Computer Engineering Commons^™

Harnessing Waste Heat From Solar Cells Using Advanced Energy Storage Systems, Hayder Ibrahim Ismael

Al-Esraa University College Journal for Engineering Sciences

Renewable energy is largely produced by photovoltaic (PV) solar cells, but such a process is greatly impacted with thermal buildup as the solar cells work. Redundant heat not only lowers the level of electrical production, but also hastens deterioration and decreases the life-time of PV modules. In this study, we suggest a hybrid system which combines high-performance energy storage devices, namely, super-capacitors, and PV modules coupled with the use of waste heat as a source of useful energy and which increases efficiency of the system in conjunction. In order to estimate the potential amount of thermal energy recovery, as well …

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 …

Behind The Prompt: The Environmental Impact Of Llm Inference, Lucy Hegenderfer, Isaac Huang

College of Engineering Summer Undergraduate Research Program

As the size and demand for large language models (LLMs) increase, the environmental impact of computational inference often exceeds training; yet industry lacks a standardized method of calculating this expanding environmental footprint. Complexity arises with task-specific computational demands, infrastructure overhead, and various GPU architectures, making cross-model assessments burdensome. Combining environmental engineering and computer science principles by validating Jegham et al.’s meta-model, we predict the carbon emissions and water consumption during inference, providing metrics to raise user awareness of AI’s growing environmental footprint. Additional work supports integration into a multi-agent conversational system that encourages responsible scheduling and prompting, guiding the user …

Revit Walasee: An Auto-Generated In-Wall Revit Model, Ally Delgado, Andrew Kimball, Calianna Collins, Yi Qian Goh

Computer Science and Engineering Senior Theses

The Revit WalaSee is a software-hardware integration tool designed to make building renovations smarter and more sustainable. In the construction industry, rework and demolition make up a large part of global construction waste and carbon emissions, largely due to the lack of internal wall documentation in older buildings. Our project addresses this issue by developing the pipeline between the Walabot wall scanner, a handheld device that detects hidden elements behind drywall, and Autodesk Revit, a widely used platform for Building Information Modeling (BIM).With the Revit WalaSee, someone without extensive technical training could scan any wall and produce accurate 3D modelling …

Ai-Powered Inspection: A Computer Vision System For Efficient Defects Detection In Underground Infrastructures, Rasha Alshawi

LSU New Orleans Theses and Dissertations

Undetected defects in culverts and sewer pipes pose significant risks to public safety, leading to infrastructure collapses, flooding, and transportation disruptions. Traditional manual inspections are time-consuming, costly, and prone to human error, while existing automated methods struggle with occlusions, irregular defect shapes, class imbalances, and high computational demands. To address these challenges, this dissertation develops advanced semantic segmentation systems that automate defect detection, significantly improving efficiency and accuracy.

This research introduces a series of innovative models designed to overcome these challenges in underground infrastructure inspection. Using dual-attentive mechanisms, sparsely connected blocks, and depth-separable convolutions, these models improve segmentation performance and …

Robot-Integrated 4d Building Information Modeling (4d Bim): Framework For Planning Safe Autonomous Construction Operations In Dynamic Environments, Hafiz Oyedimeji Oyediran

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

In the construction industry, the use of autonomous robots is considered a solution to overcome the heavy reliance on human workers to perform repetitive, strenuous, and hazardous tasks. While these robots offer the advantage of autonomous operation, ensuring their safe and efficient integration within construction sites requires precise planning. Such planning must account for the varying project complexities such as scope, site layout, tasks, timelines, existence of human workers, and other spatiotemporal conditions of the construction site. Currently, there are no methods to safely plan autonomous robot operations considering these factors within the overarching construction planning process. Thus, autonomous robots …

Assessing Water Quantity And Quality In The Mississippi River Valley Alluvial Aquifer And Coastal Louisiana Through Integrated Airborne Electromagnetic And Borehole Data, Michael George Henin Attia Khalil

LSU Doctoral Dissertations

Numerical modeling has contributed significantly to the understanding of groundwater systems. Many challenges are associated with constructing groundwater models which include an accurate understanding of the geology and aquifer parameters estimation. Traditionally boreholes are a successful way to capture geological features, however, boreholes often have sparse data. Airborne electromagnetic (AEM) data allows for efficient and cost-effective surveying of large areas, providing valuable information about the subsurface electrical resistivity. By bridging the gap between boreholes, AEM data offers a broader view of the aquifer system's structure and heterogeneity. However, interpreting geophysical AEM data has uncertainties. Developing a framework to apply the …

Earthquake Wrangler: Leveraging Ios Technology For Earthquake Detection And Early Warning Application To Enhance Public Safety., Luis F. Salome

Theses and Dissertations--Civil Engineering

Earthquakes are devastating natural phenomena and generate secondary hazards such as tsunamis, landslides and fires. Their catastrophic impacts span both developed nations including the United States, Japan, Turkey, and Italy and developing countries such as El Salvador, Haiti, Nepal and the Philippines, where disparities in early warning infrastructure remain important. Seismic events start with stress waves generated by tectonic plate motion, with body waves (P- waves and S-waves) and surface Rayleigh and love waves that carry energy through the earth. While some regions have adopted advanced early warning systems based on seismic hazard models and strong ground motion analysis, others …

Cognitive Map Generation For Vision And Language Navigation, Alexander Sandoval Mesa

Dissertations and Theses

Visual-Language Navigation (VLN) presents significant challenges for autonomous agents, such as robots and virtual assistants, particularly in complex, dynamic environments where the seamless integration of visual perception and natural language understanding is critical. Traditional VLN systems often struggle with effectively aligning language instructions and visual scene understanding, limiting their adaptability and navigation efficiency.

This thesis proposes a novel Cognitive Map-based framework that addresses these challenges by transforming natural language navigation instructions into structured graph representations. The Cognitive Map consists of nodes representing waypoints, landmarks, decision points, and edges encoding spatial relationships and navigational actions. These maps are generated using Large …

Crop2cloud Platform: Real-Time Data Integration For Agricultural Water Monitoring, Bryan Nsoh, Abia Katimbo, Kendall Dejonge, Wei-Zhen Liang, Hongzhi N. Guo, Yufeng Ge, Derek M. Heeren, Yeyin Shi, Xin Qiao, Daran R. Rudnick, Hope Njuki Nakabuye, Birru Girma, Isa Kabenge, Joshua Wanyama

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Efficient water management is vital for sustainable agriculture, yet integrating real-time data for precise irrigation remains a challenge. This study designed the Crop2Cloud (C2C) platform, a system that leverages advanced sensors using Internet of Things (IoT), edge and cloud computing techniques, and computed Water Stress Indices (WSIs) and machine learning models (i.e., fuzzy logic), to provide scalable and real-time irrigation decisions. The C2C platform aggregates several data including Volumetric Water Content (VWC) from TDR sensors (Acclima Inc., US) installed at four multiple depths, canopy temperatures (Tc) measured by Infrared Radiometers (IRTs) (Apogee Instruments, US), as well as weather information and …

Firelog: An Open-Source, Low-Cost System For Temperature Logging During Wildland Fires With High Spatial And Temporal Resolution, Nipuna Chamara, Yufeng Ge, Sabrina E. Russo

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Measuring flame, air, and soil temperatures during wildland fires, including wildfires and controlled burns in land management contexts, is crucial for research and applications in fire ecology, safety, and management in a wide array of ecosystems, from grasslands to forests. However, open-source and commercial systems are needed for measuring and logging flame and air temperatures that are user-friendly, economical, modular, and customizable. This paper details the design, development, and validation of the FireLog system. Laboratory validation experiments demonstrated high measurement accuracy, with a minimum coefficient of determination (R2) of 0.98 and the highest observed root mean square error (RMSE) of …

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 …

Basic Safety Message Generation Through A Video-Based Analytics For Potential Safety Application, Abyad Enan

All Theses

With the advancement of modern artificial intelligence techniques, computer vision can play a vital role in enhancing roadway safety by reducing the risk of imminent collisions. To do so, a vision-based safety application is required, where a roadside camera can monitor the roadway traffic and predict potential risks of crashes in real-time. If any risky situation or behavior is observed that may lead to a crash, then a safety application can send warnings to the vehicles at risk. For vision-based safety applications on a roadway section, it is important to accurately monitor each vehicle’s location, speed, acceleration, heading direction, etc. …

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 …