Engineering Commons^™

Symmetry And Scale: The Precise Engineering Of Chitosan-Based Polyhedral For The Delivery Of Therapeutic Materials At The Nanoscale, Ahmed. J. Jasim, Noor Malik Saadoon

AUIQ Technical Engineering Science

Preparation of chitosan-based drug delivery carriers requires converting linear polysaccharide chains into individual 3D objects. By building on the natural structural properties of chitin-based polymers, in addition to control the geometry of organically derived raw material from feedstock to submicron polyhedral or spherical dimensions. This geometric change is governed by a surface area-to-volume ratio that maximizes the exposure of the therapeutic payload to the external environment. The approach centres on the development of such carriers using ion-complexation and emulsification methodologies, which involve electrostatic cross-linking of ion-binding pairs to define an impenetrable boundary separating a liquid from a solid phase. Critical …

Availability Model To Evaluate Ai Data Centers’ Role In Grid Stability, Troy Mcsimov, Trevor S. Kunz, Jeffrey Billo

SMU Data Science Review

The United States has made it clear; it is imperative that the US wins the global AI race. This paper focuses on one of the most challenging puzzle pieces surfaced at the POWER Data Center conference (San Antonio, Sept. 30.); for Electric Reliability Council of Texas (ERCOT) the limiting factor is not generation alone but the need to balance generation and load to preserve grid reliability.

The regulatory landscape fundamentally changed with the passage of Texas Senate Bill 6 in June 2025, which mandates new large loads must "contribute to the recovery of the interconnecting electric utility’s costs" (Texas Legislature, …

Reducing Range Anxiety Through Predictive Modeling Of Ev Battery Degradation, Caleb Thornsbury, Christian Castro, Bivin Sadler

SMU Data Science Review

Electric Vehicles (EV) range anxiety remains one of the top barriers for broader adoption. Range anxiety can be attributed to battery pack age and degradation over time. This paper plans to explore how to address this issue by creating a machine learning model that can predict degradation based on usage, temperature, battery chemistry, charging habits and exploring whether other factors tie into range degradation. This research will be using real world charging data along with lab tested chemistry data to build a model that can be chemistry specific for degradation. This paper will help perspective used-EV buyers learn about battery …

Redesigning Online Graduate Orientation To Foster Academic Resilience And Prevent Underperformance, Stella Michael-Makri, David E. Rodriguez

Journal of Academic Underperformance

Graduate students in fully online programs often begin their academic journey without adequate preparation for the emotional, structural, and cultural challenges of graduate-level work. For students who are first-generation, racially marginalized, international, or returning to education after time away, this lack of scaffolding can lead to early disengagement, underperformance, or attrition. Orientation, often treated as a checklist of logistical tasks, represents a missed opportunity for meaningful academic intervention. This manuscript proposes a five-module conceptual model for online graduate orientation designed to proactively support online graduate students in the domains of emotional regulation and academic identity, time management and executive functioning, …

Corrigendum Notice: Motion Fusion: A Robust Ensemble Learning Framework For Accurate Sensor-Based Human Activity Recognition, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF CORRIGENDUM FOR: Almulla, Hussein K.; Mohammed, Hussam J.; Al-Waisy, Alaa S.; Al-Fahdawi, Shumoos; Had, Ahmed Adnan; and AL-Attar, Bourair (2025) ``MotionFusion: A Robust Ensemble Learning Framework for Accurate Sensor-Based Human Activity Recognition,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 3, Article 14.
DOI: https://doi.org/10.52866/2788-7421.1289.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/14.
Reason for Corrigendum: In the published version of the above article, a number of typographical and formatting errors were identified. These corrections do not affect the study design, results, or conclusions, and are provided below to ensure accuracy and consistency. 1) Feature subset sizes …

Corrigendum Notice: Machine Learning Algorithms To Detect Cyber-Attack In The Internet Of Things Platform, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF CORRIGENDUM FOR: Al-anni, Maad Kamal; Almuttairi, Rafah M.; Al-Hamadani, Ammar A.; Zidan, Khamis A.; Alsaadi, Husam Ibrahiem Husain; and Al-Sultany, Ghaidaa A (2025) ``Machine Learning Algorithms to Detect Cyber-Attack in the Internet of Things Platform,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 2, Article 26.
DOI: https://doi.org/10.52866/2788-7421.1268.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss2/26.
Reason for Corrigendum: In the published version of this article, the authors and publisher wish to correct the following items:

1. DOI correction: The DOI printed in the article PDF as ``10.52866/ijcsm.0000'' is incorrect and should be ``10.52866/2788-7421.1268.''
2. Dataset split correction: …

Corrigendum Notice: Finding General Mathematical Formulas For Extraction The Minimal Path Sets Of Complex Parallel-Series Networks, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF CORRIGENDUM FOR: Lafta, Mariem Hassan and Hassan, Zahir Abdul Haddi (2025) ``Finding General Mathematical Formulas for Extraction the Minimal Path Sets of Complex Parallel-Series Networks,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 1, Article 11.
DOI: https://doi.org/10.52866/2788-7421.1237.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss1/11.
Reason for Corrigendum: In the published article, the definition of minimal path set is stated incorrectly. The text defines a minimal path set as ``a set of components whose failure leads to failure of the whole CPSN,'' which corresponds to a minimal cut set, not a minimal path set. Correction: A …

Corrigendum Notice: Federated Learning-Driven Iot And Edge Cloud Networks For Smart Wheelchair Applications, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF CORRIGENDUM FOR: Mohammed, Mazin Abed; Abd Ghani, Mohd Khanapi; Lakhan, Abdullah; AL-Attar, Bourair; and Khaled, Waleed (2025) ``Federated Learning-Driven IoT and Edge Cloud Networks for Smart Wheelchair Applications,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 1, Article 9.
DOI: https://doi.org/10.52866/2788-7421.1241.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss1/9.
Reason for Corrigendum: In the published version of this article, the authors and publisher wish to correct the following items:

1. Table 5 (Task Status entry) — data cell error
In Table 5, the entry for Device ID 3, Iteration 5 contains an incorrect/misaligned value in the Task Status …

Corrigendum Notice: A New Approach For Multiprocessor System-On-Chip Application Scheduling In Hybrid Flow Shop, Iraqi Journal For Computer Science And Mathematics

Iraqi Journal for Computer Science and Mathematics

NOTICE OF CORRIGENDUM FOR: Khraibet, Tahani Jabbar; Kalaf, Bayda Atiya; and Jasim, Ahmed Abbas (2025) ``A New Approach for Multiprocessor System-On-Chip Application Scheduling in Hybrid Flow Shop,'' Iraqi Journal for Computer Science and Mathematics: Vol. 6: Iss. 3, Article 45.
DOI: https://doi.org/10.52866/2788-7421.1318.
Available at: https://ijcsm.researchcommons.org/ijcsm/vol6/iss3/45.
Reason for Corrigendum: This note corrects (i) author-affiliation metadata, (ii) minor textual duplications/typographical errors, (iii) a naming inconsistency of the proposed algorithm, and (iv) duplicated sentences in the dataset description. These corrections do not change the experimental results or conclusions; they improve clarity and metadata accuracy. 1) Correction to author affiliation metadata …

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.

Enhancing Engineering Education For Students With Intellectual Disabilities Through Universal Design For Learning, Bree Jimenez, Ginevra Courtade

Journal of Science Education for Students with Disabilities

This study explores the impact of a Universal Design for Learning (UDL) aligned engineering curriculum on teacher confidence and student engagement in special education classrooms, specifically focusing on students with intellectual and developmental disabilities (IDD). The research investigates how the curriculum, combined with targeted professional development (PD), supports teachers in delivering high-quality engineering instruction. Through a mixed methods approach, including surveys, interviews, focus groups, and classroom observations, data revealed significant improvements in teacher self-efficacy, particularly in areas such as scaffolding, differentiation, and accessibility. Teachers reported increased confidence in their ability to implement engineering lessons and foster engineering mindsets in their …

Research Of Logic Elements Based On Complementary Bipolar Transistors, Nodira Batirdjanovna Alimova, Nilufar Baxtiyorovna Gulyamova

Chemical Technology, Control and Management

Important parameters for any type of inverter – a NOT logic gate – are the power consumption during switching and the supply voltage. The proposed connection of complementary (two different types) bipolar transistors reduces the current consumption and supply voltage by simultaneously using the cutoff and saturation modes of the bipolar transistors. It has been theoretically and experimentally established that an inverter using complementary bipolar transistors operates at low supply voltages, approximately 0.7 V. Power consumption is virtually independent of the inverter's static state. A method for calculating the transfer characteristic of an inverter using complementary bipolar transistors is developed, …

Algorithms Of Stable Adaptive Observation Of A Multidimensional Undefinite Object, Tursunova Sadoqat Abdusalom Qizi

Chemical Technology, Control and Management

This article presents an algorithm for simultaneously estimating the parameters and state coordinates of a multidimensional control object when some of its state variables are not directly measured. The inability to measure all state variables (coordinates) of an object is a well-known drawback of identification schemes. Such conditions require the construction of adaptive state observers. This work demonstrates that when identifying the parameters of a mathematical model for an uncertain multidimensional object, the asymptotic stability of the object and the convergence of its parameters to the model parameters are ensured, provided the input vector is sufficiently informative. The construction of …

Physical And Chemical Study Of Interaction In The Urea–Valine System For The Creation Of Modified Liquid Nitrogen Fertilizers, Suvonkul Erkhanovich Nurmonov, Saydullo Khamidovich Azimov

Chemical Technology, Control and Management

This study reports the results of a comprehensive physicochemical investigation of the urea–L-valine binary system, conducted to validate its potential as a modified base for liquid nitrogen fertilizers.

By utilizing the methods of isomolar series, visual-polythermal analysis, X-ray phase (XRD) and single-crystal X-ray diffraction (SC-XRD), synchronous thermal analysis (TGA/DTA), and FT-IR spectroscopy, it was determined that the interaction between components in both aqueous solutions and the solid phase results in the formation of molecular associates stabilized by hydrogen bonds, without the formation of new stoichiometric compounds.

The concentration and temperature limits of the system's stability were defined, revealing a reduction …

Analysis Of The Carbonization Process Of Ammoniated Brine In Ammonia-Soda Production, Nadirbek Rustambekovich Yusupbekov, Djalolitdin Paxritdinovich Mukhitdinov, Fotima Faxritdinovna Iskhakova

Chemical Technology, Control and Management

The work provides an analytical review of the current state of modeling and controlling the carbonization process of ammoniated brine. It analyzes modern methods of mathematical, simulation, and intelligent modeling of heat and mass transfer, hydrodynamics, carbonation kinetics, and crystallization. The paper considers the potential of using digital twins, neural network models, fuzzy logic devices, and hybrid models to improve forecasting accuracy and the adaptability of process solutions. Modern carbonation process control strategies are also considered. A detailed analysis is provided of predictive control (MPC), neuro-fuzzy controllers, decentralized and multivariate control systems that ensure stable column operation under disturbances, optimize …

Analytical Method For Investigating Nonlinear Magnetic Circuits Of Measuring Transducers With A Standard Parameter Distribution Structure, Javhar Sulton O'G'Li Fayzullayev

Chemical Technology, Control and Management

The article proposes a new analytical method for investigating magnetic circuits with distributed parameters and nonlinear magnetic coupling. The method is based on introducing into the system of nonlinear differential equations of such circuits the condition that the second derivative of the magnetic flux with respect to the circuit length is equal to zero, as well as on assuming that one of the geometric parameters of the studied magnetic circuit – the value of the air gap between ferromagnetic cores, their thickness, width, or the linear value of the number of turns of the distributed excitation winding – is a …

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.

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 …

Adaptive-Robust Control Of Dynamic Systems Using Generalized Predictive Methods, Shuxrat Tulyaganov

Chemical Technology, Control and Management

This paper considers an approach to adaptive-robust control of dynamic systems using generalized anticipation, where the object is described by a locally linearized model. Known self-tuning algorithms show insufficient stability to inaccurate selection of delay or model order. A generalized predictive control approach is suggested, with simulation outcomes showing superiority over traditional methods like generalized minimum variance control and pole assignment.This sliding horizon algorithm is based on predicting future system output signals several steps ahead, based on assumptions about subsequent control actions. One effective assumption is the presence of a “control horizon,” beyond which control signal increments are assumed to …

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 …

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 …

The Effect Of Polyester And Lycra Loop Lengths On The Recovery Properties Of Single Jersey Knitted Fabrics, Abdelmonem Fouda, Moaaz Eldeeb

Mansoura Engineering Journal

Knitted fabrics are well known for their comfort due to their ability to elongate in the wale direction at the expense of the course direction, and vice versa. However, they lack dimensional stability, especially single jersey knitted fabrics. To address this issue, Lycra threads have recently been incorporated into their production to improve shape recovery after stress is released. Despite this enhancement, the fabric does not fully return to its original shape, highlighting the need to measure this phenomenon accurately. This study aims to firstly: simulate the production of a frame designed to measure the recovery and elongation of knitted …

Sustainable Aviation Fuel (Saf) From Used Cooking Oil (Uco) In Egypt: Opportunities And Challenges., Lamiaa Abdallah

Mansoura Engineering Journal

Global aviation sector contributes nearly 2.5% of global CO2 emissions. Aviation is hard-to-decarbonize sector due to the high energy densities required for aircraft. Commercial aviation is fueled by kerosene-based jet fuel. Alternatives for this carbonbased fuel include electric batteries, hydrogen fuel, and SAF. Electric batteries have very low energy densities. Hydrogen would require a complete change of the aviation system, including fuel & airport infrastructure. SAF is the only viable option in the short to medium term. SAF is produced from sustainable feed-stocks (like agricultural oils), with no embodied carbon. Existing airplanes can use traditional fuel blended with up to …

Elevating The Underrepresented And Marginalized Using Experiences In Stem (Lumens): A Stem Diversity And Inclusion Initiative, Robert Cobb Jr, Paula E. Faulkner, Deiadra Modlin, Obinna Chiekezi, Victoria Cobbold, Madison Beaudoin

Journal of Research Initiatives

The study offered a 5-week summer immersion program to address the shortage of students from underrepresented populations enrolling in degree programs and seeking careers in science, technology, engineering, and mathematics (STEM). The study also addressed the importance of offering summer immersion programs to close the achievement gap. A quantitative descriptive design was used to gather data from participants related to STEM lessons during the program. Gender, grade level, and race served as the demographic variables. The study included 21 secondary students in grades 9–12. Pre- and post-tests assessed participants' knowledge gain regarding STEM lessons. Data analyzed with SPSS version 29 …

Globalizing The Engineering Job Market: Optimizing Engineering Career Expos To Serve International Students, Hailey A. Hesseltine

Journal of Global Education and Research

As the United States hosts approximately one million international students annually, it becomes imperative that on-campus resources are tailored to meet the needs of this diverse student population. One on-campus resource that is crucial to student success is career services, especially considering the aspirations of many international students to secure employment post-graduation. To address this, this study aimed to understand the satisfaction levels of international engineering students with an engineering career expo in Hawaiʻi. Utilizing a combination of surveys and interviews using a neo-racism framework, international students shared their experiences from the career expo through discussion and assessment. Information given …

Impact Of Femalized Kinesthetic Learning Model On African American Middle School Girls’ Career Interest, Mercy F. Fash, Andrea Ofori-Boadu

Journal of Global Education and Research

Engaging African American middle school girls in out-of-school-time (OST) Architecture, Engineering, and Construction (AEC) programs can boost interest in male-dominated AEC careers. This study adopts Lent’s Social Cognitive Career Theory to evaluate the impact of an OST feminized AEC kinesthetic learning model (fAEC-KLM) on the career interests of this demographic. Through a qualitative research approach, fourteen (14) African American middle school girls from Guilford County, NC, completed pre- and post-interviews on how fAEC-KLM interactions influenced their AEC career interests. Inductive thematic analysis was carried out on transcribed interviews. Results show that effective components, such as lectures on AEC, bridge construction …

N-Dqn: Neutrosophic Deep Q-Network For Uncertainty-Aware Forecasting And Decision Optimization, Rania Lutfi

Neutrosophic Systems with Applications

Uncertainty remains a critical challenge in dynamic spatiotemporal forecasting. This study proposes the Neutrosophic Deep Q-Network (N-DQN), a framework that integrates neutrosophic logic with deep reinforcement learning to enhance decision optimization under uncertainty. Features are modeled through truth, indeterminacy, and falsity membership functions, enabling robust handling of ambiguous data. The framework incorporates attention-guided preprocessing and horizon-aware optimization to adapt predictions across short- and long-term intervals. Experiments on benchmark traffic datasets (METR-LA and PEMS-BAY) demonstrate improved forecasting accuracy and reduced error rates compared with established baselines. The results highlight the scalability and resilience of N-DQN, positioning it as a promising approach …

Optimized Deep Learning Framework With H2o For Lung Cancer Prediction, Walaa Hassan Ibrahim, Mohamed S. Saraya, Sally M. Elghamrawy, Ali I. Eldesouky

Mansoura Engineering Journal

The automatic diagnosis of lung cancer using chest X-ray (CXR) images has significantly advanced with progress in computing, machine learning, and deep learning. However, detecting lesions and nodules remains challenging due to CXR limitations. Early lung cancer detection is critical for successful treatment, but current AI algorithms often rely on large annotated datasets, which are not always available. To address this, a novel multi-classification deep learning framework is proposed that combines CXR and CT images. This approach leverages the detailed feature detection capabilities of CT scans alongside the complementary views from CXRs, improving early-stage lung cancer detection and classification precision. …