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In this paper we proposed a system for automatic fetal detection and approximation in ultrasound image. We used Adaboost. MH based on Multi Stump Classifier to detect fetal organs in ultrasound. After fetal organ detected, it is approximated using Randomized Hough Transform. Experiments result show that mean accuracy of the fetal organs detection reaches 93.92% with mean kappa coefficient value reaches...
The probability hypothesis density (PHD) filter handles the measurements periodically, once a scan period. Since measurements have to be gathered for a scan period before the PHD filter can perform a recursion, significant delay may arise if the scan period is long. To reduce this delay, we proposed sequential PHD filter. A Gaussian mixture implementation of the sequential PHD filter for nonlinear...
For typical indoor positioning systems employing a training/positioning model based on Wi-Fi fingerprints, significant training costs extremely restrict this kind of indoor localization system to be widely deployed and implemented with real location based applications. In this paper, we present a crowd-based approach to solve this problem, which automatically collects and constructs fingerprints database...
In this paper we present a higher order moment-matching algorithm for computing the distribution parameters of nonlinear transformation random variables. The new algorithm has two distinct aspects compared to the standard Unscented Kalman Filter (UKF). First, the sigma points are computed in two steps using the covariance matrix and higher-order moments. Second, the associated weights are positive...
This work presents a parallel implementation of the Parareal method using Portable Extensible Toolkit for Scientific Computation (PETSc). An optimal control problem of a parabolic partial differential equation with known boundary conditions and initial state is solved, where the minimized cost function relates the controller v usage and the approximation of the solution y to an optimal known function...
This work addresses a vision-based target tracking problem between a mobile observer and a target in the presence of a circular obstacle. The task of keeping the target in the observer's field-of-view is modeled as a pursuit-evasion game by assuming that the target is adversarial in nature. Due to the presence of obstacles, this is formulated as a game with state constraints. The objective of the...
The Spring-Loaded Inverted Pendulum (SLIP) is a widely used model for the description of humans and animals running motion. The SLIP model is, however, sensitive to impact angle for various terrain heights. One known method for increasing the model's robustness to terrain changes is the Swing Leg Retraction (SLR) method. Despite its popularity, an analytic formulation of this method has yet been provided...
The shape and center of mass of a part are crucial parameters to algorithms for planning automated manufacturing tasks. As industrial parts are generally manufactured to tolerances, the shape is subject to variations, which, in turn, also cause variations in the location of the center of mass. Planning algorithms should take into account both types of variation to prevent failure when the resulting...
The paper deals with discretisation of 2-D spatially invariant systems. Three different discretisation schemes are used — Tustin's approximation, backward difference scheme and Crank-Nicolson discretisation. Their properties and importance are discussed in the paper. As an example a heat conduction in a rod is considered. Its model discrete in both time and space is obtained using all the above mentioned...
Maximum likelihood (ML) based modulation detector provides the optimal performance in the sense that the detection error probability is minimized, if no prior probability of candidate modulations is available at the modulation detector. However, the evaluation of the likelihood function requires prohibitively high computational complexity. This contribution deals with an approximation of the ML detector,...
The major benefits of the emerging cloud computing infrastructure include elimination of the fixed cost and reduction in the marginal cost for the users due to the economy of scale and dynamic resource sharing. This paper argues that these unquestionable economic benefits of dynamic resource sharing are inherently associated with systemic risks and drawbacks. This possibility necessitates shift in...
In this paper, we consider the localization problem on wireless sensor networks in indoor environments, in the case when low cost ranging techniques are used. Each sensor node seeks to estimate its local map (i.e., its own position and that of the sensor nodes in its neighborhood) by collecting noisy measurements of the received signal strength indicator (RSSI) from packets sent by its neighbors....
We consider a system of two nodes transmitting to an access point on quasi-static Rayleigh fading channels. We use signal-to-noise ratio (SNR) thresholds to characterize the requirements of each node, in terms of throughput and reliability, and we study their impact on outage probability. Given the average quality of the uplink channels, we formulate conditions on the SNR thresholds for decode-and-forward...
The steady-state response of a nonlinear object, stimulated by sinusoidal signal, contains both the sinusoidal components of the same pulsation and higher harmonics. In the case of a linear plant with complex poles, working on the border of stability, a steady-state response of a sinusoidal input also contains the components with different pulsations. Their amplitude and phase shifts are dependent...
The paper presents the average path estimation algorithm. This algorithm is based on the approximation curve, which shape should by defined as closely as possible to the shape of the analyzed path. With the use of this initial curve, the data space is divided into the intervals. All of the interval paths points are averaged individually. After the calculations, there is only one average point for...
We present an alternative derivation of analytical expressions for the coefficients of the perturbative nonlinear pre-compensation algorithm in dispersion-unmanaged regime for arbitrary pulse shapes. We specialize to Nyquist pulse-shapes and show the usefuleness of new formulae through simulations and experiments.
A novel fault approximation tool (FAT) is presented for use in distribution networks with a high penetration of inverter-interfaced distributed generation. The FAT does not rely on balanced operation nor an absolute reference point for voltage calculations, both of which are required for Newton-Raphson load flow calculations. Simulations show that the FAT provides an accurate representation of the...
Recent advancements in renewable energy has created a need for both high step-up and high efficiency dc-dc converters. These needs have typically been addressed with converters using high frequency transformers to achieve the desired gain. The transformer design, however, is challenging. This paper presents a high step-up current fed converter based on the classical Cockcroft-Walton (CW) multiplier...
This paper presents a scheme to improve the accuracy of the stochastic FDTD (S-FDTD) method. The S-FDTD calculates the variations in the electromagnetic fields caused by variability or uncertainty in the electrical properties. The accuracy of the S-FDTD method is controlled by the approximations for the correlation coefficients of the fields and the electrical properties. In this paper, a new approximation...
The equations of motion of a maneuvering vessel under the action of wind, current, rudder and propulsion are solved by the MATLAB Runge-Kutta solver ode45. The hydrodynamic derivatives used are those presented by Clarke et al. (1982)[1]. Wind and current loads are applied to segments of the vessel via a relative velocity formulation and drag coefficients. Course control is achieved by autopilot gains...
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