Over the last years, the development of Autonomous Underwater Vehicles (AUV) with attached robotic manipulators, the so-called Underwater Vehicle Manipulator System (UVMS), has gained significant research attention, d...
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This paper compares artificial intelligence (AI) methods to predict mechanical properties of sheet metal in stamping processes. The deviation of the mechanical properties of each blank leads to unpredicted failures in...
This paper compares artificial intelligence (AI) methods to predict mechanical properties of sheet metal in stamping processes. The deviation of the mechanical properties of each blank leads to unpredicted failures in stamping processes, such as fracture and spring back. The research team of this paper has been building a real time control system for stamping process in a smart factory. In order to facilitate that, it is necessary to predict the mechanical properties of each blank with non-destructive testing. The regression models based on the linear algebraic scheme have traditionally brought reliable results in terms of matching the measured non-destructive testing values to the mechanical properties. With a parallel to algebraic regression models, in recent studies on various domains, AI models have been adopted to improve the accuracy of the end-results and effectiveness of the models. This paper discusses the applicability of AI models for predicting the mechanical properties based on the eddy-current non-destructive testing method. For the study, 6 input features are collected through the eddy-current non-destructive testing to map eddy-current input data to mechanical properties of the blank. Yield stress and uniform elongation were predicted by using five AI methods, i.e., regularized linear regression, support vector regularized linear regression, support vector regression, multi-layer neural network, random forest regression, and gradient boosting regression were compared. The model performance, validated with 20% of test data that are intact during the training phase, is the main discussion point of this paper. Future works to improve the predictive accuracy of AI models is also discussed.
We study networks of human decision-makers who independently decide how to protect themselves against Susceptible-Infected-Susceptible (SIS) epidemics. Motivated by studies in behavioral economics showing that humans ...
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This paper studies the synchronization of a finite number of Kuramoto oscillators in a frequency-dependent bidirectional tree network. We assume that the coupling strength of each link in each direction is equal to th...
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Risk assessment is an inevitable step in implementation of a cyber-defense strategy. An important part of this assessment is to reason about the impact of possible attacks. In this paper, we propose a framework for es...
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The size of search space has an impact on the efficiency of test data generation by meta-heuristic algorithms. To enhance the efficiency of test data generation, a method that reduces search space utilizing interval a...
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The affine formation maneuver control problem of a leader-follower type multi-agent systems with the directed interaction graphs is studied in this paper. This paper firstly gives and proves a sufficient and necessary...
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The affine formation maneuver control problem of a leader-follower type multi-agent systems with the directed interaction graphs is studied in this paper. This paper firstly gives and proves a sufficient and necessary condition of achieving the affine localizability. Then, under the（d + 1）-reachable condition of the given d-dimensional nominal formation with d + 1 leaders, a formation of agents can be reshaped in arbitrary dimension by only controlling these leaders. In the sequel, a novel distributed control method for the followers with single-integrator dynamics is proposed to achieve the desired time-varying maneuvers, and the global stability is also proved. Corresponding simulations are carried out to verify the theoretical results,which show that these followers are tracking the time-varying references accurately and continuously.
Chirality, non-reciprocity and quantum correlations are at the centre of a wide range of intriguing effects and applications across natural sciences and emerging quantum technologies. However, the direct link combinin...
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The Mixed convention/braking Actuation Mobile Robot (MAMR) was designed to tackle some of the drawbacks of conventional mobile robots such as losing controllability due to primary actuator failures, mechanical complex...
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The concentration detection of the mixed gas is significant to operate safely and efficiently as well as reduce the emission of pollutants. In this paper, a concentration detection system based on acoustic relaxation ...
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The concentration detection of the mixed gas is significant to operate safely and efficiently as well as reduce the emission of pollutants. In this paper, a concentration detection system based on acoustic relaxation attenuation is designed in order to reconstruct the three-dimensional images. The system is based on FPGA, supplemented by other hardware circuits. The consists of the system, the choice of the ultrasonic transducer, the calculation of amplifier magnification, and the specific design of circuit are elaborated in the paper. Experiments certificate that the hardware system can measure the attenuation intensity and flight time of ultrasonic waves in real time accurately. It is the base to detect the concentration of the gas mixture.
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