The Globalization Strategy of Vietnamese IT Enterprises in the Context of ASEAN Economic Community Via the Case Study of Fpt Corporation Hoang Van Cuong, (Director of International Mobility Department, Fpt University Vietnam)

Vietnam IT Industry has been growing rapidly duringthe past 15 years. It has been considered as the mainshort cut to develop the Vietnamese economy from a lowincome to a middle income country (MIC). From 2002to 2013, the revenue of software industry increased 52times to reach nearly 3 US$billion; and the revenue ofhardware industry increased 70.5 times to reach 36.8US$ billion. Hanoi and Ho Chi Minh City – the twobiggest cities in Vietnam have been ranked in the Top100 outsourcing destinations by Tholons (an advisoryfirm for global outsourcing and investment).ASEAN is one of the key markets for Vietnam'sIT industry. The region also provides a high potentiallabor force market to solve the human resourceproblems of the IT enterprises. In this context, ASEANEconomic Community will have a significant influenceto the development of Vietnam's IT enterprises.This paper will discuss the globalizationstrategy of Vietnamese IT enterprises in the context ofASEAN Economic community via the case of FPTCorporation – the leading IT Company in Vietnamwhich currently has its office in Singapore, Malaysia,Thailand, Laos, Cambodia, Myanmar, Indonesia andthe Philippines

Consistency Properties of Species Tree Inference by Minimizing Deep Coalescences

Methods for inferring species trees from sets of gene trees need to account for the possibility of discordance among the gene trees. Assuming that discordance is caused by incomplete lineage sorting, species tree estimates can be obtained by finding those species trees that minimize the number of -deep- coalescence events required for a given collection of gene trees. Efficient algorithms now exist for applying the minimizing-deep-coalescence (MDC) criterion, and simulation experiments have demonstrated its promising performance. However, it has also been noted from simulation results that the MDC criterion is not always guaranteed to infer the correct species tree estimate. In this article, we investigate the consistency of the MDC criterion. Using the multipscies coalescent model, we show that there are indeed anomaly zones for the MDC criterion for asymmetric four-taxon species tree topologies, and for all species tree topologies with five or more taxa.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90434/1/cmb-2E2010-2E0102.pd

Surfaces of Revolution with Constant Gaussian Curvature in Four-Space

In this paper, we show that the constant property of the Gaussian curvature of surfaces of revolution in both $\mathbb R^4$ and $\mathbb R_1^4$ depend only on the radius of rotation. We then give necessary and sufficient conditions for the Gaussian curvature of the general rotational surfaces whose meridians lie in two dimensional planes in $\mathbb R^4$ to be constant, and define the parametrization of the meridians when both the Gaussian curvature is constant and the rates of rotation are equal.Comment: 8 paper

EnSolver: Uncertainty-Aware CAPTCHA Solver Using Deep Ensembles

The popularity of text-based CAPTCHA as a security mechanism to protect websites from automated bots has prompted researches in CAPTCHA solvers, with the aim of understanding its failure cases and subsequently making CAPTCHAs more secure. Recently proposed solvers, built on advances in deep learning, are able to crack even the very challenging CAPTCHAs with high accuracy. However, these solvers often perform poorly on out-of-distribution samples that contain visual features different from those in the training set. Furthermore, they lack the ability to detect and avoid such samples, making them susceptible to being locked out by defense systems after a certain number of failed attempts. In this paper, we propose EnSolver, a novel CAPTCHA solver that utilizes deep ensemble uncertainty estimation to detect and skip out-of-distribution CAPTCHAs, making it harder to be detected. We demonstrate the use of our solver with object detection models and show empirically that it performs well on both in-distribution and out-of-distribution data, achieving up to 98.1% accuracy when detecting out-of-distribution data and up to 93% success rate when solving in-distribution CAPTCHAs.Comment: Epistemic Uncertainty - E-pi UAI 2023 Worksho

Electronic Scan Strategy for Phased Array Weather Radar Using a Space–Time Characterization Model

AbstractThis paper presents an adaptive scan strategy concept for phased array weather radars (PAWR) with the objective of increasing the scan speed and capturing features of the storm system while maintaining the measurement accuracy. The adaptive scan strategy is developed based on the space–time variability of the storm under observation. Quickly evolving regions are scanned more often and the spatial sampling resolution is matched to the spatial scale. A model that includes the interaction between space and time is used to extract spatial and temporal scales of the medium and to define scanning regions. The temporal scale constrains the radar revisit time, while the measurement accuracy controls the radar's dwell time. These conditions are employed in a task scheduler that works on a ray-by-ray basis and is designed to balance task priority and radar resources. The scheduler algorithm also includes an optimization procedure for minimizing radar scan time. The model and the scan strategy are demonstrated using simulation data. The results show that the proposed scan strategy can reduce the scan time significantly without compromising data quality