Vietnamese and the NP/DP parameter

This paper investigates the place of Vietnamese in the NP/DP typology as formulated by Bošković (2005, 2008, 2009, 2010). We show that Bošković’s NP/DP parameter breaks down into at least three separate parameters. In many languages, these three parameters line up in a consistent manner and conspire to give the impression that there is a single macro-parameter at work. However, due to its mixed status, Vietnamese reveals that there are in fact three smaller parameters (nominal, clausal, and quantificational) at work, and that these are independently fixed (as [–DP], [+TP], and [–movement], respectively). Moreover, Vietnamese can in general be classified as a topic-prominent language, a classification which requires more research but which plays an important role in determining the behavior of Vietnamese with regard to many of the syntactic properties discussed

Hemispheric Asymmetries for Color and Number Working Memory Tasks

A large number of studies in psychology and cognitive neuroscience suggest that the left and right cerebral hemispheres have differences in specialization of processing. The left hemisphere tends to be specialized for complex capacities such as language and numbers, whereas the right hemisphere typically shows advantages for visuospatial attention and recognition of nonverbal form. The present study was designed to investigate whether these functional cerebral asymmetries would extend to working memory tasks. It was hypothesized that the left hemisphere would have more advantage for accurate responses to a Number-based memory task, whereas the right hemisphere would be relatively advantaged for accurate responses on a Color-based memory task. For the Color-based memory task, we used a Corsi-Block memory task (4x4 grid). For the Number-based memory task, we used a string of 8 digits. In each case, to-be-remembered stimuli were constructed sequentially, such that participants (N = 39) had to form and maintain the image in working memory. Participants then compared these remembered stimuli with flashed images that appeared either on the left or right edge of the screen. We recorded the correct responses and the response time. The left hemisphere appears to be advantaged for accurate responses when the memory stimuli are numerical in nature, whereas the right hemisphere has more advantage for accurate responses on the color-memory task

How Can Educators Make Use Of Feedback Types And Process To Optimize Student Performance?

Feedback is one of the most common educational tools, which is frequently used in classrooms among multiple fields and grades. Although teachers use it to improve students’ learning, not all feedback would impact students positively. Instead, some feedback can be ineffective or damaging to learners, leading to a decrease in educators’ teaching productivity. This paper strives to answer the question, How can educators make use of feedback types and process to optimize student performance? It addresses research surrounding feedback and categorizes it based on four factors: positivity, levels, language used, and forms of feedback. From the research findings, this paper emphasizes that depending on its types, feedback can positively, negatively, or not at all affect learners who receive the comments. The paper also demonstrates similar findings regarding peer feedback, in comparison to teacher feedback. This research culminated in a two-session professional development, allowing the author to share the research findings regarding feedback with others and provide guidelines to help educators improve their feedback quality. To enhance this interaction, a variety of assessments and group activities are provided to learners, ensuring the quality of information that the audience receives

Comparison of Sampling-Based Algorithms for Multisensor Distributed Target Tracking

Nonlinear filtering is certainly very important in estimation since most real-world problems are nonlinear. Recently a considerable progress in the nonlinear filtering theory has been made in the area of the sampling-based methods, including both random (Monte Carlo) and deterministic (quasi-Monte Carlo) sampling, and their combination. This work considers the problem of tracking a maneuvering target in a multisensor environment. A novel scheme for distributed tracking is employed that utilizes a nonlinear target model and estimates from local (sensor-based) estimators. The resulting estimation problem is highly nonlinear and thus quite challenging. In order to evaluate the performance capabilities of the architecture considered, advanced sampling-based nonlinear filters are implemented: particle filter (PF), unscented Kalman filter (UKF), and unscented particle filter (UPF). Results from extensive Monte Carlo simulations using different configurations of these algorithms are obtained to compare their effectiveness for solving the distributed target tracking problem

The Impact of the Covid-19 Pandemic on Corporate Financial Fragility in the Vietnamese Manufacturing Industry

In the past decades, under the government’s export-led growth strategy, the Vietnamese manufacturing sector – the backbone of the whole Vietnamese economy – has established a deep tie with the international market and the reliance on foreign buyers has fueled the growth of this sector before COVID-19. However, during the pandemic, when the global market contracted at -3.5 percent and demand slumped globally, this existing growth model and the manufacturing sector’s reliance on foreign buyers induced significant risks to this sector from both the demand and supply side. Using the firm-level data on 41 manufacturing exporting companies from the Vietstock database and national-level data on the development of COVID-19 and the magnitude of fiscal policies enacted from the IMF and World bank, this paper investigates the impact of the COVID-19 situation in significant trading partners and in Vietnam on the bankruptcy risks of manufacturing companies. Using a fixed-effect regression model, we found that the COVID-19 pandemic introduced great revenue volatility but did not undermine the solvency levels of Vietnamese manufacturers. Further examination of firm-level financial ratios elucidates that a decade of high growth has built up the necessary firm-level financial resilience that allows these manufacturers to withstand massive macroeconomic shocks

Comparison of Sampling-Based Algorithms for Multisensor Distributed Target Tracking

Nonlinear filtering is certainly very important in estimation since most real-world problems are nonlinear. Recently a considerable progress in the nonlinear filtering theory has been made in the area of the sampling-based methods, including both random (Monte Carlo) and deterministic (quasi-Monte Carlo) sampling, and their combination. This work considers the problem of tracking a maneuvering target in a multisensor environment. A novel scheme for distributed tracking is employed that utilizes a nonlinear target model and estimates from local (sensor-based) estimators. The resulting estimation problem is highly nonlinear and thus quite challenging. In order to evaluate the performance capabilities of the architecture considered, advanced sampling-based nonlinear filters are implemented: particle filter (PF), unscented Kalman filter (UKF), and unscented particle filter (UPF). Results from extensive Monte Carlo simulations using different configurations of these algorithms are obtained to compare their effectiveness for solving the distributed target tracking problem