STRUCTURAL, VIBRATIONAL, OPTICAL, AND MAGNETIC PROPERTIES OF 0-3 TYPE PARTICULATE PbTiO3-NiFe2O4 COMPOSITES

We synthesized 0-3 type (1-x)PbTiO3-xNiFe2O4 (x = 0.0-0.5) multiferroic composites with two independently crystallized parent phases by the sol-gel method. Structural, surface morphology, vibrational, optical, and magnetic characteristics were investigated by X-ray diffraction (XRD), SEM, Raman scattering, UV-vis absorption, and magnetization (M-H) measurements, respectively. The XRD result showed that the lattice parameter a of the PbTiO3 (PTO) phase decreased while lattice parameter c increased after compositing, leading to a decrease in the tetragonal ratio c/a. SEM images indicated that the NiFe2O4 (NFO) crystals that crystallized later are small and adhere to the surface of the large PTO particles. The strong cohesion between the two components was also revealed by the gradual shift of the Raman peaks to the lower wavelength and the reduction of the Raman intensity as the NFO content increased. The UV-vis absorption result showed the co-absorption spectra of the parent phases in the composites. Magnetization curves presented a sharp increase in saturation magnetization MS with NFO content from 0.014 emu/g for the PTO sample to 14.360 emu/g for the composite containing 50 mol% NFO. This study indicates an effective method in the search for multilayer composites

The Improvement Model of Navigational Safety for Inland Waterway Transport

This paper aims at evaluating navigational safety for inland waterway transport (IWT). In doing so, the literature and operational features of IWT were initially reviewed to figure out risk elements (REs) influencing the navigational safety for IWT. After that, a fuzzy Analytic Hierarchical Process (AHP) approach was adopted to estimate the weight for the likelihood and consequence measures of REs. Then, continuous risk matrix (RM) was introduced to identify REs\u27 risk level. Lastly, to test the proposed research model\u27s applicability, IWT operators across Vietnam were empirically surveyed. The empirical findings could be useful for IWT operators in launching managerial policies to boost their navigational safety. Furthermore, the proposed risk evaluation framework may serve as a methodological reference in relevant literature

Multi-layer heterogeneous ensemble with classifier and feature selection.

Deep Neural Networks have achieved many successes when applying to visual, text, and speech information in various domains. The crucial reasons behind these successes are the multi-layer architecture and the in-model feature transformation of deep learning models. These design principles have inspired other sub-fields of machine learning including ensemble learning. In recent years, there are some deep homogenous ensemble models introduced with a large number of classifiers in each layer. These models, thus, require a costly computational classification. Moreover, the existing deep ensemble models use all classifiers including unnecessary ones which can reduce the predictive accuracy of the ensemble. In this study, we propose a multi-layer ensemble learning framework called MUlti-Layer heterogeneous Ensemble System (MULES) to solve the classification problem. The proposed system works with a small number of heterogeneous classifiers to obtain ensemble diversity, therefore being efficiency in resource usage. We also propose an Evolutionary Algorithm-based selection method to select the subset of suitable classifiers and features at each layer to enhance the predictive performance of MULES. The selection method uses NSGA-II algorithm to optimize two objectives concerning classification accuracy and ensemble diversity. Experiments on 33 datasets confirm that MULES is better than a number of well-known benchmark algorithms

Covid-19 Pandemic and Performance of Economic Sectors in Vietnam

Purpose of the paper: This study aims to consider the Covid impact on stock – price volatility of different industry groups in Vietnam by using the M-GARCH model

Covid-19 Pandemic and Performance of Economic Sectors in Vietnam

Purpose of the paper: This study aims to consider the Covid impact on stock – price volatility of different industry groups in Vietnam by using the M-GARCH model

Objectively measured physical activity of Vietnamese adults with type 2 diabetes: Opportunities to intervene

Objectives: To objectively determine and compare the physical activity (PA) levels of adults newly diagnosed with type 2 diabetes (T2D) and adults without T2D in Vietnam using an accelerometer. Methods: A total of 120 participants with newly diagnosed T2D and 120 adults without T2D were recruited from a large hospital in Hanoi, the capital city of Vietnam. All participants wore an ActiGraph GT3X accelerometer for at least 5 days, including 1 weekend day. Freedson cut-off points were used to estimate different intensities of PA. In addition, comparisons between groups were made with respect to achieving the World Health Organization (WHO) and International Diabetes Federation (IDF) recommended PA guidelines. Results: Men with T2D had significantly lower levels of PA than men without T2D. The respective multivariable-adjusted mean values of daily step count, daily light-intensity, moderate-intensity, and moderate-to-vigorous-intensity PA were approximately 14%, 19%, and 22% lower in the men with T2D than in their non-T2D counterparts. However, women with T2D accumulated a greater number of steps per day than women without T2D. Only 59.2% of the adults with T2D met the minimum recommended level of PA (WHO and IDF), compared to 74.2% of adults without T2D (p<0.05). After adjusting for potential confounders, participants with T2D experienced 50.0% significantly lower odds of achieving PA recommendations. Conclusions: Vietnamese men with T2D were less physically active than those without T2D, and adults with T2D were less likely to meet PA guidelines. The results suggest a need for integrating PA into the self-management of this chronic condition

A homogeneous-heterogeneous ensemble of classifiers.

In this study, we introduce an ensemble system by combining homogeneous ensemble and heterogeneous ensemble into a single framework. Based on the observation that the projected data is significantly different from the original data as well as each other after using random projections, we construct the homogeneous module by applying random projections on the training data to obtain the new training sets. In the heterogeneous module, several learning algorithms will train on the new training sets to generate the base classifiers. We propose four combining algorithms based on Sum Rule and Majority Vote Rule for the proposed ensemble. Experiments on some popular datasets confirm that the proposed ensemble method is better than several well-known benchmark algorithms proposed framework has great flexibility when applied to real-world applications. The proposed framework has great flexibility when applied to real-world applications by using any techniques that make rich training data for the homogeneous module, as well as using any set of learning algorithms for the heterogeneous module

Hidden in the jungle of Vietnam: a new species of Quasipaa (Amphibia, Anura, Dicroglossidae) from Ngoc Linh Mountain

A new species of Quasipaa is described from Ngoc Linh Mountain of the Kon Tum Massif in central Vietnam. The new species is morphologically distinguishable from its congeners on the basis of a combination of the following diagnostic characters: SVL 79.6–84.3 mm in males and 64.6–69.9 mm in females; head broader than long; vomerine teeth present; external vocal sacs absent; tympanum slightly visible; dorsum with lines of thick ridges and small round tubercles; flanks covered by oval and round tubercles; supratympanic fold present; dorsolateral fold absent; ventrolateral sides, ventral surface of arms, and all fingers with spines in males; the absence of spines on chest and belly in males; toes fully webbed to distal portion of terminal phalanx; in life, dorsum dark brown, chest and belly immaculate white. Phylogenetic analyses found that the genetic divergence of the new species and its congeners ranged from 4.2–5.1% (compared with Quasipaa boulengeri) to 7.6–8.1% (compared with Q. shini) in the 16S gene