Digital Commons Network^™

Real-Time Sdn–Iot Integrated Framework For Intelligent Emergency Vehicle Prioritization In Smart Cities, Sura F. Ismail

Mesopotamian Journal of Computer Science

Urban traffic control has become increasingly complex with rising vehicle density, particularly in smart cities. Timely arrival of emergency vehicles is critical, yet existing systems relying on manual transmitters and sirens offer limited range and effectiveness. This paper proposes a real-time intelligent traffic management framework integrating Software-Defined Networking (SDN), Internet of Things (IoT) technologies, and the Edge of Things (EoT)—a paradigm combining edge computing with IoT to enable low-latency processing at the network edge. The framework connects the SUMO traffic simulator and Veins vehicular network framework via TraCI, with the RYU SDN controller dynamically adjusting traffic signals and vehicle routes …

Haze-Image-Dataset: A Large-Scale Benchmark For Image Dehazing In Variable Fog And Low-Light Conditions, Mustafa J. Shahbaz, Ali A.D. Al-Zuky

Mesopotamian Journal of Computer Science

To enhance image dehazing and visual recognition in real-world conditions, we introduce HAZE-IMAGE-DATASET, a large-scale dataset comprising nearly 42,000 images. It is constructed from 1,532 clean images sourced globally and captured using a Samsung smartphone, covering diverse natural and urban scenes. The dataset includes synthetic and real haze variations. Synthetic haze was generated using MATLAB-based atmospheric scattering models with depth maps for 10 fog levels. Colored haze was created using alpha blending (α = 0.4) in six colors: red, green, blue, yellow, white, and black. Low-light conditions were simulated via uniform darkening at 10 levels. Also, 616 real haze images …

Towards Achieving The Un Sustainable Development Goals: The Role Of Ai In Municipality Services, Thabit Sultan Mohammed, Karim Mohammed Aljebory, Ahmed Thabit Sultan

Mesopotamian Journal of Computer Science

In 2015, the United Nations adopted the Sustainable Development Goals (SDGs) to end poverty, protect the planet, and ensure global peace and prosperity by 2030. However, progress has been hindered by challenges like the COVID-19 pandemic, climate change, funding shortages, political instability, and data limitations. Municipal services, crucial to achieving the SDGs, provide essential functions like waste management, healthcare, and public safety. Artificial Intelligence (AI) offers innovative solutions to enhance these services, improving urban sustainability and fostering public-private collaboration. This research examines AI's role in municipal services, analyzing its applications, benefits, challenges, and future potential through case studies and expert …

Enhanced Tea Algorithm Performance Using Affine Transformation And Chaotic Arnold Map, Nada Hussein M. Ali, Mays M. Hoobi, Sura Abed Sarab Hussien

Mesopotamian Journal of Computer Science

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing …

Enhanced Iot Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection And Adaptive Smote, Sura Abed Sarab Hussien, Mustafa S. Ibrahim Alsumaidaie, Nada Hussein M. Ali

Mesopotamian Journal of Computer Science

The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrate that GWO reduces features from 32 …

Dgen: A Dynamic Generative Encryption Network For Adaptive And Secure Image Processing, Mohammed Rajih Jassim, Qusay M. Salih, Ghada Al-Kateb

Mesopotamian Journal of Computer Science

Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public …

Lightweight Deep Reinforcement Learning Model For Energy-Efficient Resource Allocation In Edge Computing, Ghassan A. Abed, Mohanad A. Al-Askari

Mesopotamian Journal of Computer Science

A lightweight digital twin model for a single 6G cell operating in the D-band (140 GHz) with a 1 GHz bandwidth is presented in this work with the goal of assessing the cell's capacity, coverage, and terminal time in order to support extended reality (XR) applications. With a tangent dispersion of 3 dB and a path exponent of n = 2.2, the model is based on the free-space loss equation as per ITU-R Recommendation P.525. The instantaneous capacity is determined using the Shannon-Hartley theorem. Three XR sessions are created every minute using a Poisson method, and their durations are determined …

Agentic Ai-Enhanced Virtual Reality For Adaptive Immersive Learning Environments, Indra Kishor, Udit Mamodiya, Mohammed Almaayah, Amer Alqutaish, Rami Shehab, Theyazn H. H. Aldhyani

Mesopotamian Journal of Computer Science

Immersive learning using Virtual Reality (VR) has gained prominence for delivering experiential, engaging education. However, most VR learning environments lack real-time adaptability, personalization, and cognitive responsiveness. This study presents an Agentic AI-enabled VR framework that autonomously adjusts pedagogical content, interaction style, and challenge level based on learner behavior, emotions, and performance feedback. The proposed system integrates a reinforcement learning-based agent with a virtual reality module to form an intelligent tutor capable of independent decision-making. A neuro-symbolic model processes multi-modal feedback (gesture, speech, gaze, performance) to determine context-aware pedagogical strategies. The system employs a self-evolving curriculum logic that adapts in real …

Effects Of Ionophore And Yeast Addition To The Diet On Starch Digestion And Rumen Andblood Parameters In Sheep With Subacute Rumen Acidosis, Şevket Evci̇, Mehmet Aki̇f Karsli, Mehmet Demi̇rci̇, Gökhan Şen

Turkish Journal of Veterinary & Animal Sciences

This study aimed to investigate the prevention of acidosis in ruminants, which causes yield and financial losses, and toevaluate the effects of feed additives on starch digestion. Four male Bafra yearling lambs with cannulated rumens were used in a 60-daystudy. Each lamb underwent 10 days of adaptation to a ration and 5 days of sampling for four different rations including a control ration(CR), monensin ration (MR), Saccharomyces cerevisiae ration (SR), and a ration with the combination of monensin and Saccharomycescerevisiae (MSR). The experiment followed a 4 × 4 Latin-square design. Dry matter intake and digestion rates were recorded as 2404 …

Characterization Of The Biofilm-Forming Ability And Certain Virulence Characters Ofaeromonas Spp. Isolates From Rainbow Trout, Türker Çelebi̇, Ertan Emek Onuk, Esra Demi̇rbaş, Gökçen Di̇nç

Turkish Journal of Veterinary & Animal Sciences

Aeromonas spp., commonly found in the aquatic environment, cause infections in both fish and humans. Their pathogenicitydepends on various virulence factors and ability to form biofilm. The current study aimed to determine the biofilm-forming capabilitiesand certain virulence characteristics of 25 Aeromonas spp. isolates obtained from rainbow trout in Türkiye. The biofilm-forming abilitiesof isolates were investigated comparatively using Congo red agar (CRA), the tube method (TM), and tissue culture plates (TCPs).Potential virulence factors, including hemolytic activity, gelatinase production, serine protease activity, DNase activity, and motility,were evaluated using phenotypic tests. Additionally, the distribution of four known virulence genes, namely aerA, exu, fla, …

A Guide To Urban Planning And Environmentalism, Michael Lewyn

Scholarly Works

Review of The Sustainable Urban Design Handbook, by Nico Larco, Kaarin Knudson.

A Brief Look At Authoritarianism And Totalitarianism Through A Perspective Of Jewish Law And Tradition, Samuel J. Levine

Scholarly Works

A view of authoritarianism and totalitarianism through a perspective of Jewish law and tradition might take various forms and draw upon different approaches, depending on a number of components, including definitions of terms, modes of analysis, and the scope of disciplines and materials to be incorporated. Rather than attempting to present a comprehensive or determinative presentation of historical and philosophical considerations of these issues, this essay will briefly explore conceptual lessons from narrative, political, and legal sources of Jewish tradition, suggesting that Jewish thought recognizes, at once, both the importance of unity and authority and the dangers of authoritarianism and …

Time-Pressured Negotiations, Hal Abramson

Scholarly Works

This Article considers how to negotiate when you do not have the time to use your best negotiation practices. No other article has considered what to do when in a time-pressured negotiation other than to advise you not to be trapped by a deadline. When you have no choice but to rush, this Article examines the choices that will reduce the risks posed by skipping any best practices.

This Article first considers the inherent risks of taking shortcuts and then describes a negotiation map suitable when not rushed as a guide for selecting shortcuts when rushed. After this introduction, the …

Cardiac Timing Effects On Response Speed Are Modulated By Blood Pressure But Not Heart Rate Variability In Healthy Young Adults, Xiao Yang, Catalina Roldan, Michael Gazzanigo, Yasmine Nabulsi, Fang Fang

Research and Infrastructure Service Enterprise (RISE) Faculty Publications

Cardiac timing effects reflect the dynamic interplay between interoceptive and exteroceptive processes. Human information processing tends to be facilitated during cardiac diastole and inhibited during systole, reflecting autonomic regulation and the neuromodulation by baroreceptor afferents. Thus, blood pressure (BP) and vagally-mediated heart rate variability (vmHRV) are potential modulators of those effects. Additionally, cognitive control appears to play a critical role in the processes. However, whether cardiac timing effects are influenced by those factors remains unclear. The present study aimed to clarify these relationships. Fifty-one healthy young adults completed three experimental sessions to assess BP, short-term HRV, and cardiac timing effects. …

Repressed Memories And The Body Keeps The Score: Public Perceptions And Prevalence, Kris-Ann S. Anderson, Quincy C. Miller, Deryn Strange, Kamala London

Publications and Research

The “memory wars” resurgence has renewed debates over the validity of repressed memories. This revival appears linked to factors such as changing statutes of limitations, confusion about repression, and unchallenged social media content. In a nationally representative online survey of American adults (N = 1581), we examined (a) beliefs in repression and the body keeps the score, (b) the prevalence of recovered memory claims, and (c) the impact of question phrasing on recovered memory reporting. An overwhelming 94% of respondents expressed belief in repressed memory, and 77% endorsed the idea that the body keeps the score. Additionally, 3.6% (n = …

Does Performance Change Budgets? Punctuated Equilibrium, Performance, And The Budget For Juvenile Justice In An American State, Elaine Yi Lu, Robert Hines, Katherine Willoughby

Publications and Research

How performance informs budgeting and budgets is contentious and unclear. Applying punctuated equilibrium theory, this research seeks to understand if performance information once placed on the media and macropolitical agendas can lead to long term budgetary shifts. This research highlights how the accumulation of performance information punctuated the funding scheme and created a new equilibrium over time.

This research uses mixed methods to study the impact of performance on Florida’s (USA) Department of Juvenile Justice (DJJ) over a 20-year period. First, we conduct a media review of 400 randomly sampled newspaper articles to characterize the media discourse around the DJJ …

Assessing The Predictive Validity Of The Network Inventory Of Risk, Victories, And Needs Assessment (Nirvana) For Youth Receiving Prevention Services., Michael T. Baglivio, Kevin T. Wolff, Katherine Jackowski

Publications and Research

The current study assesses the predictive validity of a newly-developed holistic risk/needs assessment for youth receiving prevention services. Employing a multiyear statewide sample of over 17,000 prevention youth, multivariate and Area Under Curve techniques are used to examine predictive validity in predicting future formal juvenile justice system involvement (new law violations) across sex, race/ethnicity, and multiple youth age ranges. Furthermore, predictive validity across the severity of the subsequent offense type (misdemeanor, non-violent felony, violent felony) was examined. Findings demonstrate large effect sizes for static risk only, dynamic risk only, and total risk plus protective scores on future offending. Sex and …

A Battle Of The Chatbots: An Exploratory Comparison Of Chatgpt, Gemini, Copilot, Claude, Perplexity And Huggingchat, Karen Okamoto

Publications and Research

This exploratory study compares the output of the free versions of six generative artificial intelligence (AI) chatbots—ChatGPT, Gemini, Copilot, Claude, Perplexity and HuggingChat. Five questions were submitted to all of the chatbots and examined according to the length of the response, tone of the response, and any additional features provided by the chatbots such as citations, web links, and helpful follow-up questions. This comparison found that Perplexity excelled at responding to all of the questions though others provided strong outputs as well, pointing to the possible importance of using multiple chatbot for answers and for continually examining different chatbots given …

The Towering Inferno: Art, Policy, And Legacy, Charles R. Jennings

Publications and Research

The Christian Regenhard Center for Emergency Response Studies, leveraging the expertise of its faculty, staff, Advisory Board and colleagues, has consistently programmed activities focused on high-rise fire safety. The upcoming 50^th anniversary of the film The Towering Inferno was an inspiration.

We decided this would be more lighthearted and less purely technical than many of our events. We wanted to consider both the film, and use it to reflect on the state of fire safety in tall buildings in New York City.

Of course it does not escape us that the topic of fire safety is a serious one, …

Understanding Violence In Juvenile Correctional Facilities: A National Study Of Victim-Offender Overlap In The United States, Tzu-Ying Lo, Yu-Hsuan Liu, Amy Adamczyk

Publications and Research

The phenomenon of victim-offender overlap within juvenile correctional facilities is an underexplored area in criminological research. This study examines the prevalence and correlates of victim-offender overlap using data from two collections of the National Survey of Youth in Custody conducted in 2008–2009 and 2012. Our findings reveal that the victim-offender overlap group constitutes a significant proportion of incarcerated youth. Multinomial logistic regression analysis indicates that institutional factors, such as correctional officer legitimacy, in-facility gang membership, fear of inmate assault, experience of filing complaints against staff, and time served, significantly differentiate victim-offenders from the three other groups: victims-only, offenders-only, and those …

Victim-Offender Overlap Among Incarcerated Youth In The United States: A Bivariate Probit Analysis Using National Data, Tzu-Ying Lo, Yu-Hsuan Liu, Amy Adamczyk

Publications and Research

For many crimes, people who are the perpetrators may also be the victims. While several studies have investigated the victim-offender overlap, very few have examined the relationship for incarcerated youth where institutional conditions can exacerbate the overlap. Drawing on ideas from routine activities theory, this study explores the victim-offender overlap among incarcerated American youth using data from the 2008–2009 National Survey of Youth in Custody (NSYC-1, N = 8,625) and the 2012 National Survey of Youth in Custody (NSYC-2, N = 8,125). Findings from a bivariate probit regression indicate that younger age, higher facility populations, negative perceptions of officer legitimacy, …

Research News, Grants, 2025, Volume 2, Soumyajit Majumdar

Grants (2015-)

Grants and contracts awarded during April - June 2025.

Research News, Grants, 2025, Volume 4, Soumyajit Majumdar

Grants (2015-)

Grants and contracts awarded during October - December 2025.

Osa-Diff: An Origin Sampling Based Adversarial Attack Using Diffusion Models, Shayan Jalalipour, Banafsheh Rekabdar

Computer Science Faculty Publications and Presentations

Diffusion models are becoming an increasingly popular emerging technology, however their use in adversarial attacks remains a scarcely explored topic. We show that diffusion models can be used to create end-to-end hidden adversarial perturbations with high rate of success, and propose a novel diffusion based adversarial attack that allows for substantially faster training time (through improved convergence on high quality images) and with substantially less computational overhead than typical diffusion model training

Polynomial-Time Constant-Approximation For Fair Sum-Of-Radii Clustering, Sina Nezhad, Sayan Bandyapadhyay, Tianzhi Chen

Computer Science Faculty Publications and Presentations

In a seminal work, Chierichetti et al. [20] introduced the (t,k)-fair clustering problem: Given a set of red points and a set of blue points in a metric space, a clustering is called fair if the number of red points in each cluster is at most t times and at least 1/t times the number of blue points in that cluster. The goal is to compute a fair clustering with at most k clusters that optimizes certain objective function. Considering this problem, they designed a polynomial-time O(1)- and O(t)-approximation for the k-center and the k-median objective, respectively. Recently, Carta et …

Retrieval-Augmented Feature Generation For Domain-Specific Classification, Xinhao Zhang, Jinghan Zhang, Fengran Mo, Dakshak Keerthi Chandra, Yu-Zhong Chen, Fei Xie, Kunpeng Liu

Computer Science Faculty Publications and Presentations

Feature generation can significantly enhance learning outcomes, particularly for tasks with limited data. An effective way to improve feature generation is to expand the current feature space using existing features and enriching the informational content. However, generating new, interpretable features usually requires domain-specific knowledge on top of the existing features. In this paper, we introduce a Retrieval-Augmented Feature Generation method, RAFG, to generate useful and explainable features specific to domain classification tasks. To increase the interpretability of the generated features, we conduct knowledge retrieval among the existing features in the domain to identify potential feature associations. These associations are expected …

Welcome From The Editor, Joshua E. Young

Iowa Journal of Communication

No abstract provided.

An Earnest Appeal, James M. Taylor

Heritage Material

No abstract provided.

Defeats Of The Devil: As Seen In The Life Of James M. Taylor, James M. Taylor

Heritage Material

No abstract provided.

Twice Sold, Twice Ransomed : Autobiography Of Mr. And Mrs. L. P. Ray, Mrs. Emma J. Ray

Heritage Material

No abstract provided.