Physical Sciences and Mathematics Commons^™

Hyperseed: An End-To-End Method To Process Hyperspectral Images Of Seeds, Tian Gao, Anil Kumar Nalini Chandran, Puneet Paul, Harkamal Walia, Hongfeng Yu

School of Computing: Faculty Publications

High-throughput, nondestructive, and precise measurement of seeds is critical for the evaluation of seed quality and the improvement of agricultural productions. To this end, we have developed a novel end-to-end platform named HyperSeed to provide hyperspectral information for seeds. As a test case, the hyperspectral images of rice seeds are obtained from a high-performance line-scan image spectrograph covering the spectral range from 600 to 1700 nm. The acquired images are processed via a graphical user interface (GUI)-based open-source software for background removal and seed segmentation. The output is generated in the form of a hyperspectral cube and curve for each …

Hyperseed: An End-To-End Method To Process Hyperspectral Images Of Seeds, Tian Gao, Anil Kumar Nalini Chandran, Puneet Paul, Harkamal Walia, Hongfeng Yu

School of Computing: Faculty Publications

High-throughput, nondestructive, and precise measurement of seeds is critical for the evaluation of seed quality and the improvement of agricultural productions. To this end, we have developed a novel end-to-end platform named HyperSeed to provide hyperspectral information for seeds. As a test case, the hyperspectral images of rice seeds are obtained from a high-performance line-scan image spectrograph covering the spectral range from 600 to 1700 nm. The acquired images are processed via a graphical user interface (GUI)-based open-source software for background removal and seed segmentation. The output is generated in the form of a hyperspectral cube and curve for each …

Aerial Flight Paths For Communication, Alisha Bevins, Brittany Duncan

School of Computing: Faculty Publications

This article presents an understanding of naive users’ perception of the communicative nature of unmanned aerial vehicle (UAV) motions refined through an iterative series of studies. This includes both what people believe the UAV is trying to communicate, and how they expect to respond through physical action or emotional response. Previous work in this area prioritized gestures from participants to the vehicle or augmenting the vehicle with additional communication modalities, rather than communicating without clear definitions of the states attempting to be conveyed. In an attempt to elicit more concrete states and better understand specific motion perception, this work includes …

Optimal Container Migration For Mobile Edge Computing: Algorithm, System Design And Implementation, Taewoon Kim, Motassem Al-Tarazi, Jenn-Wei Lin, Wooyeol Choi

School of Computing: Faculty Publications

Edge computing is a promising alternative to cloud computing for offloading computationally heavy tasks from resource-constrained mobile user devices. Placed at the edge of the network, edge computing is particularly advantageous to delay-limited applications for having a short distance to end- users. However, when a mobile user moves away from the service coverage of the associated edge server, the advantage gradually vanishes, increasing response time. Although service migration has been studied to address this problem focusing on minimizing the service downtime, both zero-downtime and the amount of traffic generated as a result of migration need further study. In this paper, …

Computational Solutions To Exosomal Microrna Biomarker Detection In Pancreatic Cancer, Thuy T. An

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

Pancreatic cancer is the fourth leading cause of cancer death in the United States and the 5-year survival rate is only 5% to 10%. There are only a few non-specific symptoms associated with the early-stage cancer, therefore most patients are diagnosed in a late stage. Due to the lack of effective treatments and the fact that the early stage has a 39% 5-year survival rate, the biggest hope to control this disease is early detection. Therefore, discovery of effective and reliable non-invasive biomarkers for early detection of pancreatic cancer has been a major topic. Very recently, exosomal microRNAs have become …

Semantically Meaningful Sentence Embeddings, Rojina Deuja

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

Text embedding is an approach used in Natural Language Processing (NLP) to represent words, phrases, sentences, and documents. It is the process of obtaining numeric representations of text to feed into machine learning models as vectors (arrays of numbers). One of the biggest challenges in text embedding is representing longer text segments like sentences. These representations should capture the meaning of the segment and the semantic relationship between its constituents. Such representations are known as semantically meaningful embeddings. In this thesis, we seek to improve upon the quality of sentence embeddings that capture semantic information.

The current state-of-the-art models are …

Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad

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

Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …

Comparative Analysis Of Kmer Counting And Estimation Tools, Ankitha Vejandla

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

The rapid development of next-generation sequencing (NGS) technologies for determining the sequence of DNA has revolutionized genome research in recent years. De novo assemblers are the most commonly used tools to perform genome assembly. Most of the assemblers use de Bruijn graphs that break the sequenced reads into smaller sequences (sub-strings), called kmers, where k denotes the length of the sub-strings. The kmer counting and analysis of kmer frequency distribution are important in genome assembly. The main goal of this research is to provide a detailed analysis of the performance of different kmer counting and estimation tools that are currently …

Agent Based Modeling Of The Spread Of Social Unrest Based On Infectious Disease Spread Model, Anup Adhikari

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

Social unrest activities are the tools for people to show dissatisfaction, and often people are motivated by similar unrest activities in another region. This causes a spread of unrest activities across space and time. In this thesis, we model the spread of social unrest across time and space. The underlying novel methodology is to model the regions as agents that transition from one state to another based on changes in their environment. The methodology involves (1) creating a region vector for each agent based on socio-demographic, cultural, economic, infrastructural, geographic, and environmental (SCEIGE) factors, (2) formulating neighborhood distance function to …

Fingerlings Mass Estimation: A Comparison Between Deep And Shallow Learning Algorithms, Adair Da Silva Oliveira Junior, Diego André Sant’Ana, Marcio Carneiro Brito Pache, Vanir Garcia, Vanessa Aparecida De Moares Weber, Gilberto Astolfi, Fabricio De Lima Weber, Geazy Vilharva Menezes, Gabriel Kirsten Menezes, Pedro Lucas França Albuquerque, Celso Soares Costa, Eduardo Quirino Arguelho De Queiroz, João Victor Araújo Rozales, Milena Wolff Ferreira, Marco Hiroshi Naka, Hemerson Pistori

School of Computing: Faculty Publications

The paper presents some results regarding the automatic mass estimation of Pintado Real fingerlings, using machine learning techniques to support the fish production process. For this purpose, an image dataset called FISHCV1206FSEG, was created which is composed of 1206 images of fingerlings with their respective annotated masses. Through the fish contours, the area and perimeter were extracted, and submitted to the J48, SVM, and KNN classification algorithms and a linear regression algorithm. The images were also submitted to ResNet50, In- ceptionV3, Exception, VGG16, and VGG19 convolutional neural networks. As a result, the classification algorithm J48 reached an accuracy of 58.2% …

Information Extraction And Classification On Journal Papers, Lei Yu

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

The importance of journals for diffusing the results of scientific research has increased considerably. In the digital era, Portable Document Format (PDF) became the established format of electronic journal articles. This structured form, combined with a regular and wide dissemination, spread scientific advancements easily and quickly. However, the rapidly increasing numbers of published scientific articles requires more time and effort on systematic literature reviews, searches and screens. The comprehension and extraction of useful information from the digital documents is also a challenging task, due to the complex structure of PDF.

To help a soil science team from the United States …

Crest Or Trough? How Research Libraries Used Emerging Technologies To Survive The Pandemic, So Far, Scout Calvert

UNL Libraries: Faculty Publications

Introduction

In the first months of the COVID-19 pandemic, it was impossible to tell if we were at the crest of a wave of new transmissions, or a trough of a much larger wave, still yet to peak. As of this writing, as colleges and universities prepare for mostly in-person fall 2021 semesters, case counts in the United States are increasing again after a decline that coincided with easier access to the COVID vaccine. Plans for a return to campus made with confidence this spring may be in doubt, as we climb the curve of what is already the second …

Users’ Sentiment Analysis Toward National Digital Library Of India: A Quantitative Approach For Understanding User Perception, Ritu Sharma, Sarita Gulati, Amanpreet Kaur, Rupak Chakravarty

Library Philosophy and Practice (e-journal)

Sentiment analysis is also known as opinion mining. Sentiment analysis is contextual mining of text which identifies and extracts subjective information in textual data. It is extremely used by business, educational organizations, and social media monitoring to gain the general outlook of the wide public regarding their product and policy. The current study looks for gaining insights into user reviews on the National Digital Library of India (NDLI) mobile app (android and iOS). For this purpose, sentiment analysis will be used. It yields an average of 3.64/5 ratings based on 11,861 reviews. The dataset includes a total of 4560 user …

Multi-Feature Data Repository Development And Analytics For Image Cosegmentation In High-Throughput Plant Phenotyping, Rubi Quiñones, Francisco Munoz-Arriola, Sruti Das Choudhury, Ashok Samal

School of Computing: Faculty Publications

Cosegmentation is a newly emerging computer vision technique used to segment an object from the background by processing multiple images at the same time. Traditional plant phenotyping analysis uses thresholding segmentation methods which result in high segmentation accuracy. Although there are proposed machine learning and deep learning algorithms for plant segmentation, predictions rely on the specific features being present in the training set. The need for a multi-featured dataset and analytics for cosegmentation becomes critical to better understand and predict plants’ responses to the environment. High-throughput phenotyping produces an abundance of data that can be leveraged to improve segmentation accuracy …

Deepsec: A Deep Learning Framework For Secreted Protein Discovery In Human Body Fluids, Dan Shao, Lan Huang, Yan Wang, Kai He, Xueteng Cui, Yao Wang, Qin Ma, Juan Cui

School of Computing: Faculty Publications

Motivation: Human proteins that are secreted into different body fluids from various cells and tissues can be promising disease indicators. Modern proteomics research empowered by both qualitative and quantitative profiling techniques has made great progress in protein discovery in various human fluids. However, due to the large number of proteins and diverse modifications present in the fluids, as well as the existing technical limits of major proteomics platforms (e.g. mass spectrometry), large discrepancies are often generated from different experimental studies. As a result, a comprehensive proteomics landscape across major human fluids are not well determined.

Results: To bridge …

Power-Over-Tether Unmanned Aerial System Leveraged For Trajectory Influenced Atmospheric Sensing, Daniel Rico

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

The use of unmanned aerial systems (UASs) in agriculture has risen in the past decade and is helping to modernize agriculture. UASs collect and elucidate data previously difficult to obtain and are used to help increase agricultural efficiency and production. Typical commercial off-the-shelf (COTS) UASs are limited by small payloads and short flight times. Such limits inhibit their ability to provide abundant data at multiple spatiotemporal scales. In this thesis, we describe the design and construction of the tethered aircraft unmanned system (TAUS), which is a novel power-over-tether UAS configured for long-term, high throughput atmospheric monitoring with an array of …

A Real-World, Hybrid Event Sequence Generation Framework For Android Apps, Jun Sun

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

Generating meaningful inputs for Android apps is still a challenging issue that needs more research. Past research efforts have shown that random test generation is still an effective means to exercise User-Interface (UI) events to achieve high code coverage. At the same time, heuristic search approaches can effectively reach specified code targets. Our investigation shows that these approaches alone are insufficient to generate inputs that can exercise specific code locations in complex Android applications.

This thesis introduces a hybrid approach that combines two different input generation techniques--heuristic search based on genetic algorithm and random instigation of UI events, to reach …

Aerial Flight Paths For Communication, Alisha Bevins

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

This body of work presents an iterative process of refinement to understand naive perception of communication using the motion of an unmanned aerial vehicle (UAV). This includes what people believe the UAV is trying to communicate, and how they expect to respond through physical action or emotional response. Previous work in this area sought to communicate without clear definitions of the states attempting to be conveyed. In an attempt to present more concrete states and better understand specific motion perception, this work goes through multiple iterations of state elicitation and label assignment. The lessons learned in this work will be …

Using Contextual Bandits To Improve Traffic Performance In Edge Network, Aziza Al Zadjali

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

Edge computing network is a great candidate to reduce latency and enhance performance of the Internet. The flexibility afforded by Edge computing to handle data creates exciting range of possibilities. However, Edge servers have some limitations since Edge computing process and analyze partial sets of information. It is challenging to allocate computing and network resources rationally to satisfy the requirement of mobile devices under uncertain wireless network, and meet the constraints of datacenter servers too. To combat these issues, this dissertation proposes smart multi armed bandit algorithms that decide the appropriate connection setup for multiple network access technologies on the …

Application Of Artificial Intelligence And Machine Learning In Libraries: A Systematic Review, Rajesh Kumar Das, Mohammad Sharif Ul Islam

Library Philosophy and Practice (e-journal)

As the concept and implementation of cutting-edge technologies like artificial intelligence and machine learning has become relevant, academics, researchers and information professionals involve research in this area. The objective of this systematic literature review is to provide a synthesis of empirical studies exploring application of artificial intelligence and machine learning in libraries. To achieve the objectives of the study, a systematic literature review was conducted based on the original guidelines proposed by Kitchenham et al. (2009). Data was collected from Web of Science, Scopus, LISA and LISTA databases. Following the rigorous/ established selection process, a total of thirty-two articles were …

Facility Location Games With Ordinal Preferences, Hau Chan, Minming Li, Chenhao Wang

School of Computing: Faculty Publications

We consider a new setting of facility location games with ordinal preferences. In such a setting, we have a set of agents and a set of facilities. Each agent is located on a line and has an ordinal preference over the facilities. Our goal is to design strategyproof mechanisms that elicit truthful information (preferences and/or locations) from the agents and locate the facilities to minimize both maximum and total cost objectives as well as to maximize both minimum and total utility objectives. For the four possible objectives, we consider the 2-facility settings in which only preferences are private, or locations …

Fire Suppression And Ignition With Unmanned Aerial Vehicles, Carrick Detweiler, Sebastian Elbaum, James Higgins, Christian Laney, Craig Allen, Dirac L. Twidwell Jr, Evan Michale Beachly

School of Computing: Faculty Publications

An unmanned aerial vehicle (UAV) can be configured for fire suppression and ignition. In some examples, the UAV includes an aerial propulsion system, an ignition system, and a control system. The ignition system includes a container of delayed-ignition balls and a dropper configured by virtue of one or more motors to actuate and drop the delayed-ignition balls. The control system is configured to cause the UAV to fly to a site of a prescribed burn and, while flying over the site of the prescribed burn, actuate one or more of the delayed-ignition balls. After actuating the one or more delayed-ignition …

Content Analysis For Advocating The Role Of Digital Scholarship In University Libraries In Delhi Under Open Access Environment, Ritu Nagpal

Library Philosophy and Practice (e-journal)

The present study aims to provide a comprehensive overview of Digital Scholarship. The introduction of Digital Scholarship in Libraries has become indispensable. The study is established upon Digital Scholarship in University Libraries in consideration to Content Analysis of Academic Library Website. The research work further more examines the different entities to analyze and interpret the parameters for applicability of Digital Scholarship in University Libraries. Limiting to the Central University Libraries in Delhi according University Grants Commission the study proposes a model of Digital Scholarship which could be adopted by the Institutions of National importance. The proposed model highlights the transformational …

Towards A Machine Learning Based Generalizable Framework For Detecting Covid-19 Misinformation On Social Media, Yuanzhi Chen

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

Since the beginning of the COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, online social media has become a conduit for the rapid propagation of misinformation. The misinformation is a type of fake news that is created inadvertently without the intention of causing harm. Yet COVID-19 misinformation has caused serious social disruptions including accidental death and destruction of public property. Timely prevention of the propagation of online misinformation requires the development of automated detection tools. Machine learning (ML) based models have been used to automate techniques for identifying fake news. These techniques involve converting text data …

Using An Integrative Machine Learning Approach To Study Microrna Regulation Networks In Pancreatic Cancer Progression, Roland Madadjim

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

With advances in genomic discovery tools, recent biomedical research has produced a massive amount of genomic data on post-transcriptional regulations related to various transcript factors, microRNAs, lncRNAs, epigenetic modifications, and genetic variations. In this direction, the field of gene regulation network inference is created and aims to understand the interactome regulations between these molecules (e.g., gene-gene, miRNA-gene) that take place to build models able to capture behavioral changes in biological systems. A question of interest arises in integrating such molecules to build a network while treating each specie in its uniqueness. Given the dynamic changes of interactome in chaotic systems …

Real-Time Monitoring Of Fdm 3d Printer For Fault Detection Using Machine Learning: A Bibliometric Study, Vaibhav Kisan Kadam, Satish Kumar, Arunkumar Bongale

Library Philosophy and Practice (e-journal)

Additive Manufacturing has wide application range including healthcare, Fashion, Manufacturing, Prototypes, Tooling etc. AM techniques are subjected to various defects that may be printing defects or anomalies in machine. There is gap between current AM techniques and smart manufacturing since current AM lacks in build sensors necessary for process monitoring and fault detection. Both of these issues can be solved by incorporating real-time monitoring into AM. So the study is carried out to identify recent work done in AM to improve current system. For this bibliometric study Scopus database is used, study is kept limited to year 2010-2021 and English …

Analysis Of Students’ Multi-Representation Ability In Augmented Reality-Assisted Learning, Sri Jumini, Edy Cahyono, Muhamad Miftakhul Falah

Library Philosophy and Practice (e-journal)

Not all learning sources can directly and cheaply be presented, so augmented reality media is needed to be applied to students with various talents and intelligence. This study aims to analyze students’ multi-representation ability through the use of augmented reality media. The research method was carried out through pre-experiment with one group posttest only design. Test question items were given to see the students’ multi-representation ability. Data analysis was carried out through the percentage of the number of students achieving test scores of more than or equal to 80 on a scale of 100. The results showed that 88% (28 …

Separator Of Diametral Path Graphs, Cuong Than

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

Nowadays, graph algorithms have been applied to many practical issues such as networking, very large-scale integration (VLSI), and transport systems, etc. Constructing an algorithm to find a maximum independent set (MIS) is one of the first NP-Hard problems which have been studied for a long time. Most scientists believe that there is no polynomial-time algorithm for this problem in general graphs. However, many efficient algorithms and approximation schemes to resolve the MIS problem are found in some special graph classes. In this thesis, we are going to introduce a separator construction for a diametral path graph. By using a property …

Model Counting Meets F0 Estimation, A. Pavan, N. V. Vinodchandran, Arnab Bhattacharyya, Kuldeep S. Meel

School of Computing: Faculty Publications

Constraint satisfaction problems (CSP’s) and data stream models are two powerful abstractions to capture a wide variety of problems arising in different domains of computer science. Developments in the two communities have mostly occurred independently and with little interaction between them. In this work, we seek to investigate whether bridging the seeming communication gap between the two communities may pave the way to richer fundamental insights. To this end, we focus on two foundational problems: model counting for CSP’s and computation of zeroth frequency moments (F₀) for data streams.

Our investigations lead us to observe striking similarity …

Modernizing Legacy Business Practices And Maintaining Backwards Compatibility When Replacing Legacy Software, Thomas Hillebrandt

Honors Theses

As technology advances and hardware as well as user expectations becomes more advanced, software systems must change alongside or go obsolete. When software is no longer developed, decisions must be made regarding its future. Through various methods, legacy software may continue to see usage far past its obsolescence, however legacy software will sooner or later face replacement by new applications, built for state-of-the-art machines, to comply with modern requirements. When writing new software to replace older programs, the added challenge for developers is to help the client also modernize their workflow. When a program has been in long time use …