Life Sciences Commons^™

Poster: Image Disguising For Privacy-Preserving Deep Learning, Sagar Sharma, Keke Chen

Kno.e.sis Publications

No abstract provided.

Feasibility Of Recording Sleep Quality And Sleep Duration Using Fitbit In Children With Asthma, Amit Sheth, Hong Y. Yip, Utkarshani Jaimini, Dipesh Kadariya, Vaikunth Sridharan, Revathy Venkataramanan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra

Kno.e.sis Publications

Sleep disorders are common in children with asthma and are increasingly implicated in poor asthma control. Smart wearables such as the Fitbit wristband allow monitoring of users’ sleep duration and quality in their natural surroundings. However, the utility and efficacy of using such wearable devices to monitor sleep in pediatric patients with asthma have not been well-established. Thus, the objective of this study is to demonstrate the feasibility of recording sleep quality and sleep duration using Fitbit in children with asthma.

Khealth: A Personalized Healthcare Approach For Pediatric Asthma, Utkarshani Jaimini, Hong Y. Yip, Revathy Venkataramanan, Dipesh Kadariya, Vaikunth Sridharan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra, Amit Sheth

Kno.e.sis Publications

Can we assess the asthma control level, determine vulnerability, and medication compliance for a patient? Can we understand the causal relationship between the asthma symptom and possible factors responsible for it? Can we reduce the number of asthma attacks through continuous monitoring of the patient’s health condition?

“How Is My Child’S Asthma?” Digital Phenotype And Actionable Insights For Pediatric Asthma, Utkarshani Jaimini, Krishnaprasad Thirunarayan, Maninder Kalra, Revathy Venkataramanan, Dipesh Kadariya, Amit Sheth

Kno.e.sis Publications

Background: In the traditional asthma management protocol, a child meets with a clinician infrequently, once in 3 to 6 months, and is assessed using the Asthma Control Test questionnaire. This information is inadequate for timely determination of asthma control, compliance, precise diagnosis of the cause, and assessing the effectiveness of the treatment plan. The continuous monitoring and improved tracking of the child’s symptoms, activities, sleep, and treatment adherence can allow precise determination of asthma triggers and a reliable assessment of medication compliance and effectiveness. Digital phenotyping refers to moment-by-moment quantification of the individual-level human phenotype in situ using data from …

Personalized Health Knowledge Graph, Amelia Gyrard, Manas Gaur, Saeedeh Shekarpour, Krishnaprasad Thirunarayan, Amit Sheth

Kno.e.sis Publications

Our current health applications do not adequately take into account contextual and personalized knowledge about patients. In order to design “Personalized Coach for Healthcare” applications to manage chronic diseases, there is a need to create a Personalized Healthcare Knowledge Graph (PHKG) that takes into consideration a patient’s health condition (personalized knowledge) and enriches that with contextualized knowledge from environmental sensors and Web of Data (e.g., symptoms and treatments for diseases). To develop PHKG, aggregating knowledge from various heterogeneous sources such as the Internet of Things (IoT) devices, clinical notes, and Electronic Medical Records (EMRs) is necessary. In this paper, we …

Khealth Digital Personalized Healthcare Technology For Pediatric Asthma, Utkarshani Jaimini, Hong Y. Yip, Revathy Venkataramanan, Dipesh Kadariya, Vaikunth Sridharan, Tanvi Banerjee, Krishnaprasad Thirunarayan, Maninder Kalra, Amit Sheth

Kno.e.sis Publications

Episodic:Traditional Clinician Centric Healthcare

Questions to be answered:

1.Can we reduce the number of asthma attacks through continuous monitoring of the patient's health condition?

2.Can we predict the asthma attack based on the data collected from the patient?

3.Can we predict the asthma vulnerability score for a patient?

4.Can we predict the asthma severity level of a patient?

5.Can we understand the casual relationship between the asthma symptom and the possible factors responsible for it?

Rehabilitation Of An Injured Golden Eagle (Aquila Chrysaetos): A Case Study, Fida Muhammad Khan, Fakhar-I- Abbas, Abu Ul Hassan Faiz

Journal of Bioresource Management

Habitat destruction and anthropogenic activities cause wild birds to migrate towards urban areas in search of food and sometimes nesting in high-roof buildings, where they are caught by local people using different techniques and are further used for hunting or recreational purposes. An injured Golden Eagle (Aquila chrysaetos) was found entangled in bushes near the vicinity of Balkasar Research Complex, Chakwal, Pakistan. After complete physical examination, a wound on the right wing and closed leg fracture was diagnosed. The successful treatment was done by anti-parasitic and anti-bacterial drugs with careful monitoring. Splint was adjusted after aligning the fractured …

Discovering Explanatory Models To Identify Relevant Tweets On Zika, Roopteja Muppalla, Michele Miller, Tanvi Banerjee, William L. Romine

Kno.e.sis Publications

Zika virus has caught the worlds attention, and has led people to share their opinions and concerns on social media like Twitter. Using text-based features, extracted with the help of Parts of Speech (POS) taggers and N-gram, a classifier was built to detect Zika related tweets from Twitter. With a simple logistic classifier, the system was successful in detecting Zika related tweets from Twitter with a 92% accuracy. Moreover, key features were identified that provide deeper insights on the content of tweets relevant to Zika. This system can be leveraged by domain experts to perform sentiment analysis, and understand the …

A Knowledge Graph Framework For Detecting Traffic Events Using Stationary Cameras, Roopteja Muppalla, Sarasi Lalithsena, Tanvi Banerjee, Amit Sheth

Kno.e.sis Publications

With the rapid increase in urban development, it is critical to utilize dynamic sensor streams for traffic understanding, especially in larger cities where route planning or infrastructure planning is more critical. This creates a strong need to understand traffic patterns using ubiquitous sensors to allow city officials to be better informed when planning urban construction and to provide an understanding of the traffic dynamics in the city. In this study, we propose our framework ITSKG (Imagery-based Traffic Sensing Knowledge Graph) which utilizes the stationary traffic camera information as sensors to understand the traffic patterns. The proposed system extracts image-based features …

La Crisis Ignorada, Joseph Pokorski

Best Integrated Writing

Pokorski researched the food production practices of pre-Columbian civilizations. He uses his research to evaluate the current food production practices of transnational corporations and offers suggestions for best practices.

Best Integrated Writing 2017 - Complete Edition

Best Integrated Writing

Best Integrated Writing includes excellent student writing from Integrated Writing courses taught at Wright State University. The journal is published annually by the Wright State University Department of English Language and Literatures.

Khealth Bariatrics: A Multisensory Approach To Monitoring Patient’S Postsurgical Behavior, Revathy Venkataramanan, Utkarshani Jaimini, Amit Sheth, Joon K. Shim, Priti Parikh, Dene S. Berman

Symposium of Student Research, Scholarship, and Creative Activities Materials

The rate of obesity is on the rise reaching epidemic proportions. According to American Society for Metabolic and Bariatric Surgery (ASMBS), 500 million people all over the world are obese. The data from Centers for Disease Control and Prevention(CDC) shows that more than 36% of adults in the United States have obesity. According to World Health Organization (WHO), 65% of the world’s population lives in countries where the occurrence of death due to overweight and obesity is higher than being underweight. It is well established that weight loss surgery can play a significant role in reducing, or even eliminating medical …

Measuring Gender-Based Violence Attitude On Twitter, Goonmeet Bajaj, Tanvi Banerjee, Amir Hossein Yazdavar, Valerie L. Shalin, Amit Sheth

Symposium of Student Research, Scholarship, and Creative Activities Materials

This study examines social media to analyze communication patterns, specifically in the Gender-Based Violence domain. It explores the pragmatic content of tweets to categorize them into one of the following groups: Belief, Fact Reporting, or Other to determine the tweeting practices prevalent in this domain.

Legalization Of Gay Marriage And Its Impact On Military Stereotypes Of Homosexuals, Jasmine Moore

Symposium of Student Research, Scholarship, and Creative Activities Materials

Homosexuality has become a popular research topic in a variety of professional fields, and over the last decade has become a priority for the military. Since the implementation of the law repealing Don't Ask Don't Tell (DADT) researchers have questioned what effects repealing this law has had on the military as a whole. Particular attention has been spent on studying the attitudes and stereotypes about homosexuals after DADT was repealed. However, there is a lack of research examining how marriage equality affects society's stereotypes about homosexuals serving in the United States military.

It was hypothesized that participants that have personal …

Wright State University's Celebration Of Research, Scholarship And Creative Activities Book Of Abstracts From Friday, April 21, 2017, Wright State University

Symposium of Student Research, Scholarship, and Creative Activities Materials

The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Annual Celebration of Research, Scholarship and Creative Activities on April 21, 2017.

Treating Chronic Post Herpetic Neuralgia Using Topical Superconcentrated Capsaicin, Jaree Naqvi, Scott Seider, Jason Miller, Cole Budinsky, Amol Soin

Symposium of Student Research, Scholarship, and Creative Activities Materials

Post Herpetic Neuralgia (PHN) is a painful condition that occurs after reactivation of the dormant Herpes Zoster Virus.Typically PHN presents with a unilateral rash affecting a single dermatome which is accompanied by burning, irritation, and hypersensitivity for >3 months.Current treatment includes anticonvulsants, tricyclic antidepressants, narcotic/nonnarcotic painkillers, and topical lidocaine.

We propose the utilization of a superconcentrated transdermal patch of capsaicin called Qutenza 8%, which is 300 times more potent than current OTC capsaicin. The treatment protocol using Qutenza to treat refractory PHN proposes a novel approach to the treatment of this condition.

Capsaicin is commonly known as the active chemical …

Social Workers’ Salaries Vs. Educational Student Debt Burden: A Losing Battle, Michael Wadham

Symposium of Student Research, Scholarship, and Creative Activities Materials

College tuitions rise at disparate rates with starting salaries and inflation, causing student debt to weigh on social work graduates. Data was collected from 701 social workers in an NASW - Ohio Chapter survey to investigate this disparity and its consequences. The purpose of this study was to analyze the qualitative data set, 174 written comments, for themes and perceptions. The following themes, echoed in current research on the topics of social work salary and student debt burden, were identified: unmanageable debt and financial burden, varying lengths of time and repayment methods, social workers feeling undervalued and underpaid, loan forgiveness …

Eassistant: Cognitive Assistance For Identification And Auto-Triage Of Actionable Conversations, Hamid R. Motahari Nezhad, Kalpa Gunaratna, Juan Cappi

Kno.e.sis Publications

The browser and screen have been the main user interfaces of the Web and mobile apps. The notification mechanism is an evolution in the user interaction paradigm by keeping users updated without checking applications. Conversational agents are posed to be the next revolution in user interaction paradigms. However, without intelligence on the triage of content served by the interaction and content differentiation in applications, interaction paradigms may still place the burden of information overload on users. In this paper, we focus on the problem of intelligent identification of actionable information in the content served by applications, and in particular in …

What Are People Tweeting About Zika? An Exploratory Study Concerning Its Symptoms, Treatment, Transmission, And Prevention, Michele Miller, Tanvi Banerjee, Roopteja Muppalla, William L. Romine, Amit Sheth

Kno.e.sis Publications

Background: In order to harness what people are tweeting about Zika, there needs to be a computational framework that leverages machine learning techniques to recognize relevant Zika tweets and, further, categorize these into disease-specific categories to address specific societal concerns related to the prevention, transmission, symptoms, and treatment of Zika virus.

Objective: The purpose of this study was to determine the relevancy of the tweets and what people were tweeting about the 4 disease characteristics of Zika: symptoms, transmission, prevention, and treatment.

Methods: A combination of natural language processing and machine learning techniques was used to determine what people were …

Identifying Depressive Disorder In The Twitter Population, Goonmeet Bajaj, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth

Kno.e.sis Publications

Depression is a highly prevalent public health challenge and a major cause of disability across the globe.

• Annually 6.7% of Americans (that is, more than 16 million).
• Traditional approaches to curb depression involve survey·based methods via phone or online questionnaires.
• Large temporal gaps and cognitive bias.

Social media provides a method for learning users' feelings, emotions, behaviors, and decisions in real-time.

A Novel Approach For Classifying Gene Expression Data Using Topic Modeling, Soon Jye Kho, Himi Yalamanchili, Michael L. Raymer, Amit Sheth

Kno.e.sis Publications

Understanding the role of differential gene expression in cancer etiology and cellular process is a complex problem that continues to pose a challenge due to sheer number of genes and inter-related biological processes involved. In this paper, we employ an unsupervised topic model, Latent Dirichlet Allocation (LDA) to mitigate overfitting of high-dimensionality gene expression data and to facilitate understanding of the associated pathways. LDA has been recently applied for clustering and exploring genomic data but not for classification and prediction. Here, we proposed to use LDA inclustering as well as in classification of cancer and healthy tissues using lung cancer …

Road Accidents Bigdata Mining And Visualization Using Support Vector Machines, Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

Kno.e.sis Publications

Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new …

Relatedness-Based Multi-Entity Summarization, Kalpa Gunaratna, Amir Hossein Yazdavar, Krishnaprasad Thirunarayan, Amit Sheth, Gong Cheng

Kno.e.sis Publications

Representing world knowledge in a machine processable format is important as entities and their descriptions have fueled tremendous growth in knowledge-rich information processing platforms, services, and systems. Prominent applications of knowledge graphs include search engines (e.g., Google Search and Microsoft Bing), email clients (e.g., Gmail), and intelligent personal assistants (e.g., Google Now, Amazon Echo, and Apple’s Siri). In this paper, we present an approach that can summarize facts about a collection of entities by analyzing their relatedness in preference to summarizing each entity in isolation. Specifically, we generate informative entity summaries by selecting: (i) inter-entity facts that are similar and …

A Semantics-Based Measure Of Emoji Similarity, Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran

Kno.e.sis Publications

Emoji have grown to become one of the most important forms of communication on the web. With its widespread use, measuring the similarity of emoji has become an important problem for contemporary text processing since it lies at the heart of sentiment analysis, search, and interface design tasks. This paper presents a comprehensive analysis of the semantic similarity of emoji through embedding models that are learned over machine-readable emoji meanings in the EmojiNet knowledge base. Using emoji descriptions, emoji sense labels and emoji sense definitions, and with different training corpora obtained from Twitter and Google News, we develop and test …

Knowledge Of Forest Ecosystem Among Forest Guards In Southern Nigeria, Norris I. Erhabor

Journal of Bioresource Management

Undertaken study assessed the level of ecological knowledge among forest guards in southern Nigeria. Descriptive survey research design was used for study. A structured questionnaire was administered to 60 respondents that are employed by forest guards system. Central question the study attempts to answer is the level of knowledge of the ecosystem among forest guards. Analysis of data revealed that forest guards have inadequate knowledge of ecosystem. Calculated mean score of respondents was 14.25. This mean score is lower than theoretical mean of 16 (80%). A binomial test revealed that fairly high number of respondents had inadequate knowledge of …

Preliminary Investigation Of Walking Motion Using A Combination Of Image And Signal Processing, Bradley Schneider, Tanvi Banerjee

Kno.e.sis Publications

We present the results of analyzing gait motion in first-person video taken from a commercially available wearable camera embedded in a pair of glasses. The video is analyzed with three different computer vision methods to extract motion vectors from different gait sequences from four individuals for comparison against a manually annotated ground truth dataset. Using a combination of signal processing and computer vision techniques, gait features are extracted to identify the walking pace of the individual wearing the camera as well as validated using the ground truth dataset. Our preliminary results indicate that the extraction of activity from the video …

Analyzing Clinical Depressive Symptoms In Twitter, Amir Hossein Yazdavar, Hussein S. Al-Olimat, Tanvi Banerjee, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

350 million people are suffering from clinical depression worldwide.

What Motivates High School Students To Take Precautions Against The Spread Of Influenza? A Data Science Approach To Latent Modeling Of Compliance With Preventative Practice, William L. Romine, Tanvi Banerjee, William R. Folk, Lloyd H. Barrow

Kno.e.sis Publications

– This study focuses on a central question: What key behavioral factors influence high school students’ compliance with preventative measures against the transmission of influenza? We use multilevel logistic regression to equate logit measures for eight precautions to students’ latent compliance levels on a common scale. Using linear regression, we explore the efficacy of knowledge of influenza, affective perceptions about influenza and its prevention, prior illness, and gender in predicting compliance. Hand washing and respiratory etiquette are the easiest precautions for students, and hand sanitizer use and keeping the hands away from the face are the most difficult. Perceptions of …

Comparing Network Centrality Measures Of Non-Traditional Students In An Introductory Physics Class, Emily N. Sandt, Adrienne L. Traxler

Symposium of Student Research, Scholarship, and Creative Activities Materials

The goal of this research was to compare different models of network influence for students. Two research questions were composed: 1. How do common centrality measures compare when ranking students' network influence? 2. Do centrality values of non-traditional students show different trend than traditional students?

Finding Specific, Topic Related Information From A Sea Of Social Media Posts, Scott J. Duberstein, Daniel Asamoah, Derek Doran, Shu Z. Schiller

Symposium of Student Research, Scholarship, and Creative Activities Materials

As social media continues to become an incredible mode of communication in daily life dealing with the exchange of information, these systems provide authors a platform where they can share their thoughts, feelings, and experiences about a number of topics. Harnessing the information expressed publicly through these modes can be incredibly powerful: public perceptions, signals, and data about a variety of specific topics could be extracted and studied from these posts. However, there is a common trade-off in collecting information about a topic from social media: the more specific the topic, generally, the more challenging it is to extract meaningful …