Computer Sciences Commons^™

Diversity And Inclusion In The Workplace; Benefits, Challenges And Strategies For Success, Margaret Leone

School of Professional Studies

In this case study I have explored the topic of diversity and inclusion in the workplace and learned how it can transform a business. When D&I is a serious business strategy supported by senior management it can help recruit and retain top talent, increase profits, and unleash creativity among other benefits. It is important to have leadership that is inclusive so they can set the tone for their staff

This case study evaluates the D&I culture at The Children’s Study Home (CHS) and explores best practices for improvement. CHS is a non-profit human service agency in Western MA, that’s mission …

Young People, Social Media, And Impacts On Well-Being, Andreana Nop

School of Professional Studies

Millennials and Generation Z were born into an age where social media and digital technology have been integrated in nearly all aspects of their lives. While social media has proven to be a valuable communication tool in connecting with each other and sharing information, the long-term psychosocial effects are beginning to become more apparent as social media matures. This study analyzes what these effects are and how communication is impacted for these young people. It questions how young people can leverage social media and decrease harm. The study will be conducted through a literature review and analysis. Its goal is …

Managing Burnout And Secondary Traumatic Stress In Human Service Organizations, Naomi Ingram

School of Professional Studies

This Case Study explores how burnout and secondary traumatic stress impact staffing, service delivery, and organizational effectiveness in a human service agency. The Case Study is focused around Ascentria Care Alliance’s Children & Family Services in Massachusetts, which encompasses three foster care programs: the Unaccompanied Refugee Minor (URM), Division of Children’s Services (DCS), and Intensive Foster Care (IFC) programs. Both individual and organizational approaches are needed to most effectively address burnout and secondary traumatic stress. Individual workers need to build resilience factors such as self-compassion and mindfulness, set appropriate boundaries with clients, engage in ongoing training, support, consultation, and supervision, …

Rest Homes: Their Value On Massachusetts Healthcare Continuum, Ronald Pawelski

School of Professional Studies

In Massachusetts, rest homes provide cost effective care for elderly residents in a community setting. Rest homes, however, are not well-understood and the rest home industry itself suffers greatly, not only from a lack of understanding of the services they provide, but also from the strain on their financial resources due to both competition from other healthcare options and insufficient reimbursement rates for residents’ care.

The paper explores the financial challenges facing the industry and outlines the data that speaks to the value of the rest home care option for both the residents themselves and Massachusetts state healthcare budget. It …

A Case Study On The Best Practices Of The Facilitating Organization For Peer Recovery Support Services In The State Of New Hampshire, Maggie Ringey

School of Professional Studies

In working with the Facilitating Organization for Peer Recovery Support Services through Harbor Homes, I have found that the Recovery Community Organizations that receive support through the FO provide valuable services that help individuals that struggle with substance use disorder achieve and maintain long term sobriety and recovery. The RCOs throughout New Hampshire bridge gaps in services and treatments that are left untouched by traditional clinical methods and through regular check ins, participants at the RCOs have reported that the services provided resulted in positive outcomes in their lives. Throughout the course of this research, I found that the RCOs …

Elder Isolation In Immigrant Communities, Jessica Da Silva

School of Professional Studies

This paper examined loneliness, as a measurement of perceived social isolation, in older immigrant adults. Previous research shows that older adults are more likely to experience social isolation and loneliness. Both of which have a direct correlation with their overall health (Wilson & Molton, 2010, Cacioppo et al., 2002) and mortality rates (Holt-Lunstad et al, 2015). Another international study found that immigrants in particular are at a higher risk for experiencing loneliness (Government of Canada, 2018). In this study, 35 immigrants and non-immigrants participants answered a survey which included 20 questions from the UCLA Loneliness Scale Version 3 (Russel, 1996). …

Dallas, Tx: The Staggering Wealth Gap, Macy Golman

School of Professional Studies

In the summer of 2019, I had the privilege of serving as an AmeriCorps member with an organization called Equal Heart. One of Equal Heart’s main initiatives was to provide meals to children in underserved populations, to make sure that without school in session, these children would still be receiving food. Unfortunately, in many instances, without these meals, many of the children we served would likely not know when they would be eating their next fulfilling meal. There were certain pockets of Dallas that we would travel to everyday, places that were fifteen minutes maximum from my house, but places …

Early Detection Of Mild Cognitive Impairment With In-Home Sensors To Monitor Behavior Patterns In Community-Dwelling Senior Citizens In Singapore: Cross-Sectional Feasibility Study, Iris Rawtaer, Rathi Mahendran, Ee Heok Kua, Hwee-Pink Tan, Hwee Xian Tan, Tih-Shih Lee, Tze Pin Ng

Research Collection School Of Computing and Information Systems

Background: Dementia is a global epidemic and incurs substantial burden on the affected families and the health care system. A window of opportunity for intervention is the predementia stage known as mild cognitive impairment (MCI). Individuals often present to services late in the course of their disease and more needs to be done for early detection; sensor technology is a potential method for detection.Objective: The aim of this cross-sectional study was to establish the feasibility and acceptability of utilizing sensors in the homes of senior citizens to detect changes in behaviors unobtrusively.Methods: We recruited 59 community-dwelling seniors (aged >65 years …

Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim

McKelvey School of Engineering Graduate Student Theses & Dissertations

Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross-sectional nature of training and prediction processes. Finding temporal patterns in EHR is especially …

Predicting Disease Progression Using Deep Recurrent Neural Networks And Longitudinal Electronic Health Record Data, Seunghwan Kim

McKelvey School of Engineering Graduate Student Theses & Dissertations

Electronic Health Records (EHR) are widely adopted and used throughout healthcare systems and are able to collect and store longitudinal information data that can be used to describe patient phenotypes. From the underlying data structures used in the EHR, discrete data can be extracted and analyzed to improve patient care and outcomes via tasks such as risk stratification and prospective disease management. Temporality in EHR is innately present given the nature of these data, however, and traditional classification models are limited in this context by the cross- sectional nature of training and prediction processes. Finding temporal patterns in EHR is …

Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya

Electronic Theses and Dissertations

Generalized linear models have broad applications in biostatistics and sociology. In a regression setup, the main target is to find a relevant set of predictors out of a large collection of covariates. Sparsity is the assumption that only a few of these covariates in a regression setup have a meaningful correlation with an outcome variate of interest. Sparsity is incorporated by regularizing the irrelevant slopes towards zero without changing the relevant predictors and keeping the resulting inferences intact. Frequentist variable selection and sparsity are addressed by popular techniques like Lasso, Elastic Net. Bayesian penalized regression can tackle the curse of …

Development Of Fully Balanced Ssfp And Computer Vision Applications For Mri-Assisted Radiosurgery (Mars), Jeremiah Sanders

Dissertations and Theses (Open Access)

Prostate cancer is the second most common cancer in men and the second-leading cause of cancer death in men. Brachytherapy is a highly effective treatment option for prostate cancer, and is the most cost-effective initial treatment among all other therapeutic options for low to intermediate risk patients of prostate cancer. In low-dose-rate (LDR) brachytherapy, verifying the location of the radioactive seeds within the prostate and in relation to critical normal structures after seed implantation is essential to ensuring positive treatment outcomes.

One current gap in knowledge is how to simultaneously image the prostate, surrounding anatomy, and radioactive seeds within the …

Use Of Eye-Tracking To Identify Psychological Indicators Of Sleepiness, Debasis Roy, Fiona Fui-Hoon Nah, Matthew Thimgan

Research Collection School Of Computing and Information Systems

Sleepiness or sleep deprivation creates a serious hazard or obstacle to task execution and performance. Sleep deprivation can be life-threating (e.g., when driving or executing attention-critical tasks). We are interested to examine if eye-tracking technology can be used to assess and detect sleepiness in an online environment. In this research proposal, we will focus on examining the relationships between sleepiness and parameters involving pupil size, blinks, and saccades.

Who And When To Screen: Multi-Round Active Screening For Network Recurrent Infectious Diseases Under Uncertainty, Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe

Research Collection School Of Computing and Information Systems

Controlling recurrent infectious diseases is a vital yet complicated problem in global health. During the long period of time from patients becoming infected to finally seeking treatment, their close contacts are exposed and vulnerable to the disease they carry. Active screening (or case finding) methods seek to actively discover undiagnosed cases by screening contacts of known infected people to reduce the spread of the disease. Existing practice of active screening methods often screen all contacts of an infected person, requiring a large budget. In cooperation with a research institute in India, we develop a model of the active screening problem …

On Privacy-Aware Escience Workflows, Khalid Belhajjame, Noura Faci, Zakaria Maamar, Vanilson Burégio, Edvan Soares, Mahmoud Barhamgi

All Works

© 2020, Springer-Verlag GmbH Austria, part of Springer Nature. Computing-intensive experiments in modern sciences have become increasingly data-driven illustrating perfectly the Big-Data era. These experiments are usually specified and enacted in the form of workflows that would need to manage (i.e., read, write, store, and retrieve) highly-sensitive data like persons’ medical records. We assume for this work that the operations that constitute a workflow are 1-to-1 operations, in the sense that for each input data record they produce a single data record. While there is an active research body on how to protect sensitive data by, for instance, anonymizing datasets, …

A Model For The Spread Of Infectious Diseases In A Region, Elizabeth Hunter, Brian Mac Namee, John D. Kelleher

Articles

In understanding the dynamics of the spread of an infectious disease, it is important to understand how a town’s place in a network of towns within a region will impact how the disease spreads to that town and from that town. In this article, we take a model for the spread of an infectious disease in a single town and scale it up to simulate a region containing multiple towns. The model is validated by looking at how adding additional towns and commuters influences the outbreak in a single town. We then look at how the centrality of a town …

Volume 12, Haleigh James, Hannah Meyls, Hope Irvin, Megan E. Hlavaty, Samara L. Gall, Austin J. Funk, Karyn Keane, Sarah Ghali, Antonio Harvey, Andrew Jones, Rachel Hazelwood, Madison Schmitz, Marija Venta, Haley Tebo, Jeremiah Gilmer, Bridget Dunn, Benjamin Sullivan, Mckenzie Johnson

Incite: The Journal of Undergraduate Scholarship

Introduction, Dr. Roger A. Byrne, Dean

From the Editor, Dr. Larissa "Kat" Tracy

From the Designers, Rachel English, Rachel Hanson

Immortality in the Mortal World: Otherworldly Intervention in "Lanval" and "The Wife of Bath's Tale" by Haleigh James

Analysis of Phenolic Compounds in Moroccan Olive Oils by HPLC by Hannah Meyls

Art by Hope Irvin

The Effects of Cell Phone Use on Gameplay Enjoyment and Frustration by Megan E. Hlavaty, Samara L. Gall, and Austin J. Funk

Care, No Matter What: Planned Parenthood's Use of Organizational Rhetoric to Expand its Reputation by Karyn Keane

Analysis of Petroleum Products for …

Information Mining For Covid-19 Research From A Large Volume Of Scientific Literature, Sabber Ahamed, Manar D. Samad

Computer Science Faculty Research

The year 2020 has seen an unprecedented COVID-19 pandemic due to the outbreak of a novel strain of coronavirus in 180 countries. In a desperate effort to discover new drugs and vaccines for COVID-19, many scientists are working around the clock. Their valuable time and effort may benefit from computer-based mining of a large volume of health science literature that is a treasure trove of information. In this paper, we have developed a graph-based model using abstracts of 10,683 scientific articles to find key information on three topics: transmission, drug types, and genome research related to coronavirus. A subgraph is …

Visualizing Metabolic Network Dynamics Through Time-Series Metabolomic Data., Lea F Buchweitz, James T Yurkovich, Christoph Blessing, Veronika Kohler, Fabian Schwarzkopf, Zachary A King, Laurence Yang, Freyr Jóhannsson, Ólafur E Sigurjónsson, Óttar Rolfsson, Julian Heinrich, Andreas Dräger

Articles, Abstracts, and Reports

BACKGROUND: New technologies have given rise to an abundance of -omics data, particularly metabolomic data. The scale of these data introduces new challenges for the interpretation and extraction of knowledge, requiring the development of innovative computational visualization methodologies. Here, we present GEM-Vis, an original method for the visualization of time-course metabolomic data within the context of metabolic network maps. We demonstrate the utility of the GEM-Vis method by examining previously published data for two cellular systems-the human platelet and erythrocyte under cold storage for use in transfusion medicine.

RESULTS: The results comprise two animated videos that allow for new insights …

Complexities Of Data, Tasks And Workflows In Health It Management, Gaurav Jetley

USF Tampa Graduate Theses and Dissertations

This dissertation focuses on three key aspects in health IT management: (1) Complexities in the collection of health data in electronic health record (EHR) systems and the use of EHR data in research, (2) Complexities of collaboration between physicians and AI for improving healthcare delivery, and (3) Complexities of workflows and collaborations between healthcare organization (HCO) staff during the delivery of care. The first dissertation essay (Chapter 1) examines the key data quality issues that arise in recorded health information in EHR systems, provides quality thresholds that the data needs to meet for mitigating errors and increasing reproducibility of downstream …

A Survey Of Feature Extraction And Fusion Of Deep Learning For Detection Of Abnormalities In Video Endoscopy Of Gastrointestinal-Tract, Hussam Ali, Muhammad Sharif, Mussarat Yasmin, Mubashir Husain Rehmani, Farhan Riaz

Publications

A standard screening procedure involves video endoscopy of the Gastrointestinal tract. It is a less invasive method which is practiced for early diagnosis of gastric diseases. Manual inspection of a large number of gastric frames is an exhaustive, time-consuming task, and requires expertise. Conversely, several computer-aided diagnosis systems have been proposed by researchers to cope with the dilemma of manual inspection of the massive volume of frames. This article gives an overview of different available alternatives for automated inspection, detection, and classification of various GI abnormalities. Also, this work elaborates techniques associated with content-based image retrieval and automated systems for …

Cyber Security In The Healthcare Industry, Giovanni Ordonez 20

Honor Scholar Theses

No abstract provided.

Investigation Of Glucose Oxidation At Gold Nanoparticles Deposited At Carbon Nanotubes Modified Glassy Carbon Electrode By Theoretical And Experimental Methods., Farhat Saira, Humaira Razzaq, Misbah Mumtaz, Safeer Ahmad, Muhammad Aftab Rafiq, Azra Yaqub, Nabiha Dilshad, Ayesha Ihsan, Muhammad Masood Ul Hasan

Karbala International Journal of Modern Science

In the current research work, AuNPs-CNTs nanocomposite was synthesized chemically and decoration of AuNPs on the surface of MWCNTs was confirmed by UV-Vis, SEM and XPS analysis. Synthesized nanocomposite was utilized for its application towards non-enzymatic glucose sensing by modifying glassy carbon electrode with nanocomposite employing electrochemical techniques. In addition, theoretical calculations were performed by Density Functional Theory (DFT), employing B3YLP with basis set 6- 311+G(d,p) in gaseous phase and LANL2DZ basis set. Both theoretical and experimental results predicted Au-CNTs composite as a better candidate for glucose oxidation as compared to CNTs and AuNPs alone, owing to the synergistic effect …

Learning In The Machine: To Share Or Not To Share?, Jordan Ott, Erik Linstead, Nicholas Lahaye, Pierre Baldi

Engineering Faculty Articles and Research

Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible. This discrepancy raises the fundamental question of whether weight-sharing is necessary. If so, to which degree of precision? If not, what are the alternatives? The goal of this study is to investigate these questions, primarily through simulations where the weight-sharing assumption is relaxed. Taking inspiration from neural circuitry, we explore the use of Free Convolutional Networks and neurons with variable connection patterns. Using Free Convolutional Networks, we show that while weight-sharing is a pragmatic optimization …

Nf-Κb Inhibitors Attenuate Mcao Induced Neurodegeneration And Oxidative Stress—A Reprofiling Approach, Awais Ali, Fawad Ali Shah, Alam Zeb, Imran Malik, Arooj Mohsin Alvi, Lina Tariq Alkury, Sajid Rashid, Ishtiaq Hussain, Najeeb Ullah, Arif Ullah Khan, Phil Ok Koh, Shupeng Li

All Works

© Copyright © 2020 Ali, Shah, Zeb, Malik, Alvi, Alkury, Rashid, Hussain, Ullah, Ullah Khan, Koh and Li. Stroke is the leading cause of morbidity and mortality worldwide. About 87% of stroke cases are ischemic, which disrupt the physiological activity of the brain, thus leading to a series of complex pathophysiological events. Despite decades of research on neuroprotectants to probe for suitable therapies against ischemic stroke, no successful results have been obtained, and new alternative approaches are urgently required in order to combat this pathological torment. To address these problems, drug repositioning/reprofiling is explored extensively. Drug repurposing aims to identify …

A 12-Lead Ecg Database To Identify Origins Of Idiopathic Ventricular Arrhythmia Containing 334 Patients, Jianwei Zhang, Guohua Fu, Kyle Anderson, Huimin Chu, Cyril Rakovski

Mathematics, Physics, and Computer Science Faculty Articles and Research

Cardiac catheter ablation has shown the effectiveness of treating the idiopathic premature ventricular complex and ventricular tachycardia. As the most important prerequisite for successful therapy, criteria based on analysis of 12-lead ECGs are employed to reliably speculate the locations of idiopathic ventricular arrhythmia before a subsequent catheter ablation procedure. Among these possible locations, right ventricular outflow tract and left outflow tract are the major ones. We created a new 12-lead ECG database under the auspices of Chapman University and Ningbo First Hospital of Zhejiang University that aims to provide high quality data enabling detection of the distinctions between idiopathic ventricular …

A Nwb-Based Dataset And Processing Pipeline Of Human Single-Neuron Activity During A Declarative Memory Task, N. Chandravadia, D. Liang, A. G. P. Schjetnan, A. Carlson, M. Faraut, J. M. Chung, C. M. Reed, B. Dichter, Uri Maoz, S. K. Kalia, T. A. Valiante, A. N. Mamelak, U. Rutishauser

Psychology Faculty Articles and Research

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import …

Electronic Image Detectability Under Varying Illumination Conditions, Jeremy J. Miller

Theses and Dissertations

Light in the built environment plays an essential role in the vision and the health of humans through non-visual receptors in the eyes. Unfortunately, image analysts and other Air Force personnel who engage in the detection of objects on softcopy displays are often required to work in very dimly-lit or dark environments as higher illumination reduces the contrast of displayed information. Literature has shown that increases in light exposure improves circadian rhythm entrainment and reduces the negative health consequences of insufficient lighting. This research examines the effects of indoor lighting to determine if increases in ambient illumination or changes to …

Distributed Adaptive State Estimation And Tracking By Using Active-Passive Sensor Networks, Akhilesh Raj, Sarangapani Jagannathan, Tansel Yucelen

Electrical and Computer Engineering Faculty Research & Creative Works

Heterogeneous sensor networks (HSN) find a wide range of applications in the field of military and civilian environments, where sensor nodes are utilized to estimate the position of a target with both dynamics and control input being unknown for the purposes of tracking. In the HSN, nodes are considered active depending upon their ability to sense the target output while the others are taken passive. Accurate estimation requires local information exchange among the spatially located sensor nodes, so that the active nodes as well as the passive nodes converge simultaneously to the same value. The local information exchange among the …

The Application Of Digital Health To The Assessment And Treatment Of Substance Use Disorders: The Past, Current, And Future Role Of The National Drug Abuse Treatment Clinical Trials Network, Lisa A. Marsch, Aimee Campbell, Cynthia Campbell, Ching-Hua Chen, Emre Ertin, Udi Ghitza, Chantal Lambert-Harris, Saeed Hassanpour, August F. Holtyn, Yih-Ing Hser, Petra Jacobs, Jeffrey D. Klausner, Shea Lemley, David Kotz, Andrea Meier, Bethany Mcleman, Jennifer Mcneely, Varun Mishra, Larissa Mooney, Edward Nunes, Chrysovalantis Stafylis, Catherine Stanger, Elizabeth Saunders, Geetha Subramaniam, Sean Young

Dartmouth Scholarship

The application of digital technologies to better assess, understand, and treat substance use disorders (SUDs) is a particularly promising and vibrant area of scientific research. The National Drug Abuse Treatment Clinical Trials Network (CTN), launched in 1999 by the U.S. National Institute on Drug Abuse, has supported a growing line of research that leverages digital technologies to glean new insights into SUDs and provide science-based therapeutic tools to a diverse array of persons with SUDs.

This manuscript provides an overview of the breadth and impact of research conducted in the realm of digital health within the CTN. This work has …