1,247 research outputs found
An Inverse Approximation and Saturation Order for Kantorovich Exponential Sampling Series
In the present article, an inverse approximation result and saturation order
for the Kantorovich exponential sampling series are established.
First we obtain a relation between the generalized exponential sampling series
and for the space of all uniformly continuous and
bounded functions on Next, a Voronovskaya type theorem for
the sampling series is proved. The saturation order for the
series is obtained using the Voronovskaya type theorem. Further,
an inverse result for is established for the class of
log-H\"{o}lderian functions. Moreover, some examples of kernels satisfying the
conditions, which are assumed in the hypotheses of the theorems, are discussed
Short term complex hydro thermal scheduling using integrated PSO-IBF algorithm
In this article, an integrated evolutionary technique such as particle swarm optimization (PSO) algorithm and improved bacterial foraging algorithm (IBFA) have been developed to provide an optimum solution to the scheduling problem with complex thermal and hydro generating stations. PSO algorithm is framed based on the intelligent behavior of the fish school and a flock of birds and the optimal solution in the multidimensional search region is achieved by assigning a random velocity to each potential solution (called the particle). BFA is designed by following the prey-seeking (chemotactic) nature of E. coli bacteria. This technique is followed in an improved manner to get the convergence rate in dynamic for a hyperspace problem by implementing a chemotactic step in a linearly decreased way instead of the static one. The effectiveness of this integrated algorithm is evaluated by using it in a complex thermal and hydro generating system. In this testing system, multiple numbers of cascaded reservoirs in hydro plants have a time coupling effect and thermal power units have a valve point loading effect. The simulation results indicate its merits by comparing it with other meta-heuristic techniques related to the fuel cost required to generate the thermal power.
Relevance vector machine based fault classification in wind energy conversion system
This Paper is an attempt to develop the multiclass classification in the Benchmark fault model applied on wind energy conversion system using the relevance vector machine (RVM). The RVM could apply a structural risk minimization by introducing a proper kernel for training and testing. The Gaussian Kernel is used for this purpose. The classification of sensor, process and actuators faults are observed and classified in the implementation. Training different fault condition and testing is carried out using the RVM implementation carried out using Matlab on the Wind Energy Conversion System (WECS). The training time becomes important while the training is carried out in a bigger WECS, and the hardware feasibility is prime while the testing is carried out on an online fault detection scenario. Matlab based implementation is carried out on the benchmark model for the fault detection in the WECS. The results are compared with the previously implemented fault detection technique and found to be performing better in terms of training time and hardware feasibility
Hysteresis-based Voltage and Current Control Techniques for Grid Connected Solar Photovoltaic Systems: Comparative Study
Solar PV system development and integration with existing grid is very fast in recent years all over the world, as they require limited maintenance, pollution free and simple structure. When observing the factors affecting the performance of the grid connected solar photovoltaic system, the inverter output voltage with harmonics add with the harmonics generated due to the non-linear loads, retain a bigger challenge to maintain power quality in the grid. To maintain grid power quality, better inverter control technique should be developed. This paper presents the two control techniques for grid-tied inverters. This study developed the hysteresis controller for the inverter. Hysteresis controller used in this work two way (i) Voltage control mode (ii) Current control mode. Matlab/Simulink model is developed for the proposed system. Further the study presents the comparative evaluation of the performance of both control techniques based on the percentage of total harmonic distortion (THD) with the limits specified by the standards such as IEEE 1547 and IEC 61727 and IEEE Std 519-201
Poincar\'{e} cycle of a multibox Ehrenfest urn model with directed transport
We propose a generalized Ehrenfest urn model of many urns arranged
periodically along a circle. The evolution of the urn model system is governed
by a directed stochastic operation. Method for solving an -ball, -urn
problem of this model is presented. The evolution of the system is studied in
detail. We find that the average number of balls in a certain urn oscillates
several times before it reaches a stationary value. This behavior seems to be a
peculiar feature of this directed urn model. We also calculate the Poincar\'{e}
cycle, i.e., the average time interval required for the system to return to its
initial configuration. The result can be easily understood by counting the
total number of all possible microstates of the system.Comment: 10 pages revtex file with 7 eps figure
Methyl (E)-2-[(2-nitrophenoxy)methyl]-3-phenylacrylate
The title compound, C17H15NO5, adopts an E conformation with respect to the C=C double bond of the phenylacrylate unit. The phenyl ring and methyl acrylate group of the phenylacrylate unit are disordered over two sets of sites with site-occupancy ratios of 0.705 (5):0.295 (5) and 0.683 (3):0.317 (3), respectively. The mean plane through the benzene ring of the phenyl acrylate makes dihedral angles of 88.4 (8) (major component) and 86.7 (8)° (minor component) with the nitrophenoxy ring; the dihedral angle between the two components is 3.64 (6)°. Intramolecular C—H⋯O interactions stabilise the molecular structure. In the crystal, C—H⋯O interactions result in a chain of molecules running along the b axis
Increased levels of ligands of Toll-like receptors 2 and 4 in type 1 diabetes
Type 1 diabetes is a proinflammatory state characterised by increased levels of circulating biomarkers of inflammation and monocyte activity. We have shown increased Toll-like receptor 2 (TLR2) and TLR4 expression and signalling in monocytes from type 1 diabetic patients. Several endogenous ligands of TLR2 and TLR4 have been identified; however, there is a paucity of data on levels of these endogenous ligands in diabetes. Thus, the aim of this study was to examine circulating levels of exogenous/endogenous ligands of TLR2 and TLR4 in type 1 diabetic patients and to compare these with the levels in matched healthy controls.
Healthy controls (n = 37) and type 1 diabetic patients (n = 34) were recruited, and a fasting blood sample was obtained. Circulating levels of endotoxin, heat-shock protein 60 (Hsp60), high-mobility group box 1 (HMGB1) and growth arrest-specific 6 (GAS6) proteins were assessed by ELISA, and TLR2 and TLR4 expression was determined by flow cytometry.
Levels of the classical TLR4 ligand, endotoxin, were significantly elevated in type 1 diabetic patients compared with those in matched controls. Hsp60 and HMGB1 concentrations were also significantly increased in the patients (p < 0.01 and p < 0.001, respectively). No significant differences were observed in GAS6.
We report the novel observation that levels of ligands of TLR2 and TLR4 are significantly elevated in type 1 diabetes, and this, in concert with hyperglycaemia, accounts for the increase in TLR2 and TLR4 activity, underscoring the proinflammatory state of type 1 diabetes
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