Engineering Commons^™

A Proposed Load Forecasting Strategy Developed On Smart Electrical Grid Employing Deep Learning Techniques, Noha A. Sakr, Ahmed I. Saleh, Rana Mohamed El-Balka

Mansoura Engineering Journal

Smart electrical grids, which involve the application of intelligent information and communication technologies, are becoming the core ingredient in the ongoing modernization of the electricity delivery infrastructure. They enable the real-time monitoring and direction of network components, which has led to the emergence of new jobs and responsibilities including autonomous intelligent load forecasting. As it gives energy management intelligence, load forecasting is a crucial function for the operation and planning of the electrical system. Many works and studies have been made over the years to enhance smart grids, almost all of these works target the data collected in Fog computing …

Case Study On Application Of External Protection Screen In Trifoliate Spindle-Shaped Super High-Rise Building, Liu Jian, Liu Wen, Li Xinxue, Wang Zhi, Ahmed Mohamed Salama

Mansoura Engineering Journal

This paper presents a comprehensive case study of the design, analysis and application of an external protection screen for a trifoliate spindle-shaped supertall building. The study aims to provide a technical solution for the structural challenges associated with complex changes in façade geometry, especially within the context of a self-climbing external protection system. A numerical model was developed using Finite Element Analysis software SAP2000 to simulate the structure of protection screen, analyzing its effects under the action of various loads. By means of a parametric study, the key parameters of this protection screen such as climbing unit configuration …

Colorado Gravimetric Geoid Model Using A Combination Of Window Technique And Modified Stokes’ Kernel, Hussein A. Abd-Elmotaal, Atef Makhloof, Ayman Hassan, Mostafa Ashry, Hussein Mohasseb, Mostafa Abd-Elbaky

Mansoura Engineering Journal

In the framework of the IAG 1-cm geoid experiment in Colorado, a detailed gravimetric geoid for Colorado has been computed within this investigation. The geoid has been computed through the window remove-compute-restore technique (Abd-Elmotaal and Kühtreiber, 1999, 2003). The window technique has been chosen because of its unambiguous behaviour of treating the local and global topographic-isostatic masses. The window technique needs the harmonic analysis of the topographic-isostatic masses for the data window to a high-degree. The necessary derivations of the appropriate expressions for the needed dimensionless potential harmonic coefficients of the topographic-isostatic masses within the data window for high-degrees are …

Existence And Stability Of A Mathematical Model Solution Of Classical Brain Metabolite Variations In The Circadian Rhythm, Eman A. A. Ziada

Mansoura Engineering Journal

This research aims to study an important model in view of its applications to brain metabolite variations in the circadian rhythm. We will discuss the solution existence and stability of the general form of this model and give its solution by using numerical and analytical methods. The numerical method is the proposed numerical method (El- Sayed method), and two analytical methods, the Adomian decomposition method (ADM) and the Picard method (PM). The uniqueness of the solution will be proved, the convergence of the series solution will be discussed, and an error analysis will be given. The numerical solution of the …

Motion Planning For A Flexible Modular Raft Robot, Chun-Yi She

Dartmouth College Master’s Theses

This thesis presents a hierarchical motion planning framework for SoftRafts, a modular and deformable aquatic robot capable of performing locomotion and manipulation tasks on water surfaces. SoftRafts consist of soft and rigid components that enable structural reconfiguration, offering adaptability in unstructured aquatic environments.

To address the complexity of planning in high-dimensional, deformable systems, the proposed method uses a bounding-shape abstraction, specifically, enclosing circles and rectangular bounding boxes to simplify motion planning. These enclosures abstract the robot's overall shape, reducing the high-dimensional planning problem into a lower-dimensional problem. A global planner uses a probabilistic roadmap (PRM) to compute a collision-free path …

Insights In Cybersecurity Of A Smart Campus - A Review, Mircea Ţălu

Journal of Cybersecurity Education, Research and Practice

The profound impact of the Internet of Things (IoT) on various fronts, is driven by technological advancements, the ubiquitous spread of information, and the emergence of transformative events. IoT presents a diverse array of possibilities within university environments, fostering a more connected and enhanced educational experience. This research undertakes a comprehensive review of existing literature to provide context to the IoT and underscore its crucial significance in the realm of smart campuses. Additionally, the paper explores the intricate connections between IoT and key concepts such as cybersecurity and wireless sensor networks to present a holistic perspective. It delves into the …

Influence Of Unmanned Aerial Vehicle (Uav) Payloads And Flight Speeds On Pesticide Droplet Deposition: Indoor Testing Rig Study, Siti Amni Ismail, Azmi Yahya, Ahmad Suhaizi Mat Su, Anas Mohd Mustafah, Norhayu Asib

ASEAN Journal on Science and Technology for Development

This study aims to determine droplet deposition resulting from dynamic change in payloads and flight speeds of Unmanned Aerial Vehicle (UAV) during operation. The study was conducted at Universiti Putra Malaysia, Serdang, Malaysia. The Advansia A1 hexacopter was first set to fly at combinations of 3 payloads (3.3, 6.6, and 9.9 kg) with 3 flight speeds (3, 5 and 7 m/s) to collect individual rotor RPM, which will later be used to set the rotors’ speed during indoor testing experiment. During the experiment, actual pesticide (Alosa EC) was used at 0.5% concentration in the spray deposition test. The droplet deposition …

Understanding Heterogeneous Nucleation In Iron Alloys From First Principles: A Review And Discussion, Semen Naumovich Lekakh

Materials Science and Engineering Faculty Research & Creative Works

Heterogeneous nucleation during solidification plays a key role in structure formation of different types of iron-based alloys, including steels and cast irons. A review summarizes the novel theoretical methods which were used to understand the nature of heterogeneous nucleation in iron-based alloys. An ab initio simulation of atomic adsorption was used to predict the activity of heterogeneous nuclei, and the thermodynamic methods were applied to design conditions for desired precipitate formation in the iron melts. A high-resolution TEM study of individual nucleus and statistics of nuclei family, obtained from an automated SEM/EDX analysis, illustrates a possibility to design processes of …

High-Temperature Performance Of Alloyed Cast Irons And Cr/Ni Austenitic Steels—An Overview And Discussion, Simon N. Lekakh, Mei Li, Larry Godlewski

Materials Science and Engineering Faculty Research & Creative Works

Fe-based cast alloys, including cast irons and steels, have been used in service at a wide range of mechanical and thermal load in oxidizing environment. Special alloying practices can be used to improve high temperature performance of Fe-based cast alloys in an oxidizing atmosphere. At elevated temperatures, alloying elements can produce a protective interface layer which prevents oxidant penetration into the metal matrix. However, a combination of thermo-mechanical loads along with surface oxidation can decrease the materials integrity by destroying the stable protected interface limiting the range of working parameters and lifetime performance of the material. This overview aims to …

Flexural Strength Of (Hf,Nb,Ta,Ti,Zr)B2–(Hf,Nb,Ta,Ti,Zr)C High-Entropy Dual-Phase Ceramics, Rubia Hassan, William G. Fahrenholtz, Gregory E. Hilmas, Jeremy Watts

Materials Science and Engineering Faculty Research & Creative Works

The room and elevated temperature flexural strengths were measured for (Hf,Nb,Ta,Ti,Zr)B2–(Hf,Nb,Ta,Ti,Zr)C high-entropy dual-phase ceramics. The fracture of ceramics originated from two distinct flaw populations that were either surface defects introduced during specimen preparation or volume defects introduced during processing. The average strength at room temperature was 638 ± 94 MPa with individual bars strengths as high as ∼800 MPa. At 1800°C, average strength increased to 786 ± 265 MPa with individual bar strengths as high as ∼1050 MPa. Above 1800°C, creep dominated resulting in deformation of the bars without fracture. The fracture mode changed from completely trans granular at room …

Optimization Of Persulfate Activation System Using Ferrous Sulfate For Toc Removal From Real Domestic Wastewater, Mohamed Fouad, Mohamed Mossad, Mohamed Gar Alalm, Mahmoud Samy

Mansoura Engineering Journal

The reuse of treated wastewater is increasingly recognized as a sustainable solution to address global water shortage. This study investigates the effectiveness of a persulfate-based advanced oxidation process (AOP) using sodium persulfate (Na2S2O8) activated by ferrous sulfate (FeSO4) as a tertiary treatment for secondary effluents. Real municipal wastewater was collected from Agouzain Wastewater Treatment Plant (WWTP) in Kafr El-Sheikh, Egypt. A Box Benkhen design (BBD) was employed to optimize three key variables: FeSO4 dose (0.5–2.0 g/L), Na2S2O8 dose (0.5–2.0 g/L), and pH (3.0–9.0), with total organic carbon (TOC) removal as the main response. Under optimized conditions (0.50 g/L FeSO4, 2.00 …

Mixing-Controlled Combustion Of Ethanol Enabled By Prechamber Ignition (Pc-Mcc): A Preliminary Experimental Demonstration, Jared Zeman, Ziming Yan, Michael Bunce, Adam Dempsey

Mechanical Engineering Faculty Research and Publications

This numerical study focuses on assessing the key design parameters of interest for use of an active prechamber igniter as an ignition assistance device to enable mixing-controlled combustion (MCC) of ethanol (E100) in a heavy-duty Caterpillar C9.3B engine. Computational fluid dynamic (CFD) simulations of a baseline diesel and prechamber retrofitted C9.3B at a gross indicated mean effective pressure (IMEPg) of 5 bar and 1800 rpm are carried out using CONVERGE. In particular, the sizing of the prechamber volume, sizing of total orifice cross sectional area (orifice diameter), and location of the prechamber relative to a centrally mounted common rail direct …

Introducing Sustainable Development Goals In College Curricula: A Way Forward, Christy Ashley, Jason D. Oliver, Hillary Leonard

Markets, Globalization & Development Review

The commentary proposes a blueprint to help guide curriculum innovations, partnerships, and teaching interventions that incorporate the United Nations sustainable development goals (SDGs) into the curriculum. It suggests the utilization of AACSB’s Societal Impact Canvas with Ancona et al.’s (2007) Leadership Capabilities (Sensemaking, Relating, Visioning, Inventing) to provide a blueprint for mission-aligned SDG integration at a local level. It provides an illustrative example from the University of Rhode Island (USA), where the focus is on the Blue Economy. It aims to provide practical guidance for how a college or university can efficiently organize to gain stakeholder input that helps enhance …

A Large Electroencephalogram Database Of Freewill Reaching And Grasping Tasks For Brain Machine Interfaces, Bhoj Raj Thapa, John Boggess, Jihye Bae

Electrical and Computer Engineering Faculty Publications

Brain machine interfaces (BMIs) offer great potential to improve the quality of life for individuals with neurological disorders or severe motor impairments. Among various neural recording modalities, electroencephalogram (EEG) is particularly favorable for BMIs due to its noninvasive nature, portability, and high temporal resolution. Existing EEG datasets for BMIs are often limited to experimental settings that fail to address subjects’ freewill in decision making. We present a large EEG dataset, containing a total of 6808 trials, recorded from 23 healthy young adults (eight females and 15 males with an age range from 18 to 24 years) while performing reaching and …

Burnout At University: Cross-Sectional Study Among Dental Students, Manal Elhijazi, Hajar Nafia, Ihsane Benyahya

Health Sciences

Context: The university constitutes a demanding and competitive learning environment which can impact the well-being of students. The objective of this survey is to assess the burnout of students at the faculty of dentistry.

Materials and methods: A cross-sectional study was conducted via an anonymous questionnaire with 3 sections: socio-demographic data, lifestyle and habit, and burnout through the Maslach burnout inventory-student survey (MBI-SS) . Continuous variables were presented as means and standard deviations,categorical variables as numbers and percentages. The variables were tested in univariate analysis to assess predictive factors related to burnout using the Khi-2 test. The significance level was …

Effective Management Of Disused Sealed Radioactive Sources In Uganda, Susan Nalumansi

International Journal of Nuclear Security

Sealed radioactive sources are used in a wide range of applications in Uganda, such as medicine, agriculture, geology, industry, and other fields. After a given useful period, the sealed sources can no longer perform their intended purpose and are thus regarded as disused. However, depending on the activity of the source, the disused sources are highly active and can cause significant damage to human health and the environment when mismanaged. A regulatory body was established with the mandate to regulate peaceful applications of ionizing radiation in Uganda. Given the vulnerability of sealed sources at the end of their life cycle …

Development Of Stalling Detection Algorithms And Operator Behavior Models For Evaluating Hydraulic Excavator Performance, Mateo Fernando Montenegro Defaz

Masters Theses

This study aims to develop a reliable algorithm for stalling detection and investigate how operator behaviors impact the truck-loading process, focusing on swing and bucket rotations. While the study of excavator digging conditions and equipment performance is well understood, describing stalling from telemetry data and the influence of operators’ behavior on overall system efficiency remain underexplored. This study seeks to: (i) develop a reliable algorithm for stall detection by analyzing key operational variables such as velocity and angles; (ii) implement statistical and machine learning techniques, specifically a Support Vector Machine (SVM) classification algorithm, to differentiate between ideal and non-ideal digging …

Applying Machine Learning Methods To Generate Understandings Of Differential Item Functioning In A Flu Knowledge Assessment, William L. Romine, Tanvi Banerjee, Derrick Cox

Computer Science and Engineering Faculty Publications

Current influenza trends, including the severity of the 2025 flu season and the prevalence of H5 bird flu in livestock, necessitate efforts to better understand how to educate students about its transmission. Although validated assessments of influenza knowledge exist, these have not been evaluated for affective and demographic biases. We explore differential item functioning (DIF) effects in four items focused on specific aspects of flu transmission derived from a validated influenza knowledge assessment. In doing so, we introduce and utilize a machine learning framework for exploration of DIF which offers greater flexibility than traditional statistical approaches in terms of studying …

Axial Flux Permanent Magnet Generators For Direct-Drive Wind Turbines - Review And Optimal Design Studies, Matin Vatani, Ali Mohammadi, Donovin D. Lewis, John F. Eastham, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents a comprehensive analysis of the feasibility, cost, and electromagnetic performance of five distinct types of axial flux permanent magnet (AFPM) generators designed for direct-drive wind turbines. The generator configurations investigated include a single-sided AFPM generator with a surface-mounted PM rotor (AFPMG), a double-sided AFPM generator featuring PMs on the stator and a reluctance rotor (AFPMG-RR), a coreless stator AFPM generator with surface PMs (CAFPMG-SPM), and a coreless stator AFPM generator with a Halbach PM array rotor (CAFPMG-Hal). Each generator’s operating principles and configurations are thoroughly explained and compared. Large-scale multi-objective design optimizations were conducted on each type, …

Review Of Coreless Axial Flux Permanent Magnet Machines With Applications Including Electric Aircraft Propulsion, Matin Vatani, Donovin D. Lewis, John F. Eastham, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Axial flux permanent magnet (AFPM) machines with entirely or stator coreless configurations offer significant advantages, including low rotational losses, the absence of cogging torque, minimal torque ripple, and the potential for high specific power density. Advances in permanent magnet (PM) technology and cooling techniques have enabled fully coreless AFPM machines to achieve high magnetic and current loadings without core saturation, making them suitable for high performance applications like electric aircraft propulsion. This paper reviews recent advancements in coreless AFPM machines, tracing their historical and chronological development. Various topologies, including single- and double-sided and multi-disk designs, are examined to identify the …

Speed Variation Based Power Regulation Concept For Dynamic Wireless Charging, Donovin D. Lewis, Sudarshan T. Harave, Omer Onar, Mostak Mohammad, Veda Prakash Galigekere, Gui-Jia Su, Dan Ionel

Electrical and Computer Engineering Graduate Research

On-road wireless charging of electric vehicles (EVs) in-motion could potentially reduce range anxiety or battery size with wide-spread deployment. The planning and implementation of such systems are greatly complicated due to their susceptibility to load variation inherent to traffic flow. This paper proposes a method for derisking the potential for traffic slowdowns by compensating for reduced vehicle speed and investigates how implementation may affect system performance. A load modeling case study is presented at 200kW for a mile of high-speed roadway employing speed-based power regulation with results indicating average power usage and maximum car hosting capability can be reduced by …

Fault-Tolerant High-Power Two-Phase Coreless Afpm Motor-Drive System Concept, Yaser Chulaee, Ali Mohammadi, Matin Vatani, Aaron M. Cramer, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper proposes a fault-tolerant, high-power two-phase coreless axial flux permanent magnet (AFPM) motor drive system concept. Initially, the performance of a two-phase variant of the coreless AFPM machine is compared with that of its three-phase counterpart using both 3D finite element analysis (FEA) and experiments. Thanks to the intrinsic unique features of coreless AFPM machines, the analysis of the results demonstrates that the two-phase configuration has comparable power density (kW/kg) and efficiency. In terms of fault tolerance, the two-phase configuration exhibits superior performance, as the mutual inductance between phases is zero, resulting in an electric machine with magnetically decoupled …

Two-Level Multi-Objective Design Optimization Including Torque Ripple Minimization For Stator Excited Synchronous And Flux Switching Machines, Ali Mohammadi, Oluwaseun A. Badewa, Yaser Chulaee, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Electric machine performance can be enhanced through torque ripple mitigation, which reduces mechanical vibrations and improves system stability and operation. This paper proposes a novel two-level optimization method for synchronous flux-switching and hybrid excitation machines, featuring an innovative multi-point spline shaping approach for torque ripple minimization. The study employs experimentally validated models based on a prototype with a similar topology. The optimization process is implemented on two distinct designs: a 20-pole inner rotor PM-excited stator machine and a 28-pole outer rotor DC-excited stator machine. Analysis results demonstrate that the proposed innovative method significantly reduces torque ripple in both configurations. Force …

Electromagnetic Design Characterization Of Synchronous Machines With Flux Switching Effect Employing Reluctance Rotors And Stators With Pms And Ac Concentrated Coils, Oluwaseun A. Badewa, Ali Mohammadi, Donovin D. Lewis, Somasundaram Essakiappan, Madhav Manjrekar, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper introduces an innovative design for a synchronous electric motor that has phase coils and permanent magnets (PM) embedded in the stator. The electric machine contains both concentrated winded phase coils in dedicated slots and spoke-type permanent magnets solely in the stator. The spoke-type magnet arrangement achieves a high flux intensity even with low remanence non-rare earth permanent magnets. As the rotor has no active electromagnetic components, the risk for demagnetization is reduced and advanced cooling applied to the stator can enable high-speed operation. The principle of operation and polarity of the motor are investigated with a unique approach …

Social Engineering Scenario Generation For Awareness-Based Attack Resilience, Jade Webb

Master's Projects

Social engineering is found in a strong majority of cyberattacks today, as it is a powerful manipulation tactic that does not require the technical skills of hacking. Calculated social engineers utilize simple communication to deceive and exploit their victims, all by capitalizing on the vulnerabilities of human nature: trust and fear. When successful, this inconspicuous technique can lead to millions of dollars in losses. Social engineering is not a one-dimensional technique; criminals often leverage a combination of strategies to craft a robust yet subtle attack. In addition, offenders are continually evolving their methods in efforts to surpass preventive measures. A …

Cca Analysis Using Computer Vision Techniques, Rahul Thakur

Master's Projects

Coral reefs are an essential part of the marine ecosystem. They perform a wide variety of tasks, some directly and others indirectly. They can produce oxygen, absorb carbon dioxide, along with supporting ocean habitat. Crustose Coralline Algae (“CCA”) plays an important role in helping provide structural support to Coral Reef ecosystems. However, global warming is causing ocean water to become more acidic resulting in coral bleaching. This is leading to changes in coral environments and causing coral deaths at alarming rates. Object detection using computer vision techniques, specifically deep learning, can help to monitor coral reef health and identify CCA …

Retrieval-Augmented Generation (Rag) Chatbots: A Comparative Study Of Claude, Gpt-4o, Deepseek, And Llama, Kalindi Vijesh Parekh

Master's Projects

The use of Retrieval-augmented generation (RAG) in chatbot platforms has transformed academic spaces by significantly improving information accessibility. RAG has become a viable approach to upgrading Large Language Models (LLMs) with external knowledge access in real time. With the growing availability of advanced LLMs such as GPT, DeepSeek, Claude, Gemini, and Llama, there is a growing need to compare RAG systems based on different LLMs. This study compares the responses of four different RAG chatbots using popular LLMs against a uniquely designed evaluation dataset. Specifically, the study compares the responses and performance of closed-source (GPT-4o and Claude) and open-source models …

Smart: Semantic Mapping And Analysis For Regional Terrain Using Multi-Scale U-Net And Topsis, Rashmi Sonth

Master's Projects

Accurate land use classification is the backbone for urban planning. But with poor quality satellite images, varied landscapes and structures which are changing faster than ever, it becomes a challenge to define clear boundaries and hence to urban planning. This research explores the application of deep-learning model for land use classification and asses the suitability of the land. The proposed model combines a multi-scale U-Net architecture with Transformer blocks applied on a multi-spectral satellite images that improves the semantic segmentation greatly across the urban and rural regions. Additionally, a patch-wise segmentation is applied to overcome the common problem of feature …

Detecting Ai-Generated News Articles Using Unsupervised Machine Learning Algorithms, Lilou Sicard-Noel

Master's Projects

The widespread adoption of Large Language Models (LLMs) has revolutionized text generation and heightened concerns over misinformation and the erosion of journalistic integrity. Detecting AI-generated text is critical to addressing these challenges, yet current detection methods face adaptability, scalability, and accuracy limitations. This research paper uses machine-learning techniques to explore the classification of human and AI-generated articles, including a mix of human and AI-written content. The primary focus is on evaluating the effectiveness of clustering algorithms (K-Means and Agglomerative Clustering), auto-encoders, and Part-Of- Speech Tag Transition Matrix Log-Likelihood for distinguishing between AI-generated and human-written texts. Our findings reveal that while …

Mycelia: Cross-Chain Data Oracle Using Frost Signatures, Bala Komatireddy

Master's Projects

The interoperability of heterogeneous blockchain networks is the basis for the widespread application of blockchains in various fields. Cross-chain data oracles play a significant role in enabling distributed applications to exchange data and assets across different blockchains, thereby greatly enriching and expanding the application scenarios and use of blockchains. With the continuous advancement of blockchain technology, more and more researchers and industry participants have begun to focus on developing cross-chain data oracles. Current cross-chain data oracles face issues with trust, as they rely on centralized intermediaries or limited validator networks, increasing the risk of manipulation or single points of failure. …