Search

The rapid industrialization of nations in Southeast Asia (SEA) has led to a decline in these countries’ air quality, including high levels of particulate matter (PM). Monitoring these air pollutants is crucial to understanding the pollution status of the area and developing management plans for improvement. The metrological conditions in the region present challenges as high temperature and high humidity have been known to cause errors in the measurements. This study investigated the performance of five PM monitoring instruments with different working principles. The air temperature was mostly over 25 °C with relative humidity usually remaining above 80%, which is typical of SEA weather. Measurements from all instruments had good correlations with each other as their linear regressions yielded slopes of 1 ± 0.15 and R2 > 0.65. Moreover, this study found that depending on the chosen reference instrument, not all factors affect the devices equally. In particular, using Partisol as a reference, the PM2.5 concentration, air temperature, and relative humidity had less impact upon the relative bias level compared to using Leckel as a reference. In addition, the high cost of monitoring instruments also poses financial constraints on how many monitoring stations can be deployed. To tackle this issue, this study presents ManPMS whose design is based on that of the USEPA Title 40 Part 50 with slight modifications. The cost to manufacture and assemble the instrument was only 2/3 the price of a typical instrument with similar performance.

Background: Hypertension and type 2 diabetes mellitus belong to the most costly chronic diseases worldwide. The Socialist Republic of Vietnam is a country with a high burden of communicable and non-communicable diseases, with hypertension and diabetes among the top contributors to premature mortality. Objective: The aim of the study was to describe and assess the scale of the burden of hypertension and type 2 diabetes mellitus in the Socialist Republic of Vietnam. Methods: An ecological study employing secondary data analysis was conducted. Data from the Institute of Health Metrics and Evaluation and Vietnamese Health Statistic Yearbooks were analysed by linear and polynomial regression analyses, Kendall rank correlation, and Pearson correlation. Results: From 1990 to 2017, on average, 22% of all deaths and 11% of all disability-adjusted life years were associated with high systolic blood pressure, and 3% of all deaths and 2% of all disability-adjusted life years were attributable to type 2 diabetes mellitus in the Socialist Republic of Vietnam. The decrease in the number of elementary nurses, as well as the increase in health insurance expenditures per inpatient, seems to be, with the highest degree of certainty, correlated with type 2 diabetes mellitus death and disability-adjusted life years rates. Conclusion: If the tracked progress remains at the same pace, the Socialist Republic of Vietnam will likely be unable to achieve the targets related to Goal 3 of the United Nations 2030 Agenda for Sustainable Development. Developing regulatory frameworks and social demand for professionalism could encourage nurses to pursue higher education.

Along with economic development, urbanization will generate a large amount of solid waste and put pressure on the waste management systems in developing countries. Face-to-face interview methods were used to investigate the current status of construction and demolition waste (CDW) management (collection, transportation, treatment, and storage) as well as reveal attitudes of governmental agencies and enterprises towards CDW recycling and recycled material products in Hai Phong City, Vietnam. Waste generation rates (WGRs) of the works were also determined by site surveys and as-built drawings method of typical old buildings to be demolished and two licensed new construction works. WGRs of 34.5 kg/m2 and 758 kg/m2 were identified during the construction and demolition of small private houses, respectively, while WGRs at public house demolition sites were 1053 kg/m2. To effectively manage the CDW, the gross floor area of new construction work was estimated by a multiple regression equation with the population and gross region domestic product growth. Based on this model combining the investigation results, the amount of CDW increase in 5–30 years is also predicted. This data set will help management agencies plan storage yards as well as select the appropriate CDW treatment and recycling methods, contributing to building a sustainable and effective CDW management model for Hai Phong City as well as Vietnam in the future.

Examination timetabling is one of 3 critical timetabling jobs besides enrollment timetabling and teaching assignment. After a semester, scheduling examinations is not always an easy job in education management, especially for many data. The timetabling problem is an optimization and Np-hard problem. In this study, we build a multi-objective optimizer to create exam schedules for more than 2500 students. Our model aims to optimize the material costs while ensuring the dignity of the exam and students' convenience while considering the rooms' design, the time requirement of each exam, which involves rules and policy constraints. We propose a programmatic compromise to approach the maximum tar-get optimization model and solve it using the Genetic Algorithm. The results show the effectiveness of the introduced algorithm.

While investigating a giraffe's death in a Vietnamese zoo, we successfully identified and isolated Lumpy skin disease virus (LSDV) from skin nodule biopsies and ruptured nodule wound swab samples. Phylogenetic analysis indicated that the isolate obtained in this study was closely related to the previous Vietnamese and Chinese LSDV strains from cattle. This is the first report on the genome detection and isolation of LSDV in a diseased giraffe in Vietnam. Further study is needed to better understand the epidemiology of this disease in wildlife.

The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially logistics. In this study, we introduced an adaptive method to a complex VRP. It combines multi-objective optimization and several forms of VRPs with practical requirements for an urban shipment system. The optimizer needs to consider terrain and traffic conditions. The proposed model also considers customers' expectations, shipper considerations as goals, and the common goal like transportation cost. We offered compromise programming to approach the multi-objective problem by decomposing the original multi-objective problem into a minimized distance-based problem. We designed a hybrid version of the Genetic algorithm with the Local Search algorithm to solve the proposed problem. We evaluate the effectiveness of the proposed algorithm with the Tabu Search algorithm, the original Genetic algorithm on the tested dataset. The results show that our method is an effective decision-making tool for the multi-objective VRP and an effective solver for the new variation of VRP.

There is a growing demand for a flexible, precise calibration facility for aerosol monitoring instruments. This study investigated ManDust1, an aerosol calibration facility that is compatible with a variety of different operating principles. The facility comprises four systems: (a) a clean air supply system, (b) an aerosol generator system, (c) a diffuser tower, and (d) a sampling system. A compact and modular diffuser tower provides turbulence flow to homogeneously mix the injected aerosol before collection by custom-made isokinetic sampling probes. The velocity profile in the diffuser tower was computed and measured to be turbulent, generating a well-mix aerosol condition with spatial homogeneity of 4.38% across all sampling locations. A computational fluid dynamics (CFD) simulation conducted to confirm the dimension of the facilty was able to generate turbulence flow and mixing. The facility stably provided aerosols from 0 to 10 µm with variable concentrations from a few µg/m3 to 1000 µg/m3. The uncertainty budget in this study was calculated to be 5.98% when the facility was operated at 600 µg/m3 (95% confident level), and span drift was calculated to be 3.15% after 120 h of measurement.

In this study, it is going to investigate properties of lightweight geopolymer specimens aerated by aluminium powder. It has been established well that aluminium powder can be appropriately used for foaming of traditional concrete. Reaction between aluminium powder and alkali activator in geopolymers of this study caused high porous structures based on the weight ratios of constituent materials. Different specimens were made by changing sodium silicate to sodium hydroxide, and alkali activator to fly ash weight ratios. Fly ash was partially substituted by aluminium powder with 1.5, 3.0 and 5.0 wt.% in different mixtures. Results indicated that substituting of 5.0 wt.% of fly ash by aluminium powder in the specimens with alkali activator to fly ash weight ratio of 0.35 and sodium silicate to sodium hydroxide weight ratio of 2.5 causes the best foamed specimen with the lowest density. Compressive strength of all aerated specimens were in the range of 0.9–4.35 MPa, which is suitable for using as bricks, fire-resistant panels, buried pipeline and so on. SEM analysis was conducted to evaluate the microstructure of successfully aerated geopolymers. It was seen that in highly aerated specimens, the foaming reaction is too fast that prevents complete alkali activation of geopolymers and therefore, many unreacted fly ash particles remains.

Simulation and experimental measurements are presented for 60 GHz transmission systems based on upconversion. We demonstrate that chirp in modulated semiconductor lasers combined with upconversion allows to realize a simple system resistant to chromatic dispersion without the need for customized filter. The comparison between two 60 GHz modulation schemes highlights the possibility to reduce power fading, due to chromatic dispersion, to a value as low as optical fiber attenuation.

This molecular dynamics (MD) simulation carries a detailed analysis of a pressure-induced structural transition supercooled liquid and amorphous silicene (a-silicene). Low-density models of supercooled liquid and a-silicene containing 10 000 atoms are obtained by rapid cooling processes from the melts. Then, an a-silicene model at T = 1000 K, a supercooled liquid model at T = 1500 K and a liquid silicon model at T = 2000 K have been isothermally compressed step by step up to a high density in order to observe the pressure-induced structural changes. Specifically 'Cairo tiling' pentagonal and square lattices of silicene are discovered in our calculations. Structural properties of those penta-silicene and tetra-silicene models have been carefully analyzed through the radial distribution functions, interatomic distances, bond-angle distributions under high-pressure condition. The dependence of pressure on formation behaviors is calculated via pressure-volume and energy-density relationships. The first order transition from low-density supercooled liquid/amorphous silicene to high-density penta-silicene and continuous transition from low-density liquid to high-density tetra-silicene are discussed. Atomic mechanism and sp3/sp2 hybridization evolution are inspected whereas the role of low-membered ring defects/boundary promises remarkable application and advanced research in future.

In this paper, we demonstrate multiband orthogonal frequency division multiplexing (MB-OFDM) transmission of quadrature phase shift keying (QPSK) modulation with 200-Mb/s bit rate by all-optical frequency up-conversion using external modulator for ultrawideband (UWB) applications to 60-GHz band radio-over-fiber (RoF) network. Error vector magnitude (EVM) measurements are used to evaluate the performance of our system and an EVM root mean square (rms) of 12.6% at 60 GHz is obtained with our technique and corresponds to bit error rate (BER) below 10-9, in compliance with standard requirements.

In transitional economies, the scale of economic enterprise and the allocation of property rights shape social structures and influence income distribution. In agrarian economies, where labor-intensive family enterprises dominate, political officials' income advantages decline rapidly relative to those of private entrepreneurs. Larger enterprises, however, provide greater income opportunities for officials, especially when a government retains an ownership stake in the initial phases of reform. This article replicates the findings from an earlier study of rural China using comparable survey data from Vietnam. We find that during the first two decades of rural market reform in Vietnam and China, the scale and ownership of firms differed radically. Small family enterprises dominated rural development in Vietnam, whereas China's development was dominated by larger firms, initially established by rural governments. Consequently, while cadre income advantages have kept pace with those of private entrepreneurs in China, they have declined rapidly in Vietnam.

This paper presents an efficient training approach for support vector machines that will improve their ability to learn from a large or imbalanced data set. Given an original training set, the proposed approach applies unsupervised learning to extract a smaller set of salient training exemplars, which are represented by weighted cluster centers and the target outputs. In subsequent supervised learning, the objective function is modified by introducing a weight for each new training sample and the corresponding penalty term. In this paper, we investigate two methods of defining the weight based on cluster vectors. The proposed SVM training is implemented and tested on two problems: (i) gender classification of facial images using the FERET data set; (ii) income prediction using the UCI Adult Census data set. Experiment results show that compared to standard SVM training, the proposed approach leads to much faster SVM training, produces a more compact classifier while maintaining generalization ability.

This chapter is concerned with the class imbalance problem, which has been recognised as a crucial problem in machine learning and data mining. The problem occurs when there are significantly fewer training instances of one class compared to another class.

In this article, we propose a new supervised learning approach for pattern classification applications involving large or imbalanced data sets. In this approach, a clustering technique is employed to reduce the original training set into a smaller set of representative training exemplars, represented by weighted cluster centers and their target outputs. Based on the proposed learning approach, two training algorithms are derived for feed-forward neural networks. These algorithms are implemented and tested on two pattern classification applications - skin detection and image classification. Experimental results show that with the proposed learning approach, it is possible to design networks in a fraction of time taken by the standard learning approach, without compromising the generalization ability and overall classification performance.