A hybrid model for aspect-based sentiment analysis on customer feedback: research on the mobile commerce sector in Vietnam

Feedback and comments on mobile commerce applications are extremely useful and valuable information sources that reflect the quality of products or services to determine whether data is positive or negative and help businesses monitor brand and product sentiment in customers’ feedback and understand customers’ needs. However, the increasing number of comments makes it increasingly difficult to understand customers using manual methods. To solve this problem, this study builds a hybrid research model based on aspect mining and comment classification for aspect-based sentiment analysis (ABSA) to deeply comprehend the customer and their experiences. Based on previous classification results, we first construct a dictionary of positive and negative words in the e-commerce field. Then, the POS tagging technique is applied for word classification in Vietnamese to extract aspects of model commerce related to positive or negative words. The model is implemented with machine and deep learning methods on a corpus comprising more than 1,000,000 customer opinions collected from Vietnam's four largest mobile commerce applications. Experimental results show that the Bi-LSTM method has the highest accuracy with 92.01%; it is selected for the proposed model to analyze the viewpoint of words on real data. The findings are that the proposed hybrid model can be applied to monitor online customer experience in real time, enable administrators to make timely and accurate decisions, and improve the quality of products and services to take a competitive advantage

Asymmetry and Symmetry of real exchange rate effect on the bilateral trade balance between Vietnam and the United States: aggregated and disaggregated levels of investigation

Bilateral trade balance always deserves particular interest of policy makers and economists. In this paper, we examined the asymmetric and symmetric effect of real exchange rate on bilateral trade balance between Vietnam and the US at both aggregated and disaggregated commodity levels. We employed both Linear Autoregressive Distributed Lag (ARDL) and Non-linear ARDL (NARDL) models to a dataset spanning over 18 years. We found that (i) both symmetry and asymmetry of real exchange rates are not significant to explain the total trade balance between Vietnam and the United States; (ii) unlike the insignificant effect on the aggregated level, the empirical evidence at the disaggregated level is mixed and dependent on product category. Our findings reveal that (iii) the claim of unfair trade by using exchange rate from the US Treasury is unclear from our estimations; and (iv) a depreciation of USD (i.e. appreciation of VND) leads the long-run US’s trade balance will improve for 10 commodities, and whereas an appreciation of USD (depreciation of VND), long-run trade balance will improve for 11 commodities. The results suggest that only a number of specific industries will benefit from USD appreciation or depreciation

Asymmetry and Symmetry of real exchange rate effect on the bilateral trade balance between Vietnam and the United States: aggregated and disaggregated levels of investigation

Bilateral trade balance always deserves particular interest of policy makers and economists. In this paper, we examined the asymmetric and symmetric effect of real exchange rate on bilateral trade balance between Vietnam and the US at both aggregated and disaggregated commodity levels. We employed both Linear Autoregressive Distributed Lag (ARDL) and Non-linear ARDL (NARDL) models to a dataset spanning over 18 years. We found that (i) both symmetry and asymmetry of real exchange rates are not significant to explain the total trade balance between Vietnam and the United States; (ii) unlike the insignificant effect on the aggregated level, the empirical evidence at the disaggregated level is mixed and dependent on product category. Our findings reveal that (iii) the claim of unfair trade by using exchange rate from the US Treasury is unclear from our estimations; and (iv) a depreciation of USD (i.e. appreciation of VND) leads the long-run US’s trade balance will improve for 10 commodities, and whereas an appreciation of USD (depreciation of VND), long-run trade balance will improve for 11 commodities. The results suggest that only a number of specific industries will benefit from USD appreciation or depreciation

A Non-destructive Radar Device for Detecting Additive Materials in Concrete

The use of electronic devices based on electromagnetic waves is promising for inspecting additives in structural concrete. However, the existing commercial devices are high-cost and do not publicly provide circuit design information. To overcome this issue, this study designed a low-cost nondestructive testing device with a radar sensor, using an HB-100 radar sensor module to generate and receive the radar wave. A suitable bandpass filter was used to suppress electrical noise in the received signal, an Arduino board was used for signal processing, and the measured data were displayed on a computer. The output at the IF pin of the sensor module presents the Doppler frequency and absorbance of the target materials. The device was tested to detect additives inside the concrete. An additive material can be recognized by the fact that the obtained signal magnitudes are different with different additive materials. The findings in this study can contribute to making a low-cost nondestructive testing device based on radar technology for structural concrete inspection

How scientific research changes the Vietnamese higher education landscape: Evidence from social sciences and humanities between 2008 and 2019

Background: In the context of globalization, Vietnamese universities, whose primary function is teaching, there is a need to improve research performance. Methods: Based on SSHPA data, an exclusive database of Vietnamese social sciences and humanities researchers’ productivity, between 2008 and 2019 period, this study analyzes the research output of Vietnamese universities in the field of social sciences and humanities. Results: Vietnamese universities have been steadily producing a high volume of publications in the 2008-2019 period, with a peak of 598 articles in 2019. Moreover, many private universities and institutions are also joining the publication race, pushing competitiveness in the country. Conclusions: Solutions to improve both quantity and quality of Vietnamese universities’ research practice in the context of the industrial revolution 4.0 could be applying international criteria in Vietnamese higher education, developing scientific and critical thinking for general and STEM education, and promoting science communication

How Digital Natives Learn and Thrive in the Digital Age: Evidence from an Emerging Economy

As a generation of ‘digital natives,’ secondary students who were born from 2002 to 2010 have various approaches to acquiring digital knowledge. Digital literacy and resilience are crucial for them to navigate the digital world as much as the real world; however, these remain under-researched subjects, especially in developing countries. In Vietnam, the education system has put considerable effort into teaching students these skills to promote quality education as part of the United Nations-defined Sustainable Development Goal 4 (SDG4). This issue has proven especially salient amid the COVID−19 pandemic lockdowns, which had obliged most schools to switch to online forms of teaching. This study, which utilizes a dataset of 1061 Vietnamese students taken from the United Nations Educational, Scientific, and Cultural Organization (UNESCO)’s “Digital Kids Asia Pacific (DKAP)” project, employs Bayesian statistics to explore the relationship between the students’ background and their digital abilities. Results show that economic status and parents’ level of education are positively correlated with digital literacy. Students from urban schools have only a slightly higher level of digital literacy than their rural counterparts, suggesting that school location may not be a defining explanatory element in the variation of digital literacy and resilience among Vietnamese students. Students’ digital literacy and, especially resilience, also have associations with their gender. Moreover, as students are digitally literate, they are more likely to be digitally resilient. Following SDG4, i.e., Quality Education, it is advisable for schools, and especially parents, to seriously invest in creating a safe, educational environment to enhance digital literacy among students

STEM education and outcomes in Vietnam: Views from the social gap and gender issues

United Nations’ Sustainable Development Goals 4 Quality Education has highlighted major challenges for all nations to ensure inclusive and equitable quality access to education, facilities for children, and young adults. The SDG4 is even more important for developing nations as receiving proper education or vocational training, especially in science and technology, means a foundational step in improving other aspects of their citizens’ lives. However, the extant scientific literature about STEM education still lacks focus on developing countries, even more so in the rural area. Using a dataset of 4967 observations of junior high school students from a rural area in a transition economy, the article employs the Bayesian approach to identify the interaction between gender, socioeconomic status, and students’ STEM academic achievements. The results report gender has little association with STEM academic achievements; however, female students (αa_Sex[2] = 2.83) appear to have achieved better results than their male counterparts (αa_Sex[1] = 2.68). Families with better economic status, parents with a high level of education (βb(EduMot) = 0.07), or non-manual jobs (αa_SexPJ[4] = 3.25) are found to be correlated with better study results. On the contrary, students with zero (βb(OnlyChi) = -0.14) or more than two siblings (βb(NumberofChi) = -0.01) are correlated with lower study results compared to those with only one sibling. These results imply the importance of providing women with opportunities for better education. Policymakers should also consider maintaining family size so the parents can provide their resources to each child equally

Policy Response, Social Media and Science Journalism for the Sustainability of the Public Health System Amid the COVID-19 Outbreak: The Vietnam Lessons

Vietnam, with a geographical proximity and a high volume of trade with China, was the first country to record an outbreak of the new Coronavirus disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 or SARS-CoV-2. While the country was expected to have a high risk of transmission, as of April 4, 2020—in comparison to attempts to contain the disease around the world—responses from Vietnam are being seen as prompt and effective in protecting the interests of its citizens, with 239 confirmed cases and no fatalities. This study analyzes the situation in terms of Vietnam’s policy response, social media and science journalism. A self-made web crawl engine was used to scan and collect official media news related to COVID-19 between the beginning of January and April 4, yielding a comprehensive dataset of 14,952 news items. The findings shed light on how Vietnam—despite being under-resourced—has demonstrated political readiness to combat the emerging pandemic since the earliest days. Timely communication on any developments of the outbreak from the government and the media, combined with up-to-date research on the new virus by the Vietnamese science community, have altogether provided reliable sources of information. By emphasizing the need for immediate and genuine cooperation between government, civil society and private individuals, the case study offers valuable lessons for other nations concerning not only the concurrent fight against the COVID-19 pandemic but also the overall responses to a public health crisis

Numerical simulation of all-normal dispersion visible to near-infrared supercontinuum generation in photonic crystal fibers with core filled chloroform

This study proposes a photonic crystal fiber made of fused silica glass, with the core infiltrated with chloroform as a new source of supercontinuum (SC) spectrum. We numerically study the guiding properties of the fiber structure in terms of characteristic dispersion and mode area of the fundamental mode. Based on the results, we optimized the structural geometries of the CHCl3-core photonic crystal fiber to support the broadband SC generations. The fiber structure with a lattice constant of 1 μm, a filling factor of 0.8, and the diameter of the first-ring air holes equaling 0.5 μm operates in all-normal dispersion. The SC with a broadened spectral bandwidth of 0.64 to 1.80 μm is formed by using a pump pulse with a wavelength of 850 nm, 120 fs duration, and power of 0.833 kW. That fiber would be a good candidate for all-fiber SC sources as cost-effective alternative to glass core fibers

An effective algorithm for reliability-based optimization of stiffened Mindlin plate

Nowadays, stiffened plates have been widely used in many branches of structural engineering such as aircraft, ships, bridges, buildings etc... In comparison with common bending plate structures, stiffened plates not only have larger bending stiffness but also use less amount of material. Hence, it usually has higher economic efficiency. However, to obtain high effectiveness in solving the design problems of the stiffened plate, the reliability-based optimization problems need to be established together with the ordinary numerical computing methods. Therefore, the paper presents an approach to establish and solve the reliability-based optimization problem for the stiffened Mindlin plate. To analyze the behavior of Mindlin plate, we use the recently proposed CS-DSG3 element. The random variables are chosen to be elastic modulus, density of mass and external force. The design variables are the thickness, the width and the height of the stiffened plate. The objective function can be the strain energy or the mass of the structure and subjected to the constraints of displacement or vibration frequency. The reliability-based optimization algorithm used in this paper is a three-step closed loop: 1) Estimating the random variables by the Reliability Index (RI) method; 2) Solving the optimization problem using Sequential Quadratic Programming (SQP) method; 3) Checking and estimating the reliability by the first-order reliability method (FORM) in which the limit state function is the limit of displacement or vibration frequency of the structure