Digital Commons Network^™

Q-Learning Enhanced Memetic Algorithm For Robust Scheduling Of Space Launch Missions, Rui Lin, Xiaolu Liu, Yonghao Du, Mingyang Geng, Zhenshun Shi

Journal of System Simulation

Abstract: A robust optimization mathematical model and an enhanced memetic algorithm (MA) for space launch mission scheduling are proposed to address the practical challenges in space launch mission scheduling under the influence of multiple uncertainties such as equipment failure, process rework due to quality issues, and technological changes. A robust optimization scheduling model for space launch missions is built by integrating the makespan under the worst-case scenario, the average maximum makespan, and the average deviation of process start times. A Q-learning enhanced memetic algorithm (QMA) is proposed, which can dynamically select parent solutions based on the population state. Simulation experiments …

Pentagonal Pdte2 Monolayer For Sustainable Solar-Driven Hydrogen Production, Narender Kumar, Shambhu Bhandari, Dario Alfè, Ravindra Pandey, Nacir Tit

Michigan Tech Publications

This investigation demonstrates that the pentagonal PdTe2 (penta-PdTe2) monolayer is a highly tunable two-dimensional (2D) photocatalyst, characterized by the bandgap of 1.87 eV and high hole mobility. Using density functional theory calculations with the HSE06 functional, we show that tensile strain engineering (particularly at +2% and +3%) is essential for enabling spontaneous water splitting. At these strain values, the valence-band maximum and conduction-band maximum straddle the water redox potentials (H+/H2 and O2/H2O) under both acidic (pH = 0) and neutral (pH = 7) conditions. The monolayer's low hole effective mass facilitates rapid charge extraction, mitigating recombination and driving the oxygen …

Adaptive Improved Particle Swarm Optimization-Based Maximum Power Point Tracking And Energy Smoothing For Photovoltaic Hybrid Battery–Supercapacitor Storage Systems, Mohammad Aminul Islam, Guo Shaokai, Jakaria Mahdi Imam, Mohammad Khairul Basher, Nowshad Amin, Tarek Abedin, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

The rapid development of photovoltaic (PV) systems has made them an important component of the global clean energy strategy. However, the intermittency and non-linear characteristics of photovoltaic (PV) output remain major challenges for stable renewable energy utilization. This study proposes an adaptive improved particle swarm optimization (IPSO)-based maximum power point tracking (MPPT) strategy integrated with hybrid energy storage coordination for photovoltaic systems. The IPSO introduces adaptive inertia adjustment, velocity clamping, and stagnation reinitialization, which improve the convergence robustness under dynamic irradiance and temperature conditions. The algorithm was benchmarked against Perturb & Observe (P&O), Incremental Conductance (INC), and standard PSO using …

Silence And Whispering In The L2 Pragmatics Classroom: Duoethnographic Insights From A Vietnamese Context, Duong Minh Tuan, Le Thi Diem Lan

The Qualitative Report

This article examined how silence and whispering shape participation in an L2 pragmatics course for English majors at a Vietnamese university. Using a duoethnographic approach, we, as lecturer–researchers and the sole participants in this study, engaged in written dialogic exchanges over a 12-week semester, drawing on salient classroom incidents and institutional texts as prompts. Our dialogues revisited scenes in which students were quiet or whispered in Vietnamese, and we interrogated our shifting interpretations of those moments in light of scholarship on silence, L2 pragmatics, and language policy. Four themes emerged. First, silence as calibrated participation showed how students strategically modulated …

From Morphological Patterns To Meaning: A Calculus Of Arabic Morphology For Morphologically Aware Machine Translation, Saleh Belhassen, Ahmed Hakami

Journal of Arabic Sciences and Humanities

The computational processing of Arabic morphology presents a substantial challenge due to its intricate, non-concatenative root-and-pattern structure, which often leads to semantic ambiguity in translation. This paper introduces the Pattern Matrix Calculus (PMC), a mathematical and algorithmic framework that formalizes Arabic derivational morphology as an algebra of computable functions. Word formation is conceptualized as W = V(P(R)) — meaning that a word (W) is generated by applying a morphological pattern (P) to a consonantal root (R) and then adding vocalization (V). Derivational patterns are encoded as matrices, enabling operations such as comparison, composition, and direct inference of morphological meaning (i.e., …

Structural, Spectroscopic And Dft Study Of C11H8N2O4 As A Potential Sars-Cov-2 MPro Inhibitor, Mücahit Yılmaz, Mehmet Hanifi Kebiroğlu

Baghdad Science Journal

In this study, the structural, electronic, and spectroscopic properties of the 3-(1,3-benzodioxol-5-yl)-1H-pyrazole-5-carboxylic acid (C₁₁H₈N₂O₄) molecule, which has potential biological activity and optoelectronic properties, were investigated theoretically. All quantum chemical calculations were performed at the B3LYP/6-311G(d,p) basis set level using Density Functional Theory (DFT). Frequency analysis of the optimized geometric structure confirmed that the structure has a stable minimum on the potential energy surface. The calculated energy gap of 3.982 eV, because of Frontier Molecular Orbital (FMO) analysis, revealed the chemical stability and Intramolecular Charge Transfer (ICT) behavior of the molecule. The calculated …

A Hybrid Non-Monotone Cubic Line-Search Method With Subset-Based Armijo Acceptance For Multi-Objective Optimization, Jwan Nasrulla, Ivan. Latif

Baghdad Science Journal

Line-search techniques are vital to first-order optimization algorithms because they provide stable and efficient convergence. In multi-objective optimization, designing effective step-length rules is especially difficult because conflicting objectives are involved, and such situations make it often impossible to design a rule that involves strict monotonic decrease of all components, and results in premature stagnation. In this paper a Hybrid Non-Monotone Cubic (HNMC) line-search algorithm for unconstrained multi-objective optimization problems is proposed. The proposed approach integrates cubic interpolation with two non-monotone reference mechanisms, i.e. sliding window maximum and exponential moving average. A subset-based Armijo acceptance rule is used to permit controlled …

Role Of Eccentricity-Based Topological Indices In Predictive Modeling Of Physicochemical Properties Of Monocyclic Aromatic Compounds, Balkishbanu Khaji, Shahistha Hanif, K Arathi Bhat

Baghdad Science Journal

Topological indices are numerical molecular descriptors in quantitative structure-property relationships (QSPR) models. The connectivity-based topological indices play a vital role in mathematical chemistry. In this article, we demonstrate the predictive power of some eccentricity-based topological indices among monocyclic aromatic hydrocarbons. Though a number of indices and several properties are considered, it is found that only the atom bond connectivity eccentricity index and geometric arithmetic eccentricity index exhibit strong correlation with properties like molecular weight, boiling point, and Log P, where P is the partition coefficient associated with the compound. Further, new helpful closed formulae for these indices for some …

Non-Linear Programming For Ar(2) Parameter Estimation: Gradient Projection And Convex Quadratic Programming Methods, Halah Fadhil Hussein Al-Hakeem, Murtaza Khan

Baghdad Science Journal

Assessing parameters in autoregressive (AR) models is a fundamental aspect of time-series analysis and is widely used in fields such as finance, climate science, and engineering. Ordinary least squares and maximum likelihood estimation are commonly used for this purpose, but their performance can be affected when the estimation process is subject to complex constraints. In this study, two nonlinear programming techniques—the Gradient Projection (GP) method and Convex Quadratic Programming (CQP) based on the complementary pivot algorithm—were examined for estimating the parameters of an AR(2) model. The two nonlinear methods were compared with traditional estimation techniques using the Mean Squared Error …

Animus And Heightened Scrutiny: A Way Out Of The ‘Dead End’, Steve Sanders

Texas A&M Law Review

Laws or government actions that are grounded in animus rather than proper public purposes violate the Constitution’s guarantee of equal protection. This principle arises from four canonical cases decided by the Supreme Court between 1973 and 2013. These cases remain good law. Yet in the past decade the Roberts Court has given scant attention to the animus doctrine, and lower courts appear to be in a muddle about how to use it. As a result, the animus doctrine has reached what one prominent scholar calls a “dead end.” The animus cases are often described as exhibiting a more skeptical, more …

Being A Padawan And Mastering The Force: A Dissertation Quest, Papia Bawa

The Qualitative Report

This study explores the experiences of one doctoral researcher and two doctoral peers navigating mentor-mentee relationships through a literary lens, employing autoethnographic methods to capture the nuanced dynamics of guidance, expectation, and emotional labor. Data were drawn from narratives found in reflective journals, personal memos, email exchanges, text messages and conversations with four faculty mentors and two doctoral peers accumulated through the doctoral journey.  The narratives were analyzed using thematic analysis. Using vignettes and incident reports, the research highlights key turning moments in the doctoral journey that shaped perceptions of mentorship, emphasizing both the cognitive and affective dimensions of academic …

“Charting The Course: 20 Years Of Cmsi And The Future Of China In The Maritime Military Domain”

CMSI Quarterly Review

Keynote address by former Chief of Naval Operations (CNO) Admiral Gary Roughead, U.S. Navy (Ret.) at the commemoration of the twentieth anniversary of the China Maritime Studies Institute (CMSI)’s official public launch.

Academic Performance In College Students: The Roles Of Physical Activity, Perceived Academic Control, And Bmi, Erin Vanderbunt, Jenna Woolley

Topics in Exercise Science and Kinesiology

Volume 7: Issue 1, Article 3, 2026.  Background: Health behaviors and motivational factors are increasingly recognized as contributors to academic performance in college students. Physical activity (PA), perceived academic control (PAC), and body mass index (BMI) have each been linked to academic outcomes, yet their combined effects remain understudied. Purpose: To examine the relationships between PA, PAC, BMI, and academic performance in undergraduate students. Methods: A total of 299 undergraduates from a regional Midwestern university participated in this study. Students completed a survey assessing demographic variables, physical activity (via IPAQ-SF), PAC, BMI, and self-reported academic performance on a …

Communication & Theater Association Of Minnesota Journal, Volume 49, Issue 2, 2026

Communication and Theater Association of Minnesota Journal

Volume 49, Issue 2 (2026) of the Communication & Theater Association of Minnesota Journal.

Welcoming Generation Alpha Through The Lens Of Connectivism: Featuring Ai's Rhetorical Agency, Lin Allen, Shea-Tinn Yeh

Communication and Theater Association of Minnesota Journal

As students pack for college do they leave space in their carry on for agency—self-empowerment through the strategic use of artificial intelligence?  And in what ways do educators address the need to define and shape their learning experience?  Preparing to welcome the first wave of Generation Alpha (Gen Alpha) by endowing them with agency, this theoretical framework draws upon the eight principles of connectivism. Gen Alpha, digital natives by necessity, demands a new learning archetype incorporating artificial intelligence (AI). However, the contested capabilities of generative artificial intelligence (GenAI) reveal a disparate, disconnected approach to responding to the ubiquity of GenAI …

Standardized Preprocedure Protocolling Of Stereotactic Breast Biopsies Enables Device-Level Supply Chain Forecasting: A Multisite Quality Improvement Analysis, Megan Kalambo, Mike Everding, Maria Montemayor, Falguni Patel, Mohit Nath

Advances in Cancer Education and Quality Improvement

Background: Breast imaging depends on single-use, vendor-proprietary consumables produced by a concentrated set of manufacturers. During supply shortages in 2026, healthcare organizations faced urgent pressure to shift from reactive to proactive inventory management. Stereotactic breast biopsy needle shortages revealed that traditional forecasting based on procedure volume lacks the granularity needed for device-specific demand. We aimed to enable device-level forecasting through standardized preprocedure protocolling.

Methods: In a retrospective analysis of 1,456 stereotactic biopsies across 4 breast imaging sites (June 2025 to June 2026), compliance with a standardized electronic protocolling tool that captured lesion count and needle size (standard vs. petite) was …

Validating A Predictive Model Of Nurse Burnout Using Integrated Data Sources, Shahin Davoudpour, Mahesh Vaidyanathan, Rinad S. Beidas, Hannah Mulroe, Elliott Brandon, Matthew Lloyd, Gabrielle M. Olson, Mallika Pandey, Daniel Blumenthal, Baljash Cheema, Gaurava Agarwal

Advances in Cancer Education and Quality Improvement

Objective: To evaluate an integrated machine learning model using routinely collected organizational data to identify nurses at increased risk for burnout.

Background: Health care worker burnout directly threatens patient safety, quality of care, and workforce stability. Although nurses experience significantly higher burnout rates than physicians and face distinct operational stressors (eg, staffing shortages, continuous bedside care demands), most predictive modeling efforts have focused on physicians. Current approaches to identifying burnout typically rely on voluntary surveys, but advances in data science and machine learning have created new opportunities to move beyond self-reported measures.

Methods: This retrospective observational study included 1,177 nurses …

Systems And Methods For Price Matching Through Payment Dispute Flows, Deepak Tomar

Defensive Publications Series

Systems and methods for price matching through payment dispute flows are provided. A request to initiate a price match is received from a consumer for a transaction made using a payment credential issued by an issuing bank. The issuing bank generates a price match dispute message and transmits the price match dispute message through a payment network to an acquirer associated with a merchant of the transaction. The merchant is notified of the price match dispute, and a response to the price match dispute is received from the acquirer or the merchant. The response indicates either agreement with the requested …

System, Method, And Computer Program Product For Routing A Machine Learning Inference Request To A Model Version Based On Properties Of A Format-Preserving Encrypted Identifier Without Decryption, Hao Qin, Ruiyang Xia

Defensive Publications Series

The present disclosure provides a method, a system, and a computer program product for routing machine learning inference requests based on properties of a format-preserving encrypted identifier without performing decryption. The method comprises receiving a transaction request containing an identifier encrypted using format-preserving encryption, wherein the encrypted identifier preserves the format and length of the original identifier. The method includes extracting a prefix portion of the encrypted identifier without performing decryption and without accessing cryptographic key material. The method includes matching the extracted prefix against a pre-computed routing table that maps encrypted prefixes to machine learning model versions, wherein the …

Account-Context-Affinity Routing For Transformer-Based Payment Authorization With Key-Value Cachestate Freshness As A Routing Signal, Durga S. Kala, Tomer Rabani, Benjamin Nativi

Defensive Publications Series

The present disclosure provides a method and a system for account-context-affinity routing in a distributed transformer inference grid. The method includes recording, by a cache state monitor embedded in each inference stack, KV cache hit and miss events for each account bucket and determining a rolling hit rate for each account bucket over a sliding window. The method includes aggregating the rolling hit rates from the inference stacks into a preference matrix mapping account buckets and inference stacks to hit rates and publishing a snapshot of the preference matrix to a routing signal bus. The method includes receiving an authorization …

Trusted Gen Ai Analytics Using Semantic Graph Grounding And Grain-Safe Query Validation, Srishti Jaiswal, Anshul Hedau

Defensive Publications Series

A computer-implemented system and method to generate trusted analytics result from a natural-language business query. Business-intent elements represented by the query are mapped to semantic objects in a semantic data graph representing business entities, approved relationships, measures, dimensions, filters, and aggregation-grain metadata. Before generation of an executable query, one or more candidate semantic query plans are generated over the semantic data graph. A validation engine validates relationship-path correctness, measure compatibility, aggregation-grain safety, ambiguity, policy constraints, and fanout or double-counting risk. Validated plans may be ranked using confidence scores, and clarification may be requested when materially different interpretations remain. A selected …

Automated Counterfactual Pair Mining In Payment Artificial-Intelligence Systems, Durga S. Kala, Om Pandey, Tanner Barcelos, Benjamin Nativi, Jun Xu

Defensive Publications Series

A system and method for identifying counterfactual transaction pairs in a payment artificial-intelligence system. An atomic embedding vector associated with a query transaction is selected, and an inference embedding vector index is queried to retrieve transaction records whose embeddings satisfy a similarity criterion. Outcome metadata associated with the retrieved records is compared with an outcome of the query transaction. A retrieved transaction having a divergent outcome is paired with the query transaction as a counterfactual transaction pair. An embedding distance between the pair members indicates decision-boundary proximity. The pair may be stored in a counterfactual-pair registry and used for decision …

Combatting Cyber Warfare, Peter Stevenson

Defensive Publications Series

This paper offers a regulatory behavior for news services that leverages Reinsurance providers as a means to giving news an equivalent metric to Moody's and Standard & Poors methods of measuring debt risk in corporations. Whilst not a all encompassing metric it provides service users with a knowledge of the trustworthiness of their preferred news source.

System For Personalized Commerce Using Multimodal Outcome Gap Analysis, Serline S. Coelho

Defensive Publications Series

Systems for connecting users with products in audiovisual content, such as videos or images, can have limitations in assisting a user to replicate a holistic outcome, for example an entire room design, which may result in fragmented or redundant product suggestions. A described system can perform multimodal analysis of content to generate a structured model of a desired outcome. This outcome model may then be compared against a model of the user's current state, which can be derived from user-authorized data sources (e.g., images of a user's environment, purchase history), to identify an outcome gap of missing products. A commerce …

Self-Improving Multi-Ai Agent System For Impact-Aware Infrastructure Configuration Remediation, Arica Schivonne Jackson, Sushma Mahadevaswamy, Sree Gowri Addepalli, Barry Qi Yuan

Defensive Publications Series

A self-improving multi-agent artificial intelligence (AI) system is proposed herein for impact-aware infrastructure configuration remediation across cloud, on-premises, network-fabric, container, and hybrid environments. The system builds a temporally weighted identity and dependency graph (TIDG) from telemetry and large language model (LLM)-extracted relationships, uses a graph neural network (GNN) to predict the operational blast radius of a proposed change, and routes each finding to one of four simulation tiers. Every tier emits a normalized per-principal good-actor impact vector. Independent security, reliability, cost, and compliance evaluators use that vector in an adversarial governance gate. Accepted changes advance through telemetry-gated observe, canary, progressive-ring, …

Secure, On-Device Financial Aggregation And Autonomous Liquidity Management, Thirumagal Dhivya Subramanian

Defensive Publications Series

Systems for personal financial management may centralize data on remote servers, which can expose sensitive information, such as user credentials and personal messages, to potential security vulnerabilities. Described systems and techniques provide for a financial management architecture that can operate locally on a user's client device (e.g., a smartphone, smart watch, wearable device, or augmented reality glasses). The architecture may utilize on-device listeners to capture unstructured financial alerts, and a lightweight, on-device large language model may parse these alerts to extract structured transaction data. A predictive analytics engine can then forecast cash flow to calculate a suggested liquidity value for …

Language Model Generation Of Executable Commands For Native User Interface Control, Ankit Aggar, Sujay Mohan

Defensive Publications Series

Conversational agents integrated into software applications can introduce user friction by providing text-based instructions that require users to perform manual navigation. This disclosure describes systems and methods where a language model can process a user's natural language input to generate a structured data payload, such as a Javascript object notation object, containing executable commands. A client-side application may intercept this payload and use a native execution engine to interpret the commands. This process can trigger direct user interface actions, for example, navigating a user to a specific screen or dynamically rendering an interactive native widget within the conversational flow. This …

Automated Risk-Based Schedule Optimization From Unstructured Project Data, Mike Goodman, Gary Foreman, Sumit Agrawal, Matt Anderson, Ashwin Mishra

Defensive Publications Series

Project management for large-scale industrial operations may be challenged by rigid plans that are susceptible to disruptions from real-world events, potentially leading to schedule and cost overruns. A system for automated workflow optimization can process unstructured data by using an agentic framework to ingest heterogeneous data, such as technical manuals and three-dimensional models, to extract project tasks and their dependencies. A bilevel optimization engine, which could be coupled with Monte Carlo risk simulation, may then process this task list to generate a risk-adjusted and optimized schedule based on variables including, for example, cost and time. This approach can facilitate a …

Preserving Threatened Wisdom In Indigenous Houses As Living Archives: An Ethnographic Study Of Spatial, Gendered Knowledge, And Community-Based Preservation Strategies In The Philippines, Lalin Abbacan Tuguic

The Qualitative Report

This qualitative study explores how Indigenous houses function as living archives of identity, ecological wisdom, and gendered knowledge in Kalinga communities in the Cordillera region of the Philippines. Using an ethnographic design grounded in prolonged engagement and reflexive practice, the research documents how historical experience, social and cultural meanings, environmental adaptation, and community‑based preservation strategies are materially and symbolically embedded in Indigenous house construction and use. Data were generated through participant observation of everyday life and rituals in and around traditional square and octagonal houses; semi‑structured interviews with elders, women, builders, youth, and community leaders; focus group discussions in local …

Illinois Model Programs Of Study Guide: Digital Technology, Education Systems Center

Reports, Analyses, and other Publications

This guide is designed to support the design and implementation of high-quality programs of study in digital technology that lead to in-demand, living-wage careers, in alignment with Illinois statute. The recommended programs of study should be customized by local K-12 and community college partners.