Indoor assistance for visually impaired people using a RGB-D camera

In this paper a navigational aid for visually impaired people is presented. The system uses a RGB-D camera to perceive the environment and implements self-localization, obstacle detection and obstacle classification. The novelty of this work is threefold. First, self-localization is performed by means of a novel camera tracking approach that uses both depth and color information. Second, to provide the user with semantic information, obstacles are classified as walls, doors, steps and a residual class that covers isolated objects and bumpy parts on the floor. Third, in order to guarantee real time performance, the system is accelerated by offloading parallel operations to the GPU. Experiments demonstrate that the whole system is running at 9 Hz

REGIONAL LINKAGE IN TOURISM: THE CASE OF VIETNAM

Abstract. This research is conducted for investigating the current situations of regional linkage in tourism development in the areas of Midlands and Northern Mountains in Vietnam. Data were collected from a survey of 755 people, including officials from State management bodies in charge of tourism, officials and staffs at tourism resorts, tourism firms, tourism scientists and tourists. In addition, we conducted focus group and interviewed tourism agency officials and tourism firms in the Midland and Mountainous provinces of Vietnam. The results show that tourism development in Vietnam in general and the Northwest region in particular is extremely fragmented, not yet forming a regional linkage; regional and national tourism development projects are just formalistic. Some causes are the limited regional integration policy, lack of appropriate regional governance mechanisms and inactive participation of the private sector in regional integration. Based on the findings, we propose a tourism sector linkage model; besides, policyimplications are given for fulfilling the linkage policies in Vietnam in particular, and more broadly for emerging countries in general.Keywords: Midlands and Northern Mountains, tourism linkage, Vietnam

Experimental and Numerical Evaluation of Concentrically Loaded RC Columns Strengthening by Textile Reinforced Concrete Jacketing

Nowadays, Textile Reinforced Concrete (TRC) has become a very popular strengthening technique for concrete structures. This paper presents an investigation on the applicability of TRC for strengthening reinforced concrete column. Both experimental and numerical studies are conducted to evaluate the confinement effects of various TRC strengthening schemes. The experimental study is performed on a series of six reinforced concrete square columns tested to failure. Two of them were un-strengthened as references, the other four were strengthened by one or two layers of Carbon Textile Reinforced Concrete (CTRC). The results indicated that the application of carbon TRC enhanced the ductility and ultimate strength of the specimens. Failure of all strengthened columns was together with tensile rupture of textile reinforcements at the corners of column. Finite element models of the CTRC strengthened columns based on ATENA software package were developed and verified with the experimental results. The analytical results show that in the specimen corner areas, textile reinforcements are subjected to a 3D complicated stress state and this may be the cause of their premature failure

Throughput Maximization Using an SVM for Multi-Class Hypothesis-Based Spectrum Sensing in Cognitive Radio

A framework of spectrum sensing with a multi-class hypothesis is proposed to maximize the achievable throughput in cognitive radio networks. The energy range of a sensing signal under the hypothesis that the primary user is absent (in a conventional two-class hypothesis) is further divided into quantized regions, whereas the hypothesis that the primary user is present is conserved. The non-radio frequency energy harvesting-equiped secondary user transmits, when the primary user is absent, with transmission power based on the hypothesis result (the energy level of the sensed signal) and the residual energy in the battery: the lower the energy of the received signal, the higher the transmission power, and vice versa. Conversely, the lower is the residual energy in the node, the lower is the transmission power. This technique increases the throughput of a secondary link by providing a higher number of transmission events, compared to the conventional two-class hypothesis. Furthermore, transmission with low power for higher energy levels in the sensed signal reduces the probability of interference with primary users if, for instance, detection was missed. The familiar machine learning algorithm known as a support vector machine (SVM) is used in a one-versus-rest approach to classify the input signal into predefined classes. The input signal to the SVM is composed of three statistical features extracted from the sensed signal and a number ranging from 0 to 100 representing the percentage of residual energy in the node’s battery. To increase the generalization of the classifier, k-fold cross-validation is utilized in the training phase. The experimental results show that an SVM with the given features performs satisfactorily for all kernels, but an SVM with a polynomial kernel outperforms linear and radial-basis function kernels in terms of accuracy. Furthermore, the proposed multi-class hypothesis achieves higher throughput compared to the conventional two-class hypothesis for spectrum sensing in cognitive radio networks

Corruption, provincial institutions and manufacturing firm productivity: New evidence from a transitional economy

Using data from nationwide surveys of provincial institutions and private manufacturing small medium enterprises, this study provided the first evidence of the impact of provincial institution quality and firms’ participation in and intensity of corrupt activities on firm productivity in Vietnam. We found that the bribe intensity instead of whether firms bribed state officials or not (measured by a dummy variable) has a negative effect on firm productivity when the endogeneity of corruption and unobservable characteristics are controlled for. This finding contrasts to a popular belief about a paradox for East Asian countries where corruption is positively associated with firm growth

Survey on Vietnamese teachers’ perspectives and perceived support during COVID-19

The COVID-19 pandemic has caused unprecedented damage to the educational system worldwide. Besides the measurable economic impacts in the short-term and long-term, there is intangible destruction within educational institutions. In particular, teachers – the most critical intellectual resources of any schools – have to face various types of financial, physical, and mental struggles due to COVID-19. To capture the current context of more than one million Vietnamese teachers during COVID-19, we distributed an e- survey to more than 2,500 randomly selected teachers from two major teacher communities on Facebook from 6th to 11th April 2020. From over 373 responses, we excluded the observations which violated our cross-check questions and retained 294 observations for further analysis. This dataset includes: (i) Demographics of participants; (ii) Teachers' perspectives regarding the operation of teaching activities during the pandemic; (iii) Teachers' received support from their schools, government bodies, other stakeholders such as teacher unions, and parents' associations; and (iv) teachers' evaluation of school readiness toward digital transformation. Further, the dataset was supplemented with an additional question on the teachers' primary source of professional development activities during the pandemic