Digital Commons Network^™

Application Of A Generative Adversarial Network To Super-Resolution Reconstruction Of Fracture Images In Logging-While-Drilling Electrical Resistivity Imaging, Han Sen, Shen Chuanhai, Xu Chen, Tian Yimeng, Zhao Biao, Wang Ze, Liu Yongkang, Kang Zhengming

Coal Geology & Exploration

Objective Logging-while-drilling electrical resistivity imaging (LWD-ERI) enables the intuitive presentation of geobodies near wellbores in images, representing an important approach to the fine-scale evaluation of stratigraphic parameters while also providing significant geological guidance during the drilling of fractured reservoirs. However, this technique faces the challenge of low image resolution in real-time data processing due to its limited well-to-surface data transmission rates, exerting adverse impacts on the qualitative identification of wellbore fractures and the quantitative evaluation of their parameters. To address this issue, this study proposed a super-resolution image reconstruction method based on a generative adversarial network (GAN), aiming to achieve …

A Surface Wave Inversion Method Incorporating Interface Constraints And Its Application In The Assessment Of Ground Vibrations Caused By Mining-Induced Seismicity, Li Cheng, Qian Changbao, Liu Ying, Cheng Yi, Ni Shengjun, Yao Huajian

Coal Geology & Exploration

Objective In mining areas of western China, underlying interfaces with significant fluctuations affect seismic exploration accuracy while also posing challenges to the assessment of ground vibrations triggered by dynamic hazards such as mining-induced seismicity. To enhance the characterization of shallow velocity structures and to provide support for dynamic hazard prevention and control in mining areas, this study developed an inversion method incorporating prior information about geological interfaces.Methods A dense array consisting of 489 single-component and 108 three-component seismometers was deployed within a mining area in Longkou Town, Junggar Banner, Inner Mongolia. Accordingly, continuous ambient noise data for about one …

Enhanced Botnet Detection Using A Modified Naïve Bayes Algorithm With Laplace Smoothing And Famd-Based Feature Agglomeration, Ahmed L. Alshami, Bashar M. Nema, Alaa H. Al-Hamami

Baghdad Science Journal

Botnets turned into a security problem that would put user privacy and security at risk. Progressive and flexible Machine Learning (ML) techniques are necessary for robust botnet revealing. In this study researchers presented an integration of the modified Naïve Bayes and M3L algorithms that uses Factor Analysis of Mixed Data (FAMD) for feature aggregation, and Laplace smoothing for adjustment to address the limitation of conventional Naïve Bayes classifiers for detecting botnet. The modified algorithm uses Laplace smoothing to address problems with zero-frequency data and improve the classifier's adaptability. FAMD was used to merge continuous and categorical features to improve the …

Recognition Of Arabic Derived Handwritten Letters Using A Vgg-Like Convolutional Neural Network, Mouhssine El Atillah

Baghdad Science Journal

Due to its complexity, the Arabic language and its extensions build a fertile field of research in the field of artificial intelligence in general and optical character recognition (OCR) specifically. There are several languages that use the Arabic alphabet in their manuscripts. These languages innovated new letters to pronounce sounds not found in the Arabic language. These letters are called 'Arabic-derived letters'. To enrich the Arabic language, we can use these letters to know the true pronunciation of intrusive words in the Arabic language. This article deals with the Arabic-derived letters (ADL) dataset. It is a new dataset that consists …

Silver Bow Creek Conservation Area (Sbcca) – Revised 95% Programmatic Technical Specifications Submittal, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Mould Risk Prevention In Healthcare Facilities In Hot And Humid Climates Through Acmv Air Supply Parameter Optimisation: Development And Validation Of A Multi-Objective Optimisation Framework, Jiang Kaiyun

Student Works (2020-2029)

Air conditioning mechanical ventilation (ACMV) supply parameters—such as airflow rate, temperature, and humidity—significantly influence indoor thermal and hygrometric conditions, influencing airflow patterns and mould proliferation. In healthcare facilities, mould poses significant health risks, particularly for immunocompromised patients, contributing to respiratory issues, allergic reactions, and infections. While ACMV systems are central to infection control and indoor air quality, conventional designs often fall short in hot and humid climates. Existing practices typically prioritise high air change rates (ACH) without sufficient dehumidification, underestimate humidity control, and assume spatial homogeneity, overlooking microclimates conducive to localised mould growth. To address these limitations, this research develops …

Stuyvesant Square Apts Llc V. Vorick

All Decisions

The landlord commenced a holdover proceeding against the tenant, alleging illegal residential occupancy of a former medical office due to uncorrectable building code violations concerning courtyard dimensions affecting natural light requirements. The court granted the landlord a final judgment of possession, finding the unit could not be legalized. However, the court also awarded the tenant treble damages for rent overcharge, holding that a commercial unit used residentially can be rent-stabilized. It dismissed the tenant's harassment claim, distinguishing "dwelling" from a narrower "dwelling unit," but granted an order to correct violations. The tenant's request for attorneys' fees was denied as they …

The Use Of Artificial Intelligence For Innovation In The Public Procurement System, Karem Sayed Aboelazm, Khalid Mohamed Dganni, Fady Tawakol, Raghda Raafat

All Works

Public procurement represents a substantial share of national economies and is increasingly shaped by the deployment of artificial intelligence (AI). The research problem addressed in this study concerns how AI can be integrated into public procurement systems without undermining core principles of transparency, accountability, and legality. The purpose of the paper is to examine the transformative potential of AI in public procurement while identifying the legal, institutional, and ethical challenges it generates. Methodologically, the study adopts a comparative analytical approach based on procurement laws, government reports, and peer-reviewed scholarship, focusing on the United Arab Emirates (UAE), Estonia, and South Korea. …

Incidence Of Autoimmune Diseases In Children With Atopy Treated With Dupilumab, Stanislaw J Gabryszewski, Kathryn Hirabayashi, Morgan Botdorf, Mitchell Maltenfort, Christopher B Forrest, Theresa W Guilbert, Madeline Schutt, Hiroki Morizono, Gerardo Vazquez Garcia, Anna Cristina Garza-Mayers, Joseph Demetrius Hernandez, Sara Anvari, Suchitra Rao, Jonathan M Spergel

Faculty, Staff and Students Publications

Background: The type 2 inflammation-blocking agent dupilumab has gained traction as an effective treatment of multiple atopic diseases. New-onset autoimmune manifestations have been infrequently reported in dupilumab-treated atopic patients, primarily among adults. Autoimmune outcomes in atopic children on dupilumab are less clear.

Objective: We aimed to determine if dupilumab treatment of atopic children is associated with increased autoimmune or autoinflammatory disease diagnosis risk.

Methods: Using a multi-institutional electronic health record database composed of 10 PEDSnet academic health systems, we performed a retrospective cohort study of children aged 6-17 with atopy (ie, moderate-to-severe atopic dermatitis and/or persistent asthma, as defined by …

Midweek Memo, Georgia Southern University

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Recent Advances In Graphene-Based Field-Effect Transistor Biosensors For Disease Biomarker Detection And Clinical Prospects, Deeksha Nagpal, Anup Singh, John Link, Abijeet Mehta, Ashok Kumar, Vinay Bhudhraja

Health & Biomedical Sciences Faculty Publications

Field-effect transistor (FET) biosensors using graphene have become one of the most promising biosensing platforms for the early diagnosis of diseases with features such as high sensitivity, label-free detection and application compatibility with point-of-care systems. Herein, we critically discuss recent advances in graphene FET (GFET) biosensor development toward clinically relevant biomarkers associated with representative diseases including cancer, neurodegenerative disease, infectious disease, and inflammatory conditions. Recent progress was reviewed to evaluate GFET architectures, surface functionalization methods, and detection quality. The biomarkers explored were clusterin in Alzheimer’s disease, thrombin in coagulopathy, estrogen receptor α (ER-α) in breast cancer, Carcinoembryonic antigen in lung …

Secure Machine Learning In Networking Systems, Wenwei Zhao

USF Tampa Graduate Theses and Dissertations

With the rapid integration of Machine Learning (ML) into networking systems, ensuring the security and trustworthiness of these intelligent frameworks has become a paramount concern. While ML offers unprecedented capabilities in spectrum management and collaborative learning, it also introduces novel vulnerabilities that can be exploited by sophisticated adversaries. This dissertation investigates and addresses critical security challenges across three key dimensions of ML-driven networking: adversarial spectrum sensing, the security of privacy-preserving unlearning processes, and efficient post-attack model recovery.

First, we address the threat of adversarial spectrum attacks in cognitive radio networks, where malicious nodes manipulate sensing reports to disrupt spectrum access. …

The Molecular Determinants Of Deglycation And Substrate Specificity In Fructosamine Kinases, Jenet Matlack

USF Tampa Graduate Theses and Dissertations

Protein glycation is a universal, non-enzymatic modification that occurs when a sugar covalently attaches to a primary amine. These spontaneous modifications may have deleterious or regulatory effects on protein function, and their removal is mediated by the conserved metabolic kinase fructosamine-3-kinase (FN3K). Despite its crucial role in protein repair, we currently have a poor understanding of how FN3K engages or phosphorylates its substrates. Additionally, the molecular basis for the distinct yet overlapping substrate specificities of FN3K and its paralog, ketosamine-3 kinase (KT3K), remains unresolved. By integrating structural biology, biochemistry, and ancestral protein reconstruction (APR), this thesis elucidates the catalytic mechanism …

Multi-Modal Tensor Fusion For Alzheimer’S Disease Recognition, Mason Li, Tiffany Le, Jiajing Huang, Yuxin Wen

Engineering Faculty Articles and Research

Accurate and early diagnosis of Alzheimer’s disease (AD) is critical for effective intervention, disease monitoring, and patient care. Traditional diagnostic approaches rely on a single modality, such as clinical assessments, neuroimaging, or genetic markers, which may fail to capture the complex, multifaceted nature of AD. Multimodal learning has therefore been explored to integrate complementary information across data sources. However, conventional fusion strategies, including early feature concatenation and late decision-level fusion, often model modalities independently and fail to capture high-order cross-modal interactions. To address these limitations, we propose a multimodal tensor fusion network (MTFN) that integrates heterogeneous data sources, including visual …

Effective Marketing Strategies Of Private Entities For Leading The United States Military Armed Forces, Harry B. Willis Iii

Walden Dissertations and Doctoral Studies

Ineffective marketing strategies contribute to lower retention outcomes by failing to communicate the value of training programs and build sustained community engagement. Training managers must implement intentional marketing strategies that strengthen community engagement and improve participant retention. Grounded in organization theory, the purpose of this qualitative pragmatic inquiry was to explore the successful marketing strategies used by training managers of private organizations in the United States to increase military numbers. The participants were six training managers from the Southwest United States. Data were collected from semistructured interviews. Through thematic analysis, four themes emerged: (a) marketing strategies, (b) training managers, (c) …

Evaluation Of Nurses' Leadership Self-Efficacy In Belize, Ruth Rosalee Reina Jones

Walden Dissertations and Doctoral Studies

Nursing leadership in Belize is lacking but crucial to the well-being of patients, families, and the healthcare team. The purpose of this non-experimental, descriptive, comparative study was to a) determine the difference in leadership self-efficacy for current nurse leaders with three years or less of leadership experience compared to current nurse leaders with more than three years of leadership experience in Belize, and b) examine the differences in leadership self-efficacy between nurses in a leadership position and nurses not in a leadership position in Belize. The theories supporting the study were Burns’ transformational leadership theory and leadership self-efficacy, based on …

Using The Karush-Kuhn-Tucher Optimization Method On A Finite Fuzzy Markov Chain, Marwan S. Jameel, Zeiad Yahya Ali Allawee, Rana Z Al-Kawaz, Sura J Hussein

Baghdad Science Journal

It is highly interesting to explore the implications of Markov chain stability because its importance in engineering, dynamic systems, energy subject and decision-making issues. This paper deals with a method to assess the stability of Markov chains, finishing our notes in finite fuzzy Markov chains. The optimization of KKT was evaluated in two approaches: a. For one thing, optimized KKT methods substitute the random transition probability with a fuzzy value in the transition matrix. The problem illustrates the efficacy of method in proving the unique properties for power bounds of a 3 × 3 matrix depending where on this it …

Predictive Reliability Assessment And Profit Optimization Of An Ice Cream Plant Using An Artificial Neural Network Technique, Akash Tewatia, Surbhi Gupta, Manju Kashyap, Archana Chauhan

Baghdad Science Journal

This study presents a reliability analysis of an ice cream manufacturing facility based on operational failure data. The research develops a ten-component system model that captures plant dynamics and organizes it into three subsystems to reduce computational complexity. The study derives key reliability parameters and constructs a state transition diagram to represent system behavior across multiple operating states. The analysis applies an Artificial Neural Network (ANN) to address the limitations of conventional analytical methods in modeling complex nonlinear systems. The ANN provides strong predictive performance and manages uncertainty within the operational environment. The proposed framework estimates system reliability with high …

New Statistical Distribution Smart1, Saad Naji Al-Azzawi, Mahmood A. Shamran, Aseel H. Ali

Baghdad Science Journal

This paper introduces a new nonclassical statistical distribution, SMART1, derived from a nonpolynomial function. This function is used in ecology to model population growth rates, in medicine to classify the relationship between activity and tumor volume in cancer, and in economics to analyze the relationship between supply and demand. The proposed distribution differs from the Gompertz distribution, which is fundamentally based on the exponential function. By contrast, the SMART1 distribution is constructed on principles of mathematical analysis, specifically through the identification of local maximum endpoints of the Gompertz growth function and the subsequent verification that the resulting function satisfies the …

Leveraging Feature Fusion And Convolutional Neural Networks For Concrete Crack Prediction, Amal Abdulbaqi Maryoosh, Saeid Pashazadeh, Pedram Salehpour

Baghdad Science Journal

Detection of cracks in concrete is crucial for the safety of bridges and the overall infrastructure. This paper presents a new hybrid method that combines handcrafted and deep features to significantly improve classification accuracy. Texture and semantic information are captured using Local Binary Patterns (LBP) and a pre-trained Xception model, respectively. These features are converted by the Bag of Visual Words (BoVW) method, combined, and the best features are selected by using the Apriori algorithm. The selected features are classified utilizing the light MobileNetV3, a large network. Our method is tested on four public datasets, namely CODEBRIM, DIMEC, Crack, BCD, …

Dual Focus Attention Block Unet (Dfab-Unet) For Robust Skin Lesion Segmentation, Fallah H. Najjar, Farhan Mohamed, Mohd Shafry Mohd Rahim, Diana Sofia De Oliveira Bernardo, Luís Filipe Almeida Bernardo, Vei Siang Chan

Baghdad Science Journal

Skin cancer is the most fatal type of cancer worldwide. Prognosis is generally much better with early detection and effective treatment relies on an accurate diagnosis of skin lesions. Despite progress in deep learning, there is still a challenge to provide accurate segmentation of dermoscopic skin lesions due to image variations stemming from different illuminative input parameters, different resolutions/image sizes, image artifacts and varying skins. These differences hinder state-of-the-art models from learning pixel-precise lesion boundaries or more contextual features, consequently impairing their generalization and clinical applicability. We introduce a new architecture called Dual Focus Attention Block UNet (DFAB-UNet) with intrinsic …

What Is The Contribution Of Thermal Selection To The Maintenance Of A Shell Color Cline In Littorina Saxatilis?, Ramón Vigo, Sarah L.Y. Lau, Juan Gefaell, Juan Galindo, Gray A. Williams, Manuela Truebano, Emilio Rolán-Alvarez

School of Biological and Marine Sciences

The study of clines, or geographical variations of a given trait, can help understand how the interactions of genetics and local environments determine phenotypic diversity. The marine snail Littorina saxatilis (Olivi, 1792) exhibits a gradual change in the relative frequencies of shell color morphs across populations in the estuary system of the Rias Baixas (Galicia, NW Iberian Peninsula). A consistent pattern of distribution occurs across these four Rias, with the interior, sheltered regions dominated by a light fawn-like morph (fulva), and the exterior, wave-exposed locations by a darker lineated morph (lineata). Measurements of rock surface temperature along one of the …

Spartan Daily, March 25, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 27

Examining The Bioethanol Yield Potential Of Varying Ratios Of Jicama (Pachyrhizus Erosus) And Footstool Palm (Saribus Rotundifolius) Stalk, Luke Gabriel R. Mara, Sasha Marie C. Haresco, Alyssa Shane M. Arro, Shalemar O. Baldoza, Raphael Carlos V. Bunga, Rica Michaela G. Dosal, Angela A. Garan, Keona Denise C. Marquez, Isabelo Raphael M. Siguenza, Kristoff Isaiah R. Soreta, Kian Stephen Torrijos, Marionne Lorraine R. Valdez, Sky Lance S. Valiente, June Ray O. Filler

DLSU Senior High School Research Congress Conference Proceedings

This study aimed to examine the bioethanol yield potential of varying ratios of Jicama (J) and Footstool Palm Stalk (FPS). The prototype used a mixed feedstock approach and was developed using the Separate Hydrolysis and Fermentation (SHF) method to extract and ferment sugars to produce ethanol. The study measured bioethanol yields by employing a posttest-only controlled group design consisting of a negative control group and three experimental groups. The results demonstrated that Experimental 3 exhibited the highest average initial sugar yield (3.71g), while the Negative Control showed the lowest average initial sugar (1.5g), showing the high sugar potential of Experimental …

Evaluating The Absorption Capacity And Ph Level Properties Of Varying Ratios Of Garlic (Allium Sativum) And Onion (Allium Cepa) Peels For The Absorbent Core Of Sanitary Napkins, Rhys Mari C. Cortezano, Jezreel Keren C. Manait, Avryl Charlizze P. Sampan, Alyannah Dennise C. Castro, Isabelle C. Romero, June Ray O. Filler

DLSU Senior High School Research Congress Conference Proceedings

Considering the need for sustainable and enhanced menstrual hygiene products, this study aimed to assess the absorption capacity and average pH value of varying ratios of onion (Allium cepa) and garlic (Allium sativum) peels in developing an eco-friendly absorbent core for sanitary napkins. Employing a pre-experimental one-shot case design, the experimental group undergoes pH and absorbency tests. The evaluation focused on measures of absorbency and pH levels of the sanitary napkin cores made from three different fiber ratios: 6g onion-4g garlic, 4g onion-6g garlic, and 5g onion-5g garlic, each combined with 10g of organic cotton. Results indicated that Ratio 3 …

Evaluating The Mechanical Performance Of Eco-Fiberboards Made From Varying Ratios Of Water Hyacinth (Eichhornia Crassipes) And Laundry Lint Microfibers, Iommi M. Vacaro, Joaquin Vielle D. Palomo, Denise Rose D. Verzosa, Udelle Y. Establecida, Ma. Annie Bien M. Sumague, June Ray O. Filler

DLSU Senior High School Research Congress Conference Proceedings

This study explored the viability of hybrid eco-fiberboards as an alternative to commercially available fiberboards. It aimed to evaluate the mechanical performance of water hyacinth (WH) and laundry lint (LL) microfibers, bound within a high-density polyethylene (HDPE) matrix to create a sustainable fiberboard. Three experimental groups with varying fiber ratios were tested for tensile and flexural strength. The results were then compared to medium-density commercial fiberboards (Positive Control), which served as a benchmark. The flexural test results showed that the experimental group with the highest LL content had a maximum strength of 35.13 MPa, comparable to that of the control …

Fitness Odyssey: The Development Of A Fitness Application For Gamifying Habit-Forming Activities That Improve The Physical Health Of Grade 12 Students, Denzyll Yuro B. Umali, Ruzzel Rey P. Barredo None, Karl Nikolai S. Parra, Frederik Louise Rosales, Myrla De Luna Torres

DLSU Senior High School Research Congress Conference Proceedings

The increasing prevalence of sedentary behavior among adolescents, inadvertently from the rapid integration of technology in day-to-day lives, raises concerns about the physical health of modern lifestyles. As teenagers and students spend more time on their phones, there is an urgent need to reframe digital tools as a solution for inactivity. This study aims to develop and evaluate Fitness Odyssey, a fitness application that gamifies physical activities, making them more engaging and rewarding for adolescents. The application tracks six primary exercises—walking, push-ups, sit-ups, squats, jumping jacks, and lunges—using a mobile phone’s accelerometer, developed with the Godot software engine. The research …

Vol. 6 Full Issue

V Music Magazine

No abstract provided.

For My People, Irma Rodriguez

CouRaGeouS Cuentos: A Journal of Counternarratives

No abstract provided.

Drone Based Operational Cloud Seeding, Jared Smith

Spring Runoff Conference

Cloud Seeding: Next Generation Operations and Validation

What is Winter Cloud Seeding? 

• The act of introducing favorable dust particles into a cloud to promote ice crystal nucleation 
• Requires naturally occurring clouds and cold temperatures 
• Aimed at enhancing winter snowpack