Can Leakage Models Be More Efficient? Non-Linear Models in Side Channel Attacks

In the last decade, many side channel attacks have been published in academic literature detailing how to efficiently extract secret keys by mounting various attacks, such as differential or correlation power analysis, on cryptosystems. Among the most efficient and widely utilized leakage models involved in these attacks are the Hamming weight and distance models which give a simple, yet effective, approximation of the power consumption for many real-world systems. These leakage models reflect the number of bits switching, which is assumed proportional to the power consumption. However, the actual power consumption changing in the circuits is unlikely to be directly of that form. We, therefore, propose a non-linear leakage model by mapping the existing leakage model via a transform function, by which the changing power consumption is depicted more precisely, hence the attack efficiency can be improved considerably. This has the advantage of utilising a non-linear power model while retaining the simplicity of the Hamming weight or distance models. A modified attack architecture is then suggested to yield the correct key efficiently in practice. Finally, an empirical comparison of the attack results is presented.

Automated mixed dimensional modelling from 2D and 3D CAD models

The motivation for this paper is to present procedures for automatically creating idealised finite element models from the 3D CAD solid geometry of a component. The procedures produce an accurate and efficient analysis model with little effort on the part of the user. The technique is applicable to thin walled components with local complex features and automatically creates analysis models where 3D elements representing the complex regions in the component are embedded in an efficient shell mesh representing the mid-faces of the thin sheet regions. As the resulting models contain elements of more than one dimension, they are referred to as mixed dimensional models. Although these models are computationally more expensive than some of the idealisation techniques currently employed in industry, they do allow the structural behaviour of the model to be analysed more accurately, which is essential if appropriate design decisions are to be made. Also, using these procedures, analysis models can be created automatically whereas the current idealisation techniques are mostly manual, have long preparation times, and are based on engineering judgement. In the paper the idealisation approach is first applied to 2D models that are used to approximate axisymmetric components for analysis. For these models 2D elements representing the complex regions are embedded in a 1D mesh representing the midline of the cross section of the thin sheet regions. Also discussed is the coupling, which is necessary to link the elements of different dimensionality together. Analysis results from a 3D mixed dimensional model created using the techniques in this paper are compared to those from a stiffened shell model and a 3D solid model to demonstrate the improved accuracy of the new approach. At the end of the paper a quantitative analysis of the reduction in computational cost due to shell meshing thin sheet regions demonstrates that the reduction in degrees of freedom is proportional to the square of the aspect ratio of the region, and for long slender solids, the reduction can be proportional to the aspect ratio of the region if appropriate meshing algorithms are used.

Fast and frugal models of clinical judgement in novice and expert physicians

Our objective was to study whether “compensatory” models provide better descriptions of clinical judgment than fast and frugal models, according to expertise and experience. Fifty practitioners appraised 60 vignettes describing a child with an exacerbation of asthma and rated their propensities to admit the child. Linear logistic (LL) models of their judgments were compared with a matching heuristic (MH) model that searched available cues in order of importance for a critical value indicating an admission decision. There was a small difference between the 2 models in the proportion of patients allocated correctly (admit or not-admit decisions), 91.2% and 87.8%, respectively. The proportion allocated correctly by the LL model was lower for consultants than juniors, whereas the MH model performed equally well for both. In this vignette study, neither model provided any better description of judgments made by consultants or by pediatricians compared to other grades and specialties.

Efficient Non-Linear Idealisations of Aircraft Fuselage Panels in Compression

Aircraft fuselages are complex assemblies of thousands of components and as a result simulation models are highly idealised. In the typical design process, a coarse FE model is used to determine loads within the structure. The size of the model and number of load cases necessitates that only linear static behaviour is considered. This paper reports on the development of a modelling approach to increase the accuracy of the global model, accounting for variations in stiffness due to non-linear structural behaviour. The strategy is based on representing a fuselage sub-section with a single non-linear element. Large portions of fuselage structure are represented by connecting these non-linear elements together to form a framework. The non-linear models are very efficient, reducing computational time significantly

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Energy expenditure during activity in the American lobster Homarus americanus:Correlations with body acceleration

How animals manage time and expend energy has implications for survivorship. Being able to measure key metabolic costs of animals under natural conditions is therefore an important tool in behavioral ecology. One method for estimating activity-specific metabolic rate is via derived measures of acceleration, often 'overall dynamic body acceleration' (ODBA), recorded by an instrumented acceleration logger. ODBA has been shown to correlate well with rate of oxygen consumption (V ?o) in a range of species during activity in the laboratory. This study devised a method for attaching acceleration loggers to decapod crustaceans and then correlated ODBA against concurrent respirometry readings to assess accelerometry as a proxy for activity-specific energy expenditure in a model species, the American lobster Homarus americanus. Where the instrumented animals exhibited a sufficient range of activity levels, positive linear relationships were found between V ?o and ODBA over 20min periods at a range of ambient temperatures (6, 13 and 20°C). Mixed effect linear models based on these data and morphometrics provided reasonably strong predictive power for estimating activity-specific V ?o from ODBA. These V ?o-ODBA calibrations demonstrate the potential of accelerometry as an effective predictor of behavior-specific metabolic rate of crustaceans in the wild during periods of activity. © 2013 Elsevier Inc.

Ecological differences and coexistence in a guild of microparasites: Bartonella in wild rodents

The study of ecological differences among coexisting microparasites has been largely neglected, but it addresses important and unusual issues because there is no clear distinction in such cases between conventional (resource) and apparent competition. Here patterns in the population dynamics are examined for four species of Bartonella (bacterial parasites) coexisting in two wild rodent hosts, bank voles (Clethrionomys glareolus) and wood mice (Apodemus sylvaticus). Using generalized linear modeling and mixed effects models, we examine, for these four species, seasonal patterns and dependencies on host density (both direct and delayed) and, having accounted for these, any differences in prevalence between the two hosts. Whereas previous studies had failed to uncover species differences, here all four were different. Two, B. doshiae and B. taylorii, were more prevalent in wood mice, and one, B. birtlesii, was more prevalent in bank voles. B. birtlesii, B. grahamii, and B. taylorii peaked in prevalence in the fall, whereas B. doshiae peaked in spring. For B. birtlesii in bank voles, density dependence was direct, but for B. taylorii in wood mice density dependence was delayed. B. birtlesii prevalence in wood mice was related to bank vole density. The implications of these differences for species coexistence are discussed.

Integrating personality research and animal contest theory:Aggressiveness in the green swordtail xiphophorus helleri

Aggression occurs when individuals compete over limiting resources. While theoretical studies have long placed a strong emphasis on context-specificity of aggression, there is increasing recognition that consistent behavioural differences exist among individuals, and that aggressiveness may be an important component of individual personality. Though empirical studies tend to focus on one aspect or the other, we suggest there is merit in modelling both within- and among-individual variation in agonistic behaviour simultaneously. Here, we demonstrate how this can be achieved using multivariate linear mixed effect models. Using data from repeated mirror trials and dyadic interactions of male green swordtails, Xiphophorus helleri, we show repeatable components of (co)variation in a suite of agonistic behaviour that is broadly consistent with a major axis of variation in aggressiveness. We also show that observed focal behaviour is dependent on opponent effects, which can themselves be repeatable but were more generally found to be context specific. In particular, our models show that within-individual variation in agonistic behaviour is explained, at least in part, by the relative size of a live opponent as predicted by contest theory. Finally, we suggest several additional applications of the multivariate models demonstrated here. These include testing the recently queried functional equivalence of alternative experimental approaches, (e.g., mirror trials, dyadic interaction tests) for assaying individual aggressiveness. © 2011 Wilson et al.

The impact of curricular change on medical students' knowledge of anatomy

Background: In recent years, following the publication of Tomorrow's Doctors, the undergraduate medical curriculum in most UK medical schools has undergone major revision. This has resulted in a significant reduction in the time allocated to the teaching of the basic medical sciences, including anatomy. However, it is not clear what impact these changes have had on medical students' knowledge of surface anatomy. Aim: This study aimed to assess the impact of these curricular changes on medical students' knowledge of surface anatomy. Setting: Medical student intakes for 1995-98 at the Queen's University of Belfast, UK. Methods: The students were invited to complete a simple examination paper testing their knowledge of surface anatomy. Results from the student intake of 1995, which undertook a traditional, 'old' curriculum, were compared with those from the student intakes of 1996-98, which undertook a new, 'systems-based' curriculum. To enhance linear response and enable the use of linear models for analysis, all data were adjusted using probit transformations of the proportion (percentage) of correct answers for each item and each year group. Results: The student intake of 1995 (old curriculum) were more likely to score higher than the students who undertook the new, systems-based curriculum. Conclusion: The introduction of the new, systems-based course has had a negative impact on medical students' knowledge of surface anatomy.

Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

Neural network based control for synchronous generators

In this paper, a Radial Basis Function neural network based AVR is proposed. A control strategy which generates local linear models from a global neural model on-line is used to derive controller feedback gains based on the Generalised Minimum Variance technique. Testing is carried out on a micromachine system which enables evaluation of practical implementation of the scheme. Constraints imposed by gathering training data, computational load, and memory requirements for the training algorithm are addressed.

Explaining young mortality

Stochastic modeling of mortality rates focuses on fitting linear models to logarithmically adjusted mortality data from the middle or late ages. Whilst this modeling enables insurers to project mortality rates and hence price mortality products it does not provide good fit for younger aged mortality. Mortality rates below the early 20's are important to model as they give an insight into estimates of the cohort effect for more recent years of birth. It is also important given the cumulative nature of life expectancy to be able to forecast mortality improvements at all ages. When we attempt to fit existing models to a wider age range, 5-89, rather than 20-89 or 50-89, their weaknesses are revealed as the results are not satisfactory. The linear innovations in existing models are not flexible enough to capture the non-linear profile of mortality rates that we see at the lower ages. In this paper we modify an existing 4 factor model of mortality to enable better fitting to a wider age range, and using data from seven developed countries our empirical results show that the proposed model has a better fit to the actual data, is robust, and has good forecasting ability.

Accounting for the effects of lipids in stable isotope (δ13C and δ15N values) analysis of skin and blubber of balaenopterid whales

RATIONALE Stable isotope values (d¹³C and d¹⁵N) of darted skin and blubber biopsies can shed light on habitat use and diet of cetaceans, which are otherwise difficult to study. Non-dietary factors affect isotopic variability, chiefly the depletion of C due to the presence of C-rich lipids. The efficacy of post hoc lipid-correction models (normalization) must be tested. METHODS For tissues with high natural lipid content (e.g., whale skin and blubber), chemical lipid extraction or normalization is necessary. C:N ratios, d¹³C values and d¹⁵N values were determined for duplicate control and lipid-extracted skin and blubber of fin (Balaenoptera physalus), humpback (Megaptera novaeangliae) and minke whales (B. acutorostrata) by continuous-flow elemental analysis isotope ratio mass spectrometry (CF-EA-IRMS). Six different normalization models were tested to correct d¹³C values for the presence of lipids. RESULTS Following lipid extraction, significant increases in d¹³C values were observed for both tissues in the three species. Significant increases were also found for d¹⁵N values in minke whale skin and fin whale blubber. In fin whale skin, the d¹⁵N values decreased, with no change observed in humpback whale skin. Non-linear models generally out-performed linear models and the suitability of models varied by species and tissue, indicating the need for high model specificity, even among these closely related taxa. CONCLUSIONS Given the poor predictive power of the models to estimate lipid-free d13C values, and the unpredictable changes in d N values due to lipid-extraction, we recommend against arithmetical normalization in accounting for lipid effects on d13C values for balaenopterid skin or blubber samples. Rather, we recommend that duplicate analysis of lipid-extracted (d13C values) and non-treated tissues (d15N values) be used. Copyright © 2012 John Wiley & Sons, Ltd.

Organizational culture predicts job satisfaction and perceived clinical effectiveness in pediatric primary care practices

Background: In recent years, there has been a growing understanding that organizational culture is related to an organization's performance. However, fewstudies have examined organizational culture in medical group practices. Objectives: The purpose of this study was to examine the relationship of organizational culture on provider job satisfaction and perceived clinical effectiveness in primary care pediatric practices. Research Design: This cross-sectional study included 36 primary care pediatric practices located in Connecticut. Participants: There were 374 participants in this study, which included 127 clinicians and 247 nonclinicians. Measures: Office managers completed a questionnaire that recorded staff and practice characteristics; all participants completed the Organizational Culture Scale, a questionnaire that assessed the practice on four cultural domains (i.e., group, developmental, rational, and hierarchical), and the Primary Care Organizational Questionnaire that evaluated perceived effectiveness and job satisfaction. Results: Hierarchical linear models using a restricted maximum likelihood estimation method were used to evaluate whether the practice culture types predicted job satisfaction and perceived effectiveness. Group culture was positively associated with both satisfaction and perceived effectiveness. In contrast, hierarchical and rational culture were negatively associated with both job satisfaction and perceived effectiveness. These relationships were true for clinicians, nonclinicians, and the practice as a whole. Conclusions: Our study demonstrates that practice culture is associated with job satisfaction and perceived clinical effectiveness and that a group culture was associated with high job satisfaction and perceived effectiveness. Copyright © 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins.