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We address two important issues in causal discovery from nonstationary or heterogeneous data, where parameters associated with a causal structure may change over time or across data sets. First, we investigate how to efficiently estimate the "driving force" of the nonstationarity of a causal mechanism. That is, given a causal mechanism that varies over time or across data sets and whose...
This paper presents a method for estimating object poses based on force sensor information using a particle filter. Autonomous robots often face uncertainty of measurement of object position when they manipulate objects. Related studies dealing with uncertainty in manipulation mainly focused on motions while grasping objects. In contrast, however, a non-grasp contact motion can be advantageous because...
In this paper, an impedance control strategy is proposed for a rigid robot collaborating with human by considering impedance learning and human motion intention estimation. The least square method is used in human impedance identification, and the robot can adjust its impedance parameters according to human impedance model for guaranteeing compliant collaboration. Neural networks (NNs) are employed...
This paper proposes intrinsic contact sensing using a particle filter. Intrinsic contact sensing is a method, which detects the contact position without any sensors on the outer shell. Force sensors are attached on the supporting point of outer shell instead. This method has been expanded to estimate contact information even without shape information. However, previous methods assume that contact...
The aircraft braking is a complex dynamic and kinematic process, involving the brake wheel and runway status, loaded state and anti-skid control strategy and other aspects, including sophisticated uncertainties and nonlinear factors. This paper aiming at the nonlinear tire model with unknown parameters, combined with the empirical fitting slip rate coefficient curve based on the linear identification...
This paper proposes a Model predictive control (MPC) for linear induction motor drive. Model Predictive Control (MPC) is a strong method for controlling drives of the linear induction motor. In comparison with the Direct Force Control (DFC), MPC is more precise and more effective in the selection of the voltage vector. The results show that this control method has a better performance in comparison...
This paper presents a reliable but low-cost way for industrial digital microscopy to implement μm-level precision of X/Y stage motion control. Other than the prevailing designs using stepper motors with open-loop control algorithms, the proposed method uses DC motors with closed-loop sliding mode control (SMC) to save the cost and allow a smooth switching between manual and motorized mode for stage...
Since the layers of the renal glomerulus play a crucial role as electric shield in the sense of stopping the pass of giant proteins like the albumin, in this paper we propose the idea that the very beginning of the renal failure of diabetic nephropathy might be explained with the laws of the electricity. Concretely, we focus on the presence of electric fields due to the flux of albumin through the...
This paper presents a new multi-muscle force estimation approach based on a HD-sEMG/force model in experimental context. Accordingly, we will try to estimate the muscle force of the three elbow flexors: Biceps Brachii (BB), Brachialis (BR) and Brachioradialis (BRD) in isometric isotonic conditions. This will be done by using a recently proposed sEMG/force equation model validated by simulation. For...
The aim of this paper is to understand how closed national networks can impact the future cyber domain from the military perspective. We argue that Russia is currently manipulating the cyber domain through identified four lines of effort that may result in advantage in a form of asymmetric frontlines in cyber battlefields. Accordingly, a ‘closed network nation’ is able to force ‘open network society’...
To predict the vibration displacement distributed on a vibrating surface, an r order Non-equidistant Grey Model (r-NGM) is proposed in this paper. This model is built by accumulating the initial discrete non-equidistant vibration displacement set with the r order Accumulated Generating Operation (r-AGO). The r-NGM is applied to a vibrating surface of a shaker to displacement prediction. The experimental...
Kinetic and spatiotemporal gait analysis provides important information for the treatment and rehabilitation of patients with gait disorders. Although motion analysis laboratories with infrared motion capture cameras and force plates are the gold standard measurement technologies for analysis, they are, in most cases, impractical for community health centers or general clinical settings because of...
In this work a system for the estimation of the forces (both longitudinal and lateral) exerted between the tires and the road is presented. Starting from two of the most commonly used descriptions of the vehicle dynamics, the single-corner and the single-track models, a system composed of Sub-Optimal Second Order Sliding Mode observers in a cascade structure plus an adaptive element is developed and...
In the last years, the worldwide sales volume of electric vehicles increased and almost all well-known automobile manufacturers now have special departments for developing autonomous vehicles. This development leads to new challenges in the automobile sector. Besides the development of necessary components, one big challenge is the compliance with safety requirements. Autonomous vehicles need a large...
This paper describes sensitivity analysis to q-axis inductance variation of the position estimation using Extended Electromitive Force (EEMF) excited by High Frequency (HF) signal injection based on the mathematical formula evaluation, and it shows that the influence on the q-axis inductance variation is very small. Finally, experimental results indicate that position estimation can be performed well...
Displacement estimation is a critical component of elastography. The measurement of sub-resolution displacements relies on high cross-correlation (CC) between repeated collinear RF acquisitions. CCs are degraded by common sources of acoustic noise, such as reverberation clutter, in addition to the displacement of scatterers within the radiation force field. CCs are also degraded spatially across the...
Permanent magnet track linear motor drives are used in numerous industrial manufacturing processes covering a wide range of material handling and conveyor applications. A traditional solution is a permanent magnet linear motor (PMLM) in which the stationary part consists of permanent magnets and the moving part of the armature. To further reduce the initial costs of such a permanent magnet track linear...
It was shown experimentally in [1], [2] that a macroscopic cylindrical solid can be rotated due to the excitation of two counter-propagating surface acoustic waves (SAWs) with different amplitudes on its surface. Arising internal distributed rotation force has been calculated phenomenologically in the partial case of a piezoelectric tube with a ring unidirectional electrode transducer (RUDT) using...
An efficient control of nano-positioning stage remains a challenging task due to the effect of noise and disturbances and nonlinear friction phenomenon which is difficult for both modeling and control. In order to solve this problem, a novel model-free control method is applied to nano-positioning stage to provide the robustness and ability of disturbance rejection. Besides, a feedforward model which...
By definition, a distinguishing attack is any test that allows distinguishing the encrypted data from random data and modern symmetric-key ciphers must be immune to such an attack. In other words, modern block ciphers are designed to have ciphertext indistinguishability. If an algorithm that can distinguish the cipher output from random faster than a brute force search is found, then that is considered...
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