Studying livestock breeding wastewater treatment with bentonite adsorbent

The possibility of using adsorbents (bentonite, diatomite and kaolinite) for obtaining adsorptive materials effective in livestock breeding wastewater treatment has been assessed. It has been shown on the example of ions of ammonia (NH4) and phosphate (PO43) that particles of bentonite have relatively high adsorption capacity. The data about adsorption kinetics have been processed with the use of first and second-order kinetic models. It has been revealed that the second-order kinetic model described better adsorption of ammonia and phosphate from aqueous solutions by particles of bentonit

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

High school teachers’ pedagogical beliefs in English as a foreign language writing instruction

Writing in a foreign language is deemed to be the most difficult language skill to learners, especially at high school level. Consequently, its teaching has become a challenging task for high school teachers in the Vietnamese context. Teacher beliefs related literature indicates that what teachers do in the classroom is directly governed by what they think and believe. Thereby, the current study adopted features of a survey research design to examine the English as a Foreign Language (EFL) high school teachers’ beliefs about writing and its teaching. A sample of seventy six EFL teachers from the eight selected high schools situated in Ho Chi Minh City was recruited for the current survey. The beliefs of EFL writing instruction of these teachers were elicited through two instruments of eighteen–item questionnaires and semi–structured interviews. Then the questionnaires were quantitatively analyzed and the interviews were qualitatively analyzed. Results of the study showed that most of the participants held different orientations about writing skill, teacher roles and its teaching. The study was closed by a brief conclusion of key findings

Thermal treatment of polyvinyl alcohol for coupling MoS2 and TiO2 nanotube arrays toward enhancing photoelectrochemical water splitting performance

Solar-driven photoelectrochemical (PEC) water splitting, using semiconductor photo-electrodes, is considered a promising renewable energy source and solution for environmental sustainability. Herein, we report polyvinyl alcohol (PVA) as a binder material for combining MoS2 and TiO2 nanotube arrays (TNAs) to improve PEC water splitting ability. By a thermal treatment process, the formation of the π conjunction in the PVA structure enhanced the PEC performance of MoS2 /TNAs, exhibiting linear sweeps in an anodic direction with the current density over 65 µA/cm2 at 0 V vs. Ag/AgCl. Besides, the photoresponse ability of MoS2 /TNAs is approximately 6-fold more significant than that of individual TNAs. Moreover, a Tafel slope of 140.6 mV/decade has been obtained for the oxygen evolution reaction (OER) of MoS2 /TNAs materials. © 2021 by the authLicensee MDPI, Basel, Switzerla

ANALYSIS OF THE POPULARITY OF VOCABULARY USED WHEN PERFORMING SPEAKING ACTIVITIES IN THE CLASS OF FIRST-YEAR ENGLISH LANGUAGE STUDENTS IN THE DIRECTION OF DISCOURSE ANALYSIS

Vocabulary learning is extremely important when learning a foreign language. Fluency in a language depends on vocabulary and its use in specific situations. Speaking well is using vocabulary flexibly and speaking fluently. Researching the popularity of vocabulary is analyzing the prevalence of vocabulary used by linguistics students in communication from discourse analysis. This is a topic the research team is working on. This project will help the researchers learn about common vocabulary that students often use to communicate outside or in the classroom. Thereby understanding whether the vocabulary that students use is diverse, rich, and for the right purpose or not. This study will help students have a more comprehensive view of the ways to use words in communication. In addition, it also helps students improve their communication vocabulary, helps in exams and can be useful for later work. In this study, the research team will investigate the students' ability to use spoken vocabulary, i.e., frequency and extent of vocabulary usage.  Article visualizations

An investigation of online teaching and lecturers' online teaching competence in Vietnam: A case study at universities of technology and education

The rapid digital transformation and the widespread influence of the COVID-19 pandemic have impacted higher education in Vietnam. This social setting fosters online teaching and lecturers’ online teaching competencies.  The aim of this study is to investigate online teaching competence at two universities of technology and education in Vietnam through a survey. Based on a review of the literature, an online teaching competence scale for lecturers was developed and its validity and reliability were evaluated using exploratory component analysis and Cronbach's alpha coefficients with data from 311 lecturers at two public universities of technology and education. The online teaching competency scale for lecturers consists of 25 items organized into five component competencies: “Understanding student learning”, “online session administration”, “digital content development and learning facilitation”, “technology” and “online learning outcomes assessment”. With the exception of “technology”, the remaining component competencies were identified as good. Not only online teaching modes but also online teaching activities and productions were also deployed to maintain learning activities especially during the COVID-19 pandemic at two universities. Recommendations for developing lecturers' online teaching competence were also considered

An identification of the tolerable time-interleaved analog-to-digital converter timing mismatch level in high-speed orthogonal frequency division multiplexing systems

High-speed Terahertz communication systems has recently employed orthogonal frequency division multiplexing approach as it provides high spectral efficiency and avoids inter-symbol interference caused by dispersive channels. Such high-speed systems require extremely high-sampling time-interleaved analog-to-digital converters at the receiver. However, timing mismatch of time-interleaved analog-to-digital converters significantly causes system performance degradation. In this paper, to avoid such performance degradation induced by timing mismatch, we theoretically determine maximum tolerable mismatch levels for orthogonal frequency division multiplexing communication systems. To obtain these levels, we first propose an analytical method to derive the bit error rate formula for quadrature and pulse amplitude modulations in Rayleigh fading channels, assuming binary reflected gray code (BRGC) mapping. Further, from the derived bit error rate (BER) expressions, we reveal a threshold of timing mismatch level for which error floors produced by the mismatch will be smaller than a given BER. Simulation results demonstrate that if we preserve mismatch level smaller than 25% of this obtained threshold, the BER performance degradation is smaller than 0.5 dB as compared to the case without timing mismatch

FedDCT: Federated Learning of Large Convolutional Neural Networks on Resource Constrained Devices using Divide and Co-Training

We introduce FedDCT, a novel distributed learning paradigm that enables the usage of large, high-performance CNNs on resource-limited edge devices. As opposed to traditional FL approaches, which require each client to train the full-size neural network independently during each training round, the proposed FedDCT allows a cluster of several clients to collaboratively train a large deep learning model by dividing it into an ensemble of several small sub-models and train them on multiple devices in parallel while maintaining privacy. In this co-training process, clients from the same cluster can also learn from each other, further improving their ensemble performance. In the aggregation stage, the server takes a weighted average of all the ensemble models trained by all the clusters. FedDCT reduces the memory requirements and allows low-end devices to participate in FL. We empirically conduct extensive experiments on standardized datasets, including CIFAR-10, CIFAR-100, and two real-world medical datasets HAM10000 and VAIPE. Experimental results show that FedDCT outperforms a set of current SOTA FL methods with interesting convergence behaviors. Furthermore, compared to other existing approaches, FedDCT achieves higher accuracy and substantially reduces the number of communication rounds (with $4-8$ times fewer memory requirements) to achieve the desired accuracy on the testing dataset without incurring any extra training cost on the server side.Comment: Under review by the IEEE Transactions on Network and Service Managemen

Impacts of Economic Development on the Awareness of Cultural Preservation of Ethnic Minority People in the Border Region of Northern Vietnam

Purpose: The aim of this study is to examine how the Vietnamese government's economic development strategies affect ethnic minority people's knowledge of cultural preservation in the border area of Northern Vietnam.   Theoretical framework: The study focuses on three main driven factors of the awareness of cultural preservation that are economic changes, societal changes, and environmental changes from three economic fields: agriculture, industry, and trade and services.   Design/methodology/approach: The research sample was taken from ethnic minorities in Northern Vietnam's border area. For questionnaire administration, interviewees are selected at random from the population. Face-to-face, drop-off, and phone-calling approaches were used to disseminate the questionnaire. We received 544 completed returns out of 725 surveys sent out. The data was then cleaned and analyzed with SPSS 20 software using Partial Least Squares Structural Equation Modelling (PLS-SEM).   Findings: The results of a study of ethnic minority communities in seven provinces in Northern Vietnam's border region show that the development of agriculture, industry, trade and service significantly impacts ethnic minority people's awareness of cultural preservation issues due to environmental changes. In contrast, economic and sociological developments appear to have little influence on ethnic minority people's attention to cultural preservation. This phenomenon may be due to the long-term effects of economic and sociological changes, which mostly affect intangible cultural heritages. In contrast, environmental impats are felt swiftly and primarily on physical cultural heritages that can be seen.   Research, Practical & Social implications: The findings of the research provide policymakers with valuable insights on the effects of economic development on cultural preservation. The study's recommendations can inform policies that promote sustainable economic development while preserving the cultural heritage of ethnic minority communities.   Originality/value: The research focuses on the border region of Northern Vietnam, which is an area of strategic importance for economic development and cultural preservation. The study's unique focus on this region provides insights into the cultural and economic dynamics of a specific area that has not been extensively studied

A Multitask Data-Driven Model for Battery Remaining Useful Life Prediction

Lithium-ion batteries (LIBs) have recently been used widely in moving devices. Understand status of the batteries can help to predict the failure and improve the effectiveness of using them. There are some lithium-ion information that define the battery health over time. These are state-of-charge (SOC), state-of-health (SOH), and remaining-useful-life (RUL). Normally, a LIB is working under charging and discharging cycles continuously. In this paper, we will focus on the data dependency of different time-slots in a cycle and in a sequence of cycles to retrieve RUL. We leverage multi-channel inputs such as temperature, voltage, current and the nature of peaks cross the cycles to improve our prediction. Comparing to existing methods, the experiments show that we can improve from 0.040 to 0.033 (reduce 17.5%) in RMSE loss, which is significant