Orientations et réalités de l’enseignement de l’histoire au Vietnam

La mondialisation s’intensifiant, l’enseignement en général et l’enseignement de l’histoire des nations en particulier sont confrontés à de nouvelles opportunités et à de nouveaux enjeux. Dans ce contexte, la question des finalités de l’enseignement de l’histoire n’est pas simple : il ne suffit pas de dire que l’histoire a pour but de comprendre le passé et de mieux préparer l’avenir. Cet article analyse le contexte et les principaux paramètres qui déterminent actuellement l’enseignement de l’histoire au Vietnam. Il présente des réalisations mais aussi des limites dans les réalités de cet enseignement. Il propose enfin des pistes d’amélioration.As globalization intensifies, teaching in general, and the teaching of the history of nations in particular, both find themselves confronted with new opportunities and new issues. In this context, the question of the purpose of history teaching is not a simple one: it is not enough to say that the aim of history is to understand the past and better prepare for the future. This paper analyses the context and main factors that currently determine history teaching in Vietnam. It presents some achievements but also some limitations of this teaching today. Lastly, it makes some suggestions for improvement.A medida que crece la mundialización, la enseñanza en general y la enseñanza de la historia de las naciones en particular se confrontan a nuevas oportunidades y distintos retos. En este contexto, el interés de la enseñanza de la historia no es tan simple : no basta con decir que la historia sirve para comprender el pasado y preparar mejor el futuro. Este artículo analiza el contexto y los principales parámetros que determinan actualmente la enseñanza de la historia en Vietnam. Y presenta las realizaciones, pero también los límites en las realidades de esta enseñanza. Por último, sugiere posibilidades de mejora

Parameter Estimation and Predictive Speed Control of Chopper-Fed Brushed DC Motors

This paper presents an effective speed control method for brushed DC motors fed by a DC chopper using the concept of Finite Control Set-Model Predictive Control (FCS-MPC). As this control algorithm requires the parameters of the controlled object, the estimation of motor parameters is first performed by using two types of data. The first data includes the output speed response corresponding to the step input voltage to obtain the transfer function in the no-load regime. The second data consists of the motor speed and armature current when a load torque is applied to the motor shaft. The discrete-time equation of the motor armature circuit is used to obtain the future values of the armature circuit current and the motor speed. A cost function is defined based on the difference between the reference and predicted motor speed. The optimal switching states of the DC chopper are selected corresponding to the maximum value of the cost function. The performance of the proposed speed control algorithm is validated on an experimental system. The simulation and experimental results obtained show that the MPC controller can outperform the conventional proportional-integral (PI) controller

Transfer AdaBoost SVM for Link Prediction in Newly Signed Social Networks using Explicit and PNR Features

AbstractIn signed social network, the user-generated content and interactions have overtaken the web. Questions of whom and what to trust has become increasingly important. We must have methods which predict the signs of links in the social network to solve this problem. We study signed social networks with positive links (friendship, fan, like, etc) and negative links (opposition, anti-fan, dislike, etc). Specifically, we focus how to effectively predict positive and negative links in newly signed social networks. With SVM model, the small amount of edge sign information in newly signed network is not adequate to train a good classifier. In this paper, we introduce an effective solution to this problem. We present a novel transfer learning framework is called Transfer AdaBoost with SVM (TAS) which extends boosting-based learning algorithms and incorporates properly designed RBFSVM (SVM with the RBF kernel) component classifiers. With our framework, we use explicit topological features and Positive Negative Ratio (PNR) features which are based on decision-making theory. Experimental results on three networks (Epinions, Slashdot and Wiki) demonstrate our method that can improve the prediction accuracy by 40% over baseline methods. Additionally, our method has faster performance time

Explaining the Organizational Commitment of Banking Employees

This study aims to demonstrate the factors influencing the organizational commitment of banking employees. The study surveyed 232 employees working in the commercial banking system in Vietnam. By combining qualitative and quantitative research methods, the study has shown that employees’ commitment to the organization is influenced by 8 factors, including the work environment, corporate culture, organizational support, job nature, training and development, income and benefits, peer relationships, and leadership style. Among these factors, leadership style is the most significant factor affecting employees’ commitment to the organization. The research results contribute to providing insights for managers to enhance the employees’ commitment to the organization in the banking sector

SEASONAL VARIATION OF PHYTOPLANKTON FUNCTIONAL GROUPS IN TUYEN LAM RESERVOIR, CENTRAL HIGHLANDS, VIETNAM

Seasonal changes in freshwater phytoplankton assemblages at Tuyen Lam Reservoir in the Central Highlands of Vietnam were classified into 23 functional groups based on physiological, morphological, and ecological characteristics. A total of 168 species were recorded during 10 surveys from 2015 to 2019 at 7 sampling sites, with Chlorophyta dominating in number of species. Phytoplankton abundance varied from 0.18×105 to 21.2×105 cells/L during the study period, mainly due to cyanobacteria. Seven of the 23 functional groups were considered to be dominant (relative density > 5%).  The dominant functional groups were groups M and G in the dry season and groups M, G, P, and E in the rainy season. Group M (Microcystis aeruginosa) was the most common in both seasons, while group P (Closterium, Staurastrum, Aulacoseira), group E (Dinobryon, Synura), and group G (Sphaerocystis, Eudorina) were more common in the rainy season. The Shannon diversity index (H¢) showed that phytoplankton communities were relatively diverse and that most of the study sites were lightly polluted. However, the ecological status has deteriorated at some locations due to the overgrowth of group M, leading to eutrophication in this reservoir. This study highlights the usefulness of functional groups in the study of seasonal changes in phytoplankton dynamics. Functional groups are applied for the first time at Tuyen Lam Reservoir and can be used to predict early-stage cyanobacterial blooms in future studies

Students’ perceptions of using note-taking in consecutive interpreting assignments

Note-taking is critical in helping interpreters memorize detailed information both quickly and accurately. Therefore, the present study was conducted as a questionnaire survey at a university in the Mekong Delta of Vietnam to investigate how students, specifically student interpreters, perceive note-taking in consecutive interpreting assignments. In detail, this study explores the students’ perceptions of the benefits and the challenges of using note-taking in consecutive interpreting assignments. The participants in this study comprised 160 students majoring in English Interpretation and Translation. Furthermore, they have taken consecutive interpreting courses and experienced taking notes in consecutive interpreting tasks. The findings of this study indicated that most students had good perceptions about note-taking used in consecutive interpretation and perceived its benefits and challenges. Moreover, some pedagogical implications for both students and teachers are made. Specifically, the study suggests that students should frequently practice it to acquire good note-taking skills. Teachers should make effective lecture designs to help students improve their note-taking skills and consecutive interpreting performance

Recent remarkable records reveal that Phia Oac-Phia Den Nature Reserve is a priority area for bat conservation in Northern Vietnam

AbstractThree short field surveys were conducted in the Phia Oac-Phia Den Nature Reserve to assess the species diversity and endemism of local bat fauna. In combination with data from a previous study, 24 bat species of 5 families, representing > 20% of the national bat diversity, were recorded in the study area. The occurrence of several bat species restricted to montane forests, that is, Murina chrysochaetes, Pipistrellus coromandra, and a potentially new species Rhinolophus cf. macrotis, suggests that Phia Oac is an important area for bat conservation in Vietnam and thus more comprehensive studies need to be performed

Gauge Bosons in the 3-3-1 Model with Three Neutrino Singlets

We show that the mass matrix of electrically neutral gauge bosons in the recent proposed  model based on $\mathrm{SU}(3)_C\otimes \mathrm{SU}(3)_L\otimes \mathrm{U}(1)_X$ group with three neutrino singlets [9] has two exact eigenvalues and corresponding eigenvectors. Hence the neutral non-Hermitian gauge boson $X^0_\mu$ is properly determined.With extra vacuum expectation values of the Higgs fields, there are mixings among charged gauge bosons $W^\pm$ and $Y^\pm$ as well as amongneutral gauge bosons $Z, Z'$ and $X^0$. From the $W$ boson decay width, we get lower bound on  scale of the model about few TeVs

Flexible interactive retrieval SysTem 3.0 for visual lifelog exploration at LSC 2022

Building a retrieval system with lifelogging data is more complicated than with ordinary data due to the redundancies, blurriness, massive amount of data, various sources of information accompanying lifelogging data, and especially the ad-hoc nature of queries. The Lifelog Search Challenge (LSC) is a benchmarking challenge that encourages researchers and developers to push the boundaries in lifelog retrieval. For LSC'22, we develop FIRST 3.0, a novel and flexible system that leverages expressive cross-domain embeddings to enhance the searching process. Our system aims to adaptively capture the semantics of an image at different levels of detail. We also propose to augment our system with an external search engine to help our system with initial visual examples for unfamiliar concepts. Finally, we organize image data in hierarchical clusters based on their visual similarity and location to assist users in data exploration. Experiments show that our system is both fast and effective in handling various retrieval scenarios