Roller Chain-Like Robot for Steel Bridge Inspection

This paper presents a novel design of steel bridge/structure inspection robot. Compared to most existing robots designed to work on particular surface contour of steel structures such as flat or curving, the proposed roller chain-like robot can implement and transfer smoothly on many kind of steel surfaces. The developed robot can be applied to inspection tasks for steel bridges with complicated structures. The robot is able to carry cameras, sensors for visual and specialized examination. Rigorous analysis of robot kinematics, adhesion force and turn-over failure has been conducted to demonstrate the stability of the proposed design. Mechanical and magnetic force analysis together with turn-over failure investigation can serve as an useful framework for designing various steel climbing robots in the future. Experimental results and field deployments prove the adhesion, climbing, inspection capability of the developed robot

ION Mn4+ VÀ Cr3+ TRONG TRƯỜNG TINH THỂ α-Al2O3

Vật liệu phát quang α-Al2O3 pha tạp Mangan (Mn4+), Crôm (Cr3+) được chế tạo bằng phương pháp nổ dung dịch urê-nitrat, sử dụng chất khử urê, ở nhiệt độ thấp. Các kết quả XRD cho thấy mẫu có cấu trúc pha lục giác. Phổ kích thích phát quang của α-Al2O3: Mn4+ và α-Al2O3: Cr3+ gồm hai dải rộng có cực đại ở 405 nm và 558 nm, tương ứng với các chuyển dời điện tử của ion Mn4+ và Cr3+ từ 4A2 → 4T1 và 4A2 → 4T2. Kết quả xác định Dq/B chứng tỏ các ion này chiếm vị trí của trường tinh thể mạnh trong mạng nền

Fast Temporal Wavelet Graph Neural Networks

Spatio-temporal signals forecasting plays an important role in numerous domains, especially in neuroscience and transportation. The task is challenging due to the highly intricate spatial structure, as well as the non-linear temporal dynamics of the network. To facilitate reliable and timely forecast for the human brain and traffic networks, we propose the Fast Temporal Wavelet Graph Neural Networks (FTWGNN) that is both time- and memory-efficient for learning tasks on timeseries data with the underlying graph structure, thanks to the theories of multiresolution analysis and wavelet theory on discrete spaces. We employ Multiresolution Matrix Factorization (MMF) (Kondor et al., 2014) to factorize the highly dense graph structure and compute the corresponding sparse wavelet basis that allows us to construct fast wavelet convolution as the backbone of our novel architecture. Experimental results on real-world PEMS-BAY, METR-LA traffic datasets and AJILE12 ECoG dataset show that FTWGNN is competitive with the state-of-the-arts while maintaining a low computational footprint. Our PyTorch implementation is publicly available at https://github.com/HySonLab/TWGNNComment: arXiv admin note: text overlap with arXiv:2111.0194

Encouraging the Startup Spirit of Students: Implications and Solutions

Starting a business by the establishment of a new business or a new business project plays an important role in the economic development of each country. Promoting the entrepreneurial spirit of students at universities is the basis for contributing to the success of start-up countries. This study provides empirical evidence of factors affecting student entrepreneurship based on survey data of a sample of 321 students. The study results clarify the factors affecting the initial entrepreneurial intention of students, and are an important foundation for starting-up in the future. Since then, the findings from regression analysis are the basis to imply some solutions from the school and the Government to promote the entrepreneurial spirit of young people. Keywords: Entrepreneurship intention; Social-education environment; Taking risk; Student DOI: 10.7176/RJFA/11-4-07 Publication date: February 29th 202

MEASURES TO IMPROVE THE LEARNING QUALITY OF BASKETBALL SUBJECT FOR NON-SPECIALIZED STUDENTS AT BAC NINH SPORTS UNIVERSITY OF VIETNAM UNDER THE CREDIT-BASED TRAINING SYSTEM

In using conventional scientific research methods in the field of physical training and sports, we selected and built the content of 04 measures to improve the quality of teaching Basketball subject for non-specialized students of Bac Ninh Sport University of Viet Nam under the credit-based training system, at the same time test the theory on the feasibility of measures by an expert method. The result showed that the selected and built measures were feasible and could be applied in practice to improve the quality of teaching Basketball subject for non-specialized students at Bac Ninh Sport University of Viet Nam under the credit-based training system.  Article visualizations

Multisensor Data Fusion for Reliable Obstacle Avoidance

In this work, we propose a new approach that combines data from multiple sensors for reliable obstacle avoidance. The sensors include two depth cameras and a LiDAR arranged so that they can capture the whole 3D area in front of the robot and a 2D slide around it. To fuse the data from these sensors, we first use an external camera as a reference to combine data from two depth cameras. A projection technique is then introduced to convert the 3D point cloud data of the cameras to its 2D correspondence. An obstacle avoidance algorithm is then developed based on the dynamic window approach. A number of experiments have been conducted to evaluate our proposed approach. The results show that the robot can effectively avoid static and dynamic obstacles of different shapes and sizes in different environments.Comment: In the 11th International Conference on Control, Automation and Information Sciences (ICCAIS 2022), Hanoi, Vietna

Seawater desalination using air gap membrane distillation-an experimental study on membrane scaling and cleaning

The connection between operating temperature and membrane scaling/cleaning during an air gap membrane distillation (AGMD) process of seawater has been systematically elucidated in this study. Experimental and mathematically simulated data demonstrate the profound influences of feed salinity and membrane scaling on water flux at various operating temperatures. Feed salinity exerted significant impacts on water flux at high operating temperatures because of aggravated polarization effects. Membrane scaling and the subsequent membrane cleaning efficiency were also strongly affected by operating temperatures. Indeed, membrane scaling was more severe and occurred at a lower water recovery when operating at 60-50 °C (feed-coolant temperature) compared to that at 35-25 °C. Moreover, membrane cleaning with fresh water and vinegar was less effective for the membrane scaled at 60-50 °C compared to 35-25 °C. Finally, membrane cleaning using vinegar was much more efficient than fresh water. Given the availability of vinegar at household level, vinegar cleaning can potentially be a low cost and readily accessible approach for MD maintenance for small scale seawater desalination applications in remote coastal communities

Genetic variation within and between three Vietnamese pine populations (Pinus merkusii) using random amplified polymorphic DNA (RAPD) markers

Pinus merkusii is an important species in Vietnam with many economic and biological contributions. The information on diversity within and between populations of a species is necessary for plantation programs, breeding and conservation strategies. Genetic diversity of three Vietnamese populations (NA, QB and QN) was analyzed using the random amplified polymorphic DNA (RAPD) markers. Nine RAPD primers produced 82 markers, 77 of which were polymorphic with 93.9% of polymorphism. The results showed higher genetic variation within populations (72%) than between populations (28%) and low Nei’s genetic differentiation index among populations (0.1867). The populations also clustered based on PCoA analysis where cluster I included NA and QB populations and Cluster II, the QN population. These results suggest that P. merkusii populations in Vietnam is necessary to develop the genetic resources.Keywords: DNA markers, genetic diversity, Pinus merkusii, random amplified polymorphic DNA (RAPD), Vietna