Comparison of stochastic filtering methods for 3D tracking

In the recent years, the 3D visual research has gained momentum with publications appearing for all aspects of 3D including visual tracking. This paper presents a review of the literature published for 3D visual tracking over the past five years. The work particularly focuses on stochastic filtering techniques such as particle filter and Kalman filter. These two filters are extensively used for tracking due to their ability to consider uncertainties in the estimation. The improvement in computational power of computers and increasing interest in robust tracking algorithms lead to increase in the use of stochastic filters in visual tracking in general and 3D visual tracking in particular. Stochastic filters are used for numerous applications in the literature such as robot navigation, computer games and behavior analysis. Kalman filter is a linear estimator which approximates system's dynamics with Gaussian model while particle filter approximates system's dynamics using weighted samples. In this paper, we investigate the implementation of Kalman and particle filters in the published work and we provide comparison between these techniques qualitatively as well as quantitatively. The quantitative analysis is in terms of computational time and accuracy. The quantitative analysis has been implemented using four parameters of the tracked object which are object position, velocity, size of bounding ellipse and orientation angle.     

Humidity sensing properties of Cu2O-PEPC nanocomposite films

In this study, the blend of copper oxide nanopowder (Cu2O), 3 wt.% and poly-N-epoxypropylcarbazole (PEPC), 2 wt.% in benzol were drop-casted on glass substrates with pre-deposited surface-type silver electrodes for the fabrication of Cu2O-PEPC nanocomposite thin films. The thicknesses of the Cu2O-PEPC films were in the range of 10-13 μm. The effect of humidity on the electrical properties of the nanocomposite films was investigated by measurement of the capacitance and dissipation of the samples at two different frequencies of the applied voltage: 120 Hz and 1 kHz. The AC resistance of the samples was determined from values of dissipation. The DC resistance was measured directly. The effect of ageing on the humidity sensing properties of the nanocomposite was observed. After the ageing it was observed that at 120 Hz and 1 kHz, under humidity of up to 86% RH , the capacitance of the cell increased by 85 and 8 times and resistance decreased by 345 and 157 times, accordingly, with respect to 30% RH conditions. It was found that with increase of the frequency, the capacitance and resistance of the samples decreased. It is assumed that the humidity response of the cell is associated with diffusion of water vapors and doping of the semiconductor nanocomposite by water molecules.     

Multiscale analysis of viscoelastic laminated composite plates using generalized differential quadrature

In this paper, a laminated composite plate is analyzed using a multiscale method. At first, material properties of a lamina are obtained using an analytical micromechanical approach called simplified unit cell method (SUCM), and then in structural level, the generalized differential quadrature method (GDQM) is used to analyze a laminated composite plate. By means of the Boltzmann superposition principle, the viscoelastic behavior of the matrix is obtained. The Prony series is considered to define the compliance of matrix. To verify the results, graphiteT300/epoxy5208 composite material is analyzed and the results are compared with existing experimental data. The multiscale algorithm includes obtaining overall properties of the composite by SUCM; then, these properties are used to define the bending stiffness. Governing equations of motion of laminated composite plate are solved via GDQM and Newton–Raphson method. Variations of stresses and displacements versus time and volume fraction of the fibers are shown for laminated composite plates with different boundary conditions.     

Robust Diversity-based Sine-Cosine Algorithm for Optimizing Hydropower Multi-reservoir Systems

Hydropower energy generation depends on the available water resources. Therefore, planning and operation of the water resource systems are paramount tasks for energy management. Since reservoirs are one of the important components of water resources systems, extracting optimal operating policies for proper management of energy generated from these systems is an imperative step. Optimizing reservoir system operation (ORSO) is a non-linear, large-scale, and non-convex problem with a large number of constraints and decision variables. To solve ORSO problem effectively, a robust diversity-based, sine-cosine algorithm (RDB-SCA) is developed in the present study by introducing several strategies to balance the global exploration and local exploitation ability and to achieve accurate and reliable solutions. An efficient linear operation rule is coupled with the RDB-SCA to maximize the energy generation. The proposed method is then applied to a real-world, multi-reservoir system to extract optimal operational policies and, consequently, maximize the energy production. It is shown that the RDB-SCA is able to generate 24, 14, and 6% more energy than the original SCA, respectively for 2-, 3-, and 4-reservoir systems. The present findings are useful to suggest guidelines for efficient operation of hydropower multi-reservoir systems. This paper is supported by https://imanahmadianfar.com/codes.

     

Topology optimization of transient problem with maximum dynamic response constraint using SOAR scheme

Frontiers of Mechanical Engineering - This paper proposes a novel method for the continuum topology optimization of transient vibration problem with maximum dynamic response constraint. An...     

A study on the efficiency of a capped hardening elasto-plastic model for soft clays

It is well known that the deformation and stress-resistant characteristics of fine-grained soils, especially soft clays, are significantly influenced by the soil softness. It is therefore very important to employ a model which can accurately simulate the effects of this phenomenon. A constitutive model must be able to create a balance among stress paths, the number of parameters, the process of parameter determination, and finally, the simplicity of the computational calculations.The current study investigates the performance of a two-yield surface (cone and cap yield surface) model for soft soils. The efficiency of the cap yield surface has been studied as well. The model has been calibrated by employing the data derived from previous researches for Bangkok clay. The incorporated data have been obtained from the results of CD triaxial, CU triaxial, and oedometer tests. The proposed method for the model calibration can accurately predict the triaxial test results and oedometer test stress path simultaneously. This method for predicting the soil behavior is based on the main soil characteristics taken from common soil mechanics tests. It can be widely employed for engineering practices, especially when complicated soil behavior is encountered.     

Effect of fortification on physico-chemical and microbiological stability of whole wheat flour

Stability of fortified whole wheat flour (WWF) was evaluated using NaFeEDTA, elemental iron, ZnSO₄ and ZnO as fortificants. Fortified WWF was stored in tin boxes and polypropylene bags for 60 days under ambient storage condition (ASC) and controlled storage condition (CSC). Fortification significantly (p ? 0.05) decreased moisture and protein content and increased ash content to 5.44%, 6% and 23%, as compared to control. Fortified WWF, assayed periodically for mould contamination manifested a significant inhibition (∼1 log reduction) in flours containing elemental iron. Low storage temperature and relative humidity (RH) indicated lower level of mould count during extended storage time. Tin boxes, as storage material, exhibited a better protection against mould attack, acting as an effective barrier for moisture. Fortificants exerted a slight deteriorative effect on texture characteristics of the chapattis made of these flours but chapattis were still accepted by the judges. Zinc fortificants seemed like having little or no effect on the quality of the flours and chapattis, made of such flours. Shelf life of fortified flour may be extended by using elemental iron as fortificant and storing the product in tin boxes under relatively low temperature and RH.     

Concurrent cell formation and layout design using scatter search

Two key decisions in designing cellular manufacturing systems are cell formation and layout design problems. In the cell formation problem, machine groups and part families are determined while in the facility layout problem the location of each machine in each cell (intra-cell layout) and the location of each cell (inter-cell layout) are decided. Owing to the fact that there are interactions between two problems, cell formation and layout design problem must be tackled concurrently to design a productive manufacturing system. In this research, two problems are investigated concurrently. Some important and realistic factors such as inter-cell layout, intra-cell layout, operations sequence, part demands, batch size, number of cells, cell size, and variable process routings are incorporated in the problem. The problem is formulated as a mathematical model. Three different methods are described to solve the problem: multi-objective scatter search (MOSS), non-dominated genetic algorithm (NSGA-II), and the ε-constraint method. The methods are employed to solve nine problems generated and adopted from the literature. Sensitivity analysis is accomplished on the parameters of the problem to investigate the effects of them on objective function values. The results show that the proposed MOSS algorithm performs better than NSGA-II and produces better solutions in comparison to multi-stage approaches.     

A new optimization method based on cellular automata for VVER-1000 nuclear reactor loading pattern

This paper presents a new and innovative optimization technique, which uses cellular automata for solving multi-objective optimization problems. Due to its ability in simulating the local information while taking neighboring effects into account, the cellular automata technique is a powerful tool for optimization. The fuel-loading pattern in nuclear reactor cores is a major optimization problem. Due to the immensity of the search space in fuel management optimization problems, finding the optimum solution requires a huge amount of calculations in the classical method. The cellular automata models, based on local information, can reduce the computations significantly. In this study, reducing the power peaking factor, while increasing the initial excess reactivity inside the reactor core of VVER-1000, which are two apparently contradictory objectives, are considered as the objective functions. The result is an optimum configuration, which is in agreement with the pattern proposed by the designer. In order to gain confidence in the reliability of this method, the aforementioned problem was also solved using neural network and simulated annealing, and the results and procedures were compared.