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Fallibility at Work: Rethinking Excellence and Error in Organizations

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ISBN: 9783319633176 9783319633183 Year: Pages: 159 DOI: https://doi.org/10.1007/978-3-319-63318-3 Language: English
Publisher: Palgrave Macmillan
Subject: Business and Management
Added to DOAB on : 2017-11-23 18:18:06
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This book addresses how organizations can deal with human fallibility in order to create space for excellence at work. Some mistakes in work settings put lives at risk, while others create openings for innovative breakthroughs. In order to deal constructively with fallibility, an organization needs a communication climate where it is normal to voice opinions, admit mistakes, and ask for help in critical situations. The book builds on interviews with practitioners in healthcare, aviation, IT, public governance, and industry. It connects narratives from these fields with theories from organizational psychology and philosophy, as well as from positive organizational scholarship. In the final chapter, an overall ethics of fallibility at work is outlined. Fallibility at Work contributes to research in multiple academic disciplines, but also reaches out to practitioners who are interested in the connections between error and excellence in organizations.

Psychological Responses to Violations of Expectations: Perspectives and Answers from Diverse Fields of Psychology

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889454457 Year: Pages: 236 DOI: 10.3389/978-2-88945-445-7 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Psychology
Added to DOAB on : 2018-11-16 17:17:57
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From Pavlov's dog expecting food when hearing a bell to stereotypes as expectations about other people’s behaviour, from Bandura’s self-efficacy as expectation for success and failure of one’s own behaviour to the "predictive brain" concept in current perception theories: expectations have been a central construct in different areas of psychological research. In each of these areas, specific concepts, theoretical approaches, and empirical methods have been developed to explain when and why expectations persist and when they do not. Many theories assume that expectations are likely to change in the face of disconfirming evidence. However, sometimes expectations persist even though they are empirically violated, suggesting that they can be “sticky” under certain circumstances. But what are these circumstances? And what are the psychological mechanisms that can explain why and when expectations persist or change after being confronted with expectation-violating evidence?Each contribution of the current book offers insights into individuals’ reactions to violations of expectations. They show that many pieces of the puzzle have been collected in the many sub-displiclines of psychology and that putting them together in an integrative fashion stays a fascinating enterprise.

Partikeldetektion in mikrofluidischen Systemen

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ISBN: 9783731503644 Year: Pages: XI, 305 p. DOI: 10.5445/KSP/1000046492 Language: GERMAN
Publisher: KIT Scientific Publishing
Subject: Technology (General)
Added to DOAB on : 2019-07-30 20:01:59
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Analysis of microparticles is an important tool in medicine, biology and chemistry. In order to address future application areas, new systems will be produced by printing technology. In this work new microfluidic particle detection systems which employ planar optics are developed and analyzed. Because the characteristic of these new systems differs greatly from established particle detection systems the signals and statistics are analyzed in depth.

Visual Mismatch Negativity (vMMN) a Prediction Error Signal in the Visual Modality

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889195602 Year: Pages: 202 DOI: 10.3389/978-2-88919-560-2 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2016-01-19 14:05:46
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Current theories of visual change detection emphasize the importance of conscious attention to detect unexpected changes in the visual environment. However, an increasing body of studies shows that the human brain is capable of detecting even small visual changes, especially if such changes violate non-conscious probabilistic expectations based on repeating experiences. In other words, our brain automatically represents statistical regularities of our visual environmental. Since the discovery of the auditory mismatch negativity (MMN) event-related potential (ERP) component, the majority of research in the field has focused on auditory deviance detection. Such automatic change detection mechanisms operate in the visual modality too, as indicated by the visual mismatch negativity (vMMN) brain potential to rare changes. VMMN is typically elicited by stimuli with infrequent (deviant) features embedded in a stream of frequent (standard) stimuli, outside the focus of attention. In this research topic we aim to present vMMN as a prediction error signal. Predictive coding theories account for phenomena such as mismatch negativity and repetition suppression, and place them in a broader context of a general theory of cortical responses. A wide range of vMMN studies has been presented in this Research Topic. Twelve articles address roughly four general sub-themes including attention, language, face processing, and psychiatric disorders. Additionally, four articles focused on particular subjects such as the oblique effect, object formation, and development and time-frequency analysis of vMMN. Furthermore, a review paper presented vMMN in a hierarchical predictive coding framework. Each paper in this Research Topic is a valuable contribution to the field of automatic visual change detection and deepens our understanding of the short term plasticity underlying predictive processes of visual perceptual learning.

Design and Applications of Coordinate Measuring Machines

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ISBN: 9783038422761 9783038422778 Year: Pages: XII, 198 DOI: 10.3390/books978-3-03842-277-8 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: General and Civil Engineering
Added to DOAB on : 2016-11-11 18:50:12
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Coordinate measuring machines (CMMs) have been conventionally used in industry for 3-dimensional and form-error measurements of macro parts for many years. Ever since the first CMM, developed by Ferranti Co. in the late 1950s, they have been regarded as versatile measuring equipment, yet many CMMs on the market still have inherent systematic errors due to the violation of the Abbe Principle in its design. Current CMMs are only suitable for part tolerance above 10 μm. With the rapid advent of ultraprecision technology, multi-axis machining, and micro/nanotechnology over the past twenty years, new types of ultraprecision and micro/nao-CMMs are urgently needed in all aspects of society.This Special Issue accepted papers revealing novel designs and applications of CMMs, including structures, probes, miniaturization, measuring paths, accuracy enhancement, error compensation, etc. Detailed design principles in sciences, and technological applications in high-tech industries, were required for submission.Topics covered, but were not limited to, the following areas:1.New types of CMMs, such as Abbe-free, multi-axis, cylindrical, parallel, etc.2.New types of probes, such as touch-trigger, scanning, hybrid, non-contact, microscopic, etc.3.New types of Micro/nano-CMMs.4.New types of measuring path strategy, such as collision avoidance, free-form surface, aspheric surface, etc.5.New types of error compensation strategy.

Computational Aerodynamic Modeling of Aerospace Vehicles

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ISBN: 9783038976103 Year: Pages: 294 DOI: 10.3390/books978-3-03897-611-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Transportation
Added to DOAB on : 2019-03-08 11:42:05
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Currently, the use of computational fluid dynamics (CFD) solutions is considered as the state-of-the-art in the modeling of unsteady nonlinear flow physics and offers an early and improved understanding of air vehicle aerodynamics and stability and control characteristics. This Special Issue covers recent computational efforts on simulation of aerospace vehicles including fighter aircraft, rotorcraft, propeller driven vehicles, unmanned vehicle, projectiles, and air drop configurations. The complex flow physics of these configurations pose significant challenges in CFD modeling. Some of these challenges include prediction of vortical flows and shock waves, rapid maneuvering aircraft with fast moving control surfaces, and interactions between propellers and wing, fluid and structure, boundary layer and shock waves. Additional topic of interest in this Special Issue is the use of CFD tools in aircraft design and flight mechanics. The problem with these applications is the computational cost involved, particularly if this is viewed as a brute-force calculation of vehicle’s aerodynamics through its flight envelope. To make progress in routinely using of CFD in aircraft design, methods based on sampling, model updating and system identification should be considered.

Keywords

wake --- bluff body --- square cylinder --- DDES --- URANS --- turbulence model --- large eddy simulation --- Taylor–Green vortex --- numerical dissipation --- modified equation analysis --- truncation error --- MUSCL --- dynamic Smagorinsky subgrid-scale model --- kinetic energy dissipation --- computational fluid dynamics (CFD) --- microfluidics --- numerical methods --- gasdynamics --- shock-channel --- microelectromechanical systems (MEMS) --- discontinuous Galerkin finite element method (DG–FEM) --- fluid mechanics --- characteristics-based scheme --- multi-directional --- Riemann solver --- Godunov method --- bifurcation --- wind tunnel --- neural networks --- modeling --- unsteady aerodynamic characteristics --- high angles of attack --- hypersonic --- wake --- chemistry --- slender-body --- angle of attack --- detection --- after-body --- S-duct diffuser --- flow distortion --- flow control --- vortex generators --- aeroelasticity --- reduced-order model --- flutter --- wind gust responses --- computational fluid dynamics --- convolution integral --- sharp-edge gust --- reduced order aerodynamic model --- geometry --- meshing --- aerodynamics --- CPACS --- MDO --- VLM --- Euler --- CFD --- variable fidelity --- multi-fidelity --- aerodynamic performance --- formation --- VLM --- RANS --- hybrid reduced-order model --- quasi-analytical --- aeroelasticity --- flexible wings --- subsonic --- wing–propeller aerodynamic interaction --- p-factor --- installed propeller --- overset grid approach

Applied Econometrics

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ISBN: 9783038979265 / 9783038979272 Year: Pages: 222 DOI: 10.3390/books978-3-03897-927-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Mathematics
Added to DOAB on : 2019-06-26 08:44:06
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Although the theme of the monograph is primarily related to “Applied Econometrics”, there are several theoretical contributions that are associated with empirical examples, or directions in which the novel theoretical ideas might be applied. The monograph is associated with significant and novel contributions in theoretical and applied econometrics; economics; theoretical and applied financial econometrics; quantitative finance; risk; financial modeling; portfolio management; optimal hedging strategies; theoretical and applied statistics; applied time series analysis; forecasting; applied mathematics; energy economics; energy finance; tourism research; tourism finance; agricultural economics; informatics; data mining; bibliometrics; and international rankings of journals and academics.

Keywords

inflation --- postage stamps --- price recovery --- historical time series --- EGARCH --- FHA loan --- home mortgage --- foreclosure --- default and prepayment --- unobserved heterogeneity --- duration models --- competing risks --- earnings forecasts --- earnings announcements --- financial markets --- financial analysts --- nonparametric time series modeling --- nonlinearity --- unified time series algorithm --- exploratory diagnostics --- control environment --- budgetary system and strategies --- operational control --- company performance --- economic growth --- economic freedom --- foreign direct investment --- panel data --- cash payments --- efficiency --- denomination range --- JEL Classification --- E42 --- E58 --- managing of financial health --- risk of bankruptcy --- prediction methods --- post-communist countries --- Misery Index --- inflation --- unemployment --- Probit and Logit models --- Okun’s law --- multivariate regression models --- heavy-tailed data --- Mahalanobis distances --- maximum likelihood estimator --- independent multivariate Student distribution --- uncorrelated multivariate Student distribution --- derivatives market --- economic development --- Granger-causality tests --- vector error correction model (VECM) --- DOLS --- FMOLS --- income inequality --- economic growth --- middle income countries --- Granger causality test --- system GMM --- oil price --- exchange rate --- trade balance --- cointegration --- frequency domain causality --- Nigeria --- Fama-French factor model --- market microstructure --- trading behavior --- panel data factor model --- social network model --- risk spillover --- abnormal returns

New Developments in Statistical Information Theory Based on Entropy and Divergence Measures

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ISBN: 9783038979364 / 9783038979371 Year: Pages: 344 DOI: 10.3390/books978-3-03897-937-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Social Sciences --- Sociology --- Statistics
Added to DOAB on : 2019-06-26 08:44:06
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This book presents new and original research in Statistical Information Theory, based on minimum divergence estimators and test statistics, from a theoretical and applied point of view, for different statistical problems with special emphasis on efficiency and robustness. Divergence statistics, based on maximum likelihood estimators, as well as Wald’s statistics, likelihood ratio statistics and Rao’s score statistics, share several optimum asymptotic properties, but are highly non-robust in cases of model misspecification under the presence of outlying observations. It is well-known that a small deviation from the underlying assumptions on the model can have drastic effect on the performance of these classical tests. Specifically, this book presents a robust version of the classical Wald statistical test, for testing simple and composite null hypotheses for general parametric models, based on minimum divergence estimators.

Keywords

sparse --- robust --- divergence --- MM algorithm --- Bregman divergence --- generalized linear model --- local-polynomial regression --- model check --- nonparametric test --- quasi-likelihood --- semiparametric model --- Wald statistic --- composite likelihood --- maximum composite likelihood estimator --- Wald test statistic --- composite minimum density power divergence estimator --- Wald-type test statistics --- Bregman divergence --- general linear model --- hypothesis testing --- influence function --- robust --- Wald-type test --- log-linear models --- ordinal classification variables --- association models --- correlation models --- minimum penalized ?-divergence estimator --- consistency --- asymptotic normality --- goodness-of-fit --- bootstrap distribution estimator --- thematic quality assessment --- relative entropy --- logarithmic super divergence --- robustness --- minimum divergence inference --- generalized renyi entropy --- minimum divergence methods --- robustness --- single index model --- model assessment --- statistical distance --- non-quadratic distance --- total variation --- mixture index of fit --- Kullback-Leibler distance --- divergence measure --- ?-divergence --- relative error estimation --- robust estimation --- information geometry --- centroid --- Bregman information --- Hölder divergence --- indoor localization --- robustness --- efficiency --- Bayesian nonparametric --- Bayesian semi-parametric --- asymptotic property --- minimum disparity methods --- Hellinger distance --- Berstein von Mises theorem --- measurement errors --- robust testing --- two-sample test --- misspecified hypothesis and alternative --- 2-alternating capacities --- composite hypotheses --- corrupted data --- least-favorable hypotheses --- Neyman Pearson test --- divergence based testing --- Chernoff Stein lemma --- compressed data --- Hellinger distance --- representation formula --- iterated limits --- influence function --- consistency --- asymptotic normality --- location-scale family --- n/a

Google Earth Engine Applications

Authors: ---
ISBN: 9783038978848 9783038978855 Year: Pages: 420 DOI: 10.3390/books978-3-03897-885-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Environmental Technology
Added to DOAB on : 2019-04-25 16:37:17
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In a rapidly changing world, there is an ever-increasing need to monitor the Earth&rsquo;s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth&rsquo;s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.

Keywords

Google Earth Engine --- NDVI --- vegetation index --- Landsat --- remote sensing --- phenology --- surface reflectance --- cropland mapping --- cropland areas --- 30-m --- Landsat-8 --- Sentinel-2 --- Random Forest --- Support Vector Machines --- segmentation --- RHSeg --- Google Earth Engine --- Africa --- remote sensing --- semi-arid --- ecosystem assessment --- land use change --- image classification --- seasonal vegetation --- carbon cycle --- Google Earth Engine --- crop yield --- gross primary productivity (GPP) --- data fusion --- Landsat --- MODIS --- MODIS --- Random Forest --- pasture mapping --- Brazilian pasturelands dynamics --- Google Earth Engine --- crop classification --- multi-classifier --- cloud computing --- time series --- high spatial resolution --- BACI --- Enhanced Vegetation Index --- Google Earth Engine --- cloud-based geo-processing --- satellite-derived bathymetry --- image composition --- pseudo-invariant features --- sun glint correction --- empirical --- spatial error --- Google Earth Engine --- low cost in situ --- Sentinel-2 --- Mediterranean --- burn severity --- change detection --- Landsat --- dNBR --- RdNBR --- RBR --- composite burn index (CBI) --- MTBS --- lower mekong basin --- landsat collection --- suspended sediment concentration --- online application --- google earth engine --- Landsat --- Google Earth Engine --- protected area --- forest and land use mapping --- machine learning classification --- China --- temporal compositing --- image time series --- multitemporal analysis --- change detection --- cloud masking --- Landsat-8 --- Google Earth Engine (GEE) --- Google Earth Engine --- LAI --- FVC --- FAPAR --- CWC --- plant traits --- random forests --- PROSAIL --- small-scale mining --- industrial mining --- google engine --- image classification --- land-use cover change --- seagrass --- habitat mapping --- image composition --- machine learning --- support vector machines --- Google Earth Engine --- Sentinel-2 --- Aegean --- Ionian --- global scale --- soil moisture --- Soil Moisture Ocean Salinity --- Soil Moisture Active Passive --- Google Earth Engine --- drought --- cloud computing --- remote sensing --- snow hydrology --- water resources --- Google Earth Engine --- user assessment --- MODIS --- snow cover --- flood --- disaster prevention --- emergency response --- decision making --- Google Earth Engine --- land cover --- deforestation --- Brazilian Amazon --- Bayesian statistics --- BULC-U --- Mato Grosso --- spatial resolution --- Landsat --- GlobCover --- SDG --- surface urban heat island --- Geo Big Data --- Google Earth Engine --- global monitoring service --- Google Earth Engine --- web portal --- satellite imagery --- trends --- earth observation --- wetland --- Google Earth Engine --- Sentinel-1 --- Sentinel-2 --- random forest --- cloud computing --- geo-big data --- cloud computing --- big data analytics --- long term monitoring --- data archival --- early warning systems

Power Electronics in Renewable Energy Systems

Authors: ---
ISBN: 9783039210442 / 9783039210459 Year: Pages: 604 DOI: 10.3390/books978-3-03921-045-9 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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This book offers a collection of 30 scientific papers which address the problems associated with the use of power electronic converters in renewable energy source-based systems. Relevant problems associated with the use of power electronic converters to integrate renewable energy systems to the power grid are presented. Some of the covered topics relate to the integration of photovoltaic and wind energy generators into the rest of the system, and to the use of energy storage to mitigate power fluctuations, which are a characteristic of renewable energy systems. The book provides a good overview of the abovementioned topics.

Keywords

modular multilevel converter --- battery energy storage system --- state-of-charge balancing --- second-life battery --- multi-energy complementary --- microgrid --- demand response --- operation optimization --- electricity price --- peak-current-mode control --- dynamic modeling --- duty-ratio constraints --- discontinuous conduction mode --- FACTS devices --- active power filter --- static compensator --- control strategies --- grid-connected converter --- SPWM --- SVM --- maximum power point tracking --- open circuit voltage --- perturb and observe --- thermoelectric generator --- two-stage photovoltaic power --- virtual synchronous generator --- adaptive-MPPT (maximum power point tracking) --- improved-VSG (virtual synchronous generator) --- power matching --- failure zone --- governor --- frequency regulation --- inverter --- voltage-type control --- static frequency characteristics --- grid-connected converter --- adaptive resonant controller --- PLL --- impedance analysis --- distorted grid --- digital signal processor (DSP) TMS320F28335 --- grid-connected inverter --- internal model --- linear quadratic regulator --- LCL filter --- photovoltaic systems --- multilevel power converter --- soft switching --- selective harmonic mitigation --- phase shifted --- voltage cancellation --- adaptive control --- sliding mode control --- speed control --- wind energy system --- microgrid (MG) --- droop control --- washout filter --- hardware in the loop (HIL) --- active front-end converter --- back-to-back converter --- permanent magnet synchronous generator (PMSG) --- THD --- type-4 wind turbine --- wind energy system --- Opal-RT Technologies® --- synchronization --- adaptive notch filter (ANF) --- phase-locked loop (PLL) --- wind power prediction --- phase space reconstruction --- multivariate linear regression --- cloud computing --- time series --- multiple VSGs --- oscillation mitigation --- coordinated control --- small-signal and transient stability --- coordination control --- energy storage --- grid support function --- inertia --- photovoltaic --- virtual synchronous generator --- weak grid --- parallel inverters --- oscillation suppression --- notch filter --- impedance reshaping --- boost converter --- peak-current-mode control --- dynamic modeling --- discontinuous operation mode --- doubly-fed induction generator --- short-circuit fault --- frequency regulation --- variable power tracking control --- improved additional frequency control --- variable coefficient regulation --- inertia and damping characteristics --- generator speed control --- electrical power generation --- turbine and generator --- grid-connected converter --- organic Rankine cycle --- renewable energy --- multiport converter (MPC) --- single ended primary inductor converter (SEPIC) --- multi-input single output (MISO) --- renewable power system --- coupled oscillators --- virtual impedance --- synchronization --- power converters --- droop control --- virtual admittance --- distributed generation --- energy --- renewable energy --- microgrids --- Energy Internet --- energy router --- microgrid --- electric vehicle --- PV --- battery-energy storage --- DC-AC power converters --- impedance emulation --- stability analysis --- power-hardware-in- the-loop --- photovoltaic generators --- maximum power point tracking --- step size --- perturbation frequency --- source and load impedance --- transient dynamics --- stability --- grid synchronization --- power electronics --- power grid --- inverter --- grid-connected --- microgrid --- experiment --- modules --- synchronverter --- power ripple elimination --- resonant controller --- unbalanced power grid --- ROCOF --- PLL --- error --- low inertia --- VSC --- n/a

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