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This article describes testing for periodicity in the presence of FD processes. We propose two approaches for testing the periodicity based on Fisher's test. The first one is performed using the periodogram which has been divided into different parts. The second one is based on the discrete wavelet transform. Properties of the tests are illustrated by means of Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In this study, we use the wavelet analysis to construct a test statistic to test for the existence of a trend in the series. We also propose a new approach for testing the presence of trend based on the periodogram of the data. Since we are also interested in the presence of a long-memory process among the data, we study the properties of our test statistics under different degrees of dependency. We compare the results when using the band periodogram test and the wavelet test with results obtained by applying the ordinary least squares (OLS) method under the same conditions. [ABSTRACT FROM AUTHOR]

This paper describes an alternative approach for testing for the existence of trend among time series. The test method has been constructed using wavelet analysis which has the ability of decomposing a time series into low frequencies (trend) and high-frequency (noise) components. Under the normality assumption, the test is distributed as F. However, using generated empirical critical values, the properties of the test statistic have been investigated under different conditions and different types of wavelet. The Harr wavelet has shown to exhibit the highest power among the other wavelet types. The methodology here has been applied to real temperature data in Sweden for the period 1850-1999. The results indicate a significant increasing trend which agrees with the 'global warming' hypothesis during the last 100 years. [ABSTRACT FROM AUTHOR]

It is well known that one of the features of long-memory processes is that they tend to have what looks like trends and cycles. A consequence of this property is that it is difficult to distinguish a long-memory process from a nonstationary process. In this paper, we study the impact of the periodicity and trend on different methods for estimating the long-memory processes parameter d. [ABSTRACT FROM AUTHOR]

Quarterly data for the period 1960:1 to 1997:2, conventional tests, a bootstrap simulation approach and a multivariate Rao's F-test have been used to investigate if the causality between government spending and revenue in Finland was changed at the beginning of 1990 due to future plans to create the European Monetary Union (EMU). The results indicate that during the period before 1990, the government revenue Granger-caused spending, while the opposite happened after 1990, which agrees better with Barro's tax smoothing hypothesis. However, when using monthly data instead of quarterly data for almost the same sample period, totally different results have been noted. The general conclusion is that the relationship between spending and revenue in Finland is still not completely understood. The ambiguity of these results may well be due to the fact that there are several time scales involved in the relationship, and that the conventional analyses may be inadequate to separate out the time scale structured relationships between these variables. Therefore, to investigate empirically the relation between these variables we attempt to use the wavelets analysis that enables us to separate out different time scales of variation in the data. We find that time scale decomposition is important for analysing these economic variables. [ABSTRACT FROM AUTHOR]

Conventional bulky and rigid electronics prevent compliant interfacing with soft human skin for health monitoring and human–machine interaction, due to the incompatible mechanical characteristics. To overcome the limitations, soft skin‐mountable electronics with superior mechanical softness, flexibility, and stretchability provide an effective platform for intimate interaction with humans. In addition, soft electronics offer comfortability when worn on the soft, curvilinear, and dynamic human skin. Herein, recent advances in soft electronics as health monitors and human–machine interfaces (HMIs) are briefly discussed. Strategies to achieve softness in soft electronics including structural designs, material innovations, and approaches to optimize the interface between human skin and soft electronics are briefly reviewed. Characteristics and performances of soft electronic devices for health monitoring, including temperature sensors, pressure sensors for pulse monitoring, pulse oximeters, electrophysiological sensors, and sweat sensors, exemplify their wide range of utility. Furthermore, the soft electronic devices for prosthetic limb, household object, mobile machine, and virtual object control are presented to highlight the current and potential implementations of soft electronics for a broad range of HMI applications. Finally, the current limitations and future opportunities of soft skin‐mountable electronics are also discussed. [ABSTRACT FROM AUTHOR]

Cloud computing (CC) is a distributed and centralized network of interconnected and interrelated systems that has emerged as an area of incredible impact, potential, and growth in the IT domain. In the last few years, this paradigm has thrived to become the fastest evolutionary segment for business and various industries. Despite the many advantages provided by the cloud, serious challenges related to privacy and security have arisen such as privacy exposure, data loss, manipulation, service-level agreement (SLA) violation, and concerns over the service and deployment models. In this article, a blockchain-based hybrid algorithm is proposed to tackle the privacy inefficiency of existing tools. A novel hybrid technique is used to encrypt data ahead of outsourcing it to data centers, and a unique digital signature is generated at clients and stored on a decentralized set of blocks. A virtual cloud similar to actual cloud service infrastructure was built to test the proposed framework. Despite the additional computational powers needed to run the proposed framework due to blockchain integration, the results show that data integrity and reliability are preserved and user's privacy is increased. Our results are discussed and benchmarked against the standard privacy tests standards such as changes in the stored data, the negligible overheads on cloud performance, and the data records of the blockchain structure. [ABSTRACT FROM AUTHOR]

Objectives To investigate whether routinely collected data from hospital episode statistics could be used to identify the gynaecologist Rodney Ledward, who was suspended in 1966 and was the subject of the Ritchie inquiry into quality and practice within the NHS. Design A mixed scanning approach was used to identify seven variables from hospital episode statistics that were likely to be associated with potentially poor performance. A blinded multivariate analysis was undertaken to determine the distance (known as the Mahalanobis distance) in the seven indicator multidimensional space that each consultant was from the average consultant in each year. The change in Mahalanobis distance over time was also investigated by using a mixed effects model. Setting NHS hospital trusts in two English regions, in the five years from 1991-2 to 1995-6. Population Gynaecology consultants (n = 143) and their hospital episode statistics data. Main outcome measure Whether Ledward was a statistical outlier at the 95% level. Results The proportion of consultants who were outliers in any one year (at the 95% significance level) ranged from 9% to 20%. Ledward appeared as an outlier in three of the five years. Our mixed effects (multi-year) model identified nine high outlier consultants, including Ledward. Conclusion It was possible to identify Ledward as an outlier by using hospital episode statistics data. Although our method found other outlier consultants, we strongly caution that these outliers should not be overinterpreted as indicative of "poor" performance. Instead, a scientific search for a credible explanation should be undertaken, but this was outside the remit of our study. The set of indicators used means that cancer specialists, for example, are likely to have high values for several indicators, and the approach needs to be refined to deal with case mix variation. Even after allowing for that, the interpretation of outlier status is still as yet unclear. Further prospective evaluation of our method is warranted, but our overall approach may be potentially useful in other settings, especially where performance entails several indicator variables. [ABSTRACT FROM AUTHOR]

The article discusses the wisdom of adjusting data in quality adjusted life years (QALY) assessments when making rationing decisions about treatment. The article argues that rationing decisions are often made on the basis of false information, since they take into account the QALY assessments of both people who will accept treatments and those who refuse it. Instead, the article suggests that QALY measures only be considered for those patients who intend to accept treatment, as their preferences will offer a better picture of how well the treatment will be received.

Presents a letter to the editor regarding an article about outliers.