Long-run real exchange rate changes and the properties of the variance of k-differences

Engel (1999) computes the variance of k-differences for each time horizon us- ing the method of Cochrane (1988) in order to measure the importance of the traded goods component in U.S. real exchange rate movements. The importance of traded goods should decrease as the horizon increases if the law of one price holds for traded goods in the long run. However, Engel ?nds that the variance of k-di¤erences decreases only initially and then increases as k approaches the sample size. He interpets the increasing variance as evidence of an increase in the long-run importance of the traded goods component. By contrast, we show that the variance of k-di¤erences tends to return to the initial value as k approaches the sample size whether the variable is stationary or unit root nonstationary. Our results imply that the increasing variances for k-values close to the sample size cannot be inter- preted as evidence of an increase in the importance of the traded goods component in the long run. We ?nd that our test results regarding the variance of k-di¤erences are consistent with smaller importance of the traded goods component in the longer run.Real exchange rate, Variance ratio, Traded and nontraded goods

Social Media as a Personal Branding Tool: A Qualitative Study of Student-Athletes’ Perceptions and Behaviors

While previous research focused on social media and student-athletes, there is a lack of knowledge about positive functions of social media use for student-athletes, especially personal branding purposes. Thus, this study aimed to explore how student-athletes perceive and use social media for personal branding purposes. A total of 11 student-athletes at a Division I university participated in semi-structured interviews. Considering the exploratory nature of the study, a qualitative inquiry and a phenomenology approach were employed to grasp an overall understanding of student-athletes’ personal branding via social media. The self-presentation theory was adopted to help understand student-athletes’ use of social media. Emerging themes included benefits and barriers of social media use, social media strategies, and concerns about negative consequences of social media. Findings from this study shed light on the importance of increasing awareness and knowledge of the concept of personal branding via social media for student-athletes. These findings also call for more effective social media training or education programs that can foster student-athletes’ positive attitude toward social media use for personal branding

FPGA-Based Low-Power Speech Recognition with Recurrent Neural Networks

In this paper, a neural network based real-time speech recognition (SR) system is developed using an FPGA for very low-power operation. The implemented system employs two recurrent neural networks (RNNs); one is a speech-to-character RNN for acoustic modeling (AM) and the other is for character-level language modeling (LM). The system also employs a statistical word-level LM to improve the recognition accuracy. The results of the AM, the character-level LM, and the word-level LM are combined using a fairly simple N-best search algorithm instead of the hidden Markov model (HMM) based network. The RNNs are implemented using massively parallel processing elements (PEs) for low latency and high throughput. The weights are quantized to 6 bits to store all of them in the on-chip memory of an FPGA. The proposed algorithm is implemented on a Xilinx XC7Z045, and the system can operate much faster than real-time.Comment: Accepted to SiPS 201

Minkowski Tensors in Two Dimensions - Probing the Morphology and Isotropy of the Matter and Galaxy Density Fields

We apply the Minkowski Tensor statistics to two dimensional slices of the three dimensional density field. The Minkowski Tensors are a set of functions that are sensitive to directionally dependent signals in the data, and furthermore can be used to quantify the mean shape of density peaks. We begin by introducing our algorithm for constructing bounding perimeters around subsets of a two dimensional field, and reviewing the definition of Minkowski Tensors. Focusing on the translational invariant statistic $W^{1,1}_{2}$ - a $2 \times 2$ matrix - we calculate its eigenvalues for both the entire excursion set ($\Lambda_{1},\Lambda_{2}$) and for individual connected regions and holes within the set ($\lambda_{1},\lambda_{2}$). The ratio of eigenvalues $\Lambda_{2}/\Lambda_{1}$ informs us of the presence of global anisotropies in the data, and $\langle \lambda_{2}/\lambda_{1} \rangle$ is a measure of the mean shape of peaks and troughs in the density field. We study these quantities for a Gaussian field, then consider how they are modified by the effect of gravitational collapse using the latest Horizon Run 4 cosmological simulation. We find $\Lambda_{1,2}$ are essentially independent of gravitational collapse, as the process maintains statistical isotropy. However, the mean shape of peaks is modified significantly - overdensities become relatively more circular compared to underdensities of the same area. When applying the statistic to a redshift space distorted density field, we find a significant signal in the eigenvalues $\Lambda_{1,2}$, suggesting that they can be used to probe the large-scale velocity field.Comment: 17 pages, accepted for publication in AP