Science and Technology Studies Commons^™

Bibliography For Interstices 2018: Beyond Human: Emotion And Ai, Kristin Laughtin-Dunker

Library Displays and Bibliographies

An annotated list of materials in the Leatherby Libraries to accompany the Interstices 2018: Beyond Human: Emotion and AI event held at Chapman University in February 2018. The event featured Lisa Joy, co-creator and executive producer of HBO’s Emmy winning hit series Westworld, Jon Gratch, Director for Virtual Human Research at the University of Southern California’s (USC) Institute for Creative Technologies and Caroline Bainbridge, a Professor of Psychoanalysis and Culture in the Department of Media, Culture and Language at the University of Roehampton London. The Leatherby Libraries also hosted two book club discussions of The Positronic …

Understanding The Novice Decision-Making Process In Forensic Footwear Examinations: Accuracy And Decision Rules, Madonna A. Nobel

Graduate Theses, Dissertations, and Problem Reports (ETD)

The reproducibility of experienced-based forensic pattern interpretation is founded on the notion that domain-specific knowledge can be successfully distributed and applied among experts within a group. This assumption persists, even when the examination is complicated by variations in case circumstances, such as impression clarity and totality, as well as media, substrate, collection mechanism and enhancement. While it is further theorized that many of these factors (as well as additional confounding factors) are at play during an examination, the manner and extent to which these sources of variability affect the examination of footwear evidence remain unclear. In order to explore this …

"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 …

Presidential Job Approval Rating Analysis Through Social Media, Subramanian Venkataraman, Subramanian Venkataraman

Dissertations and Theses

The aim of this study is to identify patterns in President Trump’s approval in the

Twitter universe through Social Media and Sentiment Analysis, and compare

against scientific polling to get meaningful insights on the limitations of Social

Media Analytics. For the purposes for this exercise, results from scientific polling

will be considered the true measure of approval, and will be used as control. In

order to perform sentiment analysis, we have used supervisory learning using

Naive Bayes Classifier algorithm which produced 0.862667 accuracy levels.

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 …

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 …

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 …

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 …

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.

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 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 …

How China Is Preparing For An Ai-Powered Future, Yujia He

Patterson School of Diplomacy and International Commerce Faculty Publications

U.S. leadership in artificial intelligence (AI) research and development (R&D) may be challenged by China’s recent and centralized policy planning aimed at rapidly developing AI-related technologies. The Chinese government supports AI as a strategic area supported by high-level policies with ambitious and quantifiable targets, inter-ministry coordination, government funding for research and development, support for workforce development, and suggestions for international collaboration and expansion. Still, as a relative latecomer in the global AI race, China faces numerous challenges to implement its policy planning, including short-term skills gap and long-term institutional constraints.

Survey Results: Complexities And Overlaps In Existing Citizen Science Mosquito Projects, Yujia He, Elizabeth Tyson

Patterson School of Diplomacy and International Commerce Faculty Publications

Currently, multiple projects worldwide engage the public in the scientific process of learning about mosquito biodiversity or monitoring mosquitoes that carry diseases like Dengue, Chikungunya, Zika and Malaria. These projects are executed at different invasion-stages and different scenarios of epidemiological risk based on their country of origin. Through surveying 12 international research teams, this brief report illuminates the differences and the overlaps in the protocols and tools used by existing citizen science mosquito monitoring projects. The analysis covers project goals, requirements and support for participants, policy impact, digital tools and data privacy.

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 …

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 …

How Do Designers Of The Built Environment Attempt To Make Ecological Sustainability Sensory Legible?, Carly L. Bartow

Architecture Undergraduate Honors Theses

This paper attempts to provide a theoretical framework for making ecosystem function and ecologically sustainable design more perceptible or sensible to people through architecture and the built environment. Design features of the Bertschi School Science Wing and the Bullitt Center in Seattle, Washington are incorporated to illustrate the sensory legibility of ecological sustainability criteria.The criteria are available to designers to help educate a building's occupants on environmentally sustainable design and motivate more sustainable behavior.

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 …

Personal Privacy: A Study To Determine Views On Privacy As It Relates To Technology Acceptance, Keith A. Wuotinen

Master's Theses and Doctoral Dissertations

This descriptive correlation study sought to learn the relationships, if any, between a person’s concern for privacy and their acceptance of technology, in conjunction with the control factors of the Big Five personality factors. The study employed a modified Concern for Information Privacy (CFIP) scale and a modified Technology Acceptance Model (TAM) approach in conjunction with the Big Five personality factors using a 51-question survey.

The study surveyed students at Eastern Michigan University in Ypsilanti, Michigan, who were enrolled in the College of Technology. The results indicated that there was a significant positive relationship between the CFIP and the TAM. …

Determining The Interruption Of Services While Performing V2i Communication Using The Spmd Prototype, Binaya Raj Joshi

Student Work

The use of Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I), Vehicle to Roadside Unit (V2R) and Vehicle to Other (V2X) communications are increasingly applied over existing and upcoming transportation means by the United States Department of Transportation (USDOT) and other federal agencies. From previous statistical data, these technologies would primarily avoid or mitigate vehicle crashes and would provide more safety, mobility and various other benefits on the roads (“Traffic Safety Facts 2012,” 2013; “Traffic Safety Facts 2013” 2014). During the communication processes between vehicles, infrastructures and roadside units’ various sensitive data such as positions and speed of the vehicles, …

Weights And Balances: Integrating Models For Prevention And Response To Southern California Offshore Oil Spills, Carmen Watts Clayton, Amoret Bunn

STAR Program Research Presentations

Licensing offshore oil and gas reserves in the United States waters are overseen by the U.S. Department of the Interior’s Bureau of Safety and Enforcement (BSEE). The licensing application includes planning for any worst-case oil spill scenario between BSEE and the applicant based on lessons learned from historic offshore spills such as the Deepwater Horizon (2010), Exxon Valdez (1989), and the Union Oil Platform Blowout (1969). The process for planning to respond to oil spills involves coordination with multiple agencies, trustees, and stakeholders to ensure that oil spill responses consider multiple factors, including ecologically sensitive species, commercial transportation and fisheries, …

A Study Of Information Security Awareness Program Effectiveness In Predicting End-User Security Behavior, James Michael Banfield

Master's Theses and Doctoral Dissertations

As accessibility to data increases, so does the need to increase security. For organizations of all sizes, information security (IS) has become paramount due to the increased use of the Internet. Corporate data are transmitted ubiquitously over wireless networks and have increased exponentially with cloud computing and growing end-user demand. Both technological and human strategies must be employed in the development of an information security awareness (ISA) program. By creating a positive culture that promotes desired security behavior through appropriate technology, security policies, and an understanding of human motivations, ISA programs have been the norm for organizational end-user risk mitigation …

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 …

Semantic, Cognitive, And Perceptual Computing: Paradigms That Shape Human Experience, Amit P. Sheth, Pramod Anantharam, Cory Henson

Kno.e.sis Publications

Unlike machine-centric computing, in which efficient data processing takes precedence over contextual tailoring, human-centric computation provides a personalized data interpretation that most users find highly relevant to their needs. The authors show how semantic, cognitive, and perceptual computing paradigms work together to produce actionable information.