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"No civil discourse, no cooperation; misinformation, mistruth." These were the words of former Facebook Vice President Chamath Palihapitiya who publicly expressed his regret in a 2017 interview over his role in co-creating Facebook. Palihapitiya shared that social media is ripping apart the social fabric of society and he also sounded

"No civil discourse, no cooperation; misinformation, mistruth." These were the words of former Facebook Vice President Chamath Palihapitiya who publicly expressed his regret in a 2017 interview over his role in co-creating Facebook. Palihapitiya shared that social media is ripping apart the social fabric of society and he also sounded the alarm regarding social media’s unavoidable global impact. He is only one of social media’s countless critics. The more disturbing issue resides in the empirical evidence supporting such notions. At least 95% of adolescents own a smartphone and spend an average time of two to four hours a day on social media. Moreover, 91% of 16-24-year-olds use social media, yet youth rate Instagram, Facebook, and Twitter as the worst social media platforms. However, the social, clinical, and neurodevelopment ramifications of using social media regularly are only beginning to emerge in research. Early research findings show that social media platforms trigger anxiety, depression, low self-esteem, and other negative mental health effects. These negative mental health symptoms are commonly reported by individuals from of 18-25-years old, a unique period of human development known as emerging adulthood. Although emerging adulthood is characterized by identity exploration, unbounded optimism, and freedom from most responsibilities, it also serves as a high-risk period for the onset of most psychological disorders. Despite social media’s adverse impacts, it retains its utility as it facilitates identity exploration and virtual socialization for emerging adults. Investigating the “user-centered” design and neuroscience underlying social media platforms can help reveal, and potentially mitigate, the onset of negative mental health consequences among emerging adults. Effectively deconstructing the Facebook, Twitter, and Instagram (i.e., hereafter referred to as “The Big Three”) will require an extensive analysis into common features across platforms. A few examples of these design features include: like and reaction counters, perpetual news feeds, and omnipresent banners and notifications surrounding the user’s viewport. Such social media features are inherently designed to stimulate specific neurotransmitters and hormones such as dopamine, serotonin, and cortisol. Identifying such predacious social media features that unknowingly manipulate and highjack emerging adults’ brain chemistry will serve as a first step in mitigating the negative mental health effects of today’s social media platforms. A second concrete step will involve altering or eliminating said features by creating a social media platform that supports and even enhances mental well-being.

ContributorsGupta, Anay (Author) / Flores, Valerie (Thesis director) / Carrasquilla, Christina (Committee member) / Barnett, Jessica (Committee member) / The Sidney Poitier New American Film School (Contributor) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

In this thesis paper, the mental health consequences of the COVID-19 pandemic are discussed. Chapter 1 discusses what inspired me to write this thesis and follows with a discussion of social isolation during the COVID-19 pandemic. Chapter 2 takes a step back and discusses biological effects of social isolation

In this thesis paper, the mental health consequences of the COVID-19 pandemic are discussed. Chapter 1 discusses what inspired me to write this thesis and follows with a discussion of social isolation during the COVID-19 pandemic. Chapter 2 takes a step back and discusses biological effects of social isolation in general. Chapter 3 discusses the psychological effects of social isolation. Finally, this thesis concludes with a discussion of what can be done to help those experiencing social isolation during the pandemic.

ContributorsHarvey, Kira Rachelle (Author) / Sturgess, Jessica (Thesis director) / Tucker, Derek (Committee member) / School of Music, Dance and Theatre (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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My research aims to determine the effectiveness of meditation and sleep applications (apps) on the reduction of anxiety and stress in college students, with a focus on sedative piano music. Results showed a significant reduction of stress and anxiety levels in college students when listening to sedative piano music versus

My research aims to determine the effectiveness of meditation and sleep applications (apps) on the reduction of anxiety and stress in college students, with a focus on sedative piano music. Results showed a significant reduction of stress and anxiety levels in college students when listening to sedative piano music versus non-sedative piano music. Music along with other therapy modalities in meditation and sleep apps show promise in reducing students’ anxiety and stress and promoting their successes.

ContributorsPantha, Bidur (Author) / Brian, Jennifer (Thesis director) / Patten, Kristopher (Committee member) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

For my thesis/creative project, I created a prototype for a mental health app. Each section of the prototype has a purpose of instilling mindfulness and healthy habits that can promote and lead to sustainable mental health. Throughout the paper I explain my reasoning for starting this project, the science of

For my thesis/creative project, I created a prototype for a mental health app. Each section of the prototype has a purpose of instilling mindfulness and healthy habits that can promote and lead to sustainable mental health. Throughout the paper I explain my reasoning for starting this project, the science of mindfulness and how it can bring about positive mental and physical changes, and the design theory behind the prototype.

ContributorsZaja, Peter (Author) / Sopha, Matthew (Thesis director) / Arrfelt, Mathias (Committee member) / Department of Finance (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

COVID-19 has shocked the bedrock of society, impacting both human life and the economy. Accompanying this shock has been the psychological distress inflicted onto the general population as a result of the emotion strain stemming from isolation/quarantine policies, being sick with COVID-19, dealing with COVID-19 losses, and post-COVID syndrome and

COVID-19 has shocked the bedrock of society, impacting both human life and the economy. Accompanying this shock has been the psychological distress inflicted onto the general population as a result of the emotion strain stemming from isolation/quarantine policies, being sick with COVID-19, dealing with COVID-19 losses, and post-COVID syndrome and its effect on quality of life. The psychological distress has been experienced by the general population, but compared to middle age (30-50) and older adults (>50 years of age), it has been young adults (18-30 years old) who have been more psychologically affected (Glowacz & Schmits, 2020). Psychological distress, specifically anxiety and depression, has been exacerbated by feelings of uncertainty, fear of illness, losing loved ones, and fear of post-COVID syndrome. Post-COVID syndrome, as with other post-viral syndromes such as post viral SARS involve lingering symptoms such as myalgic encephalomyelitis or Chronic Fatigue Syndrome (CFS), and loss of motivation (Underhill, 2015). In addition to these symptoms, patients suffering from post-COVID syndrome have also presented brain inflammation and damaged brain blood vessels (Meinhardt et al., 2021), Endotheliitis (Varga et al., 2020), CV abnormalities and changes in glucose metabolism (Williams et al., 2020). CV abnormalities and changes in glucose metabolism are connected to chronic illnesses like diabetes and heart disease respectively. These chronic illnesses are then associated with higher risk for depression as a result of the stress induced by the symptoms and their impact on quality of life (NIMH, 2021). Further monitoring, and research will be important to gauge ultimate physiological and psychological impact of COVID-19.

ContributorsPiedra Gonzalez, Michael (Author) / Vargas, Perla (Thesis director) / Oh, Hyunsung (Committee member) / College of Health Solutions (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Developed a business product with a team of CS students.

ContributorsPerri, Cole Thomas (Co-author) / Hernandez, Maximilliano (Co-author) / Schneider, Kaitlin (Co-author) / Call, Andy (Thesis director) / Hunt, Neil (Committee member) / School of Accountancy (Contributor) / Watts College of Public Service & Community Solut (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

We think about hope every day, even if we do not consciously think about it. It is an important part of our lives. It affects our subjective well-being and physical health. Yet, many people do not know the importance of hope and how it can be created within one's self.

We think about hope every day, even if we do not consciously think about it. It is an important part of our lives. It affects our subjective well-being and physical health. Yet, many people do not know the importance of hope and how it can be created within one's self. A workshop was designed to increase the knowledge of hope, primarily for college students. The workshop focused on defining hope, explaining how hope plays a part in a healthy lifestyle, and how to create hope for themselves. This project looked at the Hope Theory, discovered by Charles Snyder, and how it can be measured hope through goal attainment<br/>onattainment.

ContributorsLugo, Kaeli Ann (Author) / Hrncir, Micki (Thesis director) / Sidman, Cara (Committee member) / College of Health Solutions (Contributor) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description
Real-world environments are characterized by non-stationary and continuously evolving data. Learning a classification model on this data would require a framework that is able to adapt itself to newer circumstances. Under such circumstances, transfer learning has come to be a dependable methodology for improving classification performance with reduced training costs

Real-world environments are characterized by non-stationary and continuously evolving data. Learning a classification model on this data would require a framework that is able to adapt itself to newer circumstances. Under such circumstances, transfer learning has come to be a dependable methodology for improving classification performance with reduced training costs and without the need for explicit relearning from scratch. In this thesis, a novel instance transfer technique that adapts a "Cost-sensitive" variation of AdaBoost is presented. The method capitalizes on the theoretical and functional properties of AdaBoost to selectively reuse outdated training instances obtained from a "source" domain to effectively classify unseen instances occurring in a different, but related "target" domain. The algorithm is evaluated on real-world classification problems namely accelerometer based 3D gesture recognition, smart home activity recognition and text categorization. The performance on these datasets is analyzed and evaluated against popular boosting-based instance transfer techniques. In addition, supporting empirical studies, that investigate some of the less explored bottlenecks of boosting based instance transfer methods, are presented, to understand the suitability and effectiveness of this form of knowledge transfer.
ContributorsVenkatesan, Ashok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Li, Baoxin (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Typically, the complete loss or severe impairment of a sense such as vision and/or hearing is compensated through sensory substitution, i.e., the use of an alternative sense for receiving the same information. For individuals who are blind or visually impaired, the alternative senses have predominantly been hearing and touch. For

Typically, the complete loss or severe impairment of a sense such as vision and/or hearing is compensated through sensory substitution, i.e., the use of an alternative sense for receiving the same information. For individuals who are blind or visually impaired, the alternative senses have predominantly been hearing and touch. For movies, visual content has been made accessible to visually impaired viewers through audio descriptions -- an additional narration that describes scenes, the characters involved and other pertinent details. However, as audio descriptions should not overlap with dialogue, sound effects and musical scores, there is limited time to convey information, often resulting in stunted and abridged descriptions that leave out many important visual cues and concepts. This work proposes a promising multimodal approach to sensory substitution for movies by providing complementary information through haptics, pertaining to the positions and movements of actors, in addition to a film's audio description and audio content. In a ten-minute presentation of five movie clips to ten individuals who were visually impaired or blind, the novel methodology was found to provide an almost two time increase in the perception of actors' movements in scenes. Moreover, participants appreciated and found useful the overall concept of providing a visual perspective to film through haptics.
ContributorsViswanathan, Lakshmie Narayan (Author) / Panchanathan, Sethuraman (Thesis advisor) / Hedgpeth, Terri (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2011
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Description
The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a

The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a large amount of data is cheap and easy, annotating them with class labels is an expensive process in terms of time, labor and human expertise. This has paved the way for research in the field of active learning. Such algorithms automatically select the salient and exemplar instances from large quantities of unlabeled data and are effective in reducing human labeling effort in inducing classification models. To utilize the possible presence of multiple labeling agents, there have been attempts towards a batch mode form of active learning, where a batch of data instances is selected simultaneously for manual annotation. This dissertation is aimed at the development of novel batch mode active learning algorithms to reduce manual effort in training classification models in real world multimedia pattern recognition applications. Four major contributions are proposed in this work: $(i)$ a framework for dynamic batch mode active learning, where the batch size and the specific data instances to be queried are selected adaptively through a single formulation, based on the complexity of the data stream in question, $(ii)$ a batch mode active learning strategy for fuzzy label classification problems, where there is an inherent imprecision and vagueness in the class label definitions, $(iii)$ batch mode active learning algorithms based on convex relaxations of an NP-hard integer quadratic programming (IQP) problem, with guaranteed bounds on the solution quality and $(iv)$ an active matrix completion algorithm and its application to solve several variants of the active learning problem (transductive active learning, multi-label active learning, active feature acquisition and active learning for regression). These contributions are validated on the face recognition and facial expression recognition problems (which are commonly encountered in real world applications like robotics, security and assistive technology for the blind and the visually impaired) and also on collaborative filtering applications like movie recommendation.
ContributorsChakraborty, Shayok (Author) / Panchanathan, Sethuraman (Thesis advisor) / Balasubramanian, Vineeth N. (Committee member) / Li, Baoxin (Committee member) / Mittelmann, Hans (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013