Digital Commons Network^™

Ai-Powered Dynamic Encryption And Decryption Defense Model, Chyanne Wen Qian Lor, Ibrahim Yusof, Anang Hudaya Muhamad Amin

Journal of Informatics and Web Engineering

Static cryptographic systems that rely on fixed algorithms and predetermined keys have proven increasingly ineffective in addressing today’s adaptive and AI-powered cyber threats. This paper proposes an Artificial Intelligence (AI)-enabled dynamic encryption and decryption defence model designed to enhance cybersecurity through real-time threat classification and context-aware cryptographic response. The framework combines the Suricata intrusion detection engine with a Random Forest model developed using the CIC-IDS2017 dataset, allowing it to identify and categorize network anomalies into unified groups, including Denial-of-Service (DoS), Distributed Denial of Service (DDoS), Brute Force, and PortScan. Once threats are identified, the system dynamically selects an appropriate encryption …

Ai-Driven Intrusion Detection System For Network Security, Zhi Lin Sarah Teoh, Wee How Khoh, Hui Yen Yap, Pin Shen Teh

Journal of Informatics and Web Engineering

In the evolving landscape of cybersecurity, Intrusion Detection Systems (IDS) play a vital role in safeguarding computer networks against malicious activity. Traditional signature-based IDS approaches are increasingly ineffective in detecting novel, complex, or zero-day attacks due to their reliance on predefined rules. To overcome these limitations, this study proposes an AI-driven IDS that integrates both classical machine learning and modern deep learning techniques. The framework introduces and compares three models such as Support Vector Machine (SVM), Convolutional Neural Network (CNN), and a hybrid CNN-SVM model. The system is designed to analyze network traffic patterns and classify them as either benign …

Deep Learning Model For Burn Injury Assessment With Enhanced Diagnosis Rate, C. Pabitha, K. Revathi, R. Krishna Priya

Journal of Informatics and Web Engineering

The skin is considered as the largest organ of our body specifically satisfies the environment. As a result, the skin is vulnerable to various injuries, especially burns. Burns are linked to high rates of morbidity and mortality and can be fatal. Effective diagnosis supported by precise evaluation of the burn area and the depth of wound is critical for enabling efficacy in clinical settings. The characteristics of a burn wound on the skin include: the wound is abnormal, the skin is infected, there is discomfort, the skin is tight, and there are raised areas of skin. To properly diagnose burn …

Performance Analysis Of Faster R-Cnn And Yolov8 Model For Mango Fruits Detection, Mohd Haris Lye, Marawan Ashraf Eldeib

Journal of Informatics and Web Engineering

Mango cultivation is a vital agricultural sector in many regions, providing significant economic benefits and contributing to environmental sustainability. Traditional mango detection and harvesting methods are prone to error and are labour-intensive. Recent advances in aerial imagery and Artificial Intelligence (AI) offer innovative solutions to these challenges. An automated yield estimation and fruit harvesting system will require an accurate fruit object detection model. This study explores the application of deep learning models for mango detection on two diverse datasets. This research focuses on evaluating two primary deep learning models: Faster Region-based Convolutional Neural Network (Faster R-CNN) and You Only Look …

A Review Of Cyber-Attacks On Web Applications And Their Countermeasures, Salaheddin Beskri, Kok Why Ng

Journal of Informatics and Web Engineering

Leaders have always wondered where and how precisely Information Technology (IT) can be of value in their organizations. However, the pacing rate of technology development and cutting-edge features that technologies can provide can cause the decision-maker of an organization to rush to invest in technology upgrades without taking risks into account. The risks that may cost the existence of organizations can be caused by an adversary who commits a cyberattack against the IT assets of an organization, seizing leaders' underestimations of the risks of IT upgrades. Inevitably, there will always be new vulnerabilities in IT assets, especially in information systems. …

Multi-Agent Ai Systems For Detecting Emerging Therapeutic Targets And Intervention Patterns In Neuroplasticity Research, Raza Hasan, Salman Mahmood

Journal of Informatics and Web Engineering

The exponential growth of neuroplasticity research presents profound challenges to the manual synthesis of literature, hindering the identification of emerging therapeutic targets and intervention patterns. While multi-agent Artificial Intelligence (AI) systems have been proposed conceptually to address this, concrete implementations demonstrating end-to-end utility are scarce. This paper details the successful implementation and application of a novel four-agent AI system designed to automate the discovery, extraction, analysis, and validation of patterns in neuroplasticity literature. Our platform consists of four parts: a Literature Discovery Agent (LDA) for corpus gathering, a Concept Extraction Agent (CEA) with a multi-level NLP strategy fallback mechanism for …

Synthetic Data Generation For Healthcare And Wellness: Methods, Applications, And Future Directions, Sellappan Palaniappan, Kasthuri Subaramaniam, Oras Baker, Bui Ngoc Dung, Sumit Dhariwal

Journal of Informatics and Web Engineering

Artificial intelligence in healthcare relies heavily upon the availability of high-quality datasets, but very rigid privacy regimes, institutional silos, ethical issues, and heterogeneous data still serve to limit the availability of real-world clinical data. To combat these limitations, you focus on synthetic data generation as a privacy-preserving and scalable alternative to traditional data generation for healthcare and wellness studies. More relevant is a work on a broad and clear framework of synthesis methods based on statistical modelling, rule-based generation and domain-specific clinical logic, in contrast to recent studies that mainly target sophisticated methods for the deep learning architectures. The paper …

Ai-Powered Continuous Health Monitoring For Chronic Disease Management In Malaysia: Real-Time Risk Prediction Using Wearable Sensors And Digital Biomarkers, Umi Najiah Ahmad Razimi, Yong Yoke Leng, Nor Hapiza Mohd Ariffin, Mohammed Hazim Alkawaz

Journal of Informatics and Web Engineering

Chronic Non-Communicable Diseases (NCDs), such as diabetes mellitus, hypertension, and cardiovascular disease, make up a significant portion of the mortality cases in Malaysia, as well as impose consistent demands for costs related to health care expenditure. According to the cost reports at the national level, major NCDs (cardiovascular disease, diabetes, and cancer) are responsible for RM 9.65 billion annually as direct healthcare cost [3]. However, the current approach to managing chronic diseases focuses heavily on periodic assessments in clinic setting at weekly or monthly intervals. Here, a predictive analysis framework based on AI technology, leveraging continuous monitoring with patient data …

Intelligent Telemedicine Systems For Contactless Heart Rate Estimation Using Deep Learning-Based Rppg, Do Duc Thinh, Nguyen Duc Manh, Nguyen Thi Bich Ngoc, Vu Van Huan

Journal of Informatics and Web Engineering

Over the last ten years, telemedicine has undergone significant developments, from simple communication-based healthcare to smart and data-driven solutions. The solutions are now powered by Artificial Intelligence (AI), Machine Learning (ML), and Internet of Medical Things (IoMT) technologies. Physiological monitoring is traditionally done with contact-based sensors. The sensors include Electrocardiogram (ECG) and pulse oximeters. The sensors have various disadvantages, including hardware costs, difficulty in continuous usage, and discomfort for patients. Photoplethysmography (rPPG), a remote method of physiological monitoring, is a breakthrough technology. The method is used to estimate physiological signals, including Heart Rate (HR), from video streams captured by standard …

Rapid-Prototyping Nanofabrication: Lcd-Based Projection Lithography And Physical Vapor Deposition, Sabeel Saleem Mohammmed

University Honors Theses

The semiconductor industry's continued growth, driven in large part by demand for artificial intelligence hardware, has highlighted the need for greater workforce development in regions adjacent to major fabrication centers like Oregon's Silicon Forest. This capstone project lays the groundwork for a small scale and student led semiconductor fabrication lab at Portland State University by demonstrating two of the core steps in chip manufacturing: photolithography and thin film deposition. Rather than relying on conventional fixed reticles, this work explores a unique, low cost approach to patterning that uses an ultraviolet-compatible liquid crystal display (LCD) as a programmable reticle, allowing arbitrary …

The Role Of Urban Forests In Mitigating Flooding Effects: A Case Study In Savannah, Georgia, Gillian Bush

Undergraduate Theses, Capstones, and Recitals

Flooding in coastal communities is shaped by the interaction between natural systems and urban development. Chatham County, a low-elevation region in the Savannah, Georgia metropolitan area along the eastern coast of the United States, is prone to coastal storms and frequently affected by flooding. It serves as a useful case study to better understand the factors behind flooding and the areas that are most at risk. This study uses GIS-based analysis to examine the overlap between flood risk, urban forest cover, and impervious surfaces. The results indicate elevated vulnerability along major transportation corridors and barrier islands, where high-risk flood zones …

Fluvial-Tidal Controls On Dune Morphology And The Effects Of Nature-Based Morphology In Mitigating Storm Impacts, Abiola A. Adebiyi

Electronic Theses and Dissertations 2020 - Present

Nature-based morphological features in coastal areas, such as dunes, coral reefs, and seagrass, play dual roles as both receivers of threats from increasing human activity and climate change and defenders that mitigate potential impacts. Therefore, it is imperative to improve our understanding of how these features may affect hydrodynamic processes under various conditions. To address this need, the objectives of this research are two-fold: 1) to enhance our knowledge of changes of bedform morphology in response to different fluvial-tidal controls in the Lower Columbia River (LCR), and 2) to investigate how natural-based features may mitigate tropical storm impacts using a …

Re: Approval Letter For The Quarterly Operations And Maintenance Report Grove Gulch Sedimentation Bay For Fourth Quarter 2025 Silver Bow Creek/Bute Area Npl Site – Butte Priority Soils Operable Unit Consent Decree-Civil Action No. Cv 89-039-Bu-She (Dated May 15, 2026)., Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Phase-Resolved Measurement And Arbitrary Mode Conversion Of Structured Light, Somayeh Ghazanfarpour

Electronic Theses and Dissertations

This dissertation presents a single-shot phase and amplitude retrieval technique based on spatial light modulator (SLM)-based digital holography. The proposed method enables accurate reconstruction of complex optical fields from a single interferogram, reducing sensitivity to environmental fluctuations and improving experimental stability compared to conventional multi-shot approaches. In addition, a programmable arbitrary mode converter is developed using SLM-based wavefront shaping. By introducing controlled astigmatism and engineering the differential Gouy phase between orthogonal components, the system enables flexible transformation between structured light modes, including Hermite–Gaussian and Laguerre–Gaussian beams. Numerical results demonstrate reliable phase recovery and efficient mode conversion, validating the performance of …

Data Governance Maturity, Ai Integration, And Equity In Colorado K-12 Public Schools, John R. Curtin

Electronic Theses and Dissertations

Colorado's 179 K-12 public school districts operate as autonomous governance units, each responsible for securing and managing student data assets that span health, financial, residential, and academic records. The accelerating integration of artificial intelligence (AI) and machine learning (ML) tools into administrative workflows, productivity software, and instructional platforms has fundamentally altered the risk landscape for student data, yet governance frameworks at the state, district, and school levels have not kept pace. This dissertation investigates whether Colorado's decentralized educational governance structure is institutionally capable of producing equitable, secure, and sustainable data governance outcomes in the AI era.

Drawing on Institutional Theory …

Design Principle For Staple-Mediated Stabilization Of Peptides And Proteins, Samantha C. Hatfield

Theses and Dissertations

Macrocyclization, or stapling, has emerged as a powerful strategy to enhance the stability and function of peptides and proteins by constraining their conformational ensembles. Stapling can improve thermodynamic stability, increase resistance to proteolytic degradation, and enhance biomolecular recognition, making it particularly valuable for the development of peptide-based therapeutics. Despite these advantages, staple design remains largely empirical, relying on iterative screening of linker chemistries, lengths, and attachment sites. This trial-and-error approach limits scalability and hinders the rational design of stabilized peptide systems. In this work, we address this challenge by integrating large-scale experimental datasets with molecular dynamic simulations to develop predictive …

Evaluation And Distillation Of Source Code Generation Tasks By Large Language Models, Danny Brahman

Electronic Theses and Dissertations

Large Language Models (LLMs) are predominantly assessed based on their common sense reasoning, language comprehension, and logical reasoning abilities. While models trained in specialized domains like mathematics or coding have demonstrated remarkable advancements in logical reasoning, there remains a significant gap in evaluating their code generation capabilities. Existing benchmark datasets fall short in pinpointing specific strengths and weaknesses, impeding targeted enhancements in models’ reasoning abilities to synthesize code.

To bridge this gap, this thesis introduces two novel contributions: CodeEval and CodeQual. CodeEval is an innovative, pedagogical benchmarking method that mirrors the evaluation processes encountered in academic programming courses. It comprises …

Projected Climate Change Impacts On Soil Greenhouse Gas Emissions From A Restored Freshwater Marsh, Annika Hendrickson

University Honors Theses

Wetlands provide valuable ecosystem services, one of which is a wetlands ability to sequester carbon. Climate change and human land use threaten a wetlands ability to do so. Globally, 21% of wetlands have been lost since the 1700s. As a result, restoration of wetlands has been increasing. However, wetlands in the process of restoration emit more methane than degraded ones, and as the climate continues to change, these fluxes could respond. Projected sea level rise is expected to cause salt water to infiltrate coastal freshwater systems, increasing the salinity. Past research has found that increased salinity has led to suppressed …

Re: Approval Letter For The Quarterly Operations And Maintenance Report Grove Gulch Sedimentation Bay For First Quarter 2026 Silver Bow Creek/Bute Area Npl Site – Butte Priority Soils Operable Unit Consent Decree-Civil Action No. Cv 89-039-Bu-She (Dated May 15, 2026)., Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Comment Letter For The Revised Draft Final Butte Priority Soils Operable Unit (Bpsou) Butte Treatment Lagoon (Btl) System Annual Report – 2025 (Dated May 11, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Medical Image Integrity Protection Through U-Net Based Roi Segmentation And Hybrid Integer Wavelet–Quadtree Embedding, Muna M. Jawad, Rasha F. Nadhim, Noor A. Yousif, Ashwaq T. Hashim

Journal of Intelligent Informatics, Networking, and Cybersecurity

For decades, secure techniques in medical images have focused on securing the sensitive information through limiting direct access to the images themselves. Nonetheless, these methods tend to cause distortion on the images that can affect the diagnostic value and cause loss of crucial information. There arises the fundamental problem of secure embedding of medical data in such a way that does not affect the diagnostic integrity of the image. To overcome this limitation, a secure yet hidden data-hiding mechanism is introduced that is exploited U-Net-based deep learning for accurate Region of Interest (ROI) segmentation. Therefore U-Net architecture is used for …

Re: Conditional Approval Letter For The Draft Final Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites Sister Dump (Bres No. 38) Remedial Action Work Plan (Rawp), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Desert Dichotomies: Climatic Imaginaries Of The Arid+[Ant]Arctic, Amanda Aman

Mavs Open Press Open Educational Resources

Desert Dichotomies is a research-based architecture design studio that examines the impacts of climate change across arid and polar desert environments, revealing unexpected parallels between landscapes often understood as environmental opposites. Focusing on Antarctica, Arctic Alaska and the Sonoran Desert, the project investigates how climate change, resource extraction and human systems of control are transforming ecological processes, water systems and cultural landscapes. While arid deserts face increasing drought and water scarcity, polar deserts are experiencing accelerated warming, ice loss, permafrost thaw and flooding. Despite these contrasting conditions, both regions exhibit similar consequences, including declining water quality, biodiversity loss, infrastructural vulnerability …

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final 2024 Reclamation Improvement Sampling: Bres No. 78 – Original Mine Yard Site Evaluation Summary Report, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Unreclaimed Sites: Ur-03 Construction Completion Report (Ccr), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Revised Draft Final Unreclaimed Sites: New And Mahoney (Ur-23) Construction Completion Report (Ccr), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Beyond Emergency: Charting Pathways To Sustainable Development In Fragile And Conflict-Affected Settings: A Case Study Of Yemen, Sharif Abdurabu Salem Farid Alsahbool

Theses and Dissertations

For nearly a decade, Yemen's eastern governorates of Hadramawt, Shabwah, and Al‑Mahrah have been relatively stable, yet the international aid system has kept delivering short‑term humanitarian relief like food baskets and water trucking instead of shifting to sustainable development that could rebuild people's lives, create jobs, fix infrastructure, and strengthen local government. This thesis investigates why this transition has taken so long. Based on 21 interviews with government officials, international NGO staff, and local NGO managers in these three governorates, the study develops a new way of understanding the problem. It introduces three ideas: the 'emergency mentality', which is a …

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) 2025 Butte Reclamation Evaluation System (Bres) Site Specific Corrective Action Plans For Quadrant 2, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Data-Driven Qoe Inference For Htttp Adaptive Streaming, Tisa Selma

Thesis/ Dissertation Defenses

In HTTP adaptive streaming, accurately inferring user Quality of Experience (QoE) remains challenging due to dynamic network conditions, content variations, end-to-end encryption, intrusive advertisement interruptions, and diverse user engagement behaviors. Conventional approaches, such as ITU-T P.1203, fall short in capturing real-time user perception, accounting for ad related disruptions, or adapting to model drift over time. This dissertation therefore aims to develop a multimodal face emotion recognition (FER) based inference model that predicts QoE under encryption and advertisement conditions while being interpretable, robust, resilient to drift, and highly accurate. To achieve these objectives, a unified framework is designed and implemented. The …

Alternative Treatment Systems To Increase The Drying Rates Of Green Forage Crops, W E. Klinner, O D. Hale

IGC Proceedings (1977-2023)

Forms of conditioning treatment are being developed that aim to minimize the barrier effect of the crop cuticle without sacrificing too much of the structural strength of the herbage. Effective surface abrasion and favorable windrow structure can be achieved with steel-spoked rotors, which are now beginning to be offered commercially. More recently, plastic brushes have been developed because the higher population density and yielding ability of the crop-engaging elements, plus the absence of metal components, appeared to offer additional advantages. Four different brush conditioner systems have been evaluated in the laboratory and in replicated field experiments. Tufted brushes using trilobar …