Kernel-based object tracking using asymmetric kernels with adaptive scale and orientation selection

Kernel-based object tracking refers to computing the translation of an isotropic object kernel from one video frame to the next. The kernel is commonly chosen as a primitive geometric shape and its translation is computed by maximizing the likelihood between the current and past object observations. In the case when the object does not have an isotropic shape, kernel includes non-object regions which biases the motion estimation and results in loss of the tracked object. In this paper, we propose to use an asymmetric object kernel for improving the tracking performance. An important advantage of an asymmetric kernel over an isotropic kernel is its precise representation of the object shape. This property enhances tracking performance due to discarding the non-object regions. The second contribution of our paper is the introduction of a new adaptive kernel scale and orientation selection method which is currently achieved by greedy algorithms. In our approach, the scale and orientation are introduced as additional dimensions to the spatial image coordinates, in which the mode seeking, hence tracking, is achieved simultaneously in all coordinates. Demonstrated in a set of experiments, the proposed method has better tracking performance with comparable execution time then kernel tracking methods used in practice.     

mrPSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification

This paper presents a hybrid filter-wrapper feature subset selection algorithm based on particle swarm optimization (PSO) for support vector machine (SVM) classification. The filter model is based on the mutual information and is a composite measure of feature relevance and redundancy with respect to the feature subset selected. The wrapper model is a modified discrete PSO algorithm. This hybrid algorithm, called maximum relevance minimum redundancy PSO (mr²PSO), is novel in the sense that it uses the mutual information available from the filter model to weigh the bit selection probabilities in the discrete PSO. Hence, mr²PSO uniquely brings together the efficiency of filters and the greater accuracy of wrappers. The proposed algorithm is tested over several well-known benchmarking datasets. The performance of the proposed algorithm is also compared with a recent hybrid filter-wrapper algorithm based on a genetic algorithm and a wrapper algorithm based on PSO. The results show that the mr²PSO algorithm is competitive in terms of both classification accuracy and computational performance.     

A knowledge-based scheduling system for Emergency Departments

A knowledge-based reactive scheduling system is proposed to answer the requirements of Emergency Departments (EDs). The algorithm includes detailed patient priority, arrival time, flow time and doctor load. The main aim is to determine the patients who have higher priorities initially, and then minimize their waiting times. To achieve this aim, physicians and the other related workers can use an interactive system. In this study, we evaluated the existing system by comparing the proposed system. Also, reactive scheduling cases were evaluated for some items such as decreasing the number of doctors, changing durations and entering of an urgent patient to the system. All experiments were performed with proposed algorithm and right shift rescheduling approach.     

Investigation of acetyl ferrocene migration from hydroxyl‐terminated polybutadiene based elastomers by means of ultraviolet–visible and atomic absorption spectroscopic techniques

Migration and leakage of some mobile components in rocket propellant produces an inhomogeneous composition region at which migration takes place, which can lead to premature detonation, changes in ballistic characteristics, and so on. It is, therefore, important to be able to predict the behavior of low‐molecular‐weight mobile additives and to control the leakage of them from the propellant. At this point, our chief interest was to study the magnitude of the migration and to understand the factors that influence the migration process. In this study, the migration of a ferrocene‐based burning‐rate catalyst [acetyl ferrocene (AcF)] a from hydroxyl‐terminated polybutadiene (HTPB) based elastomer in the presence of a plasticizer (dioctyl adipate) was examined in accelerated aging conditions at 60°C for various time intervals. We also tried to minimize the migration of AcF from the loaded to the unloaded part by using an extra barrier layer consisting of polyfunctional aziridine (AST D45+) in addition to the HTPB–toluene diisocyanate composition. The migration enhanced with aging of the AcF and the barrier effects of the layer with intensified crosslink density to this migration were studied extensively. The migration was monitored by both ultraviolet–visible and atomic absorption spectroscopy (AAS) methods. A comparison of the data obtained from both of these methods was also done. The two techniques were found to be in agreement, and the Fe determinations from both methods were highly correlated, suggesting that the data were reliable, although the AAS data were found to be symmetrically somewhat higher. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 1654–1661, 2005     

The effect of tube end constraining on the axial crushing behavior of an aluminum tube

The effect of various types of end constraining on the deformation and load–displacement behavior of a 3003-H14 Al tube were experimentally and numerically studied. No effect of single-end constraining of tubes was found. Few conditions of double-end constraining tended to revert the deformation mode to mixed and/or diamond mode of deformation. Double-end constraining of tube ends further resulted in an increase in initial drop-load values, widening the initial overshot region in average load–displacement curves. The agreement between numerical and experimental results showed the capabilities of the used numerical model in order to predict end-condition effects in tubular structures.     

Synthesis and characterization of polyurethanes containing glucose for selective determination of epinephrine in the presence of a high concentration of ascorbic acid

Polyurethane (PU) films were prepared from glucose, ethylene glycol and diphenylmethane diisocyanate and used to construct a novel polymer electrode for the detection of epinephrine (EP) in the presence of a high concentration of ascorbic acid (AA). The NCO:OH molar ratio was kept constant at 1 and the saccharide content was varied. The PUs were characterized using Fourier transform infrared spectroscopy, differential scanning calorimetry and differential thermal and thermogravimetric analyses, with intrinsic viscosity and adhesive properties also being evaluated. The PUs exhibited high glass transition temperature, good thermal stability and good adhesive properties. The incorporation of saccharides into the PU structure resulted in a higher crosslinking density and a higher content of hard segments. Medium‐ to high‐molecular‐weight polymers were obtained, with inherent viscosities near or higher than 0.98–2.14 dL g^?1. The solubility of the PUs was much better than that of aromatic PUs. The modified polymer electrodes were then used to determine EP in the presence of a high concentration of AA using differential pulse voltammetry. From the amperometric results for the PU electrode, it is concluded that a PU film containing 5 wt% glucose can be used as a membrane for EP detection in the presence of a large concentration of AA, because of its strong adherence to the electrode surface, easy preparation, chemical stability, selectivity and very high statistical confidence (R = 0.9994). © 2012 Society of Chemical Industry     

First‐principles based group additivity values for thermochemical properties of substituted aromatic compounds

A set of 7 Benson group additive values (GAV) together with 15 correction terms for non‐nearest neighbor interactions (NNI) is developed to calculate the gas phase standard enthalpies of formation, entropies and heat capacities of monocyclic aromatic compounds containing methyl, ethyl, vinyl, formyl, hydroxyl, and methoxy substituents. These GAVs are obtained through least squares regression of a database of thermodynamic properties of 143 molecules, calculated at the post‐Hartree–Fock G4 composite method. Out of the 15 NNIs, which account for several well‐known substituent effects in aromatic molecules, 13 have been determined for the first time. All but two group additively calculated standard enthalpies of formation agree within 4 kJ mol^?1. The entropies and the heat capacities generally deviate less than 4 J mol^?1 K^?1 from the ab initio results. Natural bond orbital analysis is utilized to identify the underlying causes of the observed NNIs. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3858–3870, 2015     

Radiation impedance of collapsed capacitive micromachined ultrasonic transducers

The radiation impedance of a capacitive micromachined ultrasonic transducer (CMUT) array is a critical parameter to achieve high performance. In this paper, we present a calculation of the radiation impedance of collapsed, clamped, circular CMUTs both analytically and using finite element method (FEM) simulations. First, we model the radiation impedance of a single collapsed CMUT cell analytically by expressing its velocity profile as a linear combination of special functions for which the generated pressures are known. For an array of collapsed CMUT cells, the mutual impedance between the cells is also taken into account. The radiation impedances for arrays of 7, 19, 37, and 61 circular collapsed CMUT cells for different contact radii are calculated both analytically and by FEM simulations. The radiation resistance of an array reaches a plateau and maintains this level for a wide frequency range. The variation of radiation reactance with respect to frequency indicates an inductance-like behavior in the same frequency range. We find that the peak radiation resistance value is reached at higher kd values in the collapsed case as compared with the uncollapsed case, where k is the wavenumber and d is the center-to-center distance between two neighboring CMUT cells.     

Improvement of energy demand forecasts using swarm intelligence: The case of Turkey with projections to 2025

The energy supply and demand should be closely monitored and revised the forecasts to take account of the progress of liberalization, energy efficiency improvements, structural changes in industry and other major factors. Medium and long-term forecasting of energy demand, which is based on realistic indicators, is a prerequisite to become an industrialized country and to have high living standards. Energy planning is not possible without a reasonable knowledge of past and present energy consumption and likely future demands. Energy demand management activities should bring the demand and supply closer to a perceived optimum. Turkey's energy demand has grown rapidly almost every year and is expected to continue growing. However, the energy demand forecasts prepared by the Turkey Ministry of Energy and Natural Resources overestimate the demand. Recently many studies are performed by researchers to forecast the energy demand of Turkey. Particle swarm optimization (PSO) technique has never been used for such a study. In this study a model is proposed, using PSO-based energy demand forecasting (PSOEDF), to forecast the energy demand of Turkey more efficiently. Although there are other indicators as well, gross domestic product (GDP), population, import and export are used as basic energy indicators of energy demand. In order to show the accuracy of the algorithm, a comparison is made with the ant colony optimization (ACO) energy demand estimation model which is developed for the same problem.