Digital Commons Network^™

Evolutionary Game-Based Analysis Of Responses To Hallucinations In Generative Artificial Intelligence, Qiang Yan, Qianyu Zhang, Na Wei

Journal of System Simulation

Abstract: The accelerated deployment of generative artificial intelligence, particularly large language models, has amplified the social risks of hallucinations, posing systemic threats to the credibility of the information ecosystem, the effectiveness of users’ cognitive decision-making, and the governance security in the public domain. Research primarily focuses on hallucination mitigation mechanisms at the technical level or the design of regulatory frameworks at the policy level, lacking a systematic theoretical analysis of the evolutionary logic of strategic interactions among the “large language models, users, and regulators” under conditions of bounded rationality. By introducing evolutionary game theory into the field of generative artificial …

Simulation Method For Multi-Crew Construction Processes Based On Large Language Model-Powered Agent, Yifan Wang, Bin Yang, Congjun Wang

Journal of System Simulation

Abstract: Traditional construction simulation methods typically rely on predefined rules or static scheduling mechanisms, making it difficult to simulate interactive decision-making under complex constraints by dynamically adapting multi-crew construction scenarios. As a result, workforce idleness caused by process dependencies and spatial occupation fails to be solved. A simulation method for multicrew construction processes based on a LLM-powered agent was proposed. The distributed crew agents endowed with construction scenario understanding and reasoning capabilities were constructed, as well as a centralized project manager agent. A “single-manager and multiple-crew” decision-making mechanism for multi-agent interaction in construction was designed. Autonomous decision-making and coordination mechanism …

Symmetric Orthogonalization And Probabilistic Weights In Resource Quantification, Gökhan Torun

Turkish Journal of Physics

Transforming nonorthogonal bases into orthogonal ones often compromises essential properties or physical meaning in quantum systems. Here, we demonstrate that Löwdin symmetric orthogonalization (LSO) outperforms the widely used Gram–Schmidt orthogonalization (GSO) in characterizing and quantifying quantum resources, with particular emphasis on coherence and superposition. We employ LSO both to construct an orthogonal basis from a nonorthogonal one and to obtain a nonorthogonal basis from an orthogonal set, thereby mitigating ambiguity related to the basis choice in defining quantum coherence. Unlike GSO, which depends on the ordering of input states, LSO applies a symmetric transformation that treats all vectors equally and …

Optical Textures Of A Uniform Liquid Crystal Lattice: Monte Carlo Simulations With Newton Colors And Mueller Matrix Analysis, Yakup Emül

Turkish Journal of Physics

The optical textures of a uniform liquid crystal (LC) molecule lattice structure were explored through Monte Carlo (MC) simulations, combined with Mueller matrix (MM) formalism and Newton’s color theory. These simulations utilized a Lebwohl-Lasher (LL) type interacting LC lattice under periodic boundary conditions, generating ensemble-averaged configurations at two temperature regimes (kBT = 0.9 and 1.2), corresponding respectively to nematic and isotropic states. These configurations were then incorporated into the MM framework to evaluate the polarization states of transmitted light. To visually interpret the resulting interference phenomena, we propose a new visualization method based on a modern interpretation of Newton’s color …

Protecting ‘Punks’: The Shortcomings Of The Prison Rape Elimination Act, Rachel Goldsmith

Binghamton University Undergraduate Journal

Prisoner-on-prisoner sexual abuse is widespread in US male prisons, with inmates “turning each other out” by sexually assaulting each other. While the Prison Rape Elimination Act (PREA) received unanimous support in Congress in 2003, motivated by the Human Rights Watch Report “No Escape: Male Rape in Prisons,” scholars argue that the PREA fails to protect prisoners from prison rape: for example, its standards may be ineffective or criminalize consensual sex between prisoners. This essay will examine the shortcomings of the PREA, drawing on current legal scholarship, and propose solutions to enhance the law's effectiveness in protecting prisoners. The US government …

Cover And Contents

Turkish Journal of Physics

No abstract provided.

Scalar Hybrid Meson B̄Gc, Bi̇rten Barsbay İnaç

Turkish Journal of Physics

The scalar hybrid meson H_bc, containing both heavy b and c quarks, represents an intriguing exotic state in QCD. In this article, we investigate its strong decay properties using three-point QCD sum rules. We focus on the two leading decay channels, H_bc → B⁺ D⁰ and H_bc → B⁰ D⁺, which are expected to dominate the decay dynamics. The B and D mesons produced in these decays each consist of one heavy and one light quark. The strong coupling constants at the corresponding vertices are extracted, and the partial decay widths …

The 1/C Expansion Of General Relativity In A 3+1 Formulation, Revisited, Mahmut Elbi̇stan

Turkish Journal of Physics

We study the 1/c expansion of general relativity within a formulation that is compatible with both the Arnowitt-Deser-Misner and the Kol-Smolkin decompositions. The Einstein-Hilbert action takes a common form for those decompositions as they are dual to each other. We first develop a method to expand this generic form and then push the expansion up to c−3 order within this novel approach. Next, we apply our technique to the Arnowitt-Deser-Misner decomposition and expand it up to c−3 order explicitly. In order to demonstrate the applicability of our method and to highlight the duality at the level of expansion, we also …

Outburst Characteristics Of Transient  Low-Mass X-Ray Binary 4u 1608-52, Can Güngör

Turkish Journal of Physics

We present a detailed analysis of the long-term X-ray light curve of 4U 1608–52, focusing on fast-rising exponential-decay (FRED) outbursts, low-intensity states, and quiescent intervals. By calibrating the onset times of the outbursts, we identify three distinct classes for the FRED-type events: (i) the long-high outbursts, exceeding ~50 d in duration with peak count rates above ~40 cnt s-1; (ii) the short-medium outbursts, with durations of ~20 d and peak count rates of ~30-50 cnt s-1; and (iii) the short-low outbursts, also lasting ~20 d but reaching only ~20-30 cnt s-1 at peak. Furthermore, we examine the relation between preoutburst …

New Measurement And Analysis For The 15N + 11B Elastic Scattering System, Nurlan Amangeldi, İsmai̇l Boztosun, Dauren Soldatkhan, Bakytbek Mauyey, Kanat Makhanov, Raimbek Akhat, Aida Anuar, Gani Yergaliuly

Turkish Journal of Physics

New experimental data on the elastic scattering of the nuclear process 15N+11B at an energy of Elab=26.25 MeV were obtained on the DC-60 cyclotron of the INP RK. Based on a semi-microscopic analysis of the interaction of an accelerated 15N ion with 1p-shell nuclei 11B the effectiveness of the new B3Y-Fetal potential was studied. . The difference between the B3Y-Fetal potential and the traditional Yukawa potentials (M3Y-Reid and M3Y-Paris) is that its density-dependent parameters are determined from the saturation condition of nuclear matter at low energy. Analysis was performed on double folding optical model (DFOM) and so no for other …

Hybrid 3d Modelling Framework For Indoor Navigation Using Federated Learning And Internet Of Things-Enabled Edge Devices, Noopur Tyagi, Jaiteg Singh, Saravjeet Singh, Ahmad Ali Alzubi, Farman Ali, Sukhjit Singh Sehra, Babar Shah

All Works

Background There has been a recent trend towards using three-dimensional (3D) models to enhance spatial awareness and maximize resource utilization in complex environments. 3D building model can be used in various applications, such as real-time guidance and tracking the positions of individuals in multi storied buildings. Cities are now being modeled and studied in three dimensions as an improved method of urban planning. Method This study proposes an advanced indoor navigation framework that combines 3D modelling, federated learning (FL), and Internet of Things (IoT) integration to deliver reliable floor-level localization and real-time guidance. In Phase 1, highly accurate 3D models …

George Sturgeon, Metal Fluorides & Vice Chair, Mark A. Griep, George D. Sturgeon

Department of Chemistry: Faculty Interviews

Dr. George Sturgeon was a chemistry professor at the University of Nebraska -Lincoln for 39 years, from 1964 to 2003. During his time at UNL, he spent 15 years as the vice chair. Something in his youth must have sparked an interest in chemistry because he earned a bachelor’s in that subject from the University of North Dakota in Grand Forks. Then, he traveled 870 miles east to Michigan State University in East Lansing where he earned his doctorate. Immediately after graduating, he joined the University of Nebraska-Lincoln in 1964 as an assistant professor but was soon promoted to associate …

A. Introduction To The Archive Of The 1980 Flathead Lake Seismic Survey, Robert W. Lankston

1980 Flathead Lake Seismic Survey

This attempts to provide details of the hardware used during the 1980 seismic survey on Flathead Lake beyond the references in the master's thesis that described the survey and the initial use of the data.

Empowering Neurodiverse Talent In Cybersecurity Through Fair And Inclusive Ai Education, Sheikh Rabiul Islam, Yansi Keim, Mohiuddin Ahmed, Maanak Gupta, Ingrid Russell, Mahmoud Abdelsalam

Research outputs 2022 to 2026

Cybersecurity demands creativity, persistence, and sharp pattern recognition—strengths frequently reported among neurodivergent people (e.g., autism, ADHD, dyslexia). Yet AI-driven hiring pipelines can systematically disadvantage neurodivergent applicants by misreading communication styles or valuing narrow proxies of “fit.” Demand for cybersecurity talent is growing, and experts note that neurodiverse individuals are both underrepresented and highly valuable to security teams. However, progress remains uneven without targeted educational interventions [1]. We present a curricular module that simultaneously (a) centers neurodiversity as a strength in the cybersecurity workforce and (b) trains students to audit and redesign AI hiring systems using open-source fairness and explainability toolkits …

Effects Of Varying Ph, Temperature, And Sucrose Concentration On The Activity Of Invertase Enzyme, B. Rainwater, S. Pratihar

Journal of the Arkansas Academy of Science

The purpose of this research is to study the factors that affect the enzymatic activity of invertase, extracted from baker’s yeast, on hydrolysis of sucrose in aqueous medium. Invertase, a glycoprotein, is an enzyme in the glycoside hydrolase family. It catalyzes the hydrolysis of sucrose producing equimolar mixture of a-D-glucose and b-D-fructose. Invertase shows high affinity for the substrate, and is capable of both cleaving the glycosidic linkage in sucrose and transferring ab-D-O-fructofuranoside residue to an acceptor substrate. (Toledo et al. 2019). A detailed mechanism of the action of invertase was postulated by Shall et al. (Shall et al. 1971). …

Satellites, Urban Heat, And Environmental Justice: Community As The Bridge Between Analysis And Action, Joshua B. Fisher, Ambar Rivera, Ava Cison, Ashley Agatep, Kainani Tacazon, Sophia Spiegleman, Alison Mckenery, Rio E. Fisher, Reginald Archer, Jason A. Douglas

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Heat waves are increasing in frequency, intensity, magnitude, and duration, causing a disproportionate impact on marginalized communities exposed to urban heat islands. Newly emerging spaceborne thermal sensing instruments, such as ECOSTRESS and Hydrosat, now have the capabilities to measure urban surface temperatures accurately at the block level (< 100 m) and with enough frequency to capture transient heat waves (daily to subweekly). Such data are critical for monitoring and informing policy and mitigation efforts, such as resurfacing, green space, cooling stations, and medical mobilization. These serve to advance environmental justice and reduce health risks—and deaths—among the most vulnerable: minority, low-income, elderly, those with physical- and mental-health preconditions, unhoused, children, and outdoor workers. While scientists have increasingly used satellite data to quantify urban heat islands and risks to communities, there remains a significant gap in action resulting from such analyses—a figurative and literal “valley of death.” Reviewing over 500 scientific publications, we identify a critical lack of engagement with the communities being analyzed (10.9%; n = 58); yet, community engagement is key to bridging such analysis with subsequent action. Here, we demonstrate how participatory community engagement directly with data and analysis leads to increased policy changes and mitigation efforts. Our framework has immediate implications for how scientists may augment their work and thought processes to achieve …

Environmental And Social Strategies, And Sustainable Performance: The Mediating Role Of Management Control Systems, Zheng Siqi

Student Works (2020-2029)

This study investigates how environmental and social (E&S) strategies influence enterprise sustainability performance (SP), with a focus on the mediating roles of Environmental Management Control Systems (EMCS) and Social Management Control Systems (SMCS). Anchored in the Resource-Based View (RBV), the study conceptualizes E&S strategies, EMCS, and SMCS as internal organizational resources that support the implementation of sustainability-related strategic intent. Although Chinese manufacturing enterprises face increasing regulatory and societal expectations regarding environmental and social responsibilities, prior research has primarily examined the direct association between sustainability strategies and performance outcomes or has treated sustainability control systems as aggregated constructs, providing comparatively less …

Molecular Detection Of Genes Encoded For Biofilm Formation In Bacteria Isolated From The Oral Cavity Of Patients, Tebarek Al-Taei, Ali A. Al-Hisnawi

Karbala International Journal of Modern Science

Background: A biofilm is a collection of the microbial cells attached to the surface that are encased in a matrix of extracellular polymers. Biofilm formation creates a physical and chemical barrier that prevents antibiotics from reaching bacterial cells, resulting in treatment failure and reinfection. The present study aimed to investigate the biofilm formation in bacteria isolated from the oral cavity of patients.

Methods: In this study, 150 bacterial isolates were obtained from tooth and gum surface swabs of male and female patients of different ages who visited specialized centers and dental clinics in Babylon City after they were clinically diagnosed …

A Virtual Community Math Circle, Skona Brittain, Sayonita Ghosh Hajra, Steve Heller, Daniel Hodgins, Peter Petto, Gabriella Pinter, Lauren Rose, A. Gwinn Royal, Asmita Sodhi

Journal of Math Circles

The Julia Robinson Mathematics Festival (JRMF) Community Math Circle is free, volunteer-run, and online. We collaborate with JRMF and use their activities in our events. Started during the pandemic, the Community Math Circle continues to thrive. We have about 40 participants attending every month, typically kids aged 6 to 13, teachers, facilitators, and other adults. This article describes how our event is organized, planned, and executed, and how we train facilitators. We will also offer reflections on our successes and challenges.

Whose Water Is It, Anyway? Federalism And Texas V. New Mexico, Bryon Louk

Arkansas Law Review

When a problem erupts between two states, interstate compacts provide a solution without the need for a nationwide decision. Rather than waiting for federal consensus, the states can, with Congressional approval, compact to solve their problems. However, the Supreme Court’s decision in Texas v. New Mexico (Texas II) has threatened interstate compacts, ignored principles of federalism, and overextended its original jurisdiction. It has allowed the United States to force Texas and New Mexico to keep fighting over a compact, even when the states have resolved their issues on their own.

First, this Comment will describe the legal background of compact …

Metal-Free Nitrogen-Enriched Graphitic Carbon Nitride Architectures For Advanced Supercapacitor Energy Storage: Design, Synthesis, And Electrochemical Performance Optimization, Loujain Gamal Mohamed

Theses and Dissertations

Abstract

This thesis addresses the urgent global requirement for efficient energy storage materials by developing and characterizing advanced graphitic carbon nitride (g-C3N4)-based electrode materials for supercapacitors. A facile, low-cost thermal polymerization method produces 2D nitrogen-rich GCN nanosheets exhibiting excellent electrochemical stability and wide voltage windows, enabling symmetric devices with 19.33 Wh/kg energy density and remarkable cycling stability over 21,000 cycles. To overcome intrinsic limitations of pristine GCN, a 3D/2D metal free composite with bio-derived carbon (Bio-Cx) is synthesized, delivering high capacitance, wide potential windows, and ultrahigh energy density of 53.72 Wh/kg in asymmetric configurations paired with mesoporous nitrogen-doped carbon (MPNDC). …

On Cartan’S Examples Of Isoparametric Hypersurfaces And Their Focal Submanifolds, Thomas E. Cecil, Patrick J. Ryan

Mathematics and Computer Science Department Faculty Scholarship

This paper is a survey of Cartan’s examples of isoparametric hypersurfaces in spheres and their focal submanifolds that were described in his fundamental work on the subject, which appeared in four papers [2]–[5] published during the period 1938–1940.

Pediatric Inflammatory Bowel Disease Tissue Classification From Pathology Slide Images: Detecting Phenotypes Using Computer Vision, Chloe Martin-King, Ali Nael, Louis Ehwerhemuepha, Blake Calvo, Quinn Gates, Jamie Janchoi, Elisa Ornelas, Melissa Perez, Andrea Venderby, John Miklavcic, Peter Chang, Aaron Sassoon, Brian Rubio, Ghislaine Barrigan, Kenneth Grant

Food Science Faculty Articles and Research

Background and Aims

Methods

Results …

Anfis And Rbfnn Efficacy And Timescale Dependence In Spei-Based Drought Prediction Using Meteorological Inputs, Alisa Afendi, Muhamad Usman Tariq, Shuhaida Ismail, Azizul Azhar Ramli

Journal of Informatics and Web Engineering

Drought is a slow-onset natural disaster that has far-reaching effects on agriculture, water security, and socio-economic systems, especially in climate-vulnerable countries such as Malaysia. It is imperative to predict droughts for prompt mitigation efforts. In this paper, the influence of temporal scale on drought modelling has been put into discussion by analyzing a comparison between two machine learning (ML) models: Adaptive Neuro-Fuzzy Inference System (ANFIS); Radial Basis Function Neural Network (RBFNN) based on Standardized Precipitation Evapotranspiration Index (SPEI) as depicting drought. The SPEI of four timescale categories (SPEI-3, SPEI-6, SPEI-9, and SPEI-12) were calculated weekly and monthly (two different temporal …

Vehicle Re-Identification System Using Residual Network With Instance-Batch Normalization, Wei Jie Low, Kah-Ong Michael Goh, Check-Yee Law, Connie Tee, Yong-Wee Sek, Md Ismail Hossen

Journal of Informatics and Web Engineering

Vehicle Re-identification (Re-ID) has become extremely important due to the increasing number of vehicles on the road and its potential to address traffic-related challenges. As a result, there is also a growing need for efficient methods to track and identify vehicles across multiple traffic cameras. One of the biggest challenges of this task is the variations in vehicle appearances across different camera angles. This is because vehicles can appear significantly different when captured from various camera angles and viewpoints. Furthermore, the current vehicle Re-ID solutions typically require extensive coding knowledge, making it inaccessible to many potential users. Therefore, we focus …

Editorial: Intelligent Systems And The Next Wave Of Digital Innovation, Hairulnizam Mahdin

Journal of Informatics and Web Engineering

The field of artificial intelligence (AI), machine learning and intelligent automation has become pervasive in our modern digital world. It extends from business and public services to environmental management and even into people's daily experiences with technology. In this special issue "Intelligent Systems and the Next Wave of Digital Innovation," published in the Journal of Informatics and Web Engineering, reviews several studies to explore the increasing role of intelligent systems in current society and their importance. Some of the more significant areas of discussion are how to formalize the expectations for explainable AI, evaluating face recognition models in the real …

Robust Medical Image Prediction Via Adaptive Reconstruction: Bridging The Gap In Low-Quality Data, Prateek Singhal, Madan Singh

Journal of Informatics and Web Engineering

Medical image prediction plays a very significant role in clinical decision-making and early detection and diagnosis of different diseases. However, the quality of medical images has a huge impact on the predictive models' accuracy. Poor-quality data usually occurs due to problems like noise, artifacts, and low resolution and poses a major challenge for reliable medical image prediction. Framework advances medical image analysis through three novel contributions firstly, A hybrid architecture combining wavelet-based denoising with deep learning (DL) enhancement (unlike existing single-approach methods). Secondly, Cross-modality robustness validated on low-quality CT/MRI/X-rays from real clinics (versus modality-specific solutions), and lastly, A closed-loop system …

Efficiency Of Neo4j In Designing And Analysing Graph Database For Air Quality Analysis Of Indian Metro Cities, Jiten Chavda, Kishan Bharvad, Rishap Parmar, Nidhi Arora

Journal of Informatics and Web Engineering

The analysis of the Air Quality Index (AQI) is currently a popular subject in the area of sustainable research, as it is crucial for investigating and analysing the effects of air pollutants on human health in urban environments. It has been identified over the last decade that airborne pollution has become a critical issue and will remain an important concern in India in the coming years. In recent years, a variety of models and algorithms utilizing big data techniques have been developed for the analysis of air quality data. In this paper, we suggest monitoring and feature analysis of air …

Hybrid Sentiment Analysis Model For Customer Feedback Interpretation Using Lexicon, Machine Learning And Deep Learning Techniques, Jou Jia Yi, Lew Sook Ling, Tan Li Tao

Journal of Informatics and Web Engineering

Customer feedback is pivotal in enhancing service quality and user satisfaction across digital platforms. However, traditional sentiment analysis methods often struggle with informal languages, contextual nuances, and aspect-specific opinions. In this paper, a hybrid sentiment analysis framework is proposed, utilizing lexicon-based (VADER), machine learning (Support Vector Machine and Random Forest), and deep learning (BERT) techniques to achieve improved sentiment classification accuracy and interpretability compared to previous studies. The framework incorporates advanced preprocessing techniques, such as emoji normalization, handling of negation, and detection of intensifiers, to better capture emotional information in user-generated content. The objectives of this study are to develop …

An Empirical Evaluation Of Machine Learning Methods And Text Classifiers For Sentiment Analysis Of Online Consumer Reviews, Pei Qin Lo, Sew Lai Ng, Li-Xian Jiao

Journal of Informatics and Web Engineering

This study aims to identify the best predictive model for analysing online product reviews (OPRs) in the electronics industry, with a secondary focus on leveraging unstructured customer feedback to support product improvement. Using a dataset of 9,675 Oppo mobile phone reviews, this study employs three classification models—Random Forest, Support Vector Machine (SVM) and Logistic Regression–paired with Term Frequency-Inverse Document Frequency (TF-IDF) or bidirectional encoder representation transformer (BERT) as the embedding models to analyse customer sentiment and derive actionable insights. The methodology features a comprehensive analysis pipeline that includes text preprocessing with the Natural Language Toolkit (NLTK), feature extraction using) vectorization …