755 research outputs found

    The auxiliary use of LANDSAT data in estimating crop acreages: Results of the 1975 Illinois crop-acreage experiment

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    The author has identified the following significant results. It was found that classifier performance was influenced by a number of temporal, methodological, and geographical factors. Best results were obtained when corn was tasselled and near the dough stage of development. Dates earlier or later in the growing season produced poor results. Atmospheric effects on results cannot be independently measured or completely separated from the effects due to the maturity stage of the crops. Poor classifier performance was observed in areas where considerable spectral confusion was present

    The influence of tennis court surfaces on player perceptions and biomechanical response.

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    This study aimed to examine player perceptions and biomechanical responses to tennis surfaces and to evaluate the influence of prior clay court experience. Two groups with different clay experiences (experience group, n = 5 and low-experience group, n = 5) performed a 180° turning movement. Three-dimensional ankle and knee movements (50 Hz), plantar pressure of the turning step (100 Hz) and perception data (visual analogue scale questionnaire) were collected for two tennis courts (acrylic and clay). Greater initial knee flexion (acrylic 20. 8 ± 11.2° and clay 32.5 ± 9.4°) and a more upright position were reported on the clay compared to the acrylic court (P < 0.05). This suggests adaptations to increase player stability on clay. Greater hallux pressures and lower midfoot pressures were observed on the clay court, allowing for sliding whilst providing grip at the forefoot. Players with prior clay court experience exhibited later peak knee flexion compared to those with low experience. All participants perceived the differences in surface properties between courts and thus responded appropriately to these differences. The level of previous clay court experience did not influence players' perceptions of the surfaces; however, those with greater clay court experience may reduce injury risk as a result of reduced loading through later peak knee flexion

    High-Performance Silicon Photonic Single-Sideband Modulators for Cold Atom Interferometry

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    The most complicated and challenging system within a light-pulse atom interferometer (LPAI) is the laser system, which controls the frequencies and intensities of multiple laser beams over time to configure quantum gravity and inertial sensors. The main function of an LPAI laser system is to perform cold-atom generation and state-selective detection and to generate coherent two-photon process for the light-pulse sequence. Substantial miniaturization and ruggedization of the laser system can be achieved by bringing together most key functions of the laser and optical system onto a photonic integrated circuit (PIC). Here we demonstrate a high-performance silicon photonic carrier-suppressed single-sideband (CS-SSB) modulator PIC with dual-parallel Mach-Zehnder modulators (DP-MZMs) operating near 1560 nm, which can dynamically shift the frequency of the light for the desired function within the LPAI. Independent RF control of channels in SSB modulator enables the extensive study of imbalances in both the optical and RF phases and amplitudes to simultaneously reach 30 dB carrier suppression and unprecedented 47.8 dB sideband suppression with peak conversion efficiency of -6.846 dB (20.7 %). Using a silicon photonic SSB modulator with time-multiplexed frequency shifting in an LPAI laser system, we demonstrate cold-atom generation, state-selective detection, and the realization of atom interferometer fringes to estimate gravitational acceleration, g≈9.77±0.01 m/s2g \approx 9.77 \pm 0.01 \,\rm{m/s^2}, in a Rubidium (87^{87}Rb) atom system.Comment: 18 pages, 9 figure

    Experts' Judgments of Management Journal Quality:An Identity Concerns Model

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    Many lists that purport to gauge the quality of journals in management and organization studies (MOS) are based on the judgments of experts in the field. This article develops an identity concerns model (ICM) that suggests that such judgments are likely to be shaped by the personal and social identities of evaluators. The model was tested in a study in which 168 editorial board members rated 44 MOS journals. In line with the ICM, respondents rated journal quality more highly to the extent that a given journal reflected their personal concerns (associated with having published more articles in that journal) and the concerns of a relevant ingroup (associated with membership of the journal’s editorial board or a particular disciplinary or geographical background). However, judges’ ratings of journals in which they had published were more favorable when those journals had a low-quality reputation, and their ratings of journals that reflected their geographical and disciplinary affiliations were more favorable when those journals had a high-quality reputation. The findings are thus consistent with the view that identity concerns come to the fore in journal ratings when there is either a need to protect against personal identity threat or a meaningful opportunity to promote social identity

    Using machine learning to infer reasoning provenance from user interaction log data: based on the data/frame theory of sensemaking

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    The reconstruction of analysts’ reasoning processes (reasoning provenance) during complex sensemaking tasks can support reflection and decision making. One potential approach to such reconstruction is to automatically infer reasoning from low-level user interaction logs. We explore a novel method for doing this using machine learning. Two user studies were conducted in which participants performed similar intelligence analysis tasks. In one study, participants used a standard web browser and word processor; in the other, they used a system called INVISQUE (Interactive Visual Search and Query Environment). Interaction logs were manually coded for cognitive actions based on captured think-aloud protocol and posttask interviews based on Klein, Phillips, Rall, and Pelusos’s data/frame model of sensemaking as a conceptual framework. This analysis was then used to train an interaction frame mapper, which employed multiple machine learning models to learn relationships between the interaction logs and the codings. Our results show that, for one study at least, classification accuracy was significantly better than chance and compared reasonably to a reported manual provenance reconstruction method. We discuss our results in terms of variations in feature sets from the two studies and what this means for the development of the method for provenance capture and the evaluation of sensemaking systems

    Quantitative analysis of powder mixtures by raman spectrometry : the influence of particle size and its correction

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    Particle size distribution and compactness have significant confounding effects on Raman signals of powder mixtures, which cannot be effectively modeled or corrected by traditional multivariate linear calibration methods such as partial least-squares (PLS), and therefore greatly deteriorate the predictive abilities of Raman calibration models for powder mixtures. The ability to obtain directly quantitative information from Raman signals of powder mixtures with varying particle size distribution and compactness is, therefore, of considerable interest In this study, an advanced quantitative Raman calibration model was developed to explicitly account for the confounding effects of particle size distribution and compactness on Raman signals of powder mixtures. Under the theoretical guidance of the proposed Raman calibration model, an advanced dual calibration strategy was adopted to separate the Raman contributions caused by the changes in mass fractions of the constituents in powder mixtures from those induced by the variations in the physical properties of samples, and hence achieve accurate quantitative determination for powder mixture samples. The proposed Raman calibration model was applied to the quantitative analysis of backscatter Raman measurements of a proof-of-concept model system of powder mixtures consisting of barium nitrate and potassium chromate. The average relative prediction error of prediction obtained by the proposed Raman calibration model was less than one-third of the corresponding value of the best performing PLS model for mass fractions of barium nitrate in powder mixtures with variations in particle size distribution, as well as compactness

    Appointing Women to Boards: Is There a Cultural Bias?

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    Companies that are serious about corporate governance and business ethics are turning their attention to gender diversity at the most senior levels of business (Institute of Business Ethics, Business Ethics Briefing 21:1, 2011). Board gender diversity has been the subject of several studies carried out by international organizations such as Catalyst (Increasing gender diversity on boards: Current index of formal approaches, 2012), the World Economic Forum (Hausmann et al., The global gender gap report, 2010), and the European Board Diversity Analysis (Is it getting easier to find women on European boards? 2010). They all lead to reports confirming the overall relatively low proportion of women on boards and the slow pace at which more women are being appointed. Furthermore, the proportion of women on corporate boards varies much across countries. Based on institutional theory, this study hypothesizes and tests whether this variation can be attributed to differences in cultural settings across countries. Our analysis of the representation of women on boards for 32 countries during 2010 reveals that two cultural characteristics are indeed associated with the observed differences. We use the cultural dimensions proposed by Hofstede (Culture’s consequences: International differences in work-related values, 1980) to measure this construct. Results show that countries which have the greatest tolerance for inequalities in the distribution of power and those that tend to value the role of men generally exhibit lower representations of women on boards

    A terminal assessment of stages theory : introducing a dynamic states approach to entrepreneurship

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    Stages of Growth models were the most frequent theoretical approach to understanding entrepreneurial business growth from 1962 to 2006; they built on the growth imperative and developmental models of that time. An analysis of the universe of such models (N=104) published in the management literature shows no consensus on basic constructs of the approach, nor is there any empirical confirmations of stages theory. However, by changing two propositions of the stages models, a new dynamic states approach is derived. The dynamic states approach has far greater explanatory power than its precursor, and is compatible with leading edge research in entrepreneurship
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