Engineering Commons^™

Light Auditor: Power Measurement Can Tell Private Data Leakage Through Iot Covert Channels, Woosub Jung, Kailai Cui, Kenneth Koltermann, Junjie Wang, Chunsheng Xin, Gang Zhou

Electrical & Computer Engineering Faculty Publications

Despite many conveniences of using IoT devices, they have suffered from various attacks due to their weak security. Besides well-known botnet attacks, IoT devices are vulnerable to recent covert-channel attacks. However, no study to date has considered these IoT covert-channel attacks. Among these attacks, researchers have demonstrated exfiltrating users' private data by exploiting the smart bulb's capability of infrared emission.

In this paper, we propose a power-auditing-based system that defends the data exfiltration attack on the smart bulb as a case study. We first implement this infrared-based attack in a lab environment. With a newly-collected power consumption dataset, we pre-process …

Transfer Learning Using Infrared And Optical Full Motion Video Data For Gender Classification, Alexander M. Glandon, Joe Zalameda, Khan M. Iftekharuddin, Gabor F. Fulop (Ed.), David Z. Ting (Ed.), Lucy L. Zheng (Ed.)

Electrical & Computer Engineering Faculty Publications

This work is a review and extension of our ongoing research in human recognition analysis using multimodality motion sensor data. We review our work on hand crafted feature engineering for motion capture skeleton (MoCap) data, from the Air Force Research Lab for human gender followed by depth scan based skeleton extraction using LIDAR data from the Army Night Vision Lab for person identification. We then build on these works to demonstrate a transfer learning sensor fusion approach for using the larger MoCap and smaller LIDAR data for gender classification.

Long-Range Aceo Phenomena In Microfluidic Channel, Diganta Dutta, Keifer Smith, Xavier Palmer

Electrical & Computer Engineering Faculty Publications

Microfluidic devices are increasingly utilized in numerous industries, including that of medicine, for their abilities to pump and mix fluid at a microscale. Within these devices, microchannels paired with microelectrodes enable the mixing and transportation of ionized fluid. The ionization process charges the microchannel and manipulates the fluid with an electric field. Although complex in operation at the microscale, microchannels within microfluidic devices are easy to produce and economical. This paper uses simulations to convey helpful insights into the analysis of electrokinetic microfluidic device phenomena. The simulations in this paper use the Navier–Stokes and Poisson Nernst–Planck equations solved using COMSOL …

Special Section Editorial: Artificial Intelligence For Medical Imaging In Clinical Practice, Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, Marios Gavrielides

Electrical & Computer Engineering Faculty Publications

This editorial introduces the JMI Special Section on Artificial Intelligence for Medical Imaging in Clinical Practice.

Commentary On Healthcare And Disruptive Innovation, Hilary Finch, Affia Abasi-Amefon, Woosub Jung, Lucas Potter, Xavier-Lewis Palmer

Electrical & Computer Engineering Faculty Publications

Exploits of technology have been an issue in healthcare for many years. Many hospital systems have a problem with “disruptive innovation” when introducing new technology. Disruptive innovation is “an innovation that creates a new market by applying a different set of values, which ultimately overtakes an existing market” (Sensmeier, 2012). Modern healthcare systems are historically slow to accept new technological advancements. This may be because patient-based, provider-based, or industry-wide decisions are tough to implement, giving way to dire consequences. One potential consequence is that healthcare providers may not be able to provide the best possible care to patients. For example, …

Social-Engineering, Bio-Economies, And Nation-State Ontological Security: A Commentary, Brandon Griffin, Keitavius Alexander, Xavier-Lewis Palmer, Lucas Potter

Electrical & Computer Engineering Faculty Publications

Biocybersecurity is an evolving discipline that aims to identify the gaps and risks associated with the convergence of Biology (the science of life and living organisms) and cybersecurity (the science, study, and theory of cyberspace and cybernetics) to protect the bioeconomy. The biological industries’ increased reliance on digitization, automation, and computing power has resulted in benefits for the scientific community, it has simultaneously multiplied the risk factors associated with industrial espionage and the protection of data both commercial and proprietary. The sensitive and potentially destructive power of this data and its access inherently poses a risk to the national and …

Understanding And Assessing Demographic (In)Equity Resulting From Extreme Heat Exposure Due To Lack Of Tree Canopies In Norfolk, Va Using Agent-Based Modeling, Virginia Zamponi, Kevin O'Brien, Erik Jensen, Brandon Feldhaus, Russell Moore, Christopher J. Lynch, Ross Gore

VMASC Publications

Prolonged exposure to extreme heat can result in illness and death. In urban areas of dense concentrations of pavement, buildings, and other surfaces that absorb and retain heat, extreme heat conditions can arise regularly and create harmful environmental exposures for residents daily during certain parts of the year. Tree canopies provide shade and help to cool the environment, making mature trees with large canopies a simple and effective way to reduce urban heat. We develop a demographically representative 1 (agent): 1 (person) agent-based model to understand the extent to which different demographics of residents in Norfolk, VA are equitably shaded …

Computational Decision Support For Socio-Technical Awareness Of Land-Use Planning Under Complexity—A Dam Resilience Planning Case Study, Andreas Tolk, Jennifer A. Richkus, F. Leron Shults, Wesley J. Wildman

VMASC Publications

Land-use planning for modern societies requires technical competence as well as social competence. We therefore propose an integrative solution enabling better land-use planning and management through better-informed decision-making. We adapt a method developed for cross-disciplinary team building to identify the stakeholders and their various objectives and value systems. We use these results to populate artificial societies embedded into a dynamic data analytics framework as a tool to identify, explore, and visualize the challenges resulting from the different objectives and value systems in land-use planning and management. To prove the feasibility of the proposed solution, we present two use cases from …

A Structured Narrative Prompt For Prompting Narratives From Large Language Models: Sentiment Assessment Of Chatgpt-Generated Narratives And Real Tweets, Christopher J. Lynch, Erik J. Jensen, Virginia Zamponi, Kevin O'Brien, Erika Frydenlund, Ross Gore

VMASC Publications

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents' perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt …

Efficient Maritime Object Detection And Validation For Enhancing Safety Of Uncrewed Marine Systems, Ahmed Saglam, Yiannis Papelis

VMASC Publications

Safe operation of uncrewed maritime systems is a major concern in the presence of other vehicles or obstacles. Typically, perception algorithms utilize sensor data to identify obstacles that must be avoided, and AI algorithms are used to interpret raw sensor data for use in navigation and object avoidance algorithms. However, perception algorithms are typically computationally expensive. In this paper, we present an efficient method for detecting obstacles using raw lidar data in the form of range or Point Cloud, employing computationally efficient techniques that do not depend on trained models or AI matching. The approach
converts the sensor readings into …

Energy-Efficient Multi-Rate Opportunistic Routing In Wireless Mesh Networks, Mohammad Ali Mansouri Khah, Neda Moghim, Nasrin Gholami, Sachin Shetty

VMASC Publications

Opportunistic or anypath routing protocols are focused on improving the performance of traditional routing in wireless mesh networks. They do so by leveraging the broadcast nature of the wireless medium and the spatial diversity of the network. Using a set of neighboring nodes, instead of a single specific node, as the next hop forwarder is a crucial aspect of opportunistic routing protocols, and the selection of the forwarder set plays a vital role in their performance. However, most opportunistic routing protocols consider a single transmission rate and power for the nodes, which limits their potential. To address this limitation, this …

Skin Lesion Segmentation In Dermoscopic Images With Noisy Data, Norsang Lama, Jason Hagerty, Anand Nambisan, Ronald Joe Stanley, William Van Stoecker

Electrical and Computer Engineering Faculty Research & Creative Works

We Propose a Deep Learning Approach to Segment the Skin Lesion in Dermoscopic Images. the Proposed Network Architecture Uses a Pretrained Efficient Net Model in the Encoder and Squeeze-And-Excitation Residual Structures in the Decoder. We Applied This Approach on the Publicly Available International Skin Imaging Collaboration (ISIC) 2017 Challenge Skin Lesion Segmentation Dataset. This Benchmark Dataset Has Been Widely Used in Previous Studies. We Observed Many Inaccurate or Noisy Ground Truth Labels. to Reduce Noisy Data, We Manually Sorted All Ground Truth Labels into Three Categories — Good, Mildly Noisy, and Noisy Labels. Furthermore, We Investigated the Effect of Such …

Enhancing Control Room Operator Decision Making: An Application Of Dynamic Influence Diagrams In Formaldehyde Manufacturing, Joseph Mietkiewicz, Anders L. Madsen

Articles

Intoday’s rapidly evolving industrial landscape, control room operators must grapple with an ever-growing array of tasks and respon sibilities. One major challenge facing these operators is the potential for task overload, which can lead to decision fatigue and increased reliance on cognitive biases. To address this issue, we propose the use of dynamic influence diagrams (DID) as the core of our decision support system. By monitoring the process over time and identifying anomalies, DIDs can recommend the most effective course of action based on a probabilistic assessment of future outcomes. Instead of letting the operator choose or search for the …

Ovulation Prediction Using Random Forest Algorithm On Physiological Data, Kimberly D. Laynes

UNF Graduate Theses and Dissertations

Human infertility rates are on the rise -- studies have shown that one in every four women have trouble conceiving and every year those rates are rising [Halleran22]. This trend motivates procedures such as in-vitro fertilization (IVF) and intrauterine insemination (IUI) to produce a pregnancy. Such procedures are not only intricate and expensive but also carry potential unintended consequences for women's physical and mental well-being. A more profound comprehension of the menstrual cycle and its multiple phases, particularly detecting the ovulation period itself, promotes optimized treatment outcomes and reduces associated risks. To facilitate ovulation detection, new sensing technologies built into …

Extracting Road Surface Marking Features From Aerial Images Using Deep Learning, Michael Kimollo

UNF Graduate Theses and Dissertations

The traffic and roadway safety agencies spend significant efforts each year collecting roadway data, including lane configurations and other road surface marking data, such as areas with school zone markings, sidewalks, left turns, right turns, bicycle lanes, etc., for safety analysis and planning purposes. The current manual data collection methods pose significant operational and quality control challenges as they are costly and prone to errors. In addition to that the manual data collection is labor intensive and takes too much time involving high equipment costs, questionable data accuracy guarantees, and concerns about the safety of the crew.

This study aims …

Development Of High Kinetic Inductance Superconducting Nanowire Devices On High Permittivity Strontium Titanate Substrates, Jamie Timmons

UNF Graduate Theses and Dissertations

This thesis involves the fabrication and characterization of devices made from two different superconducting materials: yttrium barium copper oxide (YBCO), a high-TC complex oxide, and niobium nitride (NbN), a low-TC transition metal nitride. Both types of devices are fabricated on strontium titanate substrates, which provides a good lattice match to YBCO and also an extremely large permittivity at low temperature. We demonstrate that wet etching of YBCO thin films via bromine can be a viable microfrabriation technique for the material. Using approximately 35 nm thick epitaxially grown YBCO on an STO substrate, we were able to fabricate YBCO “microwires” with …

Alternatives To Reducing Aviation Fuel-Burn With Technology: Fully Electric Autonomous Taxibot, Denzil Neo

Student Works

Aircraft taxiing operations in the aerodrome were identified to consume the most jet fuel apart from the cruise phase of the flight. This was also well supported by various research associating taxi operations at large, congested airports, with high jet fuel consumption, high carbon emissions, and noise pollution. Existing literature recognised the potential to address the environmental issues of aerodrome taxi operations by operating External or Onboard Aircraft Ground Propulsion Systems (AGPS). Designed to power aircraft with sources other than their main engines, external Aircraft Ground Power Systems (AGPS) have shown the potential to significantly cut jet fuel consumption and …

Directional Speaker Poster, Eugene Ng, Bryan Wong, Ruhaan Das

Student Works

Changi Airport is set to expand with a new terminal, Terminal 5. Currently, many of the airport's processes are manual, requiring a high dependence on staff. This proposal aims to incorporate automation and AI for a smoother passenger experience.

Multivariate Regression And Variance In Concrete Curing Methods: Strength Prediction With Experiments, Haiyan Sally Xie, Sai Ram Gandla, Owen Shi, Pranshoo Solanki

Faculty Publications – Technology

Because concrete strengths and quality are affected by various factors, multivariate regression models are often used to analyze the differences between predicted and target outputs. However, the variableness of a predicted output and how individual input parameters affect prediction reliabilities are still uncertain in practical applications, especially for the prediction of compressive strengths of concrete. This study aims to develop multivariate models for predicting concrete strengths and providing the variance analysis of prediction results by comparisons with experiment outcomes. First, this paper provides an in-depth examination of established variance analysis methods in the context of commonly used multivariate regression models. …

Peer-To-Peer Energy Trading In Smart Residential Environment With User Behavioral Modeling, Ashutosh Timilsina

Theses and Dissertations--Computer Science

Electric power systems are transforming from a centralized unidirectional market to a decentralized open market. With this shift, the end-users have the possibility to actively participate in local energy exchanges, with or without the involvement of the main grid. Rapidly reducing prices for Renewable Energy Technologies (RETs), supported by their ease of installation and operation, with the facilitation of Electric Vehicles (EV) and Smart Grid (SG) technologies to make bidirectional flow of energy possible, has contributed to this changing landscape in the distribution side of the traditional power grid.

Trading energy among users in a decentralized fashion has been referred …

New Host Records Of Apicomplexan Blood Parasites (Haemogregarinidae And Hepatozoidae) Infecting Two Reptiles (Testudines; Ophidia) From Arkansas, C.T. Mcallister, H.W. Robison

Journal of the Arkansas Academy of Science

Relatively few records of apicomplexan blood parasites from reptiles in Arkansas have been published although the effects of these parasites on reptilian health may be of concern. Using photomicrographs we describe the morphotypes of parasite gamonts found in blood samples from the Midland smooth softshell turtle, Apalone mutica mutica, and a western Milksnake Lampropeltis gentilis from Arkansas. The turtle possessed four distinct morphological gamont forms of a Haemogregarina sp. The snake possessed two morphological forms of gamonts of a Hepatozoon sp. Both infections are new host records and the western milksnake has not been described as a host elsewhere for …

Hemoparasites (Apicomplexa: Hepatozoon; Kinetoplastida: Trypanosoma) Of Two Anurans (Hylidae; Ranidae), From Polk County, Arkansas, C.T. Mcallister, H.W. Robison

Journal of the Arkansas Academy of Science

Arkansas supports 26 species/subspecies of anurans and only one (4%), the green frog, Rana clamitans, has been previously reported with hemoparasites. Here, we collected blood samples from three species of anurans, five American green treefrogs, Dryophytes cinereus, five American bullfrogs, Rana catesbeianus, two southern leopard frogs, Rana sphenocephalus utricularius, and two Fowler’s toads, Anaxyrus fowleri from Polk County and examined each for hemoparasites. American green treefrogs and American bullfrogs harbored hemoparasites, including two (40%) D. cinereus and four (80%) R. catesbeianus with trypanosomes, and one (20%) R. catesbeiana with a Hepatozoon sp. This is the first time these two anurans …

Journal Acknowledgements And Editorial Board, Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

Table Of Contents, Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

Genetic Algorithm For Solving A Just-In-Time Inventory Model With Imperfect Rework Implemented In A Serial Multi-Echelon System, Hsien-Chung Tsao, Cheng-Chi Chung, Hsuan-Shih Lee, Chih-Ping Lin, Yan-Yun Tu, Ssu-Chi Lin

Journal of Marine Science and Technology–Taiwan

As global industrial competition intensifies, enterprises can achieve substantial competitive advantages in the supply chain management environment by promptly meeting customer demands and efficiently reducing both supply and demand costs. This paper proposes an inventory model for supply chain optimization that considers uncertain delivery lead times and defective products. Solving the model requires solving a nonlinear mixed-integer problem, which traditionally requires considerable time. Solutions to nondeterministic polynomial-time hard problems with high complexity and difficulty are often obtained using heuristic algorithms. Among these algorithms, genetic algorithms have high efficiency and quality. Therefore, we employed a genetic algorithm to solve the proposed …

An Mrf Model-Based Study On The Effect Of Fishes Upon The Characteristics Of Flow Field Of An Aquaculture Tank, Xian-Ying Shi, Zheng-Zheng Huang, Meng Li, Yinxin Zhou, Xiao-Zhong Ren, Hang-Fei Liu, Shu-Peng Du

Journal of Marine Science and Technology–Taiwan

The study aims to investigate the effect of fish movement on the flow field in the aquaculture tank of a recirculating water aquaculture system. Herein, based on the Navier-Stokes equations and the RNG k-ε turbulence model, the flow field in the aquaculture tank with fish movement was numerically simulated using the multiple reference frame (MRF) model and compared with the numerical simulation results of the fishless aquaculture tank. The results revealed that the overall mean flow velocity in the tank decreased significantly when the fish swam counter-currently with a fixed trajectory, and the overall mean flow velocity increased slightly when …

Occurrence Of Predation Of Juvenile Chum Salmon (Oncorhynchus Keta) By Chub Mackerel (Scomber Japonicus) And Spotted Mackerel (Scomber Australasicus) In Miyako Bay, Iwate Prefecture, Japan, Kei Sasaki, Miwa Yatsuya, Daisuke Shimizu, Daisuke Ojima, Shinji Komatsu

Journal of Marine Science and Technology–Taiwan

In recent years, chub mackerel (Scomber japonicus) and spotted mackerel (Scomber australasicus) have started migrating to the coastal areas off Iwate Prefecture earlier than they did previously, resulting in a geographic overlap between hatchery-bred juvenile chum salmon (Oncorhynchus keta) released at sea and the occurrence of predatory mackerel. To clarify whether the mackerels prey on the juvenile chum salmon, we captured adult mackerels by angling during the period when these species overlap in Miyako Bay, Iwate Prefecture. After capture, the stomach contents of the mackerel were examined using a combination of visual examinations and DNA metabarcoding analysis. As a result, …

Using Modflow To Assess Groundwater Storage Enhancement Via A Floodplain Infiltration Basin, Lindsay Henning

All Master's Theses

Delaying groundwater discharge into rivers until it is critically needed during baseflow conditions provides promise for lowering elevated stream temperatures and improving habitat for aquatic species. Increasing groundwater storage may accomplish this in locations where excess spring runoff can be captured and allowed to infiltrate into the subsurface for later beneficial use, a process known as Managed Aquifer Recharge (MAR). Here, MAR via an infiltration basin is considered at a site along the Teanaway River in central Washington State. The effects of simulated ephemeral ponds of sizes varying from 554 m³ to 2430 m³ (0.449 acre-feet to 1.97 …

Breast Density Classification Using Deep Learning, Conrad Thomas Testagrose

UNF Graduate Theses and Dissertations

Breast density screenings are an accepted means to determine a patient's predisposed risk of breast cancer development. Although the direct correlation is not fully understood, breast cancer risk increases with higher levels of mammographic breast density. Radiologists visually assess a patient's breast density using mammogram images and assign a density score based on four breast density categories outlined by the Breast Imaging and Reporting Data Systems (BI-RADS). There have been efforts to develop automated tools that assist radiologists with increasing workloads and to help reduce the intra- and inter-rater variability between radiologists. In this thesis, I explored two deep-learning-based approaches …

Carbon Capture, Utilization, And Storage, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet about carbon capture, utilization, and storage (CCUS) and the Energy & Environmental Research Center’s CCUS capabilities. Includes information on the Plains CO₂ Reduction (PCOR) Partnership initiative, Brine Extraction and Storage Test (BEST), Carbon Storage Assurance Facility Enterprise (CarbonSAFE), Red Trail Energy Carbon Capture and Storage, a feed study at Coal Creek Station, Bell Creek and Cedar Creek anticline projects, and Partnership for CO₂ Capture (PCO₂C).