984 resultados para geological mapping


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Mapped topographic features are important for understanding processes that sculpt the Earth’s surface. This paper presents maps that are the primary product of an exercise that brought together 27 researchers with an interest in landform mapping wherein the efficacy and causes of variation in mapping were tested using novel synthetic DEMs containing drumlins. The variation between interpreters (e.g. mapping philosophy, experience) and across the study region (e.g. woodland prevalence) opens these factors up to assessment. A priori known answers in the synthetics increase the number and strength of conclusions that may be drawn with respect to a traditional comparative study. Initial results suggest that overall detection rates are relatively low (34–40%), but reliability of mapping is higher (72–86%). The maps form a reference dataset.

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Future digital signal processing (DSP) systems must provide robustness on algorithm and application level to the presence of reliability issues that come along with corresponding implementations in modern semiconductor process technologies. In this paper, we address this issue by investigating the impact of unreliable memories on general DSP systems. In particular, we propose a novel framework to characterize the effects of unreliable memories, which enables us to devise novel methods to mitigate the associated performance loss. We propose to deploy specifically designed data representations, which have the capability of substantially improving the system reliability compared to that realized by conventional data representations used in digital integrated circuits, such as 2's-complement or sign-magnitude number formats. To demonstrate the efficacy of the proposed framework, we analyze the impact of unreliable memories on coded communication systems, and we show that the deployment of optimized data representations substantially improves the error-rate performance of such systems.

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Bias-induced oxygen ion dynamics underpins a broad spectrum of electroresistive and memristive phenomena in oxide materials. Although widely studied by device-level and local voltage-current spectroscopies, the relationship between electroresistive phenomena, local electrochemical behaviors, and microstructures remains elusive. Here, the interplay between history-dependent electronic transport and electrochemical phenomena in a NiO single crystalline thin film with a number of well-defined defect types is explored on the nanometer scale using an atomic force microscopy-based technique. A variety of electrochemically-active regions were observed and spatially resolved relationship between the electronic and electrochemical phenomena was revealed. The regions with pronounced electroresistive activity were further correlated with defects identified by scanning transmission electron microscopy. Using fully coupled mechanical-electrochemical modeling, we illustrate that the spatial distribution of strain plays an important role in electrochemical and electroresistive phenomena. These studies illustrate an approach for simultaneous mapping of the electronic and ionic transport on a single defective structure level such as dislocations or interfaces, and pave the way for creating libraries of defect-specific electrochemical responses.

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A technique for optimizing the efficiency of the sub-map method for large-scale simultaneous localization and mapping (SLAM) is proposed. It optimizes the benefits of the sub-map technique to improve the accuracy and consistency of an extended Kalman filter (EKF)-based SLAM. Error models were developed and engaged to investigate some of the outstanding issues in employing the sub-map technique in SLAM. Such issues include the size (distance) of an optimal sub-map, the acceptable error effect caused by the process noise covariance on the predictions and estimations made within a sub-map, when to terminate an existing sub-map and start a new one and the magnitude of the process noise covariance that could produce such an effect. Numerical results obtained from the study and an error-correcting process were engaged to optimize the accuracy and convergence of the Invariant Information Local Sub-map Filter previously proposed. Applying this technique to the EKF-based SLAM algorithm (a) reduces the computational burden of maintaining the global map estimates and (b) simplifies transformation complexities and data association ambiguities usually experienced in fusing sub-maps together. A Monte Carlo analysis of the system is presented as a means of demonstrating the consistency and efficacy of the proposed technique.

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Schools of nursing continuously strive to facilitate learning through student engagement and teaching strategies that encourage active learning. This paper reports on the successful use of mind mapping, an underutilised and underdeveloped strategy, to enhance teaching and learning in undergraduate nurse education (Spencer et al., 2013). Mind mapping or concept mapping has been defined in the literature as a visual representation of one’s thoughts and ideas (Abel and Freeze, 2006). It is characterised by colour, images and text in a graphical, nonlinear style. Mind maps promote the linking of concepts and capitalise on the brain’s natural aptitude for visual recognition to enhance learning and memory recall (Buzan, 2006). Traditional teaching strategies depend on linear processes, which in comparison lack engagement, associations and creativity (Spencer et al., 2013). Mind mapping was introduced to nursing students undertaking modules in ‘Dimensions of Care’ and ‘Care Delivery’ on year two of the nursing degree programme in Queen’s University Belfast. The aim of introducing mind mapping was to help students make the critical link between the pathophysiology of conditions studied and the provision of informed, safe and effective patient care, which had challenged previous student cohorts. Initially maps were instructor-made as described by Boley (2008), as a template for note taking during class and as a study aid. However, students rapidly embraced the strategy and started creating their own mind maps. Meaningful learning occurs when students engage with concepts and organise them independently in a way significant to them (Buzan, 2006). Students reported high levels of satisfaction to this teaching approach. This paper will present examples of the mind maps produced and explore how mind mapping can be further utilised within the undergraduate nursing curriculum.

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The mineral concentrations in cereals are important for human health, especially for individuals who consume a cereal subsistence diet. A number of elements, such as zinc, are required within the diet, while some elements are toxic to humans, for example arsenic. In this study we carry out genome-wide association (GWA) mapping of grain concentrations of arsenic, copper, molybdenum and zinc in brown rice using an established rice diversity panel of,300 accessions and 36.9 k single nucleotide polymorphisms (SNPs). The study was performed across five environments: one field site in Bangladesh, one in China and two in the US, with one of the US sites repeated over two years. GWA mapping on the whole dataset and on separate subpopulations of rice revealed a large number of loci significantly associated with variation in grain arsenic, copper, molybdenum and zinc. Seventeen of these loci were detected in data obtained from grain cultivated in more than one field location, and six co-localise with previously identified quantitative trait loci. Additionally, a number of candidate genes for the uptake or transport of these elements were located near significantly associated SNPs (within 200 kb, the estimated global linkage disequilibrium previously employed in this rice panel). This analysis highlights a number of genomic regions and candidate genes for further analysis as well as the challenges faced when mapping environmentally-variable traits in a highly genetically structured diversity panel.

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The mapping problem is inherent to digital musical instruments (DMIs), which require, at the very least, an association between physical gestures and digital synthesis algorithms to transform human bodily performance into sound. This article considers the DMI mapping problem in the context of the creation and performance of a heterogeneous computer chamber music piece, a trio for violin, biosensors, and computer. Our discussion situates the DMI mapping problem within the broader set of interdependent musical interaction issues that surfaced during the composition and rehearsal of the trio. Through descriptions of the development of the piece, development of the hardware and software interfaces, lessons learned through rehearsal, and self-reporting by the participants, the rich musical possibilities and technical challenges of the integration of digital musical instruments into computer chamber music are demonstrated.

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This paper presents a portable electrochemical instrument capable of real-time in situ detection and automatic identification of heavy metals. The instrument is equipped with an embedded Geographical Position System and is capable of storing the geographical position of the sample under test. Software has been developed to combine pollutant results with geographical position, in order to produce a cartographical presentation of the pollution of an area. The electrochemical instrument provides the facilities found in a traditional lab based instrument in a portable design for on-site measurements. The instrument is capable of detecting lead, cadmium, zinc, nickel, mercury, and copper with good sensitivity and precision. The system is reliable, easy to use, safe, and it may be used in a variety of situations to help environmental assessment and control.