Physical Sciences and Mathematics Commons^™

Microbial Labilization And Diversification Of Pyrogenic Dissolved Organic Matter, Aleksandar I. Goranov, Andrew S. Wozniak, Kyle W. Bostick, Andrew R. Zimmerman, Siddhartha Mitra, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

With the increased occurrence of wildfires around the world, interest in the chemistry of pyrogenic organic matter (pyOM) and its fate in the environment has increased. Upon leaching from soils by rain events, significant amounts of dissolved pyOM (pyDOM) enter the aquatic environment and interact with microbial communities that are essential for cycling organic matter within the different biogeochemical cycles. To evaluate the biodegradability of pyDOM, aqueous extracts of laboratory-produced biochars were incubated with soil microbes, and the molecular changes to the composition of pyDOM were probed using ultrahigh-resolution mass spectrometry (Fourier transform–ion cyclotron resonance–mass spectrometry). Given that solar irradiation …

Design And Synthesis Of Α-Anomeric Diacetylene-Containing Glycosides As Photopolymerizable Molecular Gelators, Guijun Wang, Dan Wang, Anji Chen, Ifeanyi S. Okafor, Lalith Palitha Samankumara

Chemistry & Biochemistry Faculty Publications

Glycolipids with diacetylene functional groups are fascinating compounds with many practical uses. Among these, diacetylene-containing gelators are especially important because they can form photopolymerizable gels, which are useful stimuli-responsive materials. Inspired by the unique properties of diacetylene-containing gelators and to understand the structural influences especially the location of the diacetylene functional groups on the self-assembling properties, a series of 15 novel N-acetyl-d-glucosamine derivatives with the diacetylene functional group introduced at the anomeric position were designed and synthesized. The diacetylene function is attached to the sugar through α-glycosylation with the distance from the anomeric oxygen being varied from one, two, …

Stratospheric Aerosol Composition Observed By The Atmospheric Chemistry Experiment Following The 2019 Raikoke Eruption, Chris D. Boone, Peter F. Bernath, Keith Labelle, Jeff Crouse

Chemistry & Biochemistry Faculty Publications

Infrared aerosol spectra derived from Atmospheric Chemistry Experiment measurements following the June 2019 Raikoke volcanic eruption are used to evaluate the composition of stratospheric aerosols in the Arctic. A blanket of aerosols, spanning an altitude range from the tropopause (8–11 km) to 20 km, persisted in the stratosphere over northern latitudes for many months. The aerosols within this blanket were almost exclusively sulfates. The percentage of sulfuric acid in the aerosols decreased over time, dropping below 50% H₂SO₄ concentration at some altitudes by March 2020. Contrary to previous reports, the aerosol blanket was not comprised of smoke …

Modeling Digital Camera Monitoring Count Data With Intermittent Zeros For Short-Term Prediction, Eben Afrifa-Yamoah, Ute Mueller

Research outputs 2022 to 2026

Digital camera monitoring has revolutionised survey designs in many fields, as an important source of information. The extended sampling coverage offered by this monitoring scheme makes it preferable compared to other traditional methods of survey. However, data obtained from digital camera monitoring are often highly variable, and characterized by sparse periods of zero counts, interspersed with missing observations due to outages. In practice, missing data of relatively shorter duration are mostly observed and are often imputed using interpolation techniques, ignoring long-term trends leading to inherent estimation biases. In this study, we investigated time series forecasting methods that adequately handle intermittency …

Edge-Iiotset: A New Comprehensive Realistic Cyber Security Dataset Of Iot And Iiot Applications For Centralized And Federated Learning, Mohamed A. Ferrag, Othmane Friha, Djallel Hamouda, Leandros Maglaras, Helge Janicke

Research outputs 2022 to 2026

In this paper, we propose a new comprehensive realistic cyber security dataset of IoT and IIoT applications, called Edge-IIoTset, which can be used by machine learning-based intrusion detection systems in two different modes, namely, centralized and federated learning. Specifically, the dataset has been generated using a purpose-built IoT/IIoT testbed with a large representative set of devices, sensors, protocols and cloud/edge configurations. The IoT data are generated from various IoT devices (more than 10 types) such as Low-cost digital sensors for sensing temperature and humidity, Ultrasonic sensor, Water level detection sensor, pH Sensor Meter, Soil Moisture sensor, Heart Rate Sensor, Flame …

Codis: Community Detection Via Distributed Seed-Set Expansion On Graph Streams, Austin Anderson

Master's Projects

Community detection has been and remains a very important topic in several fields. From marketing and social networking to biological studies, community detec- tion plays a key role in advancing research in many different fields. Research on this topic originally looked at classifying nodes into discrete communities, but eventually moved forward to placing nodes in multiple communities. Unfortunately, community detection has always been a time-inefficient process, and recent data sets have been simply to large to realistically process using traditional methods. Because of this, recent methods have turned to parallelism, but all these methods, while offering sig- nificant decrease in …

Caption And Image Based Next-Word Auto-Completion, Meet Patel

Master's Projects

With the increasing number of options or choices in terms of entities like products, movies, songs, etc. which are now available to users, they try to save time by looking for an application or system that provides automatic recommendations. Recommender systems are automated computing processes that leverage concepts of Machine Learning, Data Mining and Artificial Intelligence towards generating product recommendations based on a user’s preferences. These systems have given a significant boost to businesses across multiple segments as a result of reduced human intervention. One similar aspect of this is content writing. It would save users a lot of time …

Multi-Step Prediction Using Tree Generation For Reinforcement Learning, Kevin Prakash

Master's Projects

The goal of reinforcement learning is to learn a policy that maximizes a reward function. In some environments with complete information, search algorithms are highly useful in simulating action sequences in a game tree. However, in many practical environments, such effective search strategies are not applicable since their state transition information may not be available. This paper proposes a novel method to approximate a game tree that enables reinforcement learning to use search strategies even in incomplete information environments. With an approximated game tree, the agent predicts all possible states multiple steps into the future and evaluates the states to …

Using Machine Learning To Maximize First-Generation Student Success A Contribution To The Mission Of Aiding The Underserved, Mustafa Emre Yesilyurt

Master's Projects

The Leadership and Career Accelerator (UNVS 101) is a course offered at San José State University (SJSU) designed to hone industry skills in and provide support to students of underserved backgrounds. The main goal of this study is to determine which features are most significant to identifying the students at risk of failing the course. This will allow faculty to better focus data collection efforts and facilitate an increase in classifier accuracy. The data came as three distinct sets (sources). One contained features describing student demographics and academic history, another described the students’ experience in the course, and a third …

Enabling Use Of Signal In A Disconnected Village Environment, Evan Chopra

Master's Projects

A significant portion of the world still does not have a stable internet connection. Those people should have the ability to communicate with their loved ones who may not live near by or to share ideas with friends. To power this achievable reality, our lab has set out on making infrastructure for enabling delay tolerant applications. This network will communicate using existing smartphones that will relay the information to a connected environment. The proof of concept application our lab is using is Signal as it offers end to end encryption messaging and an open source platform our lab can develop.

5g Mobility Management Using Satellites In Leo (Low Earth Orbit), Peter Knight

Master's Projects

As technology moves forward we find ourselves demanding faster and better quality internet. Towards that end, 5G was developed. While cell towers are already being built with 5G in mind, some of the built-in limitations of 5G mean that we may be seeing satellites with it in the near future. This development would require a drastic change in the current algorithms used for handovers. These algorithms fail to take into account the high relative velocity of the satellites and result in many unnecessary handovers which increases the likelihood of a dropped connection. This paper will propose and evaluate the effectiveness …

Abstractive Text Summarization For Tweets, Siyu Chen

Master's Projects

In the high-tech age, we can access a vast number of articles, information, news, and opinion online. The wealth of information allows us to learn about the topics we are interested in more easily and cheaply, but it also requires us to spend an enormous amount of time reading online. Text summarization can help us save a lot of reading time so that we can know more information in a shorter period. The primary goal of text summarization is to shorten the text while including as much vital information as possible in the original text so fewer people use this …

A Study On Human Face Expressions Using Convolutional Neural Networks And Generative Adversarial Networks, Sriramm Muthyala Sudhakar

Master's Projects

Human beings express themselves via words, signs, gestures, and facial emotions. Previous research using pre-trained convolutional models had been done by freezing the entire network and running the models without the use of any image processing techniques. In this research, we attempt to enhance the accuracy of many deep CNN architectures like ResNet and Senet, using a variety of different image processing techniques like Image Data Generator, Histogram Equalization, and UnSharpMask. We used FER 2013, which is a dataset containing multiple classes of images. While working on these models, we decided to take things to the next level, and we …

Strategies For Competitive Advantage In Small Construction Businesses, Syheed Fields

Walden Dissertations and Doctoral Studies

Walden University

College of Management and Technology

This is to certify that the doctoral study by

Syheed Fields

has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made.

Review Committee Dr. Michael Lavelle, Committee Chairperson, Doctor of Business Administration Faculty

Dr. Carol-Anne Faint, Committee Member, Doctor of Business Administration Faculty

Dr. William Stokes, University Reviewer, Doctor of Business Administration Faculty

Chief Academic Officer and ProvostSue Subocz, Ph.D.

Walden University2022

AbstractStrategies for Competitive Advantage in Small Construction Businesses by Syheed Fields

MLD, The Pennsylvania State University, …

The Imperatives Of Political Will For Revenue Diversification In Delta State Nigeria, Benson Chukwuweike Ojoko

Walden Dissertations and Doctoral Studies

Proceeds from crude oil export account for about 90% of the revenue of the federal, state, and local governments in Nigeria. Given the vagaries of the international oil market, scholars have advocated the need for the government to look beyond oil for other revenue sources with little or no success to date. Despite the plethora of research on the phenomenon of political will, there is no research on how the construct affects revenue diversification at the subnational level. This study examined how central political will is in the design of expansionary revenue policies in Delta State, Nigeria. Developing an understanding …

City Of Milpitas Trash Capture Device Program: An Evaluation Of System Performance And Compliance With The Municipal Regional Permit, Joseph Aguilera

Master's Projects

Water pollution negatively impacts the environment and human population. The problem persists despite various mitigation efforts, strategies, and the implementation of regulatory requirements. It is estimated that Californians dispose of approximately 40 million tons of consumer items and waste materials annually (California Department of Resource Recycling and Recovery, 2019). As the population increases, it is expected that negative impacts of trash on the environment will be exacerbated. To address this, municipalities in California apply various methods to reduce trash before it enters ocean waters.

The primary vehicle for urban trash pollutants to reach ocean waters is through storm water conveyance …

Canvas Autoquiz, Archit Jain

Master's Projects

Online learning management platforms such as Canvas are thriving and quickly replacing traditional classrooms, especially during these pandemic-struck times. As more and more quizzes are administered online, we need tools that make the quiz creation process easier and faster. Canvas Autoquiz is a command-line tool that allows instructors to automatically create and upload quizzes of varying difficulty levels. It also allows instructors to export quizzes from one LMS platform to another. This project explores the need, design, and implementation of the tool, and prospective future work.

Hard Real-Time Linux On A Raspberry Pi For 3d Printing, Alvin Nguyen

Master's Projects

The project presents how a Raspberry Pi with hard real-time enabled Linux can control stepper motors to operate the kinematics of a 3D (three-dimensional) printer. The consistent performance of the Raspberry Pi with the PREEMPT-RT (real-time) patch can satisfy real hard-time requirements for 3D printing kinematics, without introducing dedicated microcontrollers. The Klipper 3D printer firmware enables one of the Raspberry Pi processors to act as the Klipper MCU, the primary controller for the hardware components. This project introduces a software implementation of the control logic for controlling the stepper motors, which utilizes the PCA9685 pwm driver and TB6612 motor drivers …

Whole File Chunk Based Deduplication Using Reinforcement Learning, Xincheng Yuan

Master's Projects

Deduplication is the process of removing replicated data content from storage facilities like online databases, cloud datastore, local file systems, etc., which is commonly performed as part of data preprocessing to eliminate redundant data that requires unnecessary storage spaces and computing power. Deduplication is even more specifically essential for file backup systems since duplicated files will presumably consume more storage space, especially with a short backup period like daily [8]. A common technique in this field involves splitting files into chunks whose hashes can be compared using data structures or techniques like clustering. In this project we explore the possibility …

Generative Adversarial Networks For Image-Based Malware Classification, Huy Nguyen

Master's Projects

Malware detection and analysis are important topics in cybersecurity. For efficient malware removal, determination of malware threat levels, and damage estimation, malware family classification plays a critical role. With the rise in computing power and the advent of cloud computing, deep learning models for malware analysis has gained in popularity. In this paper, we extract features from malware executable files and represent them as images using various approaches. We then focus on Generative Adversarial Networks (GAN) for multiclass classification and compare our GAN results to other popular machine learning techniques, including Support Vector Machine

(SVM), XGBoost, and Restricted Boltzmann Machines …

Darknet Traffic Classification, Nhien Rust-Nguyen

Master's Projects

The anonymous nature of darknets is commonly exploited for illegal activities. Previous research has employed machine learning and deep learning techniques to automate the detection of darknet traffic to block these criminal activities. This research aims to improve darknet traffic detection by assessing Support Vector Machines (SVM), Random Forest (RF), Convolutional Neural Networks (CNN) and Auxiliary-Classifier Generative Adversarial Networks (AC-GAN) for classification of network traffic and the underlying application types. We find that our RF model outperforms the state-of-the-art machine learning techniques used by prior work with the CIC-Darknet2020 dataset. To evaluate the robustness of our RF classifier, we degrade …

Faking Sensor Noise Information, Justin Chang

Master's Projects

Noise residue detection in digital images has recently been used as a method to classify images based on source camera model type. The meteoric rise in the popularity of using Neural Network models has also been used in conjunction with the concept of noise residuals to classify source camera models. However, many papers gloss over the details on the methods of obtaining noise residuals and instead rely on the self- learning aspect of deep neural networks to implicitly discover this themselves. For this project I propose a method of obtaining noise residuals (“noiseprints”) and denoising an image, as well as …

A Novel Handover Method Using Destination Prediction In 5g-V2x Networks, Pooja Shyamsundar

Master's Projects

This paper proposes a novel approach to handover optimization in fifth generation vehicular networks. A key principle in designing fifth generation vehicular network technology is continuous connectivity. This makes it important to ensure that there are no gaps in communication for mobile user equipment. Handovers can cause disruption in connectivity as the process involves switching from one base station to another. Issues in the handover process include poor load management for moving traffic resulting in low bandwidth or connectivity gaps, too many hops resulting in multiple unneccessary handovers, short dwell times and ineffective base station selection resulting in delays and …

Benchmarking Newsql Database Voltdb, Kevin Schumacher

Master's Projects

NewSQL is a type of relational database that is able to horizontally scale while retaining linearizable consistency. This is an improvement over a traditional SQL relational database because SQL databases cannot effectively scale across multiple machines. This is also an improvement over NoSQL databases because NewSQL databases are designed from the ground up to be consistent and have ACID guarantees. However, it should be noted that NewSQL databases are not a one size fits all type of database, each specific database is designed to perform well on specific workloads. This project will evaluate a NewSQL database, VoltDB, with a focus …

Virtual Machine For Spartangold, William Wang

Master's Projects

The field of blockchain and cryptocurrencies can be both difficult to grasp and improve upon, which makes aids that can assist in these tasks very useful. SpartanGold is a simplified blockchain-based cryptocurrency created at San Jose State University as a learning aid for blockchain and cryptocurrencies. In its current state, it closely resembles Bitcoin, and it is also easily expandable to implement other features.

This project extends SpartanGold with a virtual machine resembling the Ethereum Virtual Machine. Implementing this feature results in SpartanGold having Ethereum- related features, which would allow the cryptocurrency to both be a helpful learning aid for …

Analysis Of Public Sentiment Of Covid-19 Pandemic, Vaccines, And Lockdowns, Devinesh Singh

Master's Projects

CoV-2 pandemic prompted lockdown measures to be implemented worldwide; these directives were implemented nationwide to stunt the spread of the infection. Throughout the lockdowns, millions of individuals resorted to social media for entertainment, communicate with friends and family, and express their opinions about the pandemic. Simultaneously, social media aided in the dissemination of misinformation, which has proven to be a threat to global health. Sentiment analysis, a technique used to analyze textual data, can be used to gain an overview of public opinion behind CoV-2 from Twitter and TikTok. The primary focus of the project is to build a deep …

Improving Racial Diversity In The Americorps Saint Louis Emergency Response Team (Ert), Michael Mclemore

Walden Dissertations and Doctoral Studies

There is currently a significant lack of racial diversity in the fields of environmental conservation and emergency management. The purpose of this qualitative study was to identify sustainable recommendations to address the lack of racial diversity amongst members of the AmeriCorps Saint Louis Emergency Response Team (ERT). Trend analysis of the racial makeup of past ERT memberships identified a far less diverse ERT in its earlier cohorts, while illustrating improved racial diversity over the past 10 years. As a result of interviews with ERT administrators, alumni, team leaders, and current members recommendations were identified that aim to sustainably increase African …

Knowledge Management In Engineering Companies In The Nigeria Oil And Gas Industry, Babajide Adeniran Ojuola

Walden Dissertations and Doctoral Studies

Engineering companies in the Nigerian Oil and Gas Industry are not able to optimize their knowledge resources through the continual conversion of tacit knowledge to organizational knowledge. This is due to barriers that inhibit the holistic process of tacit knowledge conversion. The purpose of this qualitative case study was to understand the enablers and barriers to tacit knowledge conversion in engineering companies as perceived by engineering practitioners working in the Nigerian oil and gas industry. The central research questions focused on exploring the enablers and barriers to the conversion of tacit knowledge to organizational knowledge in oil and gas engineering …

Strategies That Improve Ux (User Experience) Design Through Product Innovation, Jibing Zhao

Walden Dissertations and Doctoral Studies

User Experience (UX) design improvement can alter business results. Information technology (IT) company leaders are concerned with UX design improvement, as it is the number one indication of product innovation success and user satisfaction. Grounded in Christensen’s disruptive innovation theory, the purpose of the qualitative single case study was to explore strategies IT company leaders and UX designers used to identify critical UX design elements that lead to improved product innovations. The participants were five IT company leaders and a focus group of four UX designers employed by a sizeable telecom organization in Beijing, China. The data were collected from …

Towards A Digital Twin For Characterising Natural Source Zone Depletion: A Feasibility Study Based On The Bemidji Site, Kaveh Sookhak Lari, Greg B. Davis, John L. Rayner

Research outputs 2022 to 2026

Natural source zone depletion (NSZD) of light non-aqueous phase liquids (LNAPLs) may be a valid long-term management option at petroleum impacted sites. However, its future long-term reliability needs to be established. NSZD includes partitioning, biotic and abiotic degradation of LNAPL components plus multiphase fluid dynamics in the subsurface. Over time, LNAPL components are depleted and those partitioning to various phases change, as do those available for biodegradation. To accommodate these processes and predict trends and NSZD over decades to centuries, for the first time, we incorporated a multi-phase multi-component multi-microbe non-isothermal approach to representatively simulate NSZD at field scale. To …