Biomedical Engineering and Bioengineering Commons^™

Empirical Research Of A Greenhouse Monitoring And Controlling System Using Zigbee Protocol, Mohammed Hijazeh, Salah Hagahmoodi

Al-Esraa University College Journal for Engineering Sciences

Greenhouses are of great importance in the agricultural field as they provide the appropriate and important environment for the growth and production of various plants regardless of the surrounding environmental conditions. Monitoring and controlling these houses are considered necessary and important in order to provide the required environment and obtain the best production. Therefore, the aim of this project is to study the monitoring and control of these houses using wireless sensor networks, which are considered modern and simple methods due to the accuracy of work and little effort they provide, and thus better production. The study will be for …

Designing An Efficient Deduplication Algorithm For Audio Files In Cloud Storage, Ammar Zakzouk, Alaa Al Sebae, Hasan Hasan

Al-Esraa University College Journal for Engineering Sciences

Data duplication is a significant challenge in large-scale data storage systems, as it consumes storage space and impacts data organization, management, and processing. An optimal storage system effectively utilizes available storage space. To solve this problem, hash algorithms are employed to generate hash keys for files. Matching files have the same hash key. However, the hash key for two different files in the data may match, and this is what we refer to as a collision. The collision issue is related to the length of the hash key. As the length of the hash key increases, the probability of a …

The Future Of Al-Driven Cybersecurity For Advanced Iot, Estqlal Hammad Dhahi, Sanaa Hammad Dhahi, Ohood Fadil Alwan

Al-Esraa University College Journal for Engineering Sciences

Internet of Things technologies experience rapid advancement because of 5G networks and upcoming 6G technologies, which resulted in transformational changes to security dynamics. This study examines the functionality of artificial intelligence through platforms developed to secure Internet of Things systems. The demand for improved security capabilities has become essential because IoT devices generate new assault channels, and their market penetration speed is escalating. Machine learning algorithms, together with deep learning and natural language processing methods, are investigated in this paper for enhancing the security protocols of IoT systems through studies found in academic literature. The paper explores upcoming developments and …

Foundations Of Artificial Intelligence In Healthcare Diagnostics: A Systematic Survey, Raghad Tariq Al-Hassani

Al-Esraa University College Journal for Engineering Sciences

Artificial Intelligence (AI) is becoming the cornerstone of the future of healthcare diagnostics, that has to ability to change the healthcare diagnostic landscape in terms of diagnostic accuracy, speed, and availability. This systematic review investigates the basic methods, tools, applications, and challenges involved in the integration of AI in diagnostic medicine. It emphasizes the using of machine learning models, deep learning networks (e.g., CNNs), NLP for clinical documentation, and smart computing infrastructures, such as edge device and IoMT. They are making possible real-time, data-driven decision making that is already at human-expert-level performance or, in some cases, even better (in the …

Secure Gif Files Based On Zuc Stream Cipher And Present Algorithm, Suhad Fakhri Hussein

Al-Esraa University College Journal for Engineering Sciences

Some important security needs include authentication, confidentiality, integrity, non-repudiation, and user privacy. Many security systems include these required protections for information transmission. The encryption process is one of the most important security measures. Many secure encryption algorithms are based on different keys and key lengths to ensure a high degree of security. GIF file format is common file format that is used in several application, securing these files through transmission is imperative. In this paper, an efficient method for encryption GIF file is proposed based on using modified present algorithm, modified ZUC stream cipher, and an efficient method for key …

Advanced Strategies And Solutions Towards More Secure And Effective Two-Factor Authentication In Networking, Zahraa Sameer Jawad

Al-Esraa University College Journal for Engineering Sciences

With the rapid increase in cybersecurity threats targeting network systems, traditional two-factor authentication (2FA) methods are insufficient to address advanced attacks. Vulnerabilities such as phishing, SIM-swapping, and social engineering exploit the limitations of SMS-based and email-based 2FA. This paper examines advanced strategies and solutions for securing networked environments through robust 2FA mechanisms, focusing on approaches like elliptic curve cryptography (ECC), digital certificates, and biometric verification. This article offers a comparative review of various strategies about their effectiveness in enhancing security, while also highlighting their capacity to optimize user-friendliness and adaptability to emerging threats. Research findings promote an effective countermeasure strategy …

Advancements In Ultrasound Technology And Iot Security: A Physics-Based Approach To Enhanced Imaging With Lightweight Encryption Algorithms, Noor Fawzi Shafiq

Al-Esraa University College Journal for Engineering Sciences

The rapid advancements in ultrasound technology, coupled with the growing significance of IoT security, present a unique opportunity to enhance imaging systems while ensuring data integrity. This study explores the integration of physics-based principles in ultrasound imaging, focusing on how lightweight encryption algorithms can secure data transmitted from IoT devices.Ultrasound technology has evolved significantly, benefiting from improved imaging techniques and the incorporation of IoT devices. As these devices proliferate across various applications, including healthcare and industrial monitoring, the need for secure data transmission becomes paramount. This paper proposes a framework that combines advanced ultrasound imaging with robust lightweight encryption methods …

Artificial Intelligence Approaches To Mitigating Network Congestion In Iot Systems, Aysar Hadi Oleiwi

Al-Esraa University College Journal for Engineering Sciences

The unprecedented explosion of Internet of Things (IOT) devices has elevated the requirements of the network infrastructures to unprecedented levels, causing severe congestion problems, especially in applications which demand low latency, high throughput, and real-time feedback. Static routing protocols, AQM, and TCP variants are some of the traditional mechanisms for congestion control that are unable to perform efficiently in dynamic and diverse IoT environments as they are reactive-based and inflexible. To this end, in this paper, we explore the promising ability of Artificial Intelligence (AI) methods such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), and their combination …

Groundwater Quality Analyses For Irrigation Purposes In Salah Al-Din, Iraq: A Review, Noor A. Radhi, Dawood E. Sachit, Abdul-Sahib T. Al-Madhhachi

Al-Esraa University College Journal for Engineering Sciences

The focus of this study is the effect of the physical and chemical characteristics of groundwaters on plants and agricultural crops, following the last studies on this matter. The results underscore the necessity for groundwater treatment before its utilization in irrigation for sustainable agricultural farming. It is also possible to identify which crop type can be grown in well-watered land, according to the characteristics of irrigation water and the yield of each crop. The study also introduces some ideas about irrigation water quality parameters such as Electrical conductivity (EC), Total Dissolved Solids (TDS), pH, Chloride (Cl^–), Sodium (Na …

Examining Iot-Enhanced For Current Developments In Face Image Authentication (Fia) Methods And Their Drawbacks, Marwa Jamal Hadi, Emaan Ouudha Oraby

Al-Esraa University College Journal for Engineering Sciences

The quick development of IoT and facial image manipulation (FIM) algorithms, as well as the growth of their user-friendly applications, highlight the pressing need for manipulation detection methods. These techniques need to demonstrate how face photos have been altered and validate their legitimacy. The scientific community has recently taken notice of the phrase “DeepFakes” and methods for detecting them. Take note of the latest methods for identifying watermark-based face image modification as well. The important thing to remember is that every one of these methods has its own set of drawbacks. This study provides a brief introduction to face image …

Computational Investigation Of The Role Of 3d Genome Architecture In The Lifecycle Of The Malaria Parasite, Srish Maulik

College of Engineering Summer Undergraduate Research Program

Malaria, a mosquito-borne infectious disease caused by the Plasmodium parasite, is responsible for more than a half a million deaths per year, the vast majority of which occur in central Africa. The parasite undergoes an incredibly complex cell molecular transformation as it transitions from living in mosquitoes to living in humans with different sets of genes being activated or silenced in order to evade the immune system of the host. Understanding how its genome guides this transition is critical for developing adequate treatments. In this project, we aim to develop a computational framework for investigating the role of the three …

Fourier-Feature Mlp Toolkit For Gpu-Accelerated Cardiac-Mri 4dcmr Strain Analysis, Aarnav T. Sabale, Marco A. Prado, Craig J. Goergen

Discovery Undergraduate Interdisciplinary Research Internship

This paper explores the embedding of a Fourier-Feature—enhanced multiplayer perceptron(MLP-FEE) at the heart of a newly refactored python workflow for four-dimensional cardiac-MRI strain quantification demonstrating how a single, compact network can outperform traditional convolution and spline-based methods. The original code, capable of orientation normalization, displacement tracking, and finite-difference strain computation, has been translated and consolidated into pytorch. By injecting sinusoidal positional encodings at the network’s input layer supplied a rich set of high-frequency basis functions hence enabling multilayer MLP to resolve gradients that cubic splines and conventional CNNs typically blur or struggle with. Profiling on an Apple-silicon GPU shows interactive …

Design Of A Teleoperabletendon-Driven Robotic Hand, Zachary Giese, Joseph Gober, Samuel Grisham, Avery Mahan, Aspen White, Brayden May, Aspen White

ATU Scholars Symposium

This work presents the design, implementation, and validation of a 3D-printed tendon-driven robotic hand with a bi-directional wireless control system. The robotic hand emulates human anatomical principles, focusing on replicating flexion and extension mechanisms of the metacarpophalangeal (MCP), proximal interphalangeal (PIP), and distal interphalangeal (DIP) joints via a tendon-pulley system. Iterative prototyping resolved initial challenges in joint stiffness, tendon routing, and servo interference, culminating in a design where a single servo drives both flexion and extension for each joint using a bidirectional tendon control mechanism. A reliable bidirectional wireless communication framework, using Arduino Nano Every microcontrollers and NRF24L01 modules, enables …

Clinical Use Of Sit2stand Ai Application For Kinematic Analysis In Prosthesis Users., Samerial Brown

Posters - 2025

Biomechanical analysis is a tool to evaluate prosthetic and orthotic patient's. These tools offer the clinician capability of understanding the mechanism of injury, gait deviation or prosthesis problem. Video based analysis require expensive hardware, software, and training which sometimes costs $40-100,000.

The recent advent of artificial intelligence (AI) has opened up the possibility of acquiring high speed human motion video analysis using low-cost hardware and open-source machine learning algorithms. Still, free assessments like the Sit2Stand test is a current clinical outcome measure which assesses ability of a patient to stand and sit as fast as possible 5x. The faster the …

Emg-Based Intraoperative Neuromonitoring Using Advanced Machine Learning Approaches, Abdalla Nabil Elsharkawy, Nourhan Zayed

Mechanical Engineering

Intraoperative neuromonitoring (IONM) plays a critical role in minimizing nerve damage during surgeries by providing real-time feedback on neural integrity. This study evaluated models associated with deep learning and machine learning models for electromyography classification of signal during intraoperative neuromonitoring (IONM). The CNNLSTM model achieved the highest accuracy (85.2%), outperforming traditional models like KNN (53%), RF (62%), and CNN (76%). This demonstrates the degree to which the CNN-LSTM model can gain insight into temporal and spatial dependencies throughout the EMG signals, which makes it optimal for real-time classification in IONM applications. This implies that deep learning techniques can improve surgical …

Neurophisology Biosignals Of Cognitive Training Classification In Virtual Reality Environment Using Deep Learning Model, Nourhan Zayed, Mohamed Reda

Mechanical Engineering

This research investigates the potential of neurophysiological biosignals fusion, such as electroencephalogram (EEG) and Eye Tracking signals (ET), to classify cognitive states during virtual reality (VR) training, specifically for the rehabilitation of neurodegenerative diseases. By analyzing EEG data collected from participants engaged in VR-based cognitive exercises, we aim to identify patterns associated with different cognitive states and develop a robust classification system. A Convolutional Neural Network (CNN) model was developed to predict task performance utilizing neurophysiological inputs in an immersive world. This system could be used to monitor cognitive function, assess treatment efficacy, and provide real-time feedback to adapt the …

Advancing Prosthetic Technology: 3d-Printed Robotic Arm With Micro Linear Actuators, Vu Tran, Nathan Reed, Mahdi Yazdanpour

Posters-at-the-Capitol

The increasing demand for affordable and accessible prosthetic solutions has driven innovation in the field of robotics. In this project, we present the design and development of a 3D-printed robotic prosthetic arm aimed at addressing the challenges faced by individuals with upper limb amputations. Our prosthetic arm utilizes five micro linear actuators to achieve precise and naturalistic movement. The design of the prosthetic arm prioritizes affordability and accessibility, with a focus on leveraging 3D printing technology to reduce manufacturing costs and enable customization. The use of micro linear actuators offers advantages in terms of compactness, lightweight construction, and efficient power …

Integrated Compliant Structure For A Hand Exoskeleton, Tristan R. Koopman

Honors Undergraduate Theses

This thesis presents the design and prototyping of a wearable hand exoskeleton that integrates a flexible structural framework to assist with hand movement while maintaining comfort and anatomical conformity. The goal was to create a device that supports tendon-driven actuation through a compliant structure, combining elements of rigidity and flexibility to match the natural geometry and motion of the human hand. Traditional hand exoskeletons often trade off motion for structure or vice versa. This project aims to bridge that gap with a hybrid compliant design that balances flexibility and support. The design process followed an iterative approach involving rapid prototyping …

Learning From Leads: A 1d Dilated Resnet For Ecg Chagas Disease Screening, Somesh Saini, Matheus Lima Diniz Araujo

Student Scholarship

No abstract provided.

Capacity Of Self Compact Concrete Walls Using Attapulgite As A Partial Replacement Of Cement Under One Way And Two Way Action Restriction, Wissam Kadhim Alsaraj, Luma Abdul Ghani Zghair, Akhlas Hashem Mohammed

Al-Esraa University College Journal for Engineering Sciences

This investigation about the structural performance of sustainable self-compact concrete walls exposed to eccentric axial regularly dispersed loading, including the effect of aspect ratio (AR) and slenderness ratio (λ) by one-way and two-way action. The experimental program includes testing ten wall panels, the eccentricity of the loading system equivalent to one-sixth of depth. These wall panels are separated into four groups, each one consisting of three specimens. first and second groups clarify the aspect ratio (H/L) effect. The results indicated for decreasing AR from (0.75 to 0.625), (0.625 to 0.5), and (0.75 to 0.5), the increase of final load is …

Exploring The Benefits Of Feature Selection Based On Bat Algorithm And Deep Learning In Brain Cancer Diagnosis, Noor Fawzi Shafiq

Al-Esraa University College Journal for Engineering Sciences

Brain cancer is considered one of the most dangerous types that must be treated as soon as possible. Therefore, it is necessary to detect brain cancer in its early stages to enhance the diagnosis of the condition. This study proposes to combine the bat algorithm (BA) with deep learning methods to identify and classify brain tumors in medical images accurately.

In this paper, the bat algorithm was used to select distinctive features from the input brain images. The Bat Algorithm (BA) is a metaheuristic optimization algorithm that mimics the echolocation behavior of bats. It efficiently explores the feature space to …

Unveiling The Hidden Threat: How Wireless Networks Fuel Serious Cyber Attacks, Ibtesam Jomaa Hawi

Al-Esraa University College Journal for Engineering Sciences

The spread of wireless networks has led to an increase in serious cyber attacks due to their weak architecture. This article focuses on reevaluating cybersecurity in wireless network technology by integrating statistical information detection methods and artificial intelligence (AI) algorithms. To construct a wireless networking scenario that accurately reflects real-life conditions, we created a data fabrication that included four pre-existing anomalies as well as four newly introduced anomalies. The synthetic dataset created from these generation processes contains 20 thousand distinguishable values, which are later divided into training and validation sets. Using the strategy described before, we began to analyze the …

A Study On Improving The Accuracy And Effectiveness Of Similarity Detection Processes In Text Files Using Nlp Techniques, Noor Abdulmuttaleb Jaafar

Al-Esraa University College Journal for Engineering Sciences

The rapid expansion of the Internet has revolutionized access to information, especially in the area of unstructured data, most of which consists of textual content. While instant access to information brings many advantages, it has also given rise to a prevalent problem – plagiarism. Copying and reusing materials without proper permission poses a significant threat to academic integrity and integrity. Rates of plagiarism, especially in academic and scientific publications, have risen with the advent of the Internet, reaching alarming levels, such as 60% in student projects. This study examines the proposed model that includes computation of similarity using cosine coefficients, …

An Intelligent System Using Deep Learning For Healthcare Monitoring In Light Of The Covid-19 And Future Pandemics Based On Iot, Sara Salman Qasim, Rajaa J. Khanjar, Jamal Nasir Hasoon, Baesher Abdullateff Abad, Ali Hussein Fadil, Shajan.M. Alsowaidi

Al-Esraa University College Journal for Engineering Sciences

Recently, the Internet of Things has become a compelling research field as a new topic of research in various disciplines, particularly in the field of healthcare, because the Internet of Things is rebuilding modern healthcare systems by integrating technology, economics, and social perspectives. The development of healthcare systems from traditional to more personalized systems in which patients can be easily diagnosed, monitored and treated and many people can be helped. People are treated and cared for remotely and this is what some people need in the crisis the world has been through like COVID-19. This epidemic is caused by the …

Speech Coding Based On A Hybrid Approach: Dct, Huffman And Run-Length Coding, Sundos Abdulameer Alazawi, Esraa Jaffar Baker, Shahbaa Mohammed Abdulmaged

Al-Esraa University College Journal for Engineering Sciences

The exponential expansion of data in the digital world necessitates the development of effective methods for data transmission and storage. Data compression (DC) strategies are suggested to reduce the quantity of data stored or conveyed due to constrained resources. As a result of DC ideas' ability to efficiently use existing storage space and transmission capacity, different methods have been developed in various areas. Speech coding is a lossy method of coding; therefore, the output signal differs slightly from the input signal. Speech coding is useful for message encryption, communication over long distances and speech quality. In the fields of digital …

The Evolution Of The University Of Al-Anbar Urban Planning Based On The Mental Picture's Diversity And The Contemporary Planning Spaces Filling, Ali Abdulsamea Hameed

Al-Esraa University College Journal for Engineering Sciences

This research concentrated on the role of environmental graphic design (EGD) and the place-making idea in the interior environment of Al-Anbar University. To develop an identity being visual for the University of Al-Anbar internal environment (IE) is this goal of project. The search sought to create and enhance the shape of the internal University of Al-Anbar vacuum by reviving the idea of place building. In order to build and filling the internal emptiness of the campus, the identity being visual must also be strengthened. The descriptive analytical approach was chosen since it was best suited to achieve the goal of …

Deciphering Mechanochemical Influences Of Emergent Actomyosin Crosstalk Using Qcm‑D, Emily M. Kerivan, Victoria N. Amari, William B. Weeks, Leigh H. Hardin, Lyle Tobin, Omayma Y. Al Azzam, Dana N. Reinemann

Faculty and Student Publications

Purpose: Cytoskeletal protein ensembles exhibit emergent mechanics where behavior in teams is not necessarily the sum of the components’ single molecule properties. In addition, filaments may act as force sensors that distribute feedback and influence motor protein behavior. To understand the design principles of such emergent mechanics, we developed an approach utilizing QCM-D to measure how actomyosin bundles respond mechanically to environmental variables that alter constituent myosin II motor behavior.

Methods: QCM-D is used for the first time to probe alterations in actin-myosin bundle viscoelasticity due to changes in skeletal myosin II concentration and motor nucleotide state. Actomyosin bundles were …

Mechanically Cost-Effective Approach For Bipedal Walking In Robots Using Instantaneous Collision Angle, Smit R. Patel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Humans, as bipedal locomotors, are effective at reducing the mechanical cost of transport (CoTmech) by adopting movement strategies and gaits that minimize energy expenditure for a given distance. By using different gaits at different speeds, leveraging their long spring-like tendons and muscle elasticity which store and release energy during movement, humans reduce the mechanical effort required for locomotion. Current locomotion solutions offered in bipedal robots, based on legacy walking and running gait models, are not great at energy efficiency unless walking at very low speeds. Additionally, the control system of robots, designed to ensure stability and adaptability, requires substantial resources, …

Collapse Of Pre-Covid-19 Differences In Performance In Online Vs. In-Person College Science Classes, And Continued Decline In Student Learning, Gregg R. Davidson, Hong Xiao, Kristin Davidson

Faculty and Student Publications

Abstract: Studies comparing student outcomes for online vs. in-person classes have reported mixed results, though with a majority finding that lower-performing students, on average, fare worse in online classes, attributed to the lack of built-in structure provided by in-person instruction. The online/in-person outcome disparity was normative for non-major geology classes at the University of Mississippi prior to COVID-19, but the difference disappeared in the years after 2020. Previously distinct trendlines of GPA-based predictions of earned-grade for online and in-person classes merged. Of particular concern, outcomes for in-person classes declined to match pre-COVID-19 online expectations, with lower-GPA students disproportionally impacted. Objective …

Wearable Sensing Systems And Data Analytics For Pressure Sensing Socket Prostheses, Stacey Le, Mio Nakagawa

College of Engineering Summer Undergraduate Research Program

Prosthetics have been widely used as the primary solution for lower limb amputations, but residual limb volume fluctuations have posed challenges to the effectiveness and comfortability of these devices. In this project, we aim to observe pressure distribution patterns in the prosthetic socket during gait using sensing technology and investigate the performance of different machine learning algorithms on determining good or bad fit.