What Shapes Undergraduate Students’ Satisfaction in Unstable Learning Contexts?

This paper investigates what determinants, and to what extent, they influence students’ satisfaction in unstable learning contexts. Using a national-scaled sample of Vietnamese HEIs with a sound theoretical background, we find that regardless of instabilities from external shocks, the key factors that shape students’ satisfaction are fixed by traditional norms (self-efficacy, infrastructure, lecturer) rather than occasional factors occurring from each event. We find in particular that self-efficacy is the most influential factor for students’ satisfaction and friendship is the most prominent element that enhances students’ self- efficacy. Overall, this paper enriched the literature on student satisfaction, especially during unstable contexts. Thus, it has important implications for educators and HEIs stakeholders in management planning in the time to come

The status of invasive plants and animals in Cu Lao Cham biosphere reserve, Quang Nam province, Vietnam

The biodiversity of Cu Lao Cham Biosphere Reserve (Hoi An City, Quang Nam Province) has been faced with some passive impacts, one of which is invasion/expansion of alien species. In 2017, according to the data of GISD, CABI and the Inter-ministerial Circular No.27/2013/TTLT-BTNMT-BNNPTNT, based on filed survey conducted in May, 19 alien plant and 3 alien animal species were recorded in the biosphere reserve. Among them, 13 plant species were identified as invaders, of which details were assessed in this study; among those invader plants, 3 species were ranked at medium risk and the 10 others were ranked at low risk. All of the medium risk-invasive plant species have been appeared on the islands but one of them - siam weed (Chromolaena odorata) were not identified as impacting to the mainland of the biosphere reserve. Likewise, all of the alien animal species have been not recognized as the invasive species. In general, the impact of alien species found in the Cu Lao Cham was assessed as “Low Risk”. The impact status of invasive species in the Hoi An mainland part is more serious than the situation in the islands. Base on the results, we suggest that, five species, beggar-ticks (Bidens pilosa), coast morning glory (Ipomoea cairica) Bay Biscayne creeping-oxeye (Sphagneticola trilobata), Blue porterweed (Stachytarpheta jamaicensis) and billygoat-weed (Ageratum conyzoides) should be added in the invasive appendix of the national invasive species list while three other species as vilfa stellata (Cynodon dactylon), guava (Psidium guava) and rose myrtle (Rhodomyrtus tomentosa) should be listed in the potential appendix of that list. It is necessary to conduct some survey to obtain solution to control invasive species as soon as possible to protect the biodiversity of this study area. Citation: Vu Anh Tai, Uong Dinh Khanh, Luu The Anh, Le Thi Thu Hien, 2017. The status of invasive plants and animals in Cu Lao Cham biosphere reserve, Quang Nam province, Vietnam. Tap chi Sinh hoc, 39(4): 434-450. DOI: 10.15625/0866-7160/v39n4.10082.*Corresponding author: [email protected] 15 June 2017, accepted 12 December 201

A Status Data Transmitting System for Vessel Monitoring

This paper presents a status data transmitting system suitable for vessel monitoring. The system consists of four main parts, which are a status data module, a frequency synthesizer, a power amplifier and a horn antenna. The status data module packs information of the identification, longitude, latitude and state of the vessel into data frames. FSK/MSK/GMSK schemes were used to modulate the data. The frequency synthesizer was designed with very high stability over temperature and very low frequency tolerance. The power amplifier provides 130 W output power at S band. The impedance bandwidth of the horn antenna can be controlled using the beveling technique

Efficiency of Farmer Organisations in Supplying Supermarkets with Quality Food in Vietnam

The development of supermarkets in Vietnam, as in other emerging countries, goes along with an increasing concern on the part of purchasers for food quality. The paper investigates whether farmer organisations are able to help small-scale farmers get access to supermarkets, and the role that supermarkets and public support play in their emergence and development. It is based on case studies involving a number of stakeholders marketing vegetables, flavoured rice and litchi fruit in Vietnam. The interviews investigated patterns of horizontal and vertical coordination that link farmers to supermarkets, the distribution of costs and benefits between farmers and traders along the chains in relation to the strategy of quality differentiation. Eight farmer associations that work in the form of private commercial organisations are regular supermarket suppliers for the selected products. Their ability to supply supermarkets is related to the combination of functions they make available to their members, especially as regards training to improve quality (appearance, taste, safety), quality promotion and control, for which they receive public support, as well as their participation in flexible contracts with supermarkets, shops and schools. Supermarket supply through farmer associations increases farmer incomes when compared with traditional chains, yet the situation is reported to change with the increase in supermarket competition. The paper argues that changes in farmer organisation are not only due to supplying supermarkets, but also to public and international support to food quality improvement, which have been of benefit to supermarkets.Agribusiness, Industrial Organization,

MINING TOP-K FREQUENT SEQUENTIAL PATTERN IN ITEM INTERVAL EXTENDED SEQUENCE DATABASE

Abstract. Frequent sequential pattern mining in item interval extended sequence database (iSDB) has been one of interesting task in recent years. Unlike classic frequent sequential pattern mining, the pattern mining in iSDB also consider the item interval between successive items; thus, it may extract more meaningful sequential patterns in real life. Most previous frequent sequential pattern mining in iSDB algorithms needs a minimum support threshold (minsup) to perform the mining. However, it’s not easy for users to provide an appropriate threshold in practice. The too high minsup value will lead to missing valuable patterns, while the too low minsup value may generate too many useless patterns. To address this problem, we propose an algorithm: TopKWFP – Top-k weighted frequent sequential pattern mining in item interval extended sequence database. Our algorithm doesn’t need to provide a fixed minsup value, this minsup value will dynamically raise during the mining proces

PILOT SCALE STUDY ON AMMONIUM REMOVAL IN PHAP VAN WATER PLANT, HANOI CITY

Joint Research on Environmental Science and Technology for the Eart

XGV-BERT: Leveraging Contextualized Language Model and Graph Neural Network for Efficient Software Vulnerability Detection

With the advancement of deep learning (DL) in various fields, there are many attempts to reveal software vulnerabilities by data-driven approach. Nonetheless, such existing works lack the effective representation that can retain the non-sequential semantic characteristics and contextual relationship of source code attributes. Hence, in this work, we propose XGV-BERT, a framework that combines the pre-trained CodeBERT model and Graph Neural Network (GCN) to detect software vulnerabilities. By jointly training the CodeBERT and GCN modules within XGV-BERT, the proposed model leverages the advantages of large-scale pre-training, harnessing vast raw data, and transfer learning by learning representations for training data through graph convolution. The research results demonstrate that the XGV-BERT method significantly improves vulnerability detection accuracy compared to two existing methods such as VulDeePecker and SySeVR. For the VulDeePecker dataset, XGV-BERT achieves an impressive F1-score of 97.5%, significantly outperforming VulDeePecker, which achieved an F1-score of 78.3%. Again, with the SySeVR dataset, XGV-BERT achieves an F1-score of 95.5%, surpassing the results of SySeVR with an F1-score of 83.5%

Modelling the relationship between crude oil and agricultural commodity prices

The food-energy nexus has attracted great attention from policymakers, practitioners and academia since the food price crisis during the 2007-2008 Global Financial Crisis (GFC), and new policies that aim to increase ethanol production. This paper incorporates aggregate demand and alternative oil shocks to investigate the causal relationship between agricultural products and oil markets, which is a novel contribution. For the period January 2000 - July 2018, monthly spot prices of 15 commodities are examined, including Brent crude oil, biofuel-related agricultural commodities, and other agricultural commodities. The sample is divided into three sub-periods, namely: (i) January 2000 - July 2006; (ii) August 2006 - April 2013; and (iii) May 2013 - July 2018. The Structural Vector Autoregressive (SVAR) model, impulse response functions, and variance decomposition technique are used to examine how the shocks to agricultural markets contribute to the variance of crude oil prices. The empirical findings from the paper indicate that not every oil shock contributes the same to agricultural price fluctuations, and similarly for the effects of aggregate demand shocks on the agricultural market. These results show that the crude oil market plays a major role in explaining fluctuations in the prices and associated volatility of agricultural commodities