7,929 research outputs found

    Focused Decoding Enables 3D Anatomical Detection by Transformers

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    Detection Transformers represent end-to-end object detection approaches based on a Transformer encoder-decoder architecture, exploiting the attention mechanism for global relation modeling. Although Detection Transformers deliver results on par with or even superior to their highly optimized CNN-based counterparts operating on 2D natural images, their success is closely coupled to access to a vast amount of training data. This, however, restricts the feasibility of employing Detection Transformers in the medical domain, as access to annotated data is typically limited. To tackle this issue and facilitate the advent of medical Detection Transformers, we propose a novel Detection Transformer for 3D anatomical structure detection, dubbed Focused Decoder. Focused Decoder leverages information from an anatomical region atlas to simultaneously deploy query anchors and restrict the cross-attention's field of view to regions of interest, which allows for a precise focus on relevant anatomical structures. We evaluate our proposed approach on two publicly available CT datasets and demonstrate that Focused Decoder not only provides strong detection results and thus alleviates the need for a vast amount of annotated data but also exhibits exceptional and highly intuitive explainability of results via attention weights. Our code is available at https://github.com/bwittmann/transoar.Comment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2023:00

    An advanced deep learning models-based plant disease detection: A review of recent research

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    Plants play a crucial role in supplying food globally. Various environmental factors lead to plant diseases which results in significant production losses. However, manual detection of plant diseases is a time-consuming and error-prone process. It can be an unreliable method of identifying and preventing the spread of plant diseases. Adopting advanced technologies such as Machine Learning (ML) and Deep Learning (DL) can help to overcome these challenges by enabling early identification of plant diseases. In this paper, the recent advancements in the use of ML and DL techniques for the identification of plant diseases are explored. The research focuses on publications between 2015 and 2022, and the experiments discussed in this study demonstrate the effectiveness of using these techniques in improving the accuracy and efficiency of plant disease detection. This study also addresses the challenges and limitations associated with using ML and DL for plant disease identification, such as issues with data availability, imaging quality, and the differentiation between healthy and diseased plants. The research provides valuable insights for plant disease detection researchers, practitioners, and industry professionals by offering solutions to these challenges and limitations, providing a comprehensive understanding of the current state of research in this field, highlighting the benefits and limitations of these methods, and proposing potential solutions to overcome the challenges of their implementation

    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

    A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms

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    Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data. A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability. To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity. A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case. The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change. The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence

    CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship

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    This book collects important contributions on smart cities. This book was created in collaboration with the ICSC-CITIES2020, held in San José (Costa Rica) in 2020. This book collects articles on: energetic efficiency and sustainability; infrastructures, energy and the environment; mobility and IoT; governance and citizenship

    Modeling, Simulation and Data Processing for Additive Manufacturing

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    Additive manufacturing (AM) or, more commonly, 3D printing is one of the fundamental elements of Industry 4.0. and the fourth industrial revolution. It has shown its potential example in the medical, automotive, aerospace, and spare part sectors. Personal manufacturing, complex and optimized parts, short series manufacturing and local on-demand manufacturing are some of the current benefits. Businesses based on AM have experienced double-digit growth in recent years. Accordingly, we have witnessed considerable efforts in developing processes and materials in terms of speed, costs, and availability. These open up new applications and business case possibilities all the time, which were not previously in existence. Most research has focused on material and AM process development or effort to utilize existing materials and processes for industrial applications. However, improving the understanding and simulation of materials and AM process and understanding the effect of different steps in the AM workflow can increase the performance even more. The best way of benefit of AM is to understand all the steps related to that—from the design and simulation to additive manufacturing and post-processing ending the actual application.The objective of this Special Issue was to provide a forum for researchers and practitioners to exchange their latest achievements and identify critical issues and challenges for future investigations on “Modeling, Simulation and Data Processing for Additive Manufacturing”. The Special Issue consists of 10 original full-length articles on the topic

    Gender and Sport

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    This volume covers current issues, cutting-edge debates and new knowledge on women and sport. The range of topics extends from female coaches and women in sport to sexual harassment, from snowboarders to schoolgirls, and from physical education to football. The aim of this book is to provide an overview of the current debates on gender and sport from a women’s perspective, to share new knowledge about important issues, in particular about gender (in)equalities, and to present insights into the causes and effects of the debates and developments in the arena of women’s sport. A special focus in all chapters will be on the perspective of change, and backgrounds, reasons and effects of gender arrangements will be analyzed by scholars who made major contributions to the development of a new gender order in sport and society. Other authors are younger scholars with new perspectives and approaches – who represent the new generation of gender researchers

    Diagnostic challenges in the evaluation of renal osteodystrophy – A Study using 18F-sodium fluoride positron emission tomography

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    The majority of patients with end-stage kidney disease develop abnormalities in bone metabolism, referred to as renal osteodystrophy. Bone abnormalities are associated with cardiovascular morbidity and mortality. The diagnosis of the subgroups of renal osteodystrophy, such as low- and high-turnover bone disease, is challenging. Bone biopsy is the gold standard, but it is invasive and not easily available. Biomarkers, such as parathyroid hormone and alkaline phosphatase, diagnostic accuracy is insufficient. A noninvasive diagnostic tool in the evaluation of renal osteodystrophy would be highly welcomed. 18F-sodium fluoride positron emission tomography (18FNaF PET) is an imaging method that measures osteoblast activity and remodeling of bone. The aims of this study were to (a) assess the usability of 18F-NaF PET and (b) to assess the possible correlation between tracer activity and findings obtained from bone biopsy (c) evaluating whether 18F-NaF PET imaging could replace bone biopsies in clinical practice. In addition, (d) the association between arterial calcification and bone metabolism was evaluated. We observed a correlation between tracer activity measured by dynamic 18F-NaF PET and parameters obtained by bone biopsy (a). The sensitivity and specificity of the method to distinguish between high- and low-turnover bone disease was good (b). Fluoride activity measured in the static 18F-NaF PET scan showed good correlation with the fluoride activity measured in the dynamic scan, after correction for tracer activity in the blood (c). A weak association between arterial calcification and bone metabolism was also established (d). 18F-NaF PET presents as a promising diagnostic tool in the evaluation of renal osteodystrophy. Our research suggests that a static 18F-NaF PET scan obtained after a single injection of tracer generates usable images of bone metabolism and could also work in a clinical setting.Diagnostiset haasteet munuaispotilaiden luustotaudin arvioinnissa – Tutkimus, jossa käytetään 18F-NaF positroniemissiotomografia Suurimmalle osalle potilaista, jotka sairastavat vaikeaa munuaisten vajaatoimintaa, kehittyy poikkeavuuksia luun aineenvaihduntaan. Luustohäiriöiden tiedetään liittyvän myös sydän- ja verisuonisairauksiin sekä kuolleisuuteen. Luustohäiriöiden alaryhmien kuten hitaan ja nopean aineenvaihdunnan luutaudin diagnosointi on haastavaa. Nykyisin katsotaan luubiopsian olevan diagnostiikan kultainen standardi, mutta se on kajoava ja käytössä vain muutamissa keskuksissa. Laboratoriokokeiden, kuten alkalisen fosfataasin tai parathormonin diagnostinen tarkkuus tiedetään puolestaan riittämättömäksi. Näin ollen erityisesti kliinisessä työssä kaivattaisiin uutta kajoamatonta menetelmää munuaistaudin aiheuttamien luustomuutosten arviointiin. 18F-NaF positroniemissiotomografia (18F-NaF PET) on kuvantamismenetelmä, joka kuvastaa luuta muodostavien solujen aktiivisuutta ja luun uudelleenmuodostumista. Tämän tutkimuksen tavoitteena oli (a) arvioida 18F-NaF PET -kuvantamisen käytettävyyttä ja (b) arvioida merkkiaineaktiivisuuden mahdollista korrelaatiota luubiopsiasta saatujen parametrien välillä. Lisäksi arvioitiin, voisiko (c) 18F-NaF PET korvata luubiopsian kliinisessä työssä. Myös (d) valtimokalkkeutumien ja luun aineenvaihdunnan häiriöiden välistä yhteyttä selvittiin. Dynaamisen 18F-NaF PET kuvauksen mitatun merkkiaineaktiivisuuden ja luubiopsialla saatujen parametrien välillä oli vahva korrelaatio (a). Menetelmä todettiin sekä herkäksi että tarkaksi kyvyssään erottaa luun alentunut ja kiihtynyt aineenvaihdunta (b). Staattisen ja dynaamisen 18F-NaF PET –kuvauksen fluoriaktiivisuus korreloivat hyvin veren merkkiaineen aktiivisuuden korjaamisen jälkeen (c). Valtimoiden kalkkeutumisasteen ja luun aineenvaihdunnan välillä puolestaan pystyttiin osoittamaan heikko assosiaatio (d). 18F-NaF PET on lupaava diagnostinen työkalu munuaispotilaiden luustotaudin arvioinnissa. Tutkimuksemme viittaa siihen, että yhden merkkiaineinjektion jälkeen saatu staattinen 18F-NaF PET kuvaus voisi toimia myös kliinisessä työssä
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