DEVELOPMENT OF A TL-3 F-SHAPE TEMPORARY CONCRETE MEDIAN BARRIER

A temporary concrete median barrier (CMB) was designed and tested for compliance under the Test Level 3 (TL-3) guidelines specified in the Recommended Procedures for the Safety Performance Evaluation of Highway Features, National Cooperative Highway Research Program (NCHRP) Report No. 350. The barrier is built to the new metric standards and has a traditional pin and loop configuration for interconnection. The objective of this research project was to develop and evaluate a standardized, temporary concrete barrier design while addressing the concerns for safety, economy, structural integrity, constructability, ease of installation, and maintenance. The resulting F-shape barrier segment is 3,800-mm long, a length that reduced the number of connections while limiting the weight of the barriers to ease handling. Full-scale crash testing demonstrated several critical design features. First, the connections need to be tight initially as practicable to limit deformation and rotation of the barriers,. Secondly, the pin needs to restrain the longitudinal barrier forces. Full-scale compliance testing of the final design demonstrated that the barrier was capable of successfully redirecting the 2000-kg vehicle. The vehicle demonstrated significant roll after contact with the barrier, which is evidenced in a majority of other concrete barrier tests. This barrier provides economical work zone protection applicable in a variety of situations, where TL-3 test criteria is warranted

DEVELOPMENT OF A TL-3 F-SHAPE TEMPORARY CONCRETE MEDIAN BARRIER

A temporary concrete median barrier (CMB) was designed and tested for compliance under the Test Level 3 (TL-3) guidelines specified in the Recommended Procedures for the Safety Performance Evaluation of Highway Features, National Cooperative Highway Research Program (NCHRP) Report No. 350. The barrier is built to the new metric standards and has a traditional pin and loop configuration for interconnection. The objective of this research project was to develop and evaluate a standardized, temporary concrete barrier design while addressing the concerns for safety, economy, structural integrity, constructability, ease of installation, and maintenance. The resulting F-shape barrier segment is 3,800-mm long, a length that reduced the number of connections while limiting the weight of the barriers to ease handling. Full-scale crash testing demonstrated several critical design features. First, the connections need to be tight initially as practicable to limit deformation and rotation of the barriers,. Secondly, the pin needs to restrain the longitudinal barrier forces. Full-scale compliance testing of the final design demonstrated that the barrier was capable of successfully redirecting the 2000-kg vehicle. The vehicle demonstrated significant roll after contact with the barrier, which is evidenced in a majority of other concrete barrier tests. This barrier provides economical work zone protection applicable in a variety of situations, where TL-3 test criteria is warranted

Envisaging a global infrastructure to exploit the potential of digitised collections

Tens of millions of images from biological collections have become available online over the last two decades. In parallel, there has been a dramatic increase in the capabilities of image analysis technologies, especially those involving machine learning and computer vision. While image analysis has become mainstream in consumer applications, it is still used only on an artisanal basis in the biological collections community, largely because the image corpora are dispersed. Yet, there is massive untapped potential for novel applications and research if images of collection objects could be made accessible in a single corpus. In this paper, we make the case for infrastructure that could support image analysis of collection objects. We show that such infrastructure is entirely feasible and well worth investing in

A choice of persistent identifier schemes for the Distributed System of Scientific Collections (DiSSCo)

Persistent identifiers (PID) to identify digital representations of physical specimens in natural science collections (i.e., digital specimens) unambiguously and uniquely on the Internet are one of the mechanisms for digitally transforming collections-based science. Digital Specimen PIDs contribute to building and maintaining long-term community trust in the accuracy and authenticity of the scientific data to be managed and presented by the Distributed System of Scientific Collections (DiSSCo) research infrastructure planned in Europe to commence implementation in 2024. Not only are such PIDs valid over the very long timescales common in the heritage sector but they can also transcend changes in underlying technologies of their implementation. They are part of the mechanism for widening access to natural science collections. DiSSCo technical experts previously selected the Handle System as the choice to meet core PID requirements. Using a two-step approach, this options appraisal captures, characterises and analyses different alternative Handle-based PID schemes and the possible operational modes of use. In a first step a weighting and ranking the options has been applied followed by a structured qualitative assessment of social and technical compliance across several assessment dimensions: levels of scalability, community trust, persistence, governance, appropriateness of the scheme and suitability for future global adoption. The results are discussed in relation to branding, community perceptions and global context to determine a preferred PID scheme for DiSSCo that also has potential for adoption and acceptance globally. DiSSCo will adopt a ‘driven-by DOI’ persistent identifier (PID) scheme customised with natural sciences community characteristics. Establishing a new Registration Agency in collaboration with the International DOI Foundation is a practical way forward to support the FAIR (findable, accessible interoperable, reusable) data architecture of DiSSCo research infrastructure. This approach is compatible with the policies of the European Open Science Cloud (EOSC) and is aligned to existing practices across the global community of natural science collections

Digital Extended Specimens: Enabling an Extensible Network of Biodiversity Data Records as Integrated Digital Objects on the Internet

The early twenty-first century has witnessed massive expansions in availability and accessibility of digital data in virtually all domains of the biodiversity sciences. Led by an array of asynchronous digitization activities spanning ecological, environmental, climatological, and biological collections data, these initiatives have resulted in a plethora of mostly disconnected and siloed data, leaving to researchers the tedious and time-consuming manual task of finding and connecting them in usable ways, integrating them into coherent data sets, and making them interoperable. The focus to date has been on elevating analog and physical records to digital replicas in local databases prior to elevating them to ever-growing aggregations of essentially disconnected discipline-specific information. In the present article, we propose a new interconnected network of digital objects on the Internet—the Digital Extended Specimen (DES) network—that transcends existing aggregator technology, augments the DES with third-party data through machine algorithms, and provides a platform for more efficient research and robust interdisciplinary discovery

Phylogeography of harbour porpoise (Phocoena phocoena) in the Southeastern North Atlantic and in the Black sea explored by the analyses of nuclear and mitochondrial DNA

19th Annual Conference of the European Cetacean Society and associated workshop, April 2-7, 2005, La Rochelle, FranceIn recent years, a decline in harbour porpoise (Phocoena phocoena) populations in the North Atlantic has been reported and this has raised concern over population sustainabilityN

Earth observation for sustainable urban planning in developing countries: needs, trends, and future directions

Abstract: Cities are constantly changing and authorities face immense challenges in obtaining accurate and timely data to effectively manage urban areas. This is particularly problematic in the developing world where municipal records are often unavailable or not updated. Spaceborne earth observation (EO) has great potential for providing up-to-date spatial information about urban areas. This article reviews the application of EO for supporting urban planning. In particular, the article overviews case studies where EO was used to derive products and indicators required by urban planners. The review concludes that EO has sufficiently matured in recent years but that a shift from the current focus on purely science-driven EO applications to the provision of useful information for day-to-day decision-making and urban sustainability monitoring is clearly needed

Using mixed objects in the training of object-based image classifications

Image classification for thematic mapping is a very common application in remote sensing, which is sometimes realized through object-based image analysis. In these analyses, it is common for some of the objects to be mixed in their class composition and thus violate the commonly made assumption of object purity that is implicit in a conventional object-based image analysis. Mixed objects can be a problem throughout a classification analysis, but are particularly challenging in the training stage as they can result in degraded training statistics and act to reduce mapping accuracy. In this paper the potential of using mixed objects in training object-based image classifications is evaluated. Remotely sensed data were submitted to a series of segmentation analyses from which a range of under- to over-segmented outputs were intentionally produced. Training objects were then selected from the segmentation outputs, resulting in training data sets that varied in terms of size (i.e. number of objects) and proportion of mixed objects. These training data sets were then used with an artificial neural network and a generalized linear model, which can accommodate objects of mixed composition, to produce a series of land cover maps. The use of training statistics estimated based on both pure and mixed objects often increased classification accuracy by around 25% when compared with accuracies obtained from the use of only pure objects in training. So rather than the mixed objects being a problem, they can be an asset in classification and facilitate land cover mapping from remote sensing. It is, therefore, desirable to recognize the nature of the objects and possibly accommodate mixed objects directly in training. The results obtained here may also have implications for the common practice of seeking an optimal segmentation output, and also act to challenge the widespread view that object-based classification is superior to pixel-based classification