Computer Engineering Commons^™

Multi-Level Energy Optimization For Connected And Automated Vehicles: From Cooperative Multi-Vehicle Control To Individual Powertrain Management, Pruthwiraj Santhosh

Dissertations, Master's Theses and Master's Reports

The transportation sector currently accounts for nearly 30% of global energy consumption, necessitating urgent advancements in vehicle efficiency to meet Net Zero targets. Leveraging connectivity and automation, this dissertation proposes and validates methodologies to reduce the energy consumption of light-duty vehicles at both fleet and individual levels.

First, a validation framework is developed to bridge the “simulation-to-real world” gap in Cooperative Automated Vehicle (CAV) research. Moving beyond virtual simulations, the study establishes a methodology for physically validating centralized control architectures via a custom Cellular V2X network. By synchronizing vehicle-powertrain models with physical test vehicles, the framework successfully orchestrates complex arterial …

The Excess Path Length Distribution: A Stochastic Model For Sample-Based Path Planners, Chaz B. Cornwall

Dissertations, Master's Theses and Master's Reports

Through random sampling, sample-based path planners enable autonomous agents to quickly find paths without human intervention. However, due to the paths' randomness, sample-based path planners currently require additional verification, partially nullifying agents' ability to act autonomously. I set out to characterize this uncertainty so humans know what to expect from these path planners and know how to alter the path planner to desired specifications. To ensure the results are theoretical as well as practical, I first create a stochastic model of path length uncertainty using the trade-off between sampling time and optimality. By leveraging this model, my proposed algorithm reduces …

Using Automotive Lidar To Reduce The Energy Consumption Of An Ego Autonomous Vehicle, Logan P. Schexnaydre

Dissertations, Master's Theses and Master's Reports

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model …

Evaluation Of Electroencephalography Processing Methods For Estimating Metabolic Energy Expenditure During Walking, Stephanie L. Pinelo

Graduate Studies Theses and Dissertations 2026

In this study, three EEG datasets, created via different levels of pre-processing, were used to train VO2 prediction models whose performance was tested and compared. Understanding the link between EEG and VO2 during walking is important when working in rehabilitation or studying metabolic energy optimization. Common methods of measuring these two bio-signals tend to be bulky, uncomfortable, and inefficient, so finding a way to predict VO2 from EEG via 1D CNN model training is a worthy pursuit.  It was hypothesized that, due to a CNN needing more data to find patterns for prediction, a minimally processed EEG dataset would have …

Teleoperated Mobile Robot For Pesticide Spraying And Greenhouse Navigation: Numerical Analysis, Wessam Atwa, Zakaria Ismail, Mohsen Egela, Mohamed G. Alkalla

Mansoura Engineering Journal

Pesticide spraying in greenhouses is a dangerous process as the operator should wear protective suits and masks against the chemicals, which cause skin and eye irritation, respiratory issues, and even cancer. Other severe conditions involve elevated temperature and humidity in the confined greenhouse atmosphere. Therefore, this article proposes a novel teleoperated mobile robot for pesticide spraying called AMR-BPS to address such issues. It aims to keep the human securely outside during the spraying process. AMR-BPS has a novel design incorporating many innovative mechanisms, such as an extendable spraying boom, independent control of each spraying side, adjustable nozzle angles, and 2D-LiDAR …

A Novel Federated Llm Framework For Distributed Traffic Modelling In Intelligent Transportation Systems, Seerat Kaur

Theses and Dissertations (Comprehensive)

Intelligent transportation systems (ITS) depend on accurate traffic prediction to support congestion management, infrastructure planning, and real-time operational decisions. Despite substantial progress in data-driven forecasting, several challenges continue to limit practical deployment: traffic data is distributed across independent regional authorities, making centralized aggregation infeasible, standard federated aggregation strategies ignore traffic-specific characteristics that meaningfully affect model quality, and existing models produce only numerical outputs without interpretable reasoning that urban planners can act upon. This thesis addresses these challenges through four contributions that collectively advance privacy-preserving, explainable, and scalable traffic forecasting.

The first contribution provides a systematic review of 129 peer-reviewed publications, …

Semantic-Weighted Lidar–Camera Slam For Robust Mapping In Vegetation-Rich Environments, David Aigbovboise Akhihiero

Graduate Theses, Dissertations, and Problem Reports (ETD)

Many LiDAR odometry and SLAM methods are lightweight and effective, but they assume that all LiDAR point returns are equally reliable. In practice, this assumption is often violated in vegetation rich or semi transparent environments, where in a single beam footprint, LiDAR beams may intersect multiple scattering surfaces like leaves, branches or glass. These ambiguities in returns produces probabilistic or biased range measurements that violate the assumptions of most geometric registration frameworks and can lead to drift and inconsistency.

To address this challenge, this dissertation proposes a semantic-weighted LiDAR-camera SLAM framework that integrates class dependent weights into a front-end LiDAR …

Dataless Neural Networks For Boolean Satisfiability And Network Optimization, Andrew Evan Gautier

Graduate Theses, Dissertations, and Problem Reports (ETD)

Combinatorial optimization problems (COPs) require searching over a finite solution space subject to constraints, with the goal of satisfying an objective function. They arise in operations research, scheduling, resource allocation, circuit design, and many other fields. Many problems in combinatorial optimization (including satisfiability and network design) are NP-hard. Traditionally, researchers have built approximate solvers that return near- optimal solutions efficiently by developing increasingly sophisticated heuristics and meta- heuristics. Deep learning has provided new opportunities for improving combinatorial solvers by leveraging neural guidance to prune the search space. Traditional neural networks have distinct drawbacks in this context: separate training and …

Data Augmentation And The Reliability Of Conformal Prediction For Uncertainty Quantification In Medical Imaging, Rizwan Ahamed

Graduate Theses, Dissertations, and Problem Reports (ETD)

The safe clinical deployment of deep learning models for high-stakes medical imaging tasks requires more than high average accuracy; it requires demonstrable, per-case reliability. Uncertainty quantification (UQ) provides the missing signal that tells a clinician when a model prediction can be trusted and when a case should be escalated for expert review. Among UQ approaches, conformal prediction (CP) is especially attractive because it produces prediction sets that are guaranteed, under the assumption of exchangeability, to contain the true label with a user chosen probability, and it does so without assumptions about the model or the data distribution. This report first …

Effect Of Local Steel Slag Incorporation On The Mechanical Properties Of Concrete, Ahmed Safaa Tariq Karmah, Wissam Khadum Alsaraj, Luma A. Zghair

Al-Esraa University College Journal for Engineering Sciences

The increasing interest in the production of concrete through the utilization of inexpensive materials has caused a rise in the number of studies concerning the use of materials with cementitious properties, such as Silica Fume, Slag, Fly Ash and other pozzolanic materials. Moreover, the increasing amounts of Steel Slag being produced from local factories that are being deposited without an available method of disposal provides an opportunity to harness the Slag in the production of an inexpensive, and possibly better concrete. Slag has been used as both an addition and substitution of the cement and fine aggregate. The mixtures included …

Decoding Climate Change: A Comprehensive Statistical Insight Into Temperature Anomalies In Iraq And Its Neighboring Countries, Jameel T. Al-Naffakha, Mohammed R. Al-Qassabanda, Israa Jafar

Al-Esraa University College Journal for Engineering Sciences

This study applies advanced statistical techniques, including the Mann-Kendall Trend Test and ARIMA forecasting, to validate and predict temperature anomalies across Iraq and its neighboring countries (2014–2024). Findings confirm a statistically significant warming trend (p < 0.00000005) across all nations, with Syria (1.02°C) and Turkey (0.97°C) experiencing the highest anomalies. GIS-based spatial analysis highlights regional disparities, identifying climate-vulnerable zones. The persistent rise in temperature anomalies correlates with worsening water scarcity, desertification, and extreme weather events, including prolonged droughts and heatwaves. Iraq’s peak anomaly (1.48°C) has exacerbated heat stress, agricultural decline, and reduced river inflows, while Kuwait and Saudi Arabia struggle to maintain critical infrastructure under record-breaking temperatures exceeding 50°C. These climate shifts pose severe risks to water availability, food security, and energy demand, necessitating urgent policy interventions. Key recommendations include enhanced water resource management, climate-adaptive agriculture, and renewable energy expansion. If left unaddressed, rising temperatures could destabilize the region, increasing socio-economic vulnerabilities and escalating resource conflicts. This study underscores the need for cross-border collaboration and sustainable adaptation policies to mitigate the long-term impacts of climate change in the Middle East.

Optimal Power Flow Control In The Iraqi Power Grid Using Artificial Intelligence Algorithms For Carbon Emission Reduction, Mohammed Shakir Juber

Al-Esraa University College Journal for Engineering Sciences

Iraq’s power sector remains in a protracted and severe crisis characterized by a significant mismatch between supply and demand, high levels of losses during transmission and distribution, as well as an increasing challenge to the resources base being largely unfavourably. These inefficiencies impose heavy costs on the national economy in excess of 40 billion annually and they also reinforce greenhouse gas emissions, and exacerbate environmental issues. To deal with these problems, we proposed in this paper that a new hybrid AI tool should be developed for the solution of multi-objective optimization problem based on purpose Genetic Algorithm (GA) merger with …

Applying Machine Learning Techniques For Early Detection Of Cyber Attacks On Iot Devices, Noor Adnan Allamy

Al-Esraa University College Journal for Engineering Sciences

This research designs, implements, and evaluates a machine learning-based framework for the early detection of cyber attacks targeting Internet of Things (IoT) devices, with a specific focus on the context and challenges present in Iraq. The study conducts a comparative analysis of three supervised learning algorithms—Support Vector Machine (SVM), Random Forest (RF), and Deep Neural Networks (DNN)—using a combination of benchmark datasets (NSL-KDD, CIC-IDS-2017, Bot-IoT) and a synthesized dataset adapted to simulate the Iraqi threat landscape. Key performance metrics, including accuracy, precision, recall, and F1-score, were used for evaluation. The proposed Random Forest model demonstrated superior performance, achieving an accuracy …

Ai-Enhanced Heat Transfer Optimization In Magnetic Bio-Nanofluids, Hasan Attyah Shaboot

Al-Esraa University College Journal for Engineering Sciences

This study presents a hybrid Artificial Intelligence–Computational Fluid Dynamics (AI-CFD) framework for optimizing heat transfer in magnetic bio-nanofluids subjected to external magnetic fields. Magnetic bio-nanofluids, composed of biocompatible base fluids containing superparamagnetic nanoparticles, exhibit tunable thermal and flow behavior, making them promising for biomedical and micro-cooling applications. Conventional optimization methods based on experiments or brute-force CFD are computationally expensive and limited in exploring the full design space. To overcome these challenges, an Artificial Neural Network (ANN) surrogate model was developed to predict two key performance indicators, the Nusselt number and the friction factor, with high accuracy (R² > 0.997). The surrogate …

Hybrid Experimental–Computational Study On The Energy Absorption Of Graphene Nanoplatelet-Reinforced Sandwich Structures, Hamdan Yousif Hamdan

Al-Esraa University College Journal for Engineering Sciences

Background: Sandwich composites are widely used in aerospace, automotive, and marine applications because of their lightweight, stiffness, and strength, but they remain prone to out-of-plane impacts and barely visible impact damage (BVID). Graphene Nanoplatelets (GNPs) have shown strong potential to improve fracture toughness and impact resistance. However, hybrid experimental–computational studies applying such reinforcement are still lacking in developing contexts like Iraq, where practical and accessible solutions are essential. Aims: The study investigates the effect of GNP reinforcement on the low-velocity impact behavior and energy absorption of glass fiber/epoxy sandwich panels with PVC foam and balsa wood cores. Objectives include fabricating …

Effect Of Thick Closed Walls Of West And South Elevations Of Iraqi Middle And South Territory Housing Building On Reducing Energy Use, Abeer Qasim Jbur, Shaimaa M. Hamza, Mayyadah Lutfi Abdulwahhab

Al-Esraa University College Journal for Engineering Sciences

Thermal insulation is one of the most important factors in achieving sustainability, increasing efficiency, and reducing energy consumption, but modern insulation materials are expensive, in addition to their availability. Therefore, through our research, we resorted to investigating the issue of reducing thermal load in buildings through the use of thick-walled facades in the southern and western facades, where we studied a building with two windows with windows on the southern and western facades and another without these windows and with thick walls, for two locations, the first in central Iraq, which is the city of Baghdad, and the second in …

The Impact Of Ethyl Levulinate Additive On Diesel Engine Performance And Emissions: An Experimental Study, Maha Ali Ghadbaan

Al-Esraa University College Journal for Engineering Sciences

This study explores the environmental and operational impact of adding Ethyl Levulinate—a biodegradable ester derived from biomass—to diesel fuel. A fuel blend known as B5El6 (comprising 5% biodiesel and 6% Ethyl Levulinate) was prepared and tested experimentally using a single-cylinder diesel engine operating at a constant speed of 1500 rpm under full load conditions. Performance metrics and emission data were recorded, and a Life Cycle Assessment (LCA) was conducted using the IMPACT2002+ methodology.

The results revealed that B5El6 significantly reduced greenhouse gas emissions (100 kg CO2 eq) and improved ecosystem quality. However, it presented challenges in terms of human health …

The Role Of The Scenario In Formulating The Contemporary Architectural Text, Rounaq Arif Mohsin, Abbas Ali Hamza, Bashar Shamil Alkhafaji

Al-Esraa University College Journal for Engineering Sciences

In order to create an integrated architectural text, which is a complicated art that blends beauty and practical elements, a rigorous design procedure is necessary. In this situation, the scenario’s role becomes crucial in developing the current architectural text and directing architectural approaches. In order to better understand how the scenario influences the design process and the interactions between various architectural aspects, this project intends to explore and analyze the impact of the scenario in developing and refining architectural text formulation approaches.

The study looks at the idea of a scenario and how it has been used in architecture, as …

Investigation Of Some Physical Properties Of Slurry Infiltrated Fibrous Concrete (Sifcon) Under Different Curing Times, Rand Kh. Mahmoud, Mohmmed Juad Khadhim, Fayq Hasan Jabbar

Al-Esraa University College Journal for Engineering Sciences

This research studied the effects of different types fibers (Basalt, Carbon and Basalt-Carbon hybrid mix) and curing ages (7, 14, 28 and 56 days) on some physical properties of - Slurry infiltrated fibrous concrete (SIFCON). Density, ultrasonic pulse velocity UPV, Poisson’s ratio and water absorption were measured for the experimental study with 30% cement replacement by Class F fly ash to increase sustainability. It was found that properties were significantly affected by the type and dosage of fiber admixture. The UPV was enhanced by basalt fibers and the absorption reduced up to an optimal range of 3–5% after which agglomeration …

Heathammer: Effects Of Thermal Stress On Dram Technology Reliability Using Rowpress And Rowhammer, Filip Roth Tronnes-Christensen

Theses

Modern DRAM scaling has reduced cell capacitance and increased thermal sensitivity, making disturbance-based faults such as RowHammer and RowPress increasingly significant reliability and security concerns. RowHammer induces bit flips through repeated row activations, while RowPress does so by holding a wordline open for an extended duration; both exploit inherent capacitive coupling and leakage mechanisms in dense DRAM arrays. This thesis introduces HeatHammer, a thermally assisted disturbance exploit that interleaves RowPress and RowHammer operations to amplify charge leakage and trigger row-traversing bit flips. Using the FPGA-based DRAM-Bender test platform, HeatHammer is evaluated on four commercially available DDR4 modules from different manufacturers …

Efficient Task Allocation Technique For Robots In Smart Warehouse Using Center Of Items (Coi) Methodology, ‪Ahmed Yahya‬‏, Mohamed S. Saraya, Ahmed I. Saleh

Mansoura Engineering Journal

Nowadays, online shopping is very important in Daily life. in 2020 During the quarantine during the spread of COVID-19, online orders increased dramatically, as a result of the great progress in fifth-generation technologies and using the Internet of Things (IoT) and industrial Internet of Things (IIoT), industry 4.0 and 5.0, fog computing, cloud computing, robots systems, and drones systems. Smart warehouses picking system becomes a Basic need and can be implemented to improve efficiency in logistics. Smart warehouses are growing more dependent on robot systems to make the process of meeting these requests more flexible and effective. Therefore, the allocation …

Mechanical And Durability Properties Of Cement Panels Reinforced With Hybrid And Pva Fibers, Shukran H. Faraj, Mohammed J. Kadhim

Al-Esraa University College Journal for Engineering Sciences

This study examines the synergistic effects of hybrid fibers (HF) and polyvinyl alcohol (PVA) fibers on the structural and thermal properties of silica-fume cement panels. Scanning electron microscopy (SEM) was employed to examine mortar mixtures with varying fiber content to assess their enhancement of microstructure. We conducted several experiments on compressive, flexural, and splitting tensile strength, in addition to water absorption and thermal conductivity. The results indicate that 1% HF exhibits superior mechanical qualities, with a compressive strength of 46.89 MPa, a flexural strength of 8.56 MPa, and a reduced thermal conductivity of 0.83 W/m•K. PVA fibers at 2% enhance …

Experimental Analysis Of Droplet Deformation Dynamics In Combined Dc Electric And Shear Flow Fields Using Dpiv, Ayad Ibrahim Khlewee

Al-Esraa University College Journal for Engineering Sciences

This paper presented a systematic study of such droplet deformation at the intersection of uniform DC electric field and hydrodynamic shear flow, in which we focused on conductivity ratio (R) and permittivity ratio (S), describing their influence. The results demonstrate that droplet dynamics is extremely sensitive to the regime: under DC only, either elongation or compression depending on whether R > S or R S, similarly to classical EHD predictions. Under shear-only conditions, deformation was dictated by the balance of elongational stresses (EC) and rotational stresses (RC), with increasing capillary number (Ca) leading to progressive elongation and oscillatory orientation dynamics. When …

The Imaginary In Architecture: The Conceptual Structure Of The Imaginary And Its Manifestations In Architectural Text, Noora Ghadir Hlail, Abbas Ali Hamza Al Greiza

Al-Esraa University College Journal for Engineering Sciences

This study explores the concept of the imaginary as a collective cognitive and cultural structure that shapes symbolic reality through images, myths, and deeply rooted symbols in collective memory. The research applies this concept within the field of architecture, aiming to understand how the imaginary is embodied in architectural texts as symbolic carriers of identity and cultural meaning. Adopting a descriptive-analytical methodology, the study develops a theoretical framework comprising key components—preconditions, mechanisms, and traits of the imaginary—and applies it to two selected case studies: the General Secretariat of the Iraqi Council of Ministers and the Louvre Abu Dhabi Museum. The …

Generative Ai For Method Development In Analytical Chemistry: A New Paradigm In Experimental Design And Optimization, Yasir Fathi Mahmood

Al-Esraa University College Journal for Engineering Sciences

The fast development of artificial intelligence (AI), especially generative AI models, is changing the environment of analytical chemistry. As classical method generation in analytical methods relies on manual trial-and-error methodology as well as statistical methods, generative AI is a new paradigm with automated generation of experimental methodology and optimization. In this paper, the authors discuss the use of generative AI-based technologies, including large language models (LLMs) and neural network-based generators, to create new, efficient, and customized methods of analysis. The paper examines existing applications, technology frameworks, and issues and offers a roadmap with regards to the future incorporation of generative …

Numerical Modeling And Experimental Validation Of A High-Temperature Latent Heat Thermal Energy Storage System Using Metallic Phase Change Materials For Concentrated Solar Power Applications, Fouad Hashim Sharhan

Al-Esraa University College Journal for Engineering Sciences

To ensure reliable performance for the power-block of CSP plants, high power density and near-isothermal discharge must be achieved. A robust means of achieving this is through thermal energy storage (TES). High temperature latent heat storage (LHS) with phase change materials (PCMs) can serve these purposes, however the conventional salts used in PCMs typically suffer from low thermal conductivity that limits power density and increases energy storage charging/discharging times. This manuscript investigates ways to address these limitations using high temperature metallic phase change materials (MPCMs) while also developing a validated numerical framework to aid in their design. To this end, …

Thermal Performance Evaluation Of Solar Cooling Systems For Educational Facilities In Baghdad, Yasser Alawi Mohammed Attia Al-Jubouri

Al-Esraa University College Journal for Engineering Sciences

Schools in Baghdad also suffer from poor thermal comfort, which is a common problem in high-temperature and low-humidity arid climates such as that of the city, where using cooling devices leads to a large energy demand and overloads on the national power grid. Such study offers a thorough assessment of the thermal performance of solar-based cooling systems in an efficient manner to be suitable for educational buildings in Baghdad. The analysis is centred on a solar thermal cooling system with absorption as the heat interaction medium, and an experimental characterisation and mathematical simulation itself are performed. A pilot installation, consisting …

Dual-Interface Wifi Packet Sniffer System Using Esp32-Cam With Real-Time Pcap Generation For Iot Network Analysis, Boy Setiawan Boy, Maghfiroh Maulani, Zico Pratama Putra, Muhammad Senoyodha Brennaf

Makara Journal of Technology

This study focuses on designing and implementing a cost-effective and energy-efficient WiFi packet sniffer system using the ESP32. The ESP32-CAM module, which combines WiFi, Bluetooth, and microSD support, is used to capture IEEE 802.11 frames in real-time via promiscuous mode. Packets are stored in packet capture format, which is compatible with tools such as Wireshark and Scapy. Developed using the official ESP-IDF, it offers low-level control and high performance. Two user interfaces were implemented: a UART-based text menu and a web-based HTTPS menu hosted on the ESP32 itself. Functional and performance evaluations were conducted with a focus on capturing broadcast …

Real-Time Deep Learning Detection Of Toraja Carving Motifs Using Yolo11m For Cultural Heritage Preservation, Herman Herman, Farid Wajdi Mufti, Abdul Rachman Manga, Haidawati Nasir

Knowledge Engineering and Data Science

Toraja carvings are an important part of Indonesia’s cultural heritage, rich in symbolic, aesthetic, and philosophical meaning. However, the identification and preservation of carving motifs still rely on subjective, time-consuming manual processes, limiting scalability and inconsistent knowledge transmission. From a Knowledge Engineering and Cognitive Data Science perspective, this challenge highlights the need for mechanisms that can transform visual cultural artifacts into structured, machine-interpretable knowledge. This study investigates the use of the YOLO11m model as a data-driven approach for modeling cultural knowledge through automated detection of three Toraja carving motifs: pa_tedong, pa_kapu_baka, and pa_manu_londongan using original images collected directly from traditional …

Algorithm For Stabilizing The Reference Trajectory Of Self-Tuning Systems With A Reference Model, Isamidin Hakimovich Sidikov, Feruzakhon Botirxon Qizi Sodiqova

Technical science and innovation

The paper addresses the problem of stabilizing self-tuning systems using adaptive control methods based on a reference process model. As the optimality criterion, the functional of maximum speed of response is selected. The algorithm for synthesizing the self-tuning system is based on a relay-linear control law, which possesses the property of invariance to small disturbances. The issue of ensuring the practical stability of the system under adaptive and multiplicative disturbances is examined. An algorithm for the synthesis of a reference trajectory stabilization system has been developed on the basis of a quasi-optimal passive self-tuning system (STS) with a reference model, …