Digital Commons Network^™

Real-Time Read And Analysis Of Air Pollution Produced From Private Electrical Generators In Mosul City Using Lorawan, Mahmood Alfathe, Awfa Aladwani, Ali Abduljabbar

Journal of Informatics and Web Engineering

This study presents a novel, site-specific deployment of a Long Range Wide Area Network (LoRaWAN)-driven air pollution monitoring network specifically for the Iraqi city of Mosul, which is beset by widespread power outages and extensive utilization of decentralized diesel generators. While these generators mitigate electricity shortages, they are enormous contributors to urban air pollution, emitting high levels of CO2 and particulates. As opposed to previous studies, which concentrate on affluent urban areas, this research addresses a very deprived locale using an extensible low-power, low-cost LoRaWAN network and high-precision CO2 sensors (Sensirion SCD30 and MH-Z19) and The Things Network (TTN) for …

A Scoping Review Of Artificial Intelligence Research Trends In Mobile Applications, Asmau Usman, Ibrahim Anka Salihu, Abdulrahman Aminu Ghali, Bilkisu Larai Muhammad Bello, Aminu Aminu Mu'azu, Amina Sambo Magaji

Journal of Informatics and Web Engineering

Over the past decade, mobile devices have become an integral part of our daily routines, offering a broad spectrum of applications that enhance everyday tasks. As more people adopt smartphones, developers are increasingly focusing on improving app quality, particularly by incorporating artificial intelligence (AI) features. This growing trend has led to a surge of interest from both researchers and industry experts, who are aiming to explore AI integration in sectors such as healthcare, education, agriculture, and e-commerce. This study conducts a thorough review of AI applications on mobile platforms by analysing 98 scholarly articles published between 2014 and 2024 from …

Impact Of Data Quality Types On Computational Time In Data Source Selection Using Ant Colony Optimization, Nor Amalina Mohd Sabri, Abd Samad Hasan Basari, Nurul Akmar Emran

Journal of Informatics and Web Engineering

Data quality varies dramatically from source to source, even within the same domain. Given these challenges, data source selection has emerged as a crucial step in information integration. It demands efficient and scalable approaches that can handle massive data volumes while ensuring the quality of results. Adapting the ACO algorithm to solve the data sources selection problems may lead to inconsistent computational time if the data sources provided are vary in quality. These challenges bring the issues of time consuming in selecting the required data sources. However, how much the computational time needed in solving the data sources selection is …

Lightweight String Similarity Approaches For Duplicate Detection In Academic Titles, Fahrudin Mukti Wibowo, Muhammad Zidny Nafan, Muhamad Azrino Gustalika, Harinda Fernando, Muhammad Hussain, Nur Afiqah Sahadun

Journal of Informatics and Web Engineering

This study addresses the critical challenge of detecting duplicate final year project (FYP) titles in academic institutions, where minor variations like reordering, synonyms, and paraphrasing often obscure plagiarism. We systematically evaluate four string similarity algorithms - Jaro-Winkler, Levenshtein Edit Distance, TF-IDF with Cosine Similarity, and Jaccard Similarity - using a synthetic dataset of 250 title pairs representing common duplication patterns. Our experiments reveal that character-based methods (Jaro-Winkler and Edit Distance) achieve perfect detection (F1-score=1.0) for literal matches, including typographical variations and phrase reordering. At the same time, TF-IDF demonstrates strong semantic capability (F1-score=0.95), albeit with some false positives. Jaccard Similarity …

Improving Code Effectiveness Through Refactoring: A Case Study, Abdullah Almogahed, Manal Othman, Mazni Omar, Samera Obaid Barraood, Abdul Rehman Gilal

Journal of Informatics and Web Engineering

Software refactoring is a crucial practice in modern software development methodologies, such as Agile and DevOps, as it enables teams to iteratively improve and evolve their codebases while minimizing the risk of introducing bugs or regressions. It fosters a culture of continuous improvement and code hygiene, ultimately leading to more robust, maintainable, and scalable software systems. However, research examining the impact of refactoring on code effectiveness is scarce. This study, therefore, seeks to investigate the impact of refactoring methods on the code’s effectiveness. The study was carried out in four distinct phases: refactoring methods selection, case study selection, software metric …

Societies’ Funds Management System Using Blockchain, Jun Xiang Lau, Nur Ziadah Harun, Suziyanti Marjudi, Abd Samad Hasan Basari, Nur Amlya Abd Majid, Roziyani Setik

Journal of Informatics and Web Engineering

Lack of transparency of the funds and lack of immutability of the funds’ records are large problems today, especially in the societies’ funds. Leveraging the Ethereum Blockchain, the system ensures complete transparency and security in recording and accessing financial transactions for any society. Advanced encryption and blockchain consensus protocols guarantee data privacy and resilience against fraud or tampering. The information entered in the system helps the treasurer to effectively manage funds and accurately and transparently pass appropriate financial transactions. This project meets the challenges of transparency and immutability in society’s fund records, providing an assurance system and promoting growth for …

Implementation Of Conjugate Gradient Method For Estimating Inflation Rate In Malaysia, Shin Yi Wong, Nur Syarafina Mohamed, Norhaslinda Zullpakkal

Journal of Informatics and Web Engineering

Optimization methods are valuable for making decisions and identifying the most suitable alternative based on a given objective function. One of the mathematical optimization methods is Conjugate Gradient (CG) method which is commonly used to solve large-scale unconstrained optimization systems with less storage space. Recently, various optimization methods have been studied and used in economics estimating. However, just a few studies have predicted inflation rate using modified CG method. Random initial points are tested on New Three-Terms (NTT) which are modified Rivaie-Mustafa-Ismail-Leong (RMIL+) and Umar Mustapha Waziri (UMW) CG method with ten optimization test functions suggested by Andrei using MATLAB. …

Conjugate Gradient Methods In Fitting Precipitation Of Rainfall Data In Malaysia, Hua Ru Tang, Nur Syarafina Mohamed, Nurul Hajar Mohd Yusoff, Norhaslinda Zullpakkal

Journal of Informatics and Web Engineering

Conjugate gradient method (CGM) is one of the most efficient numerical methods for solving unconstrained optimization problems. It is also known as an iterative method with simple formulation. The classical CGM has always been an interest to the current researchers in improving the formulation which are categorized into three-term (TTCGM), spectral (SCGM), hybrid and scaled CGM. Although there are many variations of the CGM available, choosing the most efficient and effective one for a particular problem can be a time-consuming process. In this study, spectral Hestenes-Stiefel (sHS) CGM with the greatest NOI and central processing time per unit (CPU time) …

Enhancing Imbalanced Data Augmentation: A Comparative Study Of Ganified-Smote And Latent Factor Integration, Rusma Anieza Ruslan, Nureize Arbaiy, Pei-Chun Lin

Journal of Informatics and Web Engineering

One such serious problem in machine learning (ML) is imbalanced datasets. Minority class samples are usually sparse but hold significant meaning. The model can become biased toward the majority class due to unbalanced class distribution. This results in fraudulently high accuracy without being able to detect minority cases. This bias is also most perilous in critical applications, where ignoring minority cases can be highly destructive. To overcome this problem, the Synthetic Minority Oversampling Technique (SMOTE) is one of the most widely used. SMOTE creates balanced class distribution by interpolating between existing minority samples. It creates samples that are too close …

Cloud Seeding: Enhancing Winter Snowpack To Bolster Utah's Water Supply, Lily Lambert, Kendall Becker, Binod Pokharel, Scott Hotaling

All Current Publications

As Utah’s climate warms, the state is working to combat the decline in winter snowpack caused by rising temperatures. Cloud seeding is a safe technology that, under the right conditions, can boost snowfall. In this fact sheet, we describe what cloud seeding is, where it is currently used in Utah, and the safety measures and management practices that ensure its responsible use.

Re: Comments On The Draft Final Butte Mine Waste Repository Geotechnical Investigation Work Plan (Dated September 23, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Butte Priority Soil Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites Field Sampling Plan (Fsp): Bres No. 91 – Robert Emmett Dump, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Barriers To Machine Learning Adoption In Regulated Electric Utilities, Donald R. Shiflet Jr.

USF Tampa Graduate Theses and Dissertations

Machine learning (ML) technologies have the potential to revolutionize regulated electric utilities by improving operational efficiency, enabling predictive maintenance, and optimizing energy management. Despite these advantages, the adoption of ML in this sector lags other industries due to technical, organizational, and regulatory barriers. This research, grounded in the Technology-Organization-Environment (TOE) framework, explores these barriers to uncover actionable solutions for integration. The study identifies key challenges, including explainability, cybersecurity, workforce resistance, and regulatory ambiguity to ML adoption in electric utilities. Utilizing an exploratory qualitative methodology, this approach integrates insights from the literature and industry interviews to rank barriers by frequency, severity, …

Needs Analysis Of Interactive Learning Media For Teachingheat Transfer In Physics: Students’ And Teachers’Perspectives, Rizki Eka Shintya, Ika Mustika Sari, Ida Kaniawati

Jurnal Pendidikan Sains

Heat transfer material in physics is known to be abstract. This study specifically analyzes the conceptual difficulties, and visualization needs specific to this material, which is different from the analysis of physics needs in general. This analysis does not only look for the need for traditional media but explicitly looks for the need for interactive media (simulation, animation, virtual laboratory). Therefore, this study aims to identify the need for interactive learning media in physics education, specifically in the teaching of heat transfer, from the perspective of students and teachers in West Java, Indonesia. Using a quantitative descriptive survey, data were …

Efficacy Of Teaching At The Right Level Approach Combined With The Problem-Based Learning Model On Science Learning Outcomes At Middle School, Heri Syahputra Azhar Panjaitan, Ryan Dwi Puspita

Jurnal Pendidikan Sains

This research seeks to evaluate the efficacy of the Teaching at the Right Level (TaRL) strategy in conjunction with the Problem-Based Learning (PBL) model on the scientific learning outcomes of eighth-grade students at middle school Islam Terpadu Khairul Imam. This research addresses the inadequate scientific problem-solving abilities and science learning outcomes of Indonesian students, necessitating a more interactive and individualized instructional technique. The methodology used is a quasi-experimental design with a nonequivalent control group. The sample included two purposively chosen eighth-grade classes: one experimental class (n=25) underwent the TaRL–PBL intervention, whereas the control class (n=25) simply used the lecture approach. …

Simple Probabilistic Method For Chloride Transport In Concrete, Jaehwan Kim, Sangki Park, Dong-Woo Seo, Ki-Tae Park, Joohyung Kim

International Conference on Durability of Concrete Structures

It is a well-known fact that reinforced concrete structures exposed to marine environments suffer from reinforcement corrosion due to chloride ingress, which degrades the performance of the structure. To address this issue, reinforced concrete structures are designed and constructed to have a service life of more than 100 years, but to ensure safety or durability, it is necessary to accurately predict the onset of reinforcement corrosion. Various prediction models have been developed for chloride transport in concrete, including physically based models, with Fick's 2nd law being the most commonly used empirically based model for chloride penetration in concrete. However, the …

Machine-Learning Pci Forecasts For Concrete Pavements: Evidence From A Nigerian Airfield, Abubakar Ahmad Shehu, Mohamed Shadi Mohamed, Arab M. Zakwan, Jinhui Jiang

International Conference on Durability of Concrete Structures

This study develops data-driven Pavement Condition Index (PCI) forecasting for rigid (jointed concrete) airfields to support maintenance planning, risk mitigation, and lifecycle analysis. Traditional PCI surveys per ASTM D5340 are manual, time-consuming, and subjective, motivating machine-learning alternatives. Using panel-level observations, five models predict next-year PCI from readily available variables: prior-year PCI, annual aircraft traffic, temperature, and rainfall. The models include ordinary least squares (linear), ridge, lasso, random forest (RF), and a feedforward artificial neural network (ANN). All models performed well on held-out validation data; the ANN was best, achieving ��2 = 0.985, MSE = 0.286, MAE = 0.397, and RMSE …

Chloride Transport In Low Clinker Content Concretes And Modeling, Pu Yang, Narayanan Neithalath, Manu Santhanam, Yuvaraj Dhandapani

International Conference on Durability of Concrete Structures

Chloride ion transport behaviour has been reported to be significantly influenced by the use of supplementary cementing materials in concrete, both due to physical effects such as pore structure refinement and chemical effects including chloride binding. This paper provides experimental results on diffusion of chloride ions through concretes containing limestone calcined clay as a cement replacement material at ~50% replacement level, demonstrating the beneficial effects of high-volume replacement of cement with calcined clay. A numerical simulation framework that considers the pore structure of concrete, the concentration-dependence of diffusion coefficient, and Freundlich binding is also presented. The diffusion model is augmented …

Enhancing Concrete Circularity In Construction: The Recyclebim Framework In Closing Material Loops, Miguel Azenha, Artur Kuzminykh, José Granja, Manuel Parente, M. Albadri, P. González-Cabaleiro, R. Túñez-Alcalde, Lucía Díaz-Vilariño, C. Cao, N. Ukrainczyk, E. Koenders, A. J. Babafemi, M. Colyn, W. De Villiers, A. Ditlhokwa, H. Els, K. Timm, G. Van Zijl, E. Ameh, J. Immelman, V. Ndjate, L. Petrik, E. Ciampi, G. Nisivoccia, M. G. Orecchio, E. Sandonis, V. Garcia, D. Garcia, A. Delaplace

International Conference on Durability of Concrete Structures

Despite significant progress in digitalisation across various sectors, the development of data-driven applications in the built environment remains ongoing, with a focus on improving labour productivity and addressing global sustainability challenges. The circular economy framework for reusing and recycling construction materials is still underexplored. Metrics on the amount and impact of construction and demolition waste (CDW) highlight the need for more effective circularity strategies. Although the circular economy seeks to minimise waste, maximise material reuse, and reduce environmental impacts, practical implementation within the construction sector requires further development—an area where digital technologies can offer substantial support. This study introduces the …

3d Rbsm Conduit Model For Simulating Moisture Transport In Compressively Damaged Concrete, Dawei Ren, Kohei Nagai

International Conference on Durability of Concrete Structures

This study investigates the simulation of moisture transport in concrete under compressive damage using the 3D RBSM Conduit model. The model combines stress-strain responses from concrete compression experiments with detailed crack data, providing a realistic representation of crack development under varying load conditions. By implementing both unlubricated and lubricated compression tests, different failure modes were observed, influencing penetration patterns. Simulations show that the distribution of cracks significantly accelerates moisture penetration within the concrete. Notably, uniformly distributed cracks, typical of lubricated tests, facilitate deeper and faster moisture transport compared to more localized cracks observed in unlubricated tests. This study validates the …

Comparative Assessment Of Battery And Hydrogen Energy Storage In A Grid-Connected Heat-Electricity Integrated Microgrid, Naglaa Elsherbiny, Mohamed Elgamal, Islam Ismael, Akram Elmitwally

Mansoura Engineering Journal

Given the significant challenges of conventional power systems, including high emissions and operational costs, transitioning to microgrids (MGs) is increasingly critical. This paper presents a comprehensive evaluation of three energy management strategies for a grid-connected, heat-electricity integrated MG: (i) a base case without storage, (ii) a battery-based energy storage system (B-BESS), and (iii) a hydrogenbased energy storage system (H-BESS) comprising an electrolyzer (ELC), hydrogen tank (HT), and fuel cell (FC). This study optimizes operational profit and emissions reduction by integrating renewable energy and heat recovery mechanisms. Simulation results show that, compared to the base case, both B-BESS and H-BESS significantly …

Synergistic Effects Of Orifice Geometry And Inclination Angle On The Damping Performance Of Tuned Liquid Column Vibration Absorbers, Mohamed M. Abou Elenin, Younes K. Younes, Mohamed F. Younes

Mansoura Engineering Journal

This study experimentally investigates the dynamic damping performance of passive tuned liquid column vibration absorbers (TLCVAs), focusing on the influence of vertical column inclination angle and orifice disc configuration. Free vibration tests were conducted on a primary system equipped with a TLCVA using a custom-designed test rig. The experimental framework systematically varied inclination angles from to and tested both single-hole and multi-perforated orifice discs, each designed with an equivalent total flow area. A MATLAB-based signal processing framework was employed to analyze time-domain responses, and the logarithmic decrement method was applied to determine the damping ratio of the primary system. The …

Tableau Part Ii - October 2025, Rubab Shahzad

Day Family Research Lab Workshop Series

Part Two of Introduction to Tableau. Learn to make cool visualizations using Tableau. A hands-on opportunity where we will go over calculated fields, hierarchies, unions, dashboards, and stories.

Prior experience with Tableau is recommended

Skin Cancer Image Classification Using Deep Learning With Data Segmentation Technique, Akhilesh Kumar Shrivas, Hema Vastrakar

Karbala International Journal of Modern Science

The human skin is an impressive organ and structural element often impacted by a diverse range of recognized and unknown diseases. Diagnosing disorders that affect the outermost layer of the body is the most uncertain and difficult component in the scientific field. Dermatological diseases are one of the most significant health concerns in the 21st century since their identification is challenging and costly, plagued with challenges and the subjectivity that comes with human interpretation. The main objective of this piece of research work is to develop a robust model for the classification of skin cancer diseases using deep convolution neural …

Climate Change Projections Through Optimized Machine Learning And Deep Learning Models: A Comprehensive Analysis, Hala H. Youssef, Salma S. Mohammed, Hanan M. Amer, Abeer T. Khalil

Mansoura Engineering Journal

One major worldwide issue that has far-reaching effects on environmental stability and the avoidance of natural disasters is climate change. Developing efficient mitigating strategies depends on precise climate change forecasts. To predict important climate change indicators, including temperature fluctuations, greenhouse gas (CO2, N2O, CH4, and SF6) emissions, population dynamics, sea level changes, Arctic Sea ice extent, and Antarctica mass, this study evaluated the predictive capabilities of several Machine Learning (ML) and Deep Learning (DL) techniques. The set of machine learning algorithms includes Multiple Linear Regression (MLR), K-Nearest Neighbors (KNN), Support Vector Machines (SVMs), Artificial Neural Networks (ANN), Random Forest (RF), …

Second Moment Of Degree Three L-Functions, Sampurna Pal

Doctoral Theses

Let $F$ be a Hecke-Maa\ss\  cusp form for $SL(3,\mathbb{Z})$. In this dissertation, we obtain a non-trivial upper bound of the second moment of $L(F,s)$ in the $t$-aspect: $$ \int_{T}^{2T}|L(F,1/2+it)|^2 dt\ll_{F,\epsilon} T^{3/2-3/32+\epsilon}.$$ Immediate corollaries include improvements over the existing results on the Subconvexity bound for self-dual $GL(3)$ $L$-functions in the $t$-aspect and for self-dual $GL(3)\times GL(2)$ $L$-functions in the $GL(2)$ spectral aspect, the error term in the Rankin-Selberg problem, and the zero density estimate for $GL(3)$ $L$-functions.

An Integrated Pcb-Based Heating And Auto-Ranging Platform For Volatile Organic Compound (Voc) Detection Using Carbon Nanotube Based Sensors, Thomas Kalach

USF Tampa Graduate Theses and Dissertations

This thesis presents the development, characterization, and integration of a novel low-cost, high-dynamic-range sensor platform for the detection of volatile organic compounds (VOCs), leveraging the unique electrical properties of carbon nanotube (CNT) thin films. The platform introduces a fully integrated auto-ranging analog front-end circuit capable of real-time resistance measurement spanning over eight orders of magnitude ranging from tens of ohms to hundreds of megaohms, without compromising signal resolution or precision. This was achieved through a digitally controlled, multi-path feedback architecture and controllable current source.

To further enhance sensor performance, the system incorporates a copper trace heater beneath the sensor array, …

Development Of Natural Product Analogs As Therapeutic Agents, Jacob Mara

Theses and Dissertations

Cancer stem cells (CSC) are cancer cells in a tumor mass that may self-renew and develop into various cell types, resulting in a heterogeneous tumor. CSCs have been shown to have a role in many facets of cancer formation, including tumor genesis, proliferation, and metastatic activity. They are also implicated in chemotherapeutic treatment resistance and the recurrence of some malignancies. Based on these capacities, CSCs have been identified as the next target for cancer therapy and control. Salinomycin's potential for therapeutic use based on ongoing research, as well as the synthesis of its derivatives and their biological activity, will also …

10.13.2025 Ored Connect, Liz Williamson

ORED Newsletter

• ORED Small Grants Program RFP
• Mississippi Impact Grants RFP
• Contest to Promote Lab Practices
• Field Fest
• AAAS Membership for Faculty, Staff, and Students 

Trust-Based Adjustment Of Measurement Discrepancies In Distribution Networks, Zhiwei Huang, Yachen Tang, Chee-Wooi Ten, Guangyi Liu

Michigan Tech Publications

This paper addresses security challenges in modern electricity distribution systems, where supervisory control and data acquisition (SCADA) and advanced metering infrastructure (AMI) networks are increasingly exposed to cyber threats and fraudulent activities, leading to metering discrepancies. As smart grids become more interconnected, identifying compromised meters and devices at scale requires a robust inference framework. While alarm systems provide real-time detection of anomalies such as abrupt energy consumption changes, data losses, and security breaches, the lack of seamless integration between SCADA and AMI alarm data limits their effectiveness. To enhance grid security and resilience, this paper presents a data-driven approach for …