(Re) Constructing Gender in a New Voice: the Role of Gender Identity in Sla, the Case of Malaysia

This study is a qualitative study of Malaysian children aged between four and six years engaged in a story-telling task. The question posed in this piece of research then: Is the role played by gender in SLA? If it does play a role, what then is the nature of this role? The path taken by this study is to analyze discourse in story-telling

The Effect of Text Authenticity on the Performance of Iranian EFL Students in a C-Test

As part of growing efforts to understand factors affecting c-test this study aims to investigate the effect of text authenticity on the performance of Iranian EFL students in a C-Test. The C-Test is an integrative testing instrument that measures overall language competence, very much like the cloze test. In this study the rule of two has been applied: "the second half of every second word has been deleted, beginning with the second word of the second sentence; the first and last sentences are left intact" (Katona and Dornyei 1993: 35). The research involves 60 college students in their third year, majoring in English Literature at Ershad-Damavand College. This group were randomly selected applying multi-stage sampling. Since the present study intended to investigate the role of two different formats, i.e. authentic and inauthentic texts (text translated from Persian into English), two different tailored C-Tests were made to measure and compare the performances of the participants. Two C-Tests, one with Authentic Text and the other, with Inauthentic Text were administered to this homogenized group comprising 30 subjects. The findings of this study suggest that authenticity has an effect on the performance of learners in c-tests and we should control this variable while devising a c-test

Genetic sampling for estimating density of common species.

Understanding population dynamics requires reliable estimates of population density, yet this basic information is often surprisingly difficult to obtain. With rare or difficult-to-capture species, genetic surveys from noninvasive collection of hair or scat has proved cost-efficient for estimating densities. Here, we explored whether noninvasive genetic sampling (NGS) also offers promise for sampling a relatively common species, the snowshoe hare (Lepus americanus Erxleben, 1777), in comparison with traditional live trapping. We optimized a protocol for single-session NGS sampling of hares. We compared spatial capture-recapture population estimates from live trapping to estimates derived from NGS, and assessed NGS costs. NGS provided population estimates similar to those derived from live trapping, but a higher density of sampling plots was required for NGS. The optimal NGS protocol for our study entailed deploying 160 sampling plots for 4 days and genotyping one pellet per plot. NGS laboratory costs ranged from approximately $670 to$3000 USD per field site. While live trapping does not incur laboratory costs, its field costs can be considerably higher than for NGS, especially when study sites are difficult to access. We conclude that NGS can work for common species, but that it will require field and laboratory pilot testing to develop cost-effective sampling protocols

(RE) CONSTRUCTING GENDER IN A NEW VOICE: THE ROLE OF GENDER IDENTITY IN SLA, THE CASE OF MALAYSIA

This study is a qualitative study of Malaysian children aged between four and six years engaged in a story-telling task. The question posed in this piece of research then: Is the role played by gender in SLA? If it does play a role, what then is the nature of this role? The path taken by this study is to analyze discourse in story-telling

Extend the shallow part of Single Shot MultiBox Detector via Convolutional Neural Network

Single Shot MultiBox Detector (SSD) is one of the fastest algorithms in the current object detection field, which uses fully convolutional neural network to detect all scaled objects in an image. Deconvolutional Single Shot Detector (DSSD) is an approach which introduces more context information by adding the deconvolution module to SSD. And the mean Average Precision (mAP) of DSSD on PASCAL VOC2007 is improved from SSD's 77.5% to 78.6%. Although DSSD obtains higher mAP than SSD by 1.1%, the frames per second (FPS) decreases from 46 to 11.8. In this paper, we propose a single stage end-to-end image detection model called ESSD to overcome this dilemma. Our solution to this problem is to cleverly extend better context information for the shallow layers of the best single stage (e.g. SSD) detectors. Experimental results show that our model can reach 79.4% mAP, which is higher than DSSD and SSD by 0.8 and 1.9 points respectively. Meanwhile, our testing speed is 25 FPS in Titan X GPU which is more than double the original DSSD.Comment: 7 pages, 3 figures, 3 table

Learning of Temporal Motor Patterns: An Analysis of Continuous Versus Reset Timing

Our ability to generate well-timed sequences of movements is critical to an array of behaviors, including the ability to play a musical instrument or a video game. Here we address two questions relating to timing with the goal of better understanding the neural mechanisms underlying temporal processing. First, how does accuracy and variance change over the course of learning of complex spatiotemporal patterns? Second, is the timing of sequential responses most consistent with starting and stopping an internal timer at each interval or with continuous timing? To address these questions we used a psychophysical task in which subjects learned to reproduce a sequence of finger taps in the correct order and at the correct times – much like playing a melody at the piano. This task allowed us to calculate the variance of the responses at different time points using data from the same trials. Our results show that while “standard” Weber’s law is clearly violated, variance does increase as a function of time squared, as expected according to the generalized form of Weber’s law – which separates the source of variance into time-dependent and time-independent components. Over the course of learning, both the time-independent variance and the coefficient of the time-dependent term decrease. Our analyses also suggest that timing of sequential events does not rely on the resetting of an internal timer at each event. We describe and interpret our results in the context of computer simulations that capture some of our psychophysical findings. Specifically, we show that continuous timing, as opposed to “reset” timing, is consistent with “population clock” models in which timing emerges from the internal dynamics of recurrent neural networks