The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results. © 1964-2012 IEEE.

Nonadherence in difficult asthma - facts, myths, and a time to act

Nonadherence to prescribed treatment is an important cause of difficult asthma. Rates of nonadherence amongst asthmatic patients have been shown to range between 30% and 70%. This is associated with poor health care outcomes and increased health care costs. There is no such thing as a "typical" nonadherent patient. The reasons driving nonadherence are multifactorial. Furthermore, adherence is a variable behavior and not a trait characteristic. Adherence rates can vary between the same individual across treatments for different conditions. There is no consistent link between socioeconomic status and nonadherence, and although some studies have shown that nonadherence is more common amongst females, this is not a universal finding. The commonly held perception that better adherence is driven by greater disease severity has been demonstrated to not be the case, in both pediatric and adult patients. Identification of nonadherence is the first step. If adherence is not checked, it is likely that poor adherence will be labeled as refractory disease. Failure to identify poor adherence may lead to inappropriate escalation of therapy, including the potential introduction of complex biological therapies. Surrogate measures, such as prescription counting, are not infallible. Nonadherence can be difficult to identify in clinical practice, and a systematic approach using a variety of tools is required. Nonadherence can be successfully addressed. Therefore, assessment of adherence is of paramount importance in difficult asthma management, in order to reduce exacerbations and steroid-related side effects as well as hospital and intensive care admissions, health care cost, and inappropriate treatment escalation. In this paper, we present an overview of the literature surrounding nonadherence in difficult asthma. We explore the facts and myths surrounding the factors driving nonadherence as well as how it can be identified and addressed.

Is Use of Optional Attributes and Associations in Conceptual Modeling Always Problematic? Theory and Empirical Tests

Prior research has argued that use of optional properties in conceptual models results in loss of information about the semantics of the domains represented by the models. Empirical research undertaken to date supports this argument. Nevertheless, no systematic analysis has been done of whether use of optional properties is always problematic. Furthermore, prior empirical research might have deliberately or unwittingly employed models where use of optionality always causes problems. Accordingly, we examine analytically whether use of optional properties is always problematic. We employ our analytical results to inform the design of an experiment where we systematically examined the impact of optionality on users’ ability to understand domains represented by different types of conceptual models. We found evidence that use of optionality undermines users’ ability to understand the domain represented by a model but that this effect weakens when use of mandatory properties to replace optional properties leads to more-complex models.

Empirical assessment of non-invasive population genetics in bats:Comparison of DNA quality from faecal and tissue samples

Non-invasive population genetics has become a valuable tool in ecology and conservation biology, allowing genetic studies of wild populations without the need to catch, handle or even observe the study subjects directly. We address some of the concerns regarding the limitations of using non-invasive samples by comparing the quality of population genetic information gained through DNA extracted from faecal samples and biopsy samples of two elusive bat species, Myotis mystacinus and Myotis nattereri. We demonstrate that DNA extracted from faeces and tissue samples gives comparable results for frequency based population genetic analyses, despite the occurrence of genotyping errors when using faecal DNA. We conclude that non-invasive genetic sampling for population genetic analysis in bats is viable, and although more labour-intensive and expensive, it is an alternative to tissue sampling, which is particularly pertinent when specimens are rare, endangered or difficult to capture. © 2012 Museum and Institute of Zoology PAS.

Empirical testing of genuine savings as an indicator of weak sustainability: a three-country analysis of long run trends

Genuine Savings has emerged as a widely-used indicator of sustainable development. In this paper, we use long-term data stretching back to 1870 to undertake empirical tests of the relationship between Genuine Savings (GS) and future well-being for three countries: Britain, the USA and Germany. Our tests are based on an underlying theoretical relationship between GS and changes in the present value of future consumption. Based on both single country and panel results, we find evidence supporting the existence of a cointegrating (long run equilibrium) relationship between GS and future well-being, and fail to reject the basic theoretical result on the relationship between these two macroeconomic variables. This provides some support for the GS measure of weak sustainability. We also show the effects of modelling shocks, such as World War Two and the Great Depression.

Vulnerability and robustness of SME supply chains: An empirical study of risk and disturbance management of fresh food processors in a developing market

The aim of this paper is to analyse vulnerability and robustness of small and medium size enterprises (SMEs) supply chains and to consider contextual factors that might influence the success of their disturbance management: Risky product and business environment. By using an exploratory case study it is shown how these contextual factors attribute vulnerability sources, contribute to the robustness of a company’s performance and supply chain vulnerability, as well as how a company seeks to manage internal and external vulnerability sources. The exploratory case is based on a fresh food supply chain of a manufacturing SME operating in a developing market.
Case findings suggest that fresh food supply chains of a manufacturing SME in developing markets are prone to disruptions of their logistics and production processes due to ‘riskiness’ of fresh food products, the ‘riskiness’ of developing markets, as well as ‘riskiness’ of SMEs themselves. However, this does not necessarily indicate the vulnerability of an SME and its entire supply chain. Findings indicate that SMEs can be very successful in disturbance management by selective use of redesign strategies that aim to prevent or reduce the impact of disturbances. More precise, it is likely that an SME can achieve robust performance by employing preventive redesign strategies in managing disturbances that result from internal, company related vulnerability sources, while impact reduction strategies are likely to contribute to robust performance of an SME if used to manage disturbances that result from internal, supply chain related vulnerability sources, as well as external vulnerability sources.

Empirical evaluation of multi-device profiling side-channel attacks

Side-channel analysis of cryptographic systems can allow for the recovery of secret information by an adversary even where the underlying algorithms have been shown to be provably secure. This is achieved by exploiting the unintentional leakages inherent in the underlying implementation of the algorithm in software or hardware. Within this field of research, a class of attacks known as profiling attacks, or more specifically as used here template attacks, have been shown to be extremely efficient at extracting secret keys. Template attacks assume a strong adversarial model, in that an attacker has an identical device with which to profile the power consumption of various operations. This can then be used to efficiently attack the target device. Inherent in this assumption is that the power consumption across the devices under test is somewhat similar. This central tenet of the attack is largely unexplored in the literature with the research community generally performing the profiling stage on the same device as being attacked. This is beneficial for evaluation or penetration testing as it is essentially the best case scenario for an attacker where the model built during the profiling stage matches exactly that of the target device, however it is not necessarily a reflection on how the attack will work in reality. In this work, a large scale evaluation of this assumption is performed, comparing the key recovery performance across 20 identical smart-cards when performing a profiling attack.

Environmental Inequalities and Democratic Citizenship: Linking Normative Theory with Empirical Research

The aim of this paper is to link empirical findings concerning environmental inequalities with different normative yard-sticks for assessing whether these inequalities should be deemed unjust, or not. We argue that such an inquiry must necessarily take into account some caveats regarding both empirical research and normative theory. We suggest that empirical results must be contextualised by establishing geographies of risk. As a normative yard-stick we propose a moderately demanding social-egalitarian account of justice and democratic citizenship, which we take to be best suited to identify unjust as well as legitimate instances of socio-environmental inequality.

Empirical testing of genuine savings as an indicator of weak sustainability: a three-country analysis of long run trends

Genuine Savings has emerged as a widely used indicator of sustainable development. In this paper, we use long -term data stretching back to 1870 to undertake empirical tests of the relationship between Genuine Savings (GS) and future well-being for three countries: Britain, the USA and Germany. Our tests are based on an underlying theoretical relationship between GS and changes in the present value of future consumption. Based on both single country and panel results, we find evidence supporting the existence of javascript:void(0);a cointegrating (long run equilibrium) relationship between GS and future well-being, and fail to reject the basic theoretical result on the relationship between these two macroeconomic variables. This provides some support for the GS measure of weak sustainability.