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Variance-ratio tests are routinely employed to assess the variation in return volatility over time and across markets. However, such tests are not statistically robust and can be seriously misleading within a high-frequency context. We develop improved inference procedures using a Fourier Flexible Form regression framework. The practical significance is illustrated through tests for changes in the FX intraday volatility pattern following the removal of trading restrictions in Tokyo. Contrary to earlier evidence, we find no discernible changes outside of the Tokyo lunch period. We ascribe the difference to the fragile finite-sample inference of conventional variance-ratio procedures and a single outlier. [ABSTRACT FROM AUTHOR]

The minimum covariance determinant (MCD) method is a highly robust estimator of multivariate location and scatter, for which a fast algorithm is available. Since estimating the covariance matrix is the cornerstone of many multivariate statistical methods, the MCD is an important building block when developing robust multivariate techniques. It also serves as a convenient and efficient tool for outlier detection. The MCD estimator is reviewed, along with its main properties such as affine equivariance, breakdown value, and influence function. We discuss its computation, and list applications and extensions of the MCD in applied and methodological multivariate statistics. Two recent extensions of the MCD are described. The first one is a fast deterministic algorithm which inherits the robustness of the MCD while being almost affine equivariant. The second is tailored to high‐dimensional data, possibly with more dimensions than cases, and incorporates regularization to prevent singular matrices. This article is categorized under: Statistical and Graphical Methods of Data Analysis > Multivariate Analysis Statistical and Graphical Methods of Data Analysis > Robust Methods Statistical Learning and Exploratory Methods of the Data Sciences > Knowledge Discovery [ABSTRACT FROM AUTHOR]

The Organization for Economic Cooperation and Development (OECD) recently revised the test guidelines (TGs) for genetic toxicology. This article describes the main issues addressed during the revision process, and the new and consistent recommendations made in the revised TGs for: (1) demonstration of laboratory proficiency; (2) generation and use of robust historical control data; (3) improvement of the statistical power of the tests; (4) selection of top concentration for in vitro assays; (5) consistent data interpretation and determination of whether the result is clearly positive, clearly negative or needs closer consideration; and, (6) consideration of 3R's for in vivo assay design. The revision process resulted in improved consistency among OECD TGs (including the newly developed ones) and more comprehensive recommendations for the conduct and the interpretation of the assays. Altogether, the recommendations made during the revision process should improve the efficiency, by which the data are generated, and the quality and reliability of test results. Environ. Mol. Mutagen. 58:284-295, 2017. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Adtpp is an open-source tool that adds support for algebraic data types (ADTs) to the C programming language. ADTs allow more precise description of program types and more robust handling of data structures than are directly supported by C. ADT definitions and other declarations are put in a file that is preprocessed by adtpp to produce a C header ('.h') file that can be included in C source files. The generated header file contains C type definitions, macros, and inline functions that support type-safe construction, deconstruction, and pattern matching of ADT values while avoiding unsafe operations such as casts, and avoiding the risk of errors such as dereferencing NULL pointers and accessing inappropriate fields of unions. Values are represented efficiently, using techniques from the implementation of declarative languages. For many simple data types, the memory representation is identical to a direct implementation in C, with no loss of efficiency. For more complex types, the adtpp representation is more efficient than common C representations while preserving type safety and convenience. As an example, we present a new variation of 234-trees that is very compact. Adtpp also supports parametric polymorphism such as defining a type 'list of t', where t can be any ADT, and generic functions such as length. However, polymorphic code is somewhat more verbose than for typical declarative languages, due to our reliance on the limited type checking available in C. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The calculation of metabolic turnover rates is essential for the scalable design, analysis and control of bioprocesses. A novel rate calculation algorithm is presented that is based on the dynamic adaptation of window sizes in order to deliver robust and precise rates with uniform signal-to-noise ratios. Additionally a model-based generic algorithm for deriving optimal rate calculation workflows was developed. The generic algorithms delivered more precise and accurate rates for online and offline signals, which was demonstrated for both in silico- and real batch and fed-batch fermentation process data. The presented algorithms will strongly support bioprocess development and control as enabling tools for multivariate data analysis, mechanistic modeling and dynamic experimentation. [ABSTRACT FROM AUTHOR]

Spectral clustering is a powerful tool for exploratory data analysis. Many existing spectral clustering algorithms typically measure the similarity by using a Gaussian kernel function or an undirected k-nearest neighbor (kNN) graph, which cannot reveal the real clusters when the data are not well separated. In this paper, to improve the spectral clustering, we consider a robust similarity measure based on the shared nearest neighbors in a directed kNN graph. We propose two novel algorithms for spectral clustering: one based on the number of shared nearest neighbors, and one based on their closeness. The proposed algorithms are able to explore the underlying similarity relationships between data points, and are robust to datasets that are not well separated. Moreover, the proposed algorithms have only one parameter, k. We evaluated the proposed algorithms using synthetic and real-world datasets. The experimental results demonstrate that the proposed algorithms not only achieve a good level of performance, they also outperform the traditional spectral clustering algorithms. [ABSTRACT FROM AUTHOR]

We propose a novel multiple-object tracking algorithm for real-time intelligent video surveillance. We adopt particle filtering as our tracking framework. Background modeling and subtraction are used to generate a region of interest. A two-step pedestrian detection is employed to reduce the computation time of the algorithm, and an iterative particle repropagation method is proposed to enhance its tracking accuracy. A matching score for greedy data association is proposed to assign the detection results of the two-step pedestrian detector to trackers. Various experimental results demonstrate that the proposed algorithm tracks multiple objects accurately and precisely in real time. [ABSTRACT FROM AUTHOR]

The demarcation of operational taxonomic units ( OTUs) from complex sequence data sets is a key step in contemporary studies of microbial ecology. However, as biologically motivated 'optimal' OTU-binning algorithms remain elusive, many conceptually distinct approaches continue to be used. Using a global data set of 887 870 bacterial 16 S r RNA gene sequences, we objectively quantified biases introduced by several widely employed sequence clustering algorithms. We found that OTU-binning methods often provided surprisingly non-equivalent partitions of identical data sets, notably when clustering to the same nominal similarity thresholds; and we quantified the resulting impact on ecological data description for a well-defined human skin microbiome data set. We observed that some methods were very robust to varying clustering thresholds, while others were found to be highly susceptible even to slight threshold variations. Moreover, we comprehensively quantified the impact of the choice of 16 S r RNA gene subregion, as well as of data set scope and context on algorithm performance. Our findings may contribute to an enhanced comparability of results across sequence-processing pipelines, and we arrive at recommendations towards higher levels of standardization in established workflows. [ABSTRACT FROM AUTHOR]

This paper reviews the long-run event-study debate by outlining the strengths and weakness of the most commonly used alternative techniques. The fist part of the discussion highlights that prior literature has failed to provide a single risk-adjusted model of long-run abnormal returns with no biases. Subsequently, the paper provides guidance on how one can choose among pertinent alternative techniques. As a conclusion, researchers ought to choose among alternative techniques after considering issues such as (i) the nature of dataset and market of interest, (ii) the event type (regulatory or corporate), (iii) returns' time-interval, (iv) association of the event with accounting data, (v) sample characteristics and prior evidence regarding similar events, as well as (vi) risk changes following the event. Robustness tests are essential, while the road for further research regarding the appropriate technique(s) is open. [ABSTRACT FROM AUTHOR]

Tracking the same person across multiple cameras is an important task in human motion analysis systems. It is also desirable to re-identify the individuals who have been previously seen with a single camera. This paper addresses this problem by the re-identification of the same individual in two different datasets, which are both challenging situations from human motion analysis systems. In this paper, local descriptors are introduced for image description, and support vector machines are employed for high classification performance and so an efficient bag-of-features approach for image presentation. In this way, robustness against low resolution, occlusion, and pose, viewpoint and illumination changes is achieved in a very fast way. We obtain promising results from the evaluation with situations where a number of individuals vary continuously from a multicamera system. [ABSTRACT FROM AUTHOR]

Cell-free protein expression is a promising tool for improving protein-specific expression techniques. Despite their advantages, insect cell-free expression systems are not as well established as Escherichia coli cell-free systems. In most studies, characterization and optimization strategies are based on manual 'one-factor-at-a-time' investigations that are expensive and time consuming. In this paper, two insect cell-free expression systems ( Sf9 and High Five™) were reproducibly ( CV = 2.9%) implemented on a robotic platform with integrated analytics. All experiments were planned by statistical design of experiments using central composite designs and analyzed by multivariate data analysis. Quadratic response surface models were fitted to the experimental data and model predictivity was validated successfully for both insect cell types. The characterization of the complete in vitro translation process included quantification and visualization of the parameter influences on the expression yield and the robustness of the systems. The results were compared to previous studies, which confirmed the applicability of the new method. In the future, yields from insect cell-free expression can be enhanced using a comprehensive system characterization based on optimally designed high-throughput screenings on robotic systems. [ABSTRACT FROM AUTHOR]

We examine whether the components of accruals and operating cash flows improve the predictive ability of earnings for forecasting future cash flows. Unlike most previous studies, we avoid data estimation errors and sample self-selection bias because we exploit data from Australia where reporting of actual cash flow components had been mandatory since 1992. We show that accrual components and operating cash flow components together are more useful than (i) earnings, (ii) operating cash flows and total accruals and (iii) the combination of operating cash flows with accrual components in forecasting future cash flows. These results are robust to several contextual factors, including the length of the operating cash cycle, industry membership, firm profitability and firm size. [ABSTRACT FROM AUTHOR]

SUMMARY Cloud computing is attracting the attention of the scientific community. In this paper, we develop a new cloud-based computing system in the Windows Azure platform that allows users to use the Zeolite Structure Predictor (ZSP) model through a Web browser. The ZSP is a novel machine learning approach for classifying zeolite crystals according to their framework type. The ZSP can categorize entries from the Inorganic Crystal Structure Database into 41 framework types. The novel automated system permits a user to calculate the vector of descriptors used by ZSP and to apply the model using the Random Forest™ algorithm for classifying the input zeolite entries. The workflow presented here integrates executables in Fortran and Python for number crunching with packages such as Weka for data analytics and Jmol for Web-based atomistic visualization in an interactive compute system accessed through the Web. The compute system is robust and easy to use. Communities of scientists, engineers, and students knowledgeable in Windows-based computing should find this new workflow attractive and easy to be implemented in scientific scenarios in which the developer needs to combine heterogeneous components. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Many studies in which gene expression is quantified by polymerase chain reaction represent the expression of a gene of interest ( GOI) relative to that of a reference gene ( RG). Relative expression is founded on the assumptions that RG expression is stable across samples, treatments, organs, etc., and that reaction efficiencies of the GOI and RG are equal; assumptions which are often faulty. The true variability in RG expression and actual reaction efficiencies are seldom determined experimentally. Here we present a rapid and robust method for absolute quantification of expression in Vitis where varying concentrations of genomic DNA were used to construct GOI standard curves. This methodology was utilized to absolutely quantify and determine the variability of the previously validated RG ubiquitin ( VvUbi) across three test studies in three different tissues (roots, leaves and berries). In addition, in each study a GOI was absolutely quantified. Data sets resulting from relative and absolute methods of quantification were compared and the differences were striking. VvUbi expression was significantly different in magnitude between test studies and variable among individual samples. Absolute quantification consistently reduced the coefficients of variation of the GOIs by more than half, often resulting in differences in statistical significance and in some cases even changing the fundamental nature of the result. Utilizing genomic DNA-based absolute quantification is fast and efficient. Through eliminating error introduced by assuming RG stability and equal reaction efficiencies between the RG and GOI this methodology produces less variation, increased accuracy and greater statistical power. [ABSTRACT FROM AUTHOR]

We use new data on transportation to determine its effect on the international trade of eastern and southern Africa ( ESA). The effects were estimated with gravity models using alternative techniques to check for robustness. Freight forwarders provided information on freight charges (price), average duration of shipment (time) and variability in time. The new transportation variables and the more commonly used distance variable appear to have smaller effects overall than some previous research indicated, although our distance coefficient is identical to that of Coulibaly and Fotagné for West Africa. In contrast to other research critical of distance as a proxy for transport impediments, we find similar effects from distance and our measure of transport time, but both of these variables have significantly larger coefficients than price and variability. Landlocked ESA countries are twice as dependent on trade as the whole region after accounting for control variables, but they are not significantly more affected by changes in price and time, and they are less affected by distance and variability. The relative size of the time coefficients suggests that measures to lessen delays in shipping, for instance, faster border clearance, might encourage more trade than cost cutting measures that lowered price proportionately. [ABSTRACT FROM AUTHOR]

We present a caching framework with a novel probability-based prefetching and eviction strategy applied to atomic cache units that enables interactive rendering of gigaray light fields. Further, we describe two new use cases that are supported by our framework: panoramic light fields, including a robust imaging technique and an appropriate parameterization scheme for real-time rendering and caching; and light-field-cached volume rendering, which supports interactive exploration of large volumetric datasets using light-field rendering. We consider applications such as light-field photography and the visualization of large image stacks from modern scanning microscopes. [ABSTRACT FROM AUTHOR]

To efficiently deploy eye-tracking within 3D graphics applications, we present a new probabilistic method that predicts the patterns of user's eye fixations in animated 3D scenes from noisy eye-tracker data. The proposed method utilises both the eye-tracker data and the known information about the 3D scene to improve the accuracy, robustness and stability. Eye-tracking can thus be used, for example, to induce focal cues via gaze-contingent depth-of-field rendering, add intuitive controls to a video game, and create a highly reliable scene-aware saliency model. The computed probabilities rely on the consistency of the gaze scan-paths to the position and velocity of a moving or stationary target. The temporal characteristic of eye fixations is imposed by a Hidden Markov model, which steers the solution towards the most probable fixation patterns. The derivation of the algorithm is driven by the data from two eye-tracking experiments: the first experiment provides actual eye-tracker readings and the position of the target to be tracked. The second experiment is used to derive a JND-scaled (Just Noticeable Difference) quality metric that quantifies the perceived loss of quality due to the errors of the tracking algorithm. Data from both experiments are used to justify design choices, and to calibrate and validate the tracking algorithms. This novel method outperforms commonly used fixation algorithms and is able to track objects smaller then the nominal error of an eye-tracker. [ABSTRACT FROM AUTHOR]

Aim Conservation managers are typically faced with limited resources, time and information. The philosophy underlying risk assessment should be robust to these limitations. While there is a broad support for the concept of risk assessments, there is a tendency to rely on expert opinion and exclude formal data analysis, possibly because available information is often scarce. When data analyses are conducted, often much simplified models are advocated, even though this means excluding processes believed by experts to be important. In this manuscript, we ask: should statistical analyses be conducted and decisions modified based on a single datum? How many data points are needed before predictions are meaningful? Given limited data, how complex should models be? Location World-wide. Methods We use simulation approaches with known 'true' values to assess which inferences are possible, given different amounts of information. We use two metrics of performance: the magnitude of uncertainty (using posterior mean squared error) and bias (using P- P plots). We assess six models of relevance to conservation ecologists. Results We show that the greatest reduction in uncertainty occurred at the smallest sample sizes for models examined, and much of parameter space could be excluded. Thus, analyses based on even a single datum potentially can be useful. Further, with only a few observations, the predicted distribution of outcomes matched the probabilities of actual occurrences, even for relatively complex state-space models with multiple sources of stochasticity. Main conclusions We highlight the utility of quantitative analyses even with severely limited data, given existing practices and arguments in the conservation literature. The purpose of our manuscript is in part a philosophical discourse, as modifications are needed to how conservation ecologists are often trained to think about problems and data, and in part a demonstration via simulation analysis. [ABSTRACT FROM AUTHOR]

This work introduces a variable-fidelity optimization methodology for simulation-driven design optimization of filters. Our approach is based on electromagnetic (EM) simulations of different accuracy controlled by the mesh density. A Kriging interpolation model (the surrogate) is created using sampled low-fidelity EM data and optimized to approximately locate the optimum of the high-fidelity EM model of the filter. This initial surrogate is subsequently improved by blending in the high-fidelity data accumulated during the optimization process using the co-Kriging technique. The algorithm convergence is ensured by embedding it into the trust region framework. The operation and performance of our method is demonstrated using three filter design cases. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:765-769, 2013; View this article online at wileyonlinelibrary.com. DOI: 10.1002/mop.27447 [ABSTRACT FROM AUTHOR]

In most spectral clustering approaches, the Gaussian kernel-based similarity measure is used to construct the affinity matrix. However, such a similarity measure does not work well on a dataset with a nonlinear and elongated structure. In this paper, we present a new similarity measure to deal with the nonlinearity issue. The maximum flow between data points is computed as the new similarity, which can satisfy the requirement for similarity in the clustering method. Additionally, the new similarity carries the global and local relations between data. We apply it to spectral clustering and compare the proposed similarity measure with other state-of-the-art methods on both synthetic and real-world data. The experiment results show the superiority of the new similarity: 1) The max-flow-based similarity measure can significantly improve the performance of spectral clustering; 2) It is robust and not sensitive to the parameters. [ABSTRACT FROM AUTHOR]

I use a panel data set covering 26 OECD countries between 1960 and 2004 to revisit the consumption-real exchange rate anomaly. After using demographic variables (in particular, the fertility rate) as instruments, I document a new empirical regularity that higher real exchange rates are associated with higher relative consumption. This positive relationship is statistically significant and has been shown to be robust. Such a finding may suggest that the theoretical prediction in Backus and Smith ( Journal of International Economics, Vol. 35 (1993), pp. 297-316) is no longer at odds with the data. [ABSTRACT FROM AUTHOR]

In this paper, we present a new approach for speaker diarization. First, we use the prosodic information calculated on the original speech to resynthesize the new speech data utilizing the spectrum modeling technique. The resynthesized data is modeled with sinusoids based on pitch, vibration amplitude, and phase bias. Then, we use the resynthesized speech data to extract cepstral features and integrate them with the cepstral features from original speech for speaker diarization. At last, we show how the two streams of cepstral features can be combined to improve the robustness of speaker diarization. Experiments carried out on the standardized datasets (the US National Institute of Standards and Technology Rich Transcription 04-S multiple distant microphone conditions) show a significant improvement in diarization error rate compared to the system based on only the feature stream from original speech. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the determinants of the number of large floods reported since 1990. Using the same sample of countries as Bradshaw et al. (2007), and, like them, omitting socioeconomic characteristics from the analysis, we found that a reduction in natural forest cover is associated with an increase in the reported count of large floods. This result does not hold in any of three new analyses we perform. First, we expand the sample to include all the developing countries and all countries for which data were available but were omitted in their study. Second, and more importantly, since forest management is just one possible channel through which humans can influence reported flood frequency, we account for other important human-flood interactions. People are typically responsible for deforestation, but they are also responsible for other land use changes (e.g., urbanization), for floodplain and flood emergency management, and for reporting the floods. Thus, in our analysis we account for population, urban population growth, income, and corruption. Third, we exploit the panel nature ofthe data to control for unobserved country and time heterogeneity. We conclude that not only is the link between forest cover and reported flood frequency at the country level not robust, it also seems to be driven by sample selection and omitted variable bias. The human impact on the reported frequency of large floods at the country level is not through deforestation. [ABSTRACT FROM AUTHOR]

The impacts of outsourcing provision-the arrangements whereby a firm carries out production stages for other firms-are examined on wage differentials between skilled and unskilled workers using Thailand's establishment-level data. The estimates based on a translog production function indicate that outsourcing provision augments productivity of both skilled and unskilled labor and contributes positively to wage inequality. The model predicts that a 1% increase in outsourcing provision leads to a rise in wage differentials by nearly 2.5%. The robustness check further reveals that the impacts of services provision on wage inequality are more pronounced than those of materials provision. These results highlight the importance of outsourcing provision as a new explanation of the widening skilled-unskilled wage gap in developing countries which typically emerge as a hub of outsourcing provision. [ABSTRACT FROM AUTHOR]

ABSTRACT The magnetotelluric method employs co-located surface measurements of electric and magnetic fields to infer the local electrical structure of the earth. The frequency dependent 'apparent resistivity' curves can be inaccurate at long periods if input data are contaminated - even when robust remote reference techniques are employed. Data despiking prior to processing can result in significantly more reliable estimates of long period apparent resistivities. This paper outlines a two-step method of automatic identification and replacement for spike-like contamination of magnetotelluric data; based on the simultaneity of natural electric and magnetic field variations at distant sites. This simultaneity is exploited both to identify windows in time when the array data are compromised as well as to generate synthetic data that replace observed transient noise spikes. In the first step windows in data time series that contain spikes are identified according to an intersite comparison of channel 'activity'- such as the variance of differenced data within each window. In the second step, plausible data for replacement of flagged windows are calculated by Wiener filtering coincident data in clean channels. The Wiener filters - which express the time-domain relationship between various array channels - are computed using an uncontaminated segment of array training data. Examples are shown where the algorithm is applied to artificially contaminated data and to real field data. In both cases all spikes are successfully identified. In the case of implanted artificial noise, the synthetic replacement time series are very similar to the original recording. In all cases, apparent resistivity and phase curves obtained by processing the despiked data are much improved over curves obtained from raw data. [ABSTRACT FROM AUTHOR]

SUMMARY Modern scientific experiments can generate hundreds of gigabytes to terabytes or even petabytes of data that may be maintained in large numbers of relatively small files. Frequently, these data must be disseminated to remote collaborators or computational centers for data analysis. Moving this dataset with high performance and strong robustness and providing a simple interface for users are challenging tasks. We present a data transfer framework comprising a high-performance data transfer library based on GridFTP, an extensible data scheduler with four data scheduling policies, and a GUI that allows users to transfer their dataset easily, reliably, and securely. This system incorporates automatic tuning mechanisms to select at runtime the number of concurrent threads to be used for transfers. Also included are restart mechanisms for handling client, network, and server failures. Experimental results indicate that our data transfer system can significantly improve data transfer performance and can recover well from failures. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Isolation of a regional field from a Bouguer map has always been an ambiguous and troublesome problem. It is often argued that the ambiguity arises from lack of specific criteria under which the problem may be formulated. In this paper, I show that by adopting Skeels' definition of the regional field and its corollary, criteria needed to extract the field with minimum ambiguity may be developed. The definition and its corollary allow formulation of the regional field separation problem as a weighted (robustified) and constrained least-square fitting problem with constraints extracted directly from the Bouguer map. To emphasize the constraints, I formulate the problem from the perspective of prior information constrained by observational data. The new formalism offers several advantages: weighted fitting is more robust than ordinary least squares fitting, providing a simple mechanism to eliminate data outliers and reduce the undesirable influence of local gravity disturbances. Introducing constraints into the fitting procedure effectively reduces ambiguity and increases the resolution of the fitted regional field. Moreover, imposing conditions on the fitted regional field directly from the Bouguer map is tantamount to incorporating prior information about the underlying geology and structure of the area with minimum human subjectivity. The procedure was tested on simulated and actual data sets with excellent results. Indeed the test results indicate that with properly placed constraints, the regional field may be recovered in a manner that closely emulates the graphical method. [ABSTRACT FROM AUTHOR]

In the context of the debate on the labor-market consequences of globalization, we adopt an original approach toward the identification of the wage differences between foreign and domestic firms: worker mobility. Using matched employer-employee panel data for Portugal, we consider virtually all spells of interfirm mobility over a period of 10 yr. We find that foreign firms offer significantly more generous wage policies, although there is also a (smaller) selection effect. The results are robust to the consideration of displaced workers, wage growth differences in the new firms, and different subsets of workers. ( JEL J31, J63, F23) [ABSTRACT FROM AUTHOR]

Following a sharp slowdown in H2 2018, latest survey data suggests that economic activity seems to be stabilising. There remains a wide divergence between robust activity in services and a struggling manufacturing sector, which is still reeling from the impact from several transitory shocks as well as a sharp deterioration in the external environment. This is particularly evident in the March PMI numbers, which showed services activity bouncing back to its highest level in four months whereas the manufacturing sector continued to slip, reaching its lowest level in six years. We still think that robust domestic fundamentals should help to support growth in 2019. But risks remain, especially from an increasingly adverse global environment. [ABSTRACT FROM AUTHOR]

Purpose: To modify the preprocessing technique, which was previously proposed, improving compressibility of computed tomography (CT) images to cover the diversity of three dimensional configurations of different body parts and to evaluate the robustness of the technique in terms of segmentation correctness and increase in reversible compression ratio (CR) for various CT examinations. Methods: This study had institutional review board approval with waiver of informed patient consent. A preprocessing technique was previously proposed to improve the compressibility of CT images by replacing pixel values outside the body region with a constant value resulting in maximizing data redundancy. Since the technique was developed aiming at only chest CT images, the authors modified the segmentation method to cover the diversity of three dimensional configurations of different body parts. The modified version was evaluated as follows. In randomly selected 368 CT examinations (352 787 images), each image was preprocessed by using the modified preprocessing technique. Radiologists visually confirmed whether the segmented region covers the body region or not. The images with and without the preprocessing were reversibly compressed using Joint Photographic Experts Group (JPEG), JPEG2000 two-dimensional (2D), and JPEG2000 three-dimensional (3D) compressions. The percentage increase in CR per examination (CRI) was measured. Results: The rate of correct segmentation was 100.0% (95% CI: 99.9%, 100.0%) for all the examinations. The median of CRI were 26.1% (95% CI: 24.9%, 27.1%), 40.2% (38.5%, 41.1%), and 34.5% (32.7%, 36.2%) in JPEG, JPEG2000 2D, and JPEG2000 3D, respectively. Conclusions: In various CT examinations, the modified preprocessing technique can increase in the CR by 25% or more without concerning about degradation of diagnostic information. [ABSTRACT FROM AUTHOR]