Research and Creative Activity, July 1, 2019-June 30, 2020: Major Sponsored Programs and Faculty Accomplishments in Research and Creative Activity, University of Nebraska-Lincoln

Foreword by Bob Wilhelm, Vice Chancellor for Research and Economic Development: This booklet highlights successes in research, scholarship and creative activity by University of Nebraska–Lincoln faculty during the fiscal year running July 1, 2019, to June 30, 2020. It lists investigators, project titles and funding sources on major grants and sponsored awards received during the year; fellowships and other recognitions and honors bestowed on our faculty; books published by faculty; performances, exhibitions and other creative activity; and patents and licensing agreements issued. Based on your feedback, the Office of Research and Economic Development expanded this publication to include peer-reviewed journal articles and conference presentations and recognize students and faculty mentors participating in the Undergraduate Creative Activities and Research Experience Program (UCARE) and the First-Year Research Experiences program (FYRE). While metrics cannot convey the full story of our work, they are tangible measures of impact. Nebraska achieved a record $317 million in total research expenditures in FY 2019, a 26$450 million in research expenditures by 2025. Husker researchers are stimulating economic growth through university-sponsored industry activity. Nebraska Innovation Campus created 1,657 jobs statewide and had a total economic impact of $324.1 million in FY 2019. NUtech Ventures brought in$6.6 million in licensing income in FY 2020. The University of Nebraska system now ranks 65th among the top 100 academic institutions receiving U.S. patents, jumping 14 spots from 2019. I am proud of the Nebraska Research community for facing the challenges of 2020 with grit and determination. Our researchers quickly adapted to develop solutions for an evolving pandemic — all while working apart and keeping themselves and their families safe. As an institution, we made a commitment to embrace an anti-racism journey and work toward racial equity. Advancing conversations and developing lasting solutions is among the most important work we can do as scholars. Against the backdrop of the pandemic, rising racial and social tensions, and natural disasters, Nebraska researchers worked diligently to address other pressing issues, such as obesity and related diseases, nanomaterials, agricultural resilience and the state’s STEM workforce. Let’s continue looking forward to what we can accomplish together. Thank you for participating in the grand challenges process and helping identify the wicked problems that Nebraska has unique expertise to solve. Soon, ORED will unveil a Research Roadmap that outlines how our campus will develop research expertise; enrich creative activity; bolster commitment to diversity, equity and inclusion; enhance economic development; and much more. Amidst the uncertainty of 2020, I remain confident in our faculty’s talent and commitment. I am pleased to present this record of accomplishments. Contents Awards of $5 Million or More Awards of$1 Million to $4,999,999 Awards of$250,000 to $999,999 Early Career Awards Arts and Humanities Awards of$250,000 or More Arts and Humanities Awards of $50,000 to$249,999 Arts and Humanities Awards of $5,000 to$49,999 Patents License Agreements Creative Activity Books Recognitions and Honors Journal Articles Conference Presentations UCARE and FYRE Projects Glossar

Isomorphic effects of managerial and directoral career paths

The extensive array of interlocking directorate research remains near-exclusively cross-sectional or comparative cross-sectional in nature. While this has been fruitful in identifying persistent structures of inter-organisational relationships evidence of the impact of these structures on organisational performance or activity has been more limited. This should not be surprising because, by their nature, relationships have strong longitudinal and dynamic qualities that are likely to be difficult to isolate through cross-sectional approaches. Clearly, managerial practice is inevitably strongly conditioned by the specific contingencies of the time and the information available through networks of colleagues and advisers (particularly at board level) at the time. But managerial and directoral capabilities and mental sets are also developed over time, particularly through previous experiences in these roles and the formation of long-lasting 'strong' and 'weak' relationships. This paper tests the influence of three longitudinal dimensions of managers and directors' relationships on a set of indicators of financial performance, drawing from a large dataset of detailing historic board membership of UK firms. It finds evidence of isomorphic processes through these channels and establishes that the longitudinal design considerably enhances the detection of performance effects from directorate interlocks. More broadly, the research has implications for the conception of collective action and the constitution of 'community'

Saliva continine levels of babies and mothers living with smoking fathers under different housing types in Hong Kong: a cross-sectional study

Paper Session 15 - The Challenge of Second-Hand Smoke: PA15-3BACKGROUND: After the Smoking Ordinance enacted in HK since 1/2007, shifting of smoking from outdoor to home was found, home becomes a major source of secondhand smoke (SHS) exposure of nonsmokers. OBJECTIVES: It aimed to assess the SHS exposure of babies and mothers living with smoking fathers of two housing types by using a biomarker. METHODS: Trios of smoking father, non-smoking mother and a baby under 18-months were recruited from Maternal and Child Health Centres (MCHCs) from 6/2008 to 10/2009. Consented couples completed the baseline survey including demographic data, fathers’ household smoking behaviors and mothers’ actions in protecting babies from household SHS exposure. Saliva samples from baby and mother were collected and then sent to the National University of Singapore for cotinine analyses. Log-transformations were used for the saliva cotinine due to skewed data. There were 2 housing types (public/private) and father was asked if they smoked at home (yes/no). MANOVA was used to compare the babies’ and mothers’ cotinine levels when fathers smoked at home under the 2 housing types. RESULTS: 1,158 trios were consented. 1,142 mothers’ and 1,058 babies’ samples were assayed. The mean age of the fathers and mothers was 35.5(±7.0) and 31.2(±4.9). The mean mothers’ cotinine level was 12.15ng/ml (±61.20) while babies’ was 2.38ng/ml (±6.01). 606 and 501 trios were living in public and private housing. Fathers’ smoked at home led to higher mothers’ and babies’ saliva cotininary (mean log of mothers’ cotininary: 0.14±0.62 vs. 0.05±0.55, p=0.06; babies: 0.16±0.38 vs. 0.07±0.34, p=0.003). Housing types influenced babies’ cotinine level (public: 0.17±0.37; private: 0.10±0.36, p=0.01). MANOVA showed that fathers smoked at home (Λ=0.99, p=0.01) and housing types (Λ=0.99, p=0.01) were positively related to the saliva cotinine levels. CONCLUSIONS: Father smoked at home and the housing types have greater impact on babies’ saliva cotininary, showing that they were highly exposed at home and in public housing environment. HK government should promote smoke-free homes and to provide more smoking cessation services to minimize the household SHS exposure to babiespublished_or_final_versio

정신건강에서 사용자 내러티브와 자아성찰을 지원하는 대화형 에이전트 디자인

학위논문 (박사) -- 서울대학교 대학원 : 융합과학기술대학원 융합과학부(디지털정보융합전공), 2020. 8. 서봉원.In the advent of artificial intelligence (AI), we are surrounded by technological gadgets, devices and intelligent personal assistant (IPAs) that voluntarily take care of our home, work and social networks. They help us manage our life for the better, or at least that is what they are designed for. As a matter of fact, few are, however, designed to help us grapple with the thoughts and feelings that often construct our living. In other words, technologies hardly help us think. How can they be designed to help us reflect on ourselves for the better? In the simplest terms, self-reflection refers to thinking deeply about oneself. When we think deeply about ourselves, there can be both positive and negative consequences. On the one hand, reflecting on ourselves can lead to a better self-understanding, helping us achieve life goals. On the other hand, we may fall into brooding and depression. The sad news is that the two are usually intertwined. The problem, then, is the irony that reflecting on oneself by oneself is not easy. To tackle this problem, this work aims to design technology in the form of a conversational agent, or a chatbot, to encourage a positive self-reflection. Chatbots are natural language interfaces that interact with users in text. They work at the tip of our hands as if SMS or instant messaging, from flight reservation and online shopping to news service and healthcare. There are even chatbot therapists offering psychotherapy on mobile. That machines can now talk to us creates an opportunity for designing a natural interaction that used to be humans own. This work constructs a two-dimensional design space for translating self-reflection into a human-chatbot interaction, with user self-disclosure and chatbot guidance. Users confess their thoughts and feelings to the bot, and the bot is to guide them in the scaffolding process. Previous work has established an extensive line of research on the therapeutic effect of emotional disclosure. In HCI, reflection design has posited the need for guidance, e.g. scaffolding users thoughts, rather than assuming their ability to reflect in a constructive manner. The design space illustrates different reflection processes depending on the levels of user disclosure and bot guidance. Existing reflection technologies have most commonly provided minimal levels of disclosure and guidance, and healthcare technologies the opposite. It is the aim of this work to investigate the less explored space by designing chatbots called Bonobot and Diarybot. Bonobot differentiates itself from other bot interventions in that it only motivates the idea of change rather than direct engagement. Diarybot is designed in two chat versions, Basic and Responsive, which create novel interactions for reflecting on a difficult life experience by explaining it to and exploring it with a chatbot. These chatbots are set up for a user study with 30 participants, to investigate the user experiences of and responses to design strategies. Based on the findings, challenges and opportunities from designing for chatbot-guided reflection are explored. The findings of this study are as follows. First, participants preferred Bonobots questions that prompted the idea of change. Its responses were also appreciated, but only when they conveyed accurate empathy. Thus questions, coupled with empathetic responses, could serve as a catalyst for disclosure and even a possible change of behavior, a motivational boost. Yet the chatbot-led interaction led to surged user expectations for the bot. Participants demanded more than just the guidance, such as solutions and even superhuman intelligence. Potential tradeoff between user engagement and autonomy in designing human-AI partnership is discussed. Unlike Bonobot, Diarybot was designed with less guidance to encourage users own narrative making. In both Diarybot chats, the presence of a bot could make it easier for participants to share the most difficult life experiences, compared to a no-chatbot writing condition. Yet an increased interaction with the bot in Responsive chat could lead to a better user engagement. On the contrary, more emotional expressiveness and ease of writing were observed with little interaction in Basic chat. Coupled with qualitative findings that reveal user preference for varied interactions and tendency to adapt to bot patterns, predictability and transparency of designing chatbot interaction are discussed in terms of managing user expectations in human-AI interaction. In sum, the findings of this study shed light on designing human-AI interaction. Chatbots can be a potential means of supporting guided disclosure on lifes most difficult experiences. Yet the interaction between a machine algorithm and an innate human cognition bears interesting questions for the HCI community, especially in terms of user autonomy, interface predictability, and design transparency. Discussing the notion of algorithmic affordances in AI agents, this work proposes meaning-making as novel interaction design metaphor: In the symbolic interaction via language, AI nudges users, which inspires and engages users in their pursuit of making sense of lifes agony. Not only does this metaphor respect user autonomy but also it maintains the veiled workings of AI from users for continued engagement. This work makes the following contributions. First, it designed and implemented chatbots that can provide guidance to encourage user narratives in self-reflection. Next, it offers empirical evidence on chatbot-guided disclosure and discusses implications for tensions and challenges in design. Finally, this work proposes meaning-making as a novel design metaphor. It calls for the responsible design of intelligent interfaces for positive reflection in pursuit of psychological wellbeing, highlighting algorithmic affordances and interpretive process of human-AI interaction.최근 인공지능(Artificial Intelligence; AI) 기술은 우리 삶의 면면을 매우 빠르게 바꿔놓고 있다. 특히 애플의 시리(Siri)와 구글 어시스턴트 (Google Assistant) 등 자연어 인터페이스(natural language interfaces)의 확장은 곧 인공지능 에이전트와의 대화가 인터랙션의 주요 수단이 될 것임을 능히 짐작케 한다. 실상 인공지능 에이전트는 실생활에서 콘텐츠 추천과 온라인 쇼핑 등 다양한 서비스를 제공하고 있지만, 이들의 대부분은 과업-지향적이다. 즉 인공지능은 우리의 삶을 편리하게 하지만, 과연 편안하게 할 수 있는가? 본 연구는 편하지만 편하지 않은 현대인을 위한 기술의 역할을 고민하는 데에서 출발한다. 자아성찰(self-reflection), 즉 자신에 대해 깊이 생각해 보는 활동은 자기인식과 자기이해를 도모하고 배움과 목표의식을 고취하는 등 분야를 막론하고 널리 연구 및 적용되어 왔다. 하지만 자아성찰의 가장 큰 어려움은 스스로 건설적인 성찰을 도모하기 힘들다는 것이다. 특히, 부정적인 감정적 경험에 대한 자아성찰은 종종 우울감과 불안을 동반한다. 극복이 힘든 경우 상담 또는 치료를 찾을 수 있지만, 사회적 낙인과 잣대의 부담감으로 꺼려지는 경우가 다수이다. 성찰 디자인(Reflection Design)은 인간-컴퓨터상호작용(HCI)의 오랜 화두로, 그동안 효과적인 성찰을 도울 수 있는 디자인 전략들이 다수 연구되어 왔지만 대부분 다양한 사용자 데이터 수집 전략을 통해 과거 회상 및 해석을 돕는 데 그쳤다. 최근 소위 챗봇 상담사가 등장하여 심리상담과 치료 분야에 적용되고 있지만, 이 또한 성찰을 돕기보다는 효율적인 처치 도구에 머무르고 있을 뿐이다. 즉 기술은 치료 수단이거나 성찰의 대상이 되지만, 그 과정에 개입하는 경우는 제한적이라고 할 수 있다. 이에 본 연구는 성찰 동반자로서 대화형 에이전트인 챗봇을 디자인할 것을 제안한다. 이 챗봇의 역할은 사용자의 부정적인 감정적 경험 또는 트라우마에 대해 이야기할 수 있도록 도울 뿐 아니라, 그 과정에서 반추를 통제하여 건설적인 내러티브를 이끌어 내는 가이드를 제공하는 것이다. 이러한 챗봇을 설계하기 위해, 선행 연구를 기반으로 사용자의 자기노출(user self-disclosure)과 챗봇 가이드(guidance)를 두 축으로 한 디자인 공간(design space)을 정의하였다. 그리고 자기노출과 가이드의 정도에 따른 네 가지 자아성찰 경험을 분류하였다: 자기노출과 가이드가 최소화된 회상 공간, 자기노출이 위주이고 가이드가 최소화된 설명 공간, 자기노출과 챗봇이 이끄는 가이드가 혼합된 탐색 공간, 가이드를 적극 개입시켜 자기노출을 높이는 변화 공간이 그것이다. 본 연구의 목표는 상술된 디자인 공간에서의 성찰 경험과 과정을 돕는 챗봇을 구현하고, 사용자 실험을 통해 성찰 경험과 디자인 전략에 대한 반응을 수집 및 분석함으로써 챗봇 기반의 자아 성찰 인터랙션을 새롭게 제시하고 이에 대한 실증적 근거를 마련하는 것이다. 현재까지 많은 성찰 기술은 회상에 집중되어 있기에, 나머지 세 공간에서의 성찰을 지원하는 보노봇과 기본형반응형 일기봇을 디자인하였다. 또한, 사용자 평가를 바탕으로 도출한 연구결과를 통해 도래한 인간-인공지능 상호작용(human-AI interaction)의 맥락에서 성찰 동반자로서의 챗봇 기술이 갖는 의미와 역할을 탐구한다. 보노봇과 일기봇은 인간중심상담과 대화분석의 이론적 근거를 바탕으로 한 정서지능(emotional intelligence)과 절차지능(proecedural intelligence)을 핵심 축으로, 대화 흐름 제어(flow manager)와 발화 생성(response generator)을 핵심 모듈로 구현하였다. 먼저, 보노봇은 동기강화상담(motivational interviewing)을 기반으로 고민과 스트레스에 대한 내러티브를 이끌어내어, 이에 대한 해결을 위한 가이드 질문을 통해 변화를 위한 성찰을 돕는다. 챗봇의 구현을 위해, 동기강화상담의 네 단계 대화를 설정하고 각 단계를 구성할 수 있는 상담사 발화 행동을 관련문헌에서 수집 및 전처리 과정을 거쳐 스크립트화하였다. 또한, 사전 전처리된 문장이 맥락을 유지할 수 있는 대화에 쓰일 수 있도록, 대화의 주제는 대학원생의 어려움으로 한정하였다. 보노봇과의 대화가 사용자의 성찰에 미치는 영향과 이에 대한 인식을 탐색하기 위해 질적 연구방법을 사용하여 30명의 대학원생과 사용자 실험을 진행하였다. 실험결과, 사용자는 변화 대화를 유도할 수 있는 다양한 탐색 질문을 선호하였다. 또한, 사용자의 맥락에 정확히 들어맞는 질문과 피드백은 사용자를 더욱 적극적인 자기 노출로 이끌게 할 수 있음을 발견하였다. 그러나 챗봇이 마치 상담사처럼 대화를 이끌어갈 경우, 높아진 사용자의 기대 수준으로 인해 일부 사용자가 변화에 대한 동기를 표출하였음에도 불구하고 변화에 대한 자율성을 챗봇에 양도하려는 모습 또한 나타남을 분석하였다. 보노봇 연구를 바탕으로 일기봇은 챗봇 대신 사용자가 보다 적극적으로 성찰 내러티브를 전개할 수 있도록 디자인하였다. 일기봇은 트라우마에 대한 표현적 글쓰기를 지원하는 챗봇으로, 기본형 또는 반응형 대화를 제공한다. 기본형 대화는 트라우마에 대해 자유롭게 설명할 수 있는 대화 환경을 제공하고, 반응형 대화는 사용자가 작성한 내러티브에 대한 후속 인터랙션을 통해 과거의 경험을 재탐색하도록 하였다. 또한, 후속 인터랙션의 발화 행동은 다양한 상담치료에서 발췌하되 유저의 내러티브에서 추출한 감정어 및 인간관계 키워드를 활용하도록 하였다. 각 일기봇에 대한 반응을 비교 분석하기 위해, 챗봇 없이 도큐먼트에 표현적 글쓰기 활동만을 하는 대조군을 설정하고 30명의 사용자를 모집하여 각 조건에 랜덤으로 배정, 설문과 면담을 동반한 4일간의 글쓰기 실험을 진행하였다. 실험결과, 사용자는 일기봇과의 인터랙션을 통해 보이지 않는 가상의 청자를 상상함으로써 글쓰기를 대화 활동으로 인지하고 있음을 알 수 있었다. 특히, 반응형 대화의 후속 질문들은 사용자로 하여금 상황을 객관화하고 새로운 관점으로 생각해 볼 수 있는 효과를 거두었다. 반응형 대화에서 후속 인터랙션을 경험한 사용자는 일기봇의 인지된 즐거움과 사회성, 신뢰도와 재사용 의향에 대한 평가가 다른 두 조건에서보다 유의하게 높았다. 반면, 기본형 대화 참여자는 다른 두 조건에서보다 감정적 표현의 용이성과 글쓰기의 어려움을 각각 유의하게 높게, 그리고 낮게 평가하였다. 즉, 챗봇은 많은 인터랙션 없이도 청자의 역할을 수행할 수 있었지만, 후속 질문을 통한 인터랙션이 가능했던 반응형 대화는 더욱 적극적인 유저 참여(engagement)를 이끌어낼 수 있었다. 또한, 실험이 진행됨에 따라, 사용자가 반응형 일기봇의 알고리즘에 자신의 글쓰기 주제와 단어 선택 등을 맞게 바꾸어 가는 적응적(adaptive) 행동이 관찰되었다. 앞선 연구결과를 통해, 다양한 챗봇 디자인 전략을 바탕으로 사용자의 내러티브가 다르게 유도될 수 있으며, 따라서 서로 다른 유형의 성찰 경험을 이끌어낼 수 있음을 발견하였다. 또한, 자율적인 행위인 자아성찰이 기술과의 상호작용으로 호혜적 성질을 갖게 될 때 사용자의 자율성, 상호작용의 예측가능성과 디자인 투명성에서 발생할 수 있는 갈등관계(tensions)를 탐색하고 인공지능 에이전트의 알고리즘 어포던스(algorithmic affordances)를 논의하였다. 보이지 않는 챗봇 알고리즘에 의해 사용자의 성찰이 유도될 수 있다는 것은 기존의 인간-컴퓨터 상호작용에서 강조되는 사용자 제어와 디자인 투명성에서 전복을 초래하는 것처럼 보일 수 있으나, 상징적 상호작용(symbolic interaction)의 맥락에서 오히려 사용자가 알고리즘에 의해 지나간 과거에 대한 새로운 의미를 적극 탐색해나가는 과정이 될 수 있다. 본 연구는 이것을 새로운 디자인 메타포, 즉 의미-만들기(meaning-making)로 제안하고 알고리즘의 넛지(nudge)에 의한 사용자의 주관적 해석 경험(interpretive process)을 강조한다. 이것은 하나의 챗봇 알고리즘이라 할지라도 서로 다른 사용자의 다양한 성찰 경험을 유도해낼 수 있다는 것을 의미하며, 이러한 맥락에서 인공지능은 기존의 블랙 박스를 유지하면서도 사용자의 자율성을 보장할 수 있다. 본 연구는 우리와 협업하는 인공지능 챗봇 기술의 디자인에 대한 경험적 이해를 높이고, 이론을 기반으로 한 챗봇을 구현함으로써 디자인 전략에 대한 실증적 근거를 제시한다. 또한 자아 성찰 과정에 동행하는 동반자(companion)로서의 기술로 새로운 디자인 메타포를 제시함으로써 인간컴퓨터상호작용(HCI)의 이론적 확장에 기여하고, 사용자의 부정적 경험에 대한 의미 추구를 돕는 관계지향적 인공지능으로서 향후 현대인의 정신건강에 이바지할 수 있는 사회적, 산업적 의의를 갖는다.CHAPTER 1. INTRODUCTION １ 1.1. BACKGROUND AND MOTIVATION １ 1.2. RESEARCH GOAL AND QUESTIONS ５ 1.2.1. Research Goal ５ 1.2.2. Research Questions ５ 1.3. MAJOR CONTRIBUTIONS ８ 1.4. THESIS OVERVIEW ９ CHAPTER 2. LITERATURE REVIEW １１ 2.1. THE REFLECTING SELF １１ 2.1.1. Self-Reflection and Mental Wellbeing １１ 2.1.2. The Self in Reflective Practice １５ 2.1.3. Design Space ２２ 2.2. SELF-REFLECTION IN HCI ２６ 2.2.1. Reflection Design in HCI ２６ 2.2.2. HCI for Mental Wellbeing ３６ 2.2.3. Design Opportunities ４０ 2.3. CONVERSATIONAL AGENT DESIGN ４２ 2.3.1. Theoretical Background ４２ 2.3.2. Technical Background ４７ 2.3.3. Design Strategies ４９ 2.4. SUMMARY ６９ CHAPTER 3. DESIGNING CHATBOT FOR TRANSFORMATIVE REFLECTION ７１ 3.1. DESIGN GOAL AND DECISIONS ７１ 3.2. CHATBOT IMPLEMENTATION ７６ 3.2.1. Emotional Intelligence ７６ 3.2.2. Procedural Intelligence ７７ 3.3. EXPERIMENTAL USER STUDY ７９ 3.3.1. Participants ７９ 3.3.2. Task ８０ 3.3.3. Procedure ８０ 3.3.4. Ethics Approval ８０ 3.3.5. Surveys and Interview ８１ 3.4. RESULTS ８２ 3.4.1. Survey Findings ８２ 3.4.2. Qualitative Findings ８３ 3.5. IMPLICATIONS ８８ 3.5.1. Articulating Hopes and Fears ８９ 3.5.2. Designing for Guidance ９１ 3.5.3. Rethinking Autonomy ９２ 3.6. SUMMARY ９４ CHAPTER 4. DESIGNING CHATBOTS FOR EXPLAINING AND EXPLORING REFLECTIONS ９６ 4.1. DESIGN GOAL AND DECISIONS ９６ 4.1.1. Design Decisions for Basic Chat ９８ 4.1.2. Design Decisions for Responsive Chat ９８ 4.2. CHATBOT IMPLEMENTATION １０２ 4.2.1. Emotional Intelligence １０３ 4.2.2. Procedural Intelligence １０５ 4.3. EXPERIMENTAL USER STUDY １０６ 4.3.1. Participants １０６ 4.3.2. Task １０７ 4.3.3. Procedure １０７ 4.3.4. Safeguarding of Study Participants and Ethics Approval １０８ 4.3.5. Surveys and Interviews １０８ 4.4. RESULTS １１１ 4.4.1. Quantitative Findings １１１ 4.4.2. Qualitative Findings １１８ 4.5. IMPLICATIONS １２７ 4.5.1. Telling Stories to a Chatbot １２８ 4.5.2. Designing for Disclosure １３０ 4.5.3. Rethinking Predictability and Transparency １３２ 4.6. SUMMARY １３３ CHAPTER 5. DESIGNING CHATBOTS FOR SELF-REFLECTION: SUPPORTING GUIDED DISCLOSURE １３５ 5.1. DESIGNING FOR GUIDED DISCLOSURE １３９ 5.1.1. Chatbots as Virtual Confidante １３９ 5.1.2. Routine and Variety in Interaction １４１ 5.1.3. Reflection as Continued Experience １４４ 5.2. TENSIONS IN DESIGN １４５ 5.2.1. Adaptivity １４５ 5.2.2. Autonomy １４７ 5.2.3. Algorithmic Affordance １４８ 5.3. MEANING-MAKING AS DESIGN METAPHOR １５０ 5.3.1. Meaning in Reflection １５１ 5.3.2. Meaning-Making as Interaction １５３ 5.3.3. Making Meanings with AI １５５ CHAPTER 6. CONCLUSION １５８ 6.1. RESEARCH SUMMARY １５８ 6.2. LIMITATIONS AND FUTURE WORK １６１ 6.3. FINAL REMARKS １６３ BIBLIOGRAPHY １６５ ABSTRACT IN KOREAN １９２Docto

Participative Urban Health and Healthy Aging in the Age of AI

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2022, held in Paris, France, in June 2022. The 15 full papers and 10 short papers presented in this volume were carefully reviewed and selected from 33 submissions. They cover topics such as design, development, deployment, and evaluation of AI for health, smart urban environments, assistive technologies, chronic disease management, and coaching and health telematics systems

Winthrop University Undergraduate Scholarship & Creative Activity 2019

University College and Winthrop University proudly present Undergraduate Scholarship and Creative Activity 2019. This eighth annual University-wide compilation of undergraduate work chronicles the accomplishments of students and faculty mentors from at least 34 academic departments and programs, spanning all five colleges of the university: College of Arts and Sciences (CAS), College of Business Administration (CBA), College of Education (COE), College of Visual and Performing Arts (CVPA) and University College (UC).https://digitalcommons.winthrop.edu/undergradresearch_abstractbooks/1017/thumbnail.jp

2018 FSDG Combined Abstracts

https://scholarworks.gvsu.edu/fsdg_abstracts/1000/thumbnail.jp