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Retraction Notice: Reliability-Based Design Optimization Using Differential-Algebraic Equations, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF RETRACTION FOR: Abed, Saad Abbas; Ghassan, Mona; Latef, Shaimaa Qais; and Hassan, Hind S. (2025) ``Reliability-Based Design Optimization Using Differential-Algebraic Equations,'' Iraqi Journal for Computer Science and Mathematics: vol. 6, Iss. 3, Article 8. DOI: https://doi.org/10.52866/2788-7421.1280.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/8.

Beyond The Sayable: Wittgenstein, Theory Of Mind And Affective Simulation Of Llms, Haomiaomiao Wang, Lili Zhang, Tomás E. Ward

Women+ in Early Career Research Symposium

Wittgenstein’s distinction between what can be said and what can only be shown frames a limit of propositional language. Affect and aesthetic are not primarily matters of correct description but of how expressions function within shared forms of life. Large language models (LLMs), however, increasingly produce fluent language that resembles such understanding by reproducing the patterns through which people ordinarily talk about emotion and perspective.

This paper argues that apparent Theory of Mind (ToM) in LLMs is understood as competence in the publicly shared patterns of mental-state language, rather than as grounded understanding. Using abstract artworks, we show that LLMs …

Lidar Mirror Detection Model For Autonomous Robotics, Sofiia Sarana

Women+ in Early Career Research Symposium

LiDAR sensors are widely used in autonomous robots and vehicles for mapping, navigation, and obstacle avoidance. Because mapping is a foundational capability in nearly all robotic systems, it must be both accurate and reliable. However, LiDAR frequently fails in environments containing mirrors or highly reflective surfaces, where distorted returns corrupt maps and generate false obstacles. Current solutions typically rely on additional sensors and computationally expensive sensor-fusion pipelines, which is costly and difficult to scale for compact robots with limited onboard resources. This paper presents a machine-learning–based LiDAR mirror detection model that identifies reflective surfaces directly from LiDAR data, reducing the …

Comparative Time Series Forecasting Of Pedestrian Footfall In Dublin City Centre, Mercy Koech

Women+ in Early Career Research Symposium

Research on urban populations has turned out to be a significant field of study for a long duration.Forecasting pedestrian footfall is important for urban management,retail planning,crime analysis and evaluating the influence of public gatherings.With the rise of smart cities and the proliferation of sensor technologies there now exists a rich supply of data that offers unprecedented insight into the behaviour of pedestrain traffic.This study undertakes a comprehensive analysis of timeseries forecasting methods to predict pedestrian footfall trends in Dublin City Centre a key urban area with diverse spatial characteristics and high foot traffic variability.Using data collected via PYRO-BOX Counters sensors …

Multimodal Thermal And Mechanical Characterization Of Cryopreservation Effects In Biological Cells, Subhrajyoti Sourav Kumar Kundu

LSU Master's Theses

Cryopreservation is critical for long-term storage of cells, tissues, organs, and reproductive cells in medicine, biotechnology, and conservation. However, its success is limited by ice formation and cryoinjury, prompting extensive research into analytical tools for understanding and improving cryopreservation outcomes. We outline the principles of each technique and how they are used to detect key thermal and physical events such as ice nucleation, vitrification, devitrification, and cryoinjury. DSC enables quantitative thermal characterization including critical cooling/warming rates (ranging from 1-200°C/min for various systems) and glass transition temperatures. Cryomicroscopy provides direct real time visualization of ice crystal dynamics, distinguishing intracellular versus extracellular …

Using Facial Landmarks For Lip Motion Interpretation Applications, Kimi S. Wright

Theses and Dissertations

Facial motion, particularly lip movement, carries rich information about human speech that can be leveraged for a variety of computer vision and speech-processing tasks. Unlike other pixel-based methods, this work investigates the use of facial landmarks as a compact, privacy- preserving, and computationally efficient representation for lip-motion analysis. We evaluate landmark-based models across multiple tasks, including visual voice activity detection (VVAD), lip–audio synchroniza- tion, and visual speech recognition (VSR) for liveness detection. Using LRS3-VVAD1 and LRS22 datasets, we demonstrate that landmark-only models can achieve performance comparable to pixel-based systems for VVAD and synchronization, while significantly reducing parameter counts and inference …

When The Student Surpasses The Teacher: Better Generalization In Ai-Based Seismic Waveform Quality Assessment Using Knowledge Distillation, Ali Namin, F. Jalaeifar, A. Kottke, M. Zaker Esteghamati

Civil and Environmental Engineering Student Research

This paper presents a knowledge distillation (KD)-based approach to reduce computational expenses and improve the generalizability of deep learning-based models for quality assessment of seismic waveforms. Using two different waveform datasets, teacher models are distilled into lightweight student models from two families of time-series-based and image-based models. Models from both student families are trained on a development dataset and evaluated on the testing portion of the development dataset, as well as on an entirely different external testing dataset. Results indicate that KD can provide student models with substantially reduced size (5%-10% of the teacher model's size) and latency while preserving, …

Sensing Negative-Cone Rotational Diffusion Of Dipole-Like Emitters, Yuanxin Qiu, Kaizhi A. Nie, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Fluorescence anisotropy and single-molecule orientation-localization microscopy (SMOLM) are powerful techniques that quantify the rotational diffusion of dipole-like emitters, which is important for sensing molecular interactions and chemical environments at the nanoscale. Numerous theoretical and experimental studies have thoroughly characterized single-molecule rotations even when those rotations are much faster than the detector integration time. Here, we extend the theory of measuring rotational diffusion to situations where a single dipole rotates uniformly everywhere outside of an isotropic cone of a certain size, termed a negative cone. This scenario corresponds to negative fluorescence anisotropy 𝑟 and has been observed in emitters exhibiting strong …

Development Of Hypergraph Based Deep Neural Framework For Precise Cancer Subtyping And Meta Visualization, Pooja G Ms

Theses and Dissertations

Accurate Cancer Subtyping is a cornerstone of modern oncology essential for effective diagnosis and guiding personalized treatment. Histopathological Images (HIs) which capture the microscopic structure of tissues are widely used for cancer detection and subtyping. Even though deep learning has made significant advances, existing HI based subtyping methods often focus on specific cancer types, lacking a generic framework.

A unified framework that can classify multiple cancers with high specificity is desperately needed. In response to these limitations, this thesis proposes a robust multi-cancer, multi-class subtyping framework called DSHGNet (Depthwise Separable Hypergraph Convolutional Neural Network) which integrates Depthwise Separable Convolutional Neural …

Impediments To Transforming The Healthcare Delivery System: Shifting The Paradigm From Provider Centric To Patient Centric, Elizabeth A. Regan, Manasa Devi Chinta

Faculty Publications

Introduction: 

Stated aims for digital healthcare transformation frequently cite goals for better coordinated patient-centric systems. However, despite advances in medical science, digital technologies, health policies, and billions of dollars invested over the past 25 years, most healthcare providers are far from fully realizing the demonstrated benefits of today's digital technologies for improving patient care. Sharing information across healthcare systems remains challenging. Problems with fragmentation, quality, inequities, and rising costs of care delivery persist. A recent study of 1,026 U.S. hospital systems found that only 15.8 percent achieved a digital maturity level needed to provide digitally enabled healthcare services to better …

Inductive Transducers For Measuring Vibrations, S.F. Amirov, A.Kh. Sulliev, A.A. Shoimkulov

Chemical Technology, Control and Management

A new design of an induction transducer has been developed for measuring linear and torsional vibrations in different directions with high sensitivity by constructing an inertial element consisting of four mutually perpendicular sectors and making the masses of two adjacent sectors different from the masses of the other two adjacent sectors. By constructing an inertial element in the form of a sector with two mutually diametric magnetic cores and different masses, and placing it between the horizontal and vertical axes, a design of an induction transducer has been developed that highly sensitively measures linear and torsional vibrations in different directions, …

The Main Errors Of The Ultrasonic Sensor In Measuring Water Flow In Open Channels, Anvar Urolovich Djalilov

Chemical Technology, Control and Management

This article analyzes the use of ultrasonic sensors in measuring water flow and the main errors that may occur in this process. In the conducted scientific research, a time-pulse ultrasonic sensor was tested. The absolute, relative and repeatability errors of the sensor during water flow measurement were studied. The absolute error represents the largest difference between the value recorded by the sensor and the real value, affecting the overall accuracy of the measurement system. This error can vary depending on environmental factors, the design and operating principles of the sensor. During the experiment, the performance of this sensor was …

Synthesis Of An Adaptive Synergistic Fuzzy Discrete Controller For Nonlinear Systems, Isamidin Xakimovich Sidikov, Gulruxsor Murot Qizi Nashvandova, Feruzakhon Botirxon Qizi Sodiqova

Chemical Technology, Control and Management

The paper considers the issues of synthesizing an adaptive fuzzy synergetic controller with discrete time for nonstationary nonlinear dynamic objects. The proposed approach is based on the integrated use of synergetic control principles and fuzzy logic methods, which ensure the formation of a control law for nonlinear dynamic objects that provides asymptotic stability of the control system. Such a hybrid combination makes it possible to guarantee the asymptotic stability of the closed-loop system and to shape the required dynamic behavior of the object over a wide range of operating modes. In addition, this approach provides the ability to adapt to …

Pid Control For Lower Limb Exoskeletons: A Framework Evaluation, Javlonbek Rakhmatillaev, Vytautas Bučinskas

Chemical Technology, Control and Management

This research provides a detailed guideline for implementing and evaluating Proportional Integral Derivative (PID) control frameworks in lower limb rehabilitation exoskeleton robotics. It examines the role of control systems within rehabilitation robotics, outlines the principles of PID control, describes exoskeleton architecture, explores applications of PID control, reviews optimization strategies, presents experimental validations, and considers future developments in the field. The proposed control framework incorporates aspects of mechanical design, actuator and sensor selection, and PID-based control algorithms, thereby promoting safe, accurate, and individualized rehabilitation support. Recommendations and effective guidance for future work are also presented.

Review Of Modern Methods For Identification, Forecasting, And Intelligent Control Of Wastewater Biological Treatment Processes, Mirkhalil Agzamovich Ismailov, Boburbek Zokirjon O'G'Li Mannobjonov

Chemical Technology, Control and Management

This article presents a comprehensive review of contemporary approaches to the automation and intelligent control of wastewater biological treatment processes. Particular emphasis is placed on the digitalisation of wastewater treatment plants, ranging from the implementation of automated process control systems (APCS/SCADA-based solutions) to the application of predictive algorithms and the development of digital twins of bioreactors.

Special attention is devoted to mathematical models that underpin the control of bioprocesses. The evolution of the most widely used activated sludge models—ASM1, ASM2d, and ASM3—is examined, as these models describe key processes such as microbial community growth, nitrification, denitrification, and phosphorus removal. It …

Dynamic Deep Prompt Optimization For Defending Against Jailbreak Attacks On Llms, Doniyorkhon Obidov, Honggang Yu, Xiaolong Guo, Kaichen Yang

Michigan Tech Publications

Large Language Models (LLMs) demonstrate impressive capabilities across many applications but remain vulnerable to jailbreak attacks, which elicit harmful or unintended content. While model fine-tuning is an option for safety alignment, it is costly and prone to catastrophic forgetting. Prompt optimization has emerged as a promising alternative, yet existing prompt-based defenses typically rely on static modifications (e.g., fixed prefixes or suffixes) that cannot adapt to diverse and evolving attacks.

We propose Dynamic Deep Prompt Optimization (DDPO), the first jailbreak defense based on deep prompt optimization. DDPO uses the target LLM’s own intermediate layers as feature extractors to dynamically generate defensive …

Self-Aware Quantum-Inspired Routing Framework For 6g And Quantum Networks, Haitham M. Abdelghany, Mohamed M. Ashour

Mansoura Engineering Journal

This paper introduces a quantum-hybrid-aware routing framework that incorporates the concepts of quantum computing with meta-cognitive learning to improve adaptability, reliability, and awareness in dynamic quantum networks. The proposed system accommodates a new IoT, edge computing and 6G system, where routing schemes should be flexible and robust and have cross-topology functionality. Conventional methods of quantum reinforcement learning can be characterized by a trade-off between exploration and decision stability. To cope with this, the proposed self-aware hybrid architecture is a combination of quantum-enhanced learning and a meta-cognitive awareness layer to allow autonomous agents to monitor performance and adjust routing strategies on …

Comment On The Draft Environmental Impact Statement For New Operations For Lake Powell And Lake Mead Post-2026, Bryan Williams, Caitlyn Andrus, Brittany Fager, Matthew Fugal, Parker Hansen, Ashley Jones, Shaun Joseph, Ashley Mcallister, Braden Wilding, David Rosenberg

Civil and Environmental Engineering Student Research

We appreciate the Bureau of Reclamation’s extensive effort in preparing the Post-2026 Draft Environmental Impact Statement (Draft EIS) for operational guidelines for Lake Powell, Lake Mead, and the Colorado River Basin. This commentary will address positives, questions, and concerns from the Draft EIS. We also share recommendations for consideration in the Final EIS.

Design And Evaluation Of A Collaborative Xr Framework With Abstract Building Blocks For Manufacturing System Prototyping, Shaun Macdonald, Bixun Chen, Yuanjie Xia, Rami Ghannam

School of Engineering Technology Faculty Publications

Manufacturing systems are complex installations designed and developed by stakeholders with differing expertise. However, system design primarily features traditional methods, long lead times, and siloed environments, which obstruct comprehension, communication, or collaboration. Prior research has used extended reality (XR) to prototype and visualise specific manufacturing applications; however, flexible system modelling remains complex. To address these issues and lay the foundation for future-facing manufacturing design as part of Industry 4.0, we introduce ARTIFY—a prototype XR framework for conceptual system prototyping. It features abstract building blocks that can be semantically reconfigured to support early-stage modelling of varied manufacturing systems in immersive environments. …

Hybrid Cnn–Gru-Based Demand–Supply Forecasting To Enhance Sustainability In Renewable-Integrated Smart Grids, Süleyman Emre Eyimaya, Necmi Altin

Faculty Publications

The rapid integration of renewable energy sources in smart grids has introduced significant uncertainty in both power generation and consumption patterns, posing challenges to environmental, economic, and operational sustainability. Accurate short-term forecasting of energy demand and supply is essential for achieving optimal scheduling, grid stability, and resilient operation in renewable-integrated power systems. This study proposes a hybrid deep learning framework combining Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU) for intelligent joint demand–supply forecasting in smart grids. The model was developed and implemented in MATLAB using real-world datasets comprising electricity consumption, photovoltaic (PV) generation, temperature, and irradiance variables. Comparative …

Co-Electrospinning Polyacrylonitrile (Pan) / Polymer Of Intrinsic Microporosity-1 (Pim-1) For Electrochemical-Based Sensor For Pyridine Detection And Absorption, Samar A. Salim

Nanotechnology Research Centre

The electrospinning of the polymer of intrinsic microporosity-1 (PIM-1) poses challenges due to its limited solubility and tendency to form bead-like structures at high concentrations. This work details the synthesis and analysis of electrospun composite fibers made from polyacrylonitrile (PAN) and PIM-1 for electrochemical applications. The data analysis confirmed the successful incorporation of PIM-1 into the PAN matrix. The fiber characteristics were significantly influenced by PIM-1 loading (1–10%), resulting in fiber diameters ranging from 0.8 to 1.7 μm. A 10% concentration of PIM-1 results in the formation of macropores with diameters ranging from 0.5 to 1.7 μm. Optical analysis using …

Development Of A Framework For Identifying Asphalt Pavement Cracking Distresses Using Machine Learning, Dingxin Cheng

Mineta Transportation Institute

Asphalt pavement cracking is one of the most critical distresses affecting pavement performance and service life. When pavement deteriorates, it can lead to safety hazards, higher vehicle maintenance costs, and expensive repairs for cities and states—making early detection essential for everyone who relies on the roadway system. To address this challenge, the research team developed a prototype cracking identification system that integrates a customized machine learning model with computer vision algorithms. High-resolution images collected from drones or ground-based cameras are processed within the system to automatically detect and classify major cracking types. The core of the framework utilizes the You …

An Adaptive Immersive Training Framework For Miner Self-Escape Readiness In Underground Mining Emergencies, Muhammad Azeem Raza, Samuel Frimpong, Saima Ghazal

Mining Engineering Faculty Research & Creative Works

Underground mining environments are complex and hazardous operations where emergencies continue to happen. Underground mine emergencies require rapid, high-stakes decision-making under conditions of uncertainty, stress, and limited visibility. Conventional mine emergency training largely relies on instruction-based approaches which provide insufficient exposure to the cognitive and behavioral demands of real underground emergency situations. There has been an identified need to train miners for knowledge, skills, abilities, and other characteristics (KSAOs). This study proposes an Adaptive Immersive Training Framework (AITF), a cognitively grounded architecture that integrates cognitive task analysis (CTA), KSAOs, and situational awareness assessment for miner self-escape training and readiness. The …

The Impact Of Human Myoblasts On Macrophage Polarization In A Coculture Model, Elisabeth Ann Stodola

Biomedical Engineering

Peripheral Artery Disease (PAD) is characterized by the buildup of atherosclerotic plaque in the lower extremities that occludes blood flow, and affects over 200 million people worldwide. Without effective treatment, PAD can lead to claudication, ischemia, ulcers, and gangrene. PAD causes more amputations in the United States than any other condition, and for severe cases that require revascularization, procedures benefit fewer than 50% of patients. This demonstrates a clear need for alternative therapies. Potential therapies for PAD target expansion of collateral blood vessels around the area of occlusion – a process called arteriogenesis to compensate for loss of blood flow …

Failure Of Infrastructure Systems: A Multilevel Network Analysis Of Decision-Making And Influential Behavioral Constructs, Tamima Elbashbishy, Radwa Eissa, Islam H. El-Adaway, Jeffrey S. Russell

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

High-profile failures of infrastructure systems are often attributed to design flaws. However, these incidents can also stem from a broader set of interconnected decisions made by stakeholders involved in the planning, management, and operation of these systems. While ethical guidelines and professional codes are designed to prevent such failures, cognitive biases may undermine adherence. Previous research efforts, primarily focused on ethical violations using case studies, have overlooked how behavioral ethics constructs and professional conduct could drive these breaches. This paper addresses this knowledge gap by (1) conducting an analysis of three system failure cases at the micro, meso, and macro …

Design And Validation Of A Wearable Respiratory Protection System For Wildland Firefighters, Oliver Pilon

Master's Theses

Wildland and Wildland–Urban Interface firefighters are routinely exposed to hazardous smoke with fine particulate matter, carbon monoxide, volatile organic compounds, and other toxic combustion products. Existing protective gear has significant limitations and shortcomings for these conditions. Respirators with tight-fitting facepieces make it difficult to breathe and speak. On the other hand, self-contained breathing apparatuses are too heavy, have a limited duration of use, and do not work well with long wildland fire scenes, while smaller protective equipment like N-95’s and gaiters provide very little protection. These constraints contribute to low adoption rates and prolonged occupational exposure.

This thesis presents the …

On Signifiable Computability: Part Iii: A Note On Unnameable Functions On Natural Numbers, Vladimir A. Kulyukin

Computer Science Faculty and Staff Publications

A writing system 𝔚 on an alphabet 𝒜 is a tuple (ℜ,𝔐), where ℜ is a finite set of text formation rules and 𝔐 is a finite rule application mechanism that generates texts on 𝒜. A natural writing system forms natural language texts on an alphabet such as Sanskrit on Devanagari. An artificial writing system generates formal language texts on an alphabet such as Lisp on Unicode. Let ℕ ={0,1,2,…} be the set of natural numbers. A function on natural numbers 𝑓 :ℕ^𝑘 ↦ ℕ, 0 < 𝑘 ∈ ℕ, is nameable by a writing system on an alphabet if, and only if, the system can generate a text on the alphabet that names f and no other function. We show that there exist functions on natural numbers unnameable in principle in that they cannot be named by any writing system on any alphabet. Our results imply the following computability-theoretic hierarchy of functions on natural numbers: computable ⊊ partially computable ⊊ nameable ⊊ 𝔉, where 𝔉 is the set of functions on ℕ.

Portable Ice Cube Maker, Ayden Ziegler, Emiliano Hansen, Wyatt Engdahl, Dane Hansen

Mechanical Engineering

This Final Design Report outlines the senior design project undertaken by a team of mechanical engineering students at California Polytechnic State University, San Luis Obispo, for the development of a portable backpacking ice cube maker. The project aims to design, build, and test a lightweight, compact device that produces ice cubes for backpackers in remote outdoor environments. The goal is to create a functional prototype that is durable, user-friendly, and suitable for backcountry use. This document details background research, project objectives, and project plan, and current design status.

Pollinators Exhibit For Paso Robles Children’S Museum, Isabelle Moll, Matthew Moore, Joseph Hovanesian, Evan Stock, Matthew Wiecking

Mechanical Engineering

This report documents the design and development of an interactive pollination exhibit created for the Paso Robles Children’s Museum as part of the Mechanical Engineering Senior Project program. The goal of the project was to design a durable, safe, and engaging educational exhibit that introduces children to the role of pollinators in local ecosystems and agriculture through hands-on play. The final design features a triple-track system with rolling bee elements and a central pollen ball pathway that demonstrates how pollinators move between flowers and return resources to the hive. The exhibit incorporates visual feedback and locally inspired design elements to …

3d Bouldering Project, Joseph Robison

Liberal Arts and Engineering Studies

Many indoor rock climbers struggle to make the transition from indoor to outdoor bouldering due to differences in route visualization. This project applies photogrammetry to create 3D scans of outdoor holds with accurate measurements and textures to improve climber visualization. The measurements were then mapped onto a Tension Board 1 simulation. Six climbers were divided into control and simulation groups to test effectiveness. Results showed that confidence and perception of outdoor ability were increased in the simulation group. Performance outcomes were approximately equal between both groups. These findings suggest that visualization tools can enhance mental preparation for outdoor climbing.