Computer Engineering Commons^™

Sustainability In An It Context, Dikran Kassabian

Sustainability Research & Practice Seminar Presentations

No abstract provided.

Effective Geometric Modeling For Scientific Computing And Forensic Reconstruction, Celong Liu

LSU Doctoral Dissertations

Geometric modeling is a fundamental and critical problem for many computer graphic and computer vision problems. We usually want to build a parameterization which establishes a low-distortion one-to-one map between geometric data and canonical parametric domain, and it is a fundamental tool to support many visual data processing tasks such as mesh generation, finite element simulations, visual analytics, geometric reconstruction, etc. In this dissertation, I studied two problems. The first is to construct low- distortion canonical (polycube) parameterization of large-scale geometric regions, with which high-quality semi-structured quad meshes can be generated and used to facilitate more efficient scientific computing. The …

An Extensive Game-Based Resource Allocation For Securing D2d Underlay Communications, Oleksii Rudenko, Yuhong Liu, Chenwei Wang, Susanto Rahardja

Computer Science and Engineering

Device-to-device (D2D) communication has been increasingly attractive due to its great potential to improve cellular communication performance. While resource allocation optimization for improving the spectrum efficiency is of interest in the D2D-related work, communication security, as a key issue in the system design, has not been well investigated yet. Recently, a few studies have shown that D2D users can actually serve as friendly jammers to help enhance the security of cellular user communication against eavesdropping attacks. However, only a few studies considered the security of D2D communications. In this paper, we consider the secure resource allocation problem, particularly, how to …

Stochastic Methods To Find Maximum Likelihood For Spam E-Mail Classification, Seyed M. -H. Mansourbeigi

Computer Science Student Research

The increasing volume of unsolicited bulk e-mails leads to the need for reliable stochastic spam detection methods for the classification of the received sequence of e-mails. When a sequence of emails is received by a recipient during a time period, the spam filters have already classified them as spam or not spam. Due to the dynamic nature of the spam, there might be emails marked as not spam but are actually real spams and vice versa. For the sake of security, it is important to be able to detect real spam emails. This paper utilizes stochastic methods to refine the …

High-Performing Pgm-Free Aemfc Cathodes From Carbon-Supported Cobalt Ferrite Nanoparticles, Xiong Peng, Varchaswal Kashyap, Benjamin Ng, Sreekumar Kurungot, Lianqin Wang, John R. Varcoe, Mustain E William

Faculty Publications

Efficient and durable non-precious metal electrocatalysts for the oxygen reduction reaction (ORR) are highly desirable for several electrochemical devices, including anion exchange membrane fuel cells (AEMFCs). Here, cobalt ferrite (CF) nanoparticles supported on Vulcan XC-72 carbon (CF-VC) were created through a facile, scalable solvothermal method. The nano-sized CF particles were spherical with a narrow particle size distribution. The CF-VC catalyst showed good ORR activity, possessing a half-wave potential of 0.71 V. Although the intrinsic activity of the CF-VC catalyst was not as high as some other platinum group metal (PGM)-free catalysts in the literature, where this catalyst really shined was …

Diagnosis Of Brain Diseases Via Multi-Scale Time-Series Model, Zehua Zhang, Junhai Xu, Jijun Tang, Quan Zou, Fei Guo

Faculty Publications

The functional magnetic resonance imaging (fMRI) data and brain network analysis have been widely applied to automated diagnosis of neural diseases or brain diseases. The fMRI time series data not only contains specific numerical information, but also involves rich dynamic temporal information, those previous graph theory approaches focus on local topology structure and lose contextual information and global fluctuation information. Here, we propose a novel multi-scale functional connectivity for identifying the brain disease via fMRI data. We calculate the discrete probability distribution of co-activity between different brain regions with various intervals. Also, we consider nonsynchronous information under different time dimensions, …

Recipe For Disaster, Zac Travis

MFA Thesis Exhibit Catalogs

Today’s rapid advances in algorithmic processes are creating and generating predictions through common applications, including speech recognition, natural language (text) generation, search engine prediction, social media personalization, and product recommendations. These algorithmic processes rapidly sort through streams of computational calculations and personal digital footprints to predict, make decisions, translate, and attempt to mimic human cognitive function as closely as possible. This is known as machine learning.

The project Recipe for Disaster was developed by exploring automation in technology, specifically through the use of machine learning and recurrent neural networks. These algorithmic models feed on large amounts of data as a …

Wiwear: Wearable Sensing Via Directional Wifi Energy Harvesting, Huy Vu Tran, Archan Misra, Jie Xiong, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Energy harvesting, from a diverse set of modes such as light or motion, has been viewed as the key to developing batteryless sensing devices. In this paper, we develop the nascent idea of harvesting RF energy from WiFi transmissions, applying it to power a prototype wearable device that captures and transmits accelerometer sensor data. Our solution, WiWear, has two key innovations: 1) beamforming WiFi transmissions to significantly boost the energy that a receiver can harvest ~23 meters away, and 2) smart zero-energy, triggering of inertial sensing, that allows intelligent duty-cycled operation of devices whose transient power consumption far exceeds what …

Long-Term Trajectories Of Human Civilization, Seth D. Baum, Stuart Armstrong, Timoteus Ekenstedt, Olle Häggström, Robin Hanson, Karin Kuhlemann, Matthijs M. Maas, James D. Miller, Markus Salmela, Anders Sandberg, Kaj Sotala, Phil Torres, Alexey Turchin, Roman V. Yampolskiy

Faculty and Staff Scholarship

Purpose: This paper aims to formalize long-term trajectories of human civilization as a scientific and ethical field of study. The long-term trajectory of human civilization can be defined as the path that human civilization takes during the entire future time period in which human civilization could continue to exist. Design/methodology/approach: This paper focuses on four types of trajectories: status quo trajectories, in which human civilization persists in a state broadly similar to its current state into the distant future; catastrophe trajectories, in which one or more events cause significant harm to human civilization; technological transformation trajectories, in which radical technological …

Statistical Algorithm For Nonuniformity Correction In Focal-Plane Arrays, Majeed M. Hayat, Sergio N. Torres, Ernest Armstrong, Stephen C. Cain, Brian Yasuda

Electrical and Computer Engineering Faculty Research and Publications

A statistical algorithm has been developed to compensate for the fixed-pattern noise associated with spatial nonuniformity and temporal drift in the response of focal-plane array infrared imaging systems. The algorithm uses initial scene data to generate initial estimates of the gain, the offset, and the variance of the additive electronic noise of each detector element. The algorithm then updates these parameters by use of subsequent frames and uses the updated parameters to restore the true image by use of a least-mean-square error finite-impulse-response filter. The algorithm is applied to infrared data, and the restored images compare favorably with those restored …

Hybrid Field Oriented And Direct Torque Control For Sensorless Bldc Motors Used In Aerial Drones, Kellen Carey, Nathan M. Zimmerman, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this study, a sensorless hybrid control scheme for brushless direct current (BLDC) motors for use in multirotor aerial vehicles is introduced. In such applications, the control scheme must satisfy high-performance demands for a wide range of rotor speeds and must be robust to motor parameter uncertainties and measurement noise. The proposed controller combines field-oriented control (FOC) and direct torque control (DTC) techniques to take benefit of the advantages offered by each of these techniques individually. Simulation results demonstrate the effectiveness of the proposed control scheme over a wide range of rotor speeds as well as good robustness against parameter …

Computationally Efficient Strand Eddy Current Loss Calculation In Electric Machines, Alireza Fatemi, Dan M. Ionel, Nabeel Demerdash, Dave A. Staton, Rafal Wrobel, Yew Chuan Chong

Electrical and Computer Engineering Faculty Research and Publications

A fast finite element (FE) based method for the calculation of eddy current losses in the stator windings of randomly wound electric machines is presented in this paper. The method is particularly suitable for implementation in large-scale design optimization algorithms where a qualitative characterization of such losses at higher speeds is most beneficial for identification of the design solutions that exhibit the lowest overall losses including the ac losses in the stator windings. Unlike the common practice of assuming a constant slot fill factor s _f for all the design variations, the maximum s _f in the developed method is …

Freelabel: A Publicly Available Annotation Tool Based On Freehand Traces, Philipe A. Dias, Zhou Shen, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

Large-scale annotation of image segmentation datasets is often prohibitively expensive, as it usually requires a huge number of worker hours to obtain high-quality results. Abundant and reliable data has been, however, crucial for the advances on image understanding tasks recently achieved by deep learning models. In this paper, we introduce FreeLabel, an intuitive open-source web interface that allows users to obtain high-quality segmentation masks with just a few freehand scribbles, in a matter of seconds. The efficacy of FreeLabel is quantitatively demonstrated by experimental results on the PASCAL dataset as well as on a dataset from the agricultural domain. Designed …

A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some new areas that present more opportunities. Different methods have been proposed based on different categories of learning, including supervised, semi-supervised, and un-supervised learning. Experimental results show state-of-the-art performance using deep learning when compared to traditional machine learning approaches in the fields of image processing, computer vision, speech recognition, machine translation, art, medical imaging, medical information processing, robotics and control, bioinformatics, natural language …

Frameup: An Incriminatory Attack On Storj: A Peer To Peer Blockchain Enabled Distributed Storage System, Xiaolu Zhang, Justin Grannis, Ibrahim Baggili, Nicole Lang Beebe

Electrical & Computer Engineering and Computer Science Faculty Publications

In this work we present a primary account of frameup, an incriminatory attack made possible because of existing implementations in distributed peer to peer storage. The frameup attack shows that an adversary has the ability to store unencrypted data on the hard drives of people renting out their hard drive space. This is important to forensic examiners as it opens the door for possibly framing an innocent victim. Our work employs Storj as an example technology, due to its popularity and market size. Storj is a blockchain enabled system that allows people to rent out their hard drive space …

Decreasing Technology Design Costs By Using Youtube Video To Evaluate User Acceptance, Tom Chappelear

UNO Student Research and Creative Activity Fair

User acceptance is a measure that contributes to technology feasibility which is a decision point that entrepreneurs use to help make better investment decisions (Hoffer, 2011). User acceptance testing is part of a design strategy where the system designer attempts to minimize risks and provide design information that an entrepreneur can use to make better investment decisions (Hoffer, 2011). A user acceptance testing instruments can range from a low-cost coffeeshop review to expensive lab-based user testing (Shneiderman, 2017). This study builds upon the User Acceptance of Information Technology (UTAUT) model to measure user acceptance for the system being evaluated (Venkatesh, …

Estimating Variations In Metabolic Cost Within The Stride Cycle During Level And Uphill Walking, Arash Mohammadzadeh Gonabadi

UNO Student Research and Creative Activity Fair

Indirect calorimetry provides the average cost of a stride cycle and prevents from identifying which part of the gait cycle causes increased metabolic cost in patients, however, recent simulation methods allow estimating the time profile of metabolic cost within the stride cycle. In this study, we compare the estimations of the time profile of the metabolic cost of two simulation methods for level and uphill walking. We used kinematic, kinetic and electromyography data from level and uphill walking (one participant) to estimate the time profiles of metabolic cost using the muscle-level metabolic model of Umberger using electromyography and kinematic data …

A Correlation Network Model For Managing Safety And Performance Issues In Bridges And Civil Infrastructures, Prasad Chetti

UNO Student Research and Creative Activity Fair

Many recent studies have shown that a large percentage of bridges in many parts of the world have low safety rating. National Bridge Inventory (NBI) database contains the information of more than 600,000 bridges, where each bridge has 116 parameters. Current safety inspections require bridge inspectors to manually inspect each bridge every few years. Manpower and budget constraints limit such approach from inspecting the bridges more frequently. Clearly, more efficient approaches need to be developed to improve the process of bridge inspection and increase the overall safety of bridges and civil infrastructures. In this study, we propose a Correlation Network …

A Shared-Memory Algorithm For Updating Single-Source Shortest Paths In Large Weighted Dynamic Networks, Sriram Srinivasan

UNO Student Research and Creative Activity Fair

In the last decade growth of social media, increased the interest of network algorithms for analyzing large-scale complex systems. The networks are highly unstructured and exhibit poor locality, which has been a challenge for developing scalable parallel algorithms. The state-of-the-art network algorithms such as Prim's algorithm for Minimum Spanning Tree, Dijkstra's algorithm for Single Source Shortest Path and ISPAN algorithm for detecting strongly connected components are designed and optimized for static networks. The networks which change with time i.e. the dynamic networks such as social networks, the above-mentioned approaches can only be utilized if they are recomputed from scratch each …

Mobility-Based Models For Advancing Diagnostic/Predictive Healthcare, Elham Rastegari

UNO Student Research and Creative Activity Fair

Functional ability has been always considered as one of the important determining factors of individuals’ health and quality of life. Traditional movement analysis systems require expensive facilities and frequent visits for patients to specialized laboratories. Portability and affordability of wearable sensors along with their improved accuracy and capability of monitoring movement during daily activities make them a potential alternative for analyzing mobility patterns for clinical and health assessment purposes. Wearable-based movement data, when combined with other relevant clinical or laboratory data, could enhance evidence-based healthcare and data-driven Clinical Decision Support Systems (CDSS). Utilizing the data from wearable devices, many researchers …

Urea Functionalization Of Ultrasound-Treated Biochar: A Feasible Strategy For Enhancing Heavy Metal Adsorption Capacity, Baharak Sajjadi, James William Broome, Wei Yin Chen, Daniell L. Mattern, Nosa O. Egiebor, Nathan Hammer, Cameron L. Smith

Faculty and Student Publications

© 2018 Elsevier B.V. The main objective of a series of our researches is to develop a novel acoustic-based method for activation of biochar. This study investigates the capability of biochar in adsorbing Ni(II) as a hazardous contaminant and aims at enhancing its adsorption capacity by the addition of extra nitrogen and most probably phosphorous and oxygen containing sites using an ultrasono-chemical modification mechanism. To reach this objective, biochar physically modified by low-frequency ultrasound waves (USB) was chemically treated by phosphoric acid (H3PO4) and then functionalized by urea (CO(NH2)2). Cavitation induced by ultrasound waves exfoliates and breaks apart the regular …

Making Personal Goals More Achievable, Adam Carlson

ENGS 86 Independent Projects (AB Students)

Achieving long-term goals has a large impact on one’s life. However, this success requires focused, consistent work even when the achievement is not imminent. Presently, we turn to calendars and task management applications for help. But, these tools quickly become cluttered making it difficult to visualize progress. I created an iPhone application which emphasizes long-term thinking. First-time users must provide three long-term goals with deadlines. Then, they have the opportunity to add smaller, to-do items to their week. For each item, the user must specify a long-term goal to which it is associated. The long-term association ensures users stay focused.

3d Scanning Of Pottery Sherds For Archaeology, Zoe Yu, Jessica E. Teipel, Joseph P. Leonor, Julia A. Holgado, Zhuofan Zhang

ENGS 89/90 Reports

Archaeological digs typically last up to a few months and can produce up to 2000 sherds of pottery a day. Archaeologists cannot legally return home with their findings, so they must document them at the dig site. Current methods of documenting sherds are costly, time-consuming, and have low throughput in terms of sherds documented. Thus this team has aimed to create a scanner capable of collecting data at a rate of about one minute per sherd, allowing the user to scan 500 sherds over a 10 hour work day. Ideally, the scanner should produce 3D models of the sherds consistently …

10_Fdr_Written_Project Central Vehicle Controller For Hybrid Racecar, Elias D. Bello, Trammell J. Saltzgaber, Leina C. Mcdermott, Alex S. Newman, Jennifer Jain

ENGS 89/90 Reports

Our ENGS 89/90 team has designed and tested a new central vehicle controller for the Dartmouth Formula Racing team's hybrid racecar. The new controller allows for the implementation of various control strategies, logs data from sensors onboard the vehicle, and is accompanied by well-documented firmware and hardware and an automotive-grade enclosure.

Machine Shop Instruction Tool, John Sullivan, Junfei Yu, Tao Wang, Yuteng Mei

ENGS 89/90 Reports

This team has developed a digital learning solution to supplement the machine shop’s training curriculum that students will be able to access remotely anytime and anywhere. This solution will improve how efficiently the machine tools are taught, reduce the time needed to educate each student, and possibly give more students time to learn in the machine shop. In addition, the team has delivered a code repository and documentation to the machine shop. In the future, this solution can be extended to other machines and courses at Thayer. Students will be able to apply their knowledge to their future engineering projects.

My Baseball Collection App, Nicolas A. Parra

Computer Science and Software Engineering

My Baseball Collection is an iOS application that aims to simplify the management and expansion of physical baseball trading card collections. The app allows users to digitize their baseball card collection by uploading images of cards they possess, creating a wishlist of cards they are seeking, and viewing the collections and wishlists of other users. This project seeks to provide quality of life improvements to those within the baseball card trading community and to further facilitate communication and trading in an online world.

Infrared And Electro-Optical Stereo Vision For Automated Aerial Refueling, William E. Dallmann

Theses and Dissertations

Currently, Unmanned Aerial Vehicles are unsafe to refuel in-flight due to the communication latency between the UAVs ground operator and the UAV. Providing UAVs with an in-flight refueling capability would improve their functionality by extending their flight duration and increasing their flight payload. Our solution to this problem is Automated Aerial Refueling (AAR) using stereo vision from stereo electro-optical and infrared cameras on a refueling tanker. To simulate a refueling scenario, we use ground vehicles to simulate a pseudo tanker and pseudo receiver UAV. Imagery of the receiver is collected by the cameras on the tanker and processed by a …

Relevance Analysis For Document Retrieval, Eric Labouve

Master's Theses

Document retrieval systems recover documents from a dataset and order them according to their perceived relevance to a user’s search query. This is a difficult task for machines to accomplish because there exists a semantic gap between the meaning of the terms in a user’s literal query and a user’s true intentions. Even with this ambiguity that arises with a lack of context, users still expect that the set of documents returned by a search engine is both highly relevant to their query and properly ordered. The focus of this thesis is on document retrieval systems that explore methods of …

Human-Centered Enterprise Resource Maintenance Management, Sharon Sue Chinoy

Theses and Dissertations

In complex domains, maintenance personnel may be required to use multiple software tools for receiving status information and controlling resources across the enterprise. These tools have evolved to be effective for collecting status, but often lack integrated contextual information for personnel to understand failure event impact to the enterprise and operational mission. Through a human-centered design approach, salient concepts and semantically relevant maintenance information can be captured within a domain. This research will show that an ontology can be a useful method to establish a common frame of reference to promote better situation awareness and more effective decision-making and collaboration …

2019 (Spring) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the spring of 2019.