Digital Commons Network^™

The Criminal Justice System And The Lgbtq Community: An Anti-Queer Regime, Steven Peck

Themis: Research Journal of Justice Studies and Forensic Science

The LGBTQ community in the US, while experiencing great strides in social equality, continues to suffer disproportionately in the criminal justice system. Historical precedents of criminalizing the LGBTQ community are rife within the criminal justice system; the establishment of anti-sodomy laws, belief of inherent criminality, and a heteronormative perspective have all fostered a greater anti-queer regime. The criminalization and incarceration of the LGBTQ community remain steadfastly in place, with little to no reprieve. Establishing a new narrative in the criminalization and imprisonment of the LGBTQ community may assist in efforts to achieve real change within the criminal justice system. Moving …

Drivers’ Response To Scenarios When Driving Connected And Automated Vehicles Compared To Vehicles With And Without Driver Assist Technology, Srinivas S. Pulugurtha, Raghuveer Gouribhatla

Mineta Transportation Institute

Traffic related crashes cause more than 38,000 fatalities every year in the United States. They are the leading cause of death among drivers up to 54 years in age and incur $871 million in losses each year. Driver errors contribute to about 94% of these crashes. In response, automotive companies have been developing vehicles with advanced driver assistance systems (ADAS) that aid in various driving tasks. These features are aimed at enhancing safety by either warning drivers of a potential hazard or picking up certain driving maneuvers like maintaining the lane. These features are already part of vehicles with Driver …

Factors Influencing Career Choice Among Secondary School Students In Aba North Of Abia State And Implications For School Library Development, Ndubuisi Eze Chukwu, Chinenye Ifeoma Ogidi, Immaculata N. Akaneme, Leonard Chidi Ilechukwu

Library Philosophy and Practice (e-journal)

The purpose of the study was to investigate factors influencing the career choice among secondary school students and implications for school library development. The study design adopted was ex-post-facto. The study was guided by four research questions and four null hypotheses. A sample of 65 students was selected using the multi-stage sampling technique. Data were collected with a self-structured questionnaire structured on a 4-point rating scale. The research questions were analyzed using mean and standard deviation. The null hypotheses were tested at 0.5 level of significance using independent t-test. The major findings showed that there is no significant difference in …

Influence Of Preschool Librarians’ Demographic Characteristics On Their Library Discipline Practices: An Ex-Post Facto Research, Christian S. Ugwuanyi Phd, Charity C. Okeke M.Ed, Chinedu I.O. Okeke Prof

Library Philosophy and Practice (e-journal)

The success of various discipline practices in controlling children's behavior in the classroom has been a major source of concern among preschool librarians. Despite the relevance of library discipline in managing disruptive conduct in children, there appears to be a knowledge gap regarding the impact of preschool librarians' demographic features on their discipline practices. As a result, this study measured the influence/impact of preschool librarians' demographic factors on their library disciplinary practices using authoritarian behavioural theory. With a sample of 156 preschool librarians in Enugu State's Nsukka Education Zone, the study used an ex-post facto research design. The researchers developed …

Electronic Health (E-Health) Literacy Among Undergraduate University Students, Kalsoom Akhtar, Shazia Yusuf Dr, Samar Fahd Dr, Imran Ajmal

Library Philosophy and Practice (e-journal)

E-health literacy refers to the knowledge of electronic resources and searching techniques that are required to obtain credible health information. E-health literacy can help the general population to search, acquire, appraise, use and interpret health-related information from electronic sources, as well as to be able to apply the gained information to address and solve health-related problems.

A large scale cross-sectional survey was conducted to appraise the e-health literacy skills among undergraduate psychology students. The population of the study comprised of undergraduate psychology students enrolled in the public sector universities. A questionnaire was developed by conducting a thorough review of the …

Reed Magazine, Issue 155, Khem K. Arya, John T. Battaglia, Soramimi Hanarejima, Cora Lewis, Aeriel Merillat, Mohamed Shalabi, Ocean Vuong, Yiru Zhang, Marjan Kamali, Rashad Hosein, Suzanne Rico, Kirsten Reneau, Jerilynn Aquino, Katie Culligan, Susan Dambroff, Max Dorfman, Sean Enfield, Leah Kuenzi, Kazim Ali, John Blair, Tom Bennett, Partridge Boswell, Dante Di Stefano, Jonathan Greenhause, Lynn Hoggard, Leslie Anne Mcilroy, David J.S. Pickering, Noelani Piters, Kait Quinn, Henry 7 Reneau Jr, Danielle Roberts, Leona Sevick, Terry Tierney, Brendan Todt, Pamela Wax, Erin Wilson, Maggie Wolff, Xiadi Zhai, Matty Heimgartner, Antara Gangwal, Lance Fung, Caroline Dejeneffe, Koko Alexander, Dottie Lo Bue, Timothy Edward Cech, Jerome Chia-Horng Lin, Doug Edwards, Brittany Fanning, Irina Greciuhina, Roy Huerta, Le Joe, Hana Lock, Loren Marie, Nelson Muff, Shubham Sharma, Heather Perrine Shreve, Rachel Silva, Soap Soap, Kelly A. Harrison, Persis Karim

Reed Magazine

No abstract provided.

A Process Evaluation Of Intelligence Gathering Using Social Media For Emergency Management Organizations In California, Alan Barner

Master's Projects

When responding to an emergency, correct and timely information is often the difference between a successful response and a potential disaster. The information that emergency managers in California receive from the public often dictates how agencies respond to emergencies. The emergence of social media has presented several benefits to emergency managers regarding intelligence gathering during the emergency response process. Simultaneously, the emergence of social media has raised several concerns for the stakeholders involved. One major issue involves inaccurate information circulating on social media platforms during ongoing disasters. If emergency managers cannot discern incorrect information from correct information, disaster response may …

Task Force Rattlesnake: A Cost Analysis Of Fire Crew Base Pay In California, Galen R. Yusufzai-Boggs

Master's Projects

Wildfire management in California is an expensive program totaling over $3 billion in 2020, where the state provides two-thirds of the budget from the general fund (Peters et al., 2020). California has consistently used the state military to assist in wildland fire mitigation efforts; however, for the first time it has created a year-round team to reduce fuels to clean up the state’s forests. Further analysis would determine if Task Force Rattlesnake is an effective use of the state’s budget for wildfire mitigation.

An Evaluation Of The County Of Santa Clara’S Reentry Alcohol And Drug Studies Peer Mentor Program, Sarah Oliveira

Master's Projects

In the United States, incarceration rates have increased dramatically over the last three decades, soaring above any other country. Significant factors contributing to the increase include changes in sentencing laws and policies that target drug-related offenders and prioritize punishment over rehabilitation. Strict sentencing laws have led to mass incarceration, which has caused severe prison overcrowding and led to the infringement of fundamental human rights in prisons (Gottesdiener, 2011).

According to the U.S. Department of Labor, approximately 600,000 individuals are released from federal and state prisons each year (Carson, 2018). In California, an estimated one in three adults has an arrest …

Covid-19 In The Bay Area: The Impact Of A Pandemic On Different Demographics In Selected Counties From 2020 - 2021, Maria Del Rosario Rodriguez Lomeli

Master's Projects

The world experienced a novel coronavirus disease outbreak in Wuhan, China in December of 2019 (Dhillon et al., 2020). Within months it spread worldwide, becoming a pandemic known as the novel coronavirus SARS-CoV2 or COVID-19 (Hunter, 2020). COVID- 19 continued to spread, with public health officials worldwide urging countries to enact stay-at-home orders that could decrease the fast spread of the virus. The Chinese government's official report states that the virus originated in the Huanan Seafood Market located in Wuhan in October of 2019 (Dhillon et al., 2020). The World Health Organization (WHO) was alerted of the virus within a …

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 …

Gesture Recognition Using Neural Networks, Ashwini Kurady

Master's Projects

The advances in technology have brought in a lot of changes in the way humans go about their lives. This has enhanced the significance of Artificial Neural Networks and Computer Vision- based interactions with the world. Gesture Recognition is one of the major focus areas in Computer Vision. This involves Human Computer Interfaces (HCI) that would capture and understand human actions. In this project, we will explore how Neural Network concepts can be applied in this challenging field of Computer Vision. By leveraging the latest research for Gesture Recognition, we researched on how to capture the movement across different frames …

Poriferal Vision: Deep Transfer Learning-Based Sponge Spicules Identification & Taxonomic Classification, Sudhin Domala

Master's Projects

The phylum Porifera includes the aquatic organisms known as sponges. Sponges are classified into four classes: Calcarea, Hexactinellida, Demospongiae, and Homoscleromorpha. Within Demospongiae and Hexactinellida, sponges’ skeletons are needle-like spicules made of silica. With a wide variety of shapes and sizes, these siliceous spicules’ morphology plays a pivotal role in assessing and understanding sponges' taxonomic diversity and evolution. In marine ecosystems, when sponges die their bodies disintegrate over time, but their spicules remain in the sediments as fossilized records that bear ample taxonomic information to reconstruct the evolution of sponge communities and sponge phylogeny.

Traditional methods of identifying spicules from …

Hidden Markov Models With Momentum, Andrew Miller

Master's Projects

Momentum is a popular technique for improving convergence rates during gradient descent. In this research, we experiment with adding momentum to the Baum-Welch expectation-maximization algorithm for training Hidden Markov Models. We compare discrete Hidden Markov Models trained with and without momentum on English text and malware opcode data. The effectiveness of momentum is determined by measuring the changes in model score and classification accuracy due to momentum. Experiments indicate that adding momentum to Baum-Welch can reduce the number of iterations required for initial convergence during HMM training, particularly in cases where the model is slow to converge. However, momentum does …

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 …

Robustness Of Image-Based Malware Analysis, Katrina Tran

Master's Projects

Being able to identify malware is important in preventing attacks. Image-based malware analysis is the study of images that are created from malware. Analyzing these images can help identify patterns in malware families. In previous work, "gist descriptor" features extracted from images have been used in malware classification problems and have shown promising results. In this research, we determine whether gist descriptors are robust with respect to malware obfuscation techniques, as compared to Convolutional Neural Networks (CNN) trained directly on malware images. Using the Python Image Library, we create images from malware executables and from malware that we obfuscate. We …

Modeling Sequencing Artifacts For Next Generation Sequencing, Yvonna Leung

Master's Projects

Advancements in Next Generation Sequencing (NGS) have enabled detection of genetic alterations at large scales with high throughputs. NGS offers advantages over the established sequencing method, Sanger sequencing, by processing large sections of the genome simultaneously at a lower cost with higher accuracy. However, recent research has shown that sequencing artifacts are introduced at various steps in the NGS workflow. These artifacts are the result of an accumulation of errors from multiple steps, such as library preparation and downstream processes, and can result in variants being identified that aren’t actually present in the sequenced genome. Therefore, there is a need …

Mirna-Seq Analysis Pipeline And R Shiny App, Alexis Torres

Master's Projects

ABSTRACT Thrombosis in the internal jugular vein (IJV) has been identified as a risk factor for astronauts undergoing spaceflight, following a 2019 study in which one astronaut developed a thrombus, and several others experienced stagnant or retrograde blood flow. To better understand this phenomenon, a model that simulates the effects of microgravity on blood flow in the IJV is being developed. mRNA and microRNA NGS sequencing will be used to study the transcriptome of human umbilical vein endothelial cells (HUVEC) in simulated microgravity conditions. A microRNA sequencing (miRNA-seq) pipeline has been developed to quantify the miRNA sequencing results. A graphical …

“What I Have Learned About Ethnic Studies Is To Love Myself More”: A Look At Culturally Sustaining Pedagogy And Newcomer Students, Lan Nguyen

Master's Projects

Throughout American history, schooling has been used as a tool of settler colonialism, hegemony, and white supremacy. This process of utilizing schooling as a tool of domination has been labeled by theorists as “miseducation”. To attempt to combat the miseducation that students experience in their schooling, I implemented culturally sustaining pedagogy, which necessitates the maintenance and strengthening of students’ relationships with their cultures in schools. In my project, I focused on newcomer students, as immigrant students are often the most underserved population in schools, and also are the most vulnerable to assimilationist teachings. This project utilized classroom observations, student work, …

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 …

Cloud Provisioning And Management With Deep Reinforcement Learning, Alexandru Tol

Master's Projects

The first web applications appeared in the early nineteen nineties. These applica- tions were entirely hosted in house by companies that developed them. In the mid 2000s the concept of a digital cloud was introduced by the then CEO of google Eric Schmidt. Now in the current day most companies will at least partially host their applications on proprietary servers hosted at data-centers or commercial clouds like Amazon Web Services (AWS) or Heroku.

This arrangement seems like a straight forward win-win for both parties, the customer gets rid of the hassle of maintaining a live server for their applications and …

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 …

Proxy Re-Encryption In Blockchain-Based Application, Wangcheng Yuan

Master's Projects

Nowadays, blockchain-based technology has risen to a new dimension. With the advantage of the decentralized identity, data are transferred through decentralized and public ledgers. Those new contracts provide great visibility. However, there is still a need to keep some data private in many cases. Those private data should be encrypted while still benefiting from the decentralized on-chain protocol. Securing those private data in such a decentralized blockchain-based system is thus a critical problem. Our solution provides a decentralized protocol that lets users grant access to their private data with proxy re-encryption in SpartanGold (a blockchain-based cryptocurrency). We implement a third-party …

Graph Neural Networks For Malware Classification, Vrinda Malhotra

Master's Projects

Malware is a growing threat to the digital world. The first step to managing this threat is malware detection and classification. While traditional techniques rely on static or dynamic analysis of malware, the generation of these features requires expert knowledge. Function call graphs (FCGs) consist of program functions as their nodes and their interprocedural calls as their edges, providing a wealth of knowledge that can be utilized to classify malware without feature extraction that requires experts. This project treats malware classification as a graph classification problem, setting node features using the Local Degree Profile (LDP) model and using different graph …

Adversarial Attacks On Android Malware Detection And Classification, Srilekha Nune

Master's Projects

Recent years have seen an increase in sales of intelligent gadgets, particularly those using the Android operating system. This popularity has not gone unnoticed by malware writers. Consequently, many research efforts have been made to develop learning models that can detect Android malware. As a countermeasure, malware writers can consider adversarial attacks that disrupt the training or usage of such learning models. In this paper, we train a wide variety of machine learning models using the KronoDroid Android malware dataset, and we consider adversarial attacks on these models. Specifically, we carefully measure the decline in performance when the feature sets …

Jparsec - A Parser Combinator For Javascript, Sida Zhong

Master's Projects

Parser combinators have been a popular parsing approach in recent years. Compared with traditional parsers, a parser combinator has both readability and maintenance advantages.

This project aims to construct a lightweight parser construct library for Javascript called Jparsec. Based on the modular nature of a parser combinator, the implementation uses higher-order functions. JavaScript provides a friendly and simple way to use higher-order functions, so the main construction method of this project will use JavaScript's lambda functions. In practical applications, a parser combinator is mainly used as a tool, such as parsing JSON files.

In order to verify the utility of …

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.

Review Of Ludwig Van Beethoven, Symphonien V: Nr. 9 D-Moll Opus 125, Ed. Beate Angelika Kraus, Barry Cooper

The Beethoven Journal

No abstract provided.