Computer Engineering Commons^™

Emerging Cyber Risks & Threats In Healthcare Systems: A Case Study In Resilient Cybersecurity Solutions, Abdiaziz Abdi, Hajar Bennouri, Anthony Keane

Conference Papers

The exponential growth of digitalisation in healthcare and the ongoing threat of cybersecurity breaches are significant and cast a shadow over the industry’s progress. As the cost of data breaches reaches unprecedented levels, reaching an average of US$10.93 million in 2023 alone, and the frequency of attacks escalates, evidenced by a staggering 60% increase in phishing incidents between 2022 and 2023 reported by Smarttech247, Healthcare infrastructure is at a critical intersection. In this paper, we address the complex relationship between harnessing the potential of digital systems to improve and combating the escalating risks posed by cyber threats. The cyberattack on …

Robust Quantitative Photoacoustic Imaging For Colorectal Cancer Treatment Monitoring, Sitai Kou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Colorectal cancer is the 2nd leading cause of cancer death in the United States and the incidence among population under 50 years old has been increasing for the past decade. Contrary to obvious vascular and morphological structures in pre-treatment colorectal cancer, during treatment and post-treatment colorectal cancer tissue often contains fibrosis and edema in tumor bed. These complications cause difficulties in evaluating tissue response to neoadjuvant chemoradiation therapy with MRI and endoscopy, leading to unnecessary resection of rectum, which increases healthcare cost and impacts patient quality of life. Photoacoustic (PA) imaging is a promising tool for observing blood distribution in …

Deep Learning For Multiple Unmanned Aerial Vehicle Coordination In Air Corridors, Liangkun Yu

Electrical and Computer Engineering ETDs

In the future, city skies will be filled with Unmanned Aerial Vehicles (UAVs) for rapid urban transport, including parcel deliveries and air taxis. NASA's Urban Air Mobility (UAM) envisions UAVs navigating air corridors. These virtual pathways ensure safety and compliance with regulations. However, current research on UAM practical applications is limited. This dissertation focuses on designing air corridors, developing UAV control systems, and ensuring the robustness of control algorithms against disturbances in real-world environments.

Our design features an air corridor system with horizontal lanes and on-off ramps, conceptualized as cylindrical spaces and tori, respectively. To enable each UAV to locally …

Quantum & Classical Machine Learning Studies Of Semiconductor Crystal Epitaxy, Andrew S. Messecar, Steven M. Durbin, Robert A. Makin

Waldo Library Student Exhibits

Molecular beam epitaxy (MBE) is an ultra–high vacuum crystal growth technique for the synthesis of high–purity materials. MBE allows for controlled deposition to the precision of a single atomic layer.

Understanding the optimal synthesis conditions for MBE can enhance experiment design and accelerate the discovery of new materials.

In this study, we apply materials informatics – investigating the utility of both quantum and conventional machine learning algorithms – to a decade’s worth of plasma–assisted MBE (PAMBE) data of GaN and InN. The goal is to investigate the relationships between PAMBE growth conditions and figures of merit for semiconductor crystals.

Learning From Oversampling: A Systematic Exploitation Of Oversampling To Address Data Scarcity Issues In Deep Learning- Based Magnetic Resonance Image Reconstruction, Ibsa Kumara Jalata, Reeshad Khan, Ukash Nakarmi

Computer Science and Computer Engineering Faculty Publications and Presentations

Data acquisitions in Magnetic Resonance Imaging (MRI) are inherently slow due to sequential acquisition protocol. Image reconstruction from under-sampled data is posed as an inverse problem in traditional model-based learning paradigms. Recent data-centric learning frameworks such as deep learning (DL) frameworks are data hungry, and demand a large, labeled training data sets. To address the lack of large training datasets, in MRI reconstructions, researchers approach the problem in two ways: (1) unsupervised method where the model is trained without the presence of fully sampled data. (2) using a method that efficiently use the limited dataset for training purpose. In this …

The Impacts Of Dimensionality, Diffusion, And Directedness On Intrinsic Cross-Model Simulation In Tile-Based Self-Assembly, Daniel Hader, Matthew J. Patitz

Computer Science and Computer Engineering Faculty Publications and Presentations

Motivated by applications in DNA-nanotechnology, theoretical investigations in algorithmic tile-assembly have blossomed into a mature theory. In addition to computational universality, the abstract Tile Assembly Model (aTAM) was shown to be intrinsically universal (FOCS 2012), a strong notion of completeness where a single tile set is capable of simulating the full dynamics of all systems within the model; however, this construction fundamentally required non-deterministic tile attachments. This was confirmed necessary when it was shown that the class of directed aTAM systems, those where all possible sequences of tile attachments result in the same terminal assembly, is not intrinsically universal (FOCS …

Development Of A Rule-Based Monitoring System For Autonomous Heavy Equipment Safety, Amirpooya Shirazi

Department of Construction Engineering and Management: Dissertations, Theses, and Student Research

Roadway construction work zones are constantly exposed to interactions among construction equipment, workers, and vehicles. Furthermore, ensuring safety in these areas is considered a challenging task due to the complexity of the environment. As shown in the rising trend of fatal accidents in roadway work zones, current OSHA regulations in construction safety are insufficient in effectively detecting unsafe situations and mitigating the risks. Furthermore, best practices, such as internal traffic control planning (ITCP), exhibit critical limitations requiring continuous monitoring of active work zones as well as adjustments to the site coordination plans due to the dynamic nature of work zone …

Laser 3d Printing Of Diamond-Based Composite Materials For Thermal Management Applications, Nada Kraiem

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

With the trend towards miniaturization of electrical equipment and the constant increase in power density in semiconductor devices, efficient heat management has become a major concern for researchers. Indeed, this technological evolution imposes increasingly strict constraints in terms of thermal dissipation, necessitating innovative solutions to ensure better durability and reliability of components. In this context, the use of composite materials offering high thermal conductivity (TC) and low coefficient of thermal expansion (CTE) compared to pure metals has become essential to address overheating issues in electronic components.

The utilization of advanced materials such as diamond (D), with exceptional TC and hardness …

Improving Tcp Performance Using P4-Programmable Data Planes, Jose Antonio Gomez Gaona

Theses and Dissertations

The Transmission Control Protocol (TCP) forms the foundation of reliable end-to-end communication and is widely used by many applications for efficient data transfers across the Internet. TCP relies on various congestion control algorithms (CCAs) to manage its response to network congestion. These algorithms ensure fairness among competing flows and optimize the use of available bandwidth. However, since TCP is deployed within end hosts, its capacity to attain visibility of network events is constrained. This limitation arises from the closed nature of non-programmable network devices, which prevents researchers from exploring customized actions in response to network events. Recently, the emergence of …

Studying The Performance Of Object Recognition With Fusion Of Visible Light And Infrared Images With Neural Networks, Plamen Petkov

Doctoral Dissertations and Master's Theses

Neural networks have been used for object detection and recognition in both color and intensity camera images. As the use of infrared cameras, colloquially termed thermal cameras, has increased and costs have decreased, object detection and recognition in infrared camera images have been increasingly studied. An infrared image is treated as an intensity image, just like a grayscale camera image, except the intensity corresponds to infrared radiation instead of visible light. The information provided by these two types of images are different, especially in different lighting and environmental situations, and some types of objects are more easily recognized in visible …

Safe And Efficient Operation Of Mobile Robots In Indoor Environments: A User-Centric Shared Control System With High-Level Navigation Capabilities, Ahmet Saglam

Electrical & Computer Engineering Theses & Dissertations

Hospitalization and isolation can be a traumatic experience for immunocompromised children, especially because they are separated from their families and friends. Social robots have been proposed as a way to improve the quality of care for children hospitalized in isolation by providing alternative means of social interaction and support. Remote control of such robots in a hospital setting, particularly where safety is a major concern, can be a daunting task for young patients.

This dissertation introduces a multilevel shared control system for mobile robots, specifically companion robots in hospital-like indoor spaces. The system integrates user inputs with algorithmic semi-autonomous control …

The Logical Implications Of Open Public Data: Examining The Current Situation, Reviewing The Problems And Advancing The Rule Of Law, Yanlei Cheng, Lin Zhang, Xu Zhang

Journal of Scientific Information Research

[Purpose/significance]Digital rule of law government is a new paradigm of government governance that is compatible with digital China and digital society. Data elements have become an important driving force for high-quality economic development in the era of digital, and public data openness is an important issue in the construction of digital rule of law government. [Method/process]In this paper, the regulations, policies and technical standards of the central government and 10 provinces, including Zhejiang, Shandong, Guizhou, Guangdong, Sichuan, Fujian, Guangxi, Hainan, Jiangxi and Jiangsu as research samples to examine the current system of regulations and policies on the opening up of …

Privacy-Preserved Data Trading Via Verifiable Data Disturbance, Man Zhang, Xinghua Li, Yanbing Ren, Bin Luo, Yinbin Miao, Ximeng Liu, Robert H. Deng

Research Collection School Of Computing and Information Systems

To motivate data owner (DO) to trade data, the existing data trading allows DO to sell the disturbed data to the data consumer (DC), where the disturbance parameter and the data price are negotiated by them, and DO independently adds the disturbance noise to data (usually continuous type) following the negotiation result. However, DOs may violate the negotiated parameter and add more noise to data while obtaining the negotiated price, which damages DC's disturbed data availability. This deficiency is rooted in the absence of supervision and verifiability on DOs’ independent disturbances. Aiming at the above problem, we devise a privacy-preserved …

Artificial Intelligence For Authentication Through Mental Profiling Technique, Nawaf Mazloum, Christine Abou-Saleh, Hassan Mazloum, Charles Anosike

BAU Journal - Science and Technology

A new approach to user authentication using mental profiling saw light, which is a technique that involves measuring an individual's cognitive abilities and psychological traits to create a unique profile, using Artificial Intelligence techniques. These profiles can then be used to identify users securely and efficiently, even in the presence of sophisticated attacks, by harnessing AI-driven systems for mental profile creation and user authentication.

After reviewing the existing literature on authentication and mental profiling, it presents a new mental profiling test that is specifically designed for authentication purposes. The test was evaluated on a sample of 100 users, and results …

Control And Management Of The Balance Of Active And Reactive Power In A Power Supply System With A Solar Power Plant, Narzullo Nuriddinovich Mirzoyev, Siroj Sobirovich Nurov

Chemical Technology, Control and Management

This article discusses the development of a measurement and control system for monitoring and managing the balance of active and reactive power at power plants based on “Green” energy sources. Monitoring and management of the balance of active and reactive power based on a measurement and control system, calculated expressions are developed to solve the problem of reactive power compensation when transmitting electricity at power plants based on “green” energy sources. Reactive power is calculated based on measured active power, and combined reactive power sources generate the reactive power required by the network based on control signals. Schemes for connecting …

Decision-Making Algorithms For Drilling Instrument Control Systems, Fuzayl Fozil Ugli Odilov

Chemical Technology, Control and Management

The control of the movement of the drilling tool and the structure of the well are considered. An effective control algorithm for drilling systems that provides control of well trajectory parameters is analyzed. In technological processes, it is necessary to control several parameters or several systems at the same time. It is considered necessary to create decision-making algorithms for the formation of managerial effects for the control system of such technological processes. The controlled oriented type of the bottom of the drill string was analyzed. Work was carried out on the decision-making algorithm for the processing of control effects. The …

Simulation Of Rice Disease Recognition Based On Improved Attention Mechanism Embedded In Pr-Net Model, Yang Lu, Pengfei Liu, Siyuan Xu, Qiwang Liu, Fuqian Gu, Peng Wang

Journal of System Simulation

Abstract: Aiming at the low accuracy of existing CNN models in identifying rice leaf diseases, a hybrid convolutional neural network model PRC-Net (parallel residual with coordinate attention network) combining parallel structure and residual structure is proposed. A parallel structure is introduced to improve the receptive field of convolution, and the residual structure is combined to achieve the complete and continuous transmission of feature information. An improved spatial attention mechanism is embedded into the backbone model PR-Net to enhance the degree of aggregation of lesion feature information at different scales. In order to further improve the accuracy of disease identification and …

Just-In-Time Learning Energy Consumption Predictive Modeling Method In Multi-Condition Production Process, Sheng Wei, Yan Wang, Zhicheng Ji

Journal of System Simulation

Abstract: Aiming at the problem that the global energy consumption prediction model is only suitable for part of the prediction sample and the model is computationally intensive, the idea of just-in-time learning is introduced, and the local weighted partial least squares method combined with the energy consumption model is used to establish a temporary local energy consumption prediction model. The inertia weights of the particle swarm algorithm are improved, considering the effects of particle fitness, number of iterations and population size on the convergence speed and convergence accuracy of the particle swarm algorithm, a nonlinear change adaptive inertia weight strategy …

Completion Time Simulation Prediction Method For Aircraft Assembly Process With Batch And Sortie, Changjian Jiang, Hu Fan, Tao Luo, Wen Yuan, Zehao He

Journal of System Simulation

Abstract: Aiming at the product differentiation analysis limitation of traditional discrete event simulation method, a simulation prediction method for aircraft assembly process with batch and sortie is proposed. Around the aircraft sortie number, the formal definition of various basic elements and interactions in the assembly process with batch and sortie is studied, and the construction of station and whole line simulation model is carried out. The simulation promotion framework and execution mechanism supporting the product differentiation analysis are studied. Based on the simulation results, a method for predicting the completion time of sorties based on interval estimation method is proposed. …

Adaptive Pid Control Algorithm Based On Ppo, Zhiyong Zhou, Fei Mo, Kai Zhao, Yunbo Hao, Yufeng Qian

Journal of System Simulation

Abstract: A six-axis robotic arm is built and simulated in a complex control environment with disturbances by using MATLAB physics engine and Python, which provides a trial-and-error environment for the robotic arm training that could not be provided in reality. Proximal policy optimization(PPO) algorithm in reinforcement learning is proposed to improve the traditional PID control algorithm. By introducing the multi-agent idea and on the basis of the different effects of the three parameters of PID on control system and the characteristics of the six-axis robotic arm, the three parameters are separately trained as different intelligent individuals to achieve a new …