Digital Commons Network^™

Basil Oil As An Environmentally Friendly Corrosion Inhibitor For Aisi 1010 Mild Steel Pipes In The Cooling Towers, Mohammed Ali Kadhim, Nagam Obaid Kariem, Rasha Al-Saedi

Baghdad Science Journal

One of the most significant industrial problems is the corrosion of construction metals such as mild steel in pipes and storage tanks of cooling towers. Several preventive measures are used to minimize corrosion. One of them uses various corrosion inhibitors, some of which are organic and others inorganic. Most inorganic corrosion inhibitors are environmentally unfriendly materials. These inhibitors, mixed with cooling tower water, are discharged into rivers or seawater. Many of them are toxic and affect biological life through their ingestion by humans and animals or through their entry into the soil. Basil plant oil is suggested as a new …

Brain Tumor Segmentation Based On Convolutional Neural Network And Integration Of Deep And Shallow Features, Rula Sami Aleesa

Baghdad Science Journal

Segmentation of Brain tumors refers to one of the most challenging problems in analyzing a medical image. To establish accurate brain tumor region delineation, brain tumor segmentation is used. Feature extraction refers to one of the basic steps in the processing of an image that aids classification. Various features’ kinds are extracted from MRI images. The traditional classifiers of Machine learning need hand-crafted features that are time-consuming and susceptible to errors made by humans. Against this, Deep learning is too powerful in terms of feature extraction and has already been extensively applied for the aims of classification. The presented technique …

Crop-Type Mapping Using A Machine-Learning Strategic Approach And A Combination Of Vegetation Indices, Indarto Indarto, Mahrus Irsyam, Fahmi Arif Kurnianto, Wheny Khristianto, Nurud Diniyah

Baghdad Science Journal

Mapping and identifying crop types are essential for predicting crop potential in agricultural fields. The crop-type map can be obtained using remote sensing data. The study area consists of two districts, namely Pasrujambe and Candipuro Districts, located in Lumajang Regency. Sentinel-2 images with 10% cloud cover recorded 12 days were used as input data. The images were processed using the Google Earth Engine (GEE) platform with eight scenarios of vegetation indices combination. Moreover, the most common classification algorithm widely used to produce crop-type maps, Random Forest (RF), was applied to generate crop-type classification maps from Sentinel-2 data. The training and …

Bioinformatics-Inspired Secure Video Encryption Using Chaotic Maps And Light Streaming Algorithms, Rajaa K. Hasoun, Rasha S. Ali, Ahmed G. Hameed, Ghassan H. Abdul-Majeed

Baghdad Science Journal

The Traditional encryption methods, such as AES, can be too slow for large video files, necessitating the development of faster and more efficient solutions for real-time video security. This research aims to enhance video security during transmission by developing a novel video encryption algorithm that is both fast and robust, specifically designed to handle large video datasets efficiently. The proposed video encryption algorithm integrates lightweight streaming algorithms for enhanced speed, modern cryptographic techniques, and chaotic maps for heightened security. The encryption process involves three key steps: Dividing the video into frames and scrambling/encrypting each frame, employing three innovative techniques: vertical …

Selling The Impossible: A Critical Study Of Nostalgia, Persuasion And Ethical Implications, Francois Elmaleh

Masters Theses

This thesis examines the psychological, cultural and iconic influence of mid-20th-century comic book advertising and its enduring influence on modern marketing. With a concentration on adolescent readership, it examines how advertisements in comics shaped consumerist behavior through aspirational discourse, gendered address and emotional manipulation. Through literature reviews, visual analyses and case studies—such as the Charles Atlas bodybuilding campaign, Sea Monkeys and X-ray glasses—this research investigates the rhetorical strategies and ethical ramifications of advertising to children.

The objectives are fivefold: (1) to inventory and analyze dominant advertising strategies employed in comic book ads, (2) to explore how they reinforced cultural and …

A255: Active Health-Oriented Digital Development Of China's National Fitness Events: Connotations, Challenges, And Pathways, Xingyu Fei, Li Liu

International Journal of Physical Activity and Health

The 20th National Congress of the Communist Party of China emphasized building a Digital China and accelerating the digital economy. The "14th Five-Year Plan for Sports" proposed constructing a digital sports project with four platforms and one center, drawing significant academic and industry attention to the digital development of mass fitness events. However, research on digital sports events remains limited, focusing mainly on broadcasting and technology applications. This study explores the challenges of high-quality development in digital mass fitness events and proposes pathways for digital enhancement. Using literature review, logical reasoning, and semi-structured interviews to define the concept of digital …

A017: Research On The Application Of Artificial Intelligence Empowered Blended Teaching In College Physical Education Courses, Heyao Gao, Shouzhong Zhang

International Journal of Physical Activity and Health

With the rapid development of educational informatization in colleges and universities, the blended teaching model has gradually become a hot topic in the field of education. Artificial intelligence, with its powerful data processing and intelligent analysis capabilities, provides new opportunities for the application of blended teaching in college physical education courses. This study aims to explore the application effects of artificial intelligence empowered online-offline blended teaching in college physical education courses, promote the improvement of physical education teaching quality, and the development of students' physical literacy. Method: Questionnaire survey and experimental method adopted. A physical education course university selected as …

A049: Research On The Intelligent Development Path Of New Quality Productivity, Enabling The Sports Park, Yiyang Liao

International Journal of Physical Activity and Health

The new quality productivity is a collection of cutting-edge technologies such as artificial intelligence, big data, and cloud computing, with high-tech, high efficiency, and high-quality characteristics, and is the key engine to enable the intelligent and high-quality development of sports parks. Since the "14th Five-Year Plan" period, the intelligent and high-quality development of sports parks has been the main theme of the national fitness strategy. However, at this stage, the wisdom of sports parks in China is still in the initial stage, and there are many problems to be solved. Therefore, this study conducts an in-depth analysis of the intrinsic …

A141: A Developmental Study Of The Digital Transformation Of University Physical Education Driven By New Qualitative Productivity, Changzhou Xu, Yu Dong

International Journal of Physical Activity and Health

Under the strategic background of ‘Education Modernization 2035’ and ‘Sports Power’, the digital transformation of physical education in colleges and universities is faced with the historic opportunity of being driven by the new quality of productivity. This study focuses on the logic, obstacles, and breakthrough paths of the transformation of university physical education driven by new quality productivity, aiming to build a theoretical framework and propose systematic solutions for the reference of high-quality development. Comprehensive use of literature, expert interviews, and other methods to systematically explore the interaction mechanism between new quality productivity and the digital transformation of physical education. …

A149: Research On The Application Of Artificial Intelligence In Football, Ziliang Ruan, Jingmeng Sun, Shuyue Zhang

International Journal of Physical Activity and Health

With the development of artificial intelligence technology in the sports field, the role of sports data information is becoming increasingly significant. Specifically, in the application of football, artificial intelligence technology is used to scientifically mine data from human sports activities, analyze the patterns of training and competition, intelligently prevent sports injuries, analyze the competitive state of athletes, and form scientific training plans, thereby enhancing the performance of competitive sports and achieving scientific fitness and proactive health. The core concept of artificial intelligence technology is to mine data and explore the patterns within it to explain current phenomena and predict the …

A172: Research History, Hotspots, And Trends Of Triathlon In China, Shiyu Ding

International Journal of Physical Activity and Health

In the 80s of the 20th century, triathlon was widely spread after it was introduced to China. Over the years, with the development of scientific sports training and national fitness, China's triathlon research has gradually attracted attention, and its research involves sports science, medicine, psychology, and mechanical engineering. Therefore, to promote the sustainable development of triathlon in China, this study reviews the history, hotspots, and trends of triathlon research in the past, and provides a theoretical reference for subsequent research. The data in this study were obtained from the China National Knowledge Infrastructure (CNKI) database. A total of 263 relevant …

Usa V. Nicole Schuster

2026 Decisions

USDC for the Eastern District of Pennsylvania

Simulation Study On Nh3 Combustion And NoX Emissions Under Gas Turbine-Relevant Conditions, Kumeesha Arumawadu, Braxton Wiggins, Ziyu Wang

Mechanical and Aerospace Engineering Student Publications and Presentations

Ammonia (NH₃) is a zero-carbon fuel and an attractive hydrogen (H₂) carrier for gas turbine power generation due to its high energy density, ease of storage, and transportation. This study numerically investigates NH₃/air combustion using a hybrid Well-Stirred Reactor (WSR) and Plug Flow Reactor (PFR) model in Cantera at pressures of 1–20 atm, temperatures of 1850–2150 K, and equivalence ratios (ϕ) of 0.7–1.2. The effects of pressure, equivalence ratio, and temperature on NH₃ conversion and NO formation are examined. Results show that NH₃ exhibits a non-monotonic conversion curve with pressure after the …

2026-01-14 What Comes Next? Seattle U Seniors Share Their Stories, Maya Deguzman

The Spectator Online

No abstract provided.

Volumetric Wear Analysis Of Polyethylene Orthopedic Liners Using Point Clouds, Gabriel Landi

Dartmouth College Master’s Theses

In vivo wear of ultra-high molecular weight polyethylene (UHMWPE) orthopedic bearings represents a major problem in shoulder and knee arthroplasty, with significant amounts of devices failing due to the complication itself, and even more due to associated reasons for retrieval, including aseptic loosening. However, quantification of UHMWPE wear has largely been limited to linear and in vitro volumetric analyses, obscuring the understanding of the amount of clinically relevant material loss. This study proposes new methods to measure articular, rim, and backside surfaces of retrieved shoulder and knee UHMWPE liners, centered around the coordinate measuring machine (CMM)-based collection of high density …

A Neutrosophic Homological-Gröbner Framework For Ai-Driven Media Education Evaluation, Mona Gharib, Hafiz Muhammad Athar Farid, José M. Merigó, Muhammad Riaz

Sustainable Machine Intelligence Journal

The integration of artificial intelligence (AI) with media technologies has transformed teaching in Journalism and Communication, introducing new challenges for quality evaluation. Traditional assessment methods fail to capture the uncertainty, inconsistency, and incompleteness inherent in modern educational data. This paper proposes a Neutrosophic Homological–Gröbner Framework, which unifies three perspectives: neutrosophic sets to encode uncertain evidence, homological algebra to analyze structural coherence, and Gröbner bases to systematically simplify interdependent evaluation rules.

Within this framework, diverse evidence is encoded into neutrosophic triplets, daggregate into course-level indicators, and organized into neutrosophic chain complexes, where Betti indices reveal coherence and fragmentation. Educational policies are …

High-Performance Deep Learning Techniques For Plant Disease Detection: Performance Analysis, Validation, And Applications, Doaa El-Shahat, Ahmed Elmasry

Sustainable Machine Intelligence Journal

The early detection of plant diseases is an indispensable task to improve crop yields and production quality. Crop disease observations by experienced pathologists are difficult and might take a long time. Therefore, deep learning (DL) techniques have been utilized to present an automated detection technique that could accurately and timely detect plant diseases. Several DL models in the literature were proposed, but no paper conducted a comparative study between those models to determine which of them was the best alternative for this task. Therefore, twenty-one DL models are compared in this review paper to show which of them could achieve …

Rf-Et-Ann: Hybrid Machine Learning Model For Forecasting Short-Term Photovoltaic Power Production, Walid Abdullah, Ahmed Ismail Ebada, Mohamed Abouhawwash

Sustainable Machine Intelligence Journal

Accurately forecasting photovoltaic (PV) power generation is a challenging problem due to the non-linear and highly variable characteristics of solar data, which is strongly influenced by several interdependent factors, such as environmental conditions, system characteristics, and technical aspects. In this study, a newly proposed machine learning (ML) technique based on integrating random forest (RF), extra trees (ET), and artificial neural networks (ANN) is presented to tackle this problem with better predictive accuracy, ensuring that solar energy is used more consistently, effectively, and economically; this model is dubbed RF-ET-ANN for short. Hybridization of these three models will help capture non-linear aspects …

Gnmsa: An Accurate Parameter Estimation Of Semi-Empirical Proton Exchange Membrane Fuel Cells Model Using A Hybrid Artificial Intelligence–Based Optimization Approach, Dina Atef, Doaa El-Shahat, Hafiz Burhan Ul Haq, Zaka Ur Rehman, Muhammad Nauman Irshad

Sustainable Machine Intelligence Journal

The PEMFC parameter estimation problem has recently piqued the interest of several researchers due to its significance in reaching better PEMFC modeling. However, existing PEMFC parameter estimation algorithms encounter significant difficulty in solving this problem because of its complex and highly nonlinear nature. Therefore, this paper presents a new hybrid approach, termed GNMSA, for addressing this problem more accurately. This hybrid approach combines the exploration operator of the generalized normal distribution optimization with the exploitation operator of the mantis search optimization (MSA), resulting in this strong variant that has high abilities to alleviate stagnation in local optima and expedite convergence …

An Enhanced Optimization Algorithm For Estimating Pem Fuel Cells Parameters: Performance Comparison And Real-World Applicability, Ibrahim Alrashdi, Karam M. Sallam

Sustainable Machine Intelligence Journal

Accurate modeling is critical for the efficient design, control, and optimization of a proton exchange membrane (PEM) fuel cell. This problem is regarded as a multi-modal, multi-variate, non-linear optimization problem, and several methods in the literature have been presented to tackle it. However, those methods still suffer from either being stuck into local optima or a slow convergence rate. To solve this problem more accurately in terms of final results and convergence speed, this study proposes a hybrid optimization algorithm based on enhancing the recently proposed crested porcupine optimizer (CPO) using two new optimization methods, namely ranking-based optimization and exploration-exploitation …

Deep Learning In Precision Agriculture: A Systematic Review Of Methods, Datasets, And Applications, Mariam Ahmed

Sustainable Machine Intelligence Journal

With the growing demand for food and water for the world population. Deep learning is one of the most powerful approaches for smart agriculture, offering the capacity for accurate and fast data manipulation and decision-making. To this end, this study contributes to the body of knowledge as follows. We present a comprehensive review of deep learning methods commonly applied in precision agriculture, categorized into three main categories: discriminative, generative, and hybrid models. Given the data-driven nature of DL, we provided a structured overview and tabulation of available datasets in precision agriculture, by categorizing them according to modality to guide dataset …

Securing U.S. Leadership In Agentic Ai Literacy And Adoption: U.S. Vs Chinese Government Policies And Initiatives, Satyadhar Joshi

Harrisburg University Other Works

This paper conducts a comparative analysis of U.S. and Chinese frameworks for AI literacy and adoption, with focus on agentic AI and Artificial General Intelligence (AGI) systems capable of autonomous reasoning and execution. We examine national policies, educational integration, governance structures, and technological roadmaps, employing both qualitative review and quantitative modeling. Mathematical formulations include multi-dimensional literacy scoring, Bass diffusion models for adoption dynamics, risk assessment functions, regulatory effectiveness indices, competitiveness metrics, and optimization frameworks for resource allocation. Our analysis reveals divergent paradigms: the U.S. Favors decentralized, innovation-driven approaches with emphasis on interoperability and public-private collaboration; while China pursues centralized, state-led …

The Bg News January 14, 2026, Bowling Green State University

BG News (Student Newspaper)

The BGSU campus student newspaper. January 14, 2026. Volume 105-Issue 13.

Weighing The Power Of Ai Against Its Impact, Kallie Bauer, Emily Brenner

Research, Reports, and Publications

No abstract provided.

Robust Qr Code Counterfeit Detection By Integrating Vgg19 Neural Embedding And Triplet Loss, Gede Putra Kusuma, Yulianto Yulianto, Renaldy Fredyan, Hendi Chandi, Jeffry William Tan, Philip Kwan, Muhammad Dafa Syukur

Baghdad Science Journal

Detecting counterfeit Quick Response codes plays a critical role in protecting the integrity of products and documents. This paper presents a novel methodology to increase the reliability of QR code counterfeit detection by integrating neural embedding VGG19 and triplet loss. The approach uses deep neural networks. Specifically, the modification of the VGG19 architecture is used to extract unique features from QR codes. These features are embedded in a multi-dimensional space using neural embedding methods. The use of the triplet loss function aims to increase the discriminative power of the embeddings, ensuring the discriminative power of the embeddings, and ensuring that …

Reproducible Semantic Data Management Workflow For Materials Data Science: Generating Knowledge Graphs With Robust Fairifcation Pipelines, Kyle R. Henrikson, Van D. Tran, Meredith Francis, Isabella Giammattei, Quynh D. Tran, Laura S. Bruckman, Erika I. Barcelos, Roger H. French

Student Scholarship

Combining data from multiple sources is crucial for efficient knowledge aggregation in materials data science. FAIR data from ontology and Linked Data principles enable this. Semantic data management streamlines data exchange and aggregation, ensuring information is available and extractable. FAIRLinked and GraphDB provide solutions for consolidating, hosting, and extracting meaningful insight from multimodal data.

Africa's Global Influence, Faez Al-Haq - Abidemi Salami

Masters Theses

This thesis believes in the design and production of an interactive kids' coloring book on Africa's extensive influence on world cultures, history, economies, and artistic heritage. In a bid to reverse centuries of misrepresentation and large-scale miseducation regarding Africa within early childhood textbooks, this work aims to design an interactive, kid-friendly guide that informs young readers about the central role Africa plays in today's world. Informed by thorough literature review and referencing case studies of successful education and culture intervention, the proposal positions Africa's global reach, spanning from its precolonial trading networks, philosophic structures, diaspora contributions, art heritage, and cultural …

Trauma-Informed Practices (Tips) And Burnout, Job Satisfaction, And Ptsd In First Responders, Tyler Mcdonough

Doctoral Dissertations and Projects

First responders are the frontline defense of society and consist of people that push back against chaos to keep our communities civilized and in functioning order. This study aimed to ensure that first responders’ mental health is adequate for home life as well as daily job functions, and to assess which Trauma Informed Practices (TIPs) can lead to positive outcomes in reducing first responder’s feelings of burnout, increasing their job satisfaction, and suppressing frequency of PTSD symptoms. TIPs are different intervention techniques that are designed to assist the individual with a variety of emotions such as anxiety, stress, burnout, and …

Vietnam Music Education For Professional Careers In The Music Industry, Dylan Bao Nguyen

Doctoral Dissertations and Projects

Vietnam, a country in Southeast Asia, holds a rich cultural heritage and diverse musical traditions that span more than four thousand years. The country began commercializing its music industry around 1997 and expanded it into a significant national sector by 2015. Even with this expansion, Vietnamese music remains largely unfamiliar to global listeners, creating an urgent need for strong music education programs that support the industry’s development. To understand why Vietnamese music struggles to achieve global visibility in the age of globalization, researchers must examine the current conditions of music education and identify the specific factors that limit its international …

Algorithmic Editors: Section 230, Big Tech, And The Need For Clarity, Richard Gruters

Seton Hall Law Review

No abstract provided.