Digital Commons Network^™

A Proposal Video Encryption Using Light Stream Algorithm, Ataa R. Alawi, Nidaa F. Hassan

Engineering and Technology Journal

Video encrypting is one technique to protect digital videos, it used to avoid unwanted interference and viewing of the transmitted videos. In this paper, a new selective video cryptography algorithm is suggested using light stream algorithm. As it known video size is large in size and it consume time in the encryption process, ChaCha a light encryption algorithm has been used to reduce the encryption time, encryption is done by Xoring frames of video with the key generated from ChaCha algorithm, it produced an acceptable results from robustness point view, but still encryption process consumed time, thus to speed up …

Survey Of Recent Video Watermarking Techniques, Taisir N. Hummadia, Nidaa F. Hassanb

Engineering and Technology Journal

With the development of the Internet coupled with expanding the accessibility of multimedia, various copyright issues have resulted. Several researchers have been working on watermarks to provide the security, durability, and a perception of multimedia. This paper a review of some recent works is presented related to video watermarking techniques, this study focuses on the pros and cons of recent video watermarking, areas of application, and the different types and attacks that are standing against these watermarking techniques. The results obtained from this study showed that watermark techniques based on the transfer domain, are more popular than those of the …

Detection Face Parts In Image Using Neural Network Based On Matlab, Shahad L. Galib, Fouad S. Tahir, Asma A. Abdulrahman

Engineering and Technology Journal

Recently, face recognition system (FRS) is implemented in different applications including a range of vital services like airports and banking systems for security purposes. Therefore, deployed surveillance systems have been established which led to the urgent need to develop a vital face recognition system. In this work, a new algorithm was proposed for recognition of the face, personal and color images by training the convolutional neural network using the MATLAB program to build a new program for detection of the face, then building a separate program to discover the lips, nose, and eyes, New methods were explored to analyze the …

A New Hybrid Technique For Face Identification Based On Facial Parts Moments Descriptors, Shaymaa M. Hamandi, Abdul Monem S. Rahma, Rehab F. Hassan

Engineering and Technology Journal

Robust facial feature extraction is an effective and important process for face recognition and identification system. The facial features should be invariant to scaling, translation, illumination and rotation, several feature extraction techniques may be used to increase the recognition accuracy. This paper inspects three-moment invariants techniques and then determines how is influenced by the variation which may happen to the various shapes of the face (globally and locally) Globally means the whole face shapes and locally means face part's shape (right eye, left eye, mouth, and nose). The proposed technique is tested using CARL database images. The proposal method of …

License Plate Tilt Correction: A Review, Nada N. Kamal, Enas Tariq

Engineering and Technology Journal

Tilt correction is an essential step in the license plate recognition system (LPR). The main goal of this article is to provide a review of the various methods that are presented in the literature and used to correct different types of tilt that appear in the digital image of the license plates (LP). This theoretical survey will enable the researchers to have an overview of the available implemented tilt detection and correction algorithms. That’s how this review will simplify for the researchers the choice to determine which of the available rotation correction and detection algorithms to implement while designing their …

Using Texture Feature In Fruit Classification, Mauj H. Abd Al Karim, Abdulamir A. Karim

Engineering and Technology Journal

Recent advances in computer vision have allowed wide-ranging applications in every area of life. One such area of application is the classification of fresh products, but the classification of fruits and vegetables has proven to be a complex problem and needs further development. In recent years, various machine learning techniques have been exploited with many methods of describing the different features of fruit and vegetable classification in many real-life applications. Classification of fruits and vegetables presents significant challenges due to similarities between layers and irregular characteristics within the class.Hence , in this work, three feature extractor/ descriptor which are local …

Determination Efficient Classification Algorithm For Credit Card Owners: Comparative Study, Raghad A. Azeez

Engineering and Technology Journal

Today in the business world, significant loss can happen when the borrowers ignore paying their loans. Convenient credit-risk management represents a necessity for lending institutions. In most times, some persons prefer to late their monthly payments, otherwise, they may face difficulties in the loan payment process to the financial institution. Mainly, most fiscal organizations are considered managed and refined client classification systems, scanning a valid client from invalid ones. This paper produces the data mining idea, specifically the classification technique of data mining and builds a system of data mining process structure. The credit scoring problem will be applied using …

A Proposed Speaker Recognition Method Based On Long-Term Voice Features And Fuzzy Logic, Iman H. Hadi, Alia K. Abdul-Hassan

Engineering and Technology Journal

Speaker recognition depends on specific predefined steps. The most important steps are feature extraction and features matching. In addition, the category of the speaker voice features has an impact on the recognition process. The proposed speaker recognition makes use of biometric (voice) attributes to recognize the identity of the speaker. The long-term features were used such that maximum frequency, pitch and zero crossing rate (ZCR). In features matching step, the fuzzy inner product was used between feature vectors to compute the matching value between a claimed speaker voice utterance and test voice utterances. The experiments implemented using (ELSDSR) data set. …

Assessing The Performance Of The Evacuated Tube Solar Collector Using Smart Curtain Through (Pso Based Pid) Controller And Nano Fluids, Hosham S.Anead, Khalid F. Sultan, Sura Abdul Jabbar

Engineering and Technology Journal

This research revealed control on Nano fluid temperature in the evacuated tube solar collector system, where Nano fluids used in ETSC as working fluid to increase heating system thermal efficiency. Smart curtain was used to shadow the evacuated tube solar collector and to control the temperature of the Nano fluid in heating or cooling condition which is moved by the stepper motor which is programmed to move through the Arduino board using an artificial intelligence method such as (PSO based PID) controller method . Where the curtain's main idea is to control the polarization of the sun's radiation, the work …

A Brief Survey On Modern Iris Feature Extraction Methods, Hanaa M. Ahmed, Mohammed A. Taha

Engineering and Technology Journal

This paper presents a survey of some of the most recent research work on the extraction phase of the Iris recognition system. Iris biometric system has been used for person recognition in wide applications where person identity authentication required for its stability and uniqueness as compared to other biometric systems. Iris based recognition systems consist of stages are Iris localization, normalization, feature extraction, and matching. The extraction of features influences the precision and reliability of the biometric system, so several methods have been used.

Experimental Investigation Of Thermosyphon Thermal Performance Using Different Filling Ratio, Talib Z. Farge, Samar J. Ismael, Rawad M.Thyab

Engineering and Technology Journal

The present work investigated the thermal performance of thermosyphon by using distilled water as a working fluid at different filling ratios (50%, 60%, and 70 %). The thermosyphon was manufactured from a copper tube with outer and inner diameters (26 and 24) mm, respectively. The thermosyphon was tested experimentally at different input power (100, 200 and 300) Watt. The operating temperature of the oil was chosen below 85°C. Experimental results revealed that the filling ratio of 60% exhibited the best heat dissipation at the highest operating temperature. While the low operating temperature and 50 % filling ratio show better heat …

Direct Shear Strength Of Rpc Member, Shahad Q. Madhlom, Hussein A. Aziz, Ammar A. Ali

Engineering and Technology Journal

In this research paper, results are obtained from Reactive Powder Concrete (RPC) push-off specimens - double L shape subjected to direct shear loading. Different parameters considered are compressive strength, percentages of steel fiber, presence of aggregate and shear reinforcement. The results show that increasing in steel fiber content starting from 0.0% and ending with 1.5% leads to increases in the shear strength by (261%) and attempt to decrease its brittleness. The presence of steel fiber content enhances and improves the tensile strength and the shear strength. Using RPC in constructing the specimens enhances the shear strength by 29.6% compared with …

Attention-Based Ensemble Deep Learning Model For Arabic And English Fake News Classification, Ameer Alhaq Alshamery

Journal of Intelligent Informatics, Networking, and Cybersecurity

It is difficult to classify articles as fake news since one article may consist of true facts with only some statements being fake. Moreover, classification becomes complicated for the Arabic language owing to its morphology and several ways of spelling, as well as the lack of well-classified and marked data sets. This paper presents an Ensemble Deep Learning Model (EDLM) used for Arabic and English fake news classification. The EDLM consists of CNN, Bi-LSTM with attention, and Bi-GRU with attention networks. Each of them produces one probability of the article, which is then summed up to a final probability via …

Novel Dynamic Batch-Sensitive Adam Optimiser For Vehicular Accident Injury Severity Prediction, Daniel Asare Kyei, Alimatu Saadia-Yussiff, Maame G. Asante-Mensah, Abdul Lateef-Yussiff, Charles Roland Haruna, Derry Emmanuel

Iraqi Journal for Computer Science and Mathematics

The choice of optimiser is important in deep learning, as it strongly influences model efficiency and speed of convergence. However, many commonly used optimisers encounter difficulties when applied to imbalanced and sequential datasets, limiting their ability to capture patterns of minority classes. In this study, we propose Dynamic Batch-Sensitive Adam (DBS-Adam), an optimiser that dynamically scales the learning rate using a batch difficulty score derived from exponential moving averages of gradient norms and batch loss. DBS-Adam improves training stability and accelerates convergence by increasing updates for difficult batches and reducing them for easier ones. We evaluate DBS-Adam by integrating it …

Genpix: A Diverse Dataset For Fake Image Detection, Guessoum Dalila, Benblidia Nadjia, Boumahdi Fatima, Remmide Mohamed Abdelkarim, Nouri Tarek-Amine, Bataouche Azeddine-Lotfi

Iraqi Journal for Computer Science and Mathematics

The rapid advancement of sophisticated generative models has intensified the need for robust fake image detection systems. However, many existing benchmark datasets suffer from limited diversity in content types and generation techniques, constraining the generalization ability of detection models. To address these limitations, we introduce GenPix (Generalized Pixels), a comprehensive dataset encompassing over 80,000 images spanning diverse categories, including faces, objects, and scenes, generated by multiple state-of-the-art models such as Generative Adversarial Networks (GANs) and diffusion-based architectures. The dataset includes samples from different generation methods to ensure broad coverage of fake image characteristics.

GenPix provides a realistic evaluation environment that …

Eyolov8-Msaff: An Enhanced Object Detection Algorithm With Multi-Scale Attention And Feature Fusion For Small And Dense Object Detection In Uav Applications, Mohammed Hasan Mutar, Morteza Valizadeh, Alaa Hussein Abdulaal, Mehdi Chehel Amirani

Iraqi Journal for Computer Science and Mathematics

The proliferation of unmanned aerial vehicles (UAVs) has necessitated the development of sophisticated object detection algorithms capable of handling the unique challenges posed by aerial imagery. Traditional detection methods often struggle with small object sizes, dense distributions, and complex backgrounds characteristic of UAV-captured scenes. This research presents EYOLOv8-MSAFF (Enhanced YOLOv8 with Multi-Scale Attention and Feature Fusion), a novel deep learning architecture specifically engineered for superior performance in UAV-based object detection tasks. The proposed methodology integrates four innovative components: a Hybrid Spatial-Channel Attention Mechanism (HSCAM) that processes attention information in parallel rather than sequentially, an Adaptive Multi-Scale Feature Fusion Module (AMSFFM) …

A Novel Hierarchical Multi-Scale Attention Mechanism For Enhanced Yolov8 Performance In Unmanned Aerial Vehicle-Based Small Object Detection, Mohammed Hasan Mutar, Morteza Valizadeh, Alaa Hussein Abdulaal, Mehdi Chehel Amirani

Iraqi Journal for Computer Science and Mathematics

Object detection in Unmanned Aerial Vehicle (UAV) images presents significant challenges due to the prevalence of small and densely packed objects, as well as variations in scale, orientation, and lighting conditions. This paper introduces a novel object detection algorithm, Hierarchical Multi-Scale Attention YOLO (HMSA-YOLO), which is an improved version of YOLOv8 designed to address these challenges. The proposed method incorporates a novel Hierarchical Multi-Scale Attention (HMSA) module, a Bidirectional Feature Pyramid Network (BiFPN) for enhanced feature fusion, a modified loss function, and an adaptive anchor optimization technique. The HMSA module effectively captures both channel and spatial dependencies at multiple scales, …

Dynamic Media Device Power Management Using Proximity Inferred From Wireless Signals, Nikita Agarwal

Defensive Publications Series

Power management for media devices can be inefficient when a user is listening to audio content but is not actively viewing the display, potentially leading to increased energy consumption. Systems and methods can manage display power by inferring user proximity. The technology can utilize wireless signal characteristics, such as a received signal strength indicator from a user's personal peripheral device (e.g., a smartwatch, smartphone, or earbuds), to establish virtual zones around a media playback device. When the system infers that a user has moved from a viewing zone to a listening zone, it can automatically deactivate the display panel while …

Discursive Consciousness And Pedagogical Reasoning Within Teacher Collaborative Inquiry In Rural Mexico, Nelly Yllen Charles Martinez

Theses and Dissertations

This study examines teacher collaborative learning within Matemáticas Equitativas (MATEQ), a school-based professional learning model designed to support equitable mathematics instruction through collaborative inquiry and peer observation. Drawing on Anthony Giddens' structure-agency theory, this research adopts an interpretive qualitative case study with discourse-oriented analysis to examine teachers' pedagogical reasoning by looking at manifestations of discursive consciousness--defined as the capacity to articulate and rationalize one's actions in discourse--during collaborative meetings. Findings show that both the interactional structures and collaborative resources embedded in MATEQ--in particular peer facilitated uses of observation rubrics--mediated teachers' discursive consciousness, strengthening the pedagogical reasoning shared within collaborative inquiry. …

Selective Factors Impacting Charter High School Enrollment, Nathan Marshall

Theses and Dissertations

This study examined factors influencing high school choice among Utah families, comparing parent priorities between charter and traditional public high schools. Using one-way ANOVA with Tukey honestly significant difference (HSD) post hoc comparisons, parental priorities were analyzed across personal, school community, and academic factors. Parents choosing traditional public high schools rated personal and school community factors significantly higher, emphasizing relationships and school climate, while charter high school parents rated academic factors significantly higher, favoring rigor and instructional quality. Charter parents' priorities were not uniform, however, but varied significantly by school model, suggesting that the charter-versus-traditional divide masks meaningful differences within …

Spae: Deciphering Cell Cycle Dynamics And Cell States In Single-Cell Rna-Seq Data, Jiahao Yi, Jiajia Liu, Peng Guo, Yuan-Nong Ye, Xiaobo Zhou

Faculty, Staff and Student Publications

Rapid advances in single-cell RNA sequencing (scRNA-seq) technology have enabled the investigation of gene expression changes at the single-cell level, particularly for elucidating the heterogeneity among cells and complex biological processes. This technique reveals subtle molecular differences within individual cells, thereby offering a unique viewpoint for the investigation of cell cycle progression, cellular differentiation, and disease pathogenesis. However, accurately identifying and analyzing cell cycle dynamics in scRNA-seq data remains challenging due to the complexity of the data and the subtle differences between cell states. To address this challenge, we developed the integrated Sinusoidal and Piecewise AutoEncoder (SPAE), an autoencoder-based piecewise …

Acquisitions Unit Annual Report 2025-2026, Andrée J. Rathemacher

Technical Services Reports and Statistics

Annual Report of the Acquisitions Unit, University Libraries, University of Rhode Island for FY2026. Covers personnel, work flow, special projects, and serial, monograph, and e-resource acquisitions. Supplemental files include data on library materials expenditures by a number of variables as well as important working documents from the year.

Bridging The Gap In Science Research: Preparing Students For College- Level Research In The Sciences, Victoria Helwig, Yaoguang Li

UConn Library Presentations

Many first-year students enter college unprepared to fully engage with scientific literature and academic library resources. Drawing on experiences from academic librarians working with STEM students, this session explores common gaps in science research skills, including navigating databases, identifying scholarly sources, and understanding the structure of scientific literature. Participants will be introduced to practical strategies and classroom-ready activities to better prepare students for college-level research. Discussion questions: What science research skills do students struggle with most when entering college? How can high school instruction better support these skills? Where can librarians and educators collaborate to support student success?

A Mathematical Decision-Making Framework For Athlete Development In A Collegiate Taekwondo Community: Prioritizing Coaching Interventions Using Statistical Analysis And The Analytic Hierarchy Process, King Harold A. Recto, Hazel Jade L. Antonio, Jhyrald Anthony P. Dalida

Electronics, Computer, and Communications Engineering Faculty Publications

Athlete development within collegiate sports communities requires informed decisions regarding the prioritization of coaching interventions and allocation of developmental resources. However, such decisions are frequently guided by experience and intuition, limiting opportunities for systematic and evidence-based decision-making. This study develops a mathematical decision-making framework for athlete development by integrating statistical analysis and the Analytic Hierarchy Process (AHP) within a collegiate taekwondo community. Data were collected from 25 collegiate taekwondo athletes who satisfied established eligibility criteria, including participation in University Athletic Association of the Philippines (UAAP) competitions during the previous three seasons. Athletes evaluated coaching practices across five dimensions: Training and …

Human And Ai Editing Tool Use Among Online Professional Practice/Applied Practice Doctoral Students, Valerie A. Storey, Tracy Greene, Lori Salgado

All Faculty and Staff Scholarship

The purpose of this qualitative study was to explore online professional practice doctoral students' and recent graduates' (2022-2025) use of editing software, GenAI/AI browser extensions, and human editors, examining their practices and institutional policy perspectives. Using Lentz's (2024) ethical authorship framework, researchers analyzed 29 participant responses. Four themes emerged: Foundational Academic Excellence and Support, Innovative Learning and Development, Quality Assurance and Professional Growth, and Inconsistent Institutional Practice and Ethical Oversight. Findings identified distinct functional purposes and five commonalities across editorial resources. Participants strategically employed different resources while maintaining authorial agency and critical judgment, yet reported widespread inconsistency in faculty guidance, …

Comparative Performance Evaluation Of A Gpu-Accelerated Watershed Model For Flood Inundation Mapping, Maliha Ali

Electronic Theses and Dissertations 2020 - Present

This study evaluates PyWMP (Python-based Watershed Modeling and Planning), which is a flood modeling framework developed by the Center for Water Resiliency and Risk Reduction (CWR3) at Florida Atlantic University (FAU). The framework includes a 2D Rain-on-Mesh (ROM) solver, which is an explicit finite-volume shallow-water equation model. PyWMP is compared against HEC-RAS 2D and Flood Modeller for their rain-on-grid capabilities for watershed-scale flood inundation mapping under three design storm scenarios. The performance of PyWMP was evaluated using both quantitative and spatial metrics. Mean absolute error values showed that the average depth difference between each model is under 1 foot. Percent …

Effects Of O-Glcnacylation And Phosphorylation On Tau Aggregation By Cd And Tem, Andrew Whyte Jr.

Electronic Theses and Dissertations 2020 - Present

Alzheimer’s disease (AD) is characterized by the accumulation of extracellular amyloid-β (Aβ) plaques and intracellular neurofibrillary tangles composed of aggregated tau protein. Among the numerous post-translational modifications that regulate tau function, phosphorylation and O-GlcNAcylation have emerged as key modulators of tau aggregation and pathology. While phosphorylation is generally associated with tau misfolding and fibril formation, O-GlcNAcylation has been proposed to exert protective effects through its interplay with phosphorylation. However, the site-specific structural consequences of these modifications remain incompletely understood.

The objective of this work was to develop synthetic tools for the site-specific incorporation of O-GlcNAc and phosphate …

Analysis Of Flood Modeling For The Replication Of An Extreme Rainfall Event In South Florida, Lusnel Fritznel Ferdinand

Electronic Theses and Dissertations 2020 - Present

Flooding is the most common natural disaster in the United States, and trends show an increase in flood risk for the foreseeable future. Florida averages 45 flood disasters per year, at an annual cost of $86 million. Communities in Florida are susceptible to a variety of flood-inducing sources, including tropical cyclones, extreme rainfall, and rising sea levels, which can impact the tourism industry and the economic well-being of residents. The first objective of the thesis was to use flood modeling to replicate the extreme rainfall event that caused heavy flooding in Broward County, Florida, from April 12-13, 2023. A commercial …

Environmental Dna For Endangered Freshwater Mussel Monitoring: A Review On Global Synthesis Of Edna Methods, Challenges, And Innovative Strategies, Mizanur Rahman, Md. Saydur Rahman, Richard J. Kline

School of Earth, Environmental, & Marine Sciences Faculty Publications

Freshwater mussels (family Unionidae) are among the most endangered aquatic species worldwide, making effective monitoring vital for their conservation. Traditional surveys are laborious, time-consuming, and often miss rare or low-density populations. Environmental DNA (eDNA) is a highly sensitive, non-invasive approach for freshwater mussel detection and monitoring; however, uncertainties in ecological interpretation continue to limit its broader application in freshwater biodiversity monitoring. We conducted a systematic review of 49 peer-reviewed studies, identified through an extensive literature search, to assess temporal research trends, methodological advancements, ecological contexts, and regulatory readiness of freshwater mussel eDNA monitoring. Findings show that freshwater mussel eDNA research …

A Data-Driven Framework For Mitigating Breast Cancer Overdiagnosis: From Estimation To Risk-Adjusted Computer-Aided Diagnosis, William M. Brown Jr.

LSU Doctoral Dissertations

In Computer-Aided Diagnosis (CAD) of cancer, standard cost metrics (false-positives and false-negatives) fundamentally fail to account for overdiagnosis. Overdiagnosis is a critical scenario where a disease is correctly detected (true-positive) but is biologically indolent and would never have caused the patient harm or symptoms. While widely recognized in the medical community as a major healthcare crisis driving stressful and invasive overtreatment, overdiagnosis remains severely under-researched within computer science and engineering. This dissertation addresses this interdisciplinary gap by defining the three key computational challenges of overdiagnosis: (i) accurate estimation, (ii) harm quantification, and (iii) algorithmic mitigation. To overcome the estimation challenge, …