Digital Commons Network^™

Understanding The Importance Of Creativity Towards Psychological Safety In The Library Workplace, Jennifer Hopwood Ed.D.

School of Information Student Research Journal

Employee Engagement is one of the leading factors toward organizational success. Happier employees are engaged employees. However, employees cannot reach engagement unless there are feelings of psychological safety. One tool that libraries can utilize to increase the engagement of their staff is to invest in opportunities for workplace creativity.

Professionalism In Lis: A Blend Of Theory And Practical Application, Amber Passey

School of Information Student Research Journal

No abstract provided.

Haitian Immigrants' Information Needs And Behaviors: Libraries, Information Professionals And Haitians In The United States, Natasha Finnegan

School of Information Student Research Journal

Haitian immigrants are a socially excluded growing demographic in the United States that deals with racism, anti-immigrant sentiment, anti-Haiti rhetoric, and language barriers. Information professionals need to understand Haitian information behavior, their cultural preferences, and barriers in order to successfully fulfill their information needs. This article examines other disciplines’ relevant and scholarly research literature on Haitian immigrants in the United States to discover their trends of information behavior and barriers so that the Library and Information Science field can create effective information pathways to support their community. Haitian immigrants turn to their families and trusted individuals for their information needs, …

Book Review: Information At Work: Information Management In The Workplace, Katriina Byström, Jannica Heinström, Ian Ruthven, Samuel A. Kauffman

School of Information Student Research Journal

No abstract provided.

Ischool Student Research Journal, Vol. 12, Iss. 2

School of Information Student Research Journal

No abstract provided.

Libraries As Determinants Of Guided Inquiry Learning Approach In Social Studies, Favour O. Atubi

Library Philosophy and Practice (e-journal)

This study is an attempt to determine how school libraries can be used to provide a guided learning approach to social studies. The case study was carried out using a group study approach, supervised by three social studies teachers and a school librarian. The population of this study comprises of one hundred and sixteen (116) Junior Secondary Three (3) students from a state owned school in Delta state, southern Nigeria. A sample of fifteen (15) students, made up of three (3) groups of five (5) students each were drawn through a purposive sampling technique. Three teachers of social studies and …

Bill And Mike: How Two Irishmen Slaked The Thirst Of California’S Great Cities, Glen Gendzel

Faculty Research, Scholarly, and Creative Activity

Los Angeles and San Francisco, with nearly 20 million residents in their combined metropolitan areas, are California’s two most famous cities. Yet neither city has anything close to an adequate water supply within hundreds of miles. Tremendous feats of hydraulic engineering are necessary to store and transport water from California’s inland mountain rivers to big cities on the state’s semi-arid coast. In the early twentieth century, a pair of Irish immigrant engineers named Bill and Mike took charge of building these water systems for Los Angeles and San Francisco. William Mulholland (“Bill”) was a self-taught school dropout whose projects bringing …

Librarians’ Digital Literacy Skills And Services Delivery In Academic Libraries In Taraba State, Nigeria: A Correlation, Chukwuemeka Chukwueke, Israel Habibu Idris

Library Philosophy and Practice (e-journal)

The study correlated the digital literacy skills of librarians in academic libraries in Taraba State, Nigeria and their services delivery. The correlational design was adopted in studying 112 librarians drawn from 11 academic libraries in Taraba State. A researcher-made questionnaire was used for data collection. 112 copies of the questionnaire were administered but 109 were retrieved. Data was analysed using descriptive and inferential statistics. The single null hypothesis was tested at 0.05 level of significance using the linear regression. Consequently, the strength of relationship between variables was decided using the Creswell correlational ranking and results presented in frequency tables. Findings …

Hear Their Voices!, José Aguiñaga

Faculty Learning Communities

No abstract provided.

Curiosity, Connection, & Community In Vertebrate Evolution & Natural History, Jessica Castillo Vardaro

Faculty Learning Communities

No abstract provided.

Hip Hop Medicine Mixtape, Johnny C. Ramirez

Faculty Learning Communities

No abstract provided.

That Place You Remember Liking As A Kid, Anne F. Walker

Faculty Learning Communities

No abstract provided.

Sjsu Erfa News, Winter 2023, San Jose State University, Emeritus And Retired Faculty Association

Emeritus and Retired Faculty Association (ERFA) Newsletter

Volume 37, No 2

2022/2023 Lrsp: Inaya Rehman, Inaya Rehman, Michael Aguilar

Library Research Scholars Program

This research study examines the relationship between COVID-19 pandemic-induced social isolation, self-efficacy, and academic outcomes among students at San Jose State University.

Using survey data from a sample of students, the study found that social isolation negatively impacts self-efficacy among students, leading to a decline in confidence and belief in their abilities to succeed academically. In turn, self-efficacy was found to be positively related to academic outcomes, as students with a strong sense of self-efficacy were more likely to perform well academically. The study also found that the negative relationship between social isolation and academic outcomes was less pronounced among …

2022-2023 Annual Report, Society Of American Archivists Student Chapter

Annual Reports

The 2022-2023 Annual Report records the activities of the San Jose State University Society of American Archivists Student Chapter (SAASC). The report lists SAASC members who are also individual members of SAA, provides a summary of the chapter’s events for the year, and updates to chapter outreach and visibility. The report also includes information on the publication of Archeota, the SAASC open source digital publication.

2022/2023 Lrsp: Eleanor Rideout, Eleanor Rideout

Library Research Scholars Program

Throughout history, life narratives have fueled and supported social movements through testimony and counter-narrative on the part of the author (Schaffer & Smith, 2004) and narrative empathy on the part of the reader (Keen, 2006). Narrative empathy invests individuals in a cause, and can serve as the basis for readers’ later involvement in social movements (Keen, 2006). These concepts of life narrative form an interesting connection with comics theory, which suggests that the form engages readers in unique ways through character identification, subjective reading, and closure. In connecting these ideas, this study explores how the medium of comics can be …

Cultivating Parental Participation And Community Engagement Through Building A Culinary Garden And Teaching Kitchen: Latinx Perspectives On Parental Participation In A Community School, Jaclynne Michelle Medina

Dissertations

This study researched how a school could increase parental participation and community engagement while building a new Culinary Garden and Teaching Kitchen project. This engagement was foundational for expanding parental participation opportunities and further developing the community school. The study explored ways to balance power relationships between the home and school to develop an implementation plan that better reflects the community being served. Theoretical lenses such as CRT and LatCrit were the basis for centering the voices of Latinx families and valuing their various forms of capital consistent with the Community Cultural Model. Participants influenced the design of the garden …

Establishing A Framework For The Ethical And Legal Use Of Web Scrapers By Cybercrime And Cybersecurity Researchers: Learnings From A Systematic Review Of Australian Research, Katie Logos, Russell Brewer, Colette Langos, Bryce Westlake

Faculty Research, Scholarly, and Creative Activity

The Internet has become an increasingly attractive location for collecting data about cyber threats, driven by the abundance of quality data available and accessible online. As such, researchers and practitioners have turned to automated data collection technologies (ADCT), including ‘web crawlers’ and ‘web scrapers’, to study these threats. The rapid proliferation of ADCT has meant directions for their ethical and legal operation have been slow to adapt, with no clear guidelines regulating their use for research. This article identifies the relevant ethical and legal frameworks guiding the deployment of ADCT in Australia for cybersecurity research. This is accomplished through a …

Reducing Catheter-Associated Urinary Tract Infection Rates By Educating Staff On Bundle Interventions, Tirath Kaur

Master's Projects

PURPOSE: Catheter associated urinary tract infection is an undesired burden to the patients and healthcare system. This systematic review explores the published literature and determines the impact of educating nursing staff on the indication of urinary catheter, insertion of foley catheters, maintenance of urinary catheters, and periodical communication between nurses and physicians for changing foley catheters can reduce the CAUTI rates in adult patients in the acute care hospital setting. METHOD: A systemic review was conducted using CINHAL, Science Direct, PubMed, and MEDLINE within the time period of ten years from 2012 to 2022. Eight published articles are reviewed and …

A Roadmap To Safer Hyaluronic Acid Injections, Mandi Lonergan

Master's Projects

Non surgical aesthetic treatments have become increasingly more popular in the United States (2020 Plastic Surgery Statistics Report 2021). Hyaluronic acid (HA) fillers are the second most popular non-surgical aesthetic treatment behind Botulinum toxin injections (The Aesthetic Society, 2021). The increased use of these fillers has led to increased rates of complications With the release of new long lasting fillers in 2014, providers began to see an increase in delayed onset nodules (DON). A DON is considered in the aesthetic field to be a nodule that occurs 30 days to years after filler injection (Convery et al., 2021). A …

The Impact Of Utilizing The Eat, Sleep, Console Model On Pharmacologic Interventions And Length Of Stay, Kareena Parks

Master's Projects

Purpose: This systematic review seeks to explore whether utilizing Eat, Sleep, Console (ESC) over the Finnegan Neonatal Abstinence Scale (FNASS) in the neonatal abstinence syndrome (NAS) population decreases length of stay or pharmacological interventions.
Method: Systematic literature review utilizing CINAHL, PubMed and Google Scholar databases.
Results: Utilizing Eat Sleep Console, over FNASS decreased length of stay and pharmacologic intervention.
Conclusions: There is compelling research suggesting a change in NAS treatment from FNASS to ESC with a decrease in length of stay and pharmacologic intervention. However, there is an opportunity for further studies providing higher levels of evidence as the current …

Classification Of Darknet Traffic By Application Type, Shruti Sharma

Master's Projects

The darknet is frequently exploited for illegal purposes and activities, which makes darknet traffic detection an important security topic. Previous research has focused on various classification techniques for darknet traffic using machine learning and deep learning. We extend previous work by considering the effectiveness of a wide range of machine learning and deep learning technique for the classification of darknet traffic by application type. We consider the CICDarknet2020 dataset, which has been used in many previous studies, thus enabling a direct comparison of our results to previous work. We find that XGBoost performs the best among the classifiers that we …

Real Time Panoramic Image Processing, Matthew Gerlits

Master's Projects

Image stitching algorithms are able to join sets of images together and provide a wider field of a vision when compared with an image from a single standard camera. Traditional techniques for accomplishing this are able to adequately produce a stitch for a static set of images, but suffer when differing lighting conditions exist between the two images. Additionally, traditional techniques suffer from processing times that are too slow for real time use cases. We propose a solution which resolves the issues encountered by traditional image stitching techniques. To resolve the issues with lighting difference, two blending schemes have been …

Implicit Racial Bias: A Human Computer Interaction Study Using Eye Tracker, Wenfan Zhang

Master's Projects

Contemporary Human-Computer Interaction (HCI) research has an increasing emphasis on reducing ethnicity bias. The study presents a new method to explore and reduce biases using detailed experiments. The experimental procedure involves presenting participants with images of ethnically diverse characters across three conditions. The study's results significantly illuminate ethnicity bias in character selection dynamics. Participants exposed to targeted training interventions displayed a significant shift in preferences for characters engaged in intellectual activities. Notably, this shift was influenced by the ethnicity of the characters involved. Interestingly, the eye-tracking data unveiled distinct patterns of cognitive load, characterized by slower response times and greater …

Enhancing Driver Distraction Detection Through The Synergy Of Deep And Traditional Machine Learning, Gowtham Chandrasekaran

Master's Projects

Distracted driving is a major contributor to motor vehicle accidents, causing injury and loss of life. It is one of the major factors that affect the overall driving behavior of a person. Insurance companies take into consideration factors like gender, age, etc. to set insurance premiums for their customers. Today, machine learning and artificial intelligence can eradicate this bias. A machine learning model can analyze driving behavior, such as the frequency and severity of accidents, the speed at which they drive, and their habits such as distracted driving. Based on this information, the model can then determine the risk of …

Spartandark: Anonymity Model Integration With A Blockchain Network Using Spartangold, Nishanth Uchil

Master's Projects

Demand for blockchain ecosystems has seen exponential growth in recent times due to its decentralized nature and trustless verification process for the transactions involved. However, transaction data needs to be leveraged for verification, which coupled with the transparent nature of the blockchain ledger, provides sufficient data for malicious entities to reveal identities and even financial history of users. Data masking techniques have been employed over the years to make blockchain transactions anonymous, making them resistant to identity analysis, a key set of methods being zero-knowledge proof (zk-proof) protocols that guarantee zero data leak. In this research, we develop SpartanDark, a …

Enhancing The Queueing Process For Yioop's Scheduler, Gargi Sheguri

Master's Projects

Indexing in search engines is the process of storing information related to crawled pages to facilitate searches. A crucial determinant of the success of a search engine is the efficiency of the indexing process utilized, which greatly affects both the speed and relevancy of search results. Yioop is an open-source web search engine that employs an inverted index strategy, wherein each term is mapped to a list of the documents it appeared in while crawling.

The primary aim of this project is to better the indexing system used by Yioop, and thus improve the quality of the Search Engine Results …

Temporal Dilation In Video Resnet For Sign Language Translation, Xiaoqian Yang

Master's Projects

Sign languages, vital for communication among the deaf and hard-of-hearing (DHH) people, face a significant linguistic diversity challenge with over 200 distinct sign languages worldwide. Bridging this communication gap is a priority. Traditional tools like interpreters and costly translation devices have limitations. This project aims to use deep learning techniques to develop a model capable of recognizing sign language from short videos. Our model not only recognizes the sign from a single video clip, but is also capable of making prediction of consecutive pairs of signs. To achieve zero-short gesture sequence recognition, we propose a novel temporal dilation strategy, converting …

Graphical User Interface For Evidential Reasoning Models, Rohin Gopalakrishnan

Master's Projects

The Capri system is an evidential reasoning system based on the belief function calculus to support automated reasoning and decision making in uncertain environments. Example domains of application include, medical diagnosis, as well as identifying biological biomarkers. The purpose of this project is to build a Python web-based and app-based Graphical User Interface (GUI), called PyGrapher, that facilitates building graphical evidential reasoning models. The graphical models built using PyGrapher will then be converted to a form that is suitable for input to the Capri system. The PyGrapher system provides an intuitive means to build and manipulate evidential reasoning models as …

Nuancenet: Comparative Analysis Of Ai In Complex Language Interpretation For Disaster Detection, Pavan Koushik Kommuri

Master's Projects

Disaster Detection using Twitter content is critical for emergency response, but accurately identifying relevant tweets remains challenging due to nuances, informal language, and emotional expressions. This paper presents a comparative analysis between traditional Machine Learning models, Deep Learning models and Large Language Models (LLM) for classifying disaster vs. non-disaster tweets. While existing works have applied pattern recognition and dataset-specific learning, LLMs with their deeper understanding of linguistics and semantics can potentially handle the complexities of tweets more effectively. This study leverages LLMs including Llama2, Mistral, and Falcon, Open AI GPT 3.5, hypothesizing their superior contextual comprehension will excel in tweets …