Science and Technology Studies Commons^™

"The Devil Is In The Details:" Inland Northwest Stakeholders’ Views On Three Forest-Based Bioenergy Scenarios, Soren Newman, Darin Saul, Robert Keefe, Ryan Jacobson, Tamara Laninga, Jillian Moroney

University Author Recognition Bibliography: 2017

Public and private initiatives are actively exploring a range of forest-based bioenergy development options in the Inland Northwest of the United States. These efforts are motivated in part by the potential to generate renewable energy while creating a market for forest residues that would facilitate hazardous fuels reduction and provide economic opportunities. Understanding stakeholders’ perspectives is critical to the feasibility and long-term viability of bioenergy projects. This study presents stakeholder perspectives on forest-based bioenergy development strategies for communities in the forested areas of Idaho, western Montana, eastern Washington, and eastern Oregon. We developed three scenarios based on bioenergy initiatives currently …

Examining The Relationships Between Gender Role Congruity, Identity, And The Choice To Persist For Women In Undergraduate Physics Majors, Bronwen Bares Pelaez

FIU Electronic Theses and Dissertations

Persistent gender disparity limits the available contributors to advancing some science, technology, engineering, and math (STEM) fields. While higher education can be an influential time-point for ensuring adequate participation, many physics programs across the U.S. have few women in classroom or lab settings. Prior research indicates that these women face considerable barriers. For university students, faculty, and administration to appropriately address these issues, it is important to understand the experiences of women as they navigate male-dominated STEM fields.

This explanatory sequential mixed methods study explored undergraduate female physics majors’ experiences with their male-dominated academic and research spaces in the U.S. …

Picture This: Using Photo-Research Exhibits As Science Outreach, Eden J.V. Hennessey, Mindi D. Foster, Shohini Ghose

Psychology Faculty Publications

Is a picture worth a thousand words? This paper discusses a unique science outreach initiative–provocative photo-research exhibits on sexism in science.

Gender imbalance in science, technology, engineering, and math (STEM) is not only a concern from a social justice perspective, but also has negative consequences for scientific innovation and the economy, given that lack of workplace gender diversity is associated with lower revenue and returns. Science outreach (i.e., public outreach by scientists) could be particularly impactful in Waterloo, Ontario – a region known as ‘Canada’s Silicon Valley’ that contributes over $30-billion annually to the global economy. Portraying complex social issues …

Vr Usability From Elderly Cohorts: Preparatory Challenges In Overcoming Technology Rejection, George Coldham, David M. Cook

Dr. David M Cook

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 …

Kelihos Botnet: A Never-Ending Saga, Arsh Arora, Max Gannon, Gary Warner

Annual ADFSL Conference on Digital Forensics, Security and Law

This paper investigates the recent behavior of the Kelihos botnet, a spam-sending botnet that accounts for many millions of emails sent each day. The paper demonstrates how a team of students are able to perform a longitudinal malware study, making significant observations and contributions to the understanding of a major botnet using tools and techniques taught in the classroom. From this perspective the paper has two objectives: encouragement and observation. First, by providing insight into the methodology and tools used by student researchers to document and understand a botnet, the paper strives to embolden other academic programs to follow a …

Parallel Design Of A Product And Internet Of Things (Iot) Architecture To Minimize The Cost Of Utilizing Big Data (Bd) For Sustainable Value Creation, Ryan Bradley, Ibrahim S. Jawahir, Niko Murrell, Julie Whitney

Institute for Sustainable Manufacturing Faculty Publications

Information has become today's addictive currency; hence, companies are investing billions in the creation of Internet of Things (IoT) frameworks that gamble on finding trends that reveal sustainability and/or efficiency improvements. This approach to “Big Data” can lead to blind, astronomical costs. Therefore, this paper presents a counter approach aimed at minimizing the cost of utilizing “Big Data” for sustainable value creation. The proposed approach leverages domain/expert knowledge of the system in combination with a machine learning algorithm in order to limit the needed infrastructure and cost. A case study of the approach implemented in a consumer electronics company is …

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 …

Yale’S Environmental Performance Index: The Construction And Use Of A Composite Index For Global Sustainability, Zach Wendling

Yale Day of Data

No abstract provided.

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.

The Future Of The Iran Nuclear Deal: Pretty Bright From Its Verification Lens, Mutti Anggitta

International Journal of Nuclear Security

This manuscript discusses the JCPOA’s verification mechanism, especially its four innovative additional safeguards measures: much broader monitoring of Iran’s nuclear program, access with a deadline and dispute resolution mechanism, the Procurement Channel, and the prohibition of weaponization activities. It considers the possible implications of such safeguards measures for the future of the deal and for the non-proliferation regime. This manuscript found that the four additional safeguards measures, if implemented with the Iran’s Comprehensive Safeguards Agreement and the Additional Protocol, would increase the effectiveness of monitoring and verification measures under the deal. In short, they will significantly contribute to the success …

Assessing Patient And Caregiver Intent To Use Mobile Device Videoconferencing For Remote Mechanically-Ventilated Patient Management, Brian R. Smith

Master's Theses and Doctoral Dissertations

The Michigan Medicine adult Assisted Ventilation Clinic (AVC) supports patients with neuromuscular disorders and spinal cord injuries and their caregivers at home, helping them avoid expensive emergency department visits, hospitalization, and unnecessary or excessive treatments. Mobile device videoconferencing provides an effective capability for remote mechanically-ventilated patient management but must rely upon an unknown infrastructure comprising patient and caregiver mobile device ownership, connectivity, and experience—and intent to use the service if provided. The purpose of this study was to measure the extent of this infrastructure and the perceived ease of use, perceived usefulness, and intent to use this mobile device …

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 …