Digital Commons Network^™

A Calibrated And Conformal Deep Learning Framework For Trustworthy Antinuclear Antibody Pattern Recognition With Selective Referral To Experts, Hussein Ali Hussein Al Naffakh, Ahmed Dheyaa Radhi, Raghdah Maytham Hameed, Muntaha Abdullah Reishaan, Fouad A. Majeed, Rozaida Ghazali

Karbala International Journal of Modern Science

Reading antinuclear antibody patterns on human epithelial cells by indirect immunofluorescence is the reference screen for systemic autoimmune rheumatic diseases, but it is slow, subjective, and variable between observers. Deep learning reaches high accuracy on this task, yet most systems return a single prediction without stating how reliable it is, which is unsafe in a diagnostic workflow. This paper presents an intelligent decision support framework built around a single calibrated uncertainty signal. That signal is the control variable for four reliability modules: confidence calibration, conformal prediction, error detection, and selective referral. A feature space out of distribution detector serves as …

Re: Approval Letter For The Uncontrolled Surface Flow Areas Drainage C 95% Design Remedial Action Work Plan, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Resilient Ethical Governance By Design: Building Resilience For Future-Ready Smart Cities Against Emerging Technology Disruptions In Public Sector – A Case Study Of Dallas Smart City, Emmanuel Asamoah Asare

Doctoral Dissertations and Projects

This dissertation examines how Dallas’s smart city strategic policies foster resilience against disruptions associated with emerging technologies, particularly artificial intelligence and Internet of Things systems. Using a convergent mixed-methods comparative case study, Dallas serves as the primary case, Austin serves as a U.S. municipal comparator, and Barcelona serves as a qualitative benchmark for ethical and trust-centered smart city governance. The study integrates document analysis, broadband and digital equity indicators, stakeholder engagement evidence, and exploratory quantitative comparisons to assess how governance adaptability, preparedness, functionality, equity, and stakeholder trust shape resilience outcomes.

The findings provide partial support for the study’s hypotheses. Dallas …

Re: Conditional Approval Letter For Butte Priority Soils Operable Unit (Bpsou) Final Diggings East Dewatering Treatability Study Pre-Design Investigation Work Plan (Pdiwp) (Dated September 8, 2026) And The 2026 Final Diggings East Dewatering Treatability Study Quality Assurance Project Plan (Qapp) (Dated September 8, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Comparison Of Gravity Separation And Flotation For Pyrite Recovery From Tailings, Gülay Bulut, Gönül Göksu Gökçe, Dilruba Karamanlı, Oğuzhan Mert Gürkan, Ergin Sarp Zenzirci, Binnur Kırım, Alim Gül

Journal of Sustainable Mining

Tailings generated during the production of lead, zinc, and copper concentrates contain significant amounts of sulfide minerals, particularly pyrite. Pyrite, which remains in tailings after the recovery of other metals, is one of the main contributors to acid mine drainage (AMD). Therefore, recovering pyrite from tailings is environmentally and economically an important issue. In this study, pyrite recovery from tailings was investigated using flotation and gravity separation methods. Mineralogical characterization and liberation analyses were conducted by Mineral Liberation Analysis (MLA), indicating that pyrite is the major sulfide mineral with over 76% liberation degree even in the coarsest fractions. Flotation tests …

Challenges, Trends, And The Role Of Lstm In Ai-Based Predictive Maintenance Of Electrolyzers For Solar Hydrogen Systems: A Review, Yani Koerniawan Kuatno, Muhamad Zahim Sujod

Turkish Journal of Electrical Engineering and Computer Sciences

The transition toward low-carbon energy systems has increased interest in hydrogen as a clean energy carrier, with solar-driven water electrolysis emerging as a promising technology due to its high efficiency and compatibility with renewable energy sources. However, dynamic operating conditions and intermittent renewable input accelerate electrolyzer degradation, reducing reliability and system lifespan. Predictive maintenance (PdM), supported by artificial intelligence (AI), offers a data-driven approach to anticipate failures and improve operational durability. This review systematically investigates AI-based PdM approaches for electrolyzers, with an emphasis on long short-term memory (LSTM) networks and Internet of things (IoT) integration. Following PRISMA 2020 guidelines, 35 …

Measurement-Aware Zero-Phase Iterative Learning Control For Robust Regulation Of Nonideal Boost Converters In Electric Vehicle Fast Charging, Aytaç Altan, Mohammed S. Alzaidi, Cağfer Yanarateş

Turkish Journal of Electrical Engineering and Computer Sciences

Integrating battery energy storage with DC-DC boost converters for electric vehicle fast charging exposes the regulator to ageing-induced parameter drift, periodic load pulses, and, critically, the nonidealities in the output-voltage sensing chain. This paper proposes a measurement-aware, zero-phase iterative learning control scheme for robust output-voltage regulation of a nonideal boost converter whose parameters are matched to those of a commercial Texas Instruments TPS6102x battery regulator. The controller combines an inner proportional-integral stabilizing loop with an outer zero-phase learning law that updates a feedforward correction based on the sensor-captured output trajectory; a forward-backward robustness filter suppresses the amplification of measurement noise …

Portrait: Holistic Data Visualization Using Neural Networks, Chayan Maitra

Doctoral Theses

With the exponential growth of complex data across domains, effective visualization has become increasingly crucial for understanding relationships hidden within high-dimensional spaces. However, existing visualization techniques often struggle to effectively capture and represent such high-dimensional data. Motivated by this challenge, we have developed NeuroDAVIS, a neural network model designed to visualize high-dimensional data by extracting meaningful latent representations through deep feature extraction. While NeuroDAVIS has successfully addressed the visualization aspect, we have soon recognized the necessity of identifying the most relevant features that contribute to the visualization and downstream analysis. To address this issue, we have extended our framework and …

Uae Audiences' Reliance On Social Media As A Source Of Information On Complementary And Alternative Medicine: A Study Of Al Ain City Residents Based On Media System Dependency Theory, Abdul Rahman Al-Toum, Mohammed Al-Kaabi, Najoud Al-Mansouri, Ahmed Bin Ishaq, Amer Khaled Ahmad, Maram Manajrah

Middle East Journal of Communication Studies

This study examined the extent to which UAE audiences rely on social media as a source of information on complementary and alternative medicine (CAM) and the resulting effects of this reliance. Grounded in Media System Dependency Theory, the study employed an audience survey using a questionnaire administered to a sample of (132) Emirati citizens in Al Ain. The findings revealed that the combined medium and high reliance reached (53%). Regarding the effects, cognitive effects recorded the highest arithmetic means, followed by affective and behavioral effects at comparable levels. Hypothesis testing showed no statistically significant differences in the degree of reliance …

Analysis Of The Influence Of Anthropometric Dimensions Of Postural Ergonomics Using Multiple Linear Regression, Gashbeen Faisal Najmaddin, Edrees Muhammed Tahir Harki

Al-Bahir

Ergonomics is the study of designing and arranging a workspace or product to optimize the “fit” between people and their work, ensuring safety, comfort, and efficiency. The scientific literature indicates that ergonomic perspectives on the workplace are connected to the anthropometrics of societies. This study primarily aims to create a model that integrates multiple predictive variables to estimate the target variable. Multiple linear regression analysis is used to identify how different anthropometric dimensions predict postural ergonomics during prolonged sitting. Based on the regression models’ results, the predicted can be calculated using user anthropometry and existing chair dimensions. Furthermore, the primary …

Can Artificial Seagrass Meadows Reduce Pathogenic Bacteria In Coral Reef Ecosystems- A Mesocosm Study, Hewa Pathirannahelage Athri Thathsarani Weerakoon, Jimmy Kuo, Pi-Jen Liu, Kwee Siong Tew

Journal of Marine Science and Technology–Taiwan

Seagrass meadows provide essential coastal ecosystem functions by stabilizing sediments, enhancing water quality, and shaping nutrient and microbial dynamics. With global seagrass losses accelerating due to climate change and anthropogenic pressures, artificial seagrass (ASG) has been proposed as a nature-based alternative to mimic these functions. However, its ability to replicate biological interactions, particularly microbial regulation and pathogen suppression, remains unclear. In this study, we conducted a six-week mesocosm experiment comparing natural Thalassia hemprichii and ASG within coral reef-associated habitats in southern Taiwan. Physicochemical parameters, sedimentation rates, nutrient concentrations, and planktonic and benthic bacterial communities were analyzed. Sedimentation rates and nutrient …

Identifying The Causality And Criticality Of Factors Influencing The Promotion Of Asian Island-Hopping Cruise Tourism In Taiwan, Hsiao-Chuan Liu, Gin-Shuh Liang, Feng-Ming Tsai, Yu-Ling Lien

Journal of Marine Science and Technology–Taiwan

Following the COVID-19 pandemic, the global tourism industry has steadily recovered since 2022. Island-hopping cruises have gained increasing attention for enhancing regional connectivity and diversifying marine travel experiences; however, their development in Asia remains limited compared with that in Europe and the Caribbean due to fragmented policy coordination, inadequate port infrastructure, and uneven technological readiness. Although Taiwan possesses a geographic advantage and can serve as a strategic hub linking Asian island destinations, systematic planning and stakeholder coordination remain insufficient, resulting in unclear mechanisms that drive or constrain island-hopping cruise tourism. Existing studies mainly focus on market demand or passenger behavior, …

A Resilience Early Warning Assessment Of The Maritime Supply Chain: A Case Study Of China’S New Energy Vehicle Exports, Xiuqian Chen, Liangyong Chu, Mengyao Wang, Jiayin Du, Yiming Zhang, Xiyao Xu

Journal of Marine Science and Technology–Taiwan

Enhancing resilience through early warning is a critical strategy for mitigating disruption risks in the maritime supply chain (MSC). This study proposes a novel early warning assessment framework to determine the resilience of the MSC. It is referred to as a resilience early warning system. An evaluation index system for shipping enterprises is developed based on four dimensions: withstand capacity, adaptive capacity, learning capability, and the external environment. A resilience assessment model that uses the Bayesian best-worst method (BBWM) and the extension cloud model (ECM) is established to quantify MSC resilience. An early warning evaluation model based on a Bayesian …

Public-Port Throughput As An Activity Proxy For Near-Port Air Quality And Health: A Transferable Two-Scale Framework (Kaohsiung, 2017–2024), Ping-Jen Wang, Ying-Lin Hsu, Shih-Hao Chang, Bao-Tzung Wu

Journal of Marine Science and Technology–Taiwan

We developed a two-scale time series framework using monthly container throughput (20-foot equivalent units, TEU) as a port activity indicator. Applied to Kaohsiung, Taiwan (2017–2024), we related TEU to near-port NO₂ and PM₂.₅ (monthly) and air quality to outpatient respiratory diagnoses (weekly) across the 2019–2020 sulfur rules and the COVID-19 pandemic. Transfer-function models indicate TEU tends to lead near-port NO₂ by 6–9 months. Structural break tests at policy dates indicate nonsignificant changes in levels and slopes, suggesting gradual rather than abrupt shifts in the activity–pollution linkage. Weekly two-pollutant distributed-lag Poisson models estimated relative risks (lags 0–8) per interquartile range (IQR) …

Decision Support Tool For The Maintenance Of Meter Gauge Railway Permanent-Way Infrastructures: A Concept Paper, Hamisi J. Maulid, Beatus A.T Kundi, Juma M. Matindana, Ismail W. R. Taifa Dr

Tanzania Journal of Engineering and Technology (TJET)

A Decision Support Tool (DST) represents a transformative way of modernising maintenance practice on the permanent-way infrastructure of Meter Gauge Railway (MGR). Maintenance practice remains largely reactive, as the MGR plays a strategic role in transporting both freight and passengers, resulting in inefficient resource allocation, high operational risk, and growing Lifecycle expenses. This concept paper explores the potential and the design challenges for a DST that combines fuzzy analytic hierarchy process (Fuzzy-AHP) modelling, multi-criteria decision analysis (MCDA), Geographic Information Systems (GIS) and predictive machine learning (ML) analytics for evidence-based, future-oriented maintenance management. The paper draws on peer-reviewed studies from …

Hydro-Chemical And Bacteriological Assessment Of Zanzibar Groundwater Resources, Subira Munishi, Andrew Kimati

Tanzania Journal of Engineering and Technology (TJET)

Groundwater is the primary freshwater source in Zanzibar, sustaining domest ic, agricultural, and tourism needs. Increasing demand has intensified the pressure on this limited resource and has led to over-abstraction and contamination. Amid the growing demand and contamination pressures, this study examines the quality of groundwater in Zanzibar to clarify current conditions and emerging risks, and inform resource management and public health priority interventions. Particularly, the present hydro-chemical and bacteriological quality and variability was examined for both Unguja and Pemba Islands. A total of seventy-two samples were collected using a stratified random sampling approach, with the first field campaign focusing …

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Unreclaimed Sites: Ur-42 Site Evaluation Summary Report (Sesr) (Dated July 22, 2026), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) 2026 Final Backfill And Cover Soil Quality Assurance Project Plan (Qapp) Dated August 26, 2026, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit, Draft Final Unreclaimed Sites: Ur-31 Site Evaluation Summary Report, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Draft Final 2023 Unreclaimed Sites Sampling: Ur-43 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Developing A Deep Learning-Based Artificial Intelligence System For Detecting Scientific Misinformation On Digital Platforms, Shorouq Al-Awawdeh, Ayah Al- Jafari

Middle East Journal of Communication Studies

Objectives: This study develops and evaluates an Arabic scientific misinformation detection system by fine-tuning AraBERT-base-v2. It examines the effects of early stopping and input sequence length on model performance, interprets selected linguistic characteristics associated with misleading content, and discusses the limitations of using machine-translated data.

Methodology: The study adopted a mixed-methods design, employing a systematic integration of quantitative and qualitative approaches, supported by an interpretive qualitative reading. The initial database consisted of 23,546 records, including 123 Arabic articles collected from the Akeed, Sheek, and Taqeen platforms, and 23,423 foreign-language records drawn from the GossipCop and PolitiFact collections within FakeNewsNet. After …

Broadening The Community Of Nudibranch Enthusiasts Through Multilingual Educational Programming To Increase Climate Advocacy Engagement, Richelle Li Tanner, Cintya Felix Mendivil, Ashley Lam, Lorena Muñoz, Micah Kim, Elena G. Morales Poot, Gabrielle Keeler-May

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Environmental literacy and advocacy for environmental protections are essential components of responsible stewardship. For coastal communities, stewardship requires knowledge of ocean processes and the biological communities living within these ecosystems. While many studies highlight difficulties in engaging American audiences in environmental concern and stewardship due to hyper-individualistic societal values, tidepooling is one recreational pathway to coastal community engagement that strengthens sense of place, and therefore, responsibility to protect natural resources. We sought to broaden the tidepooling community to include more diverse voices through a participatory science program with inland city-dwelling, multilingual, and non-English speaking adults. Using nudibranchs as an environmental …

Butte Priority Soils Operable Unit Final Butte Priority Soils Operable Unit Unreclaimed Sites Field Sampling And Investigation Plan: Ur-41 – Montana Street And Interstate 90, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Monthly Progress Report Butte Priority Soils Operable Unit Consent Decree Partial Remedial Design/Remedial Action And Operation And Maintenance, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Butte Priority Soils Operable Unit Unreclaimed Sites Field Sampling And Investigation Plan: Ur-51 –Area Near Bres No. 50 – Zelia And Mountain Con Mine, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Butte Priority Soils Operable Unit Unreclaimed Sites Field Sampling And Investigation Plan: Ur-52 Area West Of Bres No. 133 – Dexter Mill, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Butte Priority Soils Operable Unit Unreclaimed Sites Field Sampling And Investigation Plan: Ur-52 Area West Of Bres No. 133 – Dexter Mill, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Libs-Based Detection And Preliminary Classification Of Microplastic Signatures In Soil Samples., Ekhlas Jabir Mahmood

Al-Bahir

Contamination of terrestrial systems by microplastics (MPs) has become a critical environmental hazard, but detection of such contaminants in a complex soil system is a challenge for conventional analytical techniques. This research aims to assess the potential of Laser-Induced Breakdown Spectroscopy (LIBS) for the detection and differentiation of different types of microplastics, including HDPE, LDPE, PP, PS, and PVC, dispersed in the soil of Al Najaf, Iraq. Soil samples were collected from different functional zones, namely, Industrial, Commercial, Agricultural, Residential, and Roadside, at the surface level and 30 cm depth. Detection was done by measuring the intensity of the C/H …

A Transformer-Based Approach With Data Augmentation For Multilabel Emotional Context Detection, Mohsin Hasan Hussein, Marem H. Abdulabas, Azha Talal Mohammed Ali, Homam Aziz Ghazi

Al-Bahir

Emotion identification in texts is becoming increasingly difficult because of the wide variety of ways emotions are represented. This study uses a fine-tuned Robustly Optimized Bidirectional Encoder Representations from Transformers Approach

(RoBERTa) to offer a Transformer-based model for identifying multilabel emotional context in textual data. To balance emotion categories and enhance the model's capacity for generalization, data augmentation is applied on two different datasets: Semantic Evaluation and Cross-lingual Emotion Dataset (SemEval and XED) English corpus. This stage is considered one of the most important steps in preprocessing as it greatly helps to improve the results. The RoBERTa model was then …

From Dissertation To Deployment: A Unified Software Platform Operationalizing Clinical-Prediction And Sequential-Security Ai For Healthcare, Olsi Shehu, Damiana Teliti, Jasmin Kevrić, Bekir Karlik

Communications of the IIMA

Advances in machine learning for healthcare are abundant, yet most validated models remain confined to research notebooks and never reach secure, usable clinical software. This paper addresses that deployment gap by presenting a unified, security-hardened software platform that operationalizes two complementary streams of doctoral research inside a single, role-based hospital information system. The first stream contributes a clinical-prediction capability: an ultra-hybrid ensemble that couples a quantum-inspired feature transformation, particle-swarm feature selection, and calibrated soft voting for cancer-outcome prediction (96.41% accuracy, AUC-ROC 0.983 on TCGA-BRCA), survival stratification, multi-cancer generalization, and pharmacogenomic drug-response classification (89.31% mean accuracy across 25 compounds). The second …