153 research outputs found

    DEVELOPMENT AND APPLICATION OF THE ENVIRONMENTAL HYDRODYNAMIC 3D MODEL FOR COMPUTATION AND FORECASTING OF OIL POLLUTIONS IN COASTAL MARINE ENVIRONMENT

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    Joint Research on Environmental Science and Technology for the Eart

    Fuzzy gain scheduling control apply to an RC Hovercraft

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    The Fuzzy Gain Scheduling (FGS) methodology for tuning the Proportional – Integral – Derivative (PID) traditional controller parameters by scheduling controlled gains in different phases, is a simple and effective application both in industries and real-time complex models while assuring the high achievements over pass decades, is proposed in this article. The Fuzzy logic rules of the triangular membership functions are exploited on-line to verify the Gain Scheduling of the Proportional – Integral – Derivative controller gains in different stages because it can minimize the tracking control error and utilize the Integral of Time Absolute Error (ITAE) minima criterion of the controller design process. For that reason, the controller design could tune the system model in the whole operation time to display the efficiency in tracking error. It is then implemented in a novel Remote Controlled (RC) Hovercraft motion models to demonstrate better control performance in comparison with the PID conventional controller

    Audio-Based Deep Learning Frameworks for Detecting COVID-19

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    This paper evaluates a wide range of audio-based deep learning frameworks applied to the breathing, cough, and speech sounds for detecting COVID-19. In general, the audio recording inputs are transformed into low-level spectrogram features, then they are fed into pre-trained deep learning models to extract high-level embedding features. Next, the dimension of these high-level embedding features are reduced before fine-tuning using Light Gradient Boosting Machine (LightGBM) as a back-end classification. Our experiments on the Second DiCOVA Challenge achieved the highest Area Under the Curve (AUC), F1 score, sensitivity score, and specificity score of 89.03%, 64.41%, 63.33%, and 95.13%, respectively. Based on these scores, our method outperforms the state-of-the-art systems, and improves the challenge baseline by 4.33%, 6.00% and 8.33% in terms of AUC, F1 score and sensitivity score, respectively

    ARSENIC REMOVAL FROM GROUND WATER : RESEARCHES AND PRACTICAL IMPLEMENTATION CONDUCTED AT INSTITUTE OF CHEMISTRY, VIETNAMESE ACADEMY OF SCIENCE AND TECHNOLOGY

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    Joint Research on Environmental Science and Technology for the Eart

    A study on multi-criteria decision-making in powder mixed electric discharge machining cylindrical shaped parts

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    In life as well as in engineering, many times, it is necessary to choose the best option among many different options. That will be more difficult when the criteria given for the selection contradict each other. For example, when external cylindrical grinding, the minimum surface roughness requirement necessitates a small depth of cut and feed rate. The material removal rate will be reduced in this case, and this requirement will conflict with the maximum material removal rate requirement. To solve the above problem, a very useful tool is multi-criteria decision-making (MCDM). In this paper, for the first time, MCDM results for powder mixed discharge machining (PMEDM) cylindrical parts of SKD11 tool steel with copper electrodes have been presented. In this work, eighteen experiments with the L18 (16×53) design using the Taguchi method were conducted. Six main input process parameters include the powder concentration, the pulse current, the servo voltage, the pulse on time, and the pulse off time. To select an alternative that simultaneously ensures two criteria including minimum surface roughness (RS) and maximum material removal speed (MRS), four different MCDM methods including MAIRCA (Multi-Attributive Ideal-Real Comparative Analysis), MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution), TOPSIS (Technique for order of preference by similarity to ideal solution), and EAMR (Area-based Method of Ranking) and two methods of criteria weight calculation including MEREC (Method based on the Removal Effects of Criteria) and Entropy methods were selected. The results of MCDM when PMEDM SKD11 tool steel cylindrical parts with two methods for weight determination and four methods for solving MCDM problem were evaluated. In addition, the best alternative to ensure simultaneous minimum RS and maximum MRS was proposed

    SEASONAL VARIATION OF PHYTOPLANKTON FUNCTIONAL GROUPS IN TUYEN LAM RESERVOIR, CENTRAL HIGHLANDS, VIETNAM

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    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

    The Impacts of Distance between Phosphor Layers on Optical Properties of Triple-Layer Phosphor Structure

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    One of the crucial goals often thought of in connection with remote phosphors is to make the emitted photon larger than other structures. However, the two biggest hurdles that make achieving the goals more challenging are color uniformity and Color Rendering Index (CRI). This is the reason why people have started to pay more attention to these issues in recent research papers. Thus, this study will present the idea of controlling the distance between phosphor layers to control the optical parameters of White light LED (WLED). Based on the Mie scattering theory, which is about absorption and scattering of plane electromagnetic waves by uniform isotropic particles of the simplest form (sphere, infinite cylinder) which are in a uniform and isotropic dielectric infinite medium, the results of the study are confirmed to be completely accurate and reliable. Specifically, when d = 0.64 mm, the flux can increase to 9.7% compared to the original. Similarly, when d = 0.84 mm, the color uniformity can be double better meanwhile the CRI value is kept intact. Once fully calculated and substantiated, the paper will provide comparable results in practice for the production of higher quality WLED

    Cost optimization of two-stage helical gearboxes with second stage double gear-sets

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    In practice, the cost of a gearbox plays a very important role in the trade. Therefore, reducing the cost of gearboxes is an important task not only when manufacturing the gearboxes but also when designing them. In order to reduce the cost of a gearbox, there are many solutions in which determining the optimal partial gear ratios of a gearbox is an effective measure. This is because it not only the size, the mass but also the cost of a gearbox depends greatly on the partial gear ratios. This work presents a method for calculating the cost function of two-stage helical gearboxes with second-stage double gear-sets based on the mass of the components that construct the gearbox. The cost objective function is minimized to achieve the optimal transmission ratios. Furthermore, screening experiments are carried out with nine important input parameters that have significant effects on the optimum transmission ratio of the second stage. These parameters are the total gearbox ratio, the coefficient of wheel face width of the first stage, coefficient of wheel face width of the second stage, the allowable contact stress of the first stage, the allowable contact stress of the second stage, the output torque, the cost of gearbox housing, the cost of gears, and the shaft cost. The experimental results of were analysed by using the Analysis of Variance (ANOVA) method with the help of Minitab 19 software. The results demonstrate that the effective weight of the input parameters and their interactions on the output response was investigated. Also, a regression model for computing the optimal transmission ratio of the second stage was proposed. This brings significance not only in the design process but also in manufacturing since the gearbox cost can decreas
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