NAVIGATION STRATEGY FOR MOBILE ROBOT BASED ON COMPUTER VISION AND YOLOV5 NETWORK IN THE UNKNOWN ENVIRONMENT

Intelligent mobile robots must possess the ability to navigate in complex environments. The field of mobile robot navigation is continuously evolving, with various technologies being developed. Deep learning has gained attention from researchers, and numerous navigation models utilizing deep learning have been proposed. In this study, the YOLOv5 model is utilized to identify objects to aid the mobile robot in determining movement conditions. However, the limitation of deep learning models being trained on insufficient data, leading to inaccurate recognition in unforeseen scenarios, is addressed by introducing an innovative computer vision technology that detects lanes in real-time. Combining the deep learning model with computer vision technology, the robot can identify different types of objects, allowing it to estimate distance and adjust speed accordingly. Additionally, the paper investigates the recognition reliability in varying light intensities. The findings of this study offer promising directions for future breakthroughs in mobile robot navigatio

Social Security and Population Ageing in Vietnam: A Guarantee for the Elderly People’s Life

Demographic change affects the socio-economic development of any country. In Vietnam, the population and housing censuses from 1989 to 2019 showed an appreciable increasing proportion of the elderly in the total population and fast ageing pace. Older people have many difficulties in their life. Among them, only 27% have pensions or stable incomes, and the rest 73% live without pensions, facing many difficulties. Vietnam is a developing country, and social security policies are in the process of completion. Therefore, improving the social security system, as well as creating opportunities for active ageing and wellbeing for older people, was one of the strategic goals of the Long-Term Development Plan that Vietnam’s government has been carried out for more than half a century. In this article, the issues of demographic change, population ageing, social security system, social assistance and pension benefits as the actual sociological problem are studied by using quantitative methods and comparative analysis approach to confirm the research questions; the proposals made by the authors can be helpful for today’s reforming social security system in Vietnam and social policy making in context of ageing in Vietnam where a large number of elderly people do not have any social benefits

Effects of Data Standardization on Hyperparameter Optimization with the Grid Search Algorithm Based on Deep Learning: A Case Study of Electric Load Forecasting

This study investigates data standardization methods based on the grid search (GS) algorithm for energy load forecasting, including zero-mean, min-max, max, decimal, sigmoid, softmax, median, and robust, to determine the hyperparameters of deep learning (DL) models. The considered DL models are the convolutional neural network (CNN) and long short-term memory network (LSTMN). The procedure is made over (i) setting the configuration for CNN and LSTMN, (ii) establishing the hyperparameter values of CNN and LSTMN models based on epoch, batch, optimizer, dropout, filters, and kernel, (iii) using eight data standardization methods to standardize the input data, and (iv) using the GS algorithm to search the optimal hyperparameters based on the mean absolute error (MAE) and mean absolute percent error (MAPE) indexes. The effectiveness of the proposed method is verified on the power load data of the Australian state of Queensland and Vietnamese Ho Chi Minh city. The simulation results show that the proposed data standardization methods are appropriate, except for the zero-mean and min-max methods

Magnetophonon Resonance in Quantum Wells with Parabolic Potential

The linear dc magnetoconductivity in the$(x,y)$ plane of a parabolic quantum well, with a magnetic field$\vec B = B\vec e_z$ applied, is evaluated for electron - opticalphonon interaction. For nonpolar optical and polar optical phonons,the magneto-conductivity oscillates as a function of the magneticfield with resonances occurring when $P\omega_c=\omega_0$, where$\omega_c$ and $\omega_0$ are cyclotron frequency and optical phononfrequency, respectively, and where $P$ is an integer. The analyticresults are numerically evaluated to show explicitly the dependenceof magneto-conductivity on the magnetic field, the confinementfrequency in $z$ direction, and the temperature of the system

An Application of Modified T2FHC Algorithm in Two-Link Robot Controller

Parallel robotic systems have shown their advantages over the traditional serial robots such as high payload capacity, high speed, and high precision. Their applications are widespread from transportation to manufacturing fields. Therefore, most of the recent studies in parallel robots focus on finding the best method to improve the system accuracy. Enhancing this metric, however, is still the biggest challenge in controlling a parallel robot owing to the complex mathematical model of the system. In this paper, we present a novel solution to this problem with a Type 2 Fuzzy Coherent Controller Network (T2FHC), which is composed of a Type 2 Cerebellar Model Coupling Controller (CMAC) with its fast convergence ability and a Brain Emotional Learning Controller (BELC) using the Lyaponov-based weight updating rule. In addition, the T2FHC is combined with a surface generator to increase the system flexibility. To evaluate its applicability in real life, the proposed controller was tested on a Quanser 2-DOF robot system in three case studies: no load, 180 g load and 360 g load, respectively. The results showed that the proposed structure achieved superior performance compared to those of available algorithms such as CMAC and Novel Self-Organizing Fuzzy CMAC (NSOF CMAC). The Root Mean Square Error (RMSE) index of the system that was 2.20E-06 for angle A and 2.26E-06 for angle B and the tracking error that was -6.42E-04 for angle A and 2.27E-04 for angle B demonstrate the good stability and high accuracy of the proposed T2FHC. With this outstanding achievement, the proposed method is promising to be applied to many applications using nonlinear systems

Domestic Enterprises in Supply Chains of Multinational Corporations: Vietnam Case Study

Abstract—Vietnam’s international integration has also changed rapidly with the trend of gradually entering the global supply chain (GSC) and global value chain (GVC) that help create a powerful dynamic for national economic development. However, the main activities of the manufacturing subsidiaries of reputable MNCs located in Vietnam often specialize in the final product assembly (final assembly schedule-FAS). Correlatively, some Vietnam’s domestic enterprises (VDEs) are engaged either in outsourcing, or become MNC suppliers, but their position in the SCs is unstable. In this article, synthesis methodology and framework of analysis were used to clarify the status of Vietnam’s suppliers and their limited power in buyer-supplier relationships and to make some recommendations that may be useful to related parties. The article also provides an overview of the unprecedented impacts of the COVID-19 pandemic on Vietnamese businesses, and the appropriate responses to reshape and strengthen SCs for production in VietNam

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

Tri-axis convective accelerometer with closed-loop heat source

In this paper, we report the details and findings of a study on tri-axis convective accelerometer, which is designed with the closed-loop type heat source and thermal sensing hotwire elements. The closed-loopheat source enhances the convective flow to the central part where a hotwire is placed to measure the vertical component of acceleration. The simulation was conducted using numerical analysis, and the devicewas prototyped by additive manufacturing. The device, functioning as a tilt sensor and an accelerometer,was tested up to acceleration of 20 g. The experiments were successfully conducted and the experimental results agreed reasonably with those obtained by numerical analysis. The results demonstrated that the closed-loop heat source could reduce the cross effect between the acceleration components. The scalefactor and cross-sensitivity had the values of 0.26 micro�V/g and 1.2%, respectively. The cross-sensitivity andthe effects of heating power were also investigated in this study