Graph Wavelets for Spatial Traffic Analysis

A number of problems in network operations and engineering call for new methods of traffic analysis. While most existing traffic analysis methods are fundamentally temporal, there is a clear need for the analysis of traffic across multiple network links — that is, for spatial traffic analysis. In this paper we give examples of problems that can be addressed via spatial traffic analysis. We then propose a formal approach to spatial traffic analysis based on the wavelet transform. Our approach (graph wavelets) generalizes the traditional wavelet transform so that it can be applied to data elements connected via an arbitrary graph topology. We explore the necessary and desirable properties of this approach and consider some of its possible realizations. We then apply graph wavelets to measurements from an operating network. Our results show that graph wavelets are very useful for our motivating problems; for example, they can be used to form highly summarized views of an entire network's traffic load, to gain insight into a network's global traffic response to a link failure, and to localize the extent of a failure event within the network.

Solder life prediction in a thermal analysis software environment

This paper describes recent developments made to the stress analysis module within FLOTHERM, extending its capability to handle viscoplastic behavior. It also presents the validation of this approach and results obtained for an SMT resistor as an illustrative example. Lifetime predictions are made using the creep strain energy based models of Darveaux. Comment is made about the applicability of the damage model to the geometry of the joint under study.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.

No or only population-specific effect of PON1 on human longevity: A comprehensive meta-analysis

Paraoxonase 1 (PON1) has been suggested as a plausible candidate gene for human longevity due to its modulation of cardiovascular disease risk, by preventing oxidation of atherogenic low-density lipoprotein. The role of the PON1 192 Q/R polymorphism has been analyzed for association with survival at old age in several populations, albeit with controversial results. To reconcile the conflicting evidence, we performed a large association study with two samples of 2357 Germans and 1025 French, respectively. We combined our results with those from seven previous studies in the largest and most comprehensive meta-analysis on PON1 192 Q/R and longevity to-date, to include a total of 9580 individuals. No significant association of PON1 192 Q/R with longevity was observed, for either R allele or carriership. This finding relied on very large sample sizes, is supported by different analysis methods and is therefore considered very robust. Moreover, we have investigated a potential interaction of PON1 192 Q/R with APOE epsilon4 using data from four populations. Whereas a significant result was found in the German sample, this could not be confirmed in the other examined groups. Our large-scale meta-analysis provided no evidence that the PON1 192 Q/R polymorphism is associated with longevity, but this does not exclude the possibility of population-specific effects due to the influence of, and interaction between, different genetic and/or environmental factors (e.g. diet).

DESIGN, ANALYSIS, AND RELIABILTY OF SOLAR PANEL ROTATION MECHANISM FOR MICROSATELLITE

Solar array rotation mechanism provides a hinged joint between the solar panel and satellite body, smooth rotation of the solar array into deployed position and its fixation in this position. After unlocking of solar panel (while in orbit), rotation bracket turns towards ready-to-work position under the action of driving spring. During deployment, once reached the required operating angle (defined by power subsystem engineer), the rotation bracket collides with the fixed bracket that is mounted on body of the satellite, to stop rotation. Due to the effect of collision force that may alter the rotation mechanism function, design of centrifugal brake is essential. At stoppage moment micro-switches activate final position sensor and a stopper locks the rotation bracket. Design of spring and centrifugal brake components, static finite element stress analysis of primary structure body of rotation mechanism at stoppage moment have been obtained. Last, reliability analysis of rotation mechanism is evaluated. The benefit of this study is to aid in the design of rotation mechanism that can be used in micro-satellite applications.

Assessment Method for a Power Analysis to Identify Differentially Expressed Pathways

Gene expression data can provide a very rich source of information for elucidating the biological function on the pathway level if the experimental design considers the needs of the statistical analysis methods. The purpose of this paper is to provide a comparative analysis of statistical methods for detecting the differentially expression of pathways (DEP). In contrast to many other studies conducted so far, we use three novel simulation types, producing a more realistic correlation structure than previous simulation methods. This includes also the generation of surrogate data from two large-scale microarray experiments from prostate cancer and ALL. As a result from our comprehensive analysis of 41,004 parameter configurations, we find that each method should only be applied if certain conditions of the data from a pathway are met. Further, we provide method-specific estimates for the optimal sample size for microarray experiments aiming to identify DEP in order to avoid an underpowered design. Our study highlights the sensitivity of the studied methods on the parameters of the system. © 2012 Tripahti and Emmert-Streib.

Analysing partial ranks by using smoothed paired comparison methods:An investigation of value orientation in Europe

This paper introduces the paired comparison model as a suitable approach for the analysis of partially ranked data. For example, the Inglehart index, collected in international social surveys to examine shifts in post-materialistic values, generates such data on a set of attitude items. However, current analysis methods have failed to account for the complex shifts in individual item values, or to incorporate subject covariates. The paired comparison model is thus developed to allow for covariate subject effects at the individual level, and a reparameterization allows the inclusion of smooth non-linear effects of continuous covariates. The Inglehart index collected in the 1993 International Social Science Programme survey is analysed, and complex non-linear changes of item values with age, level of education and religion are identified. The model proposed provides a powerful tool for social scientists.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

Wear analysis and prediction of the life of a riveting die used in the automotive industry

Knowledge on the life span of the riveting dies used in the automotive industry is sparse. It is often the case that only when faulty products are produced are workers aware that their tool needs to be changed. This is of course costly both in terms of time and money. Responding to this challenge, this paper proposes a methodology which integrates wear and stress analysis to quantify the life of a riveting die. Experiments are carried out to measure the applied load required to split a rivet. The obtained results (i.e. force curves) are used to validate the wear mechanisms of the die observed using scanning electron microscopy. Sliding, impact, and adhesive wears are observed on the riveting die after a certain number of riveting cycles. The stress distribution on the die during riveting is simulated using a finite element (FE) approach. In order to confirm the accuracy of the FE model, the experimental force results are compared with the ones produced from FE simulation. The maximum and minimum von Mises' stresses generated from the FE model are input into a Goodman diagram and an S-N curve to compute the life of the riveting die. It is found that the riveting die is predicted to run for 4 980 000 cycles before failure.

The nucleus of Comet 67P/Churyumov-Gerasimenko. A new shape model and thermophysical analysis

Context. Comet 67P/Churyumov-Gerasimenko is the target of the European Space Agency Rosetta spacecraft rendez-vous mission. Detailed physical characteristation of the comet before arrival is important for mission planning as well as providing a test bed for ground-based observing and data-analysis methods. Aims: To conduct a long-term observational programme to characterize the physical properties of the nucleus of the comet, via ground-based optical photometry, and to combine our new data with all available nucleus data from the literature. Methods: We applied aperture photometry techniques on our imaging data and combined the extracted rotational lightcurves with data from the literature. Optical lightcurve inversion techniques were applied to constrain the spin state of the nucleus and its broad shape. We performed a detailed surface thermal analysis with the shape model and optical photometry by incorporating both into the new Advanced Thermophysical Model (ATPM), along with all available Spitzer 8-24 μm thermal-IR flux measurements from the literature. Results: A convex triangular-facet shape model was determined with axial ratios b/a = 1.239 and c/a = 0.819. These values can vary by as much as 7% in each axis and still result in a statistically significant fit to the observational data. Our best spin state solution has Psid = 12.76137 ± 0.00006 h, and a rotational pole orientated at Ecliptic coordinates λ = 78°(±10°), β = + 58°(±10°). The nucleus phase darkening behaviour was measured and best characterized using the IAU HG system. Best fit parameters are: G = 0.11 ± 0.12 and HR(1,1,0) = 15.31 ± 0.07. Our shape model combined with the ATPM can satisfactorily reconcile all optical and thermal-IR data, with the fit to the Spitzer 24 μm data taken in February 2004 being exceptionally good. We derive a range of mutually-consistent physical parameters for each thermal-IR data set, including effective radius, geometric albedo, surface thermal inertia and roughness fraction. Conclusions: The overall nucleus dimensions are well constrained and strongly imply a broad nucleus shape more akin to comet 9P/Tempel 1, rather than the highly elongated or "bi-lobed" nuclei seen for comets 103P/Hartley 2 or 8P/Tuttle. The derived low thermal inertia of

A kinetic analysis methodology to elucidate the roles of metal, support and solvent for the hydrogenation of 4-phenyl-2-butanone over Pt/TiO2

The rate and, more importantly, selectivity (ketone vs aromatic ring) of the hydrogenation of 4-phenyl-2-butanone over a Pt/TiO2 catalyst have been shown to vary with solvent. In this study, a fundamental kinetic model for this multi-phase reaction has been developed incorporating statistical analysis methods to strengthen the foundations of mechanistically sound kinetic models. A 2-site model was determined to be most appropriate, describing aromatic hydrogenation (postulated to be over a platinum site) and ketone hydrogenation (postulated to be at the platinum–titania interface). Solvent choice has little impact on the ketone hydrogenation rate constant but strongly impacts aromatic hydrogenation due to solvent-catalyst interaction. Reaction selectivity is also correlated to a fitted product adsorption constant parameter. The kinetic analysis method shown has demonstrated the role of solvents in influencing reactant adsorption and reaction selectivity.

Comparative Study of Different Methods for the Prediction of Drug− Polymer Solubility

In this study, a comparison of different methods to predict drug−polymer solubility was carried out on binary systems consisting of five model drugs (paracetamol, chloramphenicol, celecoxib, indomethacin, and felodipine) and polyvinylpyrrolidone/vinyl acetate copolymers (PVP/VA) of different monomer weight ratios. The drug−polymer solubility at 25 °C was predicted using the Flory−Huggins model, from data obtained at elevated temperature using thermal analysis methods based on the recrystallization of a supersaturated amorphous solid dispersion and two variations of the melting point depression method. These predictions were compared with the solubility in the low molecular weight liquid analogues of the PVP/VA copolymer (N-vinylpyrrolidone and vinyl acetate). The predicted solubilities at 25 °C varied considerably depending on the method used. However, the three thermal analysis methods ranked the predicted solubilities in the same order, except for the felodipine−PVP system. Furthermore, the magnitude of the predicted solubilities from the recrystallization method and melting point depression method correlated well with the estimates based on the solubility in the liquid analogues, which suggests that this method can be used as an initial screening tool if a liquid analogue is available. The learnings of this important comparative study provided general guidance for the selection of the most suitable method(s) for the screening of drug−polymer solubility.

Finite Element Analysis of the Enhanced Strength of Laterally Restrained RC Slabs

This paper presents the numerical simulation of the ultimate behaviour of 85 one-way and two-way spanning laterally restrained concrete slabs of variable thickness, span, reinforcement ratio, strength and boundary conditions reported in literature by different authors. The developed numerical model was described and all the assumptions were illustrated. ABAQUS, a Finite Element Analysis suite of software, was employed. Non-linear implicit static general analysis method offered by ABAQUS was used. Other analysis methods were also discussed in general in terms of application such as Explicit Dynamic Analysis and Riks method. The aim is to demonstrate the ability and efficacy of FEA to simulate the ultimate load behaviour of slabs considering different material properties and boundary conditions. The authors intended to present a numerical model that provides consistent predictions of the ultimate behaviour of laterally restrained slabs that could be used as an alternative for expensive real life testing as well as for the design and assessment of new and existing structures respectively. The enhanced strength of laterally-restrained slabs compared with conventional design methods predictions is believed to be due to compressive membrane action (CMA). CMA is an inherent phenomenon of laterally restrained concrete beams/slabs. The numerical predictions obtained from the developed model were in good correlation with the experimental results and with those obtained from the CMA method developed at the Queen’s University Belfast, UK.

How individual participant data meta-analyses have influenced trial design, conduct, and analysis

OBJECTIVES: To demonstrate how individual participant data (IPD) meta-analyses have impacted directly on the design and conduct of trials and highlight other advantages IPD might offer.

STUDY DESIGN AND SETTING: Potential examples of the impact of IPD meta-analyses on trials were identified at an international workshop, attended by individuals with experience in the conduct of IPD meta-analyses and knowledge of trials in their respective clinical areas. Experts in the field who did not attend were asked to provide any further examples. We then examined relevant trial protocols, publications, and Web sites to verify the impacts of the IPD meta-analyses. A subgroup of workshop attendees sought further examples and identified other aspects of trial design and conduct that may inform IPD meta-analyses.

RESULTS: We identified 52 examples of IPD meta-analyses thought to have had a direct impact on the design or conduct of trials. After screening relevant trial protocols and publications, we identified 28 instances where IPD meta-analyses had clearly impacted on trials. They have influenced the selection of comparators and participants, sample size calculations, analysis and interpretation of subsequent trials, and the conduct and analysis of ongoing trials, sometimes in ways that would not possible with systematic reviews of aggregate data. We identified additional potential ways that IPD meta-analyses could be used to influence trials.

CONCLUSIONS: IPD meta-analysis could be better used to inform the design, conduct, analysis, and interpretation of trials.

Modelling and aerodynamic simulation of a vehicle and failure analysis of a laminated front fender

Master Thesis in Mechanical Engineering field of Maintenance and Production