DISCUSSING PERSONAL DATA PROTECTION DURING ARBITRATION PROCEEDINGS AND LESSONS FOR VIETNAM

In today's society, where digital technologies have a pervasive influence, data protection has emerged as a paramount concern across various scientific fields. In the realm of legal science, international arbitration, as an alternative dispute resolution mechanism, also faces its own challenges in this regard. This article delves into the issue of personal data, the urgency of data protection in international arbitration, and, through an analysis of typical data protection regulations worldwide, domestic laws on data protection in general and in arbitration proceedings in particular. Based on this analysis, the article proposes recommendations for enhancing data protection in arbitration proceedings, contributing to the improvement of the Draft Commercial Arbitration Law of Vietnam.  Article visualizations

Inquiry-based learning: an effective approach to teaching science aiming to develop students’ competencies

Competency-based learning is among major changes of 2018 in Vietnam’s school curriculum, where teaching and learning aim to help school students develop core qualities and competencies in order to be successful in school, life, and prospective workplace. As this educational approach is relatively unfamiliar to Vietnamese teachers, they may feel confused about appropriate teaching strategies allowing them to obtain the new teaching goals. This would be the case when teachers have to teach integrated subjects such as Science in lower-secondary education. This paper will elaborate why inquiry-based instruction could be an effective approach that enables secondary teachers to accomplish their professional work in terms of facilitating their students to develop core competencies and those in Science. Some recommendations on teacher education and training will be made to enhance the successful implementation of inquiry-based teaching in Vietnamese classrooms

Comparison of soot radiation in diesel flame given by mathematical model and by experimental data

An integral unidirectional model is established to calculate radiation heat transfer of Diesel flame in the open air and in combustion chamber of engine. Based on the temperature and soot fraction given by the flamlet theory and soot formation model of Tesner-Magnussen, radiation of soot particulate cloud at different positions of flame is determined and compared with experimental data obtained by the two-color method.The results show that the radiation given by the model is 203 lower than that produced by experiments on the stationary flame in open air. Soot radiation intensity in the Diesel engine increases in function of load and engine speed regimes and its maximum value (about 2000 kW/m2) is reached when the highest pressure is attained in combustion chamber

Damage detection for a cable-stayed Bridge under the effect of moving loads using Transmissibility and Artificial Neural Network

Artificial Neural Network (ANN) has been widely used for Structural Health Monitoring (SHM) in the last decades. To detect damage in the structure, ANN often uses input data consisting of natural frequencies or mode shapes. However, this data is not sensitive enough to accurately identify minor structural defects. Therefore, in this study, we propose to use transmissibility to generate input data for the input layer of ANN. Transmissibility uses output signals exclusively to preserve structural dynamic properties and is sensitive to damage characteristics. To evaluate the efficiency of the proposed approach, a cable-stayed bridge with a wide variety of damage scenarios is employed. The results show that the combination of transmissibility and ANN not only accurately detect damages but also outperforms natural frequencies-based ANN in terms of accuracy and computational cost

Damage detection for a cable-stayed Bridge under the effect of moving loads using Transmissibility and Artificial Neural Network

Artificial Neural Network (ANN) has been widely used for Structural Health Monitoring (SHM) in the last decades. To detect damage in the structure, ANN often uses input data consisting of natural frequencies or mode shapes. However, this data is not sensitive enough to accurately identify minor structural defects. Therefore, in this study, we propose to use transmissibility to generate input data for the input layer of ANN. Transmissibility uses output signals exclusively to preserve structural dynamic properties and is sensitive to damage characteristics. To evaluate the efficiency of the proposed approach, a cable-stayed bridge with a wide variety of damage scenarios is employed. The results show that the combination of transmissibility and ANN not only accurately detect damages but also outperforms natural frequencies-based ANN in terms of accuracy and computational cost

All-dielectric Metamaterial for Electromagnetically-induced Transparency in Optical Region

Metamaterial (MM) is emerging as a promising approach to manipulate electromagnetic waves, spanning from radio frequency to the optical region. In this paper, we employ an effect called electromagnetically-induced transparency (EIT) in all-dielectric MM structures to create a narrow transparent window in opaque broadband of the optical region (580-670 nm). Using dielectric materials instead of metals can mitigate the large non-radiative ohmic loss on the metal surface. The unit-cell of MM consists of Silicon (Si) bars on Silicon dioxide (SiO$_{2}$) substrate, in which two bars are directed horizontally and one bar is directed vertically. By changing the relative position and dimension of the Si bars, the EIT effect could be achieved. The optical properties of the proposed MM are investigated numerically using the finite difference method with commercial software Computer Simulation Technology (CST). Then, characteristic parameters of MM exhibiting EIT effect (EIT-MM), including Q-factor, group delay, are calculated to evaluate the applicability of EIT-MM to sensing and light confinement

Adaptive fuzzy-neural network effectively disturbance compensate in sliding mode control for dual arm robot

In this study, an Adaptive Backstepping Sliding Mode Controller (ABSMC) is introduced based on the Radial Basis Function (RBF) neural network and a fuzzy logic modifier. The proposed method is used to control a Dual-Arm Robot (DAR) – a nonlinear structure with unstable parameters and external disturbances. The control aims to track the motion trajectory of both arms in the flat surface coordinate within a short time, maintaining stability, and ensuring that the tracking error converges in finite time, especially when influenced by unforeseen external disturbances. The nonlinear Backstepping Sliding Mode Control (BSMC) is effective in trajectory tracking control; however, undesired phenomena may occur if there are uncertain disturbances affecting the system or model parameters change. It is proposed to use a neural network to estimate a nonlinear function to handle unknown uncertainties of the system. The neural network parameters can be adaptively adjusted to optimal values through adaptation rules derived from Lyapunov's theorem. Additionally, fuzzy logic theory is also employed to adjust the controller parameters to accommodate changes or unexpected impacts. The performance of the Fuzzy Neural Network Backstepping Sliding Mode Control (FNN-BSMC) is evaluated through simulation results using Matlab/Simulink software. Two simulation cases are conducted: the first case assumes stable model parameters without uncertain disturbances affecting the joints, while the second case considers a model with changing parameters and disturbances. Simulation results demonstrate the effective adaptability of the proposed method when the system model is affected by various types of uncertainties from the environmen

Status Poles and Status Zoning to Model Residential Land Prices: Status-Quality Trade off Theory (Short Paper)

This study describes an approach for augmenting urban residential preference and hedonic house price models by incorporating Status-Quality Trade Off theory (SQTO). SQTO seeks explain the dynamic of urban structure using a multipolar, in which the location and strength of poles is driven by notions of residential status and dwelling quality. This paper presents in outline an approach for identifying status poles and for quantifying their effect on land and residential property prices. The results show how the incorporation of SQTO results in an enhanced understanding of variations in land / property process with increased spatial nuance. A number of future research areas are identified related to the status pole weights and the development of status pole index

Direct and indirect costs of smoking in Vietnam

This study was designed to overcome limitations of two previous investigations by calculating both direct and indirect health costs of five smoking-related diseases that are responsible for almost 75% of all smoking-related deaths in Vietnam: lung cancer, cancers of the upper aerodigestive tract, chronic obstructive pulmonary disease, ischaemic heart disease and stroke. Understanding the healthcare system is crucial for calculating the actual cost of smoking in Vietnam. The total estimated economic cost of smoking for five smoking-related diseases was 24 679.9 billion VND (US$1173.2 million), not taking into account exposure to second hand smoke