Research on the stability of the 3D frame on coral foundation subjected to impact load

This article presents an application of the finite element method (FEM) for the stability analysis of 3D frame (space bar system) on the coral foundation impacted by collision impulse. One-way joints between the rod and the coral foundation are described by the contact element. Numerical analysis shows the effect of some factors on the stability of the bar system on coral foundation. The results of this study can be used for stability analysis of the bar system on coral foundation subjected to sea wave load

Efficacy of Neural Prediction-Based NAS for Zero-Shot NAS Paradigm

In prediction-based Neural Architecture Search (NAS), performance indicators derived from graph convolutional networks have shown significant success. These indicators, achieved by representing feed-forward structures as component graphs through one-hot encoding, face a limitation: their inability to evaluate architecture performance across varying search spaces. In contrast, handcrafted performance indicators (zero-shot NAS), which use the same architecture with random initialization, can generalize across multiple search spaces. Addressing this limitation, we propose a novel approach for zero-shot NAS using deep learning. Our method employs Fourier sum of sines encoding for convolutional kernels, enabling the construction of a computational feed-forward graph with a structure similar to the architecture under evaluation. These encodings are learnable and offer a comprehensive view of the architecture's topological information. An accompanying multi-layer perceptron (MLP) then ranks these architectures based on their encodings. Experimental results show that our approach surpasses previous methods using graph convolutional networks in terms of correlation on the NAS-Bench-201 dataset and exhibits a higher convergence rate. Moreover, our extracted feature representation trained on each NAS-Benchmark is transferable to other NAS-Benchmarks, showing promising generalizability across multiple search spaces. The code is available at: https://github.com/minh1409/DFT-NPZS-NASComment: 12 pages, 6 figure

Increasing Technology-Based Driver’s Productivity Under Covid-19 Pandemic in Vietnam: the Significant Contribution of Consumer Behavior

Purpose: Ride-hailing service, after the emergence in Hanoi – capital of Vietnam in 2014, has experienced major development and gradually enhanced the inner-city travelling of citizens. This study aims at investigating technology-based driver productivity perception and identifying several important influencing factors during the period of COVID-19 pandemic   Design/methodology/approach: The samples of 370 technology-based drivers have been surveyed to collect significant data about factors impacting on worker productivity in Vietnam ride-hailing service. SPSS 26 software is conducted with two types of analyses, including descriptive analysis and statistical analysis   Findings: The findings indicate that social distances, service waste and customer behaviors possess significant impacts on worker productivity in Vietnam ride-hailing services. Several special concerned factors have been identified to raise driver’s awareness of productivity improvement in ride-hailing service.   Research, Practical and Social implication: Major implications can be suggested for improving driver productivity during and after COVID-19 pandemic, especially in term of reducing service waste and increasing customer behavior towards ride-hailing services.   Originality/value: Basing on research findings, the study becomes significant contribution to further papers as well as service managers to enhance technological driver productivity during COVID-19 pandemic.

The Impact of Thiamine Treatment in the Diabetes Mellitus

Thiamine acts as a coenzyme for transketolase (Tk) and for the pyruvate dehydrogenase and α-ketoglutarate dehydrogenase complexes, enzymes which play a fundamental role for intracellular glucose metabolism. The relationship between thiamine and diabetes mellitus (DM) has been reported in the literature. Thiamine levels and thiamine-dependent enzyme activities have been reduced in DM. Genetic studies provide opportunity to link the relationship between thiamine and DM (such as Tk, SLC19A2 gene, transcription factor Sp1, α-1-antitrypsin, and p53). Thiamine and its derivatives have been demonstrated to prevent the activation of the biochemical pathways (increased flux through the polyol pathway, formation of advanced glycation end-products, activation of protein kinase C, and increased flux through the hexosamine biosynthesis pathway) induced by hyperglycemia in DM.Thiamine definitively has a role in the diabetic endothelial vascular diseases (micro and macroangiopathy), lipid profile, retinopathy, nephropathy, cardiopathy, and neuropathy

Deep Learning-Based Signal Detection for Dual-Mode Index Modulation 3D-OFDM

In this paper, we propose a deep learning-based signal detector called DuaIM-3DNet for dual-mode index modulation-based three-dimensional (3D) orthogonal frequency division multiplexing (DM-IM-3D-OFDM). Herein, DM-IM-3D- OFDM is a subcarrier index modulation scheme which conveys data bits via both dual-mode 3D constellation symbols and indices of active subcarriers. Thus, this scheme obtains better error performance than the existing IM schemes when using the conventional maximum likelihood (ML) detector, which, however, suffers from high computational complexity, especially when the system parameters increase. In order to address this fundamental issue, we propose the usage of a deep neural network (DNN) at the receiver to jointly and reliably detect both symbols and index bits of DM-IM-3D-OFDM under Rayleigh fading channels in a data-driven manner. Simulation results demonstrate that our proposed DNN detector achieves near-optimal performance at significantly lower runtime complexity compared to the ML detector

Culture Shock of Expatriates When Working in Vietnam

Due to the globalization and future vision to become an industrialized nation,Vietnam has increasingly focuses in attracting more FDI inflow by o acknowledges the inflow of expatriates by opening its market towards globalization and liberalization of trade and services .This paper reports on a study about many expatriates who are currently living and working in Vietnam. The objectives of the study are to examine the challenges faced by the expatriates in their adjustments process, how they can deal with it and how it can effect in their job performance.Semi-structured interviews were conducted within 5 male and female expatriates working in different organization and Institutions in Vietnam. The study highlighted the psychological, socio-cultural and work challenges.Adjustments were based on individual initiatives based on the psychological and mental strengths of the expatriates, combined with efforts of peer expatriates,parent firms and host organizations

Removal of Power Line Interference from Electrocardiograph (ECG) using Proposed Adaptive Filter Algorithm

ECG signals in measurements are contaminated by noises including power line interference. In recent years, adaptive filters with different approaches have been investigated to remove power line interference in ECG.In this paper, an adaptive filter is proposed to cancel power line interference in ECG signals. The proposed algorithm is experimented with MIT-BIH ECG signals data base. The algorithm2019;s results are compared with the results of other adaptive filter algorithms using Least Mean Square (LMS), Normalized Least Mean Square (NLMS) by Signal to Noise (SNR). Theses works are performed by LabVIEW software