5,445 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
Machine learning and mixed reality for smart aviation: applications and challenges
The aviation industry is a dynamic and ever-evolving sector. As technology advances and becomes more sophisticated, the aviation industry must keep up with the changing trends. While some airlines have made investments in machine learning and mixed reality technologies, the vast majority of regional airlines continue to rely on inefficient strategies and lack digital applications. This paper investigates the state-of-the-art applications that integrate machine learning and mixed reality into the aviation industry. Smart aerospace engineering design, manufacturing, testing, and services are being explored to increase operator productivity. Autonomous systems, self-service systems, and data visualization systems are being researched to enhance passenger experience. This paper investigate safety, environmental, technological, cost, security, capacity, and regulatory challenges of smart aviation, as well as potential solutions to ensure future quality, reliability, and efficiency
Identity, Power, and Prestige in Switzerland's Multilingual Education
Switzerland is known for its multilingualism, yet not all languages are represented equally in society. The situation is exacerbated by the influx of heritage languages and English through migration and globalization processes which challenge the traditional education system. This study is the first to investigate how schools in Grisons, Fribourg, and Zurich negotiate neoliberal forces leading to a growing necessity of English, a romanticized view on national languages, and the social justice perspective of institutionalizing heritage languages. It uncovers power and legitimacy issues and showcases students' and teachers' complex identities to advocate equitable multilingual education
Using Crowd-Based Software Repositories to Better Understand Developer-User Interactions
Software development is a complex process. To serve the final software product to the end user, developers need to rely on a variety of software artifacts throughout the development process. The term software repository used to denote only containers of source code such as version control systems; more recent usage has generalized the concept to include a plethora of software development artifact kinds and their related meta-data.
Broadly speaking, software repositories include version control systems, technical documentation, issue trackers, question and answer sites, distribution information, etc. The software repositories can be based on a specific project (e.g., bug tracker for Firefox), or be crowd-sourced (e.g., questions and answers on technical Q&A websites). Crowd-based software artifacts are created as by-products of developer-user interactions which are sometimes referred to as communication channels. In this thesis, we investigate three distinct crowd-based software repositories that follow different models of developer-user interactions. We believe through a better understanding of the crowd-based software repositories, we can identify challenges in software development and provide insights to improve the software development process.
In our first study, we investigate Stack Overflow. It is the largest collection of programming related questions and answers. On Stack Overflow, developers interact with other developers to create crowd-sourced knowledge in the form of questions and answers. The results of the interactions (i.e., the question threads) become valuable information to the entire developer community. Prior research on Stack Overflow tacitly assume that questions receives answers directly on the platform and no need of interaction is required during the process. Meanwhile, the platform allows attaching comments to questions which forms discussions of the question. Our study found that question discussions occur for 59.2% of questions on Stack Overflow. For discussed and solved questions on Stack Overflow, 80.6% of the questions have the discussion begin before the accepted answer is submitted. The results of our study show the importance and nuances of interactions in technical Q&A.
We then study dotfiles, a set of publicly shared user-specific configuration files for software tools. There is a culture of sharing dotfiles within the developer community, where the idea is to learn from other developers’ dotfiles and share your variants. The interaction of dotfiles sharing can be viewed as developers sources information from other developers, adapt the information to their own needs, and share their adaptations back to the community. Our study on dotfiles suggests that is a common practice among developers to share dotfiles where 25.8% of the most stared users on GitHub have a dotfiles repository. We provide a taxonomy of the commonly tracked dotfiles and a qualitative study on the commits in dotfiles repositories. We also leveraged the state-of-the-art time-series clustering technique (K-shape) to identify code churn pattern for dotfile edits. This study is the first step towards understanding the practices of maintaining and sharing dotfiles.
Finally, we study app stores, the platforms that distribute software products and contain many non-technical attributes (e.g., ratings and reviews) of software products. Three major stakeholders interacts with each other in app stores: the app store owner who governs the operation of the app store; developers who publish applications on the app store; and users who browse and download applications in the app store. App stores often provide means of interaction between all three actors (e.g., app reviews, store policy) and sometimes interactions with in the same actor (e.g., developer forum). We surveyed existing app stores to extract key features from app store operation. We then labeled a representative set of app store collected by web queries. K-means is applied to the labeled app stores to detect natural groupings of app stores. We observed a diverse set of app stores through the process. Instead of a single model that describes all app stores, fundamentally, our observations show that app stores operates differently. This study provide insights in understanding how app stores can affect software development.
In summary, we investigated software repositories containing software artifacts created from different developer-user interactions. These software repositories are essential for software development in providing referencing information (i.e., Stack Overflow), improving development productivity (i.e., dotfiles), and help distributing the software products to end users (i.e., app stores)
Utilizing artificial intelligence in perioperative patient flow:systematic literature review
Abstract. The purpose of this thesis was to map the existing landscape of artificial intelligence (AI) applications used in secondary healthcare, with a focus on perioperative care. The goal was to find out what systems have been developed, and how capable they are at controlling perioperative patient flow. The review was guided by the following research question: How is AI currently utilized in patient flow management in the context of perioperative care?
This systematic literature review examined the current evidence regarding the use of AI in perioperative patient flow. A comprehensive search was conducted in four databases, resulting in 33 articles meeting the inclusion criteria. Findings demonstrated that AI technologies, such as machine learning (ML) algorithms and predictive analytics tools, have shown somewhat promising outcomes in optimizing perioperative patient flow. Specifically, AI systems have proven effective in predicting surgical case durations, assessing risks, planning treatments, supporting diagnosis, improving bed utilization, reducing cancellations and delays, and enhancing communication and collaboration among healthcare providers. However, several challenges were identified, including the need for accurate and reliable data sources, ethical considerations, and the potential for biased algorithms. Further research is needed to validate and optimize the application of AI in perioperative patient flow.
The contribution of this thesis is summarizing the current state of the characteristics of AI application in perioperative patient flow. This systematic literature review provides information about the features of perioperative patient flow and the clinical tasks of AI applications previously identified
A Conceptual Framework for Designing Interactive Human-Centred Building Spaces to Enhance User Experience in Specific-Purpose Buildings
Human/User interaction with buildings are mostly restricted to interacting
with building automation systems through user-interfaces that mainly aim to
improve energy efficiency of buildings and ensure comfort of occupants. This
research builds on the existing theories of Human-Building Interaction (HBI)
and proposes a novel conceptual framework for HBI that combines the concepts of
Human-Computer Interaction (HCI) and Ambient Intelligence (AmI). The proposed
framework aims to study the needs of occupants in specific-purpose buildings,
which is currently undermined. Specifically, we explore the application of the
proposed HBI framework to improve the learning experience of students in
academic buildings. Focus groups and semi-structured interviews were conducted
among students who are considered primary occupants of Goodwin Hall, a flagship
smart engineering building at Virginia Tech. Qualitative coding and concept
mapping were used to analyze the qualitative data and determine the impact of
occupant-specific needs on the learning experience of students in academic
buildings. The occupant-specific problem that was found to have the highest
direct impact on learning experience was finding study space and highest
indirect impact was Indoor Environment Quality (IEQ). We discuss new ideas for
designing Intelligent User Interfaces (IUI), e.g. Augmented Reality (AR),
increase the perceivable affordances for building occupants and considering a
context-aware ubiquitous analytics-based strategy to provide services that are
tailored to address the identified needs
The nexus between e-marketing, e-service quality, e-satisfaction and e-loyalty: a cross-sectional study within the context of online SMEs in Ghana
The spread of the Internet, the proliferation of mobile devices, and the onset of the COVID-19
pandemic have given impetus to online shopping in Ghana and the subregion. This situation
has also created opportunities for SMEs to take advantage of online marketing technologies.
However, there is a dearth of studies on the link between e-marketing and e-loyalty in terms
of online shopping, thereby creating a policy gap on the prospects for business success for
online SMEs in Ghana. Therefore, the purpose of the study was to examine the relationship
between the main independent variable, e-marketing and the main dependent variable, e-loyalty, as well as the mediating roles of e-service quality and e-satisfaction in the link between
e-marketing and e-loyalty. The study adopted a positivist stance with a quantitative method.
The study was cross-sectional in nature with the adoption of a descriptive correlational design.
A Structural Equation Modelling approach was employed to examine the nature of the
associations between the independent, mediating and dependent variables. A sensitivity
analysis was also conducted to control for the potential confounding effects of the
demographic factors. A sample size of 1,293 residents in Accra, Ghana, who had previously
shopped online, responded to structured questionnaire in an online survey via Google Docs.
The IBM SPSS Amos 24 software was used to analyse the data collected. Positive
associations were found between the key constructs in the study: e-marketing, e-service
quality, e-satisfaction and e-Loyalty. The findings from the study gave further backing to the
diffusion innovation theory, resource-based view theory, and technology acceptance model.
In addition, e-service quality and e-satisfaction individually and jointly mediated the
relationship between e-marketing and e-loyalty. However, these mediations were partial,
instead of an originally anticipated full mediation. In terms of value and contribution, this is the
first study in a developing economy context to undertake a holistic examination of the key
marketing performance variables within an online shopping context. The study uniquely tested
the mediation roles of both e-service quality and e-satisfaction in the link between e-marketing
and e-loyalty. The findings of the study are novel in the e-marketing literature as they
unearthed the key antecedents of e-loyalty for online SMEs in a developing economy context.
The study suggested areas for further related studies and also highlighted the limitations
A food recipe recommendation system based on nutritional factors in the Finnish food communit
Abstract. This thesis presents a comprehensive study on the relationships between user feedback, recipe content, and additional factors in the context of a recipe recommendation system. The aim was to investigate the influence of various factors on user ratings and comments related to nutritional variables, while also exploring the potential for personalized recipe suggestions. Statistical analysis, clustering techniques, and sentiment analysis were employed to analyze a dataset of food recipes and user feedback. We determined that user feedback is a complex phenomenon influenced by subjective factors beyond recipe content alone. Cluster analysis identified four distinct clusters within the dataset, highlighting variations in nutritional values and sentiment among recipes. However, due to an imbalanced distribution within the clusters, these relationships were not considered in the recommendation system. To address the absence of user-related data, a content-based filtering approach was implemented, utilizing nutritional factors and a health factor calculation. The system provides personalized recipe recommendations based on nutritional similarity and health considerations. A maximum limit of 20 recommended recipes was set, allowing users to specify the desired number of recommendations. The accompanying API also provides a mean squared error metric to assess recommendation quality. This research contributes to a better understanding of user preferences, recipe content, and the challenges in developing effective recommendation systems for food recipes
A Conceptual Model for Quality 4.0 Deployment in U.S. Based Manufacturing Firms
Manufacturing is currently undergoing a fourth industrial revolution, referred to as Industry 4.0, enabled by digital technologies and advances in our ability to collect and use data. Quality 4.0 is the application of Industry 4.0 to enhance the quality function within an organization. Quality practitioners are uniquely positioned within organizations and already possess data application skillsets. Despite a perception that Quality 4.0 will be critical to future success shared by a majority of industry, most companies have not attempted to implement Quality 4.0 strategy, and those that have report very low rates of success. The goal of this study was to understand the challenges and key factors behind implementation of a Quality 4.0 system and develop a model for implementation, highlighting those key factors. The model was developed through literature review, case study analysis, and expert interviews. The model indicated that four main constructs exist in Quality 4.0 deployment, digital strategy, enabling factors, methodologies, and technology. A top-level strategy should be developed to address key technology development themes as well as nontechnical business process themes. Strategy should then be executed in the domain of enabling factors and methodologies with a clear technology application serving as the output. A successful Quality 4.0 implementation will use the technology application to drive tangible quality improvement activities which add value to the business
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