A formula of evaluating structural safety based on fuzzy set theory

This article presents an approach to assess safety levels of structures. A new formula for determining the fuzzy reliability of structures is proposed for the case where the set of loading effect and set of structural durability are general fuzzy sets. Illustration example concerning the bending strength evaluation of a simple-beam structure, is presented with the choice of triangular fuzzy sets for loading effect and structural durability

Development of Multi-Robotic Arm System for Sorting System Using Computer Vision

This paper develops a multi-robotic arm system and a stereo vision system to sort objects in the right position according to size and shape attributes. The robotic arm system consists of one master and three slave robots associated with three conveyor belts. Each robotic arm is controlled by a robot controller based on a microcontroller. A master controller is used for the vision system and communicating with slave robotic arms using the Modbus RTU protocol through an RS485 serial interface. The stereo vision system is built to determine the 3D coordinates of the object. Instead of rebuilding the entire disparity map, which is computationally expensive, the centroids of the objects in the two images are calculated to determine the depth value. After that, we can calculate the 3D coordinates of the object by using the formula of the pinhole camera model. Objects are picked up and placed on a conveyor branch according to their shape. The conveyor transports the object to the location of the slave robot. Based on the size attribute that the slave robot receives from the master, the object is picked and placed in the right position. Experiment results reveal the effectiveness of the system. The system can be used in industrial processes to reduce the required time and improve the performance of the production line

Design and development of a delta robot system to classify objects using image processing

In this paper, a delta robot is designed to grasp objects in an automatic sorting system. The system consists of a delta robot arm for grasping objects, a belt conveyor for transmitting objects, a camera mounted above the conveyor to capture images of objects, and a computer for processing images to classify objects. The delta robot is driven by three direct current (DC) servo motors. The controller is implemented by an Arduino board and Raspberry Pi 4 computer. The Arduino is programmed to provide rotation to each corresponding motor. The Raspberry Pi 4 computer is used to process images of objects to classify objects according to their color. An image processing algorithm is developed to classify objects by color. The blue, green, red (BGR) image of objects is converted to HSV color space and then different thresholds are applied to recognize the object’s color. The robot grasps objects and put them in the correct position according to information received from Raspberry. Experimental results show that the accuracy when classifying red and yellow objects is 100%, and for green objects is 97.5%. The system takes an average of 1.8 s to sort an object

Path Following and Avoiding Obstacle for Mobile Robot Under Dynamic Environments Using Reinforcement Learning

Obstacle avoidance for mobile robot to reach the desired target from a start location is one of the most interesting research topics. However, until now, few works discuss about working of mobile robot in the dynamic and continuously changing environment. So, this issue is still the research challenge for mobile robots. Traditional algorithm for obstacle avoidance in the dynamic, complex environment had many drawbacks. As known that Q-learning, the type of reinforcement learning, has been successfully applied in computer games. However, it is still rarely used in real world applications. This research presents an effectively method for real time dynamic obstacle avoidance based on Q-learning in the real world by using three-wheeled mobile robot. The position of obstacles including many static and dynamic obstacles and the mobile robot are recognized by fixed camera installed above the working space. The input for the robot is the 2D data from the camera. The output is an action for the robot (velocities, linear and angular parameters). Firstly, the simulation is performed for Q-learning algorithm then based on trained data, The Q-table value is implemented to the real mobile robot to perform the task in the real scene. The results are compared with intelligent control method for both static and dynamic obstacles cases. Through implement experiments, the results show that, after training in dynamic environments and testing in a new environment, the mobile robot is able to reach the target position successfully and have better performance comparing with fuzzy controller

A continuum-microscopic method based on IRBFs and control volume scheme for viscoelastic fluid flows

A numerical computation of continuum-microscopic model for visco-elastic flows based on the Integrated Radial Basis Function (IRBF) Control Volume and the Stochastic Simulation Techniques (SST) is reported in this paper. The macroscopic flow equations are closed by a stochastic equation for the extra stress at the microscopic level. The former are discretised by a 1D-IRBF-CV method while the latter is integrated with Euler explicit or Predictor-Corrector schemes. Modelling is very efficient as it is based on Cartesian grid, while the integrated RBF approach enhances both the stability of the procedure and the accuracy of the solution. The proposed method is demonstrated with the solution of the start-up Couette flow of the Hookean and FENE dumbbell model fluids

Design a low-cost delta robot arm for pick and place applications based on computer vision

In this paper, we develop a low-cost delta robot arm for grasping objects of unspecified size thanks to a vision system. Stepper motors are used instead of ac servo motors to build a low-cost delta robot arm. Furthermore, we use available materials and machining methods such as laser cutting and 3d printing instead of CNC milling and turning to reduce fabrication costs. The controller is based on a low-cost embedded controller - Arduino Uno for controlling the robot's motion. The vision system is constructed to determine the 3D coordinate of objects in the workspace as well as the sizes of objects. The gripper is opened with a distance of two fingers equal to the size of the objects, and the robot is controlled to the objects' coordinates to grasp them. An application to pick up objects on a conveyor belt is developed to validate the design. The experimental results show that the robot system works correctly, the robot arm moves smoothly, and the information determined by the vision system has a small error, ensuring that the robot can accurately pick up products

A time discretization scheme based on integrated radial basis functions for heat transfer and fluid flow problems

This paper reports a new numerical procedure, which is based on integrated radial basis functions (IRBFs) and Cartesian grids, for solving time-dependent differential problems that can be defined on non-rectangular domains. For space discretisations, compact five-point IRBF stencils [Journal of Computational Physics, vol. 235, pp. 302-321, 2013] are utilised. For time discretisations, a two-point IRBF scheme is proposed, where the time derivative is approximated in terms of not only nodal function values at the current and previous time levels but also nodal derivative values at the previous time level. This allows functions other than a linear one to also be captured well on a time step. The use of the RBF width as an additional parameter to enhance the approximation quality with respect to time is also explored. Various kinds of test problems of heat transfer and fluid flows are conducted to demonstrate attractiveness of the present compact approximations

Association between ACE I/D genetic polymorphism and the severity of coronary artery disease in Vietnamese patients with acute myocardial infarction

BackgroundThe severity of coronary artery disease is a prognostic factor for major adverse cardiovascular events in patients diagnosed with acute myocardial infarction. ACE I/D polymorphism is one of the genetic factors that may affect the severity of coronary artery disease. This study aimed to investigate the association between ACE I/D genotypes and the severity of coronary artery disease in patients with acute myocardial infarction.Materials and methodsA single-center, prospective, observational study was conducted at the Department of Cardiology and Department of Interventional Cardiology, Cho Ray Hospital, Ho Chi Minh City, Vietnam from January 2020 to June 2021. All participants diagnosed with acute myocardial infarction underwent contrast-enhanced coronary angiography. The severity of coronary artery disease was determined by Gensini score. ACE I/D genotypes were identified in all subjects by using the polymerase chain reaction method.ResultsA total of 522 patients diagnosed with first acute myocardial infarction were recruited. The patients' median Gensini score was 34.3. The II, ID, and DD genotype rates of ACE I/D polymorphism were 48.9%, 36.4%, and 14.7%, respectively. After adjusting for confounding factors, multivariable linear regression analysis showed that the ACE DD genotype was independently associated with a higher Gensini score compared with the II or ID genotypes.ConclusionThe DD genotype of the ACE I/D polymorphism was associated with the severity of coronary artery disease in Vietnamese patients diagnosed with first acute myocardial infarction

Compact approximation stencils based on integrated flat radial basis functions

This paper presents improved ways of constructing compact integrated radial basis function (CIRBF) stencils, based on extended precision, definite integrals, higher-order IRBFs and minimum number of derivative equations, to enhance their performance over large values of the RBF width. The proposed approaches are numerically verified through second-order linear differential equations in one and two variables. Significant improvements in the matrix condition number, solution accuracy and convergence rate with grid refinement over the usual approaches are achieved

Synthesis of para-menthane 3,8 - diol from Eucalyptus citriodora essential oil for application in mosquito repellent products

To repel mosquitoes, there have been many highly effective chemical repellent products, but they carry the potential risk of being unsafe for humans and harmful to the environment. Insect repellent products derived from natural sources that are safe for humans and environmentally friendly are becoming increasingly popular. PMD is a broad-spectrum and effective insect repellent but is present in small amounts in the Eucalyptus citriodora essential oil (EO). In this study, we investigated and evaluated the conditions for synthesizing PMD from EO raw materials in an acidic environment to achieve the highest synthesis efficiency of 76.3%, and the PMD product was 96.4% pure after being converted for 5 hours at 50°C in a 0.25% H2SO4 solution. Additionally, the study also separated the two cis and trans isomers of PMD by column chromatography and determined their structures using infrared spectroscopy (IR) and nuclear magnetic resonance (NMR)