Development of a Model for the Ice Scraping Process Iowa Department of Transportation Project HR 361 Final Report, October 1996

A laboratory study has been conducted with two aims in mind. The first goal was to develop a description of how a cutting edge scrapes ice from the road surface. The second goal was to investigate the extent, if any, to which serrated blades were better than un-serrated or "classical" blades at ice removal. The tests were conducted in the Ice Research Laboratory at the Iowa Institute of Hydraulic Research of the University of Iowa. A specialized testing machine, with a hydraulic ram capable of attaining scraping velocities of up to 30 m.p.h. was used in the testing. In order to determine the ice scraping process, the effects of scraping velocity, ice thickness, and blade geometry on the ice scraping forces were determined. Higher ice thickness lead to greater ice chipping (as opposed to pulverization at lower thicknesses) and thus lower loads. S~milabr ehavior was observed at higher velocities. The study of blade geometry included the effect of rake angle, clearance angle, and flat width. The latter were found to be particularly important in developing a clear picture of the scraping process. As clearance angle decreases and flat width increases, the scraping loads show a marked increase, due to the need to re-compress pulverized ice fragments. The effect of serrations was to decrease the scraping forces. However, for the coarsest serrated blades (with the widest teeth and gaps) the quantity of ice removed was significantly less than for a classical blade. Finer serrations appear to be able to match the ice removal of classical blades at lower scraping loads. Thus, one of the recommendations of this study is to examine the use of serrated blades in the field. Preliminary work (by Nixon and Potter, 1996) suggests such work will be fruitful. A second and perhaps more challenging result of the study is that chipping of ice is more preferable to pulverization of the ice. How such chipping can be forced to occur is at present an open question.

Cutting edge: cell autonomous rather than environmental factors control bacterial superantigen-induced T cell anergy in vivo.

Anergic T cells display a marked decrease in their ability to produce IL-2 and to proliferate in the presence of an appropriate antigenic signal. Two nonmutually exclusive classes of models have been proposed to explain the persistence of T cell anergy in vivo. While some reports indicate that anergic T cells have intrinsic defects in signaling pathways or transcriptional activities, other studies suggest that anergy is maintained by environmental "suppressor" factors such as cytokines or Abs. To distinguish between these conflicting hypotheses, we employed the well-characterized bacterial superantigen model system to evaluate in vivo the ability of a trace population of adoptively transferred naive or anergized T cells to proliferate in a naive vs anergic environment upon subsequent challenge. Our data clearly demonstrate that bacterial superantigen-induced T cell anergy is cell autonomous and independent of environmental factors.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Model for managing non-core ideas to new companies, products and services in a Finnish forest company

Suomalainen metsäteollisuus on muutoksen partaalla. Uutisissa on nähty miten metsäyrityksen sulkevat tehtaita ja paperikoneita. Suomalaisessa metsäteollisuudessa keskitytään tällä hetkellä lähinnä kulujen alentamiseen ja tuottavuuden parantamiseen. Edellytyssille, että suomalainen metsäteollisuus pysyy kilpailukykyisenä, ovat kuitenkinuudet innovaatiot ja toimialojen välinen yhteistyö. Työn tavoitteena oli luoda toimintamalli UPM-Kymmene Oyj:lle, minkä avulla ydinliiketoimintaan kuulumattomat tuote- ja palveluideat saataisiin hyödynnettyä. Aihe on erittäin ajankohtainen, mikäli halutaan pitää tuotanto jatkossakin Suomessa. Luotumalli painottaa pk-sektorin roolia ja potentiaalia kehittää UPM-Kymmeneltä peräisin olevia ja heidän ydinliiketointaan kuulumattomista tuote ja palveluideoistauusia yrityksiä, tuotteita ja palveluita. Malli edustaa uudenlaista ajattelutapaa ja sen käyttöönotto vaatii perinteisen yrityskulttuurin uudistamista UPM-Kymmenessä.

A comprehensive model for quantum noise characterization in digital mammography.

NlmCategory="UNASSIGNED">A version of cascaded systems analysis was developed specifically with the aim of studying quantum noise propagation in x-ray detectors. Signal and quantum noise propagation was then modelled in four types of x-ray detectors used for digital mammography: four flat panel systems, one computed radiography and one slot-scan silicon wafer based photon counting device. As required inputs to the model, the two dimensional (2D) modulation transfer function (MTF), noise power spectra (NPS) and detective quantum efficiency (DQE) were measured for six mammography systems that utilized these different detectors. A new method to reconstruct anisotropic 2D presampling MTF matrices from 1D radial MTFs measured along different angular directions across the detector is described; an image of a sharp, circular disc was used for this purpose. The effective pixel fill factor for the FP systems was determined from the axial 1D presampling MTFs measured with a square sharp edge along the two orthogonal directions of the pixel lattice. Expectation MTFs were then calculated by averaging the radial MTFs over all possible phases and the 2D EMTF formed with the same reconstruction technique used for the 2D presampling MTF. The quantum NPS was then established by noise decomposition from homogenous images acquired as a function of detector air kerma. This was further decomposed into the correlated and uncorrelated quantum components by fitting the radially averaged quantum NPS with the radially averaged EMTF(2). This whole procedure allowed a detailed analysis of the influence of aliasing, signal and noise decorrelation, x-ray capture efficiency and global secondary gain on NPS and detector DQE. The influence of noise statistics, pixel fill factor and additional electronic and fixed pattern noises on the DQE was also studied. The 2D cascaded model and decompositions performed on the acquired images also enlightened the observed quantum NPS and DQE anisotropy.

Orthogonal function method in modelling paper web quality variation

This work is devoted to the analysis of signal variation of the Cross-Direction and Machine-Direction measurements from paper web. The data that we possess comes from the real paper machine. Goal of the work is to reconstruct the basis weight structure of the paper and to predict its behaviour to the future. The resulting synthetic data is needed for simulation of paper web. The main idea that we used for describing the basis weight variation in the Cross-Direction is Empirical Orthogonal Functions (EOF) algorithm, which is closely related to Principal Component Analysis (PCA) method. Signal forecasting in time is based on Time-Series analysis. Two principal mathematical procedures that we used in the work are Autoregressive-Moving Average (ARMA) modelling and Ornstein–Uhlenbeck (OU) process.

On the numerical simulation of machining processes

Numerical simulation of machining processes can be traced back to the early seventies when finite element models for continuous chip formation were proposed. The advent of fast computers and development of new techniques to model large plastic deformations have favoured machining simulation. Relevant aspects of finite element simulation of machining processes are discussed in this paper, such as solution methods, material models, thermo-mechanical coupling, friction models, chip separation and breakage strategies and meshing/re-meshing strategies.

Comparison of model-based above ground biomass predictions from LiDAR

In order to reduce greenhouse emissions from forest degradation and deforestation the international programme REDD (Reducing Emissions from Deforestation and forest Degradation) was established in 2005 by the United Nations Framework Convention on Climate Change (UNFCCC). This programme is aimed to financially reward to developing countries for any emissions reductions. Under this programm the project of setting up the payment system in Nepal was established. This project is aimed to engage local communities in forest monitoring. The major objective of this thesis is to compare and verify data obtained from di erect sources - remotely sensed data, namely LiDAR and field sample measurements made by two groups of researchers using two regression models - Sparse Bayesian Regression and Bayesian Regression with Orthogonal Variables.

Intelligence acquisition methods in cyber domain : examining the circumstantial applicability of cyber intelligence acquisition methods using a hierarchical model

Phenomena in cyber domain, especially threats to security and privacy, have proven an increasingly heated topic addressed by different writers and scholars at an increasing pace – both nationally and internationally. However little public research has been done on the subject of cyber intelligence. The main research question of the thesis was: To what extent is the applicability of cyber intelligence acquisition methods circumstantial? The study was conducted in sequential a manner, starting with defining the concept of intelligence in cyber domain and identifying its key attributes, followed by identifying the range of intelligence methods in cyber domain, criteria influencing their applicability, and types of operatives utilizing cyber intelligence. The methods and criteria were refined into a hierarchical model. The existing conceptions of cyber intelligence were mapped through an extensive literature study on a wide variety of sources. The established understanding was further developed through 15 semi-structured interviews with experts of different backgrounds, whose wide range of points of view proved to substantially enhance the perspective on the subject. Four of the interviewed experts participated in a relatively extensive survey based on the constructed hierarchical model on cyber intelligence that was formulated in to an AHP hierarchy and executed in the Expert Choice Comparion online application. It was concluded that Intelligence in cyber domain is an endorsing, cross-cutting intelligence discipline that adds value to all aspects of conventional intelligence and furthermore that it bears a substantial amount of characteristic traits – both advantageous and disadvantageous – and furthermore that the applicability of cyber intelligence methods is partly circumstantially limited.

Post-transaction brand and model line-up integration in the automotive industry: Case studies of European companies as target of acquisitions by Chinese and Indian multinational corporations

Corporations practice company acquisitions in order to create shareholder’s value. During the last few decades, the companies in emerging markets have become active in the acquisition business. During the last decade, large and significant acquisitions have occurred especially in automotive industry. While domestic markets have become too competitive and companies are lacking required capabilities, they seek possibilities to expand into Western markets by attaining valuable assets through acquisitions of developed country corporations. This study discusses the issues and characteristics of these acquisitions through case studies. The purpose of this study was to identify the acquisition motives and strategies for post-transaction brand and product integration as well as analyze the effect of the motives to the integration strategy. The cases chosen for the research were Chinese Geely acquiring Swedish Volvo in 2010 and Indian Tata Motors buying British Jaguar Land Rover in 2008. The main topics were chosen according to their significance for companies in automotive industry as well as those are most visible parts for consumers. The study is based on qualitative case study methods, analyzing secondary data from academic papers and news articles as well as companies’ own announcements e.g. stock exchange and press releases. The study finds that the companies in the cases mainly possessed asset-seeking and market-seeking motives. In addition, the findings refer to rather minimal post-acquisition brand and product integration strategies. Mainly the parent companies left the target company autonomous to make their own business strategies and decisions. The most noticeable integrations were in the product development and production processes. Through restructuring the product architectures, the companies were able to share components and technology between product families and brands, which results in cutting down costs and in increase of profitability and efficiency. In the Geely- Volvo case, the strategy focused more on component sharing and product development know-how, whereas in Tata Motors-Jaguar Land Rover case, the main actions were to cut down costs through component sharing and combine production and distribution networks especially in Asian markets. However, it was evident that in both cases the integration and technology sharing were executed cautiously to prevent on harming the valuable image of the luxury brand. This study has concluded that the asset-seeking motives have significant influence on the posttransaction brand and model line-up integration strategies. By taking a cautious approach in acquiring assets, such as luxury brand, the companies in the cases have implemented a successful post-acquisition strategy and managed to create value for the shareholders at least in short-term. Yritykset harjoittavat yritysostoja luodakseen osakkeenomistajille lisäarvoa. Viimeisten muutamien vuosikymmenien aikana yritykset kehittyvissä maissa ovat myös aktivoituneet yritysostoissa. Viimeisen vuosikymmenen aikana erityisesti autoteollisuudessa on esiintynyt suuria ja merkittäviä yritysostoja. Koska kilpailu kotimaan markkinoilla on kiristynyt ja yritykset ovat vailla vaadittavia valmiuksia, ne etsivät mahdollisuuksiaan laajentaa länsimaisiin markkinoihin hankkimalla arvokkaita etuja kehittyneiden maiden yrityksistä yritysostojen avulla. Tämä tutkimus pohtii näiden yritysostojen olennaisia kysymyksiä ja ominaisuuksia casetutkimuksien kautta. Tutkimuksen tarkoitus oli tunnistaa sekä yritysostojen motiiveja ja brändi- ja mallisto-integraation strategioita että analysoida kyseisten motiivien vaikutusta integraatiostrategiaan. Tapaus-tutkimuksiksi valittiin kiinalaisen Geelyn yritysosto ruotsalaisesta Volvosta vuonna 2010 ja intialaisen Tata Motorsin yritysosto englantilaisesta Jaguar Land Roverista vuonna 2008. Tutkimus on kvalitatiivinen case-tutkimus ja siinä analysoidaan toissijaista tietoa sekä akateemisten ja uutisartikkeleiden että yritysten omien ilmoitusten, kuten pörssi- ja lehdistötiedotteiden, kautta. Tutkimuksen tulokset osoittavat, että tutkittujen yritysten toiminnat perustuivat motiiveihin, joita ajoivat etujen and uusien markkinoiden tarve. Sen lisäksi tutkimustulokset osoittivat, että yritysoston jälkeinen brändi- ja mallisto-integraatio pidettiin minimaalisena. Pääasiallisesti kohdeyrityksille jätettiin autonomia tehdä omat liikkeenjohdolliset päätökset yritysstrategioihin liittyen. Huomattavimmat integraatiot koskivat tuotekehityksellisiä ja tuotannollisia prosesseja. Kehittämällä uudelleen tuotearkkitehtuureja, yritykset pystyivät jakamaan komponentteja ja teknologiaa tuoteperheiden ja brändien välillä. Tämä mahdollisti kustannusleikkauksia sekä kannattavuuden ja tehokkuuden parantamista. Geely-Volvo –tapauksessa integraatiostrategia keskittyi komponenttien jakamiseen yhteisten tuotearkkitehtuurien avulla ja tuotekehityksen ammattitaitoon, kun taas Tata Motors-JLR –tapauksessa päätoiminnat olivat kustannuksien leikkaus sekä tuotannon ja jakeluverkoston yhdistäminen erityisesti Aasian maissa. Yhteistä yrityskaupoissa oli, että brändi- ja mallisto-integraatio sekä teknologian jakaminen suoritettiin varoen ehkäistäkseen arvokkaiden luksus-brändien tuotekuvan vahingoittamista. Tutkimuksen lopputulokset osoittavat, että yrityskaupan motiiveilla on huomattava vaikutus brändija mallisto-integraation strategiaan. Toteuttamalla varovaista lähestymistapaa luksus-brändin hankinnassa ja integraatiossa, yritykset ovat onnistuneet luomaan lisäarvoa osakkeenomistajille vähintään lyhyellä aikavälillä.

Variability of the Atlantic thermohaline circulation described by three-dimensional empirical orthogonal functions

We describe the use of bivariate 3d empirical orthogonal functions (EOFs) in characterising low frequency variability of the Atlantic thermohaline circulation (THC) in the Hadley Centre global climate model, HadCM3. We find that the leading two modes are well correlated with an index of the meridional overturning circulation (MOC) on decadal timescales, with the leading mode alone accounting for 54% of the decadal variance. Episodes of coherent oscillations in the sub-space of the leading EOFs are identified; these episodes are of great interest for the predictability of the THC, and could indicate the existence of different regimes of natural variability. The mechanism identified for the multi-decadal variability is an internal ocean mode, dominated by changes in convection in the Nordic Seas, which lead the changes in the MOC by a few years. Variations in salinity transports from the Arctic and from the North Atlantic are the main feedbacks which control the oscillation. This mode has a weak feedback onto the atmosphere and hence a surface climatic influence. Interestingly, some of these climate impacts lead the changes in the overturning. There are also similarities to observed multi-decadal climate variability.

Three-level main-effects designs exploiting prior information about model uncertainty

To explore the projection efficiency of a design, Tsai, et al [2000. Projective three-level main effects designs robust to model uncertainty. Biometrika 87, 467-475] introduced the Q criterion to compare three-level main-effects designs for quantitative factors that allow the consideration of interactions in addition to main effects. In this paper, we extend their method and focus on the case in which experimenters have some prior knowledge, in advance of running the experiment, about the probabilities of effects being non-negligible. A criterion which incorporates experimenters' prior beliefs about the importance of each effect is introduced to compare orthogonal, or nearly orthogonal, main effects designs with robustness to interactions as a secondary consideration. We show that this criterion, exploiting prior information about model uncertainty, can lead to more appropriate designs reflecting experimenters' prior beliefs. (c) 2006 Elsevier B.V. All rights reserved.

Fracture toughness and cutting

An exploratory model for cutting is presented which incorporates fracture toughness as well as the commonly considered effects of plasticity and friction. The periodic load fluctuations Been in cutting force dynamometer tests are predicted, and considerations of chatter and surface finish follow. A non-dimensional group is put forward to classify different regimes of material response to machining. It leads to tentative explanations for the difficulties of cutting materials such as ceramics and brittlo polymers, and also relates to the formation of discontinuous chips. Experiments on a range of solids with widely varying toughness/strength ratios generally agree with the analysis.

Toughness & oblique metalcutting

The implications of whether new surfaces in cutting are formed just by plastic flow past the tool or by some fracturelike separation process involving significant surface work, are discussed. Oblique metalcutting is investigated using the ideas contained in a new algebraic model for the orthogonal machining of metals (Atkins, A. G., 2003, "Modeling Metalcutting Using Modern Ductile Fracture Mechanics: Quantitative Explanations for Some Longstanding Problems," Int. J. Mech. Sci., 45, pp. 373–396) in which significant surface work (ductile fracture toughnesses) is incorporated. The model is able to predict explicit material-dependent primary shear plane angles and provides explanations for a variety of well-known effects in cutting, such as the reduction of at small uncut chip thicknesses; the quasilinear plots of cutting force versus depth of cut; the existence of a positive force intercept in such plots; why, in the size-effect regime of machining, anomalously high values of yield stress are determined; and why finite element method simulations of cutting have to employ a "separation criterion" at the tool tip. Predictions from the new analysis for oblique cutting (including an investigation of Stabler's rule for the relation between the chip flow velocity angle C and the angle of blade inclination i) compare consistently and favorably with experimental results.

Probability density function estimation using orthogonal forward regression

Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression technique is adopted to construct sparse kernel density estimates. The proposed algorithm incrementally minimises a leave-one-out test error score to select a sparse kernel model, and a local regularisation method is incorporated into the density construction process to further enforce sparsity. The kernel weights are finally updated using the multiplicative nonnegative quadratic programming algorithm, which has the ability to reduce the model size further. Except for the kernel width, the proposed algorithm has no other parameters that need tuning, and the user is not required to specify any additional criterion to terminate the density construction procedure. Two examples are used to demonstrate the ability of this regression-based approach to effectively construct a sparse kernel density estimate with comparable accuracy to that of the full-sample optimised Parzen window density estimate.