Today, dosimeters are used generally for dosimetry of the diagnostic X-ray beam. Ionization chambers are appropriate instruments for monitoring and also the dosimetry of X-ray beam in medical diagnostic equipment. The...Today, dosimeters are used generally for dosimetry of the diagnostic X-ray beam. Ionization chambers are appropriate instruments for monitoring and also the dosimetry of X-ray beam in medical diagnostic equipment. The present work introduces design and investigation of a new ring-shaped monitor chamber with a PMMA body, graphite-coated PMMA windows (0.5 mm thick), a special graphite-foil central electrode (0.1 mm thick, 0.7 g/cm3 dense) that creating two sensitive volumes and a central hole for crossing the radiation beam with less attenuation. The results of performance tests conducted at the Nuclear Science and Technology Research Institute, AEOI in Karaj- Iran proved the high short and long-term stability, the very low leakage current, the low directional dependence and very high ion collection efficiency through the special design of the collecting electrode. Moreover, the FLUKA Monte Carlo simulations certified the negligible effect of central electrode on this new ring-shaped monitor chamber. According to the results of the performance tests, the new monitor chamber can be used as a standard dosimeter in order to monitor X-ray beam in primary standard dosimetry laboratories.展开更多
Rapid prototyping,real-time control and monitoring of various events in robots are crucial requirements for research in the fields of modular and swarm robotics.A large quantities of resources(time,man power,infrastru...Rapid prototyping,real-time control and monitoring of various events in robots are crucial requirements for research in the fields of modular and swarm robotics.A large quantities of resources(time,man power,infrastructure,etc.)are often invested in programming,interfacing the sensors,debugging the response to algorithms during prototyping and operational phases of a robot development cycle.The cost of developing an optimal infrastructure to efficiently address such control and monitoring requirements increases significantly in the presence of mobile robots.Though numerous solutions have been developed for minimizing the resources spent on hardware prototyping and algorithm validation in both static and mobile scenarios,it can be observed that researchers have either chosen methodologies that conflict with the power and infrastructure constraints of the research field or generated constrained solutions whose applications are restricted to the field itself.This paper develops a solution for addressing the challenges in controlling heterogeneous mobile robots.A platform named Quanta-a cost effective,energy efficient and high-speed wireless infrastructure is prototyped as a part of the research in the field of modular robotics.Quanta is capable of controlling and monitoring various events in/using a robot with the help of a light-weight communication protocol independent of the robot hardware architecture(s).展开更多
Modern manufacturing aims to reduce downtime and track process anomalies to make profitable business decisions.This ideology is strengthened by Industry 4.0,which aims to continuously monitor high-value manufacturing ...Modern manufacturing aims to reduce downtime and track process anomalies to make profitable business decisions.This ideology is strengthened by Industry 4.0,which aims to continuously monitor high-value manufacturing assets.This article builds upon the Industry 4.0 concept to improve the efficiency of manufacturing systems.The major contribution is a framework for continuous monitoring and feedback-based control in the friction stir welding(FSW)process.It consists of a CNC manufacturing machine,sensors,edge,cloud systems,and deep neural networks,all working cohesively in real time.The edge device,located near the FSW machine,consists of a neural network that receives sensory information and predicts weld quality in real time.It addresses time-critical manufacturing decisions.Cloud receives the sensory data if weld quality is poor,and a second neural network predicts the new set of welding parameters that are sent as feedback to the welding machine.Several experiments are conducted for training the neural networks.The framework successfully tracks process quality and improves the welding by controlling it in real time.The system enables faster monitoring and control achieved in less than 1 s.The framework is validated through several experiments.展开更多
文摘Today, dosimeters are used generally for dosimetry of the diagnostic X-ray beam. Ionization chambers are appropriate instruments for monitoring and also the dosimetry of X-ray beam in medical diagnostic equipment. The present work introduces design and investigation of a new ring-shaped monitor chamber with a PMMA body, graphite-coated PMMA windows (0.5 mm thick), a special graphite-foil central electrode (0.1 mm thick, 0.7 g/cm3 dense) that creating two sensitive volumes and a central hole for crossing the radiation beam with less attenuation. The results of performance tests conducted at the Nuclear Science and Technology Research Institute, AEOI in Karaj- Iran proved the high short and long-term stability, the very low leakage current, the low directional dependence and very high ion collection efficiency through the special design of the collecting electrode. Moreover, the FLUKA Monte Carlo simulations certified the negligible effect of central electrode on this new ring-shaped monitor chamber. According to the results of the performance tests, the new monitor chamber can be used as a standard dosimeter in order to monitor X-ray beam in primary standard dosimetry laboratories.
文摘Rapid prototyping,real-time control and monitoring of various events in robots are crucial requirements for research in the fields of modular and swarm robotics.A large quantities of resources(time,man power,infrastructure,etc.)are often invested in programming,interfacing the sensors,debugging the response to algorithms during prototyping and operational phases of a robot development cycle.The cost of developing an optimal infrastructure to efficiently address such control and monitoring requirements increases significantly in the presence of mobile robots.Though numerous solutions have been developed for minimizing the resources spent on hardware prototyping and algorithm validation in both static and mobile scenarios,it can be observed that researchers have either chosen methodologies that conflict with the power and infrastructure constraints of the research field or generated constrained solutions whose applications are restricted to the field itself.This paper develops a solution for addressing the challenges in controlling heterogeneous mobile robots.A platform named Quanta-a cost effective,energy efficient and high-speed wireless infrastructure is prototyped as a part of the research in the field of modular robotics.Quanta is capable of controlling and monitoring various events in/using a robot with the help of a light-weight communication protocol independent of the robot hardware architecture(s).
文摘Modern manufacturing aims to reduce downtime and track process anomalies to make profitable business decisions.This ideology is strengthened by Industry 4.0,which aims to continuously monitor high-value manufacturing assets.This article builds upon the Industry 4.0 concept to improve the efficiency of manufacturing systems.The major contribution is a framework for continuous monitoring and feedback-based control in the friction stir welding(FSW)process.It consists of a CNC manufacturing machine,sensors,edge,cloud systems,and deep neural networks,all working cohesively in real time.The edge device,located near the FSW machine,consists of a neural network that receives sensory information and predicts weld quality in real time.It addresses time-critical manufacturing decisions.Cloud receives the sensory data if weld quality is poor,and a second neural network predicts the new set of welding parameters that are sent as feedback to the welding machine.Several experiments are conducted for training the neural networks.The framework successfully tracks process quality and improves the welding by controlling it in real time.The system enables faster monitoring and control achieved in less than 1 s.The framework is validated through several experiments.
