On Binomial Ideals associated to Linear Codes

Recently, it was shown that a binary linear code can be associated to a binomial ideal given as the sum of a toric ideal and a non-prime ideal. Since then two different generalizations have been provided which coincide for the binary case. In this paper, we establish some connections between the two approaches. In particular, we show that the corresponding code ideals are related by elimination. Finally, a new heuristic decoding method for linear codes over prime fields is discussed using Gr\"obner bases

Faster Training of Mask R-CNN by Focusing on Instance Boundaries

We present an auxiliary task to Mask R-CNN, an instance segmentation network, which leads to faster training of the mask head. Our addition to Mask R-CNN is a new prediction head, the Edge Agreement Head, which is inspired by the way human annotators perform instance segmentation. Human annotators copy the contour of an object instance and only indirectly the occupied instance area. Hence, the edges of instance masks are particularly useful as they characterize the instance well. The Edge Agreement Head therefore encourages predicted masks to have similar image gradients to the ground-truth mask using edge detection filters. We provide a detailed survey of loss combinations and show improvements on the MS COCO Mask metrics compared to using no additional loss. Our approach marginally increases the model size and adds no additional trainable model variables. While the computational costs are increased slightly, the increment is negligible considering the high computational cost of the Mask R-CNN architecture. As the additional network head is only relevant during training, inference speed remains unchanged compared to Mask R-CNN. In a default Mask R-CNN setup, we achieve a training speed-up and a relative overall improvement of 8.1% on the MS COCO metrics compared to the baseline.Comment: 9 pages, 7 figures, 5 table

Assessment of Temperature-Dependent Regression Model Terms of a RUAG Six-Component Block-Type Balance

A metric called the percent contribution was applied to regression models of temperature-dependent calibration data of a RUAG six-component block-type balance in order to assess the influence of temperature-dependent regression model terms on the balance load prediction. Regression models were examined that are needed if either the Iterative or the Non-Iterative Method is used for the load prediction. Computed values of the percent contribution confirmed that the cross-product term defined by a primary load and the temperature difference is the most influential temperature-dependent term of the regression model of a primary output that the Iterative Method needs. Similarly, the analysis showed that the cross-product term defined by a primary output and the temperature difference is the most influential temperature-dependent term of the regression model of a primary load that the Non-Iterative Method needs. Computed results support conclusions that were reported in an earlier theoretical study. This study asserted that the cross-product term defined by a primary load or output and the temperature difference models the temperature-dependent shift of the gage sensitivity. The influence of other temperature-dependent terms used in the regression models of the calibration data of RUAG's balance was negligible. This observation may be explained by the fact that RUAG's block-type balances have highly linear characteristics. Overall, the percent contribution has proven itself to be a reliable and easy-to-implement metric that may also be used for the assessment of the influence of temperature-dependent regression model terms on the load prediction of a six-component strain-gage balance

China's Latent Human Capital Investment: Achieving Milestones and Competing for the Top

In this paper we provide an overview of China’s human capital strategy and educational achievements over the last two decades. While every one acknowledges China as an economic superpower, very few are aware of or realize China’s notable achievements in education as well as its internationalization of education. Since 1978, the landmark for the foundation of the Chinese modern higher education system China has made tremendous strides in education both domestically and internationally. While China maintains 10% growth in GDP, albeit with a GDP per capita at the low level of a developing country, it is also producing serious scholars and a tremendous amount of scholarly output; more and more Chinese students seek higher education abroad; and international students find a rising interest in receiving education in China.higher education, brain drain, human capital, China

Stripe-hexagon competition in forced pattern forming systems with broken up-down symmetry

We investigate the response of two-dimensional pattern forming systems with a broken up-down symmetry, such as chemical reactions, to spatially resonant forcing and propose related experiments. The nonlinear behavior immediately above threshold is analyzed in terms of amplitude equations suggested for a $1:2$ and $1:1$ ratio between the wavelength of the spatial periodic forcing and the wavelength of the pattern of the respective system. Both sets of coupled amplitude equations are derived by a perturbative method from the Lengyel-Epstein model describing a chemical reaction showing Turing patterns, which gives us the opportunity to relate the generic response scenarios to a specific pattern forming system. The nonlinear competition between stripe patterns and distorted hexagons is explored and their range of existence, stability and coexistence is determined. Whereas without modulations hexagonal patterns are always preferred near onset of pattern formation, single mode solutions (stripes) are favored close to threshold for modulation amplitudes beyond some critical value. Hence distorted hexagons only occur in a finite range of the control parameter and their interval of existence shrinks to zero with increasing values of the modulation amplitude. Furthermore depending on the modulation amplitude the transition between stripes and distorted hexagons is either sub- or supercritical.Comment: 10 pages, 12 figures, submitted to Physical Review

Imaginários e discursos de professores sobre leitura no ensino de ciências/geociências : algumas condições de produção

Pautado em aportes da Análise de Discurso de origem francesa, pressupondo que o professor tem papel fundamental na mediação da leitura e na formação do leitor de ciência, e que essa mediação se relaciona com seus imaginários, este trabalho teve como objetivo compreender aspectos das condições de produção dos imaginários de quatro professores de diferentes disciplinas de uma mesma escola sobre leitura no ensino de ciências. Apontamos que seus imaginários sobre leitura se relacionam às seguintes condições de produção: suas memórias, familiares e escolares, enquanto leitores e os discursos sobre leitura que têm chegado às escolas por meio de documentos oficiais e cursos de formação continuada. Discutimos implicações para a formação de professores: a importância de trabalhar suas memórias enquanto leitores e os sentidos sobre leitura que já circulam nas escolas

Characterizing flows with an instrumented particle measuring Lagrangian accelerations

We present in this article a novel Lagrangian measurement technique: an instrumented particle which continuously transmits the force/acceleration acting on it as it is advected in a flow. We develop signal processing methods to extract information on the flow from the acceleration signal transmitted by the particle. Notably, we are able to characterize the force acting on the particle and to identify the presence of a permanent large-scale vortex structure. Our technique provides a fast, robust and efficient tool to characterize flows, and it is particularly suited to obtain Lagrangian statistics along long trajectories or in cases where optical measurement techniques are not or hardly applicable.Comment: submitted to New Journal of Physic

Application of a Temperature-Dependent Load Prediction Method to a RUAG Six-Component Block-Type Balance

Temperature-dependent data of a RUAG six-component block-type balance was analyzed to assess the accuracy of two load prediction methods for temperature-dependent balance data. The supplied data was prepared for the analysis by splitting it into calibration and check load data subsets. The first calibration data subset was obtained at a temperature of 294 Kelvin. The second calibration data subset was obtained at a temperature of 315 Kelvin. A subset of 38 points was extracted from the second data set and used as check loads so that the accuracy of the two load prediction methods could be tested. First, the Iterative Method in combination with an extended independent and dependent variable set was used for the balance load prediction. This approach fits electrical outputs as a function of loads and the temperature and, afterwards, constructs a load iteration scheme from the regression coefficients so that loads can be predicted from outputs and the temperature during a wind tunnel test. The Non-Iterative Method was also used for the load prediction. This alternate method can more easily be implemented in a data system as loads are directly fitted as a function of electrical outputs and the temperature. Analysis results for the axial force are only discussed in the paper as similar results were obtained for the other five load components. Results for both methods clearly show that the cross-product term constructed from either a primary gage load or a primary gage output and the temperature explains the majority of the temperature-dependent part of the predicted balance load. This term models the temperature dependent nature of the gage sensitivity. Therefore, it is recommended to apply primary gage loadings at different temperatures during a balance calibration whenever temperature effects need to be described. These loadings will contain information about the temperature-dependent nature of the gage sensitivities that can be quantified by related cross-product terms in regression models of the data

Dynamics of incentives and value creation in (de-)centralised incentive systems

When young and small organisations grow into medium-sized organisations they often implement monetary incentive systems with unclear consequences. Whilst implemented to increase employee (innovative) output and value creation, they have ambiguous effects and may even reduce value creation. Due to the different effects of monetary incentives, this paper distinguishes reciprocal and opportunistic employees’ different reactions to incentives. It analyses the effects of decentralised incentive systems – and thus of incentive systems targeted better at opportunistic vs. reciprocal employees – on value creation. Here, it proposes a causal feedback structure explaining opportunistic and reciprocal employees’ different reactions and it investigates by simulation how incentives and value creation interact over time. The analysis reveals that behaviour is not pre-determined by employee disposition. It shows how dynamics evolve dependent on the interrelationships of employee dispositions and the organisational context. As such, it exemplifies the usefulness of studying dynamics of incentive systems and employee behaviour