999 resultados para RESOLUTION


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The thermal decomposition of natural ammonium oxalate known as oxammite has been studied using a combination of high resolution thermogravimetry coupled to an evolved gas mass spectrometer and Raman spectroscopy coupled to a thermal stage. Three mass loss steps were found at 57, 175 and 188°C attributed to dehydration, ammonia evolution and carbon dioxide evolution respectively. Raman spectroscopy shows two bands at 3235 and 3030 cm-1 attributed to the OH stretching vibrations and three bands at 2995, 2900 and 2879 cm-1, attributed to the NH vibrational modes. The thermal degradation of oxammite may be followed by the loss of intensity of these bands. No intensity remains in the OH stretching bands at 100°C and the NH stretching bands show no intensity at 200°C. Multiple CO symmetric stretching bands are observed at 1473, 1454, 1447 and 1431cm-1, suggesting that the mineral oxammite is composed of a mixture of chemicals including ammonium oxalate dihydrate, ammonium oxalate monohydrate and anhydrous ammonium oxalate.

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In Australia seven schemes (apart from the Superannuation Complaints Tribunal) provide alternative dispute resolution services for complaints brought by consumers against financial services industry members. Recently the Supreme Court of New South Wales held that the decisions of one scheme were amenable to judicial review at the suit of a financial services provider member and the Supreme Court of Victoria has since taken a similar approach. This article examines the juristic basis for such a challenge and contends that judicial review is not available, either at common law or under statutory provisions. This is particularly the case since Financial Industry Complaints Service Ltd v Deakin Financial Services Pty Ltd (2006) 157 FCR 229; 60 ACSR 372 decided that the jurisdiction of a scheme is derived from a contract made with its members. The article goes on to contend that the schemes are required to give procedural fairness and that equitable remedies are available if that duty is breached.

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Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

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With the increasing resolution of remote sensing images, road network can be displayed as continuous and homogeneity regions with a certain width rather than traditional thin lines. Therefore, road network extraction from large scale images refers to reliable road surface detection instead of road line extraction. In this paper, a novel automatic road network detection approach based on the combination of homogram segmentation and mathematical morphology is proposed, which includes three main steps: (i) the image is classified based on homogram segmentation to roughly identify the road network regions; (ii) the morphological opening and closing is employed to fill tiny holes and filter out small road branches; and (iii) the extracted road surface is further thinned by a thinning approach, pruned by a proposed method and finally simplified with Douglas-Peucker algorithm. Lastly, the results from some QuickBird images and aerial photos demonstrate the correctness and efficiency of the proposed process.

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Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

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The highly variable flagellin-encoding flaA gene has long been used for genotyping Campylobacter jejuni and Campylobacter coli. High-resolution melting (HRM) analysis is emerging as an efficient and robust method for discriminating DNA sequence variants. The objective of this study was to apply HRM analysis to flaA-based genotyping. The initial aim was to identify a suitable flaA fragment. It was found that the PCR primers commonly used to amplify the flaA short variable repeat (SVR) yielded a mixed PCR product unsuitable for HRM analysis. However, a PCR primer set composed of the upstream primer used to amplify the fragment used for flaA restriction fragment length polymorphism (RFLP) analysis and the downstream primer used for flaA SVR amplification generated a very pure PCR product, and this primer set was used for the remainder of the study. Eighty-seven C. jejuni and 15 C. coli isolates were analyzed by flaA HRM and also partial flaA sequencing. There were 47 flaA sequence variants, and all were resolved by HRM analysis. The isolates used had previously also been genotyped using single-nucleotide polymorphisms (SNPs), binary markers, CRISPR HRM, and flaA RFLP. flaAHRManalysis provided resolving power multiplicative to the SNPs, binary markers, and CRISPR HRM and largely concordant with the flaA RFLP. It was concluded that HRM analysis is a promising approach to genotyping based on highly variable genes.

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This paper firstly presents an extended ambiguity resolution model that deals with an ill-posed problem and constraints among the estimated parameters. In the extended model, the regularization criterion is used instead of the traditional least squares in order to estimate the float ambiguities better. The existing models can be derived from the general model. Secondly, the paper examines the existing ambiguity searching methods from four aspects: exclusion of nuisance integer candidates based on the available integer constraints; integer rounding; integer bootstrapping and integer least squares estimations. Finally, this paper systematically addresses the similarities and differences between the generalized TCAR and decorrelation methods from both theoretical and practical aspects.