10,327 research outputs found
A review of abnormal behavior detection in activities of daily living
Abnormal behavior detection (ABD) systems are built to automatically identify and recognize abnormal behavior from various input data types, such as sensor-based and vision-based input. As much as the attention received for ABD systems, the number of studies on ABD in activities of daily living (ADL) is limited. Owing to the increasing rate of elderly accidents in the home compound, ABD in ADL research should be given as much attention to preventing accidents by sending out signals when abnormal behavior such as falling is detected. In this study, we compare and contrast the formation of the ABD system in ADL from input data types (sensor-based input and vision-based input) to modeling techniques (conventional and deep learning approaches). We scrutinize the public datasets available and provide solutions for one of the significant issues: the lack of datasets in ABD in ADL. This work aims to guide new research to understand the field of ABD in ADL better and serve as a reference for future study of better Ambient Assisted Living with the growing smart home trend
New Building Blocks for Cancer Phototherapeutics: 5d Metallocorroles
Corroles are ring-contracted, triprotic analogues of porphyrins. This PhD study expands earlier knowledge in particular on ReO corroles. Early on, it became apparent that ReO corroles exhibit the highest phosphorescence quantum yields among all metallocorroles. They also sensitize singlet oxygen formation and serve as oxygen sensors and as triplet-triplet annihilation upconverters. I accordingly wanted to synthesize new classes of functionalized 5d corroles as well as to examine ReO corroles as photosensitizers in in vitro photodynamic therapy experiments. I found that amphiphilic meta/para-carboxyl-appended ReO triphenylcorroles exhibit high photocytotoxicity against multiple cancer cell lines. In the synthetic realm, one study examined electrophilic chlorination and bromination of ReO corroles. X-ray structures of ReO octachloro- and octabromocorroles yielded a host of insights into the conformational preferences of sterically hindered corrole derivatives. Another synthetic study afforded an innovative approach to water-soluble iridium corroles, involving the use of water-soluble axial ligands. I also undertook extensive studies of formylation of ReO and Au triarylcorroles, arriving at the rather elegant conclusion that whereas the former largely afford 3-monoformyl products, the latter preferentially yield 3,17-diformylproducts, presumably reflecting the higher nucleophilicity of the Au complexes. The formylcorrole products could be readily postfunctionalized, such as via the Knoevenagel reaction. The 5d formylcorroles should serve as valuable starting materials for bio- and nanoconjugated 5d metallocorroles for advanced, targeted cancer therapies. I feel privileged to have developed a new class of triplet photosensitizers – the ReO corroles – that to this day remain unique to our Tromsø laboratory. I am confident, however, that we shall soon see exciting applications of these compounds as advanced photodynamic, photothermal and multimodal cancer therapeutics
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
A Design Science Research Approach to Smart and Collaborative Urban Supply Networks
Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness.
A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense.
Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice
Perfect is the enemy of test oracle
Automation of test oracles is one of the most challenging facets of software
testing, but remains comparatively less addressed compared to automated test
input generation. Test oracles rely on a ground-truth that can distinguish
between the correct and buggy behavior to determine whether a test fails
(detects a bug) or passes. What makes the oracle problem challenging and
undecidable is the assumption that the ground-truth should know the exact
expected, correct, or buggy behavior. However, we argue that one can still
build an accurate oracle without knowing the exact correct or buggy behavior,
but how these two might differ. This paper presents SEER, a learning-based
approach that in the absence of test assertions or other types of oracle, can
determine whether a unit test passes or fails on a given method under test
(MUT). To build the ground-truth, SEER jointly embeds unit tests and the
implementation of MUTs into a unified vector space, in such a way that the
neural representation of tests are similar to that of MUTs they pass on them,
but dissimilar to MUTs they fail on them. The classifier built on top of this
vector representation serves as the oracle to generate "fail" labels, when test
inputs detect a bug in MUT or "pass" labels, otherwise. Our extensive
experiments on applying SEER to more than 5K unit tests from a diverse set of
open-source Java projects show that the produced oracle is (1) effective in
predicting the fail or pass labels, achieving an overall accuracy, precision,
recall, and F1 measure of 93%, 86%, 94%, and 90%, (2) generalizable, predicting
the labels for the unit test of projects that were not in training or
validation set with negligible performance drop, and (3) efficient, detecting
the existence of bugs in only 6.5 milliseconds on average.Comment: Published in ESEC/FSE 202
Anuário cientÃfico da Escola Superior de Tecnologia da Saúde de Lisboa - 2021
É com grande prazer que apresentamos a mais recente edição (a 11.ª) do Anuário CientÃfico da Escola Superior de Tecnologia da Saúde de Lisboa. Como instituição de ensino superior, temos o compromisso de promover e incentivar a pesquisa cientÃfica em todas as áreas do conhecimento que contemplam a nossa missão. Esta publicação tem como objetivo divulgar toda a produção cientÃfica desenvolvida pelos Professores, Investigadores, Estudantes e Pessoal não Docente da ESTeSL durante 2021. Este Anuário é, assim, o reflexo do trabalho árduo e dedicado da nossa comunidade, que se empenhou na produção de conteúdo cientÃfico de elevada qualidade e partilhada com a Sociedade na forma de livros, capÃtulos de livros, artigos publicados em revistas nacionais e internacionais, resumos de comunicações orais e pósteres, bem como resultado dos trabalhos de 1º e 2º ciclo. Com isto, o conteúdo desta publicação abrange uma ampla variedade de tópicos, desde temas mais fundamentais até estudos de aplicação prática em contextos especÃficos de Saúde, refletindo desta forma a pluralidade e diversidade de áreas que definem, e tornam única, a ESTeSL. Acreditamos que a investigação e pesquisa cientÃfica é um eixo fundamental para o desenvolvimento da sociedade e é por isso que incentivamos os nossos estudantes a envolverem-se em atividades de pesquisa e prática baseada na evidência desde o inÃcio dos seus estudos na ESTeSL. Esta publicação é um exemplo do sucesso desses esforços, sendo a maior de sempre, o que faz com que estejamos muito orgulhosos em partilhar os resultados e descobertas dos nossos investigadores com a comunidade cientÃfica e o público em geral. Esperamos que este Anuário inspire e motive outros estudantes, profissionais de saúde, professores e outros colaboradores a continuarem a explorar novas ideias e contribuir para o avanço da ciência e da tecnologia no corpo de conhecimento próprio das áreas que compõe a ESTeSL. Agradecemos a todos os envolvidos na produção deste anuário e desejamos uma leitura inspiradora e agradável.info:eu-repo/semantics/publishedVersio
Decoding spatial location of attended audio-visual stimulus with EEG and fNIRS
When analyzing complex scenes, humans often focus their attention on an object at a particular spatial location in the presence of background noises and irrelevant visual objects. The ability to decode the attended spatial location would facilitate brain computer interfaces (BCI) for complex scene analysis. Here, we tested two different neuroimaging technologies and investigated their capability to decode audio-visual spatial attention in the presence of competing stimuli from multiple locations. For functional near-infrared spectroscopy (fNIRS), we targeted dorsal frontoparietal network including frontal eye field (FEF) and intra-parietal sulcus (IPS) as well as superior temporal gyrus/planum temporal (STG/PT). They all were shown in previous functional magnetic resonance imaging (fMRI) studies to be activated by auditory, visual, or audio-visual spatial tasks. We found that fNIRS provides robust decoding of attended spatial locations for most participants and correlates with behavioral performance. Moreover, we found that FEF makes a large contribution to decoding performance. Surprisingly, the performance was significantly above chance level 1s after cue onset, which is well before the peak of the fNIRS response.
For electroencephalography (EEG), while there are several successful EEG-based algorithms, to date, all of them focused exclusively on auditory modality where eye-related artifacts are minimized or controlled. Successful integration into a more ecological typical usage requires careful consideration for eye-related artifacts which are inevitable. We showed that fast and reliable decoding can be done with or without ocular-removal algorithm. Our results show that EEG and fNIRS are promising platforms for compact, wearable technologies that could be applied to decode attended spatial location and reveal contributions of specific brain regions during complex scene analysis
Interview with Wolfgang Knauss
An oral history in four sessions (September 2019–January 2020) with Wolfgang Knauss, von Kármán Professor of Aeronautics and Applied Mechanics, Emeritus. Born in Germany in 1933, he speaks about his early life and experiences under the Nazi regime, his teenage years in Siegen and Heidelberg during the Allied occupation, and his move to Pasadena, California, in 1954 under the sponsorship of a local minister and his family. He enrolled in Caltech as an undergraduate in 1957, commencing a more than half-century affiliation with the Institute and GALCIT (today the Graduate Aerospace Laboratories of Caltech). He recalls the roots of his interest in aeronautics, his PhD solid mechanics studies with his advisor, M. Williams, and the GALCIT environment in the late 1950s and 1960s at the dawn of the Space Age, including the impact of Sputnik and classes with NASA astronauts. He discusses his experimental and theoretical work on materials deformation, dynamic fracture, and crack propagation, including his solid-propellant fuels research for NASA and the US Army, wide-ranging programs with the US Navy, and his pioneering micromechanics investigations and work on the time-dependent fracture of polymers in the 1990s.
He offers his perspective on GALCIT’s academic culture, its solid mechanics and fluid mechanics programs, and its evolving administrative directions over the course of five decades, as well as its impact and reputation both within and beyond Caltech. He describes his work with Caltech’s undergraduate admissions committee and his scientific collaborations with numerous graduate students and postdocs and shares his recollections of GALCIT and other Caltech colleagues, including C. Babcock, D. Coles, R.P. Feynman, Y.C. Fung, G. Neugebauer, G. Housner, D. Hudson, H. Liepmann, A. Klein, G. Ravichandran, A. Rosakis, A. Roshko, and E. Sechler.
Six appendices contributed by Dr. Knauss, offering further insight into his life and career, also form part of this oral history and are cross-referenced in the main text
A Case Study Examining Japanese University Students' Digital Literacy and Perceptions of Digital Tools for Academic English learning
Current Japanese youth are constantly connected to the Internet and using digital devices, but predominantly for social media and entertainment. According to literature on the Japanese digital native, tertiary students do not—and cannot—use technology with any reasonable fluency, but the likely reasons are rarely addressed. To fill the gap in the literature, this study, by employing a case study methodology, explores students’ experience with technology for English learning through the introduction of digital tools. First-year Japanese university students in an Academic English Program (AEP) were introduced to a variety of easily available digital tools. The instruction was administered online, and each tool was accompanied by a task directly related to classwork. Both quantitative and qualitative data were collected in the form of a pre-course Computer Literacy Survey, a post-course open-ended Reflection Activity survey, and interviews. The qualitative data was reviewed drawing on the Technology Acceptance Model (TAM) and its educational variants as an analytical framework. Educational, social, and cultural factors were also examined to help identify underlying factors that would influence students’ perceptions. The results suggest that the subjects’ lack of awareness of, and experience with, the use of technology for learning are the fundamental causes of their perceptions of initial difficulty. Based on these findings, this study proposes a possible technology integration model that enhances digital literacy for more effective language learning in the context of Japanese education
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