950 resultados para accuracy of estimation


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Introduction This investigation aimed to assess the consistency and accuracy of radiation therapists (RTs) performing cone beam computed tomography (CBCT) alignment to fiducial markers (FMs) (CBCTFM) and the soft tissue prostate (CBCTST). Methods Six patients receiving prostate radiation therapy underwent daily CBCTs. Manual alignment of CBCTFM and CBCTST was performed by three RTs. Inter-observer agreement was assessed using a modified Bland–Altman analysis for each alignment method. Clinically acceptable 95% limits of agreement with the mean (LoAmean) were defined as ±2.0 mm for CBCTFM and ±3.0 mm for CBCTST. Differences between CBCTST alignment and the observer-averaged CBCTFM (AvCBCTFM) alignment were analysed. Clinically acceptable 95% LoA were defined as ±3.0 mm for the comparison of CBCTST and AvCBCTFM. Results CBCTFM and CBCTST alignments were performed for 185 images. The CBCTFM 95% LoAmean were within ±2.0 mm in all planes. CBCTST 95% LoAmean were within ±3.0 mm in all planes. Comparison of CBCTST with AvCBCTFM resulted in 95% LoA of −4.9 to 2.6, −1.6 to 2.5 and −4.7 to 1.9 mm in the superior–inferior, left–right and anterior–posterior planes, respectively. Conclusions Significant differences were found between soft tissue alignment and the predicted FM position. FMs are useful in reducing inter-observer variability compared with soft tissue alignment. Consideration needs to be given to margin design when using soft tissue matching due to increased inter-observer variability. This study highlights some of the complexities of soft tissue guidance for prostate radiation therapy.

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This paper reports on the 2nd ShARe/CLEFeHealth evaluation lab which continues our evaluation resource building activities for the medical domain. In this lab we focus on patients' information needs as opposed to the more common campaign focus of the specialised information needs of physicians and other healthcare workers. The usage scenario of the lab is to ease patients and next-of-kins' ease in understanding eHealth information, in particular clinical reports. The 1st ShARe/CLEFeHealth evaluation lab was held in 2013. This lab consisted of three tasks. Task 1 focused on named entity recognition and normalization of disorders; Task 2 on normalization of acronyms/abbreviations; and Task 3 on information retrieval to address questions patients may have when reading clinical reports. This year's lab introduces a new challenge in Task 1 on visual-interactive search and exploration of eHealth data. Its aim is to help patients (or their next-of-kin) in readability issues related to their hospital discharge documents and related information search on the Internet. Task 2 then continues the information extraction work of the 2013 lab, specifically focusing on disorder attribute identification and normalization from clinical text. Finally, this year's Task 3 further extends the 2013 information retrieval task, by cleaning the 2013 document collection and introducing a new query generation method and multilingual queries. De-identified clinical reports used by the three tasks were from US intensive care and originated from the MIMIC II database. Other text documents for Tasks 1 and 3 were from the Internet and originated from the Khresmoi project. Task 2 annotations originated from the ShARe annotations. For Tasks 1 and 3, new annotations, queries, and relevance assessments were created. 50, 79, and 91 people registered their interest in Tasks 1, 2, and 3, respectively. 24 unique teams participated with 1, 10, and 14 teams in Tasks 1, 2 and 3, respectively. The teams were from Africa, Asia, Canada, Europe, and North America. The Task 1 submission, reviewed by 5 expert peers, related to the task evaluation category of Effective use of interaction and targeted the needs of both expert and novice users. The best system had an Accuracy of 0.868 in Task 2a, an F1-score of 0.576 in Task 2b, and Precision at 10 (P@10) of 0.756 in Task 3. The results demonstrate the substantial community interest and capabilities of these systems in making clinical reports easier to understand for patients. The organisers have made data and tools available for future research and development.

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Background Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction. Result We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram. Conclusions We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.

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Stormwater pollution is linked to stream ecosystem degradation. In predicting stormwater pollution, various types of modelling techniques are adopted. The accuracy of predictions provided by these models depends on the data quality, appropriate estimation of model parameters, and the validation undertaken. It is well understood that available water quality datasets in urban areas span only relatively short time scales unlike water quantity data, which limits the applicability of the developed models in engineering and ecological assessment of urban waterways. This paper presents the application of leave-one-out (LOO) and Monte Carlo cross validation (MCCV) procedures in a Monte Carlo framework for the validation and estimation of uncertainty associated with pollutant wash-off when models are developed using a limited dataset. It was found that the application of MCCV is likely to result in a more realistic measure of model coefficients than LOO. Most importantly, MCCV and LOO were found to be effective in model validation when dealing with a small sample size which hinders detailed model validation and can undermine the effectiveness of stormwater quality management strategies.

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Current design rules for the member capacities of cold-formed steel columns are based on the same non-dimensional strength curve for both fixed and pinned-ended columns at ambient temperature. This research has investigated the accuracy of using current ambient temperature design rules in Australia/New Zealand (AS/NZS 4600), American (AISI S100) and European (Eurocode 3 Part 1.3) standards in determining the flexural–torsional buckling capacities of cold-formed steel columns at uniform elevated temperatures using appropriately reduced mechanical properties. It was found that these design rules accurately predicted the member capacities of pin ended lipped channel columns undergoing flexural torsional buckling at elevated temperatures. However, for fixed ended columns with warping fixity undergoing flexural–torsional buckling, the current design rules significantly underestimated the column capacities as they disregard the beneficial effect of warping fixity. This paper has therefore recommended the use of improved design rules developed for ambient temperature conditions to predict the axial compression capacities of fixed ended columns subject to flexural–torsional buckling at elevated temperatures within AS/NZS 4600 and AISI S100 design provisions. The accuracy of the proposed fire design rules was verified using finite element analysis and test results of cold-formed lipped channel columns at elevated temperatures except for low strength steel columns with intermediate slenderness whose behaviour was influenced by the increased nonlinearity in the stress–strain curves at elevated temperatures. Further research is required to include these effects within AS/NZS 4600 and AISI S100 design rules. However, Eurocode 3 Part 1.3 design rules can be used for this purpose by using suitable buckling curves as recommended in this paper.

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Traditionally, the fire resistance rating of Light gauge steel frame (LSF) wall systems is based on approximate prescriptive methods developed using limited fire tests. These fire tests are conducted using standard fire time-temperature curve given in ISO 834. However, in recent times fire has become a major disaster in buildings due to the increase in fire loads as a result of modern furniture and lightweight construction, which make use of thermoplastics materials, synthetic foams and fabrics. Therefore a detailed research study into the performance of load bearing LSF wall systems under both standard and realistic design fires on one side was undertaken to develop improved fire design rules. This study included both full scale fire tests and numerical studies of eight different LSF wall systems conducted for both the standard fire curve and the recently developed realistic design fire curves. The use of previous fire design rules developed for LSF walls subjected to non-uniform elevated temperature distributions based on AISI design manual and Eurocode 3 Parts 1.2 and 1.3 was investigated first. New simplified fire design rules based on AS/NZS 4600, North American Specification and Eurocode 3 Part 1.3 were then proposed with suitable allowances for the interaction effects of compression and bending actions. The importance of considering thermal bowing, magnified thermal bowing and neutral axis shift in the fire design was also investigated and their effects were included. A spread sheet based design tool was developed based on the new design rules to predict the failure load ratio versus time and temperature curves for varying LSF wall configurations. The accuracy of the proposed design rules was verified using the fire test and finite element analysis results for various wall configurations, steel grades, thicknesses and load ratios under both standard and realistic design fire conditions. A simplified method was also proposed to predict the fire resistance rating of LSF walls based on two sets of equations developed for the load ratio-hot flange temperature and the time-temperature relationships. This paper presents the details of this study on LSF wall systems under fire conditions and the results.

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Cold-formed steel members are widely used in load bearing Light gauge steel frame (LSF) wall systems with plasterboard linings on both sides. However, these thin-walled steel sections heat up quickly and lose their strength under fire conditions despite the protection provided by plasterboards. Hence there is a need for simple fire design rules to predict their load capacities and fire resistance ratings. During fire events, the LSF wall studs are subjected to non-uniform temperature distributions that cause thermal bowing, neutral axis shift and magnification effects and thus resulting in a combined axial compression and bending action on the LSF wall studs. In this research a series of full scale fire tests was conducted first to evaluate the performance of LSF wall systems with eight different wall configurations under standard fire conditions. Finite element models of LSF walls were then developed, analysed under transient and steady state conditions, and validated using full scale fire tests. Using the results from fire tests and finite element analyses, a detailed investigation was undertaken into the prediction of axial compression strength and failure times of LSF wall studs in standard fires using the available fire design rules based on Australian, American and European standards. The results from both fire tests and finite element analyses were used to investigate the ability of these fire design rules to include the complex effects of non-uniform temperature distributions and their accuracy in predicting the axial compression strengths of wall studs and the failure times. Suitable modifications were then proposed to the fire design rules. This paper presents the details of this investigation into the accuracy of using currently available fire design rules of LSF walls and the results.

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Cold-formed steel members are often subject to axial compression loads in a range of applications. These thin-walled members can be subject to various types of buckling modes, including flexural-torsional buckling. Design standards provide guidelines for columns subject to flexural-torsional buckling modes at ambient temperature. However, there are no specific design guidelines for elevated temperature conditions. Hence extensive research efforts have gone into the many investigations addressing the flexural-torsional buckling behaviour of cold-formed steel columns at elevated temperatures.This research has reviewed the accuracy of the current design rules in AS/NZS 4600 and the North American Specification in determining the member capacities of cold-formed steel columns using the results from detailed finite element analyses and an experimental study of lipped channel columns. It was found that the current ambient temperature Australian and American design rules accurately predicted the member capacities of pin ended lipped channel columns undergoing flexural torsional buckling at elevated temperatures by simply using the appropriate elevated temperature mechanical properties. However, for fixed ended columns with warping fixity undergoing flexural-torsional buckling, it was found that the current design rules significantly underestimated the column capacities as they disregard the beneficial effect of warping fixity. This research has therefore proposed improved design rules and verified their accuracy using finite element analysis and test results of cold-formed lipped channel columns made of three cross-sections and five different steel grades and thicknesses. This paper presents the details of this research study and the results.

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Environmental monitoring has become increasingly important due to the significant impact of human activities and climate change on biodiversity. Environmental sound sources such as rain and insect vocalizations are a rich and underexploited source of information in environmental audio recordings. This paper is concerned with the classification of rain within acoustic sensor re-cordings. We present the novel application of a set of features for classifying environmental acoustics: acoustic entropy, the acoustic complexity index, spectral cover, and background noise. In order to improve the performance of the rain classification system we automatically classify segments of environmental recordings into the classes of heavy rain or non-rain. A decision tree classifier is experientially compared with other classifiers. The experimental results show that our system is effective in classifying segments of environmental audio recordings with an accuracy of 93% for the binary classification of heavy rain/non-rain.

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Purpose This study aims to test service providers’ ability to recognise non-verbal emotions in complaining customers of same and different cultures. Design/methodology/approach In a laboratory study, using a between-subjects experimental design (n = 153), we tested the accuracy of service providers’ perceptions of the emotional expressions of anger, fear, shame and happiness of customers from varying cultural backgrounds. After viewing video vignettes of customers complaining (with the audio removed), participants (in the role of service providers) assessed the emotional state of the customers portrayed in the video. Findings Service providers in culturally mismatched dyads were prone to misreading anger, happiness and shame expressed by dissatisfied customers. Happiness was misread in the displayed emotions of both dyads. Anger was recognisable in the Anglo customers but not Confucian Asian, while Anglo service providers misread both shame and happiness in Confucian Asian customers. Research limitations/implications The study was conducted in the laboratory and was based solely on participant’s perceptions of actors’ non-verbal facial expressions in a single encounter. Practical implications Given the level of ethnic differences in developed nations, a culturally sensitive workplace is needed to foster effective functioning of service employee teams. Ability to understand cultural display rules and to recognise and interpret emotions is an important skill for people working in direct contact with customers. Originality/value This research addresses the lack of empirical evidence for the recognition of customer emotions by service providers and the impact of cross-cultural differences.

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Head and neck squamous cell carcinoma (HNSCC) accounts for a bulk of the oral and laryngeal cancers, the majority (70%) of which are associated with smoking and excessive drinking, major known risk factors for the development of HNSCC. In contrast to reports that suggest an inverse relationship between smoking and global DNA CpG methylation, hypermethylation of promoters of a number of genes was detected in saliva collected from patients with HNSCC. Using a sensitive methylation-specific polymerase chain reaction (MSP) assay to determine specific methylation events in the promoters of RASSF1A, DAPK1, and p16 genes, we demonstrate that we can detect tumor presence with an overall accuracy of 81% in the DNA isolated from saliva of patients with HNSCC (n = 143) when compared with the DNA isolated from the saliva of healthy nonsmoker controls (n = 31). The specificity for this MSP panel was 87% and the sensitivity was 80%(with a Fisher exact test P < .0001). In addition, the test panel performed extremely well in the detection of the early stages of HNSCCs, with a sensitivity of 94% and a specificity of 87%, and a high. concordance value of 0.8, indicating an excellent overall agreement between the presence of HNSCC and a positive MSP panel result. In conclusion, we demonstrate that the promoter methylation of RASSF1A, DAPK1, and p16 MSP panel is useful in detecting hypermethylation events in a noninvasive manner in patients with HNSCC.

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This work deals with estimators for predicting when parametric roll resonance is going to occur in surface vessels. The roll angle of the vessel is modeled as a second-order linear oscillatory system with unknown parameters. Several algorithms are used to estimate the parameters and eigenvalues of the system based on data gathered experimentally on a 1:45 scale model of a tanker. Based on the estimated eigenvalues, the system predicts whether or not parametric roll occurred. A prediction accuracy of 100% is achieved for regular waves, and up to 87.5% for irregular waves.

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This paper presents a discussion on the use of MIMO and SISO techniques for identification of the radiation force terms in models for surface vessels. We compare and discuss two techniques recently proposed in literature for this application: time domain identification and frequency domain identification. We compare the methods in terms of estimates model order, accuracy of the fit, use of the available information, and ease of use and implementation.

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Fine-grained leaf classification has concentrated on the use of traditional shape and statistical features to classify ideal images. In this paper we evaluate the effectiveness of traditional hand-crafted features and propose the use of deep convolutional neural network (ConvNet) features. We introduce a range of condition variations to explore the robustness of these features, including: translation, scaling, rotation, shading and occlusion. Evaluations on the Flavia dataset demonstrate that in ideal imaging conditions, combining traditional and ConvNet features yields state-of-theart performance with an average accuracy of 97:3%�0:6% compared to traditional features which obtain an average accuracy of 91:2%�1:6%. Further experiments show that this combined classification approach consistently outperforms the best set of traditional features by an average of 5:7% for all of the evaluated condition variations.

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BACKGROUND Early detection by skin self-examination (SSE) could improve outcomes from melanoma. Mobile teledermoscopy may aid this process. OBJECTIVES To establish clinical accuracy of SSE plus mobile teledermoscopy compared to clinical skin examination (CSE) and test whether providing people with detailed SSE instructions improves accuracy. METHODS Men and women 50-64 years (n=58) performed SSE plus mobile teledermoscopy in their homes between May and November 2013 and were given technical instructions plus detailed SSE instructions (intervention) or technical instructions only (control). Within three months, they underwent a CSE. Outcome measures included: a) body sites examined, lesions photographed, and missed; b) sensitivityof SSE plus mobile teledermoscopy compared to in-person CSE using either patients or lesions as denominator, and; c) concordance of telediagnosis with CSE. RESULTS: 49 of 58 randomised participants completed the study, and submitted 309 lesions to the teledermatologist (156 intervention; 153 control group). Intervention group participants were more likely to submit lesions from their legs compared to control (p=0.03), no other differences between groups in number or site of missed lesions.11 participants (22%) did not photograph 14 pigmented lesions the dermatologist considered worthwhile photographing or requiring clinical monitoring. Sensitivity of SSE plus mobile teledermoscopy was 81.8% (95% confidence interval 64.5-93.0) using the patient as the denominator and 41.9 (27.6-56.2) using the lesion as denominator.-There was substantial agreement between telediagnosis and CSE (Kappa =0.90) accounting for differential diagnoses. CONCLUSIONS SSE plus mobile teledermoscopy is promising for surveillance of particular lesions even without provision of detailed SSE instructions, but in the format tested in this study, consumers may overlook lesions and send many non-pigmented lesions. This investigation demonstrates that high quality dermoscopic images can be taken by patients at home and for those sent, telediagnosis is highly accurate.