Physical Sciences and Mathematics Commons^™

An Optimized And Scalable Blockchain-Based Distributed Learning Platform For Consumer Iot, Zhaocheng Wang, Xueying Liu, Xinming Shao, Abdullah Alghamdi, Md. Shirajum Munir, Sujit Biswas

School of Cybersecurity Faculty Publications

Consumer Internet of Things (CIoT) manufacturers seek customer feedback to enhance their products and services, creating a smart ecosystem, like a smart home. Due to security and privacy concerns, blockchain-based federated learning (BCFL) ecosystems can let CIoT manufacturers update their machine learning (ML) models using end-user data. Federated learning (FL) uses privacy-preserving ML techniques to forecast customers' needs and consumption habits, and blockchain replaces the centralized aggregator to safeguard the ecosystem. However, blockchain technology (BCT) struggles with scalability and quick ledger expansion. In BCFL, local model generation and secure aggregation are other issues. This research introduces a novel architecture, emphasizing …

Distance Based Image Classification: A Solution To Generative Classification’S Conundrum?, Wen-Yan Lin, Siying Liu, Bing Tian Dai, Hongdong Li

Research Collection School Of Computing and Information Systems

Most classifiers rely on discriminative boundaries that separate instances of each class from everything else. We argue that discriminative boundaries are counter-intuitive as they define semantics by what-they-are-not; and should be replaced by generative classifiers which define semantics by what-they-are. Unfortunately, generative classifiers are significantly less accurate. This may be caused by the tendency of generative models to focus on easy to model semantic generative factors and ignore non-semantic factors that are important but difficult to model. We propose a new generative model in which semantic factors are accommodated by shell theory’s [25] hierarchical generative process and non-semantic factors by …

Neighborhood Retail Amenities And Taxi Trip Behavior: A Natural Experiment In Singapore, Kwan Ok Lee, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

While a small change in land use planning in existing neighborhoods may significantly reduce private vehicle trips, we do not have a great understanding of the magnitude of the project- and shock-based causal change in travel behaviors, especially for the retail purpose. We analyze the impact of newly developed malls on the retail trip behavior of nearby residents for shopping, dining or services. Using the difference-in-differences approach and big data from a major taxi company in Singapore, we find that households residing within 800 m from a new mall are significantly less likely to take taxis to other retail destinations …

Aspect Sentiment Triplet Extraction Incorporating Syntactic Constituency Parsing Tree And Commonsense Knowledge Graph, Zhenda Hu, Zhaoxia Wang, Yinglin Wang, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

The aspect sentiment triplet extraction (ASTE) task aims to extract the target term and the opinion term, and simultaneously identify the sentiment polarity of target-opinion pairs from the given sentences. While syntactic constituency information and commonsense knowledge are both important and valuable for the ASTE task, only a few studies have explored how to integrate them via flexible graph convolutional networks (GCNs) for this task. To address this gap, this paper proposes a novel end-to-end model, namely GCN-EGTS, which is an enhanced Grid Tagging Scheme (GTS) for ASTE leveraging syntactic constituency parsing tree and a commonsense knowledge graph based on …

Taurus: Towards A Unified Force Representation And Universal Solver For Graph Layout, Mingliang Xue, Zhi Wang, Fahai Zhong, Yong Wang, Mingliang Xu, Oliver Deussen, Yunhai Wang

Research Collection School Of Computing and Information Systems

Over the past few decades, a large number of graph layout techniques have been proposed for visualizing graphs from various domains. In this paper, we present a general framework, Taurus, for unifying popular techniques such as the spring-electrical model, stress model, and maxent-stress model. It is based on a unified force representation, which formulates most existing techniques as a combination of quotient-based forces that combine power functions of graph-theoretical and Euclidean distances. This representation enables us to compare the strengths and weaknesses of existing techniques, while facilitating the development of new methods. Based on this, we propose a new balanced …

Ranked Keyword Search Over Encrypted Cloud Data Through Machine Learning Method, Yinbin Miao, Wei Zheng, Xiaohua Jia, Ximeng Liu, Kim-Kwang Raymond Choo, Robert H. Deng

Research Collection School Of Computing and Information Systems

Ranked keyword search over encrypted data has been extensively studied in cloud computing as it enables data users to find the most relevant results quickly. However, existing ranked multi-keyword search solutions cannot achieve efficient ciphertext search and dynamic updates with forward security simultaneously. To solve the above problems, we first present a basic Machine Learning-based Ranked Keyword Search (ML-RKS) scheme in the static setting by using the k-means clustering algorithm and a balanced binary tree. ML-RKS reduces the search complexity without sacrificing the search accuracy, but is still vulnerable to forward security threats when applied in the dynamic setting. Then, …

Investigation Of Unexpected Purple Substance Extracted From Newsprint Paper, Raquel Wilhelm

Honors Program Theses

In an attempt to extract a green dye from newsprint advertisements, it was serendipitously discovered that a purple substance can be extracted from newsprint paper using methanol or acetic acid.1 Further investigations involving blank newsprint paper showed that the purple substance was a part of the paper itself rather than a component of the ink in the advertisements. Soxhlet extraction was used on the blank newspaper print to obtain the compound. Using different analytical instruments, characteristics of the compound were determined such as potential structures, functional groups, and percent composition. The ultimate goal was to determine the compound and its …

Data Ethics And The Dilemma Created By Turing's Learning Machines, Jacob Kuhn

Honors Program Theses

The main purpose of this research is to shed light on the good and bad that has come about from the interaction of Big Data and Artificial Intelligence in society. Transparency with the public is paramount for the future of Artificial Intelligence. Without awareness, the public is blind to the parts of the Data Revolution that could help them or hinder them. The key question is what AI advancements are being made and what ethical problems do they pose to the general population? To help answer this question, it is best to examine the founding of Artificial Intelligence and the …

A Picture Worth A Thousand Words: Factors Influencing Disability Accommodations, Alicia E. Martin

Cal Poly Humboldt theses and projects

Because not all disabilities look the same it is difficult to label a person with disabilities just by looking at them. Given that our knowledge, attitudes, and perceptions impact how we interpret our world and our willingness to act, people, including professors, may be biased toward providing accommodations for those with easily recognizable disabilities and biased against those with non-recognizable disabilities, and this may impact the disabled person’s ability to learn. This thesis aims to address whether professors’ disability-related attitudes, perceptions of accommodation reasonableness, and willingness to provide accommodations differ when the disability is recognizable (student is pictured in a …

Macrolichen Inventory Of The Horse Mountain Botanical Area, Six Rivers National Forest, California, Usa, Sarah Norvell Conway

Cal Poly Humboldt theses and projects

Macrolichen diversity and community composition was determined for an area of high botanical interest in the Coast Ranges of Northern California – the Horse Mountain Botanical Area (HMBA) in Six Rivers National Forest. The Coast Ranges have been suggested to have high epiphytic macrolichen diversity, yet detailed site-specific macrolichen surveys are lacking for the area. Here we present comprehensive data on macrolichens of the HMBA integrated with environmental metadata at the landscape level. Twenty 0.4 ha sampling plots were positioned across the varying habitats of the HMBA and macrolichens were intensively sampled from all substrata. Out of 888 total collections, …

The Effects Of Post-Harvest Residue On Plantation Forest Soils And Early Growth Of Redwood And Douglas-Fir Seedlings In Humboldt County California, Robert W. Raibley

Cal Poly Humboldt theses and projects

Forest harvest residue (slash) usefulness has been up for debate among private timberland owners, public land managers, and the timber industry for decades. The disposal of slash, viewed as having low ecological value, has received considerable attention as wildfire risk has made burning it harder. In recent years, forest scientists and ecologists have recognized the importance of decaying wood and its relationship to forest growth and regeneration. At this site in Northern California, we looked at whether forest harvest residue enriches soil near slash windrows through soils coring and lab analyses, looking for primary limited nutrients nitrate (NO₃-N) …

Seasonal Growth, Movement, And Survival Of Juvenile Coho Salmon (Oncorhynchus Kisutch) Utilizing Restored Rearing Habitat, Monica S. Tonty

Cal Poly Humboldt theses and projects

The Scott River supports the most robust population of threatened Coho Salmon Oncorhynchus kisutch remaining in the Klamath River basin. Even in the Scott River, low quality and restricted extent of juvenile rearing habitat limits the Coho Salmon population to a small fraction of historic abundance. To support persistence and recovery of Scott River Coho Salmon, the Scott River Watershed Council (SRWC) has constructed a portfolio of restoration projects to improve juvenile rearing habitat, including beaver dam analogs (BDAs). The Scott River BDAs were the first implemented anywhere in California. This study compares juvenile Coho Salmon responses associated with production …

Deeppatent2: A Large-Scale Benchmarking Corpus For Technical Drawing Understanding, Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen

Computer Science Faculty Publications

Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million …

Unttangling Irregular Actin Cytoskeleton Architectures In Tomograms Of The Cell With Struwwel Tracer, Salim Sazzed, Peter Scheible, Jing He, Willy Wriggers

Computer Science Faculty Publications

In this work, we established, validated, and optimized a novel computational framework for tracing arbitrarily oriented actin filaments in cryo-electron tomography maps. Our approach was designed for highly complex intracellular architectures in which a long-range cytoskeleton network extends throughout the cell bodies and protrusions. The irregular organization of the actin network, as well as cryo-electron-tomography-specific noise, missing wedge artifacts, and map dimensions call for a specialized implementation that is both robust and efficient. Our proposed solution, Struwwel Tracer, accumulates densities along paths of a specific length in various directions, starting from locally determined seed points. The highest-density paths originating …

Optimization Of Ported Cfd Kernels On Intel Data Center Gpu Max 1550 Using Oneapi Esimd, Mohammad Zubair, Aaron Walden, Gabriel Nastac, Eric Nielsen, Christoph Bauinger, Xiao Zhu

Computer Science Faculty Publications

We describe our experience porting FUN3D’s CUDA-optimized kernels to Intel oneAPI SYCL.We faced several challenges, including foremost the suboptimal performance of the oneAPI code on Intel’s new data center GPU. Suboptimal performance of the oneAPI code was due primarily to high register spills, memory latency, and poor vectorization. We addressed these issues by implementing the kernels using Intel oneAPI’s Explicit SIMD SYCL extension (ESIMD) API. The ESIMD API enables the writing of explicitly vectorized kernel code, gives more precise control over register usage and prefetching, and better handles thread divergence compared to SYCL. The ESIMD code outperforms the optimized SYCL …

Detecting Deceptive Dark-Pattern Web Advertisements For Blind Screen-Reader Users, Satwick Ram Kodandaram, Mohan Sunkara, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Advertisements have become commonplace on modern websites. While ads are typically designed for visual consumption, it is unclear how they affect blind users who interact with the ads using a screen reader. Existing research studies on non-visual web interaction predominantly focus on general web browsing; the specific impact of extraneous ad content on blind users' experience remains largely unexplored. To fill this gap, we conducted an interview study with 18 blind participants; we found that blind users are often deceived by ads that contextually blend in with the surrounding web page content. While ad blockers can address this problem via …

A Hybrid Deep Learning Approach For Crude Oil Price Prediction, Hind Aldabagh, Xianrong Zheng, Ravi Mukkamala

Computer Science Faculty Publications

Crude oil is one of the world’s most important commodities. Its price can affect the global economy, as well as the economies of importing and exporting countries. As a result, forecasting the price of crude oil is essential for investors. However, crude oil price tends to fluctuate considerably during significant world events, such as the COVID-19 pandemic and geopolitical conflicts. In this paper, we propose a deep learning model for forecasting the crude oil price of one-step and multi-step ahead. The model extracts important features that impact crude oil prices and uses them to predict future prices. The prediction model …

How It Professionals Acquire Soft Skills, Paul Majett

Walden Dissertations and Doctoral Studies

AbstractIn this study, I investigated how information technology (IT) professionals learn/acquire soft skills. Little is understood about how IT professionals describe and apply the soft skills that they consider necessary for their own employability. Exploring how IT professionals describe and apply soft skills is important to their future work and career advancement. The purpose of this basic qualitative study was to better understand how IT professionals learn/acquire soft skills. Bandura’s 1986, social learning theory served as the organizational conceptual framework of this study and guided the research question, which asked how IT professionals acquire learn/acquire soft skills. This research question …

Teachers’ Perceptions Of Using Culturally Relevant Education Practices To Teach Middle-Grades Mathematics, Lorna Bridgetnal Randle

Walden Dissertations and Doctoral Studies

AbstractAfrican American students and other students of color are not experiencing equitable learning outcomes in mathematics classrooms. The problem this study investigated was if and how teachers used culturally relevant education to help increase learning opportunities for African American students. This basic qualitative study aimed to explore teachers' perceptions of how they use culturally relevant education instructional practices to teach mathematics to middle-grade African American students. Further, teachers’ perceptions of their preparedness to use culturally relevant education practices were explored. Aronson and Laughter’s theory of culturally relevant education framed the study and guided data analysis. The research questions investigated if …

Cylindrical Mega-Voids In Quaternary Aeolianites, Little Exuma Island, The Bahamas: Georadar Response, Ilya Val Buynevich, H. Allen Curran, Bosiljka Glumac, Michael Savarese, Lisa Park Boush

Geosciences: Faculty Publications

In addition to karst features, tropical carbonates contain a wide range of smaller cylindrical voids (“pipes”) attributed to bioturbation, tree molds, or dissolution, among others. During geophysical investigation of the Little Exuma Island, The Bahamas, several sites with enigmatic voids were investigated using a high-frequency ground-penetrating radar (GPR) imaging.

The aim of the paper is to assess the feasibility of GPR to detect voids within lithified Holocene calcarenites of the Hannah Bay Member

How Elementary Teachers Implement The Eureka Mathematics Curriculum To Improve Mathematics Outcomes, Shannell A. Swan-Clarke

Walden Dissertations and Doctoral Studies

Many states use research-based mathematics curricula as an instructional tool to improve mathematics performance outcomes on state assessment scores. The problem was that despite the implementation of a research-based curriculum, students at XYZ Elementary School (pseudonym) had underperformed on the Partnership for Assessment of Readiness for College and Careers standardized mathematics tests since 2018. The purpose of this basic qualitative study was to discover the implementation practices of teachers using the Eureka Mathematics Curriculum to improve student outcomes at XYZ Elementary School. Dewey’s experiential learning theory was used to support and explore ideas involving the influences of curriculum implementation on …

Relationship Between Strategic Dexterity, Absorptive Capacity, And Competitive Advantage, Ifechide Monyei

Walden Dissertations and Doctoral Studies

Small- and medium-sized enterprise (SME) manufacturing executives and managers are concerned with the rapid technological changes involving artificial intelligence (AI), machine learning, and big data. To compete in the global landscape, effectively managing digital and artificial intelligence changes among SME manufacturing executives and managers is critical for leaders to compete in 2023 and beyond. Grounded in the dynamic capabilities view theory, the purpose of this quantitative correlation study was to examine the relationship between strategic dexterity, absorptive capacity, and competitive advantage. The participants were 66 executives and managers of SME manufacturing organizations who use big data and analytics daily and …

Strategies For Sustaining Success In Small Businesses In Nigeria, Mina Johnson-Hart

Walden Dissertations and Doctoral Studies

Enterprise owners in Nigeria who need more entrepreneurial skills and an understanding of the business environment may need help sustaining their market share. Nigerian small business owners are concerned with the need for entrepreneurial growth strategies because it could reduce business profitability sustainability and lead to entity failure. Grounded in the entrepreneurial orientation theory, the purpose of this qualitative multiple case study was to explore strategies Nigerian small business owners implement for sustaining success beyond 5 years. The participants were three small business owners in the professional services sector who developed strategies for sustaining success beyond 5 years. Data were …

Effective Strategies For Using Telecommuting By Owners Of Small Businesses, Thomas Law

Walden Dissertations and Doctoral Studies

Small business owners who lack effective strategies to incorporate telecommuting may be unable to retain teleworking employees, create a flexible working environment, or improve workforce morale, negatively impacting company productivity and profitability. Grounded in transformational leadership theory and sociotechnical systems theory, the purpose of this qualitative multiple case study was to explore strategies small business owners use to incorporate telecommuting to retain teleworking employees. Data were collected from five small business owners in Texas with at least 1 year of management experience and created and maintained remote working strategies. Data collection included semistructured interviews and company documents. Three themes emerged …

Understanding U.S. Customers' Intention To Adopt Robo-Advisor Technology, Deborah Wall

Walden Dissertations and Doctoral Studies

Finance and information technology scholars wrote that there is a literature gap on what factors drive investors in Western financial markets to use a Robo-advisor to manage their investments. The purpose of this qualitative, single case study with embedded units is to understand the adoption intentions of retail investors in U.S. markets to use a Robo-advisor instead of a human advisor. A single case study design addressed the literature gap, and qualitative data from seven semi=structured interviews, reflective field notes, and archival data were triangulated to answer the research question. This study was grounded in a theoretical framework that includes …

Strategies Information Technology Leaders Used In Implementing Remote Work During The Covid-19, Jouliana Kamal Barghouth

Walden Dissertations and Doctoral Studies

With the imposed lockdown in many countries due to the spread of COVID-19, many leaders were forced to adopt online technologies in transitioning employees to remote work. Leaders not adopting online technologies or remote work during a pandemic are highly susceptible to business closure. Grounded in the technology acceptance model, the purpose of this qualitative single case study was to explore strategies information technology (IT) leaders in Kuwait used to successfully transition employees to remote work during the pandemic. The participants were six IT leaders from a single multinational IT organization who contributed to strategy development during the pandemic to …

The Employees’ Perspective: Situational Leadership Style Flexibility And Effectiveness And Employee Performance In A Technological Organization, Merari Cortes

Walden Dissertations and Doctoral Studies

Poor employee performance can have adverse effects on business outcomes. Business leaders are concerned with poor performance, which can minimize profitability and negatively impact business sustainability. Grounded in the Situational Leadership II® model, the purpose of this quantitative correlational study was to examine the relationship between situational leadership style flexibility, effectiveness, and employee performance as perceived by employees, controlling for employee gender, job location, and tenure. A random sample of 99 technology company employees completed the Leader Behavior Analysis II®– Other and the Employee Job Performance measurement tools. Using hierarchical multilinear regression, employee gender, job location, and tenure were entered …

Blockchain Securities Issues: Decentralized Identity System With Key Management Perspective, Olalekan O. Adaramola

College of Graduate Studies: Theses & Dissertations

Blockchain was created many years ago to solve the problems of data transfer Integrity, several years later the issues persist. Blockchain securities are one of the most important considerations to be investigated, and data integrity is about ensuring the accuracy and validity of messages such that when they are read, they are the same as when they were first written. It is of the opinion that passing information across from one person to another cannot be the same as it was first said at the onset. Our work investigated Blockchain security issues, studying Integrity emanating from transactions across the blocks …

Investigation Of Additives And Ingredients Of Bio-Resin For Visible Wavelength Laser-Induced Polymerization, Patrick Riggs

College of Graduate Studies: Theses & Dissertations

Optical 3D printing is a branch of Additive manufacturing (AM) that utilizes low-waste production leading to efficient and rapid prototyping. Currently, this method of AM is associated with mainly petroleum-based resins. Bio-resin polymerization is an emerging research area for finding replacements for petroleum-based resins, but curing the resin with laser energy is not normally a practical use case. Current optical 3D printing uses lasers to cure liquid resins to form solid 3D objects in a layer-by-layer process which is time consuming, defect prone, and a leading limiting factor for high volume production; so, finding a way to incorporate bio-resin into …

Assessment Of Atmospheric Correction Algorithms For The Remote Sensing Of Water Quality In Southeastern U.S. Estuaries, Jerome Reimers

College of Graduate Studies: Theses & Dissertations

Water quality is a key indicator in understanding and representing an environment's overall health. Through developments in remote sensing, we can utilize satellite imagery to measure water parameters in each aquatic system. When accurate atmospheric correction is performed, remote sensing can account for atmospheric attenuation and scattering effects to better measure the reflectance and estimate optically active constituents (OAC) present in upper water columns. Atmospheric Correction for OLI lite (ACOLITE) is an atmospheric correction algorithm designed specifically for robust atmospheric correction of water surfaces, in comparison to algorithms designed more for land surfaces such as the European Space Agency’s (ESA) …