Quality Measures

Interlinking text documents with Linked Open Data enables the Web of Data to be used as background knowledge within document-oriented applications such as search and faceted browsing. As a step towards interconnecting the Web of Documents with the Web of Data, we developed DBpedia Spotlight, a system for automatically annotating text documents with DBpedia URIs. DBpedia Spotlight allows users to configure the annotations to their specific needs through the DBpedia Ontology and quality measures such as prominence, topical pertinence, contextual ambiguity and disambiguation confidence. We compare our approach with the state of the art in disambiguation, and evaluate our results in light of three baselines and six publicly available annotation systems, demonstrating the competitiveness of our system. DBpedia Spotlight is shared as open source and deployed as a Web Service freely available for public use.

Human observers can easily assess the quality of a distorted image without examining the original image as a reference. By contrast, designing objective No-Reference (NR) quality measurement algorithms is a very difficult task. Currently, NR quality assessment is feasible only when prior knowledge about the types of image distortion is available.

AbstractÐThe dearth of published empirical data on major industrial systems has been one of the reasons that software engineering has failed to establish a proper scientific basis. In this paper, we hope to provide a small contribution to the body of empirical knowledge. We describe a number of results from a quantitative study of faults and failures in two releases of a major commercial system. We tested a range of basic software engineering hypotheses relating to: The Pareto principle of distribution of faults and failures; the use of early fault data to predict later fault and failure data; metrics for fault prediction; and benchmarking fault data. For example, we found strong evidence that a small number of modules contain most of the faults discovered in prerelease testing and that a very small number of modules contain most of the faults discovered in operation. However, in neither case is this explained by the size or complexity of the modules. We found no evidence to support previous claims relating module size to fault density nor did we find evidence that popular complexity metrics are good predictors of either fault-prone or failure-prone modules. We confirmed that the number of faults discovered in prerelease testing is an order of magnitude greater than the number discovered in 12 months of operational use. We also discovered fairly stable numbers of faults discovered at corresponding testing phases. Our most surprising and important result was strong evidence of a counter-intuitive relationship between pre-and postrelease faults: Those modules which are the most fault-prone prerelease are among the least fault-prone postrelease, while conversely, the modules which are most faultprone postrelease are among the least fault-prone prerelease. This observation has serious ramifications for the commonly used fault density measure. Not only is it misleading to use it as a surrogate quality measure, but, its previous extensive use in metrics studies is shown to be flawed. Our results provide data-points in building up an empirical picture of the software development process. However, even the strong results we have observed are not generally valid as software engineering laws because they fail to take account of basic explanatory data, notably testing effort and operational usage. After all, a module which has not been tested or used will reveal no faults, irrespective of its size, complexity, or any other factor.

We report the discovery of six new substellar companions of main-sequence stars, detected through multiple Doppler measurements with the instrument HARPS installed on the ESO 3.6m telescope, La Silla, Chile. These extrasolar planets are orbiting the stars BD -17 0063, HD 20868, HD 73267, HD 131664, HD 145377, HD 153950. The orbital characteristics which best fit the observed data are depicted in this paper, as well as the stellar and planetary parameters. Masses of the companions range from 2 to 18 Jupiter masses, and periods range from 100 to 2000 days. The observational data are carefully analysed for activity-induced effects and we conclude on the reliability of the observed radial-velocity variations as of exoplanetary origin. Of particular interest is the very massive planet (or brown-dwarf companion) around the metal-rich HD 131664 with M2sini= 18.15 MJup, and a 5.34-year orbital period. These new discoveries reinforces the observed statistical properties of the exoplanet sample as known so far.

The first goal of this paper is to empirically explore the relationships between existing object-oriented coupling, cohesion, and inheritance measures and the probability of fault detection in system classes during testing. In other words, we wish to better understand the relationship between existing design measurement in OO systems and the quality of the software developed. The second goal is to propose an investigation and analysis strategy to make these kind of studies more repeatable and comparable, a problem which is pervasive in the literature on quality measurement. Results show that many of the measures capture similar dimensions in the data set, thus reflecting the fact that many of them are based on similar principles and hypotheses. However, it is shown that by using a subset of measures, accurate models can be built to predict which classes contain most of the existing faults. When predicting fault-prone classes, the best model shows a percentage of correct classifications higher than 80% and finds more than 90% of faulty classes. Besides the size of classes, the frequency of method invocations and the depth of inheritance hierarchies seem to be the main driving factors of fault proneness.

The ongoing increase of energy consumption by IT infrastructures forces data center managers to find innovative ways to improve energy efficiency. The latter is also a focal point for different branches of computer science due to its financial, ecological, political, and technical consequences. One of the answers is given by scheduling combined with dynamic voltage scaling technique to optimize the energy consumption. The way of reasoning is based on the link between current semiconductor technologies and energy state management of processors, where sacrificing the performance can save energy. This paper is devoted to investigate and solve the multi-objective precedence constrained application scheduling problem on a distributed computing system, and it has two main aims: the creation of general algorithms to solve the problem and the examination of the problem by means of the thorough analysis of the results returned by the algorithms.

The resolution value claimed for an electron microscopical three-dimensional reconstruction indicates the overall quality of the experiment. The Fourier shell correlation (FSC) criterion has now become the standard quality measure. However, what has continued to be controversial is the issue of the FSC threshold level at which one defines the reproducible resolution. Here, we discuss the theoretical behaviour of the FSC in conjunction with the various factors which influence it: the number of ''voxels'' in a given Fourier shell, the symmetry of the structure, and the size of the structure within the reconstruction volume. Both the theoretical considerations and our model experiments show that fixed-valued FSC threshold (like ''0.5'') may never be used in a reproducible criterion. Fixed threshold values are-as we show here-simply the result of incorrect assumptions in the basic statistics. Two families of FSC threshold curves are discussed: the r-factor curves and the new family of bit-based information threshold curves. Whereas r-factor curves indicate the resolution level at which one has collected information significantly above the noise level, the information curves indicate the resolution level at which enough information has been collected for interpretation.

This paper examines the implications of using the absolute value of discretionary accruals when testing for earnings management. First, we analytically develop the mean and variance of the distribution of absolute discretionary accruals, and show that the expected value is an increasing function of the variance in the underlying error term from the first-stage discretionary accrual estimation model. Second, we highlight several firm characteristics that are related to the error variance in discretionary accrual estimation models. Using simulations, we show that correlation between the earnings management partitioning variable and these firm characteristics leads to an overrejection of the null hypothesis of no earnings management. Third, we provide research design suggestions to help researchers mitigate the potential bias arising from the use of unsigned measures of earnings management. Using these suggestions, we replicate a recent study, and demonstrate that the inferences change after controlling for operating volatility.

The popularity of wireless networks has increased in recent years and is becoming a common addition to LANs. In this paper we investigate a novel use for a wireless network based on the IEEE 802.11 standard: inferring the location of a wireless client from signal quality measures. Similar work has been limited to prototype systems that rely on nearest-neighbor techniques to infer location. In this paper, we describe Nibble, a Wi-Fi location service that uses Bayesian networks to infer the location of a device. We explain the general theory behind the system and how to use the system, along with describing our experiences at a university campus building and at a research lab. We also discuss how probabilistic modeling can be applied to a diverse range of applications that use sensor data.

We present a new approach for localizing electromagnetic sources using sensors where the output of each is a vector consisting of the complete six electric and magnetic field components. Two types of source transmissions are considered: 1) single signal transmission (SST), and 2) dual signal transmission (DST). The model is given in terms of several parameters, including the wave direction of arrival (DOA) and state of polarization. A compact expression is derived for the Cramer-Rao bound (CRB) on the estimation errors of these parameters for the multisource multi-vector-sensor model. Quality measures including mean-square angular error (MSAE) and covariance of vector angular error (CVAE) are introduced, and their lower bounds are derived. The advantage of using vector sensors is highlighted by explicit evaluation of the MSAE and CVAE bounds for source localization with a single vector sensor. A simple algorithm for estimating the source DOA with this sensor is presented along with its statistical performance analysis.

The quality measures used in information retrieval are particularly difficult to optimize directly, since they depend on the model scores only through the sorted order of the documents returned for a given query. Thus, the derivatives of the cost with respect to the model parameters are either zero, or are undefined. In this paper, we propose a class of simple, flexible algorithms, called LambdaRank, which avoids these difficulties by working with implicit cost functions. We describe LambdaRank using neural network models, although the idea applies to any differentiable function class. We give necessary and sufficient conditions for the resulting implicit cost function to be convex, and we show that the general method has a simple mechanical interpretation. We demonstrate significantly improved accuracy, over a state-of-the-art ranking algorithm, on several datasets. We also show that LambdaRank provides a method for significantly speeding up the training phase of that ranking algorithm. Although this paper is directed towards ranking, the proposed method can be extended to any non-smooth and multivariate cost functions.

Modular structure is ubiquitous in real-world complex networks, and its detection is important because it gives insights in the structure-functionality relationship. The standard approach is based on the optimization of a quality function, modularity, which is a relative quality measure for a partition of a network into modules. Recently some authors have pointed out that the optimization of modularity has a fundamental drawback: the existence of a resolution limit beyond which no modular structure can be detected even though these modules might have own entity. The reason is that several topological descriptions of the network coexist at different scales, which is, in general, a fingerprint of complex systems. Here we propose a method that allows for multiple resolution screening of the modular structure. The method has been validated using synthetic networks, discovering the predefined structures at all scales. Its application to two real social networks allows to find the exact splits reported in the literature, as well as the substructure beyond the actual split.

Standard ranges of atomic and residue volumes are computed in 64 highly resolved and well-refined protein crystal structures using the classical Macromolécules Biologiques Université Libre de Bruxelles Voronoi procedure. Deviations of the atomic volumes from the standard Av. F. Roosevelt 50

phospholipid fatty acid (PLFA) analysis was used in clear-cut, wood-ash fertilized (amounts applied: 1000, 2500, and 5000 kg ha-'), or prescribed burned (both in standing and clear-cut) coniferous forests to study the effects of treatments on microbial biomass and community structure. The microbial biomass (total PLFAs) decreased significantly due to the highest rate of wood-ash fertilization, clear-cutting, and the two different fire treatments when compared to control amounts. Fungi appeared more seriously reduced by these treatments than bacteria, as revealed by a decreased index of fungal: bactexial PLFAs when compared to the controls. The community structure was evaluated using the PLFA pattern. The largest treatment effect was due to burning in both areas studied, which resulted in increases in 16: 105 and proportional decreases in 18:206. Clear-cutting and the different amounts of ash application resulted in similar changes in the PLFA pattern to the burning treatments, but these were less pro.nounced. Attempts to correlate the changes in the PLFA pattern to soil pH, bacterial pH response patterns (measured using thymidine incorporation), or substrate quality (measured using IR spectroscopy) were only partly successful. Instead, we hypothesize that the changes in the PLFA pattern of the soil organisms were related to an altered substrate quantity, that is the availability of substrates after the treatments.

In this paper we examine the causal impact of competition on management quality. We analyze the hospital sector where geographic proximity is a key determinant of competition, and English public hospitals where political competition can be used to construct instrumental variables for market structure. Since almost all major English hospitals are government run, closing hospitals in areas where the governing

Progress in optical networking has stimulated interest in optical performance monitoring (OPM), particularly regarding signal quality measures such as optical signal-to-noise ratio (SNR), Q-factor, and dispersion. These advanced monitoring methods have the potential to extend fault management and quality-of-service (QoS) monitoring into the optical domain. This paper reviews OPM applications and techniques, while examining the role of OPM as an enabling technology for advances in high-speed and optically switched networks.

In this paper, a new distortion measure for electrocardiogram (ECG) signal compression, called weighted diagnostic distortion (WDD) is introduced. The WDD measure is designed for comparing the distortion between original ECG signal and reconstructed ECG signal (after compression). The WDD is based on PQRST complex diagnostic features (such as P wave duration, QT interval, T shape, ST elevation) of the original ECG signal and the reconstructed one. Unlike other conventional distortion measures [e.g. percentage root mean square (rms) difference, or PRD], the WDD contains direct diagnostic information and thus is more meaningful and useful.

The goal of this paper is to report on the SERVQUAL gap which causes unsuccessful service delivery at a University of Technology in South Africa. Using a quantitative research design, the study adopts a SERVQUAL model adapted to a tertiary environment containing five dimensions of service quality (tangibles, responsiveness, empathy, assurance, and reliability). A convenience sampling technique was applied, the data were collected from 280 respondents at the Durban University of Technology (DUT), and the results and discussion are presented. The findings reveal that, on average, customers had high expectations in tangibles, reliability, and assurance dimensions and their highest perceptions were found in the assurance dimension. This study will benefit management of higher education institutions in identifying cost-effective ways of reducing service quality gaps.

We propose a technique for fusing a bracketed exposure sequence into a high quality image, without converting to HDR first. Skipping the physically-based HDR assembly step simplifies the acquisition pipeline. This avoids camera response curve calibration and is computationally efficient. It also allows for including flash images in the sequence. Our technique blends multiple exposures, guided by simple quality measures like saturation and contrast. This is done in a multiresolution fashion to account for the brightness variation in the sequence. The resulting image quality is comparable to existing tone mapping operators.

BACKGROUND After acute myocardial infarction (AMI), treatment with beta-blockers and angiotensin-converting enzyme inhibitors (ACEI) is widely recognized as crucial to reduce risk of a subsequent AMI. However, many patients fail to consistently remain on these treatments over time, and long-term adherence has not been well described. OBJECTIVE To examine the duration of treatment with beta-blockers and ACEI within the 24 months after an AMI. DESIGN A retrospective, observational study using medical and pharmacy claims from a large health plan operating in the Northeastern United States. SUBJECTS Enrollees with an inpatient claim for AMI who initiated beta-blocker (N = 499) or ACEI (N = 526) therapy. MEASUREMENT Time from initiation to discontinuation was measured with pharmacy refill records. Associations between therapy discontinuation and potential predictors were estimated using a Cox proportional hazards model. RESULTS ACEI discontinuation rates were high: 7% stopped within 1 month, 22% at 6 months, 32% at 1 year and 50% at 2 years. Overall discontinuation rates for beta-blockers were similar, but predictors of discontinuation differed for the two treatment types. For beta-blockers, the risk of discontinuation was highest among males and those from low-income neighborhoods; patients with comorbid hypertension and peripheral vascular disease were less likely to discontinue therapy. These factors were not associated with ACEI discontinuation. CONCLUSION Many patients initiating evidence-based secondary prevention therapies after an AMI fail to consistently remain on these treatments. Adherence is a priority area for development of better-quality measures and quality-improvement interventions. Barriers to beta-blocker adherence for low-income populations need particular attention.

Improving the quality of an organization's products and services is fundamental to business success. The once-held view that product or service specification is static and readily achievable is gone. Managers in world-class companies realize that customer wants and desires are changing, that customers' expectations must be clearly understood, and that their firm must conform to customer wishes. This customer focus requires continual quality improvement, creating a dynamic business situation.

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Objective To compare quality of care in for-profit and notfor-profit nursing homes. Design Systematic review and meta-analysis of observational studies and randomised controlled trials investigating quality of care in for-profit versus not-forprofit nursing homes. Results A comprehensive search yielded 8827 citations, of which 956 were judged appropriate for full text review. Study characteristics and results of 82 articles that met inclusion criteria were summarised, and results for the four most frequently reported quality measures were pooled. Included studies reported results dating from 1965 to 2003. In 40 studies, all statistically significant comparisons (P<0.05) favoured not-for-profit facilities; in three studies, all statistically significant comparisons favoured for-profit facilities, and the remaining studies had less consistent findings. Meta-analyses suggested that not-for-profit facilities delivered higher quality care than did for-profit facilities for two of the four most frequently reported quality measures: more or higher quality staffing (ratio of effect 1.11, 95% confidence interval 1.07 to 1.14, P<0.001) and lower pressure ulcer prevalence (odds ratio 0.91, 95% confidence interval 0.83 to 0.98, P=0.02). Non-significant results favouring not-for-profit homes were found for the two other most frequently used measures: physical restraint use (odds ratio 0.93, 0.82 to 1.05, P=0.25) and fewer deficiencies in governmental regulatory assessments (ratio of effect 0.90, 0.78 to 1.04, P=0.17). Conclusions This systematic review and meta-analysis of the evidence suggests that, on average, not-for-profit nursing homes deliver higher quality care than do for-profit nursing homes. Many factors may, however, influence this relation in the case of individual institutions.

Obtaining high-quality measurements close to a large earthquake is not easy: one has to be in the right place at the right time with the right instruments. Such a convergence happened, for the first time, when the 28 September 2004 Parkfield, California, earthquake occurred on the San Andreas fault in the middle of a dense network of instruments designed to record it. The resulting data reveal aspects of the earthquake process never before seen. Here we show what these data, when combined with data from earlier Parkfield earthquakes, tell us about earthquake physics and earthquake prediction. The 2004 Parkfield earthquake, with its lack of obvious precursors, demonstrates that reliable short-term earthquake prediction still is not achievable. To reduce the societal impact of earthquakes now, we should focus on developing the next generation of models that can provide better predictions of the strength and location of damaging ground shaking.

Proponents of open source style software development claim that better software is produced using this model compared with the traditional closed model. However, there is little empirical evidence in support of these claims. In this paper, we present the results of a pilot case study aiming: (a) to understand the implications of structural quality; and (b) to figure out the benefits of structural quality analysis of the code delivered by open source style development. To this end, we have measured quality characteristics of 100 applications written for Linux, using a software measurement tool, and compared the results with the industrial standard that is proposed by the tool. Another target of this case study was to investigate the issue of modularity in open source as this characteristic is being considered crucial by the proponents of open source for this type of software development. We have empirically assessed the relationship between the size of the application components and the delivered quality measured through user satisfaction. We have determined that, up to a certain extent, the average component size of an application is negatively related to the user satisfaction for this application.

Most quality indicators for colonoscopy measure processes; little is known about their relationship to patient outcomes. We investigated whether characteristics of endoscopists, determined from administrative data, are associated with development of postcolonoscopy colorectal cancer (PCCRC). We identified individuals diagnosed with colorectal cancer in Ontario from 2000 to 2005 using the Ontario Cancer Registry. We determined performance of colonoscopy using Ontario Health Insurance Plan data. Patients who had complete colonoscopies 7 to 36 months before diagnosis were defined as having a PCCRC. Patients who had complete colonoscopies within 6 months of diagnosis had detected cancers. We determined if endoscopist factors (volume, polypectomy and completion rate, specialization, and setting) were associated with PCCRC using logistic regression, controlling for potential covariates. In the study, 14,064 patients had a colonoscopy examination within 36 months of diagnosis; 584 (6.8%) with distal and 676 (12.4%) with proximal tumors had PCCRC. The endoscopist&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s specialty (nongastroenterologist/nongeneral surgeon) and setting (non-hospital-based colonoscopy) were associated with PCCRC. Those who underwent colonoscopy by an endoscopist with a high completion rate were less likely to have a PCCRC (distal: odds ratio [OR], 0.73; 95% confidence interval [CI], 0.54-0.97; P = .03; proximal: OR, 0.72; 95% CI, 0.53-0.97; P = .002). Patients with proximal cancers undergoing colonoscopy by endoscopists who performed polypectomies at high rates had a lower risk of PCCRC (OR, 0.61; 95% CI, 0.42-0.89; P &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt; .0001). Endoscopist volume was not associated with PCCRC. Endoscopist characteristics derived from administrative data are associated with development of PCCRC and have potential use as quality indicators.

Nonprofit organizations may predominate when output quality is difficult to monitor. Hospital care has this characteristic. This study compared program cost and quality of care for Medicare patients hospitalized following onset of four common conditions by hospital ownership. Payments on behalf of Medicare patients admitted to for-profit hospitals during the first 6 months following a health shock were higher than for those admitted to other hospitals. With quality measured in terms of survival, changes in functional and cognitive status, and living arrangements, we found no differences in outcomes by hospital ownership.

This is Part II of the paper, "Gray-Level Grouping (GLG): an Automatic Method for Optimized Image Contrast Enhancement". Part I of this paper introduced a new automatic contrast enhancement technique: gray-level grouping (GLG). GLG is a general and powerful technique, which can be conveniently applied to a broad variety of low-contrast images and outperforms conventional contrast enhancement techniques. However, the basic GLG method still has limitations and cannot enhance certain classes of low-contrast images well, e.g., images with a noisy background. The basic GLG also cannot fulfill certain special application purposes, e.g., enhancing only part of an image which corresponds to a certain segment of the image histogram. In order to break through these limitations, this paper introduces an extension of the basic GLG algorithm, selective gray-level grouping (SGLG), which groups the histogram components in different segments of the grayscale using different criteria and, hence, is able to enhance different parts of the histogram to various extents. This paper also introduces two new preprocessing methods to eliminate background noise in noisy low-contrast images so that such images can be properly enhanced by the (S)GLG technique. The extension of (S)GLG to color images is also discussed in this paper. SGLG and its variations extend the capability of the basic GLG to a larger variety of low-contrast images, and can fulfill special application requirements. SGLG and its variations not only produce results superior to conventional contrast enhancement techniques, but are also fully automatic under most circumstances, and are applicable to a broad variety of images.

We present an equilibrium model of the market for higher education. Our model simultaneously predicts student selection into institutions of higher education, financial aid, educational expenditures, and educational outcomes. We show that the model gives rise to a strict hierarchy of colleges that differ by the educational quality provided to the students. We also develop a new estimation procedure that exploits the observed variation in prices within colleges. Identification is based on variation in endowments and technology. It does not rely on observed variation in potentially endogenous characteristics of colleges such as peer quality measures and expenditures.

In 1999, the National Cancer Policy Board called attention to the quality of cancer care in the United States and recommended establishing a quality monitoring system with the capability of regularly reporting on the quality of care for patients with cancer.

Previous research has contributed much to our understanding of the relationship between corporate diversification strategy and corporate governance quality. The majority of published works has been on sophisticated and mature markets in first world nations. This paper extends previous knowledge by examining this relationship in a developing country. Malaysia is a developing country that provides a rich setting for corporate governance research. The structure of the business environment and the availability of published data make it an interesting research site.

A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality.

This research investigates whether audit committees are associated with improved earnings quality for a sample of Australian listed companies prior to the introduction of mandatory audit committee requirements in 2003. Two measures of earnings quality are used based on models first developed by and . Our results indicate that formation of an audit committee reduces intentional earnings management but not accrual estimation errors. We also find differences in the associations between audit committee accounting expertise and the two earnings quality measures. Other audit committee characteristics examined are not significantly related to either earnings quality measure.

In this paper, an improved form of iterative speech enhancement for single channel inputs is formulated. The basis of the procedure is sequential maximum a posteriori estimation of the speech waveform and its all-pole parameters as originally formulated by Lim and Oppenheim, followed by imposition of constraints upon the sequence of speech spectra. The new approaches impose intraframe and interframe constaints on the input speech signal to ensure more speechlike formant trajectories, reduce frame-to-frame pole jitter, and effectively introduce a relaxation parameter to the iterative scheme. Recently discovered properties of the line spectral pair representation of speech allow for an efficient and direct procedure for application of many of the constraint requirements. Substantial improvement over the unconstrained method has been observed in a variety of domains. First, informal listener quality evaluation tests and objective speech quality measures demonstrate the technique's effectiveness for additive white Gaussian noise. A consistent terminating point for the iterative technique is also shown. Second, the algorithms have been generalized and successfully tested for noise which is nonwhite and slowly varying in characteristics. The current systems result in substantially improved speech quality and LPC parameter estimation in this context with only a minor increase in computational requirements. Third, the algorithms were evaluated with respect to improving automatic recognition of speech in the presence of additive noise, and shown to outperform other enhancement methods in this application.

The problem of scarcity of labeled pixels, required for segmentation of remotely sensed satellite images in supervised pixel classification framework, is addressed in this article. A support vector machine (SVM) is considered for classifying the pixels into different landcover types. It is initially designed using a small set of labeled points, and subsequently refined by actively querying for the labels of pixels from a pool of unlabeled data. The label of the most interesting/ ambiguous unlabeled point is queried at each step. Here, active learning is exploited to minimize the number of labeled data used by the SVM classifier by several orders. These features are demonstrated on an IRS-1A four band multispectral image. Comparison with related methods is made in terms of number of data points used, computational time and a cluster quality measure.

The goal of multi-objective optimization is to find a set of best compromise solutions for typically conflicting objectives. Due to the complex nature of most real-life problems, only an approximation to such an optimal set can be obtained within reasonable (computing) time. To compare such approximations, and thereby the performance of multi-objective optimizers providing them, unary quality measures are usually applied. Among these, the hypervolume indicator (or S-metric) is of particular relevance due to its good properties. Moreover, this indicator has been successfully integrated into stochastic optimizers, such as evolutionary algorithms, where it serves as a guidance criterion for searching the parameter space.

The success of Skype has inspired a generation of peer-topeer-based solutions for satisfactory real-time multimedia services over the Internet. However, fundamental questions, such as whether VoIP services like Skype are good enough in terms of user satisfaction, have not been formally addressed. One of the major challenges lies in the lack of an easily accessible and objective index to quantify the degree of user satisfaction.

One of the open issues in fingerprint verification is the lack of robustness against image-quality degradation. Poor-quality images result in spurious and missing features, thus degrading the performance of the overall system. Therefore, it is important for a fingerprint recognition system to estimate the quality and validity of the captured fingerprint images. In this work, we review existing approaches for fingerprint image-quality estimation, including the rationale behind the published measures and visual examples showing their behavior under different quality conditions. We have also tested a selection of fingerprint image-quality estimation algorithms. For the experiments, we employ the BioSec multimodal baseline corpus, which includes 19 200 fingerprint images from 200 individuals acquired in two sessions with three different sensors. The behavior of the selected quality measures is compared, showing high correlation between them in most cases. The effect of low-quality samples in the verification performance is also studied for a widely available minutiae-based fingerprint matching system.

Software architecture evaluation has been proposed as a means to achieve quality attributes such as maintainability and reliability in a system. The objective of the evaluation is to assess whether or not the architecture will lead to the desired quality attributes. Recently, there have been a number of evaluation methods proposed. There is, however, little consensus on the technical and non-technical issues that a method should comprehensively address and which of the existing methods is most suitable for a particular issue. This paper presents a set of commonly known but informally described features of an evaluation method and organizes them within a framework that should offer guidance on the choice of the most appropriate method for an evaluation exercise. In this paper, we use this framework to characterise eight SA evaluation methods.

This study explores the relationships between teacher knowledge, teaching practice, and student learning in mathematics. It extends previous work that developed and evaluated an innovative approach to assessing teacher knowledge based on teachers' analyses of classroom video clips. Teachers watched and commented on 13 fraction clips. These written analyses were coded using objective rubrics to yield a reliable and valid indicator of their NICOLE B. KERSTING is an assistant professor at

The increase in digital soil mapping around the world means that appropriate and efficient sampling strategies are needed for validation. Data used for calibrating a digital soil mapping model typically are non-random samples. In such a case we recommend collection of additional independent data and validation of the soil map by a design-based sampling strategy involving probability sampling and design-based estimation of quality measures. An important advantage over validation by data-splitting or cross-validation is that model-free estimates of the quality measures and their standard errors can be obtained, and thus no assumptions on the spatial auto-correlation of prediction errors need to be made. The quality of quantitative soil maps can be quantified by the spatial cumulative distribution function (SCDF) of the prediction errors, whereas for categorical soil maps the overall purity and the map unit purities (user's accuracies) and soil class representation (producer's accuracies) are suitable quality measures. The suitability of five basic types of random sampling design for soil map validation was evaluated: simple, stratified simple, systematic, cluster and two-stage random sampling. Stratified simple random sampling is generally a good choice: it is simple to implement, estimation of the quality measures and their precision is straightforward, it gives relatively precise estimates, and no assumptions are needed in quantifying the standard error of the estimated quality measures. Validation by probability sampling is illustrated with two case studies. A categorical soil map on point support depicting soil classes in the province of Drenthe of the Netherlands (268 000 ha) was validated by stratified simple random sampling. Sub-areas with different expected purities were used as strata. The estimated overall purity was 58% with a standard error of 4%. This was 9% smaller than the theoretical purity computed with the model. Map unit purities and class representations were estimated by the ratio estimator. A quantitative soil map, depicting the average soil organic carbon (SOC) contents of pixels in an area of 81 600 ha in Senegal, was validated by random transect sampling. SOC predictions were seriously biased, and the random error was considerable. Both case studies underpin the importance of independent validation of soil maps by probability sampling, to avoid unfounded trust in visually attractive maps produced by advanced pedometric techniques.

The Society of Thoracic Surgeons established a Quality Measurement Task Force to develop a methodology for the comprehensive assessment of adult cardiac surgery quality of care, including both individual measures and an overall composite quality score. In Part 1 of a two-part series, the Task Force describes the conceptual framework, principles, and guidelines used to select and categorize the individual measures that comprise the composite score.

We consider the planning and control of multiple aerial robots manipulating and transporting a payload in three dimensions via cables. Individual robot control laws and motion plans enable the control of the payload (position and orientation) along a desired trajectory. We address the fact that robot configurations may admit multiple payload equilibrium solutions by developing constraints for the robot configuration

Modularity is a recently introduced quality measure for graph clusterings. It has immediately received considerable attention in several disciplines, and in particular in the complex systems literature, although its properties are not well understood. We study the problem of finding clusterings with maximum modularity, thus providing theoretical foundations for past and present work based on this measure. More precisely, we prove the conjectured hardness of maximizing modularity both in the general case and with the restriction to cuts, and give an Integer Linear Programming formulation. This is complemented by first insights into the behavior and performance of the commonly applied greedy agglomaration approach.

Content and methodology experts nominated by ASCO and NCCN met to select and refine metrics for breast, colon, and rectal cancer based on National Initiative for Cancer Care Quality and NCCN measures and NCCN and ASCO guidelines. Measures were selected based on their impact on disease free and overall survival, the degree to which opportunities for improvement exist, and the feasibility of data collection.