159 research outputs found
Deep Multi Temporal Scale Networks for Human Motion Analysis
The movement of human beings appears to respond to a complex motor system that contains signals at different hierarchical levels.
For example, an action such as ``grasping a glass on a table'' represents a high-level action, but to perform this task, the body needs several motor inputs that include the activation of different joints of the body (shoulder, arm, hand, fingers, etc.).
Each of these different joints/muscles have a different size, responsiveness, and precision with a complex non-linearly stratified temporal dimension where every muscle has its temporal scale.
Parts such as the fingers responds much faster to brain input than more voluminous body parts such as the shoulder.
The cooperation we have when we perform an action produces smooth, effective, and expressive movement in a complex multiple temporal scale cognitive task.
Following this layered structure, the human body can be described as a kinematic tree, consisting of joints connected.
Although it is nowadays well known that human movement and its perception are characterised by multiple temporal scales, very few works in the literature are focused on studying this particular property.
In this thesis, we will focus on the analysis of human movement using data-driven techniques.
In particular, we will focus on the non-verbal aspects of human movement, with an emphasis on full-body movements.
The data-driven methods can interpret the information in the data by searching for rules, associations or patterns that can represent the relationships between input (e.g. the human action acquired with sensors) and output (e.g. the type of action performed).
Furthermore, these models may represent a new research frontier as they can analyse large masses of data and focus on aspects that even an expert user might miss.
The literature on data-driven models proposes two families of methods that can process time series and human movement.
The first family, called shallow models, extract features from the time series that can help the learning algorithm find associations in the data.
These features are identified and designed by domain experts who can identify the best ones for the problem faced.
On the other hand, the second family avoids this phase of extraction by the human expert since the models themselves can identify the best set of features to optimise the learning of the model.
In this thesis, we will provide a method that can apply the multi-temporal scales property of the human motion domain to deep learning models, the only data-driven models that can be extended to handle this property.
We will ask ourselves two questions: what happens if we apply knowledge about how human movements are performed to deep learning models? Can this knowledge improve current automatic recognition standards?
In order to prove the validity of our study, we collected data and tested our hypothesis in specially designed experiments.
Results support both the proposal and the need for the use of deep multi-scale models as a tool to better understand human movement and its multiple time-scale nature
Central and Eastern European Literary Theory and the West
The twentieth century saw intensive intellectual exchange between Eastern and Central Europe and the West. Yet political and linguistic obstacles meant that many important trends in East and Central European thought and knowledge hardly registered in Western Europe and the US. This book uncovers the hidden westward movements of Eastern European literary theory and its influence on Western scholarship
Digital Humanities, Corpus and Language Technology/ Humanidades Digitales, Corpus y Tecnología del Lenguaje:A look from diverse case studies / Una mirada desde diversos casos de estudio
Digital Humanities, Corpus and Language Technology: A look from diverse case studies is an outstanding collection of research contributions that explores the intersection of technology and the humanities. The authors provide a comprehensive overview of how these technologies can enhance research across various disciplines, from literature to history to anthropology. This book is a mustread for anyone interested in future research in the humanities. Digital Humanities, Corpus, and Language Technologies are rapidly growing fields that have the potential to revolutionize research across various disciplines.New technologies have opened up new perspectives for research, allowing scientists to analyze data in previously impossible ways. The interdisciplinary approach and practical applications make it an invaluable resource for researchers, students, and anyone interested in the intersection of technology and the humanities
Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico
Conference proceedings info:
ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies
Raleigh, HI, United States, March 24-26, 2023
Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center
of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático.
de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-
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Methods in Contemporary Linguistics
The present volume is a broad overview of methods and methodologies in linguistics, illustrated with examples from concrete research. It collects insights gained from a broad range of linguistic sub-disciplines, ranging from core disciplines to topics in cross-linguistic and language-internal diversity or to contributions towards language, space and society. Given its critical and innovative nature, the volume is a valuable source for students and researchers of a broad range of linguistic interests
A framework for guiding the interdisciplinary design of mHealth intervention apps for physical activity behaviour change
The global pandemic of noncommunicable diseases and its associated premature mortality rates and socioeconomic burden have led to increasingly intensified efforts towards designing and delivering health promotion interventions aimed at addressing the leading modifiable health risk behaviours, such as physical inactivity. Developing physical activity behaviour change interventions that target individuals at the dual intra-interpersonal socioecological levels of health promotion has become a key objective worldwide. Digital and mobile technology is revolutionising the ways in which health behaviour change interventions are delivered to individuals across the world, with mobile health applications (mHealth apps) increasingly recognised as a powerful means of promoting physical activity behaviour change. However, with the growth and opportunities of mHealth apps, come several design challenges. Key design challenges concern the integration of theory, the incorporation of evidence-based behaviour change techniques, the application of persuasive systems design principles, and the importance of multi- and interdisciplinary collaborative design, development and evaluation approaches. These key challenges influence the output product design and effectiveness of mHealth physical activity behaviour change intervention apps. There exists a paucity of approaches for guiding and supporting the multi- and interdisciplinary collaborative design, development and evaluation of mHealth physical activity behaviour change intervention apps. To address this gap, this research study proposes an Interdisciplinary mHealth App Design Framework, framed by a novel boundary object view. This view considers the diverse communities of practice, boundary objects and supporting artefacts, process activities, and knowledge sharing practices necessary and relevant to the design of effective mHealth physical activity behaviour change intervention apps. The framework’s development is guided by a Design Science Research (DSR) approach. Its core components are based on the findings of a critical theoretical analysis of twenty existing multi- and interdisciplinary digital health development approaches. Once developed, the framework is evaluated using a qualitative DSR linguistic interpretivist approach, with semi-structured interviews as the research instrument. The thematic analysis findings from interviews with thirty-one international academic researchers and industry practitioners informs the iterative modification and revision of an enhanced Interdisciplinary mHealth App Design Framework, constituting the main DSR artefact contribution of the research study. In addition, four theoretical contributions are made to the mHealth intervention app design body of knowledge, and a practical contribution is made through the provision of guideline recommendations for academics and industry practitioners. Methodological contributions are also made in terms of applying DSR, adopting a hybrid cognitive reasoning strategy, and employing a qualitative linguistic interpretivist approach to evaluation within a DSR project.Thesis (PhD) -- Faculty of Commerce, Information Systems, 202
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