Computer Sciences Commons^™

Foodai: Food Image Recognition Via Deep Learning For Smart Food Logging, Doyen Sahoo, Hao Wang, Ke Shu, Xiongwei Wu, Hung Le, Palakorn Achananuparp, Ee-Peng Lim, Hoi, Steven C. H.

Research Collection School Of Computing and Information Systems

An important aspect of health monitoring is effective logging of food consumption. This can help management of diet-related diseases like obesity, diabetes, and even cardiovascular diseases. Moreover, food logging can help fitness enthusiasts, and people who wanting to achieve a target weight. However, food-logging is cumbersome, and requires not only taking additional effort to note down the food item consumed regularly, but also sufficient knowledge of the food item consumed (which is difficult due to the availability of a wide variety of cuisines). With increasing reliance on smart devices, we exploit the convenience offered through the use of smart phones …

Effective Statistical Energy Function Based Protein Un/Structure Prediction, Avdesh Mishra

LSU New Orleans Theses and Dissertations

Proteins are an important component of living organisms, composed of one or more polypeptide chains, each containing hundreds or even thousands of amino acids of 20 standard types. The structure of a protein from the sequence determines crucial functions of proteins such as initiating metabolic reactions, DNA replication, cell signaling, and transporting molecules. In the past, proteins were considered to always have a well-defined stable shape (structured proteins), however, it has recently been shown that there exist intrinsically disordered proteins (IDPs), which lack a fixed or ordered 3D structure, have dynamic characteristics and therefore, exist in multiple states. Based on …

Law Library Blog (August 2019): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Successful Shot Locations And Shot Types Used In Ncaa Men’S Division I Basketball, Olivia D. Perrin

All NMU Master's Theses

The primary purpose of the current study was to investigate the effect of court location (distance and angle from basket) and shot types used on shot success in NCAA Men’s DI basketball during the 2017-18 season. A secondary purpose was to further expand the analysis based on two additional factors: player position (guard, forward, or center) and team ranking. All statistical analyses were completed in RStudio and three binomial logistic regression analyses were performed to evaluate factors that influence shot success; one for all two and three point shot attempts, one for only two point attempts, and one for only …

Data-Driven Surgical Duration Prediction Model For Surgery Scheduling: A Case-Study For A Practice-Feasible Model In A Public Hospital, Kar Way Tan, Francis Ngoc Hoang Long Nguyen, Boon Yew Ang, Jerald Gan, Sean Shao Wei Lam

Research Collection School Of Computing and Information Systems

Hospitals have been trying to improve the utilization of operating rooms as it affects patient satisfaction, surgery throughput, revenues and costs. Surgical prediction model which uses post-surgery data often requires high-dimensional data and contains key predictors such as surgical team factors which may not be available during the surgical listing process. Our study considers a two-step data-mining model which provides a practical, feasible and parsimonious surgical duration prediction. Our model first leverages on domain knowledge to provide estimate of the first surgeon rank (a key predicting attribute) which is unavailable during the listing process, then uses this predicted attribute and …

Data-Driven Decision-Support For Process Improvement Through Predictions Of Bed Occupancy Rates, Kar Way Tan, Qi You Ng, Francis Ngoc Hoang Long Nguyen, Sean Shao Wei Lam

Research Collection School Of Computing and Information Systems

Managing bed utilization and ensuring the supply keeps up with the demand is not an easy task in a large public hospital with many medical disciplines. The bed managers who makes decisions on reserving and allocating beds centrally require high-dimensional data from several hospital information systems supporting emergency room, specialized clinics and bed management processes. In this work, we put together an automated process for cleaning, consolidating and integrating data from several hospital information systems to several reports required by the bed managers to analyse the bed occupancy situations across more than thirty medical disciplines. To prevent bed crunch situations …

Investigating The Effects Of Social And Temporal Dynamics In Fitness Games On Children's Physical Activity, Ankita Samariya

Boise State University Theses and Dissertations

Obesity in children has more than doubled in the last four decades. A variety of fitness technologies such as activity trackers, exergames, and mobile applications are available to promote physical activity, but few are designed adequately to meet children's specific needs. In my initial research, I found that children prefer having social interaction, a narrative, and flexibility while interacting with such technologies. Other research has shown that persuasive displays encouraged adults towards physical activity. As a part of this work, a collection of mobile applications, collectively known as KidFit Suite were developed. These applications encourage children to be physically active …

Designing The Arriving Refugee Informatics Surveillance And Epidemiology (Arive) System: A Web-Based Electronic Database For Epidemiological Surveillance, William A. Mattingly, Ruth M. Carrico, Timothy L. Wiemken, Robert R. Kelley, Rebecca A. Ford, Rahel Bosson, Kimberley A. Buckner, Julio A. Ramirez

Journal of Refugee & Global Health

Objectives: We design and implement the Arriving Refugee Informatics surVeillance and Epidemiology (ARIVE) system to improve the health of refugees undergoing resettlement and enhance existing health surveillance networks.

Materials and Methods: Using the REDCap electronic data capture software as a basis we create a refugee health database incorporating data from the Center for Disease Control and Prevention’s Electronic Disease Notification (EDN) system and domestic screening data from refugee health care providers.

Results: Domestic screening and EDN refugee health data have been integrated for 13,824 refugees resettled from 35 different countries into the state of Kentucky from the years 2013-2016.

Discussion: …

Identifying Depression In The National Health And Nutrition Examination Survey Data Using A Deep Learning Algorithm, Jihoon Oh, Kyongsik Yun, Uri Maoz, Tae-Suk Kim, Jeong-Ho Chae

Psychology Faculty Articles and Research

Background

As depression is the leading cause of disability worldwide, large-scale surveys have been conducted to establish the occurrence and risk factors of depression. However, accurately estimating epidemiological factors leading up to depression has remained challenging. Deep-learning algorithms can be applied to assess the factors leading up to prevalence and clinical manifestations of depression.

Methods

Customized deep-neural-network and machine-learning classifiers were assessed using survey data from 19,725 participants from the NHANES database (from 1999 through 2014) and 4949 from the South Korea NHANES (K-NHANES) database in 2014.

Results

A deep-learning algorithm showed area under the receiver operating characteristic curve (AUCs) …

Improving 3d Printed Prosthetics With Sensors And Motors, Rachel Zarin

Honors Projects

A 3D printed hand and arm prosthetic was created from the idea of adding bionic elements while keeping the cost low. It was designed based on existing models, desired functions, and materials available. A tilt sensor keeps the hand level, two motors move the wrist in two different directions, a limit switch signals the fingers to open and close, and another motor helps open and close the fingers. All sensors and motors were built on a circuit board, programmed using an Arduino, and powered by a battery. Other supporting materials include metal brackets, screws, guitar strings, elastic bands, small clamps, …

Social Media Text Mining Framework For Drug Abuse: An Opioid Crisis Case Analysis, Tareq Nasralah

Masters Theses & Doctoral Dissertations

Social media is considered as a promising and viable source of data for gaining insights into various disease conditions, patients’ attitudes and behaviors, and medications. The daily use of social media provides new opportunities for analyzing several aspects of communication. Social media as a big data source can be used to recognize communication and behavioral themes of problematic use of prescription drugs. Mining and analyzing such media have challenges and limitations with respect to topic deduction and data quality. There is a need for a structured approach to efficiently and effectively analyze social media content related to drug abuse in …

Early Information Access To Alleviate Emergency Department Congestion, Anjee Gorkhali

Theses and Dissertations in Business Administration

Alleviating Emergency Department (ED) congestion results in shorter hospital stay which not only reduces the cost of medical procedure but also increase the hospital performance. Length of patient stay is used to determine the hospital performance. Organization Information Processing (OIPT) Theory is used to explain the impact of information access and availability on the information processing need and ability of a hospital. Technical devices such as RFID that works as “Auto Identification tags” is suggested to increase the information availability as well as the information processing capability of the hospitals. This study suggests that the OIPT needs to be further …

Stressmon: Large Scale Detection Of Stress And Depression In Campus Environment Using Passive Coarse-Grained Location Data, Camellia Zakaria

Dissertations and Theses Collection (Open Access)

The rising mental health illnesses of severe stress and depression is of increasing concern worldwide. Often associated by similarities in symptoms, severe stress can take a toll on a person’s productivity and result in depression if the stress is left unmanaged. Unfortunately, depression can occur without any feelings of stress. With depression growing as a leading cause of disability in economic productivity, there has been a sharp rise in mental health initiatives to improve stress and depression management. To offer such services conveniently and discreetly, recent efforts have focused on using mobile technologies. However, these initiatives usually require users to …

Use Of Amulet In Behavioral Change For Geriatric Obesity Management, John A. Batsis, Alexandra B. Zagaria, Ryan J. Halter, George G. Boateng, Patrick Proctor, Stephen J. Bartels, David Kotz

Dartmouth Scholarship

Background: Obesity in older adults is a significant public health concern. Weight-loss interventions are known to improve physical function but risk the development of sarcopenia. Mobile health devices have the potential to augment existing interventions and, if designed accordingly, could improve one’s physical activity and strength in routine physical activity interventions.

Methods and results: We present Amulet, a mobile health device that has the capability of engaging patients in physical activity. The purpose of this article is to discuss the development of applications that are tailored to older adults with obesity, with the intention to engage and improve their health. …

Integration Of Random Forest Classifiers And Deep Convolutional Neural Networks For Classification And Biomolecular Modeling Of Cancer Driver Mutations, Steve Agajanian, Odeyemi Oluyemi, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Development of machine learning solutions for prediction of functional and clinical significance of cancer driver genes and mutations are paramount in modern biomedical research and have gained a significant momentum in a recent decade. In this work, we integrate different machine learning approaches, including tree based methods, random forest and gradient boosted tree (GBT) classifiers along with deep convolutional neural networks (CNN) for prediction of cancer driver mutations in the genomic datasets. The feasibility of CNN in using raw nucleotide sequences for classification of cancer driver mutations was initially explored by employing label encoding, one hot encoding, and embedding to …

Using Big Data Analytics To Improve Hiv Medical Care Utilisation In South Carolina: A Study Protocol, Bankole Olatosi, Jiajia Zhang, Sharon Weissman, Jianjun Hu, Mohammad Rifat Haider, Xiaoming Li

Faculty Publications

Introduction Linkage and retention in HIV medical care remains problematic in the USA. Extensive health utilisation data collection through electronic health records (EHR) and claims data represent new opportunities for scientific discovery. Big data science (BDS) is a powerful tool for investigating HIV care utilisation patterns. The South Carolina (SC) office of Revenue and Fiscal Affairs (RFA) data warehouse captures individual-level longitudinal health utilisation data for persons living with HIV (PLWH). The data warehouse includes EHR, claims and data from private institutions, housing, prisons, mental health, Medicare, Medicaid, State Health Plan and the department of health and human services. The …

Development And Usability Assessment Of A Connected Resistance Exercise Band Application For Strength-Monitoring, John A. Batsis, George G. Boateng, Lillian M. Seo, Curtis L. Petersen, Karen L. Fortuna, Emily V. Wechsler, Ronald J. Peterson, Summer B. Cook, Dawna Pidgeon, Rachel S. Dokko, Ryan J. Halter, David F. Kotz

Dartmouth Scholarship

Resistance exercise bands are a core component of any physical activity strengthening program. Strength training can mitigate the development of sarcopenia, the loss of muscle mass or strength and function with aging. Yet, the adherence of such behavioral exercise strategies in a home-based setting are fraught with issues of monitoring and compliance. Our group developed a Bluetooth-enabled resistance exercise band capable of transmitting data to an open-source platform. In this work, we developed an application to capture this information in real-time, and conducted three usability studies in two mixed-aged groups of participants (n=6 each) and a group of older adults …

Deep Ecg Estimation Using A Bed-Attached Geophone, Jae Yeon Park, Hyeon Cho, Wonjun Hwang, Rajesh Krishna Balan, Jeong Gil Ko

Research Collection School Of Computing and Information Systems

Electrocardiogram (ECG) signals offer rich information for analyzing and understanding the cardiac activity of a person. The continuous monitoring of ECG can help diagnose cardiac disorders, such as arrhythmia, effectively. While many wearable healthcare platforms offer continuous ECG monitoring, these devices are cumbersome in the fact that they need to be continuously attached to the human body, which causes uncomfortableness, and limits their usage when monitoring a person's ECG throughout the night as they sleep. In this work, we propose a fully non-intrusive sensing system for monitoring the ECG of a person while in bed. Specifically, we present Heartquake, a …

Towards Human Retinal Cones Spatial Distribution Modeling, Matteo Paolo Lanaro, Hélène Perrier, David Coeurjolly, Victor Ostromoukhov, Alessandro Rizzi

MODVIS Workshop

No abstract provided.

Differential Estimation Of Audiograms Using Gaussian Process Active Model Selection, Trevor Larsen

McKelvey School of Engineering Graduate Student Theses & Dissertations

Classical methods for psychometric function estimation either require excessive resources to perform, as in the method of constants, or produce only a low resolution approximation of the target psychometric function, as in adaptive staircase or up-down procedures. This thesis makes two primary contributions to the estimation of the audiogram, a clinically relevant psychometric function estimated by querying a patient’s for audibility of a collection of tones. First, it covers the implementation of a Gaussian process model for learning an audiogram using another audiogram as a prior belief to speed up the learning procedure. Second, it implements a use case of …

“Greening” Worcester: Municipal Best Practices For Sustainability, Erin Mckeon, Charline Kirongozi, Jared Duval, Antannia Greene, Qianshu Sun, Zewei Yao

School of Professional Studies

In response to the urgent threat posed by climate change, more and more cities, including Worcester, are attempting to become more environmentally responsible and sustainable. Worcester is attempting to develop ways to become more sustainable; both to strengthen their communities and to protect the planet. The Green Worcester Working Group (GWWG) tasked the Clark Capstone Team with researching best practices for municipal sustainability. The GWWG has set the following priorities: climate change mitigation, resilience, open spaces, sustainable resource management, education and awareness. Taking these into account, the Clark Capstone Team researched the sustainability practices of cities in New England, across …

Worcester Chamber Of Commerce: Recruiting Minority Business Owners, Ryan Dimaria, Alexander Hull, Xikun Lu, Haopeng Wang, Jiacheng Hou, Danning Zhao

School of Professional Studies

Our capstone project was to help the Worcester Regional Chamber of Commerce identify how to re-frame their marketing so it would be appealing to immigrant and minority owned businesses. Based on interviews and external research, our group was able to create a tangible and resourceful data set that provided justified recommendations and ideas on how the Chamber could make adjustments to their marketing plan to attract more businesses of this particular demographic in the city of Worcester. By implementing these recommendations, we believe the Chamber has the opportunity to create a more diverse group of Chamber members, add value to …

Service Now: Cmdb Research, Monika Patel, Smita Patil, Katerina Tzanavara, Manish Chauhan, Yuhao Wang, Houmin Xie, Lei Shi

School of Professional Studies

The MAPFRE Capstone team has been tasked with reviewing and recommending roadmap on the existing CMDB configuration. Paper discusses the team’s overall research on ServiceNow CMDB, Client’s deliverables and introduction to the latest technological innovations. Based on given objectives and team’s analysis we have recommended key solutions for the client to better understand the IT environment areas of business service impact, asset management, compliance, and configuration management. In addition, our research has covered all the majority of the technical and functional areas to provide greater visibility and insight into existing CMDB and IT environment.

For One Child, Zion Bereket, Xin Huang, Yitong Lin, Ruobing Pei, Rachel White, Ziyuan Li

School of Professional Studies

The entirety of this project was completed on the foundation of the three focus areas, which were identified by our client as areas of high need. The client wanted to prioritize these three areas as they believed that these three areas were the most integral to the successful achievement of their mission, as well as to the overall health and longevity of the organization.

Hiv/Aids In The Latino Community Of San Francisco: Past And Present, Jessica Da Silva

School of Professional Studies

There are approximately 122,000 people of Latino origin in San Francisco, which account for 15% of the total population (Census, 2010). Historically, Latinos have and still face several barriers to access healthcare and improvements in health (Aguirre-Molina, Molina & Zambrana, 2001). When the world was exposed to the spread of a new and unknown virus, the broader population suffered from the epidemic. The Latino community in San Francisco was and still is one of the hardest hit by the virus.

Changing The Current Perception Of Affordable Housing In Worcester, Simone Mcguinness, William Roberts, Vaske Gjino, Tong Zhou, Mengxin Ma, Sarawadee Sonpuak

School of Professional Studies

One of Worcester Interfaith’s goals is to eradicate the stigma of affordable housing in Worcester. Currently, the perception of affordable housing is of an image of unkept and old residences filled with destitute citizens who cannot afford basic needs to live in a city, let alone housing. This image is perpetuated by media, stigma, and a lack of education of the true reality of affordable housing and who its recipients are. Affordable housing-qualified citizens represent a range of educations, professions, age, race, and income levels. Affordable housing units, too, represent a variety of homes, many of which are extremely well-kept …

Seeing Eye To Eye: A Machine Learning Approach To Automated Saccade Analysis, Maigh Attre

Honors Scholar Theses

Abnormal ocular motility is a common manifestation of many underlying pathologies particularly those that are neurological. Dynamics of saccades, when the eye rapidly changes its point of fixation, have been characterized for many neurological disorders including concussions, traumatic brain injuries (TBI), and Parkinson’s disease. However, widespread saccade analysis for diagnostic and research purposes requires the recognition of certain eye movement parameters. Key information such as velocity and duration must be determined from data based on a wide set of patients’ characteristics that may range in eye shapes and iris, hair and skin pigmentation [36]. Previous work on saccade analysis has …

A Deep Learning Approach To Diagnosing Schizophrenia, Justin Barry

Electronic Theses and Dissertations

In this article, the investigators present a new method using a deep learning approach to diagnose schizophrenia. In the experiment presented, the investigators have used a secondary dataset provided by National Institutes of Health. The aforementioned experimentation involves analyzing this dataset for existence of schizophrenia using traditional machine learning approaches such as logistic regression, support vector machine, and random forest. This is followed by application of deep learning techniques using three hidden layers in the model. The results obtained indicate that deep learning provides state-of-the-art accuracy in diagnosing schizophrenia. Based on these observations, there is a possibility that deep learning …

A Virtual Reality System For Practicing Conversation Skills For Children With Autism, Natalia Stewart Rosenfield, Kathleen Lamkin, Jennifer Re, Kendra Day, Louanne E. Boyd, Erik J. Linstead

Engineering Faculty Articles and Research

We describe a virtual reality environment, Bob’s Fish Shop, which provides a system where users diagnosed with Autism Spectrum Disorder (ASD) can practice social interactions in a safe and controlled environment. A case study is presented which suggests such an environment can provide the opportunity for users to build the skills necessary to carry out a conversation without the fear of negative social consequences present in the physical world. Through the repetition and analysis of these virtual interactions, users can improve social and conversational understanding.

Deep Learning Enables Robust Assessment And Selection Of Human Blastocysts After In Vitro Fertilization, Pegah Khosravi, Ehsan Kazemi, Qiansheng Zhan, Jonas E. Malmsten, Marco Toschi, Pantelis Zisimopoulos, Alexandros Sigaras, Stuart Lavery, Lee A. D. Cooper, Cristina Hickman, Marcos Meseguer, Zev Rosenwaks, Olivier Elemento, Nikica Zaninovic, Iman Hajirasouliha

Publications and Research

Visual morphology assessment is routinely used for evaluating of embryo quality and selecting human blastocysts for transfer after in vitro fertilization (IVF). However, the assessment produces different results between embryologists and as a result, the success rate of IVF remains low. To overcome uncertainties in embryo quality, multiple embryos are often implanted resulting in undesired multiple pregnancies and complications. Unlike in other imaging fields, human embryology and IVF have not yet leveraged artificial intelligence (AI) for unbiased, automated embryo assessment. We postulated that an AI approach trained on thousands of embryos can reliably predict embryo quality without human intervention. We …