This paper introduces a new intelligent integration between an IoT platform and deep learning neural network (DNN) algorithm for the online monitoring of computer numerical control (CNC) machines. ...The proposed infrastructure is utilized for monitoring the cutting process while maintaining the cutting stability of CNC machines in order to ensure effective cutting processes that can help to increase the quality of products. For this purpose, a force sensor is installed in the milling CNC machine center to measure the vibration conditions. Accordingly, an IoT architecture is designed to connect the sensor node and the cloud server to capture the real-time machine's status via message queue telemetry transport (MQTT) protocol. To classify the different cutting conditions (i.e., stable cutting and unstable cuttings), an improved model of DNN is designed in order to maintain the healthy state of the CNC machine. As a result, the developed deep learning can accurately investigate if the transmitted data of the smart sensor via the internet is real cutting data or fake data caused by cyber-attacks or the inefficient reading of the sensor due to the environment temperature, humidity, and noise signals. The outstanding results are obtained from the proposed approach indicating that deep learning can outperform other traditional machine learning methods for vibration control. The Contact elements for IoT are utilized to display the cutting information on a graphical dashboard and monitor the cutting process in real-time. Experimental verifications are performed to conduct different cutting conditions of slot milling while implementing the proposed deep machine learning and IoT-based monitoring system. Diverse scenarios are presented to verify the effectiveness of the developed system, where it can disconnect immediately to secure the system automatically when detecting the cyber-attack and switch to the backup broker to continue the runtime operation.
Until now, many works have shown that the hydrogen evolution reaction (HER) performance can be improved by anion or cation substitution into the crystal lattice of pyrite‐structure materials. ...However, the synergistic effects of anion–cation double substitution for overall enhancement of the catalytic activity remains questionable. Here, the simultaneous incorporation of vanadium and phosphorus into the CoS2 moiety for preparing 3D mesoporous cubic pyrite‐metal Co1‐xVxSP is presented. It is demonstrated that the higher catalytic activity of CoS2 after V incorporation can be primarily attributed to abundance active sites, whereas P substitution is responsible for improving HER kinetics and intrinsic catalyst. Interestingly, due to the synergistic effect of P–V double substitution, the 3D Co1‐xVxSP shows superior electrocatalysis toward the HER with a very small overpotential of 55 mV at 10 mA cm−2, a small Tafel slope of 50 mV dec−1, and a high turnover frequency of 0.45 H2 s−1 at 10 mA cm−2, which is very close to commercial 20% Pt/C. Density functional theory calculation reveals that the superior catalytic activity of the 3D Co1‐xVxSP is contributed by the reduced kinetic energy barrier of rate‐determining HER step as well as the promotion of the desorption H2 gas process.
The synergistic effect for super electrocatalyst hydrogen evolution by anion–cation double substitution: For the first time, a new strategy is proposed to satisfy all requirements for the development of a highly active and remarkably durable hydrogen evolution reaction (HER) electrocatalyst. The obtained catalyst exhibits exceptional HER activity, which outperforms the current state‐of‐the‐art catalysts, is one of the most promising candidates for effective nonprecious metal electrocatalysts.
The Saigon River flows through one of the most rapidly growing megacities of Southeast Asia, Ho Chi Minh City (HCMC, > 8.4 million inhabitants). This tidal river is characterized by a tropical ...monsoon climate, alternating a wet and a dry season. In the last few decades, increased economic and urban developments of HCMC have led to harmful impacts on the water quality of this tidal river, with severe eutrophication events. This situation results from the conjunction of contrasting hydrological seasons and the lack of upgraded sanitation infrastructures: indeed, less than 10% of the domestic wastewater is collected and treated before being discharged directly into urban canals or rivers. This study focuses on P dynamics because this is considered the key nutrient factor controlling freshwater eutrophication. Based on field measurements and original laboratory experiments, we assessed the P levels in the river water and sediments, and investigated P adsorption/desorption capacity onto suspended sediment (SS) within the salinity gradient observed. Field surveys showed a clear impact of the HCMC megacity on the total P content in SS, which increased threefold at HCMC Center, as compared with the upstream values (0.3–0.8 gP kg−1). Downstream, in the mixed estuarine area, the Total P was lower than 0.5 gP kg−1. Laboratory experiments were carried out to characterize the influence of SS concentrations (SS = 0.25–0.9 g L−1), salinity (S = 2.6–9.3) and turbulence (G = 22–44 s−1) on the sorption capacity of P onto sediment. The size of sediment particles and their propensity to flocculate were also originally measured with a recently developed instrument: the System for the Characterization of Aggregates and Flocs (SCAF®). Under the experimental conditions considered, SS concentrations had the greatest effect on the adsorption of P onto sediment, e.g., P adsorption capacity increased when SS concentrations rose. In contrast, salinity and turbulence had a smaller effect on the adsorption properties of sediments. Among these observed variables, the SS concentration was shown to be the main driver for adsorption capacity of P onto SS within the salinity gradient. We discuss the implication of these findings on understanding P dynamics within a highly urbanized, tropical estuary.
Ho Chi Minh City (HCMC, Vietnam) is one of the fastest growing megacities in the world. In this paper, we attempt to analyse the dynamics of nutrients, suspended sediments, and water discharges in ...its aquatic systems today and in the future. The work is based on nine sampling sites along the Saigon River and one on the Dongnai River to identify the reference water status upstream from the urban area and the increase in fluxes that occur within the city and its surroundings. For the first time, the calculated fluxes allow drawing up sediment and nutrient budgets at the basin scale and the quantification of total nutrient loading to the estuarine and coastal zones (2012–2016 period). Based on both national Vietnamese and supplementary monitoring programs, we estimated the water, total suspended sediment, and nutrients (Total N, Total P, and dissolved silica: DSi) fluxes at 137 m3 year−1, 3,292 × 103 tonSS year−1, 5,323 tonN year−1, 450 tonP year−1, and 2,734 tonSi year−1 for the Saigon River and 1,693 m3 year−1, 1,175 × 103 tonSS year−1, 31,030 tonN year−1, 1,653 tonP year−1, and 31,138 tonSi year−1 for the Dongnai River, respectively. Nutrient fluxes provide an indicator of coastal eutrophication potential (indicator of coastal eutrophication potential), using nutrient stoichiometry ratios. Despite an excess of nitrogen and phosphorus over silica, estuarine waters downstream of the megacity are not heavily impacted by HCMC. Finally, we analysed scenarios of future trends (2025–2050) for the nutrient inputs on the basis of expected population growth in HCMC and improvement of wastewater treatment capacity. We observed that without the construction of a large number of additional wastewater treatment plants, the eutrophication problem is likely to worsen. The results are discussed in the context of the wastewater management policy.
Facial mask detection technology has become increasingly important even beyond the context of the COVID-19 pandemic. Along with the advancement in facial recognition technology, face mask detection ...has become a crucial feature for various applications. This paper introduces an Internet of Things (IoT) architecture based on a developed deep learning algorithm named You Only Look Once (YOLO) to keep society healthy, and secured, and collect data for future research. The proposed paradigm is built on the basis of economic consideration and is easy to implement. Yet, the used YOLOv4-tiny is one of the fastest object detection models to exist. A mask detection camera (MaskCam) that leverages the computing power of NVIDIA’s Jetson Nano edge nanodevices was built side by side with a smart camera application to detect a mask on the face of an individual. MaskCam distinguishes between mask wearers, those who are not wearing masks, and those who are not wearing masks properly according to MQTT protocol. Furthermore, a self-developed web browsing application comes with the MaskCam system to collect and visualize statistics for qualitative and quantitative analysis. The practical results demonstrate the superiority and effectiveness of the proposed smart mask detection system. On the one hand, YOLOv4-full obtained the best results even at smaller resolutions, although the frame rate is too small for real-time use. On the other hand, it is twice as fast as the other detection models, regardless of the quality of detection. Consequently, inferences may be run more frequently over the entire video sequence, resulting in more accurate output.
Graphdiyne (GDY), a new 2D material, has recently proven excellent performance in photodetector applications due to its direct bandgap and high mobility. Different from the zero‐gap of graphene, ...these preeminent properties made GDY emerge as a rising star for solving the bottleneck of graphene‐based inefficient heterojunction. Herein, a highly effective graphdiyne/molybdenum (GDY/MoS2) type‐II heterojunction in a charge separation is reported toward a high‐performance photodetector. Characterized by robust electron repulsion of alkyne‐rich skeleton, the GDY based junction facilitates the effective electron–hole pairs separation and transfer. This results in significant suppression of Auger recombination up to six times at the GDY/MoS2 interface compared with the pristine materials owing to an ultrafast hot hole transfer from MoS2 to GDY. GDY/MoS2 device demonstrates notable photovoltaic behavior with a short‐circuit current of −1.3 × 10−5 A and a large open‐circuit voltage of 0.23 V under visible irradiation. As a positive‐charge‐attracting magnet, under illumination, alkyne‐rich framework induces positive photogating effect on the neighboring MoS2, further enhancing photocurrent. Consequently, the device exhibits broadband detection (453–1064 nm) with a maximum responsivity of 78.5 A W−1 and a high speed of 50 µs. Results open up a new promising strategy using GDY toward effective junction for future optoelectronic applications.
Here, for the first time, a highly effective graphdiyne/molybdenum (GDY/MoS2) type‐II heterojunction in a charge separation is reported toward a high‐performance photodetector. The device exhibits broadband detection (453–1064 nm) with a maximum responsivity of 78.5 A W−1 and a high speed of 50 µs.
This study aims to develop an accurate dynamic cutting force model in the milling process. In the proposed model, the estimated cutting force tackles the effect of the self-excited vibration that ...causes machining instability during the cutting process. In particular, the square root of the residual cutting force between the prediction and the actual cutting force is considered as an objective function for optimizing the cutting force coefficients using the equilibrium optimizer (EO) approach instead of the trial-and-error approach. The results confirm that the proposed model can provide higher prediction accuracy when the EO is applied. In addition, the proposed EO has a minimum integral square error (ISE) of around 1.12, while the genetic algorithm (GA) has an ISE of around 1.14 and the trial-and-error method has an ISE of around 2.4. Moreover, the proposed method can help to investigate the cutting stability and to suspend the chatter phenomenon by selecting an optimal set of cutting parameters.
Determining the clinical and subclinical characteristics related to the recurrence status in patients with a thyroid carcinoma has great significance for prognosis, prediction of recurrence and ...monitoring of treatment outcomes. This study aimed to determine the association between recurrence rate and some characteristics in patients with thyroid carcinoma.
The study was conducted by descriptive method with longitudinal follow-up on 102 thyroid carcinoma patients at 103 Military Hospital, Hanoi, Vietnam, from July 2013 to December 2016.
Univariate analysis showed that there was a relationship between the recurrence characteristics in the studied patients and the characteristics of lymph node metastasis (
= 0.026; OR = 15; 95% CI = 1.4-163.2) and BRAF V600E mutation status (
= 0.01; OR = 3.41; 95% CI = 1.31-8.88). When analysing the multivariable Logistic regression model, there was a positive correlation between the occurrence of BRAF V600E gene mutation (
= 0.032; OR = 17.649; 95% CI = 1.290-241.523) and male sex (
= 0.036; OR = 12.788; 95% CI = 1.185-137.961) and the occurrence of recurrence in study patients. The mean time to relapse was earlier in male patients than in female patients (
= 0.02). The mean time to relapse in patients with the BRAF V600E mutation (31.81 ± 1.14 months) was shorter than the mean time to relapse in the group without the mutation (57.82 ± 2.08 months) (
= 0.01). The group of patients with mutations in the BRAF V600E gene increased the risk of recurrence compared with the group without the mutation (HR = 9.14,
= 0.04).
There is a positive correlation between recurrence and masculinity, lymph node metastasis and the occurrence of BRAF V600E mutations in thyroid carcinoma patients.
The integration renewable energy sources, characterized by inherently intermittent characteristics and low inertia, into grids introduce several impacts on the network operation such as stability, ...protection and challenges for management. In this paper, the stability of Con Dao Island grid in Vietnam with high renewable energy penetration, especially photovoltaic (PV) and Wind Turbine (WT) energy, is extensively studied. The main purpose of this paper is to investigate the impacts of high renewable energy integration on stability of this grid. Then, several solutions to the stability issues, including Fault Ride Through (FRT) capability of PV system and implementation of battery, is proposed and validated. Numerous scenarios are considered, including different PV penetration levels (inertia impact) and different events (short circuits and generator outage). The results obtained show the significant impact of PV penetration levels on the grid stability. However, the proposed solutions demonstrate their high effectiveness in addressing the identified instability issues of the grids.
PDF
