Digital Commons Network^™

The Application Of Machine Learning And Deep Learning On Demand Forecasting Across Time-Critical Industries: A Systematic Review, Asmaa Seyam, Sujith Samuel Mathew, May El Barachi, Cheng Zhang, Jun Shen

All Works

The applications of machine learning and deep learning in demand forecasting have attracted increasing attention, as they offer remarkable predictive capabilities that help automate forecasting processes and achieve higher accuracy. While numerous review studies have examined solutions within specific industries, there is a lack of comprehensive literature review investigating these solutions across different sectors. Therefore, this study overviews machine learning and deep learning applications in demand forecasting across time-critical industries, including power, tourism, water, transportation, and food. A two-tier classification framework is proposed to categorize demand forecasting studies by both application industry and methodological architecture. In addition, the most popular …

Dustmambanet: A Hybrid Inceptionv3–State-Space Network For Robust Solar Panel Dust Detection, Kadhim Hayawi, Sakib Shahriar

All Works

To develop a robust, scalable vision-based model for automatic detection and quantification of dust accumulation on solar photovoltaic panels, overcoming limitations of existing convolutional and attention-based methods and supporting proactive maintenance. We propose DustMambaNet, a hybrid model that consists of a pretrained InceptionV3 convolutional neural network as a feature extractor and two selective state space sequence modules. The state space modules use gated depthwise convolutions to represent long-range spatial dependencies that are of linear complexity, after rearranging spatial features to form sequences. The network provides a binary classification of dust with a severity index (DSI) and a continuous one. All …

Modeling And Generating Trustworthy Speech, Yuwen Yu

Dissertations, Theses, and Capstone Projects

As virtual agents become increasingly integrated into everyday communication, trust has become essential for effective human-AI interaction. Although recent advances in natural language generation and speech synthesis have significantly improved fluency and intelligibility, most systems are not designed to control how trustworthy they are perceived. As a result, a mismatch can emerge between perceived trustworthiness and actual system capability, leading to over-trust or under-trust. While trust is critical for meaningful interaction, current text-to-speech (TTS) systems are primarily optimized for naturalness and intelligibility rather than calibrated trustworthiness.

This dissertation investigates the perceptual foundations of trust in both human and synthesized speech …

Urban Counterpoint (1992–2003): The Piano Music Of Ed Bland, Joseph Vaz

Dissertations, Theses, and Capstone Projects

This dissertation analyzes the piano music of Ed Bland, a politically and philosophically vocal composer active in the second half of the twentieth century, whose music draws on both the European and American twentieth-century avant-garde, and on African American vernacular music genres from ragtime to hip-hop. A review of the historical and personal context for these pieces, and a detailed examination of the compositional processes used in this music, work together to demonstrate how Bland thought about the relationship between different musical genres and languages.

Through this combination of theory of musical genre, historical and biographical study, and detailed analysis …

Investigating The Role Of Striatal Cholinergic Interneuron D2 Receptors In Behavioral Flexibility, Janyn J. Alfred

Dissertations, Theses, and Capstone Projects

Dopamine (DA) and acetylcholine (ACh) interact within the striatum to shape reward-based learning and choice behavior. DA D2 receptors on cholinergic interneurons (CIN D2Rs) were genetically knocked out to investigate their role in choice allocation using a two-lever matching paradigm. Behaviorally, both knockout (KO) and wild-type (WT) mice learned the initial task equally well. When shifted to asymmetric matching schedules (VI-90 vs. VI-180), ideal matching predicts that mice should allocate exactly 67% of their total responses to the rich lever. Neither group matched as predicted by the matching law. Instead, the KO mice showed a pattern where the higher rate …

Mesoscopic Scaling Of Microwave Transmittance And Disorder-Induced Alignment, Israel Kurtz

Dissertations, Theses, and Capstone Projects

This thesis presents microwave measurements and numerical simulations of wave propagation and transmission through random mesoscopic waveguides. We analyze the scaling of mesoscopic microwave conductance, including departures from Ohm’s law near channel openings, which are frequencies at which new propagating modes enter the system, and the evolution of modal phase alignment within the medium, which leads to the observed diversity of transmission eigenvalues. We extend the transmission matrix formalism to all sample depths using the flux matrix, which relates the flux amplitude within the sample to the incident flux, and decompose the flux at each sample depth into forward- and …

Ultrafast Spectroscopy Of Organic Materials In Strong Light–Matter Interaction And Terahertz Optics, Kamyar Rashidi

Dissertations, Theses, and Capstone Projects

Ultrafast spectroscopy is a powerful tool for investigating phenomena that occur on extremely short timescales and for probing ultrabroadband spectral responses enabled by its ultrashort laser pulses. These capabilities are essential for advancing both the fundamental understanding of light–matter interactions and the development of next-generation optoelectronic technologies. The first part of this thesis investigates the ultrafast dynamics of organic exciton–polaritons and their application to controlling molecular excited-state processes using momentum-resolved pump–probe spectroscopy. A major challenge in these systems is the dark-state problem, where photoexcitation predominantly populates long-lived excitonic reservoir states that obscure the in trinsic dynamics of the hybrid light–matter …

Real-World Testing Of An Artificial Intelligence Conversational Agent As An Early Intervention And Support Tool In The Mental Health Referral Care Pathway: A Mixed-Methods Study, Rohit Shankar, Edward Meinert, Madison Milne-Ives, Emma Taylor, B Inkster, Alina Paik, Ananya Ananthakrishnan, Martin Orr, Ceire Costelloe

Peninsula Medical School

Background: The incidence of mental health concerns is growing, and demand for support is exceeding service capacity.Digital tools can provide additional support but risk causing harm if not delivered safely.Aims: We aimed to establish real-world evidence of the impact of an artificial intelligence-based mental healthconversational agent (Wysa) on depression and anxiety in patients waiting for Talking Therapies treatment.Methods: A mixed-methods randomized controlled trial was conducted with patients referred to Talking Therapies inthe Central and Northwest London NHS Foundation Trust. The primary outcome was change in depression severityover 12weeks between groups; secondary outcomes included anxiety severity, quality of life, safety, engagement, …

Internal Verdicts Track Evidence: A Template-Controlled Neutrosophic Reading Of Epistemic States In Large Language Models Via The Jacobian Lens, Maikel Leyva, Alexis Matheu Perez, Florentin Smarandache

Neutrosophic Sets and Systems

For twenty-five years, neutrosophic logic has assigned independent degrees of truth (T), indeterminacy (I), and falsity (F) to model epistemic states that classical and fuzzy semantics cannot express. All previous applications, however, measured these components on outputs: answers, judgments, expert evaluations. This paper reports, to our knowledge, the first neutrosophic reading of components inside the internal representations of a large language model. Using the recently released Jacobian lens on Qwen3.5-4B, we project intermediate-layer readouts onto lexicons of support, refutation, and hedging, obtaining layer-wise (T, I, F) profiles under three epistemic conditions (conflicting evidence, first-person false belief, factual control; n = …

Hera 2.0: Human-Governed Agentic Software Development With External Cognitive Orchestration -- An Industrial Experience Report On Ai-Dlc With Chatgpt Web As Cognitive Continuity Layer, Manuel-Enrique Puebla-Martinez

Neutrosophic Sets and Systems

The adoption of LLM-based agents in industrial software engineering has surfaced a structural problem: local agents can conduct AI-DLC workflows correctly while simultaneously pursuing incomplete or misguided problem interpretations when context is fragmented or prompts are imprecise. This experience report presents HERA 2.0, a methodology that addresses this problem through architectural separation of responsibilities: local agents perform situated execution, while ChatGPT Web acts as an external cognitive continuity layer. Evidence classification in HERA uses four operational states that naturally corresponds to the (T, I, F) structure of neutrosophic evidence degrees. An anonymized industrial case on POS-switch integration illustrates differences between …

Generative Ai For Curriculum And Assessment Design In Competency-Based Tvet: An Exploratory Evidence Map With Neutrosophic Annotations, Maria Del Refugio Patino Cayetano, Blanca Estela Calderon Munoz

Neutrosophic Sets and Systems

Technological and polytechnic universities in Mexico revise their competency-based study plans on a multi-year cycle, and generative AI (GAI) tools are increasingly used informally by faculty to draft curriculum documents and evaluation instruments, without a published evidence base for the practice. This paper reports an exploratory, non-registered scoping search of the OpenAlex database for evidence on GAI use in curriculum and assessment design, read against four explicit propositions. What remains undocumented is narrower: authoring of curriculum or evaluation documents by GAI inside a multi-year, institutional, competency-based TVET/polytechnic revision cycle, specifically within the Textile Design and Fashion Engineering discipline.

The Absorption Problem In Software-Planning Assessment: A Single-Valued Neutrosophic Model With Deferral, Angela Olivia Yanza Montalvan, Omar Mar Cornelio

Neutrosophic Sets and Systems

Planning the software production process is a knowledge-intensive activity whose assessment relies on expert, linguistic and frequently conflicting indicators. Deterministic and fuzzy models compress each assessment into a single membership value and therefore cannot distinguish ignorance from contradiction. We formalise this Absorption Problem and propose a Single-Valued Neutrosophic (SVN) model that represents each indicator as a truth-indeterminacy-falsity triple, aggregates them with an SVN weighted average under AHP-derived weights, computes a structural-indeterminacy operator from inter-indicator disagreement, and applies a deferral rule that routes high-indeterminacy projects to expert review. On a real project-management dataset (n = 199), gating on structural indeterminacy raises …

How Much Of A Multicriteria Ranking Is The Data And How Much Is The Arithmetic? A Neutrosophic Stress Test On Stakeholder Perception Data, Leili Genoveva Lopezdominguez Rivas, Sol David Lopezdominguez Rivas, Dixie Marisol Lopezdominguez Rivas, Franklin Parrales-Bravo

Neutrosophic Sets and Systems

Multicriteria rankings computed on aggregated survey means are routinely used to allocate improvement budgets in higher education, and they are read as if the closeness coefficients were ratios of need. This paper shows, on real data, that a large part of what such a ranking reports is arithmetic rather than evidence. Using doctoral survey data on university-society engagement from two state universities in Guayaquil, Ecuador, we compare a crisp entropy-TOPSIS treatment with a single-valued neutrosophic treatment in which the indeterminacy component is measured from inter-stakeholder dissent. We report that the fine order of the ranking is not identifiable from these …

Typed Abstention For Llm-Elicited Fuzzy Criteria In Multicriteria Transportation Decisions, Maikel Maikel Leyva-Vazquez, Nezir Aydin

Neutrosophic Sets and Systems

Fuzzy multicriteria decision-making (MCDM) increasingly draws its criterion evaluations from large language models (LLMs), but the aggregation step typically treats these elicited judgments as interchangeable with expert opinion, with no mechanism to flag disagreement, insufficiency, or unreliable sources. We port a source-preserving, typed-abstention decision policy into fuzzy-MCDM pipelines, instantiated on a four-alternative sustainable-transportation case, and report two live pilots. Pilot 1 returns all-coherent; Pilot 2, redesigned with criteria of greater normative dependence, shows the gate firing on real disagreement. We report both pilots candidly and verify the gate's logic with synthetic unit tests.

Neutrosophic Sets And Systems, Vol. 101, 2026, Proceedings Of The International Conference On Artificial Intelligence, Indeterminacy, And Education, University O'Higgns, Santiago, Chile, Florentin Smarandache

Neutrosophic Sets and Systems

No abstract provided.

An Investigative Approach Leveraging Digital Twin Technology For A Cnc Machine, Anand Valiavalappil

Yanbu Journal of Engineering and Science

Digital twin technology has emerged as an effective approach for improving the monitoring, validation, and optimization of Computer Numerical Control (CNC) machining operations. This study presents an investigative framework integrating Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM), Software-in-the-Loop (SIL), and Hardware-in-the-Loop (HIL) methodologies for diagnosing and rectifying machining defects in CNC systems using the digital twin - virtual model (component and asset twins). Four machining experiments were conducted using Aluminum 6061-T6, Polytetrafluoroethylene (PTFE), Brass, and Stainless Steel (AISI 304) on an EMCO CNC machine integrated with Siemens 840D controls. The first two experiments, involving turning and drilling operations, are presented in detail; the …

Coming Soon To A Cellar Near You: Novel Range Expansion Of A Short-Bodied Cellar Spider, Physocyclus Enaulus (Araneae: Pholcidae), In A Building In Central Illinois, Usa, Ricky Gieser, Mark Davis

The Great Lakes Entomologist

A reproductive population of Physocyclus enaulus Crosby, 1926 (Pholcidae: Araneae), a short-bodied cellar spider native to the American southwest and Mexico, is documented for the first time in a single building in Illinois, far outside of their known native range. The means of introduction is unknown but is likely influenced by either accidental hitchhiking spiders or a deliberate introduction to control brown recluse populations. Cellar spiders were purchased and released in the same building to predate on brown recluse spiders, but the first P. enaulus individual was found a year prior to the release. These cellar spiders have a wide-ranging …

Religion And Economics: The Economic Views Of Catholicos-Patriarch Ilia Ii Of Georgia, Giuli Giguashvili

Occasional Papers on Religion in Eastern Europe

The paper examines the impact of religion on a country’s economic development, analyzing how religious values and institutions influence economic behavior. The research employs a qualitative, comparative, and historical approach based on the systematic analysis of primary and secondary sources. Religion can promote economic growth by strengthening work ethics, education, and social order. Still, it may also hinder development through inefficient resource allocation and regulatory influence. In the context of the 1700th anniversary of Christianity in Georgia, the study highlights the relationship between Orthodox teaching and economic thought. Drawing on the epistles and sermons of the Catholicos-Patriarch of All Georgia, …

Imperial Pedagogy And Religious Constraint: The Politics Of Islamic Education In The Kazakh Steppe Under Tsarist Rule, Kunduzay Yerimbetova, Bekmurat Naimanbayev

Occasional Papers on Religion in Eastern Europe

This article examines the evolution of the Russian Empire’s educational policies toward Islamic schools in the Kazakh Steppe from the mid-nineteenth century to the 1917 Revolution. While the early imperial administration initially tolerated Islamic institutions for pragmatic governance, the latter half of the nineteenth century witnessed a decisive paradigm shift toward systematic surveillance and restriction. Drawing on archival records and colonial administrative decrees, the study analyzes the implementation of the "Ilminsky system" and the compulsory introduction of the Cyrillic alphabet as tools for cultural assimilation and Russification. The research highlights the dual nature of colonial education: while the Tsarist authorities …

Letters To My Unrequited Love, Ogadimma Ebele

Undercurrents: A Journal of Undergraduate Student Composition

Ogadimma is a political science major living in Hyde Park, Massachusetts. Writing is her passion and she credits this assignment with helping to further her composition skills. In 2019, she plans to focus all of her energy on pursuing her dream of landing a career in comedy writing.

Volume 9 (2026) Climate And Responsibility

International Journal on Responsibility

This issue focuses on the various ways responsibility affects environmental justice. Specifically, this volume urges us to think about how societal and individual (in)action influences ecological crises and what informs this behavior, with a specific focus on religious and Indigenous beliefs and values.

Enhancing Ecg Classification Using Systematic Cubic Spline Control Points With Deep Neural Networks, Hussein Qahtan Khalaf, Abeer Tariq Maolood, Nor Shahida Mohd Shah

Engineering and Technology Journal

The healthcare industry has undergone substantial growth over the past few years. Despite the development of medical technology, the diagnosis of cardiac arrhythmia is still a significant challenge for modern diagnostic methods for correct and efficient classification of electrocardiogram (ECG) signals, especially in cases of class imbalance and the complexity of the arrhythmia. This study proposes a novel deep learning model where the class imbalance problem is addressed using the Synthetic Minority Oversampling Technique (SMOTE) and the effect of signal resolution on the classification is investigated using Cubic Spline (CS) interpolation and Lightweight Deep Neural Network (CSLWDNN). Both the MIT-BIH …

Solar-Driven Photocatalytic Ceramic Membrane Reactors For Paracetamol Degradation: Process Optimization, Transport Dynamics, And Preliminary Cyclic Reusability, Adel Zrelli, Asma Abdennebi, Manoj Chandra Garg, Fanghua Li

Engineering and Technology Journal

The use of membrane separation and heterogeneous photocatalysis together appears to be an innovative way to remove long-lasting pollutants such as paracetamol (PCT) from water. To overcome the limited process by understanding hindering the practical deployment of solar-driven photocatalytic membrane reactors (PMRs), this study proposes a process-engineering-centered framework for a low-cost, integrated ceramic PMR. A laboratory-scale system was developed using inexpensive red clay ceramic membranes modified by immobilizing TiO₂ (P25) for paracetamol degradation under natural sunlight and ultraviolet irradiation. Unlike previous studies mainly focused on material development, this work evaluates the coupled effects of TiO₂ loading, membrane inclination, …

Neural Network Modelling Of Magnetic Effects In Solid-State Transformer Performance Under Variable Magnetic Operating Conditions, Godfrey Murairidzi Gotora, Blessed Ziyambe, Emanuel Rashayi

Engineering and Technology Journal

Solid State transformers (SSTs) are pivotal for renewable energy integration and smart grids, yet their performance is critically limited by non-linear magnetic effects such as core losses, flux- density saturation, and magnetising-inductance drift, that conventional analytical methods and prior artificial neural network (ANN) studies have struggled to model simultaneously across the electrical, thermal and magnetic domains. This study develops and evaluates a unified multi-output ANN framework that predicts six SST performance indicators which are efficiency, power density, total harmonic distortion, temperature rise, core loss and magnetising inductance from six operating variables (switching frequency, duty cycle, load current, ambient temperature, input …

Experimental Investigation Of Mechanical Performance Of Glass/Epoxy Hybrid Composites Reinforced With Natural Fibers, Bestwn Omer, Gailan Ismail Hasan

Engineering and Technology Journal

The use of epoxy-based composites has increased significantly due to their wide range of applications across various industries. However, these composites often require enhanced mechanical properties tailored to specific applications through the incorporation of different types of reinforcements. In this study, the effect of natural fibers on the mechanical properties (flexural strength, tensile strength, and impact energy) of composites based on two types of epoxy resins (LR202 and Sikadur®-52 LP) was investigated using the hand lay-up method. Different reinforcement fibers (fiberglass, cotton, and jute) were incorporated at various percentages. The results indicate that, among composites reinforced with a single type …

Aquila-X 3.0: Modular High-Throughput Mobile Potable-Water Factory With Adaptive Pretreatment, Parallel Production Trains, Seawater Energy Recovery, Multi-Grade Outputs, And Concentrate-First Residual Management Research Conceptual Invention, Michael Victor Caldwell Mr.

Defensive Publications Series

AQUILA-X 3.0 is a transportable, modular, multi-barrier water-production platform designed to produce more independently verified potable water per deployable system than conventional mobile RO plants while maintaining safe operation, source-specific treatment, practical energy demand, maintainability, redundancy, and complete residual accountability.

The system does not depend on one miracle component. Its capacity comes from:

• Selecting the shortest safe treatment route for each characterized source.

• Removing grit, solids, oil, algae, and foulants before fine membranes.

• Using multiple independently isolatable production trains.

• Avoiding high-pressure RO when freshwater does not need desalination.

• Using dedicated high-pressure SWRO equipment and energy recovery when seawater does need …

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The Mathematical Model Predicts Peripheral Blood Cd34+ Cell Yield And Blood Volume Processing For Peripheral Blood Stem Cell Apheresis., Rattaporn Vichitratchaneekorn, Kanokpol Siriphanthong, Kanokwan Chinbordee, Phandee Watanaboonyongcharoen, Ponlapat Ronjnuckarin

Chulalongkorn Medical Journal

Introduction: The accurate prediction of stem cell yields is important for planning peripheral blood stem cell (PBSC) collection. This study aimed to develop a formula forecasting required blood volume processing to ensure adequate CD34+ cell products.

Methods: Data from donors and patients who underwent PBSC apheresis conducted at a tertiary care hospital were reviewed. BD FACSCanto™ II and Navios EX flow cytometry machines were used to determine the pre-collection CD34+ cell counts (preCD34).

Results: Of 50 donors and 85 patients, 145 leukapheresis procedures were performed. Linear regression models accurately predicted absolute CD34+ cell yields from pre-apheresis values, supporting optimal procedural …

Assessing The Reliability Of Machine Learning Models In Classifying Depression Severity Using Facebook Text, Keito Yoneyama

Chulalongkorn Medical Journal

Depression is a growing global issue that requires urgent attention, particularly in Thailand. Without timely intervention, it can lead to serious consequences such as health complications, reduced social participation, and even suicide. Consequently, there has been increased research focused on developing algorithms to identify and classify social media data according to depression severity. This study aimed to evaluate the extent to which such algorithms are a suitable tool for the preliminary classification of Thai Facebook text into different levels of depression severity. The methodology involved data collection through surveys and Facebook scraping, followed by data preprocessing, feature engineering, and model …

Geoengineering And Criminal Liability Comparative Lessons For Penal Reform, Zico Junius Fernando, Deviana Yuanitasari, Chairul Huda, Muhammad Yamani, Arimbi Fajari Furqon

Padjadjaran Jurnal Ilmu Hukum (Journal of Law)

Geoengineering has emerged as a controversial climate technology involving large-scale interventions such as cloud seeding, weather modification, and unregulated carbon capture. While these practices are promoted as solutions to climate change, they also generate significant ecological risks that remain largely unaddressed within criminal law frameworks. This article examines the absence of explicit criminal liability for geoengineering-related harms and explores how comparative legal experiences can inform future penal reform. This research uses normative research methods with several approaches, including comparative, conceptual, and futuristic approaches. The collected legal materials are analysed qualitatively, and content analysis is employed to classify and interpret relevant …

The Expansive Power Of The House Of Representatives As A Precondition For Constitutional Rot, Isnawati Isnawati, Adam Setiawan

Padjadjaran Jurnal Ilmu Hukum (Journal of Law)

This study examines how the expansive powers of the Indonesian House of Representatives have contributed to constitutional rot because those powers no longer operate effectively or proportionately. It identifies dysfunction in the House of Representatives through weak legislative performance, inadequate oversight of the executive branch, and transactional political practices in appointment processes. Using a doctrinal legal method and contemporary constitutional theory as its analytical framework, this study argues that the expansive powers of the House of Representatives constitute a precondition for constitutional rot, evidenced by the poor exercise of legislative authority and institutional intervention through amendments to the Rules of …