Blue circular economy: opportunities for circular business models and circular design related to fishing gear (version 2)

This report aims to contribute to discussion related to the widespread and enduring problem of waste fishing gear in the world's oceans. It highlights the problem and proposes business opportunities. To help tackle the problems and opportunities in the Northern Periphery and Arctic (NPA) region, the European Commission (EC) Interreg funded Blue Circular Economy (BCE) project offers free help, including events, webinars and 1:1 mentoring to start-ups, SMEs and entrepreneurs as well as co-operatives and social enterprises in the NPA region. This report presents an overview of: • Gear used for fishing for finfish, shellfish and aquaculture • Extended Producer Responsibility (EPR) as it relates to waste fishing gear, as announced in the European Commission (EC) Single Use Plastics (SUP) Directive • Opportunities that might arise for more circular business models (CBMs) and new products for start-ups, SMEs, entrepreneurs, co-operatives and social enterprises in port cities, towns and fishing communities in the Northern Periphery and Arctic (NPA) region, and beyond • Strategies for improving the product circularity of fishing gear (circular design) The report includes a look at challenges posed by waste fishing gear in our oceans and at end of life, and, includes a short discussion on the implications for stakeholders and SMEs in the NPA region (see Appendix A). It addresses the Extended Producer Responsibility (EPR) scheme (that is part of the EC’s SUP Directive), new circular business models (CBMs) and circular design of fishing gear and finishes with overall conclusions. Fishing gear are complex products, comprising nets, ropes, components and peripherals e.g. polymers, metals, rubbers etc. This report uses the term waste "fishing gear" when referring to fishing nets, ropes, components and peripherals (FNRCPs)

Review of Smart Services for Tinnitus Self-Help, Diagnostics and Treatments

In the recent years, there has been an increasing interest in the potential of internet- and smartphone-based technologies for the support of tinnitus patients. A broad spectrum of relevant approaches, some in the form of studies, others in the form of market products, have been mentioned in literature. They include auditory treatments, internet-based Cognitive Behavioral Therapy (iCBT), serious games, and questionnaires for tinnitus monitoring. The goal of this study is to highlight the role of existing internet-based and smart technologies for the advancement of tinnitus clinical practice: we consider contributions that refer to treatments and diagnostics, and we include contributions refering to self-help measures. We elaborate on the potential and challenges of such solutions and identify constraints associated to their deployment, such as the demand for familiarity with internet-based services and the need to re-design interactive services so that they fit on the small surface of a smartwatch

DIT Teaching Fellowships Reports 2015-2016.

https://arrow.tudublin.ie/tfreports/1005/thumbnail.jp

Polyp Segmentation with Fully Convolutional Deep Neural Networks—Extended Evaluation Study

Analysis of colonoscopy images plays a significant role in early detection of colorectal cancer. Automated tissue segmentation can be useful for two of the most relevant clinical target applications—lesion detection and classification, thereby providing important means to make both processes more accurate and robust. To automate video colonoscopy analysis, computer vision and machine learning methods have been utilized and shown to enhance polyp detectability and segmentation objectivity. This paper describes a polyp segmentation algorithm, developed based on fully convolutional network models, that was originally developed for the Endoscopic Vision Gastrointestinal Image Analysis (GIANA) polyp segmentation challenges. The key contribution of the paper is an extended evaluation of the proposed architecture, by comparing it against established image segmentation benchmarks utilizing several metrics with cross-validation on the GIANA training dataset. Different experiments are described, including examination of various network configurations, values of design parameters, data augmentation approaches, and polyp characteristics. The reported results demonstrate the significance of the data augmentation, and careful selection of the method’s design parameters. The proposed method delivers state-of-the-art results with near real-time performance. The described solution was instrumental in securing the top spot for the polyp segmentation sub-challenge at the 2017 GIANA challenge and second place for the standard image resolution segmentation task at the 2018 GIANA challenge

Konzeption und Realisierung einer konfigurierbaren Plattform zur flexiblen Datenerhebung mittels moderner Webtechnologien

Der Einsatz papierbasierter Fragebögen ist heutzutage ein weit verbreitetes Mittel zur Erhebung von Daten in Studien und Umfragen. Jeder Teilnehmer erhält von einem Mitarbeiter einen Fragebogen, der anschließend bearbeitet wird. Nach der Bearbeitung müssen diese Daten für die Analyse digitalisiert werden. Diese Vorgehensweise stellt einen hohen Ressourcenverbrauch dar, insbesondere bei einer großen Anzahl an Studienteilnehmern. Die anschließende Digitalisierung der Antworten ist ebenfalls mit einem hohen Zeitaufwand verbunden. Dabei können während der Übertragung der Antworten diese falsch übertragen und somit Ergebnisse verfälscht werden. Eine Möglichkeit, diesen Problemen entgegenzutreten, wäre der Einsatz eines digitalen Fragebogensystems. Im Rahmen dieser Arbeit wird eine Plattform zur digitalen Datenerhebung entwickelt. Auf einem Server sollen Fragebögen hochgeladen werden können. Mit einem modernen Web-Client soll es möglich sein, diese Fragebögen an Nutzer zu verteilen und zu bearbeiten. Nach der Bearbeitung dieser Fragebögen werden die Antworten an den Server gesendet und dort persistiert. Komplexe Fragebögen mit einer verzweigten Ausführungslogik sollen dabei unterstützt sowie Benutzer während der Bearbeitung auf unvollständige Abgaben aufmerksam gemacht werden

XDecompo: eXplainable Decomposition Approach in Convolutional Neural Networks for Tumour Image Classification

Of the various tumour types, colorectal cancer and brain tumours are still considered among the most serious and deadly diseases in the world. Therefore, many researchers are interested in improving the accuracy and reliability of diagnostic medical machine learning models. In computer-aided diagnosis, self-supervised learning has been proven to be an effective solution when dealing with datasets with insufficient data annotations. However, medical image datasets often suffer from data irregularities, making the recognition task even more challenging. The class decomposition approach has provided a robust solution to such a challenging problem by simplifying the learning of class boundaries of a dataset. In this paper, we propose a robust self-supervised model, called XDecompo, to improve the transferability of features from the pretext task to the downstream task. XDecompo has been designed based on an affinity propagation-based class decomposition to effectively encourage learning of the class boundaries in the downstream task. XDecompo has an explainable component to highlight important pixels that contribute to classification and explain the effect of class decomposition on improving the speciality of extracted features. We also explore the generalisability of XDecompo in handling different medical datasets, such as histopathology for colorectal cancer and brain tumour images. The quantitative results demonstrate the robustness of XDecompo with high accuracy of 96.16% and 94.30% for CRC and brain tumour images, respectively. XDecompo has demonstrated its generalization capability and achieved high classification accuracy (both quantitatively and qualitatively) in different medical image datasets, compared with other models. Moreover, a post hoc explainable method has been used to validate the feature transferability, demonstrating highly accurate feature representations

Review of three-dimensional human-computer interaction with focus on the leap motion controller

Modern hardware and software development has led to an evolution of user interfaces from command-line to natural user interfaces for virtual immersive environments. Gestures imitating real-world interaction tasks increasingly replace classical two-dimensional interfaces based on Windows/Icons/Menus/Pointers (WIMP) or touch metaphors. Thus, the purpose of this paper is to survey the state-of-the-art Human-Computer Interaction (HCI) techniques with a focus on the special field of three-dimensional interaction. This includes an overview of currently available interaction devices, their applications of usage and underlying methods for gesture design and recognition. Focus is on interfaces based on the Leap Motion Controller (LMC) and corresponding methods of gesture design and recognition. Further, a review of evaluation methods for the proposed natural user interfaces is given

"Frozen conflicts" in Europe

Often forgotten but simmering "frozen conflicts" continuously mark the political map of Europe. All located in South Eastern Europe, the Black Sea area and Transcaucasia, these conflicts run along ethnic, national, cultural and linguistic lines, separating communities. This insightful book offers a rare critical analyses of the cases of Northern Cyprus, Transnistria, Abkhazia, South Ossetia, Nagorno-Karabakh, Kosovo, and Crimea. The constructive dealing with the negative consequences of 'frozen conflicts' in Europe requires taking into account the peculiarities of each case. These unresolved conflicts poison not only the regional security but impede the attainment of a united, free, peaceful, secure and prosperous Europe. The call for pragmatic solutions to promote reconciliation has as of yet remained unheard. Offering comparisons between the cases and recommendations for dealing with the conflicts, the international legal perspective on less than universally recognized states and two positive European examples of post-conflict reconciliation are provided