14,695 research outputs found
Intermodal Terminal Subsystem Technology Selection Using Integrated Fuzzy MCDM Model
Intermodal transportation is the use of multiple modes of transportation, which can lead to
greater sustainability by reducing environmental impact and traffic congestion and increasing the
efficiency of supply chains. One of the preconditions for efficient intermodal transport is the efficient
intermodal terminal (IT). ITs allow for the smooth and efficient handling of cargo, thus reducing the
time, cost, and environmental impact of transportation. Adequate selection of subsystem technologies
can significantly improve the efficiency and productivity of an IT, ultimately leading to cost savings
for businesses and a more efficient and sustainable transportation system. Accordingly, this paper
aims to establish a framework for the evaluation and selection of appropriate technologies for IT
subsystems. To solve the defined problem, an innovative hybrid multi-criteria decision making
(MCDM) model, which combines the fuzzy factor relationship (FFARE) and the fuzzy combinative
distance-based assessment (FCODAS) methods, is developed in this paper. The FFARE method
is used for obtaining criteria weights, while the FCODAS method is used for evaluation and a
final ranking of the alternatives. The established framework and the model are tested on a real-life
case study, evaluating and selecting the handling technology for a planned IT. The study defines
12 potential variants of handling equipment based on their techno-operational characteristics and
evaluates them using 16 criteria. The results indicate that the best handling technology variant is
the one that uses a rail-mounted gantry crane for trans-shipment and a reach stacker for horizontal
transport and storage. The results also point to the conclusion that instead of choosing equipment
for each process separately, it is important to think about the combination of different handling
technologies that can work together to complete a series of handling cycle processes. The main
contributions of this paper are the development of a new hybrid model and the establishment of
a framework for the selection of appropriate IT subsystem technologies along with a set of unique
criteria for their evaluation and selection
A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic
The potential utility of wastewater-based epidemiology as an early warning tool has been explored widely across the globe during the current COVID-19 pandemic. Methods to detect the presence of SARS-CoV-2 RNA in wastewater were developed early in the pandemic, and extensive work has been conducted to evaluate the relationship between viral concentration and COVID-19 case numbers at the catchment areas of sewage treatment works (STWs) over time. However, no attempt has been made to develop a model that predicts wastewater concentration at fine spatio-temporal resolutions covering an entire country, a necessary step towards using wastewater monitoring for the early detection of local outbreaks. We consider weekly averages of flow-normalised viral concentration, reported as the number of SARS-CoV-2N1 gene copies per litre (gc/L) of wastewater available at 303 STWs over the period between 1 June 2021 and 30 March 2022. We specify a spatially continuous statistical model that quantifies the relationship between weekly viral concentration and a collection of covariates covering socio-demographics, land cover and virus associated genomic characteristics at STW catchment areas while accounting for spatial and temporal correlation. We evaluate the model’s predictive performance at the catchment level through 10-fold cross-validation. We predict the weekly viral concentration at the population-weighted centroid of the 32,844 lower super output areas (LSOAs) in England, then aggregate these LSOA predictions to the Lower Tier Local Authority level (LTLA), a geography that is more relevant to public health policy-making. We also use the model outputs to quantify the probability of local changes of direction (increases or decreases) in viral concentration over short periods (e.g. two consecutive weeks). The proposed statistical framework can predict SARS-CoV-2 viral concentration in wastewater at high spatio-temporal resolution across England. Additionally, the probabilistic quantification of local changes can be used as an early warning tool for public health surveillance
A Visual Modeling Method for Spatiotemporal and Multidimensional Features in Epidemiological Analysis: Applied COVID-19 Aggregated Datasets
The visual modeling method enables flexible interactions with rich graphical
depictions of data and supports the exploration of the complexities of
epidemiological analysis. However, most epidemiology visualizations do not
support the combined analysis of objective factors that might influence the
transmission situation, resulting in a lack of quantitative and qualitative
evidence. To address this issue, we have developed a portrait-based visual
modeling method called +msRNAer. This method considers the spatiotemporal
features of virus transmission patterns and the multidimensional features of
objective risk factors in communities, enabling portrait-based exploration and
comparison in epidemiological analysis. We applied +msRNAer to aggregate
COVID-19-related datasets in New South Wales, Australia, which combined
COVID-19 case number trends, geo-information, intervention events, and
expert-supervised risk factors extracted from LGA-based censuses. We perfected
the +msRNAer workflow with collaborative views and evaluated its feasibility,
effectiveness, and usefulness through one user study and three subject-driven
case studies. Positive feedback from experts indicates that +msRNAer provides a
general understanding of analyzing comprehension that not only compares
relationships between cases in time-varying and risk factors through portraits
but also supports navigation in fundamental geographical, timeline, and other
factor comparisons. By adopting interactions, experts discovered functional and
practical implications for potential patterns of long-standing community
factors against the vulnerability faced by the pandemic. Experts confirmed that
+msRNAer is expected to deliver visual modeling benefits with spatiotemporal
and multidimensional features in other epidemiological analysis scenarios
Anuário científico 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 Científico da Escola Superior de Tecnologia da Saúde de Lisboa. Como instituição de ensino superior, temos o compromisso de promover e incentivar a pesquisa científica em todas as áreas do conhecimento que contemplam a nossa missão. Esta publicação tem como objetivo divulgar toda a produção científica 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 científico de elevada qualidade e partilhada com a Sociedade na forma de livros, capítulos 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 específicos de Saúde, refletindo desta forma a pluralidade e diversidade de áreas que definem, e tornam única, a ESTeSL. Acreditamos que a investigação e pesquisa científica 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 início 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 científica 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
Architecture Smells vs. Concurrency Bugs: an Exploratory Study and Negative Results
Technical debt occurs in many different forms across software artifacts. One
such form is connected to software architectures where debt emerges in the form
of structural anti-patterns across architecture elements, namely, architecture
smells. As defined in the literature, ``Architecture smells are recurrent
architectural decisions that negatively impact internal system quality", thus
increasing technical debt. In this paper, we aim at exploring whether there
exist manifestations of architectural technical debt beyond decreased code or
architectural quality, namely, whether there is a relation between architecture
smells (which primarily reflect structural characteristics) and the occurrence
of concurrency bugs (which primarily manifest at runtime). We study 125
releases of 5 large data-intensive software systems to reveal that (1) several
architecture smells may in fact indicate the presence of concurrency problems
likely to manifest at runtime but (2) smells are not correlated with
concurrency in general -- rather, for specific concurrency bugs they must be
combined with an accompanying articulation of specific project characteristics
such as project distribution. As an example, a cyclic dependency could be
present in the code, but the specific execution-flow could be never executed at
runtime
Learning disentangled speech representations
A variety of informational factors are contained within the speech signal and a single short recording of speech reveals much more than the spoken words. The best method to extract and represent informational factors from the speech signal ultimately depends on which informational factors are desired and how they will be used. In addition, sometimes methods will capture more than one informational factor at the same time such as speaker identity, spoken content, and speaker prosody.
The goal of this dissertation is to explore different ways to deconstruct the speech signal into abstract representations that can be learned and later reused in various speech technology tasks. This task of deconstructing, also known as disentanglement, is a form of distributed representation learning. As a general approach to disentanglement, there are some guiding principles that elaborate what a learned representation should contain as well as how it should function. In particular, learned representations should contain all of the requisite information in a more compact manner, be interpretable, remove nuisance factors of irrelevant information, be useful in downstream tasks, and independent of the task at hand. The learned representations should also be able to answer counter-factual questions.
In some cases, learned speech representations can be re-assembled in different ways according to the requirements of downstream applications. For example, in a voice conversion task, the speech content is retained while the speaker identity is changed. And in a content-privacy task, some targeted content may be concealed without affecting how surrounding words sound. While there is no single-best method to disentangle all types of factors, some end-to-end approaches demonstrate a promising degree of generalization to diverse speech tasks.
This thesis explores a variety of use-cases for disentangled representations including phone recognition, speaker diarization, linguistic code-switching, voice conversion, and content-based privacy masking. Speech representations can also be utilised for automatically assessing the quality and authenticity of speech, such as automatic MOS ratings or detecting deep fakes. The meaning of the term "disentanglement" is not well defined in previous work, and it has acquired several meanings depending on the domain (e.g. image vs. speech). Sometimes the term "disentanglement" is used interchangeably with the term "factorization". This thesis proposes that disentanglement of speech is distinct, and offers a viewpoint of disentanglement that can be considered both theoretically and practically
Gasificação direta de biomassa para produção de gás combustível
The excessive consumption of fossil fuels to satisfy the world necessities of
energy and commodities led to the emission of large amounts of greenhouse
gases in the last decades, contributing significantly to the greatest
environmental threat of the 21st century: Climate Change. The answer to this
man-made disaster is not simple and can only be made if distinct stakeholders
and governments are brought to cooperate and work together. This is
mandatory if we want to change our economy to one more sustainable and
based in renewable materials, and whose energy is provided by the eternal
nature energies (e.g., wind, solar). In this regard, biomass can have a main role
as an adjustable and renewable feedstock that allows the replacement of fossil
fuels in various applications, and the conversion by gasification allows the
necessary flexibility for that purpose. In fact, fossil fuels are just biomass that
underwent extreme pressures and heat for millions of years. Furthermore,
biomass is a resource that, if not used or managed, increases wildfire risks.
Consequently, we also have the obligation of valorizing and using this
resource.
In this work, it was obtained new scientific knowledge to support the
development of direct (air) gasification of biomass in bubbling fluidized bed
reactors to obtain a fuel gas with suitable properties to replace natural gas in
industrial gas burners. This is the first step for the integration and development
of gasification-based biorefineries, which will produce a diverse number of
value-added products from biomass and compete with current petrochemical
refineries in the future. In this regard, solutions for the improvement of the raw
producer gas quality and process efficiency parameters were defined and
analyzed. First, addition of superheated steam as primary measure allowed the
increase of H2 concentration and H2/CO molar ratio in the producer gas without
compromising the stability of the process. However, the measure mainly
showed potential for the direct (air) gasification of high-density biomass (e.g.,
pellets), due to the necessity of having char accumulation in the reactor bottom
bed for char-steam reforming reactions. Secondly, addition of refused derived
fuel to the biomass feedstock led to enhanced gasification products, revealing
itself as a highly promising strategy in terms of economic viability and
environmental benefits of future gasification-based biorefineries, due to the
high availability and low costs of wastes. Nevertheless, integrated techno economic and life cycle analyses must be performed to fully characterize the
process. Thirdly, application of low-cost catalyst as primary measure revealed
potential by allowing the improvement of the producer gas quality (e.g., H2 and
CO concentration, lower heating value) and process efficiency parameters with
distinct solid materials; particularly, the application of concrete, synthetic
fayalite and wood pellets chars, showed promising results. Finally, the
economic viability of the integration of direct (air) biomass gasification
processes in the pulp and paper industry was also shown, despite still lacking
interest to potential investors. In this context, the role of government policies
and appropriate economic instruments are of major relevance to increase the
implementation of these projects.O consumo excessivo de combustíveis fósseis para garantir as necessidades e
interesses da sociedade conduziu à emissão de elevadas quantidades de
gases com efeito de estufa nas últimas décadas, contribuindo
significativamente para a maior ameaça ambiental do século XXI: Alterações
Climáticas. A solução para este desastre de origem humana é de caráter
complexo e só pode ser atingida através da cooperação de todos os governos
e partes interessadas. Para isto, é obrigatória a criação de uma bioeconomia
como base de um futuro mais sustentável, cujas necessidades energéticas e
materiais sejam garantidas pelas eternas energias da natureza (e.g., vento,
sol). Neste sentido, a biomassa pode ter um papel principal como uma matéria prima ajustável e renovável que permite a substituição de combustíveis fósseis
num variado número de aplicações, e a sua conversão através da gasificação
pode ser a chave para este propósito. Afinal, na prática, os combustíveis
fósseis são apenas biomassa sujeita a elevada temperatura e pressão durante
milhões de anos. Além do mais, a gestão eficaz da biomassa é fundamental
para a redução dos riscos de incêndio florestal e, como tal, temos o dever de
utilizar e valorizar este recurso.
Neste trabalho, foi obtido novo conhecimento científico para suporte do
desenvolvimento das tecnologias de gasificação direta (ar) de biomassa em
leitos fluidizados borbulhantes para produção de gás combustível, com o
objetivo da substituição de gás natural em queimadores industriais. Este é o
primeiro passo para o desenvolvimento de biorrefinarias de gasificação, uma
potencial futura indústria que irá providenciar um variado número de produtos
de valor acrescentado através da biomassa e competir com a atual indústria
petroquímica. Neste sentido, foram analisadas várias medidas para a melhoria
da qualidade do gás produto bruto e dos parâmetros de eficiência do processo.
Em primeiro, a adição de vapor sobreaquecido como medida primária permitiu
o aumento da concentração de H2 e da razão molar H2/CO no gás produto sem
comprometer a estabilidade do processo. No entanto, esta medida somente
revelou potencial para a gasificação direta (ar) de biomassa de alta densidade
(e.g., pellets) devido à necessidade da acumulação de carbonizados no leito
do reator para a ocorrência de reações de reforma com vapor. Em segundo, a
mistura de combustíveis derivados de resíduos e biomassa residual florestal
permitiu a melhoria dos produtos de gasificação, constituindo desta forma uma
estratégia bastante promissora a nível económico e ambiental, devido à
elevada abundância e baixo custo dos resíduos urbanos. Contudo, devem ser
efetuadas análises técnico-económicas e de ciclo de vida para a completa
caraterização do processo. Em terceiro, a aplicação de catalisadores de baixo
custo como medida primária demonstrou elevado potencial para a melhoria do
gás produto (e.g., concentração de H2 e CO, poder calorífico inferior) e para o
incremento dos parâmetros de eficiência do processo; em particular, a
aplicação de betão, faialite sintética e carbonizados de pellets de madeira,
demonstrou resultados promissores. Finalmente, foi demonstrada a viabilidade
económica da integração do processo de gasificação direta (ar) de biomassa
na indústria da pasta e papel, apesar dos parâmetros determinados não serem
atrativos para potenciais investidores. Neste contexto, a intervenção dos
governos e o desenvolvimento de instrumentos de apoio económico é de
grande relevância para a implementação destes projetos.Este trabalho foi financiado pela The Navigator Company e por Fundos Nacionais através da Fundação para a Ciência e a Tecnologia (FCT).Programa Doutoral em Engenharia da Refinação, Petroquímica e Químic
Product-service systems and circular supply chain practices in UK SMEs: The moderating effect of internal environmental orientation
Many studies uphold product-service systems (PSSs) as key factors for the implementation of circular supply chain (CSC) practices. This paper explores this assumption by testing the links between product-, use- and result-oriented PSSs and slowing, closing, and narrowing CSC practices. It develops and validates survey items that can be used to benchmark CSC practice implementation. In addition, it tests a model that recognises the positive moderating role of internal environmental orientation. A survey is conducted with 114 manufacturing small and medium-sized enterprises (SMEs) in the United Kingdom (UK). Partial least squares structural equation modelling is conducted to evaluate two models. The results show that product-oriented PSSs positively affect the slowing, use-oriented positively affects the closing, and result-oriented positively affects the slowing and the narrowing of resource loops. Internal environmental orientation does not moderate the PSS – CSC relationship, suggesting that less internally environmentally oriented firms are not at a disadvantage
CREATING VALUE IN ADDITIVE MANUFACTURING – MODELING OF ECOSYSTEM DETERMINANTS
Despite the increasing managerial awareness for ecosystems to organize complex value propositions, little is known about how different roles can establish their business models (BM) in ecosystems. AM drives innovations in the product design and manufacturing fields predominantly across companies, indicating the eco-systemic organization of value creation without orchestrating and dominant keystone actors yet. This paper explores ecosystem determinants by analyzing the dynamic additive manufacturing (AM) paradigm. We conduct an empirical study with companies from the AM domain to visualize their value activities and define generic roles in the interdependent value creation process, adopting the e³-value methodology. By exploring these ecosystem determinants, our results aid practitioners in positioning their BMs in the AM domain and generate descriptive insights for the orchestrator BM design in a dynamic domain without orchestrating keystones
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