1,016 research outputs found

    Planetary Hinterlands:Extraction, Abandonment and Care

    Get PDF
    This open access book considers the concept of the hinterland as a crucial tool for understanding the global and planetary present as a time defined by the lasting legacies of colonialism, increasing labor precarity under late capitalist regimes, and looming climate disasters. Traditionally seen to serve a (colonial) port or market town, the hinterland here becomes a lens to attend to the times and spaces shaped and experienced across the received categories of the urban, rural, wilderness or nature. In straddling these categories, the concept of the hinterland foregrounds the human and more-than-human lively processes and forms of care that go on even in sites defined by capitalist extraction and political abandonment. Bringing together scholars from the humanities and social sciences, the book rethinks hinterland materialities, affectivities, and ecologies across places and cultural imaginations, Global North and South, urban and rural, and land and water

    Fully-Automated Packaging Structure Recognition of Standardized Logistics Assets on Images

    Get PDF
    Innerhalb einer logistischen Lieferkette müssen vielfältige Transportgüter an zahlreichen Knotenpunkten bearbeitet, wiedererkannt und kontrolliert werden. Dabei ist oft ein großer manueller Aufwand erforderlich, um die Paketidentität oder auch die Packstruktur zu erkennen oder zu verifizieren. Solche Schritte sind notwendig, um beispielsweise eine Lieferung auf ihre Vollständigkeit hin zu überprüfen. Wir untersuchen die Konzeption und Implementierung eines Verfahrens zur vollständigen Automatisierung der Erkennung der Packstruktur logistischer Sendungen. Ziel dieses Verfahrens ist es, basierend auf einem einzigen Farbbild, eine oder mehrere Transporteinheiten akkurat zu lokalisieren und relevante Charakteristika, wie beispielsweise die Gesamtzahl oder die Anordnung der enthaltenen Packstücke, zu erkennen. Wir stellen eine aus mehreren Komponenten bestehende Bildverarbeitungs-Pipeline vor, die diese Aufgabe der Packstrukturerkennung lösen soll. Unsere erste Implementierung des Verfahrens verwendet mehrere Deep Learning Modelle, genauer gesagt Convolutional Neural Networks zur Instanzsegmentierung, sowie Bildverarbeitungsmethoden und heuristische Komponenten. Wir verwenden einen eigenen Datensatz von Echtbildern aus einer Logistik-Umgebung für Training und Evaluation unseres Verfahrens. Wir zeigen, dass unsere Lösung in der Lage ist, die korrekte Packstruktur in etwa 85% der Testfälle unseres Datensatzes zu erkennen, und sogar eine höhere Genauigkeit erzielt wird, wenn nur die meist vorkommenden Packstücktypen betrachtet werden. Für eine ausgewählte Bilderkennungs-Komponente unseres Algorithmus vergleichen wir das Potenzial der Verwendung weniger rechenintensiver, eigens designter Bildverarbeitungsmethoden mit den zuvor implementierten Deep Learning Verfahren. Aus dieser Untersuchung schlussfolgern wir die bessere Eignung der lernenden Verfahren, welche wir auf deren sehr gute Fähigkeit zur Generalisierung zurückführen. Außerdem formulieren wir das Problem der Objekt-Lokalisierung in Bildern anhand selbst gewählter Merkmalspunkte, wie beispielsweise Eckpunkte logistischer Transporteinheiten. Ziel hiervon ist es, Objekte präziser zu lokalisieren, als dies insbesondere im Vergleich zur Verwendung herkömmlicher umgebender Rechtecke möglich ist, während gleichzeitig die Objektform durch bekanntes Vorwissen zur Objektgeometrie forciert wird. Wir stellen ein spezifisches Deep Learning Modell vor, welches die beschriebene Aufgabe löst im Fall von Objekten, welche durch vier Eckpunkte beschrieben werden können. Das dabei entwickelte Modell mit Namen TetraPackNet wird evaluiert mittels allgemeiner und anwendungsbezogener Metriken. Wir belegen die Anwendbarkeit der Lösung im Falle unserer Bilderkennungs-Pipeline und argumentieren die Relevanz für andere Anwendungsfälle, wie beispielweise Kennzeichenerkennung

    Development of Bridge Information Model (BrIM) for digital twinning and management using TLS technology

    Get PDF
    In the current modern era of information and technology, the concept of Building Information Model (BIM), has made revolutionary changes in different aspects of engineering design, construction, and management of infrastructure assets, especially bridges. In the field of bridge engineering, Bridge Information Model (BrIM), as a specific form of BIM, includes digital twining of the physical asset associated with geometrical inspections and non-geometrical data, which has eliminated the use of traditional paper-based documentation and hand-written reports, enabling professionals and managers to operate more efficiently and effectively. However, concerns remain about the quality of the acquired inspection data and utilizing BrIM information for remedial decisions in a reliable Bridge Management System (BMS) which are still reliant on the knowledge and experience of the involved inspectors, or asset manager, and are susceptible to a certain degree of subjectivity. Therefore, this research study aims not only to introduce the valuable benefits of Terrestrial Laser Scanning (TLS) as a precise, rapid, and qualitative inspection method, but also to serve a novel sliced-based approach for bridge geometric Computer-Aided Design (CAD) model extraction using TLS-based point cloud, and to contribute to BrIM development. Moreover, this study presents a comprehensive methodology for incorporating generated BrIM in a redeveloped element-based condition assessment model while integrating a Decision Support System (DSS) to propose an innovative BMS. This methodology was further implemented in a designed software plugin and validated by a real case study on the Werrington Bridge, a cable-stayed bridge in New South Wales, Australia. The finding of this research confirms the reliability of the TLS-derived 3D model in terms of quality of acquired data and accuracy of the proposed novel slice-based method, as well as BrIM implementation, and integration of the proposed BMS into the developed BrIM. Furthermore, the results of this study showed that the proposed integrated model addresses the subjective nature of decision-making by conducting a risk assessment and utilising structured decision-making tools for priority ranking of remedial actions. The findings demonstrated acceptable agreement in utilizing the proposed BMS for priority ranking of structural elements that require more attention, as well as efficient optimisation of remedial actions to preserve bridge health and safety

    An investigation into the environmental sustainability of the South African ornamental horticultural industry

    Get PDF
    The ornamental horticultural industry makes use of natural resources to grow plants and produce allied products to sell to consumers, landscapers, retail garden centres, hardware stores, supermarkets, and government, but at what cost to the environment? The aim of this work was to determine the current environmental awareness of growers and garden centre retailers within the ornamental horticultural industry in South Africa. Followed by an investigation into the current business practices that promote sustainable natural resource use and management as well as the obstacles and challenges that the industry faces with implementing legislation and recommendations of best practices. The study was conducted over an 18-month period and 41 growers and retail garden centres in eight of the provinces in South Africa (Appendix 10) participated in research. In each case, the study participant was asked to complete the questionnaire and where possible, a site visit was conducted and / or a semi-structured interview as well as participatory observations followed to give a comprehensive overview of the sustainability practices of the businesses. These results were then compared to international best practices and similar research conducted globally by the ornamental horticultural industry. A review of international best practices in the ornamental horticultural industry showed six environmental resources namely soil, water, fertilizers, pesticides, energy, and waste. This was seen to be common to most studies involved in the production, growth, maintenance and sales of plants and allied products. This information was used to compile a best management practice manual for South African ornamental horticulture with guidelines and practical examples for conserving and managing natural resource usage and reducing the environmental impacts of the industry. Much research has been done on the exploitation and degradation of resources due to urbanisation, industrial activities, and agricultural practices. The resources are essential to the ornamental horticultural industry but if exploited or misused, can have detrimental effects on the environmental productivity of the industry and ultimately the “Sustainable Development Goals” prescribed by the United Nations. The linking of the relevant sustainable development goals to the 9 key factors of the green economy strategized by the South African government will enable the ornamental horticultural industry to play a greater part in the green and circular economy by providing nature-based solutions to environmental problems that it is facing such as climate change and pollution.Environmental SciencesD. Phil. (Environmental Management

    SIMULATING CONSUMABLE ORDER FULFILLMENT VIA ADDITIVE MANUFACTURING TECHNOLOGIES

    Get PDF
    Operational availability of naval aircraft through material readiness is critical to ensuring combat power. Supportability of aircraft is a crucial aspect of readiness, influenced by several factors including access to 9B Cognizance Code (COG) aviation consumable repair parts at various supply echelons. Rapidly evolving additive manufacturing (AM) technologies are transforming supply chain dynamics and the traditional aircraft supportability construct. As of June 2022, there are 595 AM assets within the Navy’s inventory—all for research and development purposes. This report simulates 9B COG aviation consumable fulfillment strategies within the U.S. Indo-Pacific sustainment network for a three-year span, inclusive of traditional supply support avenues and a developed set of user-variable capability inputs. Simulated probabilistic demand configurations are modeled from historical trends that exploit a heuristic methodology to assign a “printability” score to each 9B COG requirement, accounting for uncertainty, machine failure rates, and other continuous characteristics of the simulated orders. The results measure simulated lead time across diverse planning horizons in both current and varied operationalized AM sustainment network configurations. This research indicates a measurable lead time reduction of approximately 10% across all 9B order lead times when AM is employed as an order fulfillment source for only 0.5% of orders.NPS Naval Research ProgramThis project was funded in part by the NPS Naval Research Program.Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited

    Comparative analysis of 3D- depth cameras in industrial bin picking solution

    Get PDF
    Machine vision is a crucial component of a successful bin picking solution. During the past few years, there has been large advancements in depth sensing technologies. This has led to them receiving a lot of attention, especially in bin picking applications. With reduced costs and greater accessibility, the use of machine vision has rapidly increased. Automated bin picking poses a technical challenge, which is present in numerous industrial processes. Robots need perception from their surroundings, and machine vision attempt to solve this by providing eyes to the machine. The motivation behind solving this challenge is the increased productivity, enabled by automated bin picking. The main goal of this thesis is to address the challenges of bin picking by comparing the performance of different 3D- depth cameras with illustrative case studies and experimental research. The depth cameras are exposed to different ambient conditions and object properties, where the performance of different 3D- imaging technologies is evaluated and compared between each other. The performance of a commercial bin picking solution is also researched through illustrative case studies to evaluate the accuracy, reliability, and flexibility of the solution. Feasibility study is also conducted, and the capabilities of the bin picking solution is demonstrated in two industrial applications. This research work focuses on three different depth sensing technologies. Comparison is done between structured light, stereo vision, and time-of-flight technologies. The main categories for evaluation are ambient light tolerance, reflective surfaces, and how well the depth cameras can detect simple and complex geometric features. The comparison between the depth cameras is limited to opaque objects, ranging from shiny metal blanks to matte connector components and porous surface textures. The performance of each depth camera is evaluated, and the advantages and disadvantages of each technology are discussed. Results of this thesis showed that while all of the technologies are capable of performing in a bin picking solution, structured light performed the best in the evaluation criteria of this thesis. The results from bin picking solution accuracy evaluation also illustrated some of the many challenges of bin picking, and how the true accuracy of the bin picking solution is not dictated purely by the resolution of the vision sensor. Finally, to conclude this thesis the results and future suggestions are discussed.Konenäkö on keskeinen osa automatisoitua kasasta poimintasovellusta. Syvyyskamerateknologiat ovat kehittyneet paljon kuluneiden vuosien aikana, joka on herättänyt paljon keskustelua niiden käyttömahdollisuuksista. Kustannusten alenemisen, sekä paremman saatavuuden myötä konenäön käyttö, erityisesti kasasta poimintasovelluksissa onkin lisääntynyt nopeasti. Automatisoitu kasasta poiminta kuitenkin omaa teknisiä haasteita, jotka ovat läsnä lukuisissa teollisissa prosesseissa. Motivaatio automatisoidun kasasta poiminnan taustalla on tuotettavuuden kasvu, jonka konenäkö mahdollistaa tarjoamalla dataa robotin ympäristöstä. Tämän diplomityön tavoitteina on vastata kasasta poiminnan haasteisiin vertailemalla erilaisten 3D-syvyyskameroiden suorituskykyä tapaustutkimusten sekä kokeellisen tutkimuksen avulla. Syvyyskameroiden toimintaa arvioidaan erilaisissa ympäristöissä sekä erilaisilla kappaleilla, jonka seurauksena 3D-kuvaustekniikoiden suorituskykyä vertaillaan keskenään. Työn aikana arvioidaan myös kaupallisen kasasta poimintasovelluksen suorituskykyä, jossa tutkitaan tapaustutkimusten avulla sovelluksen tarkkuutta, luotettavuutta sekä joustavuutta. Tämän lisäksi sovelluksen toimintaa pilotoidaan, ja ratkaisun ominaisuuksia demonstroidaan kahdessa teollisessa sovelluksessa. Tämä diplomityö keskittyy kolmeen eri syvyyskameratekniikkaan. Vertailu tehdään strukturoidun valon, stereonäön sekä Time-of-Flight tekniikoiden välillä. Arvioinnin pääkategoriat ovat ympäristön valoisuus, geometristen muotojen havainnointikyky, sekä heijastavat pinnat. Syvyyskameroiden välinen vertailu rajoittuu läpinäkymättömiin kappaleisiin, jotka vaihtelevat kiiltävistä metalliaihioista mattapintaisiin liitinkomponentteihin ja huokoisiin pintarakenteisiin. Tutkimuksen tulokset osoittivat, että vaikka kaikki tekniikat kykenevät automatisoituun kasasta poimintaan, strukturoitu valo suoriutui tutkituista teknologioista parhaiten. Kasasta poimintasovelluksen tarkkuuden arviointi havainnollisti myös sen monia haasteita, sekä kuinka sovelluksen todellinen tarkkuus ei riipu ainoastaan syvyyskameran resoluutiosta. Loppupäätelmien lisäksi työ päätetään ehdotuksilla tutkimuksen jatkamiseksi

    Challenges and opportunities managing “Breenfield” Assets – A case study from Norwegian Continental Shelf

    Get PDF
    This thesis examines the challenges and opportunities in managing "Breenfield" offshore energy assets during Mergers and Acquisitions in the Norwegian Continental Shelf (NCS). The study aims to analyze the dynamics of managing these assets based on existing standards, evaluate the challenges specific to the NCS, and explore methods to address these challenges during mergers and acquisitions. Key findings reveal that organizational aspects, personnel competence, and cultural differences are the primary challenges in the O&M context. Successful integration requires careful planning, consistent governance, standardization, and effective communication. Addressing personnel and organizational aspects, rather than relying solely on technology, is very important for a smooth transitioning. In addition, challenges include managing organizational changes, regulatory compliance, and harmonizing operational practices, necessitating effective communication, change management, and risk assessment. This research contributes to asset management by uncovering challenges and opportunities in managing "Breenfield" assets, filling a literature gap in offshore energy asset management during mergers and acquisitions. It also identifies best practices for future scenarios, promoting successful outcomes and a sustainable energy industry. Despite its contributions, this study has limitations, including limited relevant literature, a focus solely on the NCS offshore energy industry, confidentiality constraints, and a narrow focus on "Breenfield" assets. The research employed qualitative methods, including case study research, literature review, and report analysis. Overall, this thesis provides insights into managing "Breenfield" assets during offshore energy mergers and acquisitions. It aims to enhance asset management practices, improve efficiency, and facilitate successful integration in the energy sector, benefiting professionals, decision-makers, and future researchers

    A Business Model for IEM Plant Replication

    Get PDF
    This report is a circular economy business model for a 2000 tonne commercial intrusion extrusion moulding plant. It uses thin film waste plastic to produce durable products, with a lifespan up to 50 year

    Strawberry Production Guide For the Northeast, Midwest, and Eastern Canada 2nd Edition

    Get PDF
    This guide is intended as a comprehensive resource for both novice and experienced strawberry growers in northeastern North America. It provides information on all aspects of strawberry culture. The second edition has been updated and revised throughout, and includes expanded and new information on variety selection (Ch. 3), production systems (Ch. 4), harvesting, handling and transportation (Ch. 12), marketing (Ch. 13) and budgeting/economics (Ch. 14). In addition, a new section on diagnosing problems in strawberry plantings has been added (Ch. 15)
    corecore