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Foreground detection is the classical computer vision task of segmenting out motion information from a particular scene. Foreground detection using Gaussian Mixture Models (GMM) is the famous choice. Since first time proposed, many researchers tried to improve GMM. This paper focuses on the comparative evaluation of three most famous improvements in the algorithm. The improved methods are compared...
This paper proposes a vibration control scheme of a strip in a continuous galvanizing line using neuro-PID controller which consists of two neural networks and conventional PID controller. One NNs estimates the strip model using input-output data of the strip and other NNs updates the gains of conventional PID controller using the estimated strip model and errors between the desired and actual outputs...
In this paper, we propose a numerically reliable algorithm for computing the transfer function matrix of a descriptor system. Descriptor system has widely been used. The system often arises when modelling a linear system. Linear systems such as inversion are often represented in terms of descriptor systems. Although the representation is useful, it is not appropriate for simulation and experiment...
This paper proposes a method for detecting moving objects appeared in video captured by a moving camera. The proposed method relies on dense optical flow to differentiate moving objects from static background. Whenever video taken from a static camera is used, the dense optical flow itself is sufficient to determine the moving object in the scenes. However, in a non-static camera, all pixels are moving...
Object detection is one of the important problems for autonomous robots. Faster R-CNN, one of the state-of-the-art object detection methods, approaches real time application; nevertheless, computational time lies borderline of real time application, i.e. 5fps with VGG16 model in K40 GPU system in [1]. Moreover, computation time depends on model and image crop size, but precision is also affected;...
This paper presents a data mining technique for qualitative analysis of Hodgkin-Huxley model of cell excitability. Such problem cannot be solved analytically. Therefore we apply Monte-Carlo techniques for the generation of model parameters, and use data mining algorithm for classification of learning tuples obtained. As a result we attain a decision tree capable of classifying the excitability depending...
A novel scheme to solve the trajectory planning problem for quadrotors with model and state constraints is proposed. First the RRT (Rapidly-exploring Random Tree) algorithm is employed to generate an initial route in context of a 3D environment. Then with the model of quadrotoer, the MPC (Model Predictive Control) method is used to construct an inner simulator which can generate the trajectories satisfying...
This article presents a decentralized control strategy applied to a multi-source power system having a fuel cell (FC) system as a main power source and a secondary storage element (SSE) for peak current supply during transients and energy recovery during braking. The dedicated control structure aims to assure an optimal operation of the FC system and a desired energy level of the SSE. To attain these...
We consider the problem of area coverage for robot teams operating under resource constraints, while modeling spatio-temporal environmental phenomena. The aim of the mobile robot team is to avoid exhaustive search and only visit the most important locations that can improve the prediction accuracy of a spatio-temporal model. We use a Gaussian Process (GP) to model spatially varying and temporally...
Chest injury during unconstrained frontal collision between human and mobile robot is investigated using computer simulation with MADYMO. To assess the chest injury, Combined Thoracic Index (CTI) and Viscous Criteria(VC) was computed. Computed CTI and VC were converted into AIS level by which injury level was evaluated.
Satellite orbits are usually estimated by employing a filter system model whose state variables are the position and the velocity defined on the earth-fixed inertial (ECI) rectangular coordinate system. However, this filter formulation causes estimation errors due to nonlinearity of the measurement if the two-line element (TLE) data in which satellite's information is provided by orbital parameters...
There is developed the simulation model of single bit third order sigma-delta modulator. It provides investigation of the influence of components' parameters on modulator's error. It is presented results of investigation of integrator's nonlinearity on integral nonlinearity of this modulator. The presented results provides purposeful selecting of correction function for correction nonlinear error...
The aim of this work is to improve driver awareness by proposing a collision risk analysis method. Pedestrian in the scene is observed by sequential frames from monocular camera mounted on the car. Positional information of object is extracted by projecting the centroid of bounding box on the ground plane. Four elements of collision criteria are constructed which are pedestrian walking direction,...
A new nonlinear optimal control approach is proposed for autonomous navigation of unmanned surface vessels. The dynamic model of the surface vessels undergoes approximate linearization round local operating points which are redefined at each iteration of the control algorithm. These temporary equilibria consist of the last value of the vessel's state vector and of the last value of the control signal...
The increasing of transportation demand in Thailand requires a lot of human resources to support the future railway system. Therefore, we have developed an in-house fixed-block train control simulation system to be used as a tool for helping learners to understand train control procedures. The train control simulation system combines of train model, signaling control hardware, and controlling and...
The purpose of this research is to offer constructive algorithm for estimator search in one network model under state and measurements attacks. The model is nonstationary descriptor system including difference equations for node state variables and algebraic equations for measurements. State variables and measurements are considered as random vectors. We use information cost criterion in order to...
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