119 resultados para Environmental Conditions


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Recent road safety statistics show that the decades-long fatalities decreasing trend is stopping and stagnating. Statistics further show that crashes are mostly driven by human error, compared to other factors such as environmental conditions and mechanical defects. Within human error, the dominant error source is perceptive errors, which represent about 50% of the total. The next two sources are interpretation and evaluation, which accounts together with perception for more than 75% of human error related crashes. Those statistics show that allowing drivers to perceive and understand their environment better, or supplement them when they are clearly at fault, is a solution to a good assessment of road risk, and, as a consequence, further decreasing fatalities. To answer this problem, currently deployed driving assistance systems combine more and more information from diverse sources (sensors) to enhance the driver's perception of their environment. However, because of inherent limitations in range and field of view, these systems' perception of their environment remains largely limited to a small interest zone around a single vehicle. Such limitations can be overcomed by increasing the interest zone through a cooperative process. Cooperative Systems (CS), a specific subset of Intelligent Transportation Systems (ITS), aim at compensating for local systems' limitations by associating embedded information technology and intervehicular communication technology (IVC). With CS, information sources are not limited to a single vehicle anymore. From this distribution arises the concept of extended or augmented perception. Augmented perception allows extending an actor's perceptive horizon beyond its "natural" limits not only by fusing information from multiple in-vehicle sensors but also information obtained from remote sensors. The end result of an augmented perception and data fusion chain is known as an augmented map. It is a repository where any relevant information about objects in the environment, and the environment itself, can be stored in a layered architecture. This thesis aims at demonstrating that augmented perception has better performance than noncooperative approaches, and that it can be used to successfully identify road risk. We found it was necessary to evaluate the performance of augmented perception, in order to obtain a better knowledge on their limitations. Indeed, while many promising results have already been obtained, the feasibility of building an augmented map from exchanged local perception information and, then, using this information beneficially for road users, has not been thoroughly assessed yet. The limitations of augmented perception, and underlying technologies, have not be thoroughly assessed yet. Most notably, many questions remain unanswered as to the IVC performance and their ability to deliver appropriate quality of service to support life-saving critical systems. This is especially true as the road environment is a complex, highly variable setting where many sources of imperfections and errors exist, not only limited to IVC. We provide at first a discussion on these limitations and a performance model built to incorporate them, created from empirical data collected on test tracks. Our results are more pessimistic than existing literature, suggesting IVC limitations have been underestimated. Then, we develop a new CS-applications simulation architecture. This architecture is used to obtain new results on the safety benefits of a cooperative safety application (EEBL), and then to support further study on augmented perception. At first, we confirm earlier results in terms of crashes numbers decrease, but raise doubts on benefits in terms of crashes' severity. In the next step, we implement an augmented perception architecture tasked with creating an augmented map. Our approach is aimed at providing a generalist architecture that can use many different types of sensors to create the map, and which is not limited to any specific application. The data association problem is tackled with an MHT approach based on the Belief Theory. Then, augmented and single-vehicle perceptions are compared in a reference driving scenario for risk assessment,taking into account the IVC limitations obtained earlier; we show their impact on the augmented map's performance. Our results show that augmented perception performs better than non-cooperative approaches, allowing to almost tripling the advance warning time before a crash. IVC limitations appear to have no significant effect on the previous performance, although this might be valid only for our specific scenario. Eventually, we propose a new approach using augmented perception to identify road risk through a surrogate: near-miss events. A CS-based approach is designed and validated to detect near-miss events, and then compared to a non-cooperative approach based on vehicles equiped with local sensors only. The cooperative approach shows a significant improvement in the number of events that can be detected, especially at the higher rates of system's deployment.

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Several fringing coral reefs in Moreton Bay, Southeast Queensland, some 300 km south of the Great Barrier Reef (GBR), are set in a relatively high latitude, estuarine environment that is considered marginal for coral growth. Previous work indicated that these marginal reefs, as with many fringing reefs of the inner GBR, ceased accreting in the mid-Holocene. This research presents for the first time data from the subsurface profile of the mid-Holocene fossil reef at Wellington Point comprising U/Th dates of in situ and framework corals, and trace element analysis from the age constrained carbonate fragments. Based on trace element proxies the palaeo-water quality during reef accretion was reconstructed. Results demonstrate that the reef initiated more than 7,000 yr BP during the post glacial transgression, and the initiation progressed to the west as sea level rose. In situ micro-atolls indicate that sea level was at least 1 m above present mean sea level by 6,680 years ago. The reef remained in "catch-up" mode, with a seaward sloping upper surface, until it stopped aggrading abruptly at ca 6,000 yr BP; no lateral progradation occurred. Changes in sediment composition encountered in the cores suggest that after the laterite substrate was covered by the reef, most of the sediment was produced by the carbonate factory with minimal terrigenous influence. Rare earth element, Y and Ba proxies indicate that water quality during reef accretion was similar to oceanic waters, considered suitable for coral growth. A slight decline in water quality on the basis of increased Ba in the later stages of growth may be related to increased riverine input and partial closing up of the bay due to either tidal delta progradation, climatic change and/or slight sea level fall. The age data suggest that termination of reef growth coincided with a slight lowering of sea level, activation of ENSO and consequent increase in seasonality, lowering of temperatures and the constrictions to oceanic flushing. At the cessation of reef accretion the environmental conditions in the western Moreton Bay were changing from open marine to estuarine. The living coral community appears to be similar to the fossil community, but without the branching Acropora spp. that were more common in the fossil reef. In this marginal setting coral growth periods do not always correspond to periods of reef accretion due to insufficient coral abundance. Due to several environmental constraints modern coral growth is insufficient for reef growth. Based on these findings Moreton Bay may be unsuitable as a long term coral refuge for most species currently living in the GBR.

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It is certain that there will be changes in environmental conditions across the globe as a result of climate change. Such changes will require the building of biological, human and infrastructure resilience. In some instances, the building of such resilience will be insufficient to deal with extreme changes in environmental conditions and legal frameworks will be required to provide recognition and support for people relocating as a result of environmental change. International legal frameworks do not currently recognise or assist people displaced as a result of environmental factors. The objective of this chapter is to examine the areas of international law relevant to displacement arising from environmental factors, consider some of the proposed climate displacement instruments and suggest the most suitable international institution to host a program addressing climate displacement. In order to determine the most appropriate institution to address and regulate climate displacement, it is imperative to consider issues of governance. This paper seeks to examine this issue and determine whether it is preferable to place climate displacement programs into existing international legal frameworks, or whether it is necessary to regulate this area in an entirely new institution specifically designed to deal with the complex and cross-cutting issues surrounding the topic...

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The Oceania region, which includes Australia, New Zealand, Papua New Guinea and the islands of the tropical Pacific Ocean, has historically been free from chikungunya. However, the 2011 outbreak in New Caledonia and the ongoing outbreak in Papua New Guinea have highlighted the risk to other communities in Oceania where there are competent mosquito vectors and permissive social factors and environmental conditions. In this article we discuss the threat to this region that is posed by the recent evolution of the E1:A226V mutant strains of chikungunya virus (CHIKV).

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Dementia is an irreversible and incurable syndrome that leads to progressive impairment of cognitive functions and behavioural and psychological symptoms such as agitation, depression and psychosis. Appropriate environmental conditions can help delay its onset and progression, and indoor environmental (IE) factors have a major impact. However, there is no firm understanding of the full range of relevant IE factors and their impact levels. This paper describes a preliminary study to investigate the effects of IE on Hong Kong residential care homes (RCH) dementia residents. This involved six purposively selected focus groups, each comprising the main stakeholders of the dementia residents’ caregivers, RCH staff and/or registered nurses, and architects. Using the Critical Incident Technique, the main context and experiences of behavioural problems of dementia residents caused by IE were explored and the key causal RCH IE quality factors identified, together with the associated responses and stress levels involved. The findings indicate that the acoustic environment, lighting and thermal environment are the most important influencing factors. Many of the remedies provided by the focus groups are quite simple to carry out and are summarised in the form of recommendations to current RCHs providers and users. The knowledge acquired in this initial study will help enrich the knowledge of IE design for dementiaspecific residential facilities. It also provides some preliminary insights for healthcare policymakers and practitioners in the building design/facilities management and dementia-care sectors into the IE factors contributing to a more comfortable, healthy and sustainable RCH living environment in Hong Kong.

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Current state of the art robot mapping and navigation systems produce impressive performance under a narrow range of robot platform, sensor and environmental conditions, in contrast to animals such as rats that produce “good enough” maps that enable them to function under an incredible range of situations. In this paper we present a rat-inspired featureless sensor-fusion system that assesses the usefulness of multiple sensor modalities based on their utility and coherence for place recognition, without knowledge as to the type of sensor. We demonstrate the system on a Pioneer robot in indoor and outdoor environments with abrupt lighting changes. Through dynamic weighting of the sensors, the system is able to perform correct place recognition and mapping where the static sensor weighting approach fails.

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Tubular members have become progressively more popular due to excellent structural properties, aesthetic appearance, corrosion and fire protection capability. However, a large number of such structures are found structurally deficient due to reduction of strength when they expose to severe environmental conditions such as marine environment, cold and hot weather. Hence strengthening and retrofitting of structural members are in high demands. In recent times Carbon Fibre Reinforced Polymers (CFRP) composites appears to be an excellent solution to enhance the load carrying capacity and serviceability of steel structures because of its superior physical and mechanical properties. However, the durability of such strengthening system under cold environmental condition has not yet been well documented to guide the engineers. This paper presents the findings of a study conducted to enhance the bond durability of CFRP strengthened steel tubular members by treating steel surface using epoxy based adhesion promoter under cold weather subjected to bending. The experimental program consisted of six number of CFRP strengthened specimens and one bare specimen. The sand blasted surface of the three specimens to be strengthened was pre-treated with MBrace primer and other three were remained untreated and then cured under ambient temperature and cold weather (3oC) for three and six months period of time. The beams were then loaded to failure under four point bending. The structural response of each specimen was predicted in terms of failure mode, failure load and mid-span deflection. The research findings show that the cold weather immersion had an adverse effect on durability of CFRP strengthened structures. Moreover, the epoxy based adhesion promoter was found to enhance the bond durability in elastic range.

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Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.

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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).

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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

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This document describes large, accurately calibrated and time-synchronised datasets, gathered in controlled environmental conditions, using an unmanned ground vehicle equipped with a wide variety of sensors. These sensors include: multiple laser scanners, a millimetre wave radar scanner, a colour camera and an infra-red camera. Full details of the sensors are given, as well as the calibration parameters needed to locate them with respect to each other and to the platform. This report also specifies the format and content of the data, and the conditions in which the data have been gathered. The data collection was made in two different situations of the vehicle: static and dynamic. The static tests consisted of sensing a fixed ’reference’ terrain, containing simple known objects, from a motionless vehicle. For the dynamic tests, data were acquired from a moving vehicle in various environments, mainly rural, including an open area, a semi-urban zone and a natural area with different types of vegetation. For both categories, data have been gathered in controlled environmental conditions, which included the presence of dust, smoke and rain. Most of the environments involved were static, except for a few specific datasets which involve the presence of a walking pedestrian. Finally, this document presents illustrations of the effects of adverse environmental conditions on sensor data, as a first step towards reliability and integrity in autonomous perceptual systems.

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This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated and propagated up to the projection of the laser points onto the image. Then, for each pair of laser scan-camera image acquired, the information at corners of the laser scan is compared with the content of the image, resulting in a likelihood of correspondence. The result of this process is then used to validate segments of the laser scan that are found to be consistent with the image, while inconsistent segments are rejected. Experimental results illustrate how this technique can improve the reliability of perception in challenging environmental conditions, such as in the presence of airborne dust.

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The vast majority of current robot mapping and navigation systems require specific well-characterized sensors that may require human-supervised calibration and are applicable only in one type of environment. Furthermore, if a sensor degrades in performance, either through damage to itself or changes in environmental conditions, the effect on the mapping system is usually catastrophic. In contrast, the natural world presents robust, reasonably well-characterized solutions to these problems. Using simple movement behaviors and neural learning mechanisms, rats calibrate their sensors for mapping and navigation in an incredibly diverse range of environments and then go on to adapt to sensor damage and changes in the environment over the course of their lifetimes. In this paper, we introduce similar movement-based autonomous calibration techniques that calibrate place recognition and self-motion processes as well as methods for online multisensor weighting and fusion. We present calibration and mapping results from multiple robot platforms and multisensory configurations in an office building, university campus, and forest. With moderate assumptions and almost no prior knowledge of the robot, sensor suite, or environment, the methods enable the bio-inspired RatSLAM system to generate topologically correct maps in the majority of experiments.

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Road networks are a national critical infrastructure. The road assets need to be monitored and maintained efficiently as their conditions deteriorate over time. The condition of one of such assets, road pavement, plays a major role in the road network maintenance programmes. Pavement conditions depend upon many factors such as pavement types, traffic and environmental conditions. This paper presents a data analytics case study for assessing the factors affecting the pavement deflection values measured by the traffic speed deflectometer (TSD) device. The analytics process includes acquisition and integration of data from multiple sources, data pre-processing, mining useful information from them and utilising data mining outputs for knowledge deployment. Data mining techniques are able to show how TSD outputs vary in different roads, traffic and environmental conditions. The generated data mining models map the TSD outputs to some classes and define correction factors for each class.

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Background and Aims Successful cryopreservation of bryophytes is linked to intrinsic desiccation tolerance and survival can be enhanced by pre-treatment with abscisic acid (ABA) and sucrose. The pioneer moss Ditrichum plumbicola is naturally subjected to desiccation in the field but showed unexpectedly low survival of cryopreservation, as well as a poor response to pre-treatment. The effects of the cryopreservation protocol on protonemata of D. plumbicola were investigated in order to explore possible relationships between the production in vitro of cryopreservation-tolerant asexual propagules and the reproductive biology of D. plumbicola in nature. Methods Protonemata were prepared for cryopreservation using a four-step protocol involving encapsulation in sodium alginate, pre-treatment for 2 weeks with ABA and sucrose, desiccation for 6 h and rapid freezing in liquid nitrogen. After each stage, protonemata were prepared for light and electron microscopy and growth on standard medium was monitored. Further samples were prepared for light and electron microscopy at intervals over a 24-h period following removal from liquid nitrogen and re-hydration. Key Results Pre-treatment with ABA and sucrose caused dramatic changes to the protonemata. Growth was arrested and propagules induced with pronounced morphological and cytological changes. Most cells died, but those that survived were characterized by thick, deeply pigmented walls, numerous small vacuoles and lipid droplets in their cytoplasm. Desiccation and cryopreservation elicited no dramatic cytological changes. Cells returned to their pre-dehydration and cryopreservation state within 2 h of re-hydration and/or removal from liquid nitrogen. Regeneration was normal once the ABA/sucrose stimulus was removed. Conclusions The ABA/sucrose pre-treatment induced the formation of highly desiccation- and cryopreservation-tolerant propagules from the protonemata of D. plumbicola. This parallels behaviour in the wild, where highly desiccation-tolerant rhizoids function as perennating organs allowing the moss to endure extreme environmental conditions. An involvement of endogenous ABA in the desiccation tolerance of D. plumbicola is suggested.