The Industry 4.0 concept embodies a topic widely discussed during specialized meetings and tutorials. Originally, this approach was interpreted as an attempt to shift industrial processes towards establishing the full...
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In this paper, a dynamic co-evolution compact genetic algorithm (DCCGA) is proposed for flexible flow shop scheduling problem (FFSP) to minimize the total earliness and tardiness (E/T) penalties. In this new algorithm...
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作者:
NOLDUS, ELOCCUFIER, MUniversity of Ghent
Faculty of Applied Sciences Department of Control Engineering and Automation Technologiepark-Zwijnaarde 9 B-9052 Gent-Zwijnaarde Belgium.
A new method is presented for estimating regions of asymptotic stability for autonomous nonlinear systems. The method applies to systems that can be proven to be non-oscillatory, using a suitable Lyapunov technique. I...
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A new method is presented for estimating regions of asymptotic stability for autonomous nonlinear systems. The method applies to systems that can be proven to be non-oscillatory, using a suitable Lyapunov technique. It is especially effective for second-order systems that possess several equilibrium states for which the regions of attraction must be found. The determination of the regions of asymptotic stability requires the explicit computation of a Lyapunov function and the determination by backward numerical integration of a limited number of trajectories. The obtained estimates are close approximations of the exact regions of asymptotic stability of the system's stable equilibria.
This paper presents ontlology-based architecture for pattern recognition in the context of static source code analysis. The proposed system has three subsystems: parser, OWL ontologies and analyser. The parser subsyst...
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ISBN:
(纸本)9783540855620
This paper presents ontlology-based architecture for pattern recognition in the context of static source code analysis. The proposed system has three subsystems: parser, OWL ontologies and analyser. The parser subsystem translates the input coded to AST that is constructed as an XML tree. The OWL ontologies define code patterns and general programming concepts. The analyser subsystem constructs instances of the input code as ontology individuals and asks the reasoner to classify them. The experience gained in the implementation of the proposed system and some practical issues are discussed. The recognition system successfully integrates the knowledge representation field and static code analysis. resulting in greater flexibility of the recognition system.
To improve the efficiency of nano-electronic device fabrication, a new method named floating electrical potential assembly is proposed to realize large-scale assembly of Cu/CuO nanowires, The simulation of floating el...
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To improve the efficiency of nano-electronic device fabrication, a new method named floating electrical potential assembly is proposed to realize large-scale assembly of Cu/CuO nanowires, The simulation of floating electrical potential distribution on the micro-electrode chip is performed by COMSOL software, and the simulation result shows that the coupled electrical poten- tial on the floating drain electrodes is very close to the original electrical potential applied on the gate electrode, whicb means that the method can provide di-electrophoresis (DEP) force for all the electrode pairs at one time, thus realizing large-scale as- sembly at one time. With Cu/CuO nanowires well dispersed and micro-electrode chip fabrication, nanowires assembly experiments are performed and the experimental results show that Cu/CuO nanowires are assembled at hundreds of micro-electrodes pairs at one time, and the success rate of nanowires assembly also reaches 90%.
A prototype of a cheap IoT system for real-time monitoring of river water quality has been developed. The system consists of monitoring stations and appropriate presentation devices (computer, phone, or similar). Each...
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Aiming at solving the problem of strong coupling characteristic of the key parameters of high-speed pneumatic pulse width modulation( PWM) on / off valve, a general lumped parameter mathematical model based on the val...
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Aiming at solving the problem of strong coupling characteristic of the key parameters of high-speed pneumatic pulse width modulation( PWM) on / off valve, a general lumped parameter mathematical model based on the valves time periods was well developed. With this model,the mass flow rate and dynamic pressure characteristics of constant volumes controlled by high-speed pneumatic PWM on /off valves was well described. A variable flow rate coefficient model was proposed to substitute for the constant one used in most of the prior works to investigate PWM on /off valves' dynamical pressure response, and a formula for disclosing the inherent relationship among the PWM command signal,static mass flow rate,and sonic conductance of the valve was newly ***,an extensive set of analytical experimental comparisons were implemented to verify the validity of the proposed mathematica model. With the proposed model, PWM on /off valves' characteristics,such as mass flow rate,step pressure response of the valve control system,mean pressure and ripple amplitude,not only in the linear range,but also in the nonlinear range can be wel predicted; Good agreement between measured and calculated results was obtained,which proved that the model is helpful for designing a control strategy in a closed loop control system.
Detectability is the key property which underlies the design of any convergent observer. In this paper a method for analyzing the detectability for a class of networks of systems with unknown inputs is presented, expl...
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A detailed design of mechanisms is presented, along with the required electromagnetic system to attach the robot to the tank's wall. This is a novel mechanical design in which the robotic wheels rotate changing th...
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Least squares support vector machines(LSSVM) has a good performance in small data samples, but can't solve the large-scale sample problems. In this paper, large data set sparse least squares support vector machine...
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ISBN:
(纸本)9781538629185
Least squares support vector machines(LSSVM) has a good performance in small data samples, but can't solve the large-scale sample problems. In this paper, large data set sparse least squares support vector machines model based on stochastic entropy is proposed, and it can be applied to large-scale data samples. Firstly, the large-scale data set is divided into several subsets. Then the entropy method is used to the sparse samples in each subset. Finally, we use sparse samples sets as training samples, and use least squares support vector machine algorithm to train. The results show that the sparse least squares support vector machine model based on entropy can effectively solve the problem of large-scale data.
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