three principal loci of liability. At the outset, we note a few issues that shape our analysis.

Scaling Expertise: A Note On Homophily In Online Discourse And Content Moderation, Dylan Weber

New England Journal of Public Policy

It is now empirically clear that the structure of online discourse tends toward homophily; users strongly prefer to interact with content and other users that are similar to them. I review the evidence for the ubiquity of homophily in discourse and highlight some of its worst effects including narrowed information landscape for users and increased spread of misinformation. I then discuss the current state of moderation frameworks at large social media platforms and how they are ill-equipped to deal with structural trends in discourse such as homophily. Finally, I sketch a moderation framework based on a principal of “scaling expertise” …

Mixed Uncertainty Analysis On Pumping By Peristaltic Hearts Using Dempster-Shafer Theory, Yanyan He, Nicholas A. Battista, Lindsay D. Waldrop

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

In this paper, we introduce the numerical strategy for mixed uncertainty propagation based on probability and Dempster–Shafer theories, and apply it to the computational model of peristalsis in a heart-pumping system. Specifically, the stochastic uncertainty in the system is represented with random variables while epistemic uncertainty is represented using non-probabilistic uncertain variables with belief functions. The mixed uncertainty is propagated through the system, resulting in the uncertainty in the chosen quantities of interest (QoI, such as flow volume, cost of transport and work). With the introduced numerical method, the uncertainty in the statistics of QoIs will be represented using belief …

Henna Chatbot Capstone Review, Kobe Norcross

University Honors Theses

This thesis reviews the development of the Henna Chatbot, an AI-powered DEI consultant designed to provide personalized feedback to organizations. Sponsored by DEI consultant Arsh Haque, the project aims to address gaps in current DEI software, which often lacks team-specific feedback. The Henna Chatbot leverages GPT-3.5 Turbo to create an affordable SaaS platform where organizations can train Henna with their DEI values, and Henna will help organizations stay aligned with those values. The project spanned twenty weeks and was completed by a team of eight computer science students at Portland State University. The development process followed Agile methodologies, emphasizing effective …

Trust, Transparency, And Transport: The Impact Of Privacy Protection On The Acceptance Of Last-Mile Drone Delivery, Jurgen Heinz Famula

Electronic Theses and Dissertations

A common set of problems commercial delivery companies face is finding ways to increase the efficiency and reliability of the “last mile” of a package’s journey, all while reducing operating costs. This need for efficiency has driven many companies to explore using unmanned aerial vehicles (UAVs), or drones, to get packages to their final destination. Although UAVs have great potential to help increase efficiency in commercial package delivery, this comes at a potential cost to the privacy of people who intersect the flight paths of these unmanned vehicles. This thesis explores the effect of a mobile phone application for commercial …

Bridging Design And Perception: Novel Tools And Technologies For Creating Effective Human-Robot Interactions, Benjamin Dossett

Electronic Theses and Dissertations

This thesis explores human perception of robots through the use of novel tools and technologies. First, the impact of Augmented Reality (AR) data presentation on human perception of robots is investigated. A study conducted with the AR human-robot teaming system found that robot performance significantly influenced participants’ perceptions, overshadowing the impact of matching or mismatching robot confidence feedback. Second, the DU Want to Build-A-Bot platform is presented, which enables participatory robot design and opens the door for novel research of how robot design affects human perception. The Build-A-Bot platform enables the collection of diverse robot designs, facilitating machine learning analysis …

Evaluating The Effect Of Domain-Specific Large Language Models On Question And Response, Phillip D. Crippen

Electronic Theses and Dissertations

Large Language Models have emerged to great fanfare in the Information Technology market. Business and Information Technology leaders are currently exploring ways to apply these models to assist their organizations in executing business processes and generating innovation. Software vendors, consultants, and academics promote various approaches to making Large Language Models work effectively for business. However, little academic literature is available today that quantifies the degree of improvement possible with these domain-specific approaches over the standard capabilities of generalized Large Language Models.

The study seeks to quantify the benefits of one approach, Retrieval Augmented Generation. The study uses a collection of …

Technology And Homelessness: How Website Design And Blockchain Technology Could Impact The Unhoused, Casey Pratt

Undergraduate Theses, Capstones, and Recitals

Although technology could be used to combat inequality, it is instead increasing it. This paper discusses how the unhoused population suffers at the hand of technological inequality despite being relatively offline. It presents theories on how this would change if we reapproached how technology is used to assist the unhoused. It suggests implementing blockchain as a resource as well as modifying the websites built to assist in accessing benefits. Employees at shelters are interviewed for this paper about their experiences with using digital resources to rehouse and restabilize the vulnerable. They are asked how the sites can be improved for …

Cards With Class: Formalizing A Simplified Collectible Card Game, Dan Ha

University Honors Theses

Collectible card games (CCGs) have been a wildly popular game genre since the release of Wizards of the Coast's Magic: The Gathering. These games revolve around their thousands of cards and the hundreds of thousands of interactions they can create with their many effects. For designers, it is an incredibly demanding task to ensure that every single card works properly and that each card's text unambiguously conveys its intended behavior in all cases. The task only grows more difficult over time as the number of cards in the game grows and card effects become more complex or experimental. If the …

The Institutional Challenges Of A Quantified Self Study: An Attempt To Ascertain How Data Collected From A Mobile Device Can Be An Indicator Of Personal Mental Health Over Time, Julian Lazaras

University Honors Theses

The adoption of an application of new technology always comes with a bias, this is never more true for the case of human behavioral analytics within higher education. While movements such as the quantified self movement make strides to reinterpret the realm of data analytics, psychology, and computer science, there are inevitably limitations to the adoption and application of such approaches within the standard realm of research. Herein is presented a case where an effort to evaluate the prospect of use of mobile phone data as secondary indicators of personal mental health through the lens of data analysis was put …

Mapping Mental Models Through An Improved Method For Identifying Causal Structures In Qualitative Data, Erin S. Kenzie, Wayne Wakeland, Antonie Jetter, Kristen Hassmiller Lich, Mellodie Seater, Melinda M. Davis

Complex Systems Faculty Publications and Presentations

Qualitative data are commonly used in the development of system dynamicsmodels, but methods for systematically identifying causal structures in qualita-tive data have not been widely established. This article presents a modifiedprocess for identifying causal structures (e.g., feedback loops) that are commu-nicated implicitly or explicitly and utilizes software to make coding, tracking,and model rendering more efficient. This approach draws from existingmethods, system dynamics best practice, and qualitative data analysis tech-niques. Steps of this method are presented along with a description of causalstructures for an audience new to system dynamics. The method is applied to aset of interviews describing mental models of …

Eye Diseases Prediction And Classification Using Deep Learning Techniques., Ahmed M. Fahmy

Artificial Intelligence

In human anatomy, the eye is a major sense organ and loss of vision would have an enormous impact on quality of life. In addition, it may also be possible that the eye is showing signs of severe health problems. Eye diseases detection is mainly the problem here. Detecting eye diseases using different advanced AI- based techniques to analyze and predict the type of eye disease from retinal eye images and improve the performance and the accuracy of the proposed system. This proposed system can help ophthalmologists to save their time in manual examination. This paper aims to develop Deep …

Heterogeneous Resources In Infrastructures Of The Edge Network Paradigm: A Comprehensive Review, Qusay S. Alsaffar, Leila Ben Ayed

Karbala International Journal of Modern Science

The late 1990s saw the rise of the edge computing network paradigm, as well as an increase in the number of IoT de-vices. This concept is viewed as a link between cloud servers and end-devices, bringing processing and storage re-sources closer to clients. As a result of its low latency and high performance, researchers and developers have expressed interest in it. However, this paradigm confronts a number of obstacles and restrictions, including restricted and hetero-geneous resources at network edges. In this paper, we provide a detailed review of heterogeneous resources in edge network infrastructures using a three-dimensional method. These three …

Classification And Removal Of Hazy Images Based On A Transmission Fusion Strategy Using The Alexnet Network, Roa'a M. Al-Airaji, Haider Th. Salim Alrikabi, Rula Kamil

Karbala International Journal of Modern Science

Outdoor images are used in many domains, such as surveillance, geospatial mapping, and autonomous vehicles. The occurrence of noise in outdoor images is a widely observed phenomenon. They are primarily attributed to extreme natural and manufactured meteorological conditions, such as haze, smog, and fog. In autonomous vehicle navigation, recovering the ground truth image is essential, enabling the system to make more informed decisions. Accurate air-light and transmission map calculation is vital in recovering the ground truth image. An efficient approach for image dehazing that utilizes the mean channel prior (MCP) is presented in this paper to estimate the transmission map, …

Data Visualization, Licensing, And Other Generative Ai Initiatives At Minnesota State University Mankato, Evan Rusch, Nat Gustafson-Sundell

Library Services Publications

At Minnesota State University Mankato (MNSU), we’ve undertaken several experiments and initiatives focused on Generative Artificial Intelligence. At the start of the fall semester, we collaborated with university Information Technology Services to present a professional development session for returning faculty through the MNSU Center for Excellence in Teaching & Learning on “5 Tips for Teaching with AI.” We also presented to librarians across the regional consortium, Minitex, on “The Library & Generative AI.” This presentation included several demonstrations. It was offered as an introduction to Generative AI focused on topics most relevant to librarians, including information literacy, as well as …

Federated Learning Based Autoencoder Ensemble System For Malware Detection On Internet Of Things Devices, Steven Edward Arroyo

Theses and Dissertations

New technologies are being introduced at a rate faster than ever before and smaller in size. Due to the size of these devices, security is often difficult to implement. The existing solution is a firewall-segmented “IoT Network” that only limits the effect of these infected devices on other parts of the network. We propose a lightweight unsupervised hybrid-cloud ensemble anomaly detection system for malware detection. We perform transfer learning using a generalized model trained on multiple IoT device sources to learn network traffic on new devices with minimal computational resources. We further extend our proposed system to utilize federated learning …

Facial Skin Analysis In Malaysians Using Yolov5: A Deep Learning Perspective, Ying Huey Gan, Shih Yin Ooi, Ying Han Pang, Yi Hong Tay, Quan Fong Yeo

Journal of Informatics and Web Engineering

Nowadays, people are more concerned about their skin conditions and are more willing to spend money and time on facial care routines. The beauty sector market is increasing, and more skin type readers are being created to help people determine their skin type. While various skin type readers are in the market, each is invented and tested abroad. Those skin type readers in the beauty market are not applied well on Malaysian skin. Therefore, this paper proposes a facial skin analysis system tailored primarily for Malaysian skin. This paper integrated object detection and deep learning algorithms in developing skin-type readers. …

Real Time 3d Internal Building Directory Map, Zi Yang Chia, Pey Yun Goh

Journal of Informatics and Web Engineering

Global Positioning System (GPS) is a famous technology around the world in identifying the real time precise location of any object with the assistance of satellites. The most common application of GPS is the use of outdoor maps. GPS offers efficient, scalable and cost-effective location services. However, this technology is not reliable when the position is in an indoor environment. The signal is very weak or totally lost due to signal attenuation and multipath effects. Among the indoor positioning technologies, WLAN is the most convenient and cost effective. In recent research, machine learning algorithms have become popular and utilized in …

Assessing The Efficiency Of Deep Learning Methods For Automated Vehicle Registration Recognition For University Entrance, Muhammad Syaqil Irsyad, Zarina Che Embi, Khairil Imran Bin Ghauth

Journal of Informatics and Web Engineering

With the ever-increasing number of vehicles on the road, a faster reliable security system for university entry is needed. This paper presents an approach for Automatic Number Plate Recognition (ANPR) using deep learning and PP-OCRv3. The proposed approach utilizes a pre-trained object detection model to locate license plates, extracts a single frame of the license plate, performs license plate recognition, applies pre-processing techniques, and employs PP-OCRv3 for text extraction in real time. The system was tested with Malaysian vehicle plates, and its accuracy and speed of detection were evaluated. The results show the system's potential to be easily adapted to …

Streamlining Dental Clinic Management For Effective Digitisation Productivity And Usability, Sin-Ban Ho, En-Yu Chew, Chuie-Hong Tan

Journal of Informatics and Web Engineering

Oral health is an integral part of overall health, and poor oral hygiene can lead to a variety of health problems. Modern oral care has greatly improved our quality of life, but the increasing demand for routine dental checkups and treatments calls for improved systems for managing patient records and appointments. While technology has significantly enhanced the efficacy and experience of dental care, many dental clinics still rely on paper records to record the patient’s oral condition, but these are not easily accessible to the patients for viewing. This study aims to address the issue by developing a Dental Clinic …

Sentiment Analysis In Social Media: A Case Study Of Hike In University School Fees In Selected Nigerian Universities, Abdulahi Olarewaju Aremu, Isah Muhammad

Journal of Informatics and Web Engineering

Faced with escalating operational costs and government disinvestment, Nigerian public universities are implementing tuition fee increases to maintain institutional functionality. This necessary fiscal measure comes in the wake of 2022 industrial action, which exacerbated pre-existing financial strain through extended work stoppages and potentially higher costs associated with resuming activities, while leaving unaddressed the longstanding demands of academics for improved welfare and working conditions. The court-mandated resumption of academic activities without resolution of these core issues further strained university finances, leading to a significant increase in tuition fees. Using VADER, this study investigated social media sentiments related to the increase in …

A Bilingual Immersive Environment For Kids Learning, Tufail Ahmad, Arifa Bibi, Umar Farooq, Ihsan Rabbi

Journal of Informatics and Web Engineering

Virtual Worlds (VWs) provide an improved learning experience as they have an increased level of user participation and technological involvement. They avoid content duplication and following a set of predefined rules to overcome the issues in game environments. VWs are coherent, persistent and collaborative social places that believe in realism through immersion. Client viewer software is used for user immersion in the form of avatars and in-world content creation in these environments. This work presents a simple bi-lingual environment developed for kids’ learning in English and Urdu using the well-known VW development framework called OpenSimulator (OpSim). It used Firestorm viewer …

Secure Room-Sharing Decentralized App Development On Ethereum Block Chain Using Smart Contracts, Hasnain Raza, Reqad Ali, Jawaid Iqbal, Muhammad Awais

Journal of Informatics and Web Engineering

The purpose of this research is to analyze whether Blockchain technology can affect the share-economy. Apart from that, blockchain technology has been innovating the whole of the industries and so the academics are discovering the possibilities and starting to incorporate them in order to provide additional tech possibilities. The sharing economic system is the system which enables to share asset among the one person to the other person. It has seen the remarkable growth in the last few years, Uber, Careem, Airbnb, Zostel, Hostel World are some companies to mention which have fueled this growth. Yet, the majority of the …

Development And Validation Of Autotronic Training Module For Automobile Technology Students In Polytechnics In Southern Nigeria, Saue, Baritule Prince, Chukuigwe, Ogbondah Nndameka, Bassey, Imaobong Sunday

Journal of Informatics and Web Engineering

A research was carried out to create and verify an autotronic training module for students studying vehicle technology at polytechnics located in Southern Nigeria. The design used for the project was Research and Development (R&D). An observation has been made that the curriculum of polytechnics in Nigeria lacks sufficient substance on autotronics technology. As a result, lecturers have challenges in fully imparting the abilities that are essential for the professional world. Undoubtedly, there is now a disparity between the training that craftsmen receive and the skills that are demanded by industries. The research was carried out in the southern region …

Performance Evaluation Of Yolo Models In Plant Disease Detection, Usman Ali, Maizatul Akmar Ismail, Riyaz Ahamed Ariyaluran Habeeb, Syed Roshaan Ali Shah

Journal of Informatics and Web Engineering

Plant diseases significantly impact global agriculture, leading to substantial production losses and economic consequences. Timely disease detection can enhance crop yield, optimize resource utilization, reduce costs, and mitigate environmental effects, ultimately ensuring high-quality food production. Deep learning, specifically computer vision-based techniques, have proven invaluable in tasks like image classification, segmentation, and object detection. Deep Learning techniques such as You Only Look Once (YOLO) models are state of the art neural network algorithms used for accurate object detection. In this study, YOLOv5, YOLOv7 and YOLOv8 models were trained on CCL’20 dataset for citrus disease detection. Data augmentation techniques such as image …

Wix For Web Development And The Application Of The Waterfall Model And Project Based Learning For Project Completion: A Case Study, Mawar Madiah, Ng Kai Xuen, Tan Yew Wen, Tan Zhi Heng, Chong Zhi Tian, Chan Jia Xuan

Journal of Informatics and Web Engineering

Website development without prior knowledge of HTML or programming experience would be a significant challenge. This study aims to share the students' experiences developing a website using Wix, a user-friendly website builder. The website was assigned as a project-based assessment of one of the courses required to complete a Foundation programme. The course was delivered using a project-based learning (PBL) approach in this context. The students worked as a group to write a project proposal, plan activities, develop the website, write reports, and present the outcome. As for the website development process, the study demonstrates the completion of the project …