491 resultados para Detection, Optimisation, Assessment, Highway


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Meyerhofferite is a calcium hydrated borate mineral with ideal formula: CaB3O3(OH)5�H2O and occurs as white complex acicular to crude crystals with length up to �4 cm, in fibrous divergent, radiating aggregates or reticulated and is often found in sedimentary or lake-bed borate deposits. The Raman spectrum of meyerhofferite is dominated by intense sharp band at 880 cm�1 assigned to the symmetric stretching mode of trigonal boron. Broad Raman bands at 1046, 1110, 1135 and 1201 cm�1 are attributed to BOH in-plane bending modes. Raman bands in the 900–1000 cm�1 spectral region are assigned to the antisymmetric stretching of tetrahedral boron. Distinct OH stretching Raman bands are observed at 3400, 3483 and 3608 cm�1. The mineral meyerhofferite has a distinct Raman spectrum which is different from the spectrum of other borate minerals, making Raman spectroscopy a very useful tool for the detection of meyerhofferite in sedimentary and lake bed deposits.

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This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.

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Damage detection using modal properties is a widely accepted method. However, quantifying such damage using modal properties is still not well established. With this in mind, a research project is presently underway towards the development of a procedure to detect, locate and quantify damage in structural components using the variations in modal properties. A novel vibration based parameter called Vibration based Damage Index is introduced into the damage assessment procedure. This paper presents the early part of the research project which treats flexural members. The proposed procedure is validated using experimental data and/or theoretical techniques and illustrated through application. Outcomes of this research highlight the ability of the proposed procedure to successfully detect, locate and quantify damage in flexural structural components using the modal properties of the first few modes.

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Purpose Videokeratoscopy images can be used for the non-invasive assessment of the tear film. In this work the applicability of an image processing technique, textural-analysis, for the assessment of the tear film in Placido disc images has been investigated. Methods In the presence of tear film thinning/break-up, the reflected pattern from the videokeratoscope is disturbed in the region of tear film disruption. Thus, the Placido pattern carries information about the stability of the underlying tear film. By characterizing the pattern regularity, the tear film quality can be inferred. In this paper, a textural features approach is used to process the Placido images. This method provides a set of texture features from which an estimate of the tear film quality can be obtained. The method is tested for the detection of dry eye in a retrospective dataset from 34 subjects (22-normal and 12-dry eye), with measurements taken under suppressed blinking conditions. Results To assess the capability of each texture-feature to discriminate dry eye from normal subjects, the receiver operating curve (ROC) was calculated and the area under the curve (AUC), specificity and sensitivity extracted. For the different features examined, the AUC value ranged from 0.77 to 0.82, while the sensitivity typically showed values above 0.9 and the specificity showed values around 0.6. Overall, the estimated ROCs indicate that the proposed technique provides good discrimination performance. Conclusions Texture analysis of videokeratoscopy images is applicable to study tear film anomalies in dry eye subjects. The proposed technique appears to have demonstrated its clinical relevance and utility.

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Wastewater containing human sewage is often discharged with little or no treatment into the Antarctic marine environment. Faecal sterols (primarily coprostanol) in sediments have been used for assessment of human sewage contamination in this environment, but in situ production and indigenous faunal inputs can confound such determinations. Using gas chromatography with mass spectral detection profiles of both C27 and C29 sterols, potential sources of faecal sterols were examined in nearshore marine sediments, encompassing sites proximal and distal to the wastewater outfall at Davis Station. Faeces from indigenous seals and penguins were also examined. Faeces from several indigenous species contained significant quantities of coprostanol but not 24-ethylcoprostanol, which is present in human faeces. In situ coprostanol and 24-ethylcoprostanol production was identified by co-production of their respective epi isomers at sites remote from the wastewat er source and in high total organic matter sediments. A C 29 sterols-based polyphasic likelihood assessment matrix for human sewage contamination is presented, which distinguishes human from local fauna faecal inputs and in situ production in the Antarctic environment. Sewage contamination was detected up to 1.5 km from Davis Station.

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Aim The assessment of treatment plans is an important component in the education of radiation therapists. The establishment of a grade for a plan is currently based on subjective assessment of a range of criteria. The automation of assessment could provide a number of advantages including faster feedback, reduced chance of human error, and simpler aggregation of past results. Method A collection of treatments planned by a cohort of 27 second year radiation therapy students were selected for quantitative evaluation. Treatment sites included the bladder, cervix, larynx, parotid and prostate, although only the larynx plans had been assessed in detail. The plans were designed with the Pinnacle system and exported using the DICOM framework. Assessment criteria included beam arrangement optimisation, volume contouring, target dose coverage and homogeneity, and organ-at-risk sparing. The in-house Treatment and Dose Assessor (TADA) software1 was evaluated for suitability in assisting with the quantitative assessment of these plans. Dose volume data were exported in per-student and per-structure data tables, along with beam complexity metrics, dose volume histograms, and reports on naming conventions. Results The treatment plans were exported and processed using TADA, with the processing of all 27 plans for each treatment site taking less than two minutes. Naming conventions were successfully checked against a reference protocol. Significant variations between student plans were found. Correlation with assessment feedback was established for the larynx plans. Conclusion The data generated could be used to inform the selection of future assessment criteria, monitor student development, and provide useful feedback to the students. The provision of objective, quantitative evaluations of plan quality would be a valuable addition to not only radiotherapy education programmes but also for staff development and potentially credentialing methods. New functionality within TADA developed for this work could be applied clinically to, for example, evaluate protocol compliance.

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Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

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Background: It is important for nutrition intervention in malnourished patients to be guided by accurate evaluation and detection of small changes in the patient’s nutrition status over time. However, the current Subjective Global Assessment (SGA) is not able to detect changes in a short period of time. The aim of the study was to determine whether 7-point SGA is more time sensitive to nutrition changes than the conventional SGA. Methods: In this prospective study, 67 adult inpatients assessed as malnourished using both the 7-point SGA and conventional SGA were recruited. Each patient received nutrition intervention and was followed up post-discharge. Patients were reassessed using both tools at 1, 3 and 5 months from baseline assessment. Results: It took significantly shorter time to see a one-point change using 7-point SGA compared to conventional SGA (median: 1 month vs. 3 months, p = 0.002). The likelihood of at least a one-point change is 6.74 times greater in 7-point SGA compared to conventional SGA after controlling for age, gender and medical specialties (odds ratio = 6.74, 95% CI 2.88-15.80, p<0.001). Fifty-six percent of patients who had no change in SGA score had changes detected using 7-point SGA. The level of agreement was 100% (k = 1, p < 0.001) between 7-point SGA and 3-point SGA and 83% (k=0.726, p<0.001) between two blinded assessors for 7-point SGA. Conclusion: The 7-point SGA is more time sensitive in its response to nutrition changes than conventional SGA. It can be used to guide nutrition intervention for patients.

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Background The diagnosis of frailty is based on physical impairments and clinicians have indicated that early detection is one of the most effective methods for reducing the severity of physical frailty. Maybe, an alternative to the classical diagnosis could be the instrumentalization of classical functional testing, as Romberg test or Timed Get Up and Go Test. The aim of this study was (I) to measure and describe the magnitude of accelerometry values in the Romberg test in two groups of frail and non-frail elderly people through instrumentation with the iPhone 4®, (II) to analyse the performances and differences between the study groups, and (III) to analyse the performances and differences within study groups to characterise accelerometer responses to increasingly difficult challenges to balance. Methods This is a cross-sectional study of 18 subjects over 70 years old, 9 frail subjects and 9 non-frail subjects. The non-parametric Mann–Whitney U test was used for between-group comparisons in means values derived from different tasks. The Wilcoxon Signed-Rank test was used to analyse differences between different variants of the test in both independent study groups. Results The highest difference between groups was found in the accelerometer values with eyes closed and feet parallel: maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.01). Subjects with eyes open and feet parallel, greatest differences found between the groups were in the maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.001). With eyes closed and feet in tandem, the greatest differences found between the groups were in the minimum peak acceleration in the lateral axis (p < 0.01). Conclusions The accelerometer fitted in the iPhone 4® is able to study and analyse the kinematics of the Romberg test between frail and non-frail elderly people. In addition, the results indicate that the accelerometry values also were significantly different between the frail and non-frail groups, and that values from the accelerometer accelerometer increased as the test was made more complicated.

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The current research began from the starting point that what we are grappling with when we are dealing with violent extremists by and large is essentially ‘normal people’. What follows in this third major section of this research paper is the theoretical and conceptual search for making researchable the following question: ‘How do you assess someone who is normal?’

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Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

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A profluorescent nitroxide possessing an isoindoline nitroxide moiety linked to a perylene fluorophore was developed to monitor radical mediated degradation of melamine-formaldehyde crosslinked polyester coil coatings in an industry standard accelerated weathering tester. Trapping of polyester-derived radicals (most likely C-radicals) that are generated during polymer degradation leads to fluorescent closed-shell alkoxy amines, which was used to obtain time-dependent degradation profiles to assess the relative stability of different polyesters towards weathering. The nitroxide probe couples excellent thermal stability and satisfactory photostability with high sensitivity and enables detection of free radical damage in polyesters under conditions that mimic exposure to the environment on a time scale of hours rather than months or years required by other testing methods. There are indications that the profluorescent nitroxide undergoes partial photo-degradation in the absence of polymer-derived radicals. Unexpectedly, it was also found that UV-induced fragmentation of the NO–C bond in closed-shell alkoxy amines leads to regeneration of the profluorescent nitroxide and the respective C-radical. The maximum fluorescence intensity that could be achieved with a given probe concentration is therefore not only determined by the amount of polyester radicals formed during accelerated weathering, but also by the light-driven side reactions of the profluorescent nitroxide and the corresponding alkoxy amine radical trapping products. Studies to determine the optimum probe concentration in the polymer matrix revealed that aggregation and re-absorption effects lowered the fluorescence intensity at higher concentrations of the profluorescent nitroxide, but too low probe concentrations, where these effects would be avoided, were not sufficient to trap the amount of polyester radicals formed upon weathering. The optimized experimental conditions were used to assess the impact of temperature and UV irradiance on polymer degradation during accelerated weathering.

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Movement of tephritid flies underpins their survival, reproduction, and ability to establish in new areas and is thus of importance when designing effective management strategies. Much of the knowledge currently available on tephritid movement throughout landscapes comes from the use of direct or indirect methods that rely on the trapping of individuals. Here, we review published experimental designs and methods from mark-release-recapture (MRR) studies, as well as other methods, that have been used to estimate movement of the four major tephritid pest genera (Bactrocera, Ceratitis, Anastrepha, and Rhagoletis). In doing so, we aim to illustrate the theoretical and practical considerations needed to study tephritid movement. MRR studies make use of traps to directly estimate the distance that tephritid species can move within a generation and to evaluate the ecological and physiological factors that influence dispersal patterns. MRR studies, however, require careful planning to ensure that the results obtained are not biased by the methods employed, including marking methods, trap properties, trap spacing, and spatial extent of the trapping array. Despite these obstacles, MRR remains a powerful tool for determining tephritid movement, with data particularly required for understudied species that affect developing countries. To ensure that future MRR studies are successful, we suggest that site selection be carefully considered and sufficient resources be allocated to achieve optimal spacing and placement of traps in line with the stated aims of each study. An alternative to MRR is to make use of indirect methods for determining movement, or more correctly, gene flow, which have become widely available with the development of molecular tools. Key to these methods is the trapping and sequencing of a suitable number of individuals to represent the genetic diversity of the sampled population and investigate population structuring using nuclear genomic markers or non-recombinant mitochondrial DNA markers. Microsatellites are currently the preferred marker for detecting recent population displacement and provide genetic information that may be used in assignment tests for the direct determination of contemporary movement. Neither MRR nor molecular methods, however, are able to monitor fine-scale movements of individual flies. Recent developments in the miniaturization of electronics offer the tantalising possibility to track individual movements of insects using harmonic radar. Computer vision and radio frequency identification tags may also permit the tracking of fine-scale movements by tephritid flies by automated resampling, although these methods come with the same problems as traditional traps used in MRR studies. Although all methods described in this chapter have limitations, a better understanding of tephritid movement far outweighs the drawbacks of the individual methods because of the need for this information to manage tephritid populations.