Physical Sciences and Mathematics Commons^™

Relative Comparison Of Modern Computing To Computer Technology Of Ages, Iwasan D. Kejawa Dr., Hailly Rubio Ms.

School of Computing: Faculty Publications

Abstract

Abstract

Are there differences and similarities between the computer technology of today and yesterdays. Research had shown that there had been tremendous improvements from the computers of ages (traditional Computers) as we enter the 21st century. Both the physicality and the functionalities of computers have changed but some remain the same. The memory capacity and functions have changed, but all are still based on the old concepts of yesteryears.

Formal Concept Analysis For Image Classification And Machine Learning Models For Anti-Crispr Protein Discovery In Bioinformatics, Minal Khatri

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

This study investigates two critical areas in bioinformatics: enhancing transparency in medical image analysis and advancing the discovery of Anti-CRISPR (Acr) proteins, which have potential in developing more precise and controlled CRISPR-Cas gene editing tools. While CNN’s are increasingly applied in critical fields like medical diagnosis, understanding their decision-making process remains a challenge. Although visualization techniques like Saliency maps offer insights into CNN’s decision-making for individual images, they do not explicitly establish a relationship between the high-level features learned by CNN’s and the class labels across dataset. To bridge this gap, Formal Concept Analysis (FCA) framework is leveraged as a …

Enhanced Privacy-Enabled Face Recognition Using Κ-Identity Optimization, Ryan Karl

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Facial recognition is becoming more and more prevalent in the daily lives of the common person. Law enforcement utilizes facial recognition to find and track suspects. The newest smartphones have the ability to unlock using the user's face. Some door locks utilize facial recognition to allow correct users to enter restricted spaces. The list of applications that use facial recognition will only increase as hardware becomes more cost-effective and more computationally powerful. As this technology becomes more prevalent in our lives, it is important to understand and protect the data provided to these companies. Any data transmitted should be encrypted …

On Dyadic Parity Check Codes And Their Generalizations, Meraiah Martinez

Department of Mathematics: Dissertations, Theses, and Student Research

In order to communicate information over a noisy channel, error-correcting codes can be used to ensure that small errors don’t prevent the transmission of a message. One family of codes that has been found to have good properties is low-density parity check (LDPC) codes. These are represented by sparse bipartite graphs and have low complexity graph-based decoding algorithms. Various graphical properties, such as the girth and stopping sets, influence when these algorithms might fail. Additionally, codes based on algebraically structured parity check matrices are desirable in applications due to their compact representations, practical implementation advantages, and tractable decoder performance analysis. …

3dgaunet: 3d Generative Adversarial Networks With A 3d U-Net Based Generator To Achieve The Accurate And Effective Synthesis Of Clinical Tumor Image Data For Pancreatic Cancer, Yu Shi, Hannah Tang, Michael J. Baine, Michael A. Hollingsworth, Huijing Du, Dandan Zheng, Chi Zhang, Hongfeng Yu

School of Computing: Faculty Publications

Pancreatic ductal adenocarcinoma (PDAC) presents a critical global health challenge, and early detection is crucial for improving the 5-year survival rate. Recent medical imaging and computational algorithm advances offer potential solutions for early diagnosis. Deep learning, particularly in the form of convolutional neural networks (CNNs), has demonstrated success in medical image analysis tasks, including classification and segmentation. However, the limited availability of clinical data for training purposes continues to represent a significant obstacle. Data augmentation, generative adversarial networks (GANs), and cross-validation are potential techniques to address this limitation and improve model performance, but effective solutions are still rare for 3D …

Ict Application And Information Service Delivery In South-West Nigeria’S Public Polytechnic Libraries, Omolabake Eunice Akinyemi, Toyosi Rachel Afolabi

Library Philosophy and Practice (e-journal)

Teh study dwells on teh application of information and communication technology (ICT) for enhancing information service delivery in South-West Nigeria’s public polytechnic libraries. Teh study's goal is to determine teh extent of ICT application in polytechnic libraries. For teh study, a descriptive survey research design was adopted. Teh population of teh study consists of all teh library personnel in South-West Nigeria’s public polytechnic libraries. Teh instrument for gathering data was a questionnaire. Descriptive statistics such as mean, standard deviation, frequency count, and simple percentage were used to analyse teh data. Teh hypothesis was tested by Pearson Moment Product Correlation at …

Enhancing Academic Library Service Delivery Using Artificial Intelligence (Ai), Omolabake Akinyemi

Library Philosophy and Practice (e-journal)

Academic libraries are crucial parts of educational establishments coz they give lecturers and students access to a wealth of knowledge resources. dis article examines how artificial intelligence (AI) can change academic libraries and raise teh calibre and TEMPeffectiveness of service delivery in reference, circulation, cataloguing and classification to meet teh changing needs of library users. Examples of AI applications in academic libraries are given in teh study. Teh study explores teh possible benefits of AI in academic library and impediments to its integration. Teh study concludes dat teh use of AI in academic libraries is a big step toward better …

Motif-Cluster: A Spatial Clustering Package For Repetitive Motif Binding Patterns, Mengyuan Zhou

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Previous efforts in using genome-wide analysis of transcription factor binding sites (TFBSs) have overlooked the importance of ranking potential significant regulatory regions, especially those with repetitive binding within a local region. Identifying these homogenous binding sites is critical because they have the potential to amplify the binding affinity and regulation activity of transcription factors, impacting gene expression and cellular functions. To address this issue, we developed an open-source tool Motif-Cluster that prioritizes and visualizes transcription factor regulatory regions by incorporating the idea of local motif clusters. Motif-Cluster can rank the significant transcription factor regulatory regions without the need for experimental …

Osc-Co2: Coattention And Cosegmentation Framework For Plant State Change With Multiple Features, Rubi Quiñones, Ashok Samal, Sruti Das Choudhury, Francisco Muñoz-Arriola

School of Computing: Faculty Publications

Cosegmentation and coattention are extensions of traditional segmentation methods aimed at detecting a common object (or objects) in a group of images. Current cosegmentation and coattention methods are ineffective for objects, such as plants, that change their morphological state while being captured in different modalities and views. The Object State Change using Coattention-Cosegmentation (OSC-CO²) is an end-to-end unsupervised deep-learning framework that enhances traditional segmentation techniques, processing, analyzing, selecting, and combining suitable segmentation results that may contain most of our target object’s pixels, and then displaying a final segmented image. The framework leverages coattention-based convolutional neural networks (CNNs) and …

Short History Of The Unl Digital Commons, Paul Royster

University of Nebraska-Lincoln Libraries: Conference Presentations and Speeches

From 2005 through 2023, the UNL Digital Commons grew to be a leading example of an institutional repository. This presentation reports on personnel, history, strategy, and outstanding examples of series or contributors.

Announcement about the session:

UNL Digital Commons began in 2005 and grew into America’s 3rd-largest and most-trafficked institutional repository. Approaching 100 million downloads and spreading UNL scholarship and branding across the globe, the UNL Digital Commons boasts works from a wide variety of affiliated faculty, researchers, and students. Their participation is opening the dissemination of scholarship in radical and fundamental ways. In this session, Paul Royster traces this …

Executive Order On The Safe, Secure, And Trustworthy Development And Use Of Artificial Intelligence, Joseph R. Biden

Copyright, Fair Use, Scholarly Communication, etc.

Section 1. Purpose. Artificial intelligence (AI) holds extraordinary potential for both promise and peril. Responsible AI use has the potential to help solve urgent challenges while making our world more prosperous, productive, innovative, and secure. At the same time, irresponsible use could exacerbate societal harms such as fraud, discrimination, bias, and disinformation; displace and disempower workers; stifle competition; and pose risks to national security. Harnessing AI for good and realizing its myriad benefits requires mitigating its substantial risks. This endeavor demands a society-wide effort that includes government, the private sector, academia, and civil society.

My Administration places the highest urgency …

Statistical And Machine Learning Approaches To Describe Factors Affecting Preweaning Mortality Of Piglets, Md Towfiqur Rahman, Tami M. Brown-Brandl, Gary A. Rohrer, Sudhendu R. Sharma, Vamsi Manthena, Yeyin Shi

Biological Systems Engineering: Papers and Publications

High preweaning mortality (PWM) rates for piglets are a significant concern for the worldwide pork industries, causing economic loss and well-being issues. This study focused on identifying the factors affecting PWM, overlays, and predicting PWM using historical production data with statistical and machine learning models. Data were collected from 1,982 litters from the United States Meat Animal Research Center, Nebraska, over the years 2016 to 2021. Sows were housed in a farrowing building with three rooms, each with 20 farrowing crates, and taken care of by well-trained animal caretakers. A generalized linear model was used to analyze the various sow, …

Application And Use Of Artificial Intelligence (Ai) For Library Services Delivery In Academic Libraries In Kwara State, Nigeria, Abdullahi Olayinka Isiaka

Library Philosophy and Practice (e-journal)

The application and use Artificial Intelligence (AI) in library services delivery and operations has modernized traditional practices, enabling libraries to adapt to the evolving information needs of patrons in the digital era. The main purpose of this study is to investigate the application and use of Artificial Intelligence (AI) Technologies for Library Services Delivery in Academic Libraries in Kwara State, Nigeria. The study used a descriptive survey approach. The population was the 108 librarians in academic libraries in Kwara State, Nigeria. A total enumeration technique was employed, and a questionnaire was used to collect data from the library staff. The …

Rapid: Region-Based Pointer Disambiguation, Khushboo Chitre, Piyus Kedia, Rahul Purandare

School of Computing: Faculty Publications

Interprocedural alias analyses often sacrifice precision for scalability. Thus, modern compilers such as GCC and LLVM implement more scalable but less precise intraprocedural alias analyses. This compromise makes the compilers miss out on potential optimization opportunities, affecting the performance of the application. Modern compilers implement loop-versioning with dynamic checks for pointer disambiguation to enable the missed optimizations. Polyhedral access range analysis and symbolic range analysis enable O(1) range checks for non-overlapping of memory accesses inside loops. However, these approaches work only for the loops in which the loop bounds are loop invariants. To address this limitation, researchers proposed a …

Perceptual Cue-Guided Adaptive Image Downscaling For Enhanced Semantic Segmentation On Large Document Images, Chulwoo Pack, Leen-Kiat Soh, Elizabeth Lorang

School of Computing: Faculty Publications

Image downscaling is an essential operation to reduce spatial complexity for various applications and is becoming increasingly important due to the growing number of solutions that rely on memory-intensive approaches, such as applying deep convolutional neural networks to semantic segmentation tasks on large images. Although conventional content-independent image downscaling can efficiently reduce complexity, it is vulnerable to losing perceptual details, which are important to preserve. Alternatively, existing content-aware downscaling severely distorts spatial structure and is not effectively applicable for segmentation tasks involving document images. In this paper, we propose a novel image downscaling approach that combines the strengths of both …

Revealing Gene Regulation-Based Neural Network Computing In Bacteria, Samitha S. Somathilaka, Sasitharan Balasubramaniam, Daniel P. Martins, Xu Li

School of Computing: Faculty Publications

Bacteria are known to interpret a range of external molecular signals that are crucial for sensing environmental conditions and adapting their behaviors accordingly. These external signals are processed through a multitude of signaling transduction networks that include the gene regulatory network (GRN). From close observation, the GRN resembles and exhibits structural and functional properties that are similar to artificial neural networks. An in-depth analysis of gene expression dynamics further provides a new viewpoint of characterizing the inherited computing properties underlying the GRN of bacteria despite being non-neuronal organisms. In this study, we introduce a model to quantify the gene-to-gene interaction …

Mfa-Dvr: Direct Volume Rendering Of Mfa Models, Jianxin Sun, David Lenz, Hongfeng Yu, Tom Peterka

School of Computing: Faculty Publications

3D volume rendering is widely used to reveal insightful intrinsic patterns of volumetric datasets across many domains. However, the complex structures and varying scales of volumetric data can make efficiently generating high-quality volume rendering results a challenging task. Multivariate functional approximation (MFA) is a new data model that addresses some of the critical challenges: high-order evaluation of both value and derivative anywhere in the spatial domain, compact representation for largescale volumetric data, and uniform representation of both structured and unstructured data. In this paper, we present MFA-DVR, the first direct volume rendering pipeline utilizing the MFA model, for both structured …

A Roadmap For The Human Gut Cell Atlas, Matthias Zilbauer, Kylie R. James, Mandeep Kaur, Sebastian Pott, Zhixin Li, Albert Burger, Jay R. Thiagarajah, Joseph Burclaff, Frode L. Jahnsen, Francesca Perrone, Alexander D. Ross, Gianluca Matteoli, Nathalie Stakenborg, Tomohisa Sujino, Andreas Moor, Raquel Bartolome-Casado, Espen S. Bækkevold, Ran Zhou, Bingqing Xie, Ken S. Lau, Shahida Din, Scott T. Magness, Qiuming Yao, Semir Beyaz, Mark Arends, Alexandre Denadai-Souza, Lori A. Coburn, Jellert T. Gaublomme, Richard Baldock, Irene Papatheodorou, Jose Ordovas-Montanes, Guy Boeckxstaens, Anna Hupalowska, Sarah A. Teichmann

School of Computing: Faculty Publications

The number of studies investigating the human gastrointestinal tract using various single-cell profiling methods has increased substantially in the past few years. Although this increase provides a unique opportunity for the generation of the first comprehensive Human Gut Cell Atlas (HGCA), there remains a range of major challenges ahead. Above all, the ultimate success will largely depend on a structured and coordinated approach that aligns global efforts undertaken by a large number of research groups. In this Roadmap, we discuss a comprehensive forward-thinking direction for the generation of the HGCA on behalf of the Gut Biological Network of the Human …

Experimental Study Of Linux Flightsize Estimation, Mingrui Zhang

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Transmission Control Protocol (TCP) is a fundamental Internet protocol responsible for controlling and coordinating the Internet traffic. As a result, TCP significantly influences the overall performance and stability of the Internet. One critical information required by a TCP connection to make decisions is FlightSize, which is the total amount of outstanding data contributed by the connection to the Internet. The FlightSize information is used by a TCP connection to determine its future sending rate and also avoid traffic congestion and collapse in the Internet. Consequently, an inaccurate estimation of FlightSize can result in degraded performance and instability of the Internet. …

Spatial & Temporal Agnostic Deep-Learning Based Radio Fingerprinting, Fahmida Afrin

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Radio fingerprinting is a technique that validates wireless devices based on their unique radio frequency (RF) signals. This method is highly feasible because RF signals carry distinct hardware variations introduced during manufacturing. The security and trustworthiness of current and future wireless networks heavily rely on radio fingerprinting. In addition to identifying individual devices, it can also differentiate mission-critical targets. Despite significant efforts in the literature, existing radio fingerprinting methods require improved robustness, scalability, and resilience. This study focuses on the challenges of spatial-temporal variations in the wireless environment. Many prior approaches overlook the complex numerical structure of the in-phase and …

Economic Value Of User Interface Design, Anna Kruse

Honors Theses

The economic value of well-designed user interfaces (UI) and user experiences (UX) is challenging to quantify, a topic that the current literature does not sufficiently explore. Those responsible for deciding whether to invest resources in UI/UX typically base these decisions on monetary considerations. The link between effective UI/UX design and profit may not be immediately clear to most, yet it is universally acknowledged that satisfied customers lead to successful business. To underscore the importance of investing in UI/UX, it is crucial to define the relationship between effective design and economic success in a way that can be understood by designers, …

Agris: Wind-Adaptive Wideband Reconfigurable Intelligent Surfaces For Resilient Wireless Agricultural Networks At Millimeter-Wave Spectrum, Shuai Nie, M. C. Vuran

School of Computing: Faculty Publications

Wireless networks in agricultural environments are unique in many ways. Recent measurements reveal that the dynamics of crop growth impact wireless propagation channels with a long-term seasonal pattern. Additionally, short-term environmental factors, such as strong wind, result in variations in channel statistics. Next-generation agricultural fields, populated by autonomous tractors, drones, and high-throughput sensing systems, require high-throughput connectivity infrastructure, resulting in the future deployment of high-frequency networks, where they have not been deployed before. More specifically, when millimeter-wave (mmWave) communication systems, a viable candidate for 5G and 6G high-throughput solutions, are deployed for higher throughput, these issues become more prominent due …

Next-Generation Sequencing Data-Based Association Testing Of A Group Of Genetic Markers For Complex Responses Using A Generalized Linear Model Framework, Zheng Xu, Song Yan, Cong Wu, Qing Duan, Sixia Chen, Yun Li

School of Computing: Faculty Publications

To study the relationship between genetic variants and phenotypes, association testing is adopted; however, most association studies are conducted by genotype-based testing. Testing methods based on next-generation sequencing (NGS) data without genotype calling demonstrate an advantage over testing methods based on genotypes in the scenarios when genotype estimation is not accurate. Our objective was to develop NGS data-based methods for association studies to fill the gap in the literature. Single-variant testing methods based on NGS data have been proposed, including our previously proposed single-variant NGS data-based testing method, i.e., UNC combo method. The NGS data-based group testing method has been …

Dynamic Resource Optimization For Energy-Efficient 6g-Iot Ecosystems, James Adu Ansere, Mohsin Kamal, Izaz Ahmad Khan, Muhammad Naveed Aman

School of Computing: Faculty Publications

The problem of energy optimization for Internet of Things (IoT) devices is crucial for two reasons. Firstly, IoT devices powered by renewable energy sources have limited energy resources. Secondly, the aggregate energy requirement for these small and low-powered devices is translated into significant energy consumption. Existing works show that a significant portion of an IoT device’s energy is consumed by the radio sub-system. With the emerging sixth generation (6G), energy efficiency is a major design criterion for significantly increasing the IoT network’s performance. To solve this issue, this paper focuses on maximizing the energy efficiency of the radio sub-system. In …

A Generalization Of The Chomsky-Halle Phonetic Representation Using Real Numbers For Robust Speech Recognition In Noisy Environments, Peter Z. Revesz

School of Computing: Faculty Publications

Speech recognition is difficult when the speech signal is weak or occurs in a noisy environment. This paper presents an efficient and robust method that can reconstruct the standard pronunciation of English phonemes and words given a weak or noisy signal. The reconstruction is based on a novel representation of the reconstruction task as a problem of data retrieval from a database in two different cases: (1) when the phonemes are represented in the database as binary tuples and the input is also a binary tuple from which deletion errors occur, and (2) when the phonemes are represented in the …

Partitions Of R^N With Maximal Seclusion And Their Applications To Reproducible Computation, Jason Vander Woude

Department of Mathematics: Dissertations, Theses, and Student Research

We introduce and investigate a natural problem regarding unit cube tilings/partitions of Euclidean space and also consider broad generalizations of this problem. The problem fits well within a historical context of similar problems and also has applications to the study of reproducibility in randomized computation.

Given $k\in\mathbb{N}$ and $\epsilon\in(0,\infty)$, we define a $(k,\epsilon)$-secluded unit cube partition of $\mathbb{R}^{d}$ to be a unit cube partition of $\mathbb{R}^{d}$ such that for every point $\vec{p}\in\R^d$, the closed $\ell_{\infty}$ $\epsilon$-ball around $\vec{p}$ intersects at most $k$ cubes. The problem is to construct such partitions for each dimension $d$ with the primary goal of minimizing …

Designing Programming Languages For Writing Maintainable Software, Aaron Friesen

Honors Theses

Maintainability is crucial to the long-term success of software projects. Among other factors, it is affected by the programming language in which the software is written. Programming language designers should be conscious of how their design decisions can influence software maintainability. Non-functional properties of a language can affect the readability of source code in ways beyond the control of programmers. Language features can cause or prevent certain classes of bugs, and runtime issues especially can require significant maintenance effort. Tools external to the language, especially those developed and distributed by language implementers, can aid in the creation of maintainable software. …

Studying Developer Eye Movements To Measure Cognitive Workload And Visual Effort For Expertise Assessment, Salwa D. Aljehane, Bonita Sharif, Jonathan I. Maletic

School of Computing: Faculty Publications

Eye movement data provides valuable insights that help test hypotheses about a software developer’s comprehension process. The pupillary response is successfully used to assess mental processing effort and attentional focus. Relatively little is known about the impact of expertise level in cognitive effort during programming tasks. This paper presents a quantitative analysis that compares the eye movements of 207 experts and novices collected while solving program comprehension tasks. The goal is to examine changes of developers’ eye movement metrics in accordance with their expertise. The results indicate significant increase in pupil size with the novice group compared to the experts, …

Sim-To-Real Reinforcement Learning Framework For Autonomous Aerial Leaf Sampling, Ashraful Islam

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Using unmanned aerial systems (UAS) for leaf sampling is contributing to a better understanding of the influence of climate change on plant species, and the dynamics of forest ecology by studying hard-to-reach tree canopies. Currently, multiple skilled operators are required for UAS maneuvering and using the leaf sampling tool. This often limits sampling to only the canopy top or periphery. Sim-to-real reinforcement learning (RL) can be leveraged to tackle challenges in the autonomous operation of aerial leaf sampling in the changing environment of a tree canopy. However, trans- ferring an RL controller that is learned in simulation to real UAS …

Leveraging Aruco Fiducial Marker System For Bridge Displacement Estimation Using Unmanned Aerial Vehicles, Mohamed Aly

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The use of unmanned aerial vehicles (UAVs) in construction sites has been widely growing for surveying and inspection purposes. Their mobility and agility have enabled engineers to use UAVs in Structural Health Monitoring (SHM) applications to overcome the limitations of traditional approaches that require labor-intensive installation, extended time, and long-term maintenance. One of the critical applications of SHM is measuring bridge deflections during the bridge operation period. Due to the complex remote sites of bridges, remote sensing techniques, such as camera-equipped drones, can facilitate measuring bridge deflections. This work takes a step to build a pipeline using the state-of-the-art computer …