A novel intelligent approach for yaw position forecasting in wind energy systems

Yaw control systems orientate the rotor of a wind turbine into the wind direction, optimize the wind power generated by wind turbines and alleviate the mechanical stresses on a wind turbine. Regarding the advantages of yaw control systems, a k-nearest neighbor classifier (k-NN) has been developed in order to forecast the yaw position parameter at 10-min intervals in this study. Air temperature, atmosphere pressure, wind direction, wind speed, rotor speed and wind power parameters are used in 2, 3, 4, 5 and 6-dimensional input spaces. The forecasting model using Manhattan distance metric for k = 3 uncovered the most accurate performance for atmosphere pressure, wind direction, wind speed and rotor speed inputs. However, the forecasting model using Euclidean distance metric for k = 1 brought out the most inconsistent results for atmosphere pressure and wind speed inputs. As a result of multi-tupled analyses, many feasible inferences were achieved for yaw position control systems. In addition, the yaw position forecasting model developed was compared with the persistence model and it surpassed the persistence model significantly in terms of the improvement percent.     

Whey protein based electrosprayed nanospheres for encapsulation and controlled release of bioactive compounds from Tinospora cordifolia extract

The synergistic effects of bioactive compounds of Tinospora cordifolia have insulin mimicking and hypoglycemic activity, however, low bioavailability and poor stability limits its potential. In the present study, an appropriate delivery system was developed for the controlled release of its anti-diabetic activity. The bioactive compounds such as palmatine, berberine and palmatoside had better binding energy as observed in docking studies compared to that of the commercial active compounds. However, as these biocompounds from Tinospora cordifolia are associated with low stability and poor bioavailability, these compounds were encapsulated in a core-shell matrix of whey protein isolate. The bioactive compounds had highest antidiabetic activity in chloroform extract with an IC₅₀ concentration of 11.34 mg/ml. An increase in 28.12% activity was observed in nanoemulsion form with an average size of 82.68 ± 4.37 nm. The bioactive compounds were further encapsulated by electrospray technique for increased stability. The particles had an encapsulation efficiency of 91.2 ± 3.27% with an average particle size of 187 ± 2.71 nm. The kinetic study revealed the complete release of bioactive compounds after 24 h of incubation in buffer solution. This formulation can be further explored as novel nutraceutical delivery system with minimal side effects as compared to their synthetic counterparts. Considering the potential application of this developed technology, further upscaling as well as in-vivo experimentation on small as well as large animals should be performed.     

OPAH a model for optimal design of multipurpose small hydropower plants

The investment in small hydropower plants requires the analysis of hydrological, technical, operational, budgetary, economical and financial aspects. The analysis of each possible configuration demands the joint action of several technicians, consuming substantial time and money. During initial design of the project, simplified procedures are usually adopted which may compromise the quality of the base configuration.In this paper we will present a global overview of the OPAH model, which was developed to surpass these limitations. This global model performs the optimization of project configuration. This model uses non-linear programming optimization to analyze the multipurpose operation of the hydropower plant. It uses a numeric simulation model of unsteady flow under pressure to analyze the hydraulic circuit. It uses an economical and financial simulation model that takes in to account the project risk associated to hydrologic and market variability, the financial capacity of the investor and the fiscal aspects.     

Flow distribution and pressure drop in parallel-channel configurations of planar fuel cells

Parallel-channel configurations for gas-distributor plates of planar fuel cells reduce the pressure drop, but give rise to the problem of severe flow maldistribution wherein some of the channels may be starved of the reactants. This study presents an analysis of the flow distribution through parallel-channel configurations. One-dimensional models based on mass and momentum balance equations in the inlet and exhaust gas headers are developed for Z- and U-type parallel-channel configurations. The resulting coupled ordinary differential equations are solved analytically to obtain closed-form solutions for the flow distribution in the individual channels and for the pressure drop over the entire distributor plate. The models have been validated by comparing the results with those obtained from three-dimensional computational fluid dynamics (CFD) simulations. Application of the models to typical fuel-cell distributor plates shows that severe maldistribution of flow may arise in certain cases and that this can be avoided by careful choice of the dimensions of the headers and the channels.     

Thermoelastic evaluation of composite laminates using digital imaging processing

The study of the variation of the curvature of non-symmetric composite laminates with temperature provides a measure of the magnitude of the thermal stresses and the mechanical behavior of the material with temperature. In the present work, an experimental method based on the pioneer use of a digital camera and image processing method is proposed to perform such measurements. Taking advantage of the method and by comparing experimental and CLT, extended-CLT and FEM simulation results, an evaluation of the residual stresses is described and an approach providing more precise determination of the residual thermal stresses in non-symmetric laminates is proposed.     

An efficient and security dynamic identity based authentication protocol for multi-server architecture using smart cards

Generally, if a user wants to use numerous different network services, he/she must register himself/herself to every service providing server. It is extremely hard for users to remember these different identities and passwords. In order to resolve this problem, various multi-server authentication protocols have been proposed. Recently, Sood et al. analyzed Hsiang and Shih's multi-server authentication protocol and proposed an improved dynamic identity based authentication protocol for multi-server architecture. They claimed that their protocol provides user's anonymity, mutual authentication, the session key agreement and can resist several kinds of attacks. However, through careful analysis, we find that Sood et al.'s protocol is still vulnerable to leak-of-verifier attack, stolen smart card attack and impersonation attack. Besides, since there is no way for the control server CS to know the real identity of the user, the authentication and session key agreement phase of Sood et al.'s protocol is incorrect. We propose an efficient and security dynamic identity based authentication protocol for multi-server architecture that removes the aforementioned weaknesses. The proposed protocol is extremely suitable for use in distributed multi-server architecture since it provides user's anonymity, mutual authentication, efficient, and security.     

Compression based clustering technique for enhancing accuracy in web scale videos

Multimedia Tools and Applications - Detection and clustering of commercial advertisements plays an important role in multimedia indexing also in the creation of personalized user content. In...     

Detection of delamination in laminated composites with limited measurements combining PCA and dynamic QPSO

This paper presents an output only damage diagnostic algorithm based on frequency response functions and the principal components for health monitoring of laminated composite structures. The principal components evaluated from frequency response data, are employed as dynamical invariants to handle the effects of operational/environmental variability on the dynamic response of the structure. Finite element models of a laminated composite beam and plate are used to generate vibration data for healthy and damaged structures. Three numerical examples include a laminated composite beam, cantilever plate made of carbon–epoxy and a laminated composite simply supported plate. Varied levels of delamination of laminated composite plies and matrix cracking at varied locations in the plies are simulated at different spatial locations of the structure. Numerical investigations have been carried out to identify the spatial location of damage using the proposed principal component analysis (PCA) based algorithm. In order to limit the number of sensors on the structure, an optimal sensor placement algorithm based on PCA is employed in the present work and the effectiveness of the proposed algorithm with a limited number of sensors is also investigated. Finally, the inverse problem associated with the detection of delamination and matrix cracking is formulated as an optimization problem and is solved using the newly developed dynamic quantum particle swarm optimization (DQPSO) algorithm. Studies carried out and presented in this paper clearly indicate that the proposed SHM scheme can robustly identify the instant of damage, spatial location, the extent of delamination and matrix cracking even with limited sensor measurements and also with noisy data.     

Optimization of neural network model using modified bat-inspired algorithm

The success of an artificial neural network (ANN) strongly depends on the variety of the connection weights and the network structure. Among many methods used in the literature to accurately select the network weights or structure in isolate; a few researchers have attempted to select both the weights and structure of ANN automatically by using metaheuristic algorithms. This paper proposes modified bat algorithm with a new solution representation for both optimizing the weights and structure of ANNs. The algorithm, which is based on the echolocation behaviour of bats, combines the advantages of population-based and local search algorithms. In this work, ability of the basic bat algorithm and some modified versions which are based on the consideration of the personal best solution in the velocity adjustment, the mean of personal best and global best solutions through velocity adjustment and the employment of three chaotic maps are investigated. These modifications are aimed to improve the exploration and exploitation capability of bat algorithm. Different versions of the proposed bat algorithm are incorporated to handle the selection of the structure as well as weights and biases of the ANN during the training process. We then use the Taguchi method to tune the parameters of the algorithm that demonstrates the best ability compared to the other versions. Six classifications and two time series benchmark datasets are used to test the performance of the proposed approach in terms of classification and prediction accuracy. Statistical tests demonstrate that the proposed method generates some of the best results in comparison with the latest methods in the literature. Finally, our best method is applied to a real-world problem, namely to predict the future values of rainfall data and the results show satisfactory of the method.     

Performance of orthogonal frequency division multiplexing based M-ary quadrature amplitude modulation in asymmetrical dual-hop mixed RF-FSO transmission system

This paper investigates the performance of a dual-hop mixed relay system with radio frequency (RF) and free-space optics (FSO) communication under the effect of pointing error (PE) and atmospheric turbulence (AT). This paper considers a system where RF and FSO links are cascaded. The RF link is modeled by Nakagami-m fading, and the FSO link is modeled as gamma–gamma (G-G) fading channel. Both the channel models use orthogonal frequency division multiplexing (OFDM) with M-ary quadrature amplitude modulation (QAM). The expressions for probability density function, cumulative distribution function, signal-to-noise ratio, and ergodic capacity are derived. The moment generating function (MGF) of fading and the bit error rate (BER) of the OFDM-based M-ary QAM scheme is derived in terms of Meijer's G-function. It has been observed that, in fixed gain relay systems, the modulation scheme's BER is dominated by the SNR of the RF link. While in a variable gain relay system, the turbulence conditions of the FSO system affect the SNR and the BER of the modulation method. The feasibility of heterodyne detection and intensity modulation direct detection (IM/DD) is analyzed in terms of outage probability and ergodic capacity. The results can be used to choose the optimal modulation order and relay system for QAM-OFDM-based optical wireless systems.