The present study introduces distance based change detection (CD) algorithms in polarimetric synthetic aperture radar (PolSAR) data. PolSAR images, due to interactions between electromagnetic waves and target and beca...
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The present study introduces distance based change detection (CD) algorithms in polarimetric synthetic aperture radar (PolSAR) data. PolSAR images, due to interactions between electromagnetic waves and target and because of the high spatial resolution, can be used to study changes in the Earth's surface. The purpose of this paper is to use features extracted from the fully-polarimetry imaging radar that involved Yamaguchi four-component and H/A/ decomposition based on the distance between the vectors of features for CD. We first extract features from polarimetric decompositions of multi-looked covariance (or coherency) matrix data. We then use two well-known distance measures namely Canberra and Euclidean distances for measuring the similarity between the vectors of polarimetric decompositions at different times. Assessment of incorporated methods is performed using different criteria, such as overall accuracy, area under the receiver operating characteristic curve, and false alarms rate. The results of the experiments show that Canberra distance has better performance with high overall accuracy and low false alarm rate than Euclidean distance and other compared algorithms to detect changes.
Economic evaluation of healthcare treatment and services targeted at older people requires measurement of utility-based quality-of-life outcomes but it is not always possible to collect such outcome data. It may, howe...
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Economic evaluation of healthcare treatment and services targeted at older people requires measurement of utility-based quality-of-life outcomes but it is not always possible to collect such outcome data. It may, however, be possible to estimate these outcomes using non-utility measures of quality of life where the latter have been collected. The objective of this study was to develop a regression-based algorithm to map a non-utility-based outcome, the Older People's Quality of Life brief questionnaire (OPQoL-brief), onto a utility-based outcome, the EuroQoL 5 Dimensions 5 Levels (EQ-5D-5L). The estimation sample comprised 330 community-based Australian older people (> 65 years), while the validation sample consisted of 293 older people from a separate study. Six regression techniques were employed to estimate utilities from OPQoL-brief. The predictive accuracy of 54 regression models (six regression techniques x nine model specifications) was assessed using six criteria: mean absolute error (MAE), root mean squared error (RMSE), correlation, distribution of predicted utilities, distribution of residuals, and proportion of predictions with absolute errors < 0.05. The 54 regression models predicted EQ-5D-5L utilities that performed differently when assessed by the six criteria. However, best results were obtained from an ordinary least squares (OLS) model where all 13 OPQoL-brief items were included as continuous variables (OLS 4). RMSE and MAE estimates for this model (0.2201 and 0.1638, respectively) were within the range of published estimates. It is possible to predict valid utilities from OPQoL-brief using regression methods. We recommend OLS model (4) for this exercise.
BackgroundThere is increasing awareness of the clinical relevance of psoriasis comorbidities and of the importance of timely and effective screening for such comorbidities in the management of psoriatic patients. Prev...
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BackgroundThere is increasing awareness of the clinical relevance of psoriasis comorbidities and of the importance of timely and effective screening for such comorbidities in the management of psoriatic patients. Previous works have focused on assessing evidence for prevalence of comorbidities and on the best available evidence for sensitivity in diagnosing suspected comorbidities. No algorithms are available, which have been tested on large numbers of physicians concerning the acceptance of such algorithms both by practicing clinical dermatologists and by their consulting specialists from other fields. ObjectiveTo propose a multidimensional assessment algorithm for psoriasis comorbidities which may prove at the same time enough sensitive and practically sustainable in daily clinical practice. MethodsAfter an exhaustive literature search, we performed a Delphi procedure involving 50 dedicated dermatological centres to obtain a standardized assessment algorithm, which would meet requirements of sustainability and acceptability both from the point of view of Evidence-based Medicine as well as from the point of view of practical and clinical feasibility: to meet both requirements, results from the Delphi procedure were elaborated and modified by a restricted panel of experts. ResultsThe procedure has yielded PSOCUBE, a three-dimensional table comprising 14 clinical examination and history taking items, 32 screening laboratory and instrumental exams and 11 clinimetric scores. ConclusionPSOCUBE, a simple algorithm, may be employed by practising dermatologists to perform standardized assessment procedures on psoriatic patients raising the chances of early recognition of patients at risk for comorbidities, thus fostering more effective prevention;PSOCUBE may therefore contribute to reduce the overall impact of this chronic, widespread disease.
In this paper we consider the pair-wise sequence alignment problem with gaps, which is motivated by the re sequencing problem that requires to assemble short reads sequences into a genome sequence by referring to a re...
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ISBN:
(纸本)9781467365987
In this paper we consider the pair-wise sequence alignment problem with gaps, which is motivated by the re sequencing problem that requires to assemble short reads sequences into a genome sequence by referring to a reference sequence. The problem has been studied before for single gap and bounded number of gaps. For single gap, there was a GPU-based algorithm proposed. In our work we propose a GPU-based algorithm for the bounded number of gaps case. We implemented the algorithm and compare the performance with the CPU-based algorithm in a multithreadded environment;the results are promising with the GPU version achieving a speedup of 30 times.
Event processing is an important technology to detect what happened in the real world from a large amount of sensor data. This article is trying to find a suitable method for event processing with huge data. The autho...
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ISBN:
(纸本)9781479967261
Event processing is an important technology to detect what happened in the real world from a large amount of sensor data. This article is trying to find a suitable method for event processing with huge data. The authors formalize event processing as a problem of approximate string matching and evaluate the processing time of the two algorithms for the problem, the shift-add algorithm and the FFT-based algorithm. The shift-add algorithm is efficient for matching with a short string, however the processing time is proportional to the length of the string. On the other hand, the processing time of the FFT-based algorithm depends on the logarithm of the length of the string. Their experimental result with a common computer shows that the FFT-based algorithm is faster than the shift-add algorithm for a string longer than about 4,000.
OBJECTIVE To validate a claims-based algorithm for detecting severe rectal and urinary adverse effects (AEs) of radiotherapy (RT) to inform the design and interpretation of outcomes studies, using administrative datas...
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OBJECTIVE To validate a claims-based algorithm for detecting severe rectal and urinary adverse effects (AEs) of radiotherapy (RT) to inform the design and interpretation of outcomes studies, using administrative datasets to detect such RT AEs. METHODS An institutional billing analysis was performed to identify patients managed with RT for prostate or cervical cancer at the University of Minnesota, between 2000 and 2006. A priori, we identified Current Procedural Terminology procedural codes consistent with treatment for severe RT AEs. A retrospective chart review and a billing (ie "claims") analysis were performed to detect the procedures used to treat RT AEs. The accuracy of the claims-based algorithm was compared with chart review (the reference standard). RESULTS On chart review, 31 patients (7.6%) with severe rectal and urinary RT AEs were detected among 406 patients with nonmetastatic cancer at diagnosis. The most common AE was ureteral stenosis (25% of all AEs). The sensitivity and specificity of the claims-based analysis were 75% and 100% respectively for urethral stricture, 100% and 99% respectively for ureteral stricture, 60% and 100% respectively for radiation cystitis, 88% and 100% respectively for rectal or urinary fistula, and 88% and 100% respectively for radiation proctitis. CONCLUSION We demonstrated an excellent specificity and yet fairly good sensitivity of our claims-based algorithm for detecting treatment of urethral stricture, rectal or urinary fistulas, radiation proctitis, and ureteral stricture. These data might inform the design and interpretation of studies using claims-based methods for the detection of severe urinary AEs of pelvic RT. UROLOGY 82: 335-340, 2013. (C) 2013 Elsevier Inc.
We propose a distributed method to compute similarity (also known as kernel and Gram) matrices used in various kernel-based machine learning algorithms. Current methods for computing similarity matrices have quadratic...
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ISBN:
(纸本)9780769551449
We propose a distributed method to compute similarity (also known as kernel and Gram) matrices used in various kernel-based machine learning algorithms. Current methods for computing similarity matrices have quadratic time and space complexities, which make them not scalable to large-scale data sets. To reduce these quadratic complexities, the proposed method first partitions the data into smaller subsets using various families of locality sensitive hashing, including random project and spectral hashing. Then, the method computes the similarity values among points in the smaller subsets to result in approximated similarity matrices. We analytically show that the time and space complexities of the proposed method are subquadratic. We implemented the proposed method using the Message Passing Interface (MPI) framework and ran it on a cluster. Our results with real large-scale data sets show that the proposed method does not significantly impact the accuracy of the computed similarity matrices and it achieves substantial savings in running time and memory requirements.
In this paper, a fuzzy-based clustering algorithm with features extracted from partial discharge waveform for condition assessment of power cables has been presented. Since the nature of cable insulation assessment al...
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ISBN:
(纸本)9781467312523
In this paper, a fuzzy-based clustering algorithm with features extracted from partial discharge waveform for condition assessment of power cables has been presented. Since the nature of cable insulation assessment already has remained unsupervised, fuzzy clustering algorithms seem to be more applicable in this context. The decision making process has been designed based on static features which is capable of considering trend of results. Also, the measuring and operation conditions have been considered to present final judgment. The results have shown successful clustering of the insulation condition.
Callahan clarifies an important issue surrounding validation studies restricted to the review of cases having a particular coding algorithm to determine whether the condition represented by the codes truly exists. Dis...
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Callahan clarifies an important issue surrounding validation studies restricted to the review of cases having a particular coding algorithm to determine whether the condition represented by the codes truly exists. Disease prevalence in the population sampled for the validation is important.
In this paper, we discuss a nonadditive path costs traffic assignment problem considering emission effects. based on Venigalla's research, we put forward the traffic assignment model considering emissions at diffe...
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ISBN:
(纸本)9780769535623
In this paper, we discuss a nonadditive path costs traffic assignment problem considering emission effects. based on Venigalla's research, we put forward the traffic assignment model considering emissions at different engine operating modes. We also use two path-basedalgorithms, gradient projection (GP) algorithm and disaggregated simplicial decomposition (DSD) algorithm to solve the mathematic model respectively. Then, we apply the model as well as the algorithms into a real network and compare some computational characteristics of them. The results show that both GP and DSD algorithms have a rapid convergence speed than FW algorithm. The results also demonstrate that path-basedalgorithms can be widely used in solving large scale traffic assignment problem with nonadditive path costs.
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