Combination of Domain Knowledge and Deep Learning for Sentiment Analysis of Short and Informal Messages on Social Media

Sentiment analysis has been emerging recently as one of the major natural language processing (NLP) tasks in many applications. Especially, as social media channels (e.g. social networks or forums) have become significant sources for brands to observe user opinions about their products, this task is thus increasingly crucial. However, when applied with real data obtained from social media, we notice that there is a high volume of short and informal messages posted by users on those channels. This kind of data makes the existing works suffer from many difficulties to handle, especially ones using deep learning approaches. In this paper, we propose an approach to handle this problem. This work is extended from our previous work, in which we proposed to combine the typical deep learning technique of Convolutional Neural Networks with domain knowledge. The combination is used for acquiring additional training data augmentation and a more reasonable loss function. In this work, we further improve our architecture by various substantial enhancements, including negation-based data augmentation, transfer learning for word embeddings, the combination of word-level embeddings and character-level embeddings, and using multitask learning technique for attaching domain knowledge rules in the learning process. Those enhancements, specifically aiming to handle short and informal messages, help us to enjoy significant improvement in performance once experimenting on real datasets.Comment: A Preprint of an article accepted for publication by Inderscience in IJCVR on September 201

AN EVIDENCE FOR THE CONTRIBUTION OF ANAMMOX PROCESS IN NITROGEN REMOVAL FROM GROUNDWATER

Joint Research on Environmental Science and Technology for the Eart

Advanced Method for Motion Control of a 3 DOFs Lower Limb Rehabilitation Robot

This paper presents two motion control methods for a lower limb rehabilitation robot based on compensate gravity proportional-derivative and inverse dynamic proportional-derivative (PD) control algorithms. The Robot’s mechanism is comprised of three active joints: hip joint, knee joint and ankle joint, which are driven by DC motors. Firstly, based on Robot’s mechanism, a dynamic model of the Robot is built. Then, based on Robot’s model, motion control systems for Robot are designed. Simulation results show good performances and workability of these proposed controllers. Finally, the calculation of the joint angle errors and toque of each controller is performed. The comparison of simulation results between proposed controllers and the adaptive fuzzy controller allows to choice suitable motion control methods for Robot that can meet the requirements of a 3 DOFs lower limb rehabilitation robot for post-stroke patient

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

NGHIÊN CỨU SỬ DỤNG DỮ LIỆU CÁC AXIT BÉO TRONG PHÂN LOẠI HOÁ HỌC THỰC VẬT (CHEMOTAXONOMY) ĐỐI VỚI CÁC LOÀI RONG ĐỎ

In this paper, the compositions and contents of fatty acids in the total lipid extracts of 69 red seaweed samples belonging to 9 families (Gracilariaceae, Hypneaceae, Ceramiaceae, Bangiaceae, Hylamaniaceae, Bonnemaisoniaceae, Phyllophoraceae, Rhodymeniaceae and Halymeniaceae) are studied. According to the results, 56 fatty acids are identified, in which 12 fatty acids were considered “fatty acid markers” for the botanical classification (Chemotaxonomy) of red seaweed species such as C14:0, C15:0, C16:0, C16:1n-7, C18:0, C18:1n-9, C18:1n-7, C18:2n-6, C20:3n-6, C20:4n-6, C20:5n-3 and C22:0. By using principal component analysis method (PCA), the analysis result on two-dimensional chart showed that families of red seaweed are distributed into separate regions. Classification tree diagram of the red seaweed species based on essential fatty acid composition is also given.Chúng tôi đã tiến hành nghiên cứu thành phần và hàm lượng các axit béo trong dịch chiết lipit tổng của 69 mẫu rong đỏ Rhodophyta thuộc 9 họ Gracilariaceae, Hypneaceae, Ceramiaceae, Bangiaceae, Hylamaniaceae, Phyllophoraceae, Rhodymeniaceae, họ Halymeniaceae. Kết quả đã xác định được 56 axit béo trong đó có 12 axit béo là C14:0, C15:0, C16:0, C16:1n-7, C18:0, C18:1n-9, C18:1n-7, C18:2n-6, C20:3n-6, C20:4n-6, C20:5n-3 và C22:0 được sử dụng là những chất đánh dấu cho việc phân loại hoá học thực vật (Chemotaxonomy) đối với các loài rong đỏ. Sử dụng phương pháp phân tích cấu tử chính (PCA), kết quả thể hiện qua giản đồ hai chiều, các họ rong đỏ phân định thành các vùng riêng rẽ. Chúng tôi cũng đưa ra sơ đồ cây phân loại của các loài rong đỏ theo thành phần axit béo chính yếu

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

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

Sero-epidemiological status and risk factors of toxoplasmosis in pregnant women in Northern Vietnam

Background: In Vietnam, few studies have determined the epidemiological status of toxoplasmosis in pregnant women and no routine prenatal screening is in place. This study was conducted to evaluate the seroprevalence of this zoonotic parasitic infection in pregnant women in Northern Vietnam and to assess the association with awareness, risk factors and congenital toxoplasmosis. Methods: Approximately 800 pregnant women were included in the study from two hospitals, one in Hanoi and one in Thai Binh province, which is known to have a dense cat population. Serological immunoglobulin G (IgG) and immunoglobulin M (IgM) detection was performed to estimate the seroprevalence of toxoplasmosis and sero-incidence of maternal and congenital toxoplasmosis. In addition, a survey was conducted about awareness, clinical history, presentation of signs and symptoms relating to toxoplasmosis and to detect biologically plausible and socio-demographic risk factors associated with toxoplasmosis. Associations with seroprevalence were assessed using univariable and multivariable analysis. Results: The mean IgG seroprevalence after the full diagnostic process was 4.5% (95% confidence interval(CI): 2.7–7.0) and 5.8% (95% CI: 3.7–8.6) in Hanoi and Thai Binh hospital, respectively, and included one seroconversion diagnosed in Thai Binh hospital. Only 2.0% of the pregnant women in Hanoi hospital and 3.3% in Thai Binh hospital had heard about toxoplasmosis before this study. Conclusion: Since the percentage of seronegative, and thus susceptible, pregnant women was high and the awareness was low, we suggest to distribute information about toxoplasmosis and its prevention among women of child bearing age. Furthermore, future studies are recommended to investigate why such a low seroprevalence was seen in pregnant women in Northern Vietnam compared to other countries in South East Asia and globally