4,819 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
Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse
This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses.
This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups.
In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in usersâ speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018â6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena
2023-2024 Boise State University Undergraduate Catalog
This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State
Integration of heterogeneous data sources and automated reasoning in healthcare and domotic IoT systems
In recent years, IoT technology has radically transformed many crucial industrial and service sectors such as healthcare. The multi-facets heterogeneity of the devices and the collected information provides important opportunities to develop innovative systems and services. However, the ubiquitous presence of data silos and the poor semantic interoperability in the IoT landscape constitute a significant obstacle in the pursuit of this goal. Moreover, achieving actionable knowledge from the collected data requires IoT information sources to be analysed using appropriate artificial intelligence techniques such as automated reasoning. In this thesis work, Semantic Web technologies have been investigated as an approach to address both the data integration and reasoning aspect in modern IoT systems. In particular, the contributions presented in this thesis are the following: (1) the IoT Fitness Ontology, an OWL ontology that has been developed in order to overcome the issue of data silos and enable semantic interoperability in the IoT fitness domain; (2) a Linked Open Data web portal for collecting and sharing IoT health datasets with the research community; (3) a novel methodology for embedding knowledge in rule-defined IoT smart home scenarios; and (4) a knowledge-based IoT home automation system that supports a seamless integration of heterogeneous devices and data sources
Axisymmetry in Mechanical Engineering
The reprint is devoted to the phenomena associated with exact or approximate axial symmetry in different areas of technical physics and mechanical engineering science. How can the symmetry of the problem be used most efficiently for its analysis? Why is the symmetry broken or why is it still approximately retained? These and other questions are discussed based on systems from different fields of engineering
Environmental Impact Assessment by Green Processes
Primary energy consumption around the world has been increasing steadily since the Industrial Revolution and shows no signals of slowing down in the coming years. This trend is accompanied by the increasing pollutant concentration on the Earthâs biosystems and the general concerns over the health and environmental impacts that will ensue. Air quality, water purity, atmospheric CO2 concentration, etc., are some examples of environmental parameters that are degrading due to human activities. These ecosystems can be safeguarded without renouncing industrial development, urban and economic development through the use of low environmental impact technologies instead of equivalent pollutant ones or through the use of technologies to mitigate the negative impact of high emissions technologies. Pollutant abatement systems, carbon capture technologies, biobased products, etc. need to be established in order to make environmental parameters more and more similar to the pre-industrialization values of the planet Earth. In 15 papers international scientists addressed such topics, especially combining a high academic standard coupled with a practical focus on green processes and a quantitative approach to environmental impacts
Machine Learning and Its Application to Reacting Flows
This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows. These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the worldâs total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and âgreenerâ combustion systems that are friendlier to the environment can be designed. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation
Computational Stylistics in Poetry, Prose, and Drama
The contributions in this edited volume approach poetry, narrative, and drama from the perspective of Computational Stylistics. They exemplify methods of computational textual analysis and explore the possibility of computational generation of literary texts. The volume presents a range of computational and Natural Language Processing applications to literary studies, such as motif detection, network analysis, machine learning, and deep learning
Tidal Energy and Coastal Models: Improved Turbine Simulation
Marine renewable energy is a continually growing topic of both commercial and academic research sectors. While not as developed as other renewable technologies such as those deployed within the wind sector, there is substantial technological crossover coupled with the inherent high energy density of water, that has helped push marine renewables into the wider renewable agenda. Thus, an ever expanding range of projects are in various stages of development.As with all technological developments, there are a range of factors that can con-tribute to the rate of development or eventual success. One of the main difficulties, when looking at marine renewable technologies in a comparative view to other en-ergy generation technologies, is that the operational environment is physically more complex: Energy must be supplied in diverse physical conditions, that temporally fluctuate with a range of time scales. The constant questions to the iteration to the local ecology. The increased operational fatigue of deployed devices. The financial risk associated within a recent sector.This work presents the continual research related to the computational research development of different marine renewable technologies that were under develop-ment of several institutional bodies at the time of writing this document.The scope has a wide envelopment as the nature of novel projects means that the project failure rate is high. Thus, forced through a combination of reasons related to financial, useful purpose and intellectual property, the research covers distinct projects
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