A novel hybrid evidential belief function-based fuzzy logic model in spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam)

The main objective of this study is to investigate potential application of an integrated evidential belief function (EBF)-based fuzzy logic model for spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam). First, a landslide inventory map was constructed from various sources. Then the landslide inventory map was randomly partitioned as a ratio of 70/30 for training and validation of the models, respectively. Second, six landslide conditioning factors (slope angle, slope aspect, lithology, distance to faults, soil type, land use) were prepared and fuzzy membership values for these factors classes were estimated using the EBF. Subsequently, fuzzy operators were used to generate landslide susceptibility maps. Finally, the susceptibility maps were validated and compared using the validation dataset. The results show that the lowest prediction capability is the fuzzy SUM (76.6%). The prediction capability is almost the same for the fuzzy PRODUCT and fuzzy GAMMA models (79.6%). Compared to the frequency-ratio based fuzzy logic models, the EBF-based fuzzy logic models showed better result in both the success rate and prediction rate. The results from this study may be useful for local planner in areas prone to landslides. The modelling approach can be applied for other areas

Studying the thermo-gas-dynamic process in a muzzle brake compensator

To reduce the recoil and improve the stability of small arms, a muzzle brake compensator is attached to the muzzle of the barrel. This device uses the kinetic energy of the powder gas escaping from the bore after the bullet is fired. In this paper, the authors present the determination of the thermo-gas-dynamic model of the operation of a muzzle brake compensator and an example of calculating this type of muzzle device for the AK assault rifle using 7.62x39 mm ammunition. The results of the calculation allowed for obtaining the parameters of the powder gas flow in the process of flowing out of the muzzle device, as well as the change in the momentum of the powder gas's impact on the muzzle device. The model proposed in the article provides the basis for a quantitative evaluation of the effectiveness of using the muzzle device in stabilizing infantry weapons when firing

Career Ambition and Employee Performance Behaviour: The Presence of Ideological Development

This study develops and tests a theoretical model that investigates how career ambition can have an impact on different types of academics' performance behaviour, and how ideological development at work can affect this model in a special context of a communist country. In a study of 991 employees in a large university in Vietnam, the model is largely supported. The findings suggest that in-role behaviour has a significant mediating role in the effect of career ambition on extra-role behaviour and that this mediating effect is stronger among the group of employees who have participated in advanced ideological development in the context of Vietnamese higher education. This study advances the understanding of an underdeveloped relationship between career ambition and employee performance behaviour, and expands the knowledge of the impact of ideological development at work

Applications of Big Data Analytics in Traffic Management in Intelligent Transportation Systems

Big Data technology is emerging as a mass technology that can be applied to many industries in life. Decisions in a wide range of fields may benefit greatly from the information provided by Big Data and Analytics research. One of the areas that have benefited the most from this technology is transportation, which is known as an important field in the development of each nation and possesses a huge treasure of data that traditional technologies cannot handle. Indeed, many countries have applied Big Data-based intelligent transportation systems because it is a traffic system that interacts with vehicles and people on the road, thereby reducing traffic congestion and traffic accidents year by year in many countries. The article presents the applications of Big Data technology in smart traffic systems, thereby providing the perspective of a smart city with a smart traffic system as a critical factor. This paper's analysis indicated that smart cities could be born and further developed through the linkage of Big Data technology and smart traffic systems with smart traffic systems as the core. In addition, the results also showed that the obstacle that needs to be studied at this time is the policy and legal framework for Big Data technology. Therefore, a system managed by the state or shared between the state and the private sector should be studied in the future, aiming to harmonize interests and develop the system extensively

Studying the thermo-gas-dynamic process in a muzzle brake compensator

To reduce the recoil and improve the stability of small arms, a muzzle brake compensator is attached to the muzzle of the barrel. This device uses the kinetic energy of the powder gas escaping from the bore after the bullet is fired. In this paper, the authors present the determination of the thermo-gas-dynamic model of the operation of a muzzle brake compensator and an example of calculating this type of muzzle device for the AK assault rifle using 7.62x39 mm ammunition. The results of the calculation allowed for obtaining the parameters of the powder gas flow in the process of flowing out of the muzzle device, as well as the change in the momentum of the powder gas's impact on the muzzle device. The model proposed in the article provides the basis for a quantitative evaluation of the effectiveness of using the muzzle device in stabilizing infantry weapons when firing

Numerical Simulation of Low Salinity Water Flooding on Core Samples for an Oil Reservoir in the Nam Con Son Basin, Vietnam

Low-salinity water flooding (LSWF) is environment-friendly and operates similarly to conventional waterflooding without the need for synthetic chemical materials. The application of LSWF makes sense in Vietnam as HC production has steadily declined since 2002, and the majority of main oil fields have become near mature and mature fields. In the next years, Enhanced Oil Recovery (EOR) should be a top priority for Petro Vietnam to boost its oil production, for which the key issue is how to select a suitable EOR technology. In this study, LSWF of the Lower Miocene sand using low salinity water from Lower Oligocene sand was investigated. Previously at the Ruby field in the Cuu Long Basin, an LSWF feasibility study was carried out based on a conventional core flooding experiment, which is time-consuming and costly. This study targets the Chim Sao field in the Nam Con Son Basin, for which a cheaper and faster assessing method is required. As a result, a numerical code written in Matlab was developed and successfully validated with the core flooding experiment results obtained at the Ruby field. The LSWF simulation was conducted using the multiple ion-exchange mechanisms (MIE), and the results obtained showed an increase in the oil recovery factor by 2.19% for the Lower Miocene Sand. Another important outcome of this study is the innovative proposal and successful simulation to use the abundant low salinity water from the underlying Lower Oligocene sand as a natural LSW source to inject into the Lower Miocene oil reservoir that can be a decisive factor to help apply LSWF in practice on a wide scale not only for Chim Sao but also other similar oil fields in southern offshore Vietnam

Sliding mode control of antagonistically coupled pneumatic artificial muscles using radial basis neural network function

Abstract This study presents a novel approach to enhance the control of Pneumatic Artificial Muscle (PAM) systems by combining Sliding Mode Control (SMC) with the Radial Basis Function Neural Network (RBFNN) algorithm. PAMs, when configured antagonistically, offer several advantages in creating human-like actuators. However, their inherent nonlinearity and uncertainty pose challenges for achieving precise control, especially in rehabilitation applications where control quality is crucial for safety and efficacy. To address these challenges, we propose an RBF-SMC approach that leverages the nonlinear elimination capability of SMC and the adaptive learning ability of RBFNN. The integration of these two techniques aims to develop a robust controller capable of effectively dealing with the inherent disadvantages of PAM systems under various operating conditions. The suggested RBF-SMC approach is theoretically verified using the Lyapunov stability theory, providing a solid foundation for its effectiveness. To validate its performance, extensive multi-scenario experiments were conducted, serving as a significant contribution of this research. The results demonstrate the superior performance of the proposed controller compared to conventional controllers in terms of convergence time, robustness, and stability. This research offers a significant contribution to the field of PAM system control, particularly in the context of rehabilitation. The developed RBF-SMC approach provides an efficient and reliable solution to overcome the challenges posed by PAMs’ nonlinearity and uncertainty, enhancing control quality and ensuring the safety and efficacy of these systems in practical applications

Application of IoT Technologies in Seaport Management

Seaports have a very important role in connecting freight by sea. Goods transported through seaports in the world are increasing day by day to meet human needs. This increases the pressure to apply more technologies for better port management. The world's seaports in the 4th generation, the generation in which seaports enhance connectivity to form a large network, have shown high efficiency when applying technology to port management. This optimizes port operations and connects port information into a network that improves productivity and reduces loading and unloading times. Today, the Internet of Things is the foundation for technologies to manage and optimize operations in various fields. It is considered by scientists to be a highly influential technology in the “4.0” era. The Internet of Things (IoT) technology directly affects the activities and processes of loading and unloading goods at seaports. Modern IoT-based port management technologies such as Radio Frequency Identification (RFID) and Dedicated Short Range Communications (DSRC) are contributing to the increased speed and safe movement of goods through seaports. The application of IoT in port management has become an inevitable trend and will be presented in this article. In the next generation, seaports tend to develop into smart ports based on rapidly developing technology platforms such as IoT, blockchain, and cloud computing. Smart port development also poses many issues to be resolved, including environmental issues. In this paper, the authors present some solutions to develop smart ports in an environmentally friendly manner

Hepatoprotective Effect of Millettia dielsiana: In Vitro and In Silico Study

In silico docking studies of 50 selected compounds from Millettia dielsiana Harms ex Diels (family Leguminosae) were docked into the binding pocket of the PI3K/mTOR protein. In there, compounds trans−3−O-p-hydroxycinnamoyl ursolic acid (1) and 5,7,4′−trihydroxyisoflavone 7−O−β−D−apiofuranosyl−(1→6)−β−D−glucopyranoside (2) are predicted to be very promising inhibitors against PI3K/mTOR. They direct their cytotoxic activity against Hepatocellular carcinoma with binding affinity (BA) values, the pulling work spent to the co-crystallized ligand from the binding site of PI3K/mTOR (W and Fmax), and the non-equilibrium binding free energy (∆GneqJar) as BA values = −9.237 and −9.083 kcal/mol, W = 83.5 ± 10.6 kcal/mol with Fmax = 336.2 ± 45.3 pN and 126.6 ± 21.7 kcal/mol with Fmax = 430.3 ± 84.0 pN, and ∆GneqJar = −69.86074 and −101.2317 kcal/mol, respectively. In molecular dynamic simulation, the RMSD value of the PI3K/mTOR complex with compounds (1 and 2) was in the range of 0.3 nm to the end of the simulation. Therefore, the compounds (1 and 2) are predicted to be very promising inhibitors against PI3K/mTOR. The crude extract, ethyl acetate fraction and compounds (1 and 2) from Millettia dielsiana exhibited moderate to potent in vitro cytotoxicity on Hepatocellular carcinoma cell line with IC50 values of 81.2 µg/mL, 60.4 µg/mL, 23.1 μM, and 16.3 μM, respectively, and showed relatively potent to potent in vitro antioxidant activity on mouse hepatocytes with ED50 values of 24.4 µg/mL, 19.3 µg/mL, 30.7 μM, and 20.5 μM, respectively. In conclusion, Millettia dielsiana and compounds (1 and 2) are predicted to have very promising cytotoxic activity against Hepatocellular carcinoma and have a hepatoprotective effect