10,024 research outputs found

    The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

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    The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

    Examples of works to practice staccato technique in clarinet instrument

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    Klarnetin staccato tekniğini güçlendirme aşamaları eser çalışmalarıyla uygulanmıştır. Staccato geçişlerini hızlandıracak ritim ve nüans çalışmalarına yer verilmiştir. Çalışmanın en önemli amacı sadece staccato çalışması değil parmak-dilin eş zamanlı uyumunun hassasiyeti üzerinde de durulmasıdır. Staccato çalışmalarını daha verimli hale getirmek için eser çalışmasının içinde etüt çalışmasına da yer verilmiştir. Çalışmaların üzerinde titizlikle durulması staccato çalışmasının ilham verici etkisi ile müzikal kimliğe yeni bir boyut kazandırmıştır. Sekiz özgün eser çalışmasının her aşaması anlatılmıştır. Her aşamanın bir sonraki performans ve tekniği güçlendirmesi esas alınmıştır. Bu çalışmada staccato tekniğinin hangi alanlarda kullanıldığı, nasıl sonuçlar elde edildiği bilgisine yer verilmiştir. Notaların parmak ve dil uyumu ile nasıl şekilleneceği ve nasıl bir çalışma disiplini içinde gerçekleşeceği planlanmıştır. Kamış-nota-diyafram-parmak-dil-nüans ve disiplin kavramlarının staccato tekniğinde ayrılmaz bir bütün olduğu saptanmıştır. Araştırmada literatür taraması yapılarak staccato ile ilgili çalışmalar taranmıştır. Tarama sonucunda klarnet tekniğin de kullanılan staccato eser çalışmasının az olduğu tespit edilmiştir. Metot taramasında da etüt çalışmasının daha çok olduğu saptanmıştır. Böylelikle klarnetin staccato tekniğini hızlandırma ve güçlendirme çalışmaları sunulmuştur. Staccato etüt çalışmaları yapılırken, araya eser çalışmasının girmesi beyni rahatlattığı ve istekliliği daha arttırdığı gözlemlenmiştir. Staccato çalışmasını yaparken doğru bir kamış seçimi üzerinde de durulmuştur. Staccato tekniğini doğru çalışmak için doğru bir kamışın dil hızını arttırdığı saptanmıştır. Doğru bir kamış seçimi kamıştan rahat ses çıkmasına bağlıdır. Kamış, dil atma gücünü vermiyorsa daha doğru bir kamış seçiminin yapılması gerekliliği vurgulanmıştır. Staccato çalışmalarında baştan sona bir eseri yorumlamak zor olabilir. Bu açıdan çalışma, verilen müzikal nüanslara uymanın, dil atış performansını rahatlattığını ortaya koymuştur. Gelecek nesillere edinilen bilgi ve birikimlerin aktarılması ve geliştirici olması teşvik edilmiştir. Çıkacak eserlerin nasıl çözüleceği, staccato tekniğinin nasıl üstesinden gelinebileceği anlatılmıştır. Staccato tekniğinin daha kısa sürede çözüme kavuşturulması amaç edinilmiştir. Parmakların yerlerini öğrettiğimiz kadar belleğimize de çalışmaların kaydedilmesi önemlidir. Gösterilen azmin ve sabrın sonucu olarak ortaya çıkan yapıt başarıyı daha da yukarı seviyelere çıkaracaktır

    Breast mass segmentation from mammograms with deep transfer learning

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    Abstract. Mammography is an x-ray imaging method used in breast cancer screening, which is a time consuming process. Many different computer assisted diagnosis have been created to hasten the image analysis. Deep learning is the use of multilayered neural networks for solving different tasks. Deep learning methods are becoming more advanced and popular for segmenting images. One deep transfer learning method is to use these neural networks with pretrained weights, which typically improves the neural networks performance. In this thesis deep transfer learning was used to segment cancerous masses from mammography images. The convolutional neural networks used were pretrained and fine-tuned, and they had an an encoder-decoder architecture. The ResNet22 encoder was pretrained with mammography images, while the ResNet34 encoder was pretrained with various color images. These encoders were paired with either a U-Net or a Feature Pyramid Network decoder. Additionally, U-Net model with random initialization was also tested. The five different models were trained and tested on the Oulu Dataset of Screening Mammography (9204 images) and on the Portuguese INbreast dataset (410 images) with two different loss functions, binary cross-entropy loss with soft Jaccard loss and a loss function based on focal Tversky index. The best models were trained on the Oulu Dataset of Screening Mammography with the focal Tversky loss. The best segmentation result achieved was a Dice similarity coefficient of 0.816 on correctly segmented masses and a classification accuracy of 88.7% on the INbreast dataset. On the Oulu Dataset of Screening Mammography, the best results were a Dice score of 0.763 and a classification accuracy of 83.3%. The results between the pretrained models were similar, and the pretrained models had better results than the non-pretrained models. In conclusion, deep transfer learning is very suitable for mammography mass segmentation and the choice of loss function had a large impact on the results.Rinnan massojen segmentointi mammografiakuvista syvä- ja siirto-oppimista hyödyntäen. Tiivistelmä. Mammografia on röntgenkuvantamismenetelmä, jota käytetään rintäsyövän seulontaan. Mammografiakuvien seulonta on aikaa vievää ja niiden analysoimisen avuksi on kehitelty useita tietokoneavusteisia ratkaisuja. Syväoppimisella tarkoitetaan monikerroksisten neuroverkkojen käyttöä eri tehtävien ratkaisemiseen. Syväoppimismenetelmät ovat ajan myötä kehittyneet ja tulleet suosituiksi kuvien segmentoimiseen. Yksi tapa yhdistää syvä- ja siirtooppimista on hyödyntää neuroverkkoja esiopetettujen painojen kanssa, mikä auttaa parantamaan neuroverkkojen suorituskykyä. Tässä diplomityössä tutkittiin syvä- ja siirto-oppimisen käyttöä syöpäisten massojen segmentoimiseen mammografiakuvista. Käytetyt konvoluutioneuroverkot olivat esikoulutettuja ja hienosäädettyjä. Lisäksi niillä oli enkooderi-dekooderi arkkitehtuuri. ResNet22 enkooderi oli esikoulutettu mammografia kuvilla, kun taas ResNet34 enkooderi oli esikoulutettu monenlaisilla värikuvilla. Näihin enkoodereihin yhdistettiin joko U-Net:n tai piirrepyramidiverkon dekooderi. Lisäksi käytettiin U-Net mallia ilman esikoulutusta. Nämä viisi erilaista mallia koulutettiin ja testattiin sekä Oulun Mammografiaseulonta Datasetillä (9204 kuvaa) että portugalilaisella INbreast datasetillä (410 kuvaa) käyttäen kahta eri tavoitefunktiota, jotka olivat binääriristientropia yhdistettynä pehmeällä Jaccard-indeksillä ja fokaaliin Tversky indeksiin perustuva tavoitefunktiolla. Parhaat mallit olivat koulutettu Oulun datasetillä fokaalilla Tversky tavoitefunktiolla. Parhaat tulokset olivat 0,816 Dice kerroin oikeissa positiivisissa segmentaatioissa ja 88,7 % luokittelutarkkuus INbreast datasetissä. Esikoulutetut mallit antoivat parempia tuloksia kuin mallit joita ei esikoulutettu. Oulun datasetillä parhaat tulokset olivat 0,763:n Dice kerroin ja 83,3 % luokittelutarkkuus. Tuloksissa ei ollut suurta eroa esikoulutettujen mallien välillä. Tulosten perusteella syvä- ja siirto-oppiminen soveltuvat hyvin massojen segmentoimiseen mammografiakuvista. Lisäksi tavoitefunktiovalinnalla saatiin suuri vaikutus tuloksiin

    Learning disentangled speech representations

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    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

    'Exarcheia doesn't exist': Authenticity, Resistance and Archival Politics in Athens

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    My thesis investigates the ways people, materialities and urban spaces interact to form affective ecologies and produce historicity. It focuses on the neighbourhood of Exarcheia, Athens’ contested political topography par excellence, known for its production of radical politics of discontent and resistance to state oppression and eoliberal capitalism. Embracing Exarcheia’s controversial status within Greek vernacular, media and state discourses, this thesis aims to unpick the neighbourhoods’ socio-spatial assemblage imbued with affect and formed through the numerous (mis)understandings and (mis)interpretations rooted in its turbulent political history. Drawing on theory on urban spaces, affect, hauntology and archival politics, I argue for Exarcheia as an unwavering archival space composed of affective chronotopes – (in)tangible loci that defy space and temporality. I posit that the interwoven narratives and materialities emerging in my fieldwork are persistently – and perhaps obsessively – reiterating themselves and remaining imprinted on the neighbourhood’s landscape as an incessant reminder of violent histories that the state often seeks to erase and forget. Through this analysis, I contribute to understandings of place as a primary ethnographic ‘object’ and the ways in which place forms complex interactions and relationships with social actors, shapes their subjectivities, retains and bestows their memories and senses of historicity

    Optimising acoustic cavitation for industrial application

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    The ultrasonic horn is one of the most commonly used acoustic devices in laboratories and industry. For its efficient application to cavitation mediated process, the cavitation generated at its tip as a function of its tip-vibration amplitudes still needed to be studied in detail. High-speed imaging and acoustic detection are used to investigate the cavitation generated at the tip of an ultrasonic horn, operating at a fundamental frequency, f0, of 20 kHz. Tip-vibration amplitudes are sampled at fine increments across the range of input powers available. The primary bubble cluster under the tip is found to undergo subharmonic periodic collapse, with concurrent shock wave emission, at frequencies of f0/m, with m increasing through integer values with increasing tip-vibration amplitude. The contribution of periodic shock waves to the noise spectra of the acoustic emissions is confirmed. Transitional input powers for which the value of m is indistinct, and shock wave emission irregular and inconsistent, are identified through Vrms of the acoustic detector output. For cavitation applications mediated by bubble collapse, sonications at transitional powers may lead to inefficient processing. The ultrasonic horn is also deployed to investigate the role of shock waves in the fragmentation of intermetallic crystals, nominally for ultrasonic treatment of Aluminium melt, and in a novel two-horn configuration for potential cavitation enhancement effects. An experiment investigating nitrogen fixation via cavitation generated by focused ultrasound exposures is also described. Vrms from the acoustic detector is again used to quantify the acoustic emissions for comparison to the sonochemical nitrite yield and for optimisation of sonication protocols at constant input energy. The findings revealed that the acoustic cavitation could be enhanced at constant input energy through optimisation of the pulse duration and pulse interval. Anomalous results may be due to inadequate assessment for the nitrate generated. The studies presented in this thesis have illustrated means of improving the cavitation efficiency of the used acoustic devices, which may be important to some selected industrial processes

    The Impact of a Play Intervention on the Social-Emotional Development of Preschool Children in Riyadh, Saudi Arabia

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    Practitioners working with children have emphasized that play is vital to children’s development, Links between children’s social-emotional development and play have been widely documented. However, rigorous research evidence of these links remains limited. This study’s objectives were to measure the impact of play on children’s social-emotional development in the kingdom of Saudi Arabia; identify teachers’ viewpoints around the use of play intervention; and understand the children’s experience of play intervention. Fifty-nine children aged between five and six years, with mean age of 5.5 (SD 3.376) and eight teachers participated in the study. The study used a mixed-method strategy including questionnaires, interviews, and focus group discussions. Children’s social-emotional development was measured by using the Strengths and Difficulties Questioner (SDQ). A pre-/post-test counterbalanced design was used to measure the impact of the play intervention on children’s development. Teachers’ perspectives on play were obtained by interviewing eight teachers. Children’s views were gathered through focus group discussions. Repeated measures ANOVA was conducted to determine the differences in the SDQ score over three time points. Results showed that using unstructured loose parts play had positively impacted children’s social-emotional development. After participation in the play intervention, scores from the SDQ indicated that children demonstrated significantly less problematic emotional, conduct and peer relationship issues. They also scored significantly higher in their positive prosocial behaviour. These positive effects were sustained after six weeks of stopping the intervention. The play intervention did not however impact children’s hyperactivity level. The interviews analysis illustrates four main themes: concept and characteristics of play, play functions, developmental benefits of play, and play and practice. Regarding children’s discussion, affordance emerged as a main theme; this includes emotional, social, and functional affordances. Unstructured loose parts play intervention was demonstrated to have positive impacts on children’s social-emotional development. The study’s findings support the view that play is a way to increase children’s development

    SYSTEMS METHODS FOR ANALYSIS OF HETEROGENEOUS GLIOBLASTOMA DATASETS TOWARDS ELUCIDATION OF INTER-TUMOURAL RESISTANCE PATHWAYS AND NEW THERAPEUTIC TARGETS

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    In this PhD thesis is described an endeavour to compile litterature about Glioblastoma key molecular mechanisms into a directed network followin Disease Maps standards, analyse its topology and compare results with quantitative analysis of multi-omics datasets in order to investigate Glioblastoma resistance mechanisms. The work also integrated implementation of Data Management good practices and procedures

    Industry 4.0: product digital twins for remanufacturing decision-making

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    Currently there is a desire to reduce natural resource consumption and expand circular business principles whilst Industry 4.0 (I4.0) is regarded as the evolutionary and potentially disruptive movement of technology, automation, digitalisation, and data manipulation into the industrial sector. The remanufacturing industry is recognised as being vital to the circular economy (CE) as it extends the in-use life of products, but its synergy with I4.0 has had little attention thus far. This thesis documents the first investigating into I4.0 in remanufacturing for a CE contributing a design and demonstration of a model that optimises remanufacturing planning using data from different instances in a product’s life cycle. The initial aim of this work was to identify the I4.0 technology that would enhance the stability in remanufacturing with a view to reducing resource consumption. As the project progressed it narrowed to focus on the development of a product digital twin (DT) model to support data-driven decision making for operations planning. The model’s architecture was derived using a bottom-up approach where requirements were extracted from the identified complications in production planning and control that differentiate remanufacturing from manufacturing. Simultaneously, the benefits of enabling visibility of an asset’s through-life health were obtained using a DT as the modus operandi. A product simulator and DT prototype was designed to use Internet of Things (IoT) components, a neural network for remaining life estimations and a search algorithm for operational planning optimisation. The DT was iteratively developed using case studies to validate and examine the real opportunities that exist in deploying a business model that harnesses, and commodifies, early life product data for end-of-life processing optimisation. Findings suggest that using intelligent programming networks and algorithms, a DT can enhance decision-making if it has visibility of the product and access to reliable remanufacturing process information, whilst existing IoT components provide rudimentary “smart” capabilities, but their integration is complex, and the durability of the systems over extended product life cycles needs to be further explored

    Strung pieces: on the aesthetics of television fiction series

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    As layered and long works, television fiction series have aesthetic properties that are built over time, bit by bit. This thesis develops a group of concepts that enable the study of these properties, It argues that a series is made of strung pieces, a system of related elements. The text begins by considering this sequential form within the fields of film and television. This opening chapter defines the object and methodology of research, arguing for a non-essentialist distinction between cinema and television and against the adequacy of textual and contextual analyses as approaches to the aesthetics of these shows. It proposes instead that these programmes should be described as televisual works that can be scrutinised through aesthetic analysis. The next chapters propose a sequence of interrelated concepts. The second chapter contends that series are composed of building blocks that can be either units into which series are divided or motifs that unify series and are dispersed across their pans. These blocks are patterned according to four kinds of relations or principles of composition. Repetition and variation are treated in tandem in the third chapter because of their close connection, given that variation emerges from established repetition. Exception and progression are also discussed together in the fourth chapter since they both require a long view of these serial works. The former, in order to be recognised as a deviation from the patterns of repetition and variation. The latter, In order to be understood in Its many dimensions as the series advances. Each of these concepts is further detailed with additional distinctions between types of units, motifs, repetitions, variations, and exceptions, using illustrative examples from numerous shows. In contrast, the section on progression uses a single series as case study, Carnivàle (2003-05), because this is the overarching principle that encompasses all the others. The conclusion considers the findings of the research and suggests avenues for their application
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